Python: module mrpt.pymrpt.mrpt.maps

mrpt.pymrpt.mrpt.maps

index
(built-in)

Bindings for mrpt::maps namespace

Classes



mrpt.pymrpt.mrpt.Stringifyable(pybind11_builtins.pybind11_object)

CMetricMap(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.system.CObservable, mrpt.pymrpt.mrpt.Stringifyable, mrpt.pymrpt.mrpt.opengl.Visualizable)

CBeaconMap
CHeightGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, CHeightGridMap2D_Base)
CLandmarksMap
CMultiMetricMap
COccupancyGridMap2D(CMetricMap, CLogOddsGridMap2D_signed_char_t)
COccupancyGridMap3D(CMetricMap, CLogOddsGridMap3D_signed_char_t)
COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t

CColouredOctoMap

COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t

COctoMap

CPointsMap(CMetricMap, mrpt.pymrpt.mrpt.opengl.PLY_Importer, mrpt.pymrpt.mrpt.opengl.PLY_Exporter)

CColouredPointsMap
CPointsMapXYZI
CSimplePointsMap
CWeightedPointsMap

CRandomFieldGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t)

CGasConcentrationGridMap2D
CHeightGridMap2D_MRF(CRandomFieldGridMap2D, CHeightGridMap2D_Base)
CWirelessPowerGridMap2D

CReflectivityGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, CLogOddsGridMap2D_signed_char_t)

mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t(mrpt.pymrpt.mrpt.bayes.CParticleFilterCapable)

CMultiMetricMapPDF(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.slam.PF_implementation_mrpt_maps_CRBPFParticleData_mrpt_maps_CMultiMetricMapPDF_mrpt_bayes_particle_storage_mode_POINTER_t)

mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t(pybind11_builtins.pybind11_object)

CMultiMetricMapPDF(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.slam.PF_implementation_mrpt_maps_CRBPFParticleData_mrpt_maps_CMultiMetricMapPDF_mrpt_bayes_particle_storage_mode_POINTER_t)

mrpt.pymrpt.mrpt.config.CLoadableOptions(pybind11_builtins.pybind11_object)

TMapGenericParams(mrpt.pymrpt.mrpt.config.CLoadableOptions, mrpt.pymrpt.mrpt.serialization.CSerializable)
TSetOfMetricMapInitializers

mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t(pybind11_builtins.pybind11_object)

CRandomFieldGridMap3D(mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, mrpt.pymrpt.mrpt.serialization.CSerializable)

mrpt.pymrpt.mrpt.opengl.Visualizable(pybind11_builtins.pybind11_object)

CMetricMap(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.system.CObservable, mrpt.pymrpt.mrpt.Stringifyable, mrpt.pymrpt.mrpt.opengl.Visualizable)

CBeaconMap
CHeightGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, CHeightGridMap2D_Base)
CLandmarksMap
CMultiMetricMap
COccupancyGridMap2D(CMetricMap, CLogOddsGridMap2D_signed_char_t)
COccupancyGridMap3D(CMetricMap, CLogOddsGridMap3D_signed_char_t)
COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t

CColouredOctoMap

COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t

COctoMap

CPointsMap(CMetricMap, mrpt.pymrpt.mrpt.opengl.PLY_Importer, mrpt.pymrpt.mrpt.opengl.PLY_Exporter)

CColouredPointsMap
CPointsMapXYZI
CSimplePointsMap
CWeightedPointsMap

CRandomFieldGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t)

CGasConcentrationGridMap2D
CHeightGridMap2D_MRF(CRandomFieldGridMap2D, CHeightGridMap2D_Base)
CWirelessPowerGridMap2D

CReflectivityGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, CLogOddsGridMap2D_signed_char_t)

mrpt.pymrpt.mrpt.poses.CPointPDF(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t)

CBeacon

mrpt.pymrpt.mrpt.serialization.CSerializable(mrpt.pymrpt.mrpt.rtti.CObject)

CLandmark
CMetricMap(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.system.CObservable, mrpt.pymrpt.mrpt.Stringifyable, mrpt.pymrpt.mrpt.opengl.Visualizable)

CBeaconMap
CHeightGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, CHeightGridMap2D_Base)
CLandmarksMap
CMultiMetricMap
COccupancyGridMap2D(CMetricMap, CLogOddsGridMap2D_signed_char_t)
COccupancyGridMap3D(CMetricMap, CLogOddsGridMap3D_signed_char_t)
COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t

CColouredOctoMap

COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t

COctoMap

CPointsMap(CMetricMap, mrpt.pymrpt.mrpt.opengl.PLY_Importer, mrpt.pymrpt.mrpt.opengl.PLY_Exporter)

CColouredPointsMap
CPointsMapXYZI
CSimplePointsMap
CWeightedPointsMap

CRandomFieldGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t)

CGasConcentrationGridMap2D
CHeightGridMap2D_MRF(CRandomFieldGridMap2D, CHeightGridMap2D_Base)
CWirelessPowerGridMap2D

CReflectivityGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, CLogOddsGridMap2D_signed_char_t)

CMultiMetricMapPDF(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.slam.PF_implementation_mrpt_maps_CRBPFParticleData_mrpt_maps_CMultiMetricMapPDF_mrpt_bayes_particle_storage_mode_POINTER_t)
CRBPFParticleData
CRandomFieldGridMap3D(mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, mrpt.pymrpt.mrpt.serialization.CSerializable)
CSimpleMap
TMapGenericParams(mrpt.pymrpt.mrpt.config.CLoadableOptions, mrpt.pymrpt.mrpt.serialization.CSerializable)

mrpt.pymrpt.mrpt.slam.PF_implementation_mrpt_maps_CRBPFParticleData_mrpt_maps_CMultiMetricMapPDF_mrpt_bayes_particle_storage_mode_POINTER_t(pybind11_builtins.pybind11_object)

CMultiMetricMapPDF(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.slam.PF_implementation_mrpt_maps_CRBPFParticleData_mrpt_maps_CMultiMetricMapPDF_mrpt_bayes_particle_storage_mode_POINTER_t)

mrpt.pymrpt.mrpt.system.CObservable(pybind11_builtins.pybind11_object)

CMetricMap(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.system.CObservable, mrpt.pymrpt.mrpt.Stringifyable, mrpt.pymrpt.mrpt.opengl.Visualizable)

CBeaconMap
CHeightGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, CHeightGridMap2D_Base)
CLandmarksMap
CMultiMetricMap
COccupancyGridMap2D(CMetricMap, CLogOddsGridMap2D_signed_char_t)
COccupancyGridMap3D(CMetricMap, CLogOddsGridMap3D_signed_char_t)
COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t

CColouredOctoMap

COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t

COctoMap

CPointsMap(CMetricMap, mrpt.pymrpt.mrpt.opengl.PLY_Importer, mrpt.pymrpt.mrpt.opengl.PLY_Exporter)

CColouredPointsMap
CPointsMapXYZI
CSimplePointsMap
CWeightedPointsMap

CRandomFieldGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t)

CGasConcentrationGridMap2D
CHeightGridMap2D_MRF(CRandomFieldGridMap2D, CHeightGridMap2D_Base)
CWirelessPowerGridMap2D

CReflectivityGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, CLogOddsGridMap2D_signed_char_t)

mrpt.pymrpt.mrpt.system.mrptEvent(pybind11_builtins.pybind11_object)

mrptEventMetricMapClear
mrptEventMetricMapInsert

pybind11_builtins.pybind11_object(builtins.object)

CHeightGridMap2D_Base
CLogOddsGridMap2D_signed_char_t
CLogOddsGridMap3D_signed_char_t
CLogOddsGridMapLUT_signed_char_t
CPointCloudFilterBase

CPointCloudFilterByDistance

OccGridCellTraits
THeightGridmapCell
TMatchingExtraResults
TMatchingParams
TMatchingRatioParams
TRandomFieldCell
TRandomFieldVoxel

class CBeacon(mrpt.pymrpt.mrpt.poses.CPointPDF)

    The class for storing individual "beacon landmarks" under a variety of 3D position PDF distributions. This class is used for storage within the class CBeaconMap. The class implements the same methods than the interface "CPointPDF", and invoking them actually becomes   a mapping into the methods of the current PDF representation of the beacon, selectable by means of "m_typePDF" CBeaconMap, CPointPDFSOG

Method resolution order:

CBeacon

mrpt.pymrpt.mrpt.poses.CPointPDF

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CBeacon) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CBeacon::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CBeacon) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CBeacon, arg0: mrpt.pymrpt.mrpt.maps.CBeacon) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CBeacon, arg0: mrpt.pymrpt.mrpt.maps.CBeacon) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CBeacon, : mrpt.pymrpt.mrpt.maps.CBeacon) -> mrpt.pymrpt.mrpt.maps.CBeacon C++: mrpt::maps::CBeacon::operator=(const class mrpt::maps::CBeacon &) --> class mrpt::maps::CBeacon &

bayesianFusion(...)
bayesianFusion(*args, **kwargs) Overloaded function. 1. bayesianFusion(self: mrpt.pymrpt.mrpt.maps.CBeacon, p1: mrpt.pymrpt.mrpt.poses.CPointPDF, p2: mrpt.pymrpt.mrpt.poses.CPointPDF) -> None 2. bayesianFusion(self: mrpt.pymrpt.mrpt.maps.CBeacon, p1: mrpt.pymrpt.mrpt.poses.CPointPDF, p2: mrpt.pymrpt.mrpt.poses.CPointPDF, minMahalanobisDistToDrop: float) -> None Bayesian fusion of two point distributions (product of two distributions->new distribution), then save the result in this object (WARNING: See implementing classes to see classes that can and cannot be mixtured!) The first distribution to fuse The second distribution to fuse If set to different of 0, the result of very separate Gaussian modes (that will result in negligible components) in SOGs will be dropped to reduce the number of modes in the output. C++: mrpt::maps::CBeacon::bayesianFusion(const class mrpt::poses::CPointPDF &, const class mrpt::poses::CPointPDF &, const double) --> void

changeCoordinatesReference(...)
changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CBeacon, newReferenceBase: mrpt.pymrpt.mrpt.poses.CPose3D) -> None this = p (+) this. This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which    "to project" the current pdf. Result PDF substituted the currently stored one in the object. C++: mrpt::maps::CBeacon::changeCoordinatesReference(const class mrpt::poses::CPose3D &) --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CBeacon) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CBeacon::clone() const --> class mrpt::rtti::CObject *

copyFrom(...)
copyFrom(self: mrpt.pymrpt.mrpt.maps.CBeacon, o: mrpt.pymrpt.mrpt.poses.CPointPDF) -> None Copy operator, translating if necesary (for example, between particles and gaussian representations) C++: mrpt::maps::CBeacon::copyFrom(const class mrpt::poses::CPointPDF &) --> void

drawSingleSample(...)
drawSingleSample(self: mrpt.pymrpt.mrpt.maps.CBeacon, outSample: mrpt.pymrpt.mrpt.poses.CPoint3D) -> None Draw a sample from the pdf. C++: mrpt::maps::CBeacon::drawSingleSample(class mrpt::poses::CPoint3D &) const --> void

generateObservationModelDistribution(...)
generateObservationModelDistribution(*args, **kwargs) Overloaded function. 1. generateObservationModelDistribution(self: mrpt.pymrpt.mrpt.maps.CBeacon, sensedRange: float, outPDF: mrpt.pymrpt.mrpt.poses.CPointPDFSOG, myBeaconMap: mrpt::maps::CBeaconMap, sensorPntOnRobot: mrpt.pymrpt.mrpt.poses.CPoint3D) -> None 2. generateObservationModelDistribution(self: mrpt.pymrpt.mrpt.maps.CBeacon, sensedRange: float, outPDF: mrpt.pymrpt.mrpt.poses.CPointPDFSOG, myBeaconMap: mrpt::maps::CBeaconMap, sensorPntOnRobot: mrpt.pymrpt.mrpt.poses.CPoint3D, centerPoint: mrpt.pymrpt.mrpt.poses.CPoint3D) -> None 3. generateObservationModelDistribution(self: mrpt.pymrpt.mrpt.maps.CBeacon, sensedRange: float, outPDF: mrpt.pymrpt.mrpt.poses.CPointPDFSOG, myBeaconMap: mrpt::maps::CBeaconMap, sensorPntOnRobot: mrpt.pymrpt.mrpt.poses.CPoint3D, centerPoint: mrpt.pymrpt.mrpt.poses.CPoint3D, maxDistanceFromCenter: float) -> None Compute the observation model p(z_t|x_t) for a given observation (range value), and return it as an approximate SOG.   Note that if the beacon is a SOG itself, the number of gaussian modes will be square.   As a speed-up, if a "center point"+"maxDistanceFromCenter" is supplied (maxDistanceFromCenter!=0), those modes farther than this sphere will be discarded.   Parameters such as the stdSigma of the sensor are gathered from "myBeaconMap"   The result is one "ring" for each Gaussian mode that represent the beacon position in this object.   The position of the sensor on the robot is used to shift the resulting densities such as they represent the position of the robot, not the sensor.    CBeaconMap::insertionOptions, generateRingSOG C++: mrpt::maps::CBeacon::generateObservationModelDistribution(float, class mrpt::poses::CPointPDFSOG &, const class mrpt::maps::CBeaconMap *, const class mrpt::poses::CPoint3D &, const class mrpt::poses::CPoint3D &, float) const --> void

getAsMatlabDrawCommands(...)
getAsMatlabDrawCommands(self: mrpt.pymrpt.mrpt.maps.CBeacon, out_Str: List[str]) -> None Gets a set of MATLAB commands which draw the current state of the beacon: C++: mrpt::maps::CBeacon::getAsMatlabDrawCommands(class std::vector<std::string > &) const --> void

getCovarianceAndMean(...)
getCovarianceAndMean(self: mrpt.pymrpt.mrpt.maps.CBeacon) -> Tuple[mrpt.pymrpt.mrpt.math.CMatrixFixed_double_3UL_3UL_t, mrpt.pymrpt.mrpt.poses.CPoint3D] C++: mrpt::maps::CBeacon::getCovarianceAndMean() const --> class std::tuple<class mrpt::math::CMatrixFixed<double, 3, 3>, class mrpt::poses::CPoint3D>

getMean(...)
getMean(self: mrpt.pymrpt.mrpt.maps.CBeacon, mean_point: mrpt.pymrpt.mrpt.poses.CPoint3D) -> None C++: mrpt::maps::CBeacon::getMean(class mrpt::poses::CPoint3D &) const --> void

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CBeacon, o: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Saves a 3D representation of the beacon into a given OpenGL scene   C++: mrpt::maps::CBeacon::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

saveToTextFile(...)
saveToTextFile(self: mrpt.pymrpt.mrpt.maps.CBeacon, file: str) -> bool Save PDF's particles to a text file. See derived classes for more information about the format of generated files C++: mrpt::maps::CBeacon::saveToTextFile(const std::string &) const --> bool

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CBeacon::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CBeacon::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

generateRingSOG(...) from builtins.PyCapsule
generateRingSOG(*args, **kwargs) Overloaded function. 1. generateRingSOG(sensedRange: float, outPDF: mrpt.pymrpt.mrpt.poses.CPointPDFSOG, myBeaconMap: mrpt::maps::CBeaconMap, sensorPnt: mrpt.pymrpt.mrpt.poses.CPoint3D) -> None 2. generateRingSOG(sensedRange: float, outPDF: mrpt.pymrpt.mrpt.poses.CPointPDFSOG, myBeaconMap: mrpt::maps::CBeaconMap, sensorPnt: mrpt.pymrpt.mrpt.poses.CPoint3D, covarianceCompositionToAdd: mrpt.pymrpt.mrpt.math.CMatrixFixed_double_3UL_3UL_t) -> None 3. generateRingSOG(sensedRange: float, outPDF: mrpt.pymrpt.mrpt.poses.CPointPDFSOG, myBeaconMap: mrpt::maps::CBeaconMap, sensorPnt: mrpt.pymrpt.mrpt.poses.CPoint3D, covarianceCompositionToAdd: mrpt.pymrpt.mrpt.math.CMatrixFixed_double_3UL_3UL_t, clearPreviousContentsOutPDF: bool) -> None 4. generateRingSOG(sensedRange: float, outPDF: mrpt.pymrpt.mrpt.poses.CPointPDFSOG, myBeaconMap: mrpt::maps::CBeaconMap, sensorPnt: mrpt.pymrpt.mrpt.poses.CPoint3D, covarianceCompositionToAdd: mrpt.pymrpt.mrpt.math.CMatrixFixed_double_3UL_3UL_t, clearPreviousContentsOutPDF: bool, centerPoint: mrpt.pymrpt.mrpt.poses.CPoint3D) -> None 5. generateRingSOG(sensedRange: float, outPDF: mrpt.pymrpt.mrpt.poses.CPointPDFSOG, myBeaconMap: mrpt::maps::CBeaconMap, sensorPnt: mrpt.pymrpt.mrpt.poses.CPoint3D, covarianceCompositionToAdd: mrpt.pymrpt.mrpt.math.CMatrixFixed_double_3UL_3UL_t, clearPreviousContentsOutPDF: bool, centerPoint: mrpt.pymrpt.mrpt.poses.CPoint3D, maxDistanceFromCenter: float) -> None This static method returns a SOG with ring-shape (or as a 3D sphere) that can be used to initialize a beacon if observed the first time.   sensorPnt is the center of the ring/sphere, i.e. the absolute position of the range sensor.   If clearPreviousContentsOutPDF=false, the SOG modes will be added to the current contents of outPDF   If the 3x3 matrix covarianceCompositionToAdd is provided, it will be add to every Gaussian (to model the composition of uncertainty). generateObservationModelDistribution C++: mrpt::maps::CBeacon::generateRingSOG(float, class mrpt::poses::CPointPDFSOG &, const class mrpt::maps::CBeaconMap *, const class mrpt::poses::CPoint3D &, const class mrpt::math::CMatrixFixed<double, 3, 3> *, bool, const class mrpt::poses::CPoint3D &, float) --> void

Data descriptors defined here:

m_ID

m_locationGauss

m_locationMC

m_locationSOG

m_typePDF

Data and other attributes defined here:

TTypePDF = <class 'mrpt.pymrpt.mrpt.maps.CBeacon.TTypePDF'>

pdfGauss = <TTypePDF.pdfGauss: 1>

pdfMonteCarlo = <TTypePDF.pdfMonteCarlo: 0>

pdfSOG = <TTypePDF.pdfSOG: 2>

Static methods inherited from mrpt.pymrpt.mrpt.poses.CPointPDF:

is_3D(...) from builtins.PyCapsule
is_3D() -> bool C++: mrpt::poses::CPointPDF::is_3D() --> bool

is_PDF(...) from builtins.PyCapsule
is_PDF() -> bool C++: mrpt::poses::CPointPDF::is_PDF() --> bool

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t:

getCovariance(...)
getCovariance(*args, **kwargs) Overloaded function. 1. getCovariance(self: mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t, cov: mrpt::math::CMatrixDynamic<double>) -> None C++: mrpt::math::CProbabilityDensityFunction<mrpt::poses::CPoint3D, 3>::getCovariance(class mrpt::math::CMatrixDynamic<double> &) const --> void 2. getCovariance(self: mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t, cov: mrpt::math::CMatrixFixed<double, 3ul, 3ul>) -> None C++: mrpt::math::CProbabilityDensityFunction<mrpt::poses::CPoint3D, 3>::getCovariance(class mrpt::math::CMatrixFixed<double, 3, 3> &) const --> void 3. getCovariance(self: mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t) -> mrpt::math::CMatrixFixed<double, 3ul, 3ul> C++: mrpt::math::CProbabilityDensityFunction<mrpt::poses::CPoint3D, 3>::getCovariance() const --> class mrpt::math::CMatrixFixed<double, 3, 3>

getCovarianceDynAndMean(...)
getCovarianceDynAndMean(self: mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t, cov: mrpt::math::CMatrixDynamic<double>, mean_point: mrpt::poses::CPoint3D) -> None C++: mrpt::math::CProbabilityDensityFunction<mrpt::poses::CPoint3D, 3>::getCovarianceDynAndMean(class mrpt::math::CMatrixDynamic<double> &, class mrpt::poses::CPoint3D &) const --> void

getCovarianceEntropy(...)
getCovarianceEntropy(self: mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t) -> float C++: mrpt::math::CProbabilityDensityFunction<mrpt::poses::CPoint3D, 3>::getCovarianceEntropy() const --> double

getInformationMatrix(...)
getInformationMatrix(self: mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t, inf: mrpt::math::CMatrixFixed<double, 3ul, 3ul>) -> None C++: mrpt::math::CProbabilityDensityFunction<mrpt::poses::CPoint3D, 3>::getInformationMatrix(class mrpt::math::CMatrixFixed<double, 3, 3> &) const --> void

getMeanVal(...)
getMeanVal(self: mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t) -> mrpt::poses::CPoint3D C++: mrpt::math::CProbabilityDensityFunction<mrpt::poses::CPoint3D, 3>::getMeanVal() const --> class mrpt::poses::CPoint3D

isInfType(...)
isInfType(self: mrpt.pymrpt.mrpt.math.CProbabilityDensityFunction_mrpt_poses_CPoint3D_3UL_t) -> bool C++: mrpt::math::CProbabilityDensityFunction<mrpt::poses::CPoint3D, 3>::isInfType() const --> bool

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CBeaconMap(CMetricMap)

    A class for storing a map of 3D probabilistic beacons, using a Montecarlo, Gaussian, or Sum of Gaussians (SOG) representation (for range-only SLAM).   The individual beacons are defined as mrpt::maps::CBeacon objects.   When invoking CBeaconMap::insertObservation(), landmarks will be extracted and fused into the map.    The only currently supported observation type is mrpt::obs::CObservationBeaconRanges.    See insertionOptions and likelihoodOptions for parameters used when creating and fusing beacon landmarks.    Use "TInsertionOptions::insertAsMonteCarlo" to select between 2 different behaviors:                 - Initial PDF of beacons: MonteCarlo, after convergence, pass to Gaussians; or                 - Initial PDF of beacons: SOG, after convergence, a single Gaussian.    Refer to the papers: [] CMetricMap

Method resolution order:

CBeaconMap

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CBeaconMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CBeaconMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__getitem__(...)
__getitem__(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, i: int) -> mrpt.pymrpt.mrpt.maps.CBeacon Access to individual beacons C++: mrpt::maps::CBeaconMap::operator[](size_t) --> class mrpt::maps::CBeacon &

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CBeaconMap) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, arg0: mrpt.pymrpt.mrpt.maps.CBeaconMap) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, arg0: mrpt.pymrpt.mrpt.maps.CBeaconMap) -> None

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CBeaconMap) -> str Returns a short description of the map. C++: mrpt::maps::CBeaconMap::asString() const --> std::string

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, : mrpt.pymrpt.mrpt.maps.CBeaconMap) -> mrpt.pymrpt.mrpt.maps.CBeaconMap C++: mrpt::maps::CBeaconMap::operator=(const class mrpt::maps::CBeaconMap &) --> class mrpt::maps::CBeaconMap &

changeCoordinatesReference(...)
changeCoordinatesReference(*args, **kwargs) Overloaded function. 1. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, newOrg: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Changes the reference system of the map to a given 3D pose. C++: mrpt::maps::CBeaconMap::changeCoordinatesReference(const class mrpt::poses::CPose3D &) --> void 2. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, newOrg: mrpt.pymrpt.mrpt.poses.CPose3D, otherMap: mrpt.pymrpt.mrpt.maps.CBeaconMap) -> None Changes the reference system of the map "otherMap" and save the result in "this" map. C++: mrpt::maps::CBeaconMap::changeCoordinatesReference(const class mrpt::poses::CPose3D &, const class mrpt::maps::CBeaconMap *) --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CBeaconMap) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CBeaconMap::clone() const --> class mrpt::rtti::CObject *

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float C++: mrpt::maps::CBeaconMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CBeaconMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

get(...)
get(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, i: int) -> mrpt.pymrpt.mrpt.maps.CBeacon Access to individual beacons C++: mrpt::maps::CBeaconMap::get(size_t) --> class mrpt::maps::CBeacon &

getBeaconByID(...)
getBeaconByID(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, id: int) -> mrpt.pymrpt.mrpt.maps.CBeacon Returns a pointer to the beacon with the given ID, or nullptr if it does not exist. C++: mrpt::maps::CBeaconMap::getBeaconByID(int64_t) --> class mrpt::maps::CBeacon *

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns a 3D object representing the map. C++: mrpt::maps::CBeaconMap::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CBeaconMap) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CBeaconMap::isEmpty() const --> bool

push_back(...)
push_back(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, m: mrpt.pymrpt.mrpt.maps.CBeacon) -> None Inserts a copy of the given mode into the SOG C++: mrpt::maps::CBeaconMap::push_back(const class mrpt::maps::CBeacon &) --> void

resize(...)
resize(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, N: int) -> None Resize the number of SOG modes C++: mrpt::maps::CBeaconMap::resize(size_t) --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface).   In the case of this class, these files are generated:                 - "filNamePrefix"+"_3D.m": A script for MATLAB for drawing landmarks as 3D ellipses.                 - "filNamePrefix"+"_3D.3DScene": A 3D scene with a "ground plane grid" and the set of ellipsoids in 3D.                 - "filNamePrefix"+"_covs.m": A textual representation (see saveToTextFile) C++: mrpt::maps::CBeaconMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

saveToMATLABScript3D(...)
saveToMATLABScript3D(*args, **kwargs) Overloaded function. 1. saveToMATLABScript3D(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, file: str) -> bool 2. saveToMATLABScript3D(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, file: str, style: str) -> bool 3. saveToMATLABScript3D(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, file: str, style: str, confInterval: float) -> bool Save to a MATLAB script which displays 3D error ellipses for the map.                          The name of the file to save the script to.            The MATLAB-like string for the style of the lines (see 'help plot' in MATLAB for possibilities)    The ellipsoids will be drawn from the center to a given confidence interval in [0,1], e.g. 2 sigmas=0.95 (default is 2std = 0.95 confidence intervals)    Returns false if any error occured, true elsewere. C++: mrpt::maps::CBeaconMap::saveToMATLABScript3D(const std::string &, const char *, float) const --> bool

saveToTextFile(...)
saveToTextFile(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, fil: str) -> None Save a text file with a row per beacon, containing this 11 elements:   - X Y Z: Mean values   - VX VY VZ: Variances of each dimension (C11, C22, C33)   - DET2D DET3D: Determinant of the 2D and 3D covariance matrixes.   - C12, C13, C23: Cross covariances C++: mrpt::maps::CBeaconMap::saveToTextFile(const std::string &) const --> void

simulateBeaconReadings(...)
simulateBeaconReadings(self: mrpt.pymrpt.mrpt.maps.CBeaconMap, in_robotPose: mrpt.pymrpt.mrpt.poses.CPose3D, in_sensorLocationOnRobot: mrpt.pymrpt.mrpt.poses.CPoint3D, out_Observations: mrpt::obs::CObservationBeaconRanges) -> None Simulates a reading toward each of the beacons in the landmarks map, if any. This robot pose is used to simulate the ranges to each beacon. The 3D position of the sensor on the robot The results will be stored here. NOTICE that the fields "CObservationBeaconRanges::minSensorDistance","CObservationBeaconRanges::maxSensorDistance" and "CObservationBeaconRanges::stdError" MUST BE FILLED OUT before calling this function. An observation will be generated for each beacon in the map, but notice that some of them may be missed if out of the sensor maximum range. C++: mrpt::maps::CBeaconMap::simulateBeaconReadings(const class mrpt::poses::CPose3D &, const class mrpt::poses::CPoint3D &, class mrpt::obs::CObservationBeaconRanges &) const --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.CBeaconMap) -> int Returns the stored landmarks count. C++: mrpt::maps::CBeaconMap::size() const --> size_t

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CBeaconMap::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CBeaconMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

insertionOptions

likelihoodOptions

Data and other attributes defined here:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CBeaconMap.TInsertionOptions'>
This struct contains data for choosing the method by which new beacons are inserted in the map.

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.CBeaconMap.TLikelihoodOptions'>
With this struct options are provided to the likelihood computations

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CBeaconMap.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CBeaconMap.TMapDefinitionBase'>

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CColouredOctoMap(COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t)

    A three-dimensional probabilistic occupancy grid, implemented as an octo-tree with the "octomap" C++ library. This version stores both, occupancy information and RGB colour data at each octree node. See the base class mrpt::maps::COctoMapBase. CMetricMap, the example in "MRPT/samples/octomap_simple"

Method resolution order:

CColouredOctoMap

COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CColouredOctoMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, resolution: float) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, arg0: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> None 4. __init__(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, arg0: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, : mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> mrpt.pymrpt.mrpt.maps.CColouredOctoMap C++: mrpt::maps::CColouredOctoMap::operator=(const class mrpt::maps::CColouredOctoMap &) --> class mrpt::maps::CColouredOctoMap &

calcNumNodes(...)
calcNumNodes(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> int Traverses the tree to calculate the total number of nodes C++: mrpt::maps::CColouredOctoMap::calcNumNodes() const --> size_t

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CColouredOctoMap::clone() const --> class mrpt::rtti::CObject *

getAsOctoMapVoxels(...)
getAsOctoMapVoxels(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, gl_obj: mrpt.pymrpt.mrpt.opengl.COctoMapVoxels) -> None C++: mrpt::maps::CColouredOctoMap::getAsOctoMapVoxels(class mrpt::opengl::COctoMapVoxels &) const --> void

getClampingThresMax(...)
getClampingThresMax(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getClampingThresMax() const --> double

getClampingThresMaxLog(...)
getClampingThresMaxLog(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getClampingThresMaxLog() const --> float

getClampingThresMin(...)
getClampingThresMin(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getClampingThresMin() const --> double

getClampingThresMinLog(...)
getClampingThresMinLog(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getClampingThresMinLog() const --> float

getMetricMax(...)
getMetricMax(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, x: float, y: float, z: float) -> None maximum value of the bounding box of all known space in x, y, z C++: mrpt::maps::CColouredOctoMap::getMetricMax(double &, double &, double &) --> void

getMetricMin(...)
getMetricMin(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, x: float, y: float, z: float) -> None minimum value of the bounding box of all known space in x, y, z C++: mrpt::maps::CColouredOctoMap::getMetricMin(double &, double &, double &) --> void

getMetricSize(...)
getMetricSize(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, x: float, y: float, z: float) -> None Size of OcTree (all known space) in meters for x, y and z dimension C++: mrpt::maps::CColouredOctoMap::getMetricSize(double &, double &, double &) --> void

getNumLeafNodes(...)
getNumLeafNodes(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> int Traverses the tree to calculate the total number of leaf nodes C++: mrpt::maps::CColouredOctoMap::getNumLeafNodes() const --> size_t

getOccupancyThres(...)
getOccupancyThres(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getOccupancyThres() const --> double

getOccupancyThresLog(...)
getOccupancyThresLog(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getOccupancyThresLog() const --> float

getPointColour(...)
getPointColour(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, x: float, y: float, z: float, r: int, g: int, b: int) -> bool Get the RGB colour of a point false if the point is not mapped, in which case the returned colour is undefined. C++: mrpt::maps::CColouredOctoMap::getPointColour(const float, const float, const float, unsigned char &, unsigned char &, unsigned char &) const --> bool

getProbHit(...)
getProbHit(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getProbHit() const --> double

getProbHitLog(...)
getProbHitLog(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getProbHitLog() const --> float

getProbMiss(...)
getProbMiss(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getProbMiss() const --> double

getProbMissLog(...)
getProbMissLog(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getProbMissLog() const --> float

getResolution(...)
getResolution(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::getResolution() const --> double

getTreeDepth(...)
getTreeDepth(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> int C++: mrpt::maps::CColouredOctoMap::getTreeDepth() const --> unsigned int

getVoxelColourMethod(...)
getVoxelColourMethod(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> mrpt.pymrpt.mrpt.maps.CColouredOctoMap.TColourUpdate Get the method used to update voxels colour C++: mrpt::maps::CColouredOctoMap::getVoxelColourMethod() --> enum mrpt::maps::CColouredOctoMap::TColourUpdate

insertRay(...)
insertRay(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, end_x: float, end_y: float, end_z: float, sensor_x: float, sensor_y: float, sensor_z: float) -> None Just like insertPointCloud but with a single ray. C++: mrpt::maps::CColouredOctoMap::insertRay(const float, const float, const float, const float, const float, const float) --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> bool Returns true if the map is empty/no observation has been inserted C++: mrpt::maps::CColouredOctoMap::isEmpty() const --> bool

isPointWithinOctoMap(...)
isPointWithinOctoMap(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, x: float, y: float, z: float) -> bool Check whether the given point lies within the volume covered by the octomap (that is, whether it is "mapped") C++: mrpt::maps::CColouredOctoMap::isPointWithinOctoMap(const float, const float, const float) const --> bool

memoryFullGrid(...)
memoryFullGrid(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> int Memory usage of a full grid of the same size as the OcTree in bytes (for comparison) C++: mrpt::maps::CColouredOctoMap::memoryFullGrid() const --> size_t

memoryUsage(...)
memoryUsage(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> int Memory usage of the complete octree in bytes (may vary between architectures) C++: mrpt::maps::CColouredOctoMap::memoryUsage() const --> size_t

memoryUsageNode(...)
memoryUsageNode(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> int Memory usage of the a single octree node C++: mrpt::maps::CColouredOctoMap::memoryUsageNode() const --> size_t

setClampingThresMax(...)
setClampingThresMax(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, thresProb: float) -> None C++: mrpt::maps::CColouredOctoMap::setClampingThresMax(double) --> void

setClampingThresMin(...)
setClampingThresMin(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, thresProb: float) -> None C++: mrpt::maps::CColouredOctoMap::setClampingThresMin(double) --> void

setOccupancyThres(...)
setOccupancyThres(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, prob: float) -> None C++: mrpt::maps::CColouredOctoMap::setOccupancyThres(double) --> void

setProbHit(...)
setProbHit(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, prob: float) -> None C++: mrpt::maps::CColouredOctoMap::setProbHit(double) --> void

setProbMiss(...)
setProbMiss(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, prob: float) -> None C++: mrpt::maps::CColouredOctoMap::setProbMiss(double) --> void

setVoxelColourMethod(...)
setVoxelColourMethod(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, new_method: mrpt.pymrpt.mrpt.maps.CColouredOctoMap.TColourUpdate) -> None Set the method used to update voxels colour C++: mrpt::maps::CColouredOctoMap::setVoxelColourMethod(enum mrpt::maps::CColouredOctoMap::TColourUpdate) --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> int The number of nodes in the tree C++: mrpt::maps::CColouredOctoMap::size() const --> size_t

updateVoxel(...)
updateVoxel(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, x: float, y: float, z: float, occupied: bool) -> None Manually updates the occupancy of the voxel at (x,y,z) as being occupied (true) or free (false), using the log-odds parameters in C++: mrpt::maps::CColouredOctoMap::updateVoxel(const double, const double, const double, bool) --> void

updateVoxelColour(...)
updateVoxelColour(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap, x: float, y: float, z: float, r: int, g: int, b: int) -> None Manually update the colour of the voxel at (x,y,z) C++: mrpt::maps::CColouredOctoMap::updateVoxelColour(const double, const double, const double, const unsigned char, const unsigned char, const unsigned char) --> void

volume(...)
volume(self: mrpt.pymrpt.mrpt.maps.CColouredOctoMap) -> float C++: mrpt::maps::CColouredOctoMap::volume() --> double

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CColouredOctoMap::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CColouredOctoMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data and other attributes defined here:

AVERAGE = <TColourUpdate.AVERAGE: 2>

INTEGRATE = <TColourUpdate.INTEGRATE: 0>

SET = <TColourUpdate.SET: 1>

TColourUpdate = <class 'mrpt.pymrpt.mrpt.maps.CColouredOctoMap.TColourUpdate'>

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CColouredOctoMap.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CColouredOctoMap.TMapDefinitionBase'>

Methods inherited from COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t:

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> str C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::asString() const --> std::string

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

castRay(...)
castRay(*args, **kwargs) Overloaded function. 1. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>) -> bool 2. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>, ignoreUnknownCells: bool) -> bool 3. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>, ignoreUnknownCells: bool, maxRange: float) -> bool C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::castRay(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, struct mrpt::math::TPoint3D_<double> &, bool, double) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float Computes the ratio in [0,1] of correspondences between "this" and the "otherMap" map, whose 6D pose relative to "this" is "otherMapPose"    In the case of a multi-metric map, this returns the average between the maps. This method always return 0 for grid maps.       [IN] The other map to compute the matching with.   [IN] The 6D pose of the other map as seen from "this".         [IN] Matching parameters The matching ratio [0,1] determineMatching2D C++: mrpt::maps::CMetricMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

getPointOccupancy(...)
getPointOccupancy(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, x: float, y: float, z: float, prob_occupancy: float) -> bool C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getPointOccupancy(const float, const float, const float, double &) const --> bool

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, o: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

insertPointCloud(...)
insertPointCloud(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, ptMap: mrpt.pymrpt.mrpt.maps.CPointsMap, sensor_x: float, sensor_y: float, sensor_z: float) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::insertPointCloud(const class mrpt::maps::CPointsMap &, const float, const float, const float) --> void

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, Map: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, Map: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(*args, **kwargs) Overloaded function. 1. saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, filNamePrefix: str) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::saveMetricMapRepresentationToFile(const std::string &) const --> void 2. saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface). C++: mrpt::maps::CMetricMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t:

genericMapParams

insertionOptions

likelihoodOptions

renderingOptions

Data and other attributes inherited from COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octom...ree_octomap_ColorOcTreeNode_t.TInsertionOptions'>

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octom...ee_octomap_ColorOcTreeNode_t.TLikelihoodOptions'>

TRenderingOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octom...ree_octomap_ColorOcTreeNode_t.TRenderingOptions'>

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CColouredPointsMap(CPointsMap)

    A map of 2D/3D points with individual colours (RGB). For different color schemes, see CColouredPointsMap::colorScheme Colors are defined in the range [0,1]. mrpt::maps::CPointsMap, mrpt::maps::CMetricMap, mrpt::serialization::CSerializable

Method resolution order:

CColouredPointsMap

CPointsMap

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.opengl.PLY_Importer

mrpt.pymrpt.mrpt.opengl.PLY_Exporter

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CColouredPointsMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, o: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, arg0: mrpt.pymrpt.mrpt.maps.CColouredPointsMap) -> None 4. __init__(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, arg0: mrpt.pymrpt.mrpt.maps.CColouredPointsMap) -> None

assign(...)
assign(*args, **kwargs) Overloaded function. 1. assign(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, o: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.maps.CColouredPointsMap C++: mrpt::maps::CColouredPointsMap::operator=(const class mrpt::maps::CPointsMap &) --> class mrpt::maps::CColouredPointsMap & 2. assign(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, o: mrpt.pymrpt.mrpt.maps.CColouredPointsMap) -> mrpt.pymrpt.mrpt.maps.CColouredPointsMap C++: mrpt::maps::CColouredPointsMap::operator=(const class mrpt::maps::CColouredPointsMap &) --> class mrpt::maps::CColouredPointsMap &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CColouredPointsMap::clone() const --> class mrpt::rtti::CObject *

colourFromObservation(...)
colourFromObservation(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, obs: mrpt.pymrpt.mrpt.obs.CObservationImage, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool Colour a set of points from a CObservationImage and the global pose of the robot C++: mrpt::maps::CColouredPointsMap::colourFromObservation(const class mrpt::obs::CObservationImage &, const class mrpt::poses::CPose3D &) --> bool

getPointColor(...)
getPointColor(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, index: int, R: float, G: float, B: float) -> None Retrieves a point color (colors range is [0,1]) C++: mrpt::maps::CColouredPointsMap::getPointColor(size_t, float &, float &, float &) const --> void

getPointColor_fast(...)
getPointColor_fast(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, index: int, R: float, G: float, B: float) -> None Like  but without checking for out-of-index erors C++: mrpt::maps::CColouredPointsMap::getPointColor_fast(size_t, float &, float &, float &) const --> void

getPointRGB(...)
getPointRGB(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, index: int, x: float, y: float, z: float, R: float, G: float, B: float) -> None Retrieves a point and its color (colors range is [0,1]) C++: mrpt::maps::CColouredPointsMap::getPointRGB(size_t, float &, float &, float &, float &, float &, float &) const --> void

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Override of the default 3D scene builder to account for the individual points' color. C++: mrpt::maps::CColouredPointsMap::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

hasColorPoints(...)
hasColorPoints(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap) -> bool Returns true if the point map has a color field for each point C++: mrpt::maps::CColouredPointsMap::hasColorPoints() const --> bool

insertPointFast(...)
insertPointFast(*args, **kwargs) Overloaded function. 1. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, x: float, y: float) -> None 2. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, x: float, y: float, z: float) -> None The virtual method for  *without* calling mark_as_modified()    C++: mrpt::maps::CColouredPointsMap::insertPointFast(float, float, float) --> void

insertPointRGB(...)
insertPointRGB(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, x: float, y: float, z: float, R: float, G: float, B: float) -> None Adds a new point given its coordinates and color (colors range is [0,1]) C++: mrpt::maps::CColouredPointsMap::insertPointRGB(float, float, float, float, float, float) --> void

reserve(...)
reserve(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, newLength: int) -> None            from CPointsMap                 @{ C++: mrpt::maps::CColouredPointsMap::reserve(size_t) --> void

resetPointsMinDist(...)
resetPointsMinDist(*args, **kwargs) Overloaded function. 1. resetPointsMinDist(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap) -> None 2. resetPointsMinDist(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, defValue: float) -> None Reset the minimum-observed-distance buffer for all the points to a predefined value C++: mrpt::maps::CColouredPointsMap::resetPointsMinDist(float) --> void

resize(...)
resize(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, newLength: int) -> None C++: mrpt::maps::CColouredPointsMap::resize(size_t) --> void

save3D_and_colour_to_text_file(...)
save3D_and_colour_to_text_file(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, file: str) -> bool Save to a text file. In each line contains X Y Z (meters) R G B (range [0,1]) for each point in the map.      Returns false if any error occured, true elsewere. C++: mrpt::maps::CColouredPointsMap::save3D_and_colour_to_text_file(const std::string &) const --> bool

setPointColor(...)
setPointColor(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, index: int, R: float, G: float, B: float) -> None Changes just the color of a given point from the map. First index is 0. Throws std::exception on index out of bound. C++: mrpt::maps::CColouredPointsMap::setPointColor(size_t, float, float, float) --> void

setPointColor_fast(...)
setPointColor_fast(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, index: int, R: float, G: float, B: float) -> None Like  but without checking for out-of-index erors C++: mrpt::maps::CColouredPointsMap::setPointColor_fast(size_t, float, float, float) --> void

setPointRGB(...)
setPointRGB(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, index: int, x: float, y: float, z: float, R: float, G: float, B: float) -> None Changes a given point from map. First index is 0. Throws std::exception on index out of bound. C++: mrpt::maps::CColouredPointsMap::setPointRGB(size_t, float, float, float, float, float, float) --> void

setSize(...)
setSize(self: mrpt.pymrpt.mrpt.maps.CColouredPointsMap, newLength: int) -> None C++: mrpt::maps::CColouredPointsMap::setSize(size_t) --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CColouredPointsMap::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CColouredPointsMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

colorScheme

Data and other attributes defined here:

TColourOptions = <class 'mrpt.pymrpt.mrpt.maps.CColouredPointsMap.TColourOptions'>
The definition of parameters for generating colors from laser scans

TColouringMethod = <class 'mrpt.pymrpt.mrpt.maps.CColouredPointsMap.TColouringMethod'>

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CColouredPointsMap.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CColouredPointsMap.TMapDefinitionBase'>

cmFromHeightRelativeToSensor = <TColouringMethod.cmFromHeightRelativeToSensor: 0>

cmFromHeightRelativeToSensorGray = <TColouringMethod.cmFromHeightRelativeToSensorGray: 1>

cmFromHeightRelativeToSensorJet = <TColouringMethod.cmFromHeightRelativeToSensor: 0>

cmFromIntensityImage = <TColouringMethod.cmFromIntensityImage: 2>

Methods inherited from CPointsMap:

__iadd__(...)
__iadd__(self: mrpt.pymrpt.mrpt.maps.CPointsMap, anotherMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Inserts another map into this one. insertAnotherMap() C++: mrpt::maps::CPointsMap::operator+=(const class mrpt::maps::CPointsMap &) --> void

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> str Returns a short description of the map. C++: mrpt::maps::CPointsMap::asString() const --> std::string

boundingBox(...)
boundingBox(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.math.TBoundingBox_float_t Computes the bounding box of all the points, or (0,0 ,0,0, 0,0) if there are no points.   Results are cached unless the map is somehow modified to avoid repeated calculations. C++: mrpt::maps::CPointsMap::boundingBox() const --> struct mrpt::math::TBoundingBox_<float>

changeCoordinatesReference(...)
changeCoordinatesReference(*args, **kwargs) Overloaded function. 1. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose2D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose2D &) --> void 2. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose3D &) --> void 3. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, other: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Copy all the points from "other" map to "this", replacing each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::maps::CPointsMap &, const class mrpt::poses::CPose3D &) --> void

clipOutOfRange(...)
clipOutOfRange(self: mrpt.pymrpt.mrpt.maps.CPointsMap, point: mrpt::math::TPoint2D_<double>, maxRange: float) -> None Delete points which are more far than "maxRange" away from the given "point". C++: mrpt::maps::CPointsMap::clipOutOfRange(const struct mrpt::math::TPoint2D_<double> &, float) --> void

clipOutOfRangeInZ(...)
clipOutOfRangeInZ(self: mrpt.pymrpt.mrpt.maps.CPointsMap, zMin: float, zMax: float) -> None Delete points out of the given "z" axis range have been removed. C++: mrpt::maps::CPointsMap::clipOutOfRangeInZ(float, float) --> void

compute3DDistanceToMesh(...)
compute3DDistanceToMesh(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap2: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, maxDistForCorrespondence: float, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, correspondencesRatio: float) -> None Computes the matchings between this and another 3D points map.            This method matches each point in the other map with the centroid of the          3 closest points in 3D            from this map (if the distance is below a defined threshold).                                           [IN] The other map to compute the          matching with.                                   [IN] The pose of the other map as seen          from "this".    [IN] Maximum 2D linear distance          between two points to be matched.                           [OUT] The detected matchings pairs.                   [OUT] The ratio [0,1] of points in          otherMap with at least one correspondence. determineMatching3D C++: mrpt::maps::CPointsMap::compute3DDistanceToMesh(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, float, class mrpt::tfest::TMatchingPairListTempl<float> &, float &) --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float C++: mrpt::maps::CPointsMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

empty(...)
empty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool STL-like method to check whether the map is empty: C++: mrpt::maps::CPointsMap::empty() const --> bool

enableFilterByHeight(...)
enableFilterByHeight(*args, **kwargs) Overloaded function. 1. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, enable: bool) -> None Enable/disable the filter-by-height functionality setHeightFilterLevels Default upon construction is disabled. C++: mrpt::maps::CPointsMap::enableFilterByHeight(bool) --> void

extractCylinder(...)
extractCylinder(self: mrpt.pymrpt.mrpt.maps.CPointsMap, center: mrpt::math::TPoint2D_<double>, radius: float, zmin: float, zmax: float, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Extracts the points in the map within a cylinder in 3D defined the provided radius and zmin/zmax values. C++: mrpt::maps::CPointsMap::extractCylinder(const struct mrpt::math::TPoint2D_<double> &, const double, const double, const double, class mrpt::maps::CPointsMap *) --> void

extractPoints(...)
extractPoints(*args, **kwargs) Overloaded function. 1. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float) -> None 3. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float) -> None 4. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float, B: float) -> None Extracts the points in the map within the area defined by two corners.   The points are coloured according the R,G,B input data. C++: mrpt::maps::CPointsMap::extractPoints(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, class mrpt::maps::CPointsMap *, double, double, double) --> void

getHeightFilterLevels(...)
getHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Get the min/max Z levels for points to be actually inserted in the map enableFilterByHeight, setHeightFilterLevels C++: mrpt::maps::CPointsMap::getHeightFilterLevels(double &, double &) const --> void

getLargestDistanceFromOrigin(...)
getLargestDistanceFromOrigin(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> float This method returns the largest distance from the origin to any of the points, such as a sphere centered at the origin with this radius cover ALL the points in the map (the results are buffered, such as, if the map is not modified, the second call will be much faster than the first one). C++: mrpt::maps::CPointsMap::getLargestDistanceFromOrigin() const --> float

getLargestDistanceFromOriginNoRecompute(...)
getLargestDistanceFromOriginNoRecompute(self: mrpt.pymrpt.mrpt.maps.CPointsMap, output_is_valid: bool) -> float Like  but returns in = false if the distance was not already computed, skipping its computation then, unlike getLargestDistanceFromOrigin() C++: mrpt::maps::CPointsMap::getLargestDistanceFromOriginNoRecompute(bool &) const --> float

getPoint(...)
getPoint(*args, **kwargs) Overloaded function. 1. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Access to a given point from map, as a 2D point. First index is 0. Throws std::exception on index out of bound. setPoint, getPointFast C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &, float &) const --> void 2. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &) const --> void 3. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &, double &) const --> void 4. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &) const --> void 5. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint2D_<double> &) const --> void 6. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint3D_<double> &) const --> void

getPointFast(...)
getPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Just like  but without checking out-of-bound index and without returning the point weight, just XYZ. C++: mrpt::maps::CPointsMap::getPointFast(size_t, float &, float &, float &) const --> void

getPointWeight(...)
getPointWeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int) -> int Gets the point weight, which is ignored in all classes (defaults to 1) but in those which actually store that field (Note: No checks are done for out-of-bounds index).   setPointWeight C++: mrpt::maps::CPointsMap::getPointWeight(size_t) const --> unsigned int

insertAnotherMap(...)
insertAnotherMap(*args, **kwargs) Overloaded function. 1. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> None 2. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D, filterOutPointsAtZero: bool) -> None Insert the contents of another map into this one with some geometric transformation, without fusing close points. The other map whose points are to be inserted into this one. The pose of the other map in the coordinates of THIS map If true, points at (0,0,0) (in the frame of reference of `otherMap`) will be assumed to be invalid and will not be copied. fuseWith, addFrom C++: mrpt::maps::CPointsMap::insertAnotherMap(const class mrpt::maps::CPointsMap *, const class mrpt::poses::CPose3D &, const bool) --> void

insertPoint(...)
insertPoint(*args, **kwargs) Overloaded function. 1. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float) -> None 2. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float, z: float) -> None Provides a way to insert (append) individual points into the map: the missing fields of child classes (color, weight, etc) are left to their default values C++: mrpt::maps::CPointsMap::insertPoint(float, float, float) --> void 3. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::insertPoint(const struct mrpt::math::TPoint3D_<double> &) --> void

internal_computeObservationLikelihood(...)
internal_computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CPointsMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float @} C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

internal_computeObservationLikelihoodPointCloud3D(...)
internal_computeObservationLikelihoodPointCloud3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, pc_in_map: mrpt.pymrpt.mrpt.poses.CPose3D, xs: float, ys: float, zs: float, num_pts: int) -> float C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihoodPointCloud3D(const class mrpt::poses::CPose3D &, const float *, const float *, const float *, const unsigned long) const --> double

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CPointsMap::isEmpty() const --> bool

isFilterByHeightEnabled(...)
isFilterByHeightEnabled(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Return whether filter-by-height is enabled enableFilterByHeight C++: mrpt::maps::CPointsMap::isFilterByHeightEnabled() const --> bool

kdtree_distance(...)
kdtree_distance(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p1: float, idx_p2: int, size: int) -> float Returns the distance between the vector "p1[0:size-1]" and the data point with index "idx_p2" stored in the class: C++: mrpt::maps::CPointsMap::kdtree_distance(const float *, size_t, size_t) const --> float

kdtree_get_point_count(...)
kdtree_get_point_count(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Must return the number of data points C++: mrpt::maps::CPointsMap::kdtree_get_point_count() const --> size_t

kdtree_get_pt(...)
kdtree_get_pt(self: mrpt.pymrpt.mrpt.maps.CPointsMap, idx: int, dim: int) -> float Returns the dim'th component of the idx'th point in the class: C++: mrpt::maps::CPointsMap::kdtree_get_pt(size_t, int) const --> float

load2D_from_text_file(...)
load2D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y" coordinate pair, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load2D_from_text_file(const std::string &) --> bool

load2Dor3D_from_text_file(...)
load2Dor3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str, is_3D: bool) -> bool 2D or 3D generic implementation of  and load3D_from_text_file C++: mrpt::maps::CPointsMap::load2Dor3D_from_text_file(const std::string &, const bool) --> bool

load3D_from_text_file(...)
load3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y Z" coordinate tuple, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load3D_from_text_file(const std::string &) --> bool

mark_as_modified(...)
mark_as_modified(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Users normally don't need to call this. Called by this class or children classes, set m_largestDistanceFromOriginIsUpdated=false, invalidates the kd-tree cache, and such. C++: mrpt::maps::CPointsMap::mark_as_modified() const --> void

save2D_to_text_file(...)
save2D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y" point coordinates.                 Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save2D_to_text_file(const std::string &) const --> bool

save3D_to_text_file(...)
save3D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y Z" point coordinates.      Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save3D_to_text_file(const std::string &) const --> bool

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CPointsMap, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface) C++: mrpt::maps::CPointsMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

setHeightFilterLevels(...)
setHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Set the min/max Z levels for points to be actually inserted in the map (only if  was called before). C++: mrpt::maps::CPointsMap::setHeightFilterLevels(const double, const double) --> void

setPoint(...)
setPoint(*args, **kwargs) Overloaded function. 1. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes a given point from map, with Z defaulting to 0 if not provided. Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float, float) --> void 2. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint2D_<double> &) --> void 3. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint3D_<double> &) --> void 4. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float) --> void

setPointFast(...)
setPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes the coordinates of the given point (0-based index), *without* checking for out-of-bounds and *without* calling mark_as_modified(). Also, color, intensity, or other data is left unchanged. setPoint C++: mrpt::maps::CPointsMap::setPointFast(size_t, float, float, float) --> void

setPointWeight(...)
setPointWeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, w: int) -> None Sets the point weight, which is ignored in all classes but those which actually store that field (Note: No checks are done for out-of-bounds index). getPointWeight C++: mrpt::maps::CPointsMap::setPointWeight(size_t, unsigned long) --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Returns the number of stored points in the map. C++: mrpt::maps::CPointsMap::size() const --> size_t

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondence(float, float) const --> float

squareDistanceToClosestCorrespondenceT(...)
squareDistanceToClosestCorrespondenceT(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p0: mrpt::math::TPoint2D_<double>) -> float C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondenceT(const struct mrpt::math::TPoint2D_<double> &) const --> float

Data descriptors inherited from CPointsMap:

insertionOptions

likelihoodOptions

renderOptions

Data and other attributes inherited from CPointsMap:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TInsertionOptions'>
With this struct options are provided to the observation insertion process. CObservation::insertIntoPointsMap

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TLikelihoodOptions'>
Options used when evaluating "computeObservationLikelihood" in the derived classes. CObservation::computeObservationLikelihood

TRenderOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TRenderOptions'>
Rendering options, used in getAs3DObject()

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Importer:

getLoadPLYErrorString(...)
getLoadPLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Importer::getLoadPLYErrorString() const --> std::string

loadFromPlyFile(...)
loadFromPlyFile(*args, **kwargs) Overloaded function. 1. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str) -> bool 2. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str]) -> bool 3. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str], file_obj_info: List[str]) -> bool Loads from a PLY file. The filename to open. It can be either in binary or text format. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error in the file format or reading it. To obtain more details on the error you can call getLoadPLYErrorString() C++: mrpt::opengl::PLY_Importer::loadFromPlyFile(const std::string &, class std::vector<std::string > *, class std::vector<std::string > *) --> bool

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Exporter:

getSavePLYErrorString(...)
getSavePLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Exporter::getSavePLYErrorString() const --> std::string

saveToPlyFile(...)
saveToPlyFile(*args, **kwargs) Overloaded function. 1. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str) -> bool 2. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool) -> bool 3. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str]) -> bool 4. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str], file_obj_info: List[str]) -> bool Saves to a PLY file. The filename to be saved. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error writing the file. To obtain more details on the error you can call getSavePLYErrorString() C++: mrpt::opengl::PLY_Exporter::saveToPlyFile(const std::string &, bool, const class std::vector<std::string > &, const class std::vector<std::string > &) const --> bool

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CGasConcentrationGridMap2D(CRandomFieldGridMap2D)

    CGasConcentrationGridMap2D represents a PDF of gas concentrations over a 2D area. There are a number of methods available to build the gas grid-map, depending on the value of    "TMapRepresentation maptype" passed in the constructor (see base class mrpt::maps::CRandomFieldGridMap2D). Update the map with insertIndividualReading() or insertObservation() mrpt::maps::CRandomFieldGridMap2D, mrpt::maps::CMetricMap, mrpt::containers::CDynamicGrid, The application icp-slam, mrpt::maps::CMultiMetricMap

Method resolution order:

CGasConcentrationGridMap2D

CRandomFieldGridMap2D

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CGasConcentrationGridMap2D::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float) -> None doc 4. __init__(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float) -> None doc 5. __init__(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float, arg3: float) -> None doc 6. __init__(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float, arg3: float, arg4: float) -> None doc 7. __init__(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, mapType: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 8. __init__(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D) -> None 9. __init__(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, : mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D) -> mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D C++: mrpt::maps::CGasConcentrationGridMap2D::operator=(const class mrpt::maps::CGasConcentrationGridMap2D &) --> class mrpt::maps::CGasConcentrationGridMap2D &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CGasConcentrationGridMap2D::clone() const --> class mrpt::rtti::CObject *

getAs3DObject(...)
getAs3DObject(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, meanObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects, varObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns two 3D objects representing the mean and variance maps C++: mrpt::maps::CGasConcentrationGridMap2D::getAs3DObject(class mrpt::opengl::CSetOfObjects &, class mrpt::opengl::CSetOfObjects &) const --> void

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns a 3D object representing the map C++: mrpt::maps::CGasConcentrationGridMap2D::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

getWindAs3DObject(...)
getWindAs3DObject(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, windObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns the 3D object representing the wind grid information C++: mrpt::maps::CGasConcentrationGridMap2D::getWindAs3DObject(class std::shared_ptr<class mrpt::opengl::CSetOfObjects> &) const --> void

increaseUncertainty(...)
increaseUncertainty(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, STD_increase_value: float) -> None Increase the kf_std of all cells from the m_map         This mehod is usually called by the main_map to simulate loss of confidence in measurements when time passes C++: mrpt::maps::CGasConcentrationGridMap2D::increaseUncertainty(const double) --> void

simulateAdvection(...)
simulateAdvection(self: mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D, STD_increase_value: float) -> bool Implements the transition model of the gasConcentration map using the information of the wind maps   C++: mrpt::maps::CGasConcentrationGridMap2D::simulateAdvection(double) --> bool

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CGasConcentrationGridMap2D::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CGasConcentrationGridMap2D::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

LUT

insertionOptions

Data and other attributes defined here:

TGaussianCell = <class 'mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D.TGaussianCell'>

TGaussianWindTable = <class 'mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D.TGaussianWindTable'>

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D.TInsertionOptions'>
Parameters related with inserting observations into the map:

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CGasConcentrationGridMap2D.TMapDefinitionBase'>

Methods inherited from CRandomFieldGridMap2D:

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> str Returns a short description of the map. C++: mrpt::maps::CRandomFieldGridMap2D::asString() const --> std::string

cell2float(...)
cell2float(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, c: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float C++: mrpt::maps::CRandomFieldGridMap2D::cell2float(const struct mrpt::maps::TRandomFieldCell &) const --> float

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None Calls the base CMetricMap::clear Declared here to avoid ambiguity between the two clear() in both base classes. C++: mrpt::maps::CRandomFieldGridMap2D::clear() --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float See docs in base class: in this class this always returns 0 C++: mrpt::maps::CRandomFieldGridMap2D::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

enableProfiler(...)
enableProfiler(*args, **kwargs) Overloaded function. 1. enableProfiler(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None 2. enableProfiler(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, enable: bool) -> None C++: mrpt::maps::CRandomFieldGridMap2D::enableProfiler(bool) --> void

enableVerbose(...)
enableVerbose(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, enable_verbose: bool) -> None C++: mrpt::maps::CRandomFieldGridMap2D::enableVerbose(bool) --> void

getAsBitmapFile(...)
getAsBitmapFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_img: mrpt.pymrpt.mrpt.img.CImage) -> None Returns an image just as described in   C++: mrpt::maps::CRandomFieldGridMap2D::getAsBitmapFile(class mrpt::img::CImage &) const --> void

getAsMatrix(...)
getAsMatrix(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_mat: mrpt.pymrpt.mrpt.math.CMatrixDynamic_double_t) -> None Like saveAsBitmapFile(), but returns the data in matrix form (first row in the matrix is the upper (y_max) part of the map) C++: mrpt::maps::CRandomFieldGridMap2D::getAsMatrix(class mrpt::math::CMatrixDynamic<double> &) const --> void

getMapType(...)
getMapType(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation Return the type of the random-field grid map, according to parameters passed on construction. C++: mrpt::maps::CRandomFieldGridMap2D::getMapType() --> enum mrpt::maps::CRandomFieldGridMap2D::TMapRepresentation

getMeanAndCov(...)
getMeanAndCov(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_cov: mrpt.pymrpt.mrpt.math.CMatrixDynamic_double_t) -> None Return the mean and covariance vector of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::getMeanAndCov(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CMatrixDynamic<double> &) const --> void

getMeanAndSTD(...)
getMeanAndSTD(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_STD: mrpt::math::CVectorDynamic<double>) -> None Return the mean and STD vectors of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::getMeanAndSTD(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CVectorDynamic<double> &) const --> void

insertIndividualReading(...)
insertIndividualReading(*args, **kwargs) Overloaded function. 1. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>) -> None 2. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool) -> None 3. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool, time_invariant: bool) -> None 4. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool, time_invariant: bool, reading_stddev: float) -> None Direct update of the map with a reading in a given position of the map, using   the appropriate method according to mapType passed in the constructor. This is a direct way to update the map, an alternative to the generic insertObservation() method which works with mrpt::obs::CObservation objects. C++: mrpt::maps::CRandomFieldGridMap2D::insertIndividualReading(const double, const struct mrpt::math::TPoint2D_<double> &, const bool, const bool, const double) --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool Returns true if the map is empty/no observation has been inserted (in this class it always return false, unless redefined otherwise in base classes) C++: mrpt::maps::CRandomFieldGridMap2D::isEmpty() const --> bool

isEnabledVerbose(...)
isEnabledVerbose(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool C++: mrpt::maps::CRandomFieldGridMap2D::isEnabledVerbose() const --> bool

isProfilerEnabled(...)
isProfilerEnabled(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool C++: mrpt::maps::CRandomFieldGridMap2D::isProfilerEnabled() const --> bool

predictMeasurement(...)
predictMeasurement(*args, **kwargs) Overloaded function. 1. predictMeasurement(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x: float, y: float, out_predict_response: float, out_predict_response_variance: float, do_sensor_normalization: bool) -> None 2. predictMeasurement(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x: float, y: float, out_predict_response: float, out_predict_response_variance: float, do_sensor_normalization: bool, interp_method: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TGridInterpolationMethod) -> None Returns the prediction of the measurement at some (x,y) coordinates, and its certainty (in the form of the expected variance).   C++: mrpt::maps::CRandomFieldGridMap2D::predictMeasurement(const double, const double, double &, double &, bool, const enum mrpt::maps::CRandomFieldGridMap2D::TGridInterpolationMethod) --> void

resize(...)
resize(*args, **kwargs) Overloaded function. 1. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> None 2. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt.pymrpt.mrpt.maps.TRandomFieldCell, additionalMarginMeters: float) -> None Changes the size of the grid, maintaining previous contents. setSize C++: mrpt::maps::CRandomFieldGridMap2D::resize(double, double, double, double, const struct mrpt::maps::TRandomFieldCell &, double) --> void

saveAsBitmapFile(...)
saveAsBitmapFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filName: str) -> None Save the current map as a graphical file (BMP,PNG,...). The file format will be derived from the file extension (see CImage::saveToFile )   It depends on the map representation model:                 mrAchim: Each pixel is the ratio                 mrKalmanFilter: Each pixel is the mean value of the Gaussian that represents each cell.           C++: mrpt::maps::CRandomFieldGridMap2D::saveAsBitmapFile(const std::string &) const --> void

saveAsMatlab3DGraph(...)
saveAsMatlab3DGraph(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filName: str) -> None Save a matlab ".m" file which represents as 3D surfaces the mean and a given confidence level for the concentration of each cell.   This method can only be called in a KF map model. C++: mrpt::maps::CRandomFieldGridMap2D::saveAsMatlab3DGraph(const std::string &) const --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filNamePrefix: str) -> None The implementation in this class just calls all the corresponding method of the contained metric maps C++: mrpt::maps::CRandomFieldGridMap2D::saveMetricMapRepresentationToFile(const std::string &) const --> void

setCellsConnectivity(...)
setCellsConnectivity(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_connectivity_descriptor: mrpt::maps::CRandomFieldGridMap2D::ConnectivityDescriptor) -> None Sets a custom object to define the connectivity between cells. Must call clear() or setSize() afterwards for the changes to take place. C++: mrpt::maps::CRandomFieldGridMap2D::setCellsConnectivity(const class std::shared_ptr<struct mrpt::maps::CRandomFieldGridMap2D::ConnectivityDescriptor> &) --> void

setMeanAndSTD(...)
setMeanAndSTD(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_STD: mrpt::math::CVectorDynamic<double>) -> None Load the mean and STD vectors of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::setMeanAndSTD(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CVectorDynamic<double> &) --> void

setSize(...)
setSize(*args, **kwargs) Overloaded function. 1. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 2. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float, fill_value: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> None Changes the size of the grid, erasing previous contents.    Optional user-supplied object that will visit all grid cells to define their connectivity with neighbors and the strength of existing edges. If present, it overrides all options in insertionOptions resize C++: mrpt::maps::CRandomFieldGridMap2D::setSize(const double, const double, const double, const double, const double, const struct mrpt::maps::TRandomFieldCell *) --> void

updateMapEstimation(...)
updateMapEstimation(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None Run the method-specific procedure required to ensure that the mean & variances are up-to-date with all inserted observations. C++: mrpt::maps::CRandomFieldGridMap2D::updateMapEstimation() --> void

Data and other attributes inherited from CRandomFieldGridMap2D:

ConnectivityDescriptor = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.ConnectivityDescriptor'>
Base class for user-supplied objects capable of describing cells connectivity, used to build prior factors of the MRF graph. setCellsConnectivity()

TGridInterpolationMethod = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TGridInterpolationMethod'>

TInsertionOptionsCommon = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TInsertionOptionsCommon'>
Parameters common to any derived class. Derived classes should derive a new struct from this one, plus "public CLoadableOptions", and call the internal_* methods where appropiate to deal with the variables declared here. Derived classes instantions of their "TInsertionOptions" MUST set the pointer "m_insertOptions_common" upon construction.

TMapRepresentation = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation'>

gimBilinear = <TGridInterpolationMethod.gimBilinear: 1>

gimNearest = <TGridInterpolationMethod.gimNearest: 0>

mrAchim = <TMapRepresentation.mrKernelDM: 0>

mrGMRF_SD = <TMapRepresentation.mrGMRF_SD: 4>

mrKalmanApproximate = <TMapRepresentation.mrKalmanApproximate: 2>

mrKalmanFilter = <TMapRepresentation.mrKalmanFilter: 1>

mrKernelDM = <TMapRepresentation.mrKernelDM: 0>

mrKernelDMV = <TMapRepresentation.mrKernelDMV: 3>

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t:

cellByIndex(...)
cellByIndex(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cx: int, cy: int) -> mrpt::maps::TRandomFieldCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::cellByIndex(unsigned int, unsigned int) --> struct mrpt::maps::TRandomFieldCell *

cellByPos(...)
cellByPos(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float, y: float) -> mrpt::maps::TRandomFieldCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::cellByPos(double, double) --> struct mrpt::maps::TRandomFieldCell *

fill(...)
fill(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, value: mrpt::maps::TRandomFieldCell) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::fill(const struct mrpt::maps::TRandomFieldCell &) --> void

getResolution(...)
getResolution(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getResolution() const --> double

getSizeX(...)
getSizeX(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getSizeX() const --> size_t

getSizeY(...)
getSizeY(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getSizeY() const --> size_t

getXMax(...)
getXMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getXMax() const --> double

getXMin(...)
getXMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getXMin() const --> double

getYMax(...)
getYMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getYMax() const --> double

getYMin(...)
getYMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getYMin() const --> double

idx2cxcy(...)
idx2cxcy(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, idx: int, cx: int, cy: int) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2cxcy(int, int &, int &) const --> void

idx2x(...)
idx2x(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cx: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2x(int) const --> double

idx2y(...)
idx2y(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cy: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2y(int) const --> double

saveToTextFile(...)
saveToTextFile(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, fileName: str) -> bool C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::saveToTextFile(const std::string &) const --> bool

x2idx(...)
x2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::x2idx(double) const --> int

xy2idx(...)
xy2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::xy2idx(double, double) const --> int

y2idx(...)
y2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::y2idx(double) const --> int

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CHeightGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, CHeightGridMap2D_Base)

    Digital Elevation Model (DEM), a mesh or grid representation of a surface which keeps the estimated height for each (x,y) location. Important implemented features are the insertion of 2D laser scans (from arbitrary 6D poses) and the exportation as 3D scenes. Each cell contains the up-to-date average height from measured falling in that cell. Algorithms that can be used:   - mrSimpleAverage: Each cell only stores the current average value. This class implements generic version of mrpt::maps::CMetric::insertObservation() accepting these types of sensory data:   - mrpt::obs::CObservation2DRangeScan: 2D range scans   - mrpt::obs::CObservationVelodyneScan

Method resolution order:

CHeightGridMap2D

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t

CHeightGridMap2D_Base

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CHeightGridMap2D::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, arg0: mrpt::maps::CHeightGridMap2D::TMapRepresentation) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, arg0: mrpt::maps::CHeightGridMap2D::TMapRepresentation, arg1: float) -> None doc 4. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, arg0: mrpt::maps::CHeightGridMap2D::TMapRepresentation, arg1: float, arg2: float) -> None doc 5. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, arg0: mrpt::maps::CHeightGridMap2D::TMapRepresentation, arg1: float, arg2: float, arg3: float) -> None doc 6. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, arg0: mrpt::maps::CHeightGridMap2D::TMapRepresentation, arg1: float, arg2: float, arg3: float, arg4: float) -> None doc 7. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, mapType: mrpt::maps::CHeightGridMap2D::TMapRepresentation, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 8. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> None 9. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> None

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> str Returns a short description of the map. C++: mrpt::maps::CHeightGridMap2D::asString() const --> std::string

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, : mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> mrpt.pymrpt.mrpt.maps.CHeightGridMap2D C++: mrpt::maps::CHeightGridMap2D::operator=(const class mrpt::maps::CHeightGridMap2D &) --> class mrpt::maps::CHeightGridMap2D &

cell2float(...)
cell2float(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, c: mrpt.pymrpt.mrpt.maps.THeightGridmapCell) -> float C++: mrpt::maps::CHeightGridMap2D::cell2float(const struct mrpt::maps::THeightGridmapCell &) const --> float

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> None Calls the base CMetricMap::clear Declared here to avoid ambiguity between the two clear() in both base classes. C++: mrpt::maps::CHeightGridMap2D::clear() --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CHeightGridMap2D::clone() const --> class mrpt::rtti::CObject *

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float See docs in base class: in this class it always returns 0 C++: mrpt::maps::CHeightGridMap2D::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

countObservedCells(...)
countObservedCells(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> int Return the number of cells with at least one height data inserted. C++: mrpt::maps::CHeightGridMap2D::countObservedCells() const --> size_t

dem_get_resolution(...)
dem_get_resolution(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> float C++: mrpt::maps::CHeightGridMap2D::dem_get_resolution() const --> double

dem_get_size_x(...)
dem_get_size_x(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> int C++: mrpt::maps::CHeightGridMap2D::dem_get_size_x() const --> size_t

dem_get_size_y(...)
dem_get_size_y(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> int C++: mrpt::maps::CHeightGridMap2D::dem_get_size_y() const --> size_t

dem_get_z(...)
dem_get_z(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, x: float, y: float, z_out: float) -> bool C++: mrpt::maps::CHeightGridMap2D::dem_get_z(const double, const double, double &) const --> bool

dem_get_z_by_cell(...)
dem_get_z_by_cell(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, cx: int, cy: int, z_out: float) -> bool C++: mrpt::maps::CHeightGridMap2D::dem_get_z_by_cell(size_t, size_t, double &) const --> bool

dem_update_map(...)
dem_update_map(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> None C++: mrpt::maps::CHeightGridMap2D::dem_update_map() --> void

getMapType(...)
getMapType(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> mrpt.pymrpt.mrpt.maps.CHeightGridMap2D.TMapRepresentation Return the type of the gas distribution map, according to parameters passed on construction C++: mrpt::maps::CHeightGridMap2D::getMapType() --> enum mrpt::maps::CHeightGridMap2D::TMapRepresentation

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns a 3D object representing the map: by default, it will be a mrpt::opengl::CMesh object, unless    it is specified otherwise in mrpt::global_settings::HEIGHTGRIDMAP_EXPORT3D_AS_MESH C++: mrpt::maps::CHeightGridMap2D::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

insertIndividualPoint(...)
insertIndividualPoint(*args, **kwargs) Overloaded function. 1. insertIndividualPoint(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, x: float, y: float, z: float) -> bool 2. insertIndividualPoint(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, x: float, y: float, z: float, params: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base.TPointInsertParams) -> bool C++: mrpt::maps::CHeightGridMap2D::insertIndividualPoint(const double, const double, const double, const struct mrpt::maps::CHeightGridMap2D_Base::TPointInsertParams &) --> bool

internal_clear(...)
internal_clear(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> None C++: mrpt::maps::CHeightGridMap2D::internal_clear() --> void

internal_computeObservationLikelihood(...)
internal_computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float C++: mrpt::maps::CHeightGridMap2D::internal_computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CHeightGridMap2D::isEmpty() const --> bool

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D, filNamePrefix: str) -> None C++: mrpt::maps::CHeightGridMap2D::saveMetricMapRepresentationToFile(const std::string &) const --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CHeightGridMap2D::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CHeightGridMap2D::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

insertionOptions

m_mapType

Data and other attributes defined here:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D.TInsertionOptions'>
Parameters related with inserting observations into the map

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D.TMapDefinitionBase'>

TMapRepresentation = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D.TMapRepresentation'>

mrSimpleAverage = <TMapRepresentation.mrSimpleAverage: 0>

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t:

cellByIndex(...)
cellByIndex(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, cx: int, cy: int) -> mrpt::maps::THeightGridmapCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::cellByIndex(unsigned int, unsigned int) --> struct mrpt::maps::THeightGridmapCell *

cellByPos(...)
cellByPos(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, x: float, y: float) -> mrpt::maps::THeightGridmapCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::cellByPos(double, double) --> struct mrpt::maps::THeightGridmapCell *

fill(...)
fill(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, value: mrpt::maps::THeightGridmapCell) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::fill(const struct mrpt::maps::THeightGridmapCell &) --> void

getResolution(...)
getResolution(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::getResolution() const --> double

getSizeX(...)
getSizeX(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::getSizeX() const --> size_t

getSizeY(...)
getSizeY(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::getSizeY() const --> size_t

getXMax(...)
getXMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::getXMax() const --> double

getXMin(...)
getXMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::getXMin() const --> double

getYMax(...)
getYMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::getYMax() const --> double

getYMin(...)
getYMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::getYMin() const --> double

idx2cxcy(...)
idx2cxcy(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, idx: int, cx: int, cy: int) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::idx2cxcy(int, int &, int &) const --> void

idx2x(...)
idx2x(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, cx: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::idx2x(int) const --> double

idx2y(...)
idx2y(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, cy: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::idx2y(int) const --> double

resize(...)
resize(*args, **kwargs) Overloaded function. 1. resize(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt::maps::THeightGridmapCell) -> None 2. resize(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt::maps::THeightGridmapCell, additionalMarginMeters: float) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::resize(double, double, double, double, const struct mrpt::maps::THeightGridmapCell &, double) --> void

saveToTextFile(...)
saveToTextFile(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, fileName: str) -> bool C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::saveToTextFile(const std::string &) const --> bool

setSize(...)
setSize(*args, **kwargs) Overloaded function. 1. setSize(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 2. setSize(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float, fill_value: mrpt::maps::THeightGridmapCell) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::setSize(const double, const double, const double, const double, const double, const struct mrpt::maps::THeightGridmapCell *) --> void

x2idx(...)
x2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, x: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::x2idx(double) const --> int

xy2idx(...)
xy2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, x: float, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::xy2idx(double, double) const --> int

y2idx(...)
y2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_THeightGridmapCell_t, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::THeightGridmapCell>::y2idx(double) const --> int

Methods inherited from CHeightGridMap2D_Base:

getMinMaxHeight(...)
getMinMaxHeight(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, z_min: float, z_max: float) -> bool Computes the minimum and maximum height in the grid. False if there is no observed cell yet. C++: mrpt::maps::CHeightGridMap2D_Base::getMinMaxHeight(float &, float &) const --> bool

intersectLine3D(...)
intersectLine3D(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, r1: mrpt.pymrpt.mrpt.math.TLine3D, obj: mrpt.pymrpt.mrpt.math.TObject3D) -> bool                 @{ Gets the intersection between a 3D line and a Height Grid map (taking into account the different heights of each individual cell)   C++: mrpt::maps::CHeightGridMap2D_Base::intersectLine3D(const struct mrpt::math::TLine3D &, struct mrpt::math::TObject3D &) const --> bool

Data and other attributes inherited from CHeightGridMap2D_Base:

TPointInsertParams = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base.TPointInsertParams'>
Extra params for insertIndividualPoint()

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CHeightGridMap2D_Base(pybind11_builtins.pybind11_object)

    Virtual base class for Digital Elevation Model (DEM) maps. See derived classes for details. This class implements those operations which are especific to DEMs.

Method resolution order:

CHeightGridMap2D_Base

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, arg0: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, : mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base) -> mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base C++: mrpt::maps::CHeightGridMap2D_Base::operator=(const class mrpt::maps::CHeightGridMap2D_Base &) --> class mrpt::maps::CHeightGridMap2D_Base &

dem_get_resolution(...)
dem_get_resolution(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base) -> float C++: mrpt::maps::CHeightGridMap2D_Base::dem_get_resolution() const --> double

dem_get_size_x(...)
dem_get_size_x(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base) -> int C++: mrpt::maps::CHeightGridMap2D_Base::dem_get_size_x() const --> size_t

dem_get_size_y(...)
dem_get_size_y(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base) -> int C++: mrpt::maps::CHeightGridMap2D_Base::dem_get_size_y() const --> size_t

dem_get_z(...)
dem_get_z(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, x: float, y: float, z_out: float) -> bool Get cell 'z' (x,y) by metric coordinates. false if out of bounds or un-observed cell. C++: mrpt::maps::CHeightGridMap2D_Base::dem_get_z(const double, const double, double &) const --> bool

dem_get_z_by_cell(...)
dem_get_z_by_cell(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, cx: int, cy: int, z_out: float) -> bool Get cell 'z' by (cx,cy) cell indices. false if out of bounds or un-observed cell. C++: mrpt::maps::CHeightGridMap2D_Base::dem_get_z_by_cell(size_t, size_t, double &) const --> bool

dem_update_map(...)
dem_update_map(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base) -> None Ensure that all observations are reflected in the map estimate C++: mrpt::maps::CHeightGridMap2D_Base::dem_update_map() --> void

getMinMaxHeight(...)
getMinMaxHeight(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, z_min: float, z_max: float) -> bool Computes the minimum and maximum height in the grid. False if there is no observed cell yet. C++: mrpt::maps::CHeightGridMap2D_Base::getMinMaxHeight(float &, float &) const --> bool

insertIndividualPoint(...)
insertIndividualPoint(*args, **kwargs) Overloaded function. 1. insertIndividualPoint(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, x: float, y: float, z: float) -> bool 2. insertIndividualPoint(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, x: float, y: float, z: float, params: mrpt::maps::CHeightGridMap2D_Base::TPointInsertParams) -> bool Update the DEM with one new point. mrpt::maps::CMetricMap::insertObservation() for inserting higher-level objects like 2D/3D LIDAR scans true if updated OK, false if (x,y) is out of bounds C++: mrpt::maps::CHeightGridMap2D_Base::insertIndividualPoint(const double, const double, const double, const struct mrpt::maps::CHeightGridMap2D_Base::TPointInsertParams &) --> bool

intersectLine3D(...)
intersectLine3D(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, r1: mrpt.pymrpt.mrpt.math.TLine3D, obj: mrpt.pymrpt.mrpt.math.TObject3D) -> bool                 @{ Gets the intersection between a 3D line and a Height Grid map (taking into account the different heights of each individual cell)   C++: mrpt::maps::CHeightGridMap2D_Base::intersectLine3D(const struct mrpt::math::TLine3D &, struct mrpt::math::TObject3D &) const --> bool

Data and other attributes defined here:

TPointInsertParams = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base.TPointInsertParams'>
Extra params for insertIndividualPoint()

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CHeightGridMap2D_MRF(CRandomFieldGridMap2D, CHeightGridMap2D_Base)

    CHeightGridMap2D_MRF represents digital-elevation-model over a 2D area, with uncertainty, based on a Markov-Random-Field (MRF) estimator. There are a number of methods available to build the gas grid-map, depending on the value of    "TMapRepresentation maptype" passed in the constructor (see base class mrpt::maps::CRandomFieldGridMap2D). Update the map with insertIndividualReading() or insertObservation() mrpt::maps::CRandomFieldGridMap2D, mrpt::maps::CMetricMap, mrpt::containers::CDynamicGrid, The application icp-slam, mrpt::maps::CMultiMetricMap New in MRPT 1.4.0

Method resolution order:

CHeightGridMap2D_MRF

CRandomFieldGridMap2D

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t

CHeightGridMap2D_Base

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CHeightGridMap2D_MRF::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float) -> None doc 4. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float) -> None doc 5. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float, arg3: float) -> None doc 6. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float, arg3: float, arg4: float) -> None doc 7. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float, arg3: float, arg4: float, arg5: float) -> None doc 8. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, mapType: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float, run_first_map_estimation_now: bool) -> None 9. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, arg0: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> None 10. __init__(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, arg0: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, : mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF C++: mrpt::maps::CHeightGridMap2D_MRF::operator=(const class mrpt::maps::CHeightGridMap2D_MRF &) --> class mrpt::maps::CHeightGridMap2D_MRF &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CHeightGridMap2D_MRF::clone() const --> class mrpt::rtti::CObject *

dem_get_resolution(...)
dem_get_resolution(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> float C++: mrpt::maps::CHeightGridMap2D_MRF::dem_get_resolution() const --> double

dem_get_size_x(...)
dem_get_size_x(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> int C++: mrpt::maps::CHeightGridMap2D_MRF::dem_get_size_x() const --> size_t

dem_get_size_y(...)
dem_get_size_y(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> int C++: mrpt::maps::CHeightGridMap2D_MRF::dem_get_size_y() const --> size_t

dem_get_z(...)
dem_get_z(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, x: float, y: float, z_out: float) -> bool C++: mrpt::maps::CHeightGridMap2D_MRF::dem_get_z(const double, const double, double &) const --> bool

dem_get_z_by_cell(...)
dem_get_z_by_cell(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, cx: int, cy: int, z_out: float) -> bool C++: mrpt::maps::CHeightGridMap2D_MRF::dem_get_z_by_cell(size_t, size_t, double &) const --> bool

dem_update_map(...)
dem_update_map(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> None C++: mrpt::maps::CHeightGridMap2D_MRF::dem_update_map() --> void

getAs3DObject(...)
getAs3DObject(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, meanObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects, varObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns two 3D objects representing the mean and variance maps C++: mrpt::maps::CHeightGridMap2D_MRF::getAs3DObject(class mrpt::opengl::CSetOfObjects &, class mrpt::opengl::CSetOfObjects &) const --> void

getCommonInsertOptions(...)
getCommonInsertOptions(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TInsertionOptionsCommon Get the part of the options common to all CRandomFieldGridMap2D classes C++: mrpt::maps::CHeightGridMap2D_MRF::getCommonInsertOptions() --> struct mrpt::maps::CRandomFieldGridMap2D::TInsertionOptionsCommon *

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns a 3D object representing the map C++: mrpt::maps::CHeightGridMap2D_MRF::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

insertIndividualPoint(...)
insertIndividualPoint(*args, **kwargs) Overloaded function. 1. insertIndividualPoint(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, x: float, y: float, z: float) -> bool 2. insertIndividualPoint(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, x: float, y: float, z: float, params: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base.TPointInsertParams) -> bool C++: mrpt::maps::CHeightGridMap2D_MRF::insertIndividualPoint(const double, const double, const double, const struct mrpt::maps::CHeightGridMap2D_Base::TPointInsertParams &) --> bool

internal_clear(...)
internal_clear(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF) -> None C++: mrpt::maps::CHeightGridMap2D_MRF::internal_clear() --> void

internal_computeObservationLikelihood(...)
internal_computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float C++: mrpt::maps::CHeightGridMap2D_MRF::internal_computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CHeightGridMap2D_MRF::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CHeightGridMap2D_MRF::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

insertionOptions

Data and other attributes defined here:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF.TInsertionOptions'>
Parameters related with inserting observations into the map

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_MRF.TMapDefinitionBase'>

Methods inherited from CRandomFieldGridMap2D:

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> str Returns a short description of the map. C++: mrpt::maps::CRandomFieldGridMap2D::asString() const --> std::string

cell2float(...)
cell2float(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, c: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float C++: mrpt::maps::CRandomFieldGridMap2D::cell2float(const struct mrpt::maps::TRandomFieldCell &) const --> float

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None Calls the base CMetricMap::clear Declared here to avoid ambiguity between the two clear() in both base classes. C++: mrpt::maps::CRandomFieldGridMap2D::clear() --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float See docs in base class: in this class this always returns 0 C++: mrpt::maps::CRandomFieldGridMap2D::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

enableProfiler(...)
enableProfiler(*args, **kwargs) Overloaded function. 1. enableProfiler(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None 2. enableProfiler(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, enable: bool) -> None C++: mrpt::maps::CRandomFieldGridMap2D::enableProfiler(bool) --> void

enableVerbose(...)
enableVerbose(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, enable_verbose: bool) -> None C++: mrpt::maps::CRandomFieldGridMap2D::enableVerbose(bool) --> void

getAsBitmapFile(...)
getAsBitmapFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_img: mrpt.pymrpt.mrpt.img.CImage) -> None Returns an image just as described in   C++: mrpt::maps::CRandomFieldGridMap2D::getAsBitmapFile(class mrpt::img::CImage &) const --> void

getAsMatrix(...)
getAsMatrix(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_mat: mrpt.pymrpt.mrpt.math.CMatrixDynamic_double_t) -> None Like saveAsBitmapFile(), but returns the data in matrix form (first row in the matrix is the upper (y_max) part of the map) C++: mrpt::maps::CRandomFieldGridMap2D::getAsMatrix(class mrpt::math::CMatrixDynamic<double> &) const --> void

getMapType(...)
getMapType(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation Return the type of the random-field grid map, according to parameters passed on construction. C++: mrpt::maps::CRandomFieldGridMap2D::getMapType() --> enum mrpt::maps::CRandomFieldGridMap2D::TMapRepresentation

getMeanAndCov(...)
getMeanAndCov(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_cov: mrpt.pymrpt.mrpt.math.CMatrixDynamic_double_t) -> None Return the mean and covariance vector of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::getMeanAndCov(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CMatrixDynamic<double> &) const --> void

getMeanAndSTD(...)
getMeanAndSTD(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_STD: mrpt::math::CVectorDynamic<double>) -> None Return the mean and STD vectors of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::getMeanAndSTD(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CVectorDynamic<double> &) const --> void

insertIndividualReading(...)
insertIndividualReading(*args, **kwargs) Overloaded function. 1. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>) -> None 2. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool) -> None 3. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool, time_invariant: bool) -> None 4. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool, time_invariant: bool, reading_stddev: float) -> None Direct update of the map with a reading in a given position of the map, using   the appropriate method according to mapType passed in the constructor. This is a direct way to update the map, an alternative to the generic insertObservation() method which works with mrpt::obs::CObservation objects. C++: mrpt::maps::CRandomFieldGridMap2D::insertIndividualReading(const double, const struct mrpt::math::TPoint2D_<double> &, const bool, const bool, const double) --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool Returns true if the map is empty/no observation has been inserted (in this class it always return false, unless redefined otherwise in base classes) C++: mrpt::maps::CRandomFieldGridMap2D::isEmpty() const --> bool

isEnabledVerbose(...)
isEnabledVerbose(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool C++: mrpt::maps::CRandomFieldGridMap2D::isEnabledVerbose() const --> bool

isProfilerEnabled(...)
isProfilerEnabled(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool C++: mrpt::maps::CRandomFieldGridMap2D::isProfilerEnabled() const --> bool

predictMeasurement(...)
predictMeasurement(*args, **kwargs) Overloaded function. 1. predictMeasurement(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x: float, y: float, out_predict_response: float, out_predict_response_variance: float, do_sensor_normalization: bool) -> None 2. predictMeasurement(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x: float, y: float, out_predict_response: float, out_predict_response_variance: float, do_sensor_normalization: bool, interp_method: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TGridInterpolationMethod) -> None Returns the prediction of the measurement at some (x,y) coordinates, and its certainty (in the form of the expected variance).   C++: mrpt::maps::CRandomFieldGridMap2D::predictMeasurement(const double, const double, double &, double &, bool, const enum mrpt::maps::CRandomFieldGridMap2D::TGridInterpolationMethod) --> void

resize(...)
resize(*args, **kwargs) Overloaded function. 1. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> None 2. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt.pymrpt.mrpt.maps.TRandomFieldCell, additionalMarginMeters: float) -> None Changes the size of the grid, maintaining previous contents. setSize C++: mrpt::maps::CRandomFieldGridMap2D::resize(double, double, double, double, const struct mrpt::maps::TRandomFieldCell &, double) --> void

saveAsBitmapFile(...)
saveAsBitmapFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filName: str) -> None Save the current map as a graphical file (BMP,PNG,...). The file format will be derived from the file extension (see CImage::saveToFile )   It depends on the map representation model:                 mrAchim: Each pixel is the ratio                 mrKalmanFilter: Each pixel is the mean value of the Gaussian that represents each cell.           C++: mrpt::maps::CRandomFieldGridMap2D::saveAsBitmapFile(const std::string &) const --> void

saveAsMatlab3DGraph(...)
saveAsMatlab3DGraph(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filName: str) -> None Save a matlab ".m" file which represents as 3D surfaces the mean and a given confidence level for the concentration of each cell.   This method can only be called in a KF map model. C++: mrpt::maps::CRandomFieldGridMap2D::saveAsMatlab3DGraph(const std::string &) const --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filNamePrefix: str) -> None The implementation in this class just calls all the corresponding method of the contained metric maps C++: mrpt::maps::CRandomFieldGridMap2D::saveMetricMapRepresentationToFile(const std::string &) const --> void

setCellsConnectivity(...)
setCellsConnectivity(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_connectivity_descriptor: mrpt::maps::CRandomFieldGridMap2D::ConnectivityDescriptor) -> None Sets a custom object to define the connectivity between cells. Must call clear() or setSize() afterwards for the changes to take place. C++: mrpt::maps::CRandomFieldGridMap2D::setCellsConnectivity(const class std::shared_ptr<struct mrpt::maps::CRandomFieldGridMap2D::ConnectivityDescriptor> &) --> void

setMeanAndSTD(...)
setMeanAndSTD(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_STD: mrpt::math::CVectorDynamic<double>) -> None Load the mean and STD vectors of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::setMeanAndSTD(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CVectorDynamic<double> &) --> void

setSize(...)
setSize(*args, **kwargs) Overloaded function. 1. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 2. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float, fill_value: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> None Changes the size of the grid, erasing previous contents.    Optional user-supplied object that will visit all grid cells to define their connectivity with neighbors and the strength of existing edges. If present, it overrides all options in insertionOptions resize C++: mrpt::maps::CRandomFieldGridMap2D::setSize(const double, const double, const double, const double, const double, const struct mrpt::maps::TRandomFieldCell *) --> void

updateMapEstimation(...)
updateMapEstimation(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None Run the method-specific procedure required to ensure that the mean & variances are up-to-date with all inserted observations. C++: mrpt::maps::CRandomFieldGridMap2D::updateMapEstimation() --> void

Data and other attributes inherited from CRandomFieldGridMap2D:

ConnectivityDescriptor = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.ConnectivityDescriptor'>
Base class for user-supplied objects capable of describing cells connectivity, used to build prior factors of the MRF graph. setCellsConnectivity()

TGridInterpolationMethod = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TGridInterpolationMethod'>

TInsertionOptionsCommon = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TInsertionOptionsCommon'>
Parameters common to any derived class. Derived classes should derive a new struct from this one, plus "public CLoadableOptions", and call the internal_* methods where appropiate to deal with the variables declared here. Derived classes instantions of their "TInsertionOptions" MUST set the pointer "m_insertOptions_common" upon construction.

TMapRepresentation = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation'>

gimBilinear = <TGridInterpolationMethod.gimBilinear: 1>

gimNearest = <TGridInterpolationMethod.gimNearest: 0>

mrAchim = <TMapRepresentation.mrKernelDM: 0>

mrGMRF_SD = <TMapRepresentation.mrGMRF_SD: 4>

mrKalmanApproximate = <TMapRepresentation.mrKalmanApproximate: 2>

mrKalmanFilter = <TMapRepresentation.mrKalmanFilter: 1>

mrKernelDM = <TMapRepresentation.mrKernelDM: 0>

mrKernelDMV = <TMapRepresentation.mrKernelDMV: 3>

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t:

cellByIndex(...)
cellByIndex(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cx: int, cy: int) -> mrpt::maps::TRandomFieldCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::cellByIndex(unsigned int, unsigned int) --> struct mrpt::maps::TRandomFieldCell *

cellByPos(...)
cellByPos(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float, y: float) -> mrpt::maps::TRandomFieldCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::cellByPos(double, double) --> struct mrpt::maps::TRandomFieldCell *

fill(...)
fill(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, value: mrpt::maps::TRandomFieldCell) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::fill(const struct mrpt::maps::TRandomFieldCell &) --> void

getResolution(...)
getResolution(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getResolution() const --> double

getSizeX(...)
getSizeX(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getSizeX() const --> size_t

getSizeY(...)
getSizeY(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getSizeY() const --> size_t

getXMax(...)
getXMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getXMax() const --> double

getXMin(...)
getXMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getXMin() const --> double

getYMax(...)
getYMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getYMax() const --> double

getYMin(...)
getYMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getYMin() const --> double

idx2cxcy(...)
idx2cxcy(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, idx: int, cx: int, cy: int) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2cxcy(int, int &, int &) const --> void

idx2x(...)
idx2x(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cx: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2x(int) const --> double

idx2y(...)
idx2y(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cy: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2y(int) const --> double

saveToTextFile(...)
saveToTextFile(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, fileName: str) -> bool C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::saveToTextFile(const std::string &) const --> bool

x2idx(...)
x2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::x2idx(double) const --> int

xy2idx(...)
xy2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::xy2idx(double, double) const --> int

y2idx(...)
y2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::y2idx(double) const --> int

Methods inherited from CHeightGridMap2D_Base:

getMinMaxHeight(...)
getMinMaxHeight(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, z_min: float, z_max: float) -> bool Computes the minimum and maximum height in the grid. False if there is no observed cell yet. C++: mrpt::maps::CHeightGridMap2D_Base::getMinMaxHeight(float &, float &) const --> bool

intersectLine3D(...)
intersectLine3D(self: mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base, r1: mrpt.pymrpt.mrpt.math.TLine3D, obj: mrpt.pymrpt.mrpt.math.TObject3D) -> bool                 @{ Gets the intersection between a 3D line and a Height Grid map (taking into account the different heights of each individual cell)   C++: mrpt::maps::CHeightGridMap2D_Base::intersectLine3D(const struct mrpt::math::TLine3D &, struct mrpt::math::TObject3D &) const --> bool

Data and other attributes inherited from CHeightGridMap2D_Base:

TPointInsertParams = <class 'mrpt.pymrpt.mrpt.maps.CHeightGridMap2D_Base.TPointInsertParams'>
Extra params for insertIndividualPoint()

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CLandmark(mrpt.pymrpt.mrpt.serialization.CSerializable)

    The class for storing "landmarks" (visual or laser-scan-extracted features,...) The descriptors for each kind of descriptor are stored in the vector "features", which   will typically consists of only 1 element, or 2 elements for landmarks obtained from stereo images. CLandmarksMap

Method resolution order:

CLandmark

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CLandmark) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CLandmark::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CLandmark) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CLandmark, arg0: mrpt.pymrpt.mrpt.maps.CLandmark) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CLandmark, arg0: mrpt.pymrpt.mrpt.maps.CLandmark) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CLandmark, : mrpt.pymrpt.mrpt.maps.CLandmark) -> mrpt.pymrpt.mrpt.maps.CLandmark C++: mrpt::maps::CLandmark::operator=(const class mrpt::maps::CLandmark &) --> class mrpt::maps::CLandmark &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CLandmark) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CLandmark::clone() const --> class mrpt::rtti::CObject *

createOneFeature(...)
createOneFeature(self: mrpt.pymrpt.mrpt.maps.CLandmark) -> None Creates one feature in the vector "features", calling the appropriate constructor of the smart pointer, so after calling this method "features[0]" is a valid pointer to a CFeature object. C++: mrpt::maps::CLandmark::createOneFeature() --> void

getPose(...)
getPose(*args, **kwargs) Overloaded function. 1. getPose(self: mrpt.pymrpt.mrpt.maps.CLandmark, p: mrpt.pymrpt.mrpt.poses.CPointPDFGaussian) -> None Returns the pose as an object: C++: mrpt::maps::CLandmark::getPose(class mrpt::poses::CPointPDFGaussian &) const --> void 2. getPose(self: mrpt.pymrpt.mrpt.maps.CLandmark, p: mrpt.pymrpt.mrpt.poses.CPoint3D, COV: mrpt.pymrpt.mrpt.math.CMatrixDynamic_double_t) -> None C++: mrpt::maps::CLandmark::getPose(class mrpt::poses::CPoint3D &, class mrpt::math::CMatrixDynamic<double> &) const --> void

getType(...)
getType(self: mrpt.pymrpt.mrpt.maps.CLandmark) -> mrpt.pymrpt.mrpt.vision.TKeyPointMethod Gets the type of the first feature in its feature vector. The vector must not be empty. C++: mrpt::maps::CLandmark::getType() const --> enum mrpt::vision::TKeyPointMethod

setPose(...)
setPose(self: mrpt.pymrpt.mrpt.maps.CLandmark, p: mrpt.pymrpt.mrpt.poses.CPointPDFGaussian) -> None Sets the pose from an object: C++: mrpt::maps::CLandmark::setPose(const class mrpt::poses::CPointPDFGaussian &) --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CLandmark::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CLandmark::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

ID

features

normal

pose_cov_11

pose_cov_12

pose_cov_13

pose_cov_22

pose_cov_23

pose_cov_33

pose_mean

seenTimesCount

timestampLastSeen

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CLandmarksMap(CMetricMap)

    A class for storing a map of 3D probabilistic landmarks. Currently these types of landmarks are defined: (see mrpt::maps::CLandmark)                - For "visual landmarks" from images: features with associated descriptors.                - For laser scanners: each of the range measuremnts, as "occupancy" landmarks.                - For grid maps: "Panoramic descriptor" feature points.                - For range-only localization and SLAM: Beacons. It is also supported the simulation of expected beacon-to-sensor readings, observation likelihood,... How to load landmarks from observations: When invoking CLandmarksMap::insertObservation(), the values in CLandmarksMap::insertionOptions will     determinate the kind of landmarks that will be extracted and fused into the map. Supported feature     extraction processes are listed next:   Observation class: Generated Landmarks: Comments:   CObservationImage vlSIFT 1) A SIFT feature is created for each SIFT detected in the image,                   2) Correspondences between SIFTs features and existing ones are finded by computeMatchingWith3DLandmarks,                   3) The corresponding feaures are fused, and the new ones added, with an initial uncertainty according to insertionOptions   CObservationStereoImages vlSIFT  Each image is separately procesed by the method for CObservationImage observations   CObservationStereoImages vlColor  TODO...   CObservation2DRangeScan glOccupancy  A landmark is added for each range in the scan, with its appropiate covariance matrix derived from the jacobians matrixes.   CMetricMap

Method resolution order:

CLandmarksMap

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CLandmarksMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> None

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> str Returns a short description of the map. C++: mrpt::maps::CLandmarksMap::asString() const --> std::string

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, : mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> mrpt.pymrpt.mrpt.maps.CLandmarksMap C++: mrpt::maps::CLandmarksMap::operator=(const class mrpt::maps::CLandmarksMap &) --> class mrpt::maps::CLandmarksMap &

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> None C++: mrpt::maps::CLandmarksMap::auxParticleFilterCleanUp() --> void

changeCoordinatesReference(...)
changeCoordinatesReference(*args, **kwargs) Overloaded function. 1. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, newOrg: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Changes the reference system of the map to a given 3D pose. C++: mrpt::maps::CLandmarksMap::changeCoordinatesReference(const class mrpt::poses::CPose3D &) --> void 2. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, newOrg: mrpt.pymrpt.mrpt.poses.CPose3D, otherMap: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> None Changes the reference system of the map "otherMap" and save the result in "this" map. C++: mrpt::maps::CLandmarksMap::changeCoordinatesReference(const class mrpt::poses::CPose3D &, const class mrpt::maps::CLandmarksMap *) --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CLandmarksMap::clone() const --> class mrpt::rtti::CObject *

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float ** END FAMD **** C++: mrpt::maps::CLandmarksMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

computeLikelihood_RSLC_2007(...)
computeLikelihood_RSLC_2007(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, s: mrpt.pymrpt.mrpt.maps.CLandmarksMap, sensorPose: mrpt.pymrpt.mrpt.poses.CPose2D) -> float Computes the (logarithmic) likelihood function for a sensed observation           "o" according to "this" map.    This is the implementation of the algorithm reported in the paper:                         J.L. Blanco, J. Gonzalez, and J.A. Fernandez-Madrigal, "A           Consensus-based Approach for Estimating the Observation Likelihood of           Accurate Range Sensors", in IEEE International Conference on Robotics and           Automation (ICRA), Rome (Italy), Apr 10-14, 2007 C++: mrpt::maps::CLandmarksMap::computeLikelihood_RSLC_2007(const class mrpt::maps::CLandmarksMap *, const class mrpt::poses::CPose2D &) const --> double

computeMatchingWith2D(...)
computeMatchingWith2D(*args, **kwargs) Overloaded function. 1. computeMatchingWith2D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, maxDistForCorrespondence: float, maxAngularDistForCorrespondence: float, angularDistPivotPoint: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, correspondencesRatio: float) -> None 2. computeMatchingWith2D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, maxDistForCorrespondence: float, maxAngularDistForCorrespondence: float, angularDistPivotPoint: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, correspondencesRatio: float, sumSqrDist: float) -> None 3. computeMatchingWith2D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, maxDistForCorrespondence: float, maxAngularDistForCorrespondence: float, angularDistPivotPoint: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, correspondencesRatio: float, sumSqrDist: float, onlyKeepTheClosest: bool) -> None 4. computeMatchingWith2D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, maxDistForCorrespondence: float, maxAngularDistForCorrespondence: float, angularDistPivotPoint: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, correspondencesRatio: float, sumSqrDist: float, onlyKeepTheClosest: bool, onlyUniqueRobust: bool) -> None C++: mrpt::maps::CLandmarksMap::computeMatchingWith2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, float, float, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, float &, float *, bool, bool) const --> void

fuseWith(...)
fuseWith(*args, **kwargs) Overloaded function. 1. fuseWith(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, other: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> None 2. fuseWith(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, other: mrpt.pymrpt.mrpt.maps.CLandmarksMap, justInsertAllOfThem: bool) -> None Fuses the contents of another map with this one, updating "this" object with the result.   This process involves fusing corresponding landmarks, then adding the new ones.    The other landmarkmap, whose landmarks will be inserted into "this"    If set to "true", all the landmarks in "other" will be inserted into "this" without checking for possible correspondences (may appear duplicates ones, etc...) C++: mrpt::maps::CLandmarksMap::fuseWith(class mrpt::maps::CLandmarksMap &, bool) --> void

getMapMaxID(...)
getMapMaxID(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> int C++: mrpt::maps::CLandmarksMap::getMapMaxID() --> long

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns a 3D object representing the map. COLOR_LANDMARKS_IN_3DSCENES C++: mrpt::maps::CLandmarksMap::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

internal_computeObservationLikelihood(...)
internal_computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the (logarithmic) likelihood that a given observation was taken from a given pose in the world being modeled with this map.   In the current implementation, this method behaves in a different way according to the nature of    the observation's class:                 - "mrpt::obs::CObservation2DRangeScan": This calls "computeLikelihood_RSLC_2007".                 - "mrpt::obs::CObservationStereoImages": This calls "computeLikelihood_SIFT_LandmarkMap".   Observation class: Generated Landmarks: Comments:   CObservationImage vlSIFT 1) A SIFT feature is created for each SIFT detected in the image,           2) Correspondences between SIFTs features and existing ones are found by computeMatchingWith3DLandmarks,                    3) The corresponding feaures are fused, and the new ones added, with an initial uncertainty according to insertionOptions   CObservationStereoImages vlSIFT  Each image is separately procesed by the method for CObservationImage observations   CObservationStereoImages vlColor  TODO...   CObservation2DRangeScan glOccupancy  A landmark is added for each range in the scan, with its appropiate covariance matrix derived from the jacobians matrixes.   The robot's pose the observation is supposed to be taken from. The observation. This method returns a likelihood value > 0. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CLandmarksMap::internal_computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CLandmarksMap::isEmpty() const --> bool

loadSiftFeaturesFromImageObservation(...)
loadSiftFeaturesFromImageObservation(*args, **kwargs) Overloaded function. 1. loadSiftFeaturesFromImageObservation(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, obs: mrpt.pymrpt.mrpt.obs.CObservationImage) -> None 2. loadSiftFeaturesFromImageObservation(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, obs: mrpt.pymrpt.mrpt.obs.CObservationImage, feat_options: mrpt.pymrpt.mrpt.vision.CFeatureExtraction.TOptions) -> None Loads into this landmarks map the SIFT features extracted from an image observation (Previous contents of map will be erased)   The robot is assumed to be at the origin of the map.   Some options may be applicable from "insertionOptions" (insertionOptions.SIFTsLoadDistanceOfTheMean)    Optionally, you can pass here parameters for changing the default SIFT detector settings. C++: mrpt::maps::CLandmarksMap::loadSiftFeaturesFromImageObservation(const class mrpt::obs::CObservationImage &, const struct mrpt::vision::CFeatureExtraction::TOptions &) --> void

loadSiftFeaturesFromStereoImageObservation(...)
loadSiftFeaturesFromStereoImageObservation(*args, **kwargs) Overloaded function. 1. loadSiftFeaturesFromStereoImageObservation(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, obs: mrpt.pymrpt.mrpt.obs.CObservationStereoImages, fID: int) -> None 2. loadSiftFeaturesFromStereoImageObservation(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, obs: mrpt.pymrpt.mrpt.obs.CObservationStereoImages, fID: int, feat_options: mrpt.pymrpt.mrpt.vision.CFeatureExtraction.TOptions) -> None Loads into this landmarks map the SIFT features extracted from an observation consisting of a pair of stereo-image (Previous contents of map will be erased)   The robot is assumed to be at the origin of the map.   Some options may be applicable from "insertionOptions"    Optionally, you can pass here parameters for changing the default SIFT detector settings. C++: mrpt::maps::CLandmarksMap::loadSiftFeaturesFromStereoImageObservation(const class mrpt::obs::CObservationStereoImages &, long, const struct mrpt::vision::CFeatureExtraction::TOptions &) --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface).   In the case of this class, these files are generated:                 - "filNamePrefix"+"_3D.m": A script for MATLAB for drawing landmarks as 3D ellipses.                 - "filNamePrefix"+"_3D.3DScene": A 3D scene with a "ground plane grid" and the set of ellipsoids in 3D. C++: mrpt::maps::CLandmarksMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

saveToMATLABScript2D(...)
saveToMATLABScript2D(*args, **kwargs) Overloaded function. 1. saveToMATLABScript2D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, file: str) -> bool 2. saveToMATLABScript2D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, file: str, style: str) -> bool 3. saveToMATLABScript2D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, file: str, style: str, stdCount: float) -> bool Save to a MATLAB script which displays 2D error ellipses for the map (top-view, projection on the XY plane).                          The name of the file to save the script to.            The MATLAB-like string for the style of the lines (see 'help plot' in MATLAB for possibilities)    The ellipsoids will be drawn from the center to "stdCount" times the "standard deviations". (default is 2std = 95% confidence intervals)    Returns false if any error occured, true elsewere. C++: mrpt::maps::CLandmarksMap::saveToMATLABScript2D(std::string, const char *, float) --> bool

saveToMATLABScript3D(...)
saveToMATLABScript3D(*args, **kwargs) Overloaded function. 1. saveToMATLABScript3D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, file: str) -> bool 2. saveToMATLABScript3D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, file: str, style: str) -> bool 3. saveToMATLABScript3D(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, file: str, style: str, confInterval: float) -> bool Save to a MATLAB script which displays 3D error ellipses for the map.                          The name of the file to save the script to.            The MATLAB-like string for the style of the lines (see 'help plot' in MATLAB for possibilities)    The ellipsoids will be drawn from the center to a given confidence interval in [0,1], e.g. 2 sigmas=0.95 (default is 2std = 0.95 confidence intervals)    Returns false if any error occured, true elsewere. C++: mrpt::maps::CLandmarksMap::saveToMATLABScript3D(std::string, const char *, float) const --> bool

saveToTextFile(...)
saveToTextFile(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, file: str) -> bool Save to a text file.   In line "i" there are the (x,y,z) mean values of the i'th landmark + type of landmark + # times seen + timestamp + RGB/descriptor + ID    Returns false if any error occured, true elsewere. C++: mrpt::maps::CLandmarksMap::saveToTextFile(std::string) --> bool

simulateBeaconReadings(...)
simulateBeaconReadings(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap, in_robotPose: mrpt.pymrpt.mrpt.poses.CPose3D, in_sensorLocationOnRobot: mrpt.pymrpt.mrpt.poses.CPoint3D, out_Observations: mrpt.pymrpt.mrpt.obs.CObservationBeaconRanges) -> None Simulates a noisy reading toward each of the beacons in the landmarks map, if any. This robot pose is used to simulate the ranges to each beacon. The 3D position of the sensor on the robot The results will be stored here. NOTICE that the fields "CObservationBeaconRanges::minSensorDistance","CObservationBeaconRanges::maxSensorDistance" and "CObservationBeaconRanges::stdError" MUST BE FILLED OUT before calling this function. An observation will be generated for each beacon in the map, but notice that some of them may be missed if out of the sensor maximum range. C++: mrpt::maps::CLandmarksMap::simulateBeaconReadings(const class mrpt::poses::CPose3D &, const class mrpt::poses::CPoint3D &, class mrpt::obs::CObservationBeaconRanges &) const --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.CLandmarksMap) -> int Returns the stored landmarks count. C++: mrpt::maps::CLandmarksMap::size() const --> size_t

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CLandmarksMap::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CLandmarksMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

fuseOptions

insertionOptions

insertionResults

landmarks

likelihoodOptions

Data and other attributes defined here:

TCustomSequenceLandmarks = <class 'mrpt.pymrpt.mrpt.maps.CLandmarksMap.TCustomSequenceLandmarks'>
The list of landmarks: the wrapper class is just for maintaining the KD-Tree representation

TFuseOptions = <class 'mrpt.pymrpt.mrpt.maps.CLandmarksMap.TFuseOptions'>
With this struct options are provided to the fusion process.

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CLandmarksMap.TInsertionOptions'>
With this struct options are provided to the observation insertion process.

TInsertionResults = <class 'mrpt.pymrpt.mrpt.maps.CLandmarksMap.TInsertionResults'>
This struct stores extra results from invoking insertObservation

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.CLandmarksMap.TLikelihoodOptions'>
With this struct options are provided to the likelihood computations.

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CLandmarksMap.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CLandmarksMap.TMapDefinitionBase'>

Methods inherited from CMetricMap:

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CLogOddsGridMap2D_signed_char_t(pybind11_builtins.pybind11_object)


Method resolution order:

CLogOddsGridMap2D_signed_char_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t, arg0: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t, : mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t) -> mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t C++: mrpt::maps::CLogOddsGridMap2D<signed char>::operator=(const struct mrpt::maps::CLogOddsGridMap2D<signed char> &) --> struct mrpt::maps::CLogOddsGridMap2D<signed char> &

updateCell_fast_occupied(...)
updateCell_fast_occupied(*args, **kwargs) Overloaded function. 1. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t, x: int, y: int, logodd_obs: int, thres: int, mapArray: int, _size_x: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_occupied(const unsigned int, const unsigned int, const signed char, const signed char, signed char *, const unsigned int) --> void 2. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t, theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_occupied(signed char *, const signed char, const signed char) --> void

Static methods defined here:

updateCell_fast_free(...) from builtins.PyCapsule
updateCell_fast_free(*args, **kwargs) Overloaded function. 1. updateCell_fast_free(x: int, y: int, logodd_obs: int, thres: int, mapArray: int, _size_x: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_free(const unsigned int, const unsigned int, const signed char, const signed char, signed char *, const unsigned int) --> void 2. updateCell_fast_free(theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_free(signed char *, const signed char, const signed char) --> void

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CLogOddsGridMap3D_signed_char_t(pybind11_builtins.pybind11_object)


Method resolution order:

CLogOddsGridMap3D_signed_char_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t, : mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t) -> mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t C++: mrpt::maps::CLogOddsGridMap3D<signed char>::operator=(const struct mrpt::maps::CLogOddsGridMap3D<signed char> &) --> struct mrpt::maps::CLogOddsGridMap3D<signed char> &

updateCell_fast_free(...)
updateCell_fast_free(*args, **kwargs) Overloaded function. 1. updateCell_fast_free(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t, theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap3D<signed char>::updateCell_fast_free(signed char *, const signed char, const signed char) --> void 2. updateCell_fast_free(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t, x: int, y: int, z: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap3D<signed char>::updateCell_fast_free(const unsigned int, const unsigned int, const unsigned int, const signed char, const signed char) --> void

updateCell_fast_occupied(...)
updateCell_fast_occupied(*args, **kwargs) Overloaded function. 1. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t, theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap3D<signed char>::updateCell_fast_occupied(signed char *, const signed char, const signed char) --> void 2. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t, x: int, y: int, z: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap3D<signed char>::updateCell_fast_occupied(const unsigned int, const unsigned int, const unsigned int, const signed char, const signed char) --> void

Data descriptors defined here:

m_grid

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CLogOddsGridMapLUT_signed_char_t(pybind11_builtins.pybind11_object)


Method resolution order:

CLogOddsGridMapLUT_signed_char_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMapLUT_signed_char_t) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMapLUT_signed_char_t, arg0: mrpt.pymrpt.mrpt.maps.CLogOddsGridMapLUT_signed_char_t) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMapLUT_signed_char_t, : mrpt.pymrpt.mrpt.maps.CLogOddsGridMapLUT_signed_char_t) -> mrpt.pymrpt.mrpt.maps.CLogOddsGridMapLUT_signed_char_t C++: mrpt::maps::CLogOddsGridMapLUT<signed char>::operator=(const struct mrpt::maps::CLogOddsGridMapLUT<signed char> &) --> struct mrpt::maps::CLogOddsGridMapLUT<signed char> &

l2p(...)
l2p(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMapLUT_signed_char_t, l: int) -> float C++: mrpt::maps::CLogOddsGridMapLUT<signed char>::l2p(const signed char) --> float

l2p_255(...)
l2p_255(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMapLUT_signed_char_t, l: int) -> int C++: mrpt::maps::CLogOddsGridMapLUT<signed char>::l2p_255(const signed char) --> uint8_t

p2l(...)
p2l(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMapLUT_signed_char_t, p: float) -> int C++: mrpt::maps::CLogOddsGridMapLUT<signed char>::p2l(const float) --> signed char

Data descriptors defined here:

logoddsTable

logoddsTable_255

p2lTable

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CMetricMap(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.system.CObservable, mrpt.pymrpt.mrpt.Stringifyable, mrpt.pymrpt.mrpt.opengl.Visualizable)

    Declares a virtual base class for all metric maps storage classes.   In this class virtual methods are provided to allow the insertion   of any type of "CObservation" objects into the metric map, thus   updating the map (doesn't matter if it is a 2D/3D grid, a point map, etc.).   Observations don't include any information about the   robot pose, just the raw observation and information about   the sensor pose relative to the robot mobile base coordinates origin.   Note that all metric maps implement this mrpt::system::CObservable interface,    emitting the following events:           - mrpt::obs::mrptEventMetricMapClear: Upon call of the ::clear() method.     - mrpt::obs::mrptEventMetricMapInsert: Upon insertion of an observation that effectively modifies the map (e.g. inserting an image into a grid map will NOT raise an event, inserting a laser scan will). To check what observations are supported by each metric map, see All derived class must implement a static class factory `<metric_map_class>::MapDefinition()` that builds a default TMetricMapInitializer CObservation, CSensoryFrame, CMultiMetricMap

Method resolution order:

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMetricMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(self, /, *args, **kwargs)
Initialize self.  See help(type(self)) for accurate signature.

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CMetricMap, : mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt.pymrpt.mrpt.maps.CMetricMap C++: mrpt::maps::CMetricMap::operator=(const class mrpt::maps::CMetricMap &) --> class mrpt::maps::CMetricMap &

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float Computes the ratio in [0,1] of correspondences between "this" and the "otherMap" map, whose 6D pose relative to "this" is "otherMapPose"    In the case of a multi-metric map, this returns the average between the maps. This method always return 0 for grid maps.       [IN] The other map to compute the matching with.   [IN] The 6D pose of the other map as seen from "this".         [IN] Matching parameters The matching ratio [0,1] determineMatching2D C++: mrpt::maps::CMetricMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CMetricMap::isEmpty() const --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CMetricMap, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface). C++: mrpt::maps::CMetricMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Static methods defined here:

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMetricMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

clone(...)
clone(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Returns a deep copy (clone) of the object, indepently of its class. C++: mrpt::rtti::CObject::clone() const --> class mrpt::rtti::CObject *

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.Stringifyable:

asString(...)
asString(self: mrpt.pymrpt.mrpt.Stringifyable) -> str Returns a human-friendly textual description of the object. For classes with a large/complex internal state, only a summary should be returned instead of the exhaustive enumeration of all data members. C++: mrpt::Stringifyable::asString() const --> std::string

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.opengl.Visualizable, o: mrpt::opengl::CSetOfObjects) -> None Inserts 3D primitives representing this object into the provided container. Note that the former contents of `o` are not cleared. getVisualization() C++: mrpt::opengl::Visualizable::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CMultiMetricMap(CMetricMap)

    This class stores any customizable set of metric maps. The internal metric maps can be accessed directly by the user as smart pointers with CMultiMetricMap::mapByIndex() or via `iterator`s. The utility of this container is to operate on several maps simultaneously: update them by inserting observations, evaluate the likelihood of one observation by fusing (multiplying) the likelihoods over the different maps, etc. These kinds of metric maps can be kept inside (list may be incomplete, refer to classes derived from mrpt::maps::CMetricMap):         - mrpt::maps::CSimplePointsMap: For 2D or 3D range scans, ...         - mrpt::maps::COccupancyGridMap2D: 2D, horizontal  laser range     scans, at different altitudes.         - mrpt::maps::COccupancyGridMap3D: 3D occupancy voxel map.         - mrpt::maps::COctoMap: For 3D occupancy grids of variable resolution,     with octrees (based on the library `octomap`).         - mrpt::maps::CColouredOctoMap: The same than above, but nodes can store     RGB data appart from occupancy.         - mrpt::maps::CLandmarksMap: For visual landmarks,etc...         - mrpt::maps::CGasConcentrationGridMap2D: For gas concentration maps.         - mrpt::maps::CWirelessPowerGridMap2D: For wifi power maps.         - mrpt::maps::CBeaconMap: For range-only SLAM.         - mrpt::maps::CHeightGridMap2D: For elevation maps of height for each     (x,y) location (Digital elevation model, DEM)         - mrpt::maps::CHeightGridMap2D_MRF: DEMs as Markov Random Field (MRF)         - mrpt::maps::CReflectivityGridMap2D: For maps of "reflectivity" for     each (x,y) location.         - mrpt::maps::CColouredPointsMap: For point map with color.         - mrpt::maps::CWeightedPointsMap: For point map with weights (capable of     "fusing"). See CMultiMetricMap::setListOfMaps() for the method for initializing this class programmatically. See also TSetOfMetricMapInitializers::loadFromConfigFile for a template of ".ini"-like configuration file that can be used to define which maps to create and all their parameters. Alternatively, the list of maps is public so it can be directly manipulated/accessed in CMultiMetricMap::maps   Configuring the list of maps: Alternatives --------------------------------------------   **Method #1: Using map definition structures**   **Method #2: Using a configuration file** See TSetOfMetricMapInitializers::loadFromConfigFile() for details on expected file format.   **Method #3: Manual manipulation** [New in MRPT 1.3.0]: `likelihoodMapSelection`, which selected the map to be used when   computing the likelihood of an observation, has been removed. Use the `enableObservationLikelihood`   property of each individual map declaration. [New in MRPT 1.3.0]: `enableInsertion_{pointsMap,...}` have been also removed.   Use the `enableObservationInsertion` property of each map declaration. This class belongs to [mrpt-slam] instead of [mrpt-maps] due to the dependency on map classes in mrpt-vision. CMetricMap

Method resolution order:

CMultiMetricMap

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMultiMetricMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, initializers: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, arg0: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> None 4. __init__(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, arg0: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> None

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> str Returns a short description of the map. C++: mrpt::maps::CMultiMetricMap::asString() const --> std::string

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, o: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> mrpt.pymrpt.mrpt.maps.CMultiMetricMap Creates a deep copy C++: mrpt::maps::CMultiMetricMap::operator=(const class mrpt::maps::CMultiMetricMap &) --> class mrpt::maps::CMultiMetricMap &

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> None C++: mrpt::maps::CMultiMetricMap::auxParticleFilterCleanUp() --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CMultiMetricMap::clone() const --> class mrpt::rtti::CObject *

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float C++: mrpt::maps::CMultiMetricMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CMultiMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMultiMetricMap::getAsSimplePointsMap() const --> const class mrpt::maps::CSimplePointsMap *

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, outObj: mrpt::opengl::CSetOfObjects) -> None C++: mrpt::maps::CMultiMetricMap::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap) -> bool Returns true if **all** maps returns true in their isEmpty() method C++: mrpt::maps::CMultiMetricMap::isEmpty() const --> bool

mapByIndex(...)
mapByIndex(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, idx: int) -> mrpt.pymrpt.mrpt.maps.CMetricMap Gets the i-th map std::runtime_error On out-of-bounds C++: mrpt::maps::CMultiMetricMap::mapByIndex(size_t) const --> class std::shared_ptr<class mrpt::maps::CMetricMap>

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, filNamePrefix: str) -> None C++: mrpt::maps::CMultiMetricMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

setListOfMaps(...)
setListOfMaps(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMap, init: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers) -> None Sets the list of internal map according to the passed list of map initializers (current maps will be deleted) C++: mrpt::maps::CMultiMetricMap::setListOfMaps(const class mrpt::maps::TSetOfMetricMapInitializers &) --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CMultiMetricMap::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMultiMetricMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

maps

Methods inherited from CMetricMap:

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CMultiMetricMapPDF(mrpt.pymrpt.mrpt.serialization.CSerializable, mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, mrpt.pymrpt.mrpt.slam.PF_implementation_mrpt_maps_CRBPFParticleData_mrpt_maps_CMultiMetricMapPDF_mrpt_bayes_particle_storage_mode_POINTER_t)

    Declares a class that represents a Rao-Blackwellized set of particles for solving the SLAM problem (This class is the base of RBPF-SLAM applications).   This class is used internally by the map building algorithm in "mrpt::slam::CMetricMapBuilderRBPF" mrpt::slam::CMetricMapBuilderRBPF

Method resolution order:

CMultiMetricMapPDF

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t

mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t

mrpt.pymrpt.mrpt.bayes.CParticleFilterCapable

mrpt.pymrpt.mrpt.slam.PF_implementation_mrpt_maps_CRBPFParticleData_mrpt_maps_CMultiMetricMapPDF_mrpt_bayes_particle_storage_mode_POINTER_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMultiMetricMapPDF::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

PF_SLAM_computeObservationLikelihoodForParticle(...)
PF_SLAM_computeObservationLikelihoodForParticle(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, PF_options: mrpt.pymrpt.mrpt.bayes.CParticleFilter.TParticleFilterOptions, particleIndexForMap: int, observation: mrpt.pymrpt.mrpt.obs.CSensoryFrame, x: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Evaluate the observation likelihood for one particle at a given location C++: mrpt::maps::CMultiMetricMapPDF::PF_SLAM_computeObservationLikelihoodForParticle(const struct mrpt::bayes::CParticleFilter::TParticleFilterOptions &, size_t, const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) const --> double

PF_SLAM_implementation_custom_update_particle_with_new_pose(...)
PF_SLAM_implementation_custom_update_particle_with_new_pose(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, particleData: mrpt.pymrpt.mrpt.maps.CRBPFParticleData, newPose: mrpt.pymrpt.mrpt.math.TPose3D) -> None C++: mrpt::maps::CMultiMetricMapPDF::PF_SLAM_implementation_custom_update_particle_with_new_pose(class mrpt::maps::CRBPFParticleData *, const struct mrpt::math::TPose3D &) const --> void

PF_SLAM_implementation_doWeHaveValidObservations(...)
PF_SLAM_implementation_doWeHaveValidObservations(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, particles: List[mrpt::bayes::CProbabilityParticle<mrpt::maps::CRBPFParticleData, (mrpt::bayes::particle_storage_mode)1>], sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool C++: mrpt::maps::CMultiMetricMapPDF::PF_SLAM_implementation_doWeHaveValidObservations(const class std::deque<struct mrpt::bayes::CProbabilityParticle<class mrpt::maps::CRBPFParticleData, mrpt::bayes::particle_storage_mode::POINTER> > &, const class mrpt::obs::CSensoryFrame *) const --> bool

PF_SLAM_implementation_skipRobotMovement(...)
PF_SLAM_implementation_skipRobotMovement(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> bool C++: mrpt::maps::CMultiMetricMapPDF::PF_SLAM_implementation_skipRobotMovement() const --> bool

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, opts: mrpt.pymrpt.mrpt.bayes.CParticleFilter.TParticleFilterOptions, mapsInitializers: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers, predictionOptions: mrpt::maps::CMultiMetricMapPDF::TPredictionParams) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, arg0: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> None 4. __init__(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, arg0: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, : mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF C++: mrpt::maps::CMultiMetricMapPDF::operator=(const class mrpt::maps::CMultiMetricMapPDF &) --> class mrpt::maps::CMultiMetricMapPDF &

clear(...)
clear(*args, **kwargs) Overloaded function. 1. clear(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, initialPose: mrpt.pymrpt.mrpt.poses.CPose2D) -> None Clear all elements of the maps, and restore all paths to a single starting pose C++: mrpt::maps::CMultiMetricMapPDF::clear(const class mrpt::poses::CPose2D &) --> void 2. clear(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, initialPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> None C++: mrpt::maps::CMultiMetricMapPDF::clear(const class mrpt::poses::CPose3D &) --> void 3. clear(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, prevMap: mrpt.pymrpt.mrpt.maps.CSimpleMap, currentPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Resets the map by loading an already-mapped map for past poses. Current robot pose should be normally set to the last keyframe in the simplemap. C++: mrpt::maps::CMultiMetricMapPDF::clear(const class mrpt::maps::CSimpleMap &, const class mrpt::poses::CPose3D &) --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CMultiMetricMapPDF::clone() const --> class mrpt::rtti::CObject *

getAveragedMetricMapEstimation(...)
getAveragedMetricMapEstimation(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> mrpt.pymrpt.mrpt.maps.CMultiMetricMap Returns the weighted averaged map based on the current best estimation. If you need a persistent copy of this object, please use "CSerializable::duplicate" and use the copy. Almost 100% sure you would prefer the best current map, given by getCurrentMostLikelyMetricMap() C++: mrpt::maps::CMultiMetricMapPDF::getAveragedMetricMapEstimation() --> const class mrpt::maps::CMultiMetricMap *

getCurrentEntropyOfPaths(...)
getCurrentEntropyOfPaths(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> float Returns the current entropy of paths, computed as the average entropy of poses along the path, where entropy of each pose estimation is computed as the entropy of the gaussian approximation covariance. C++: mrpt::maps::CMultiMetricMapPDF::getCurrentEntropyOfPaths() --> double

getCurrentJointEntropy(...)
getCurrentJointEntropy(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> float Returns the joint entropy estimation over paths and maps, acording to "Information Gain-based Exploration Using" by C. Stachniss, G. Grissetti and W.Burgard. C++: mrpt::maps::CMultiMetricMapPDF::getCurrentJointEntropy() --> double

getCurrentMostLikelyMetricMap(...)
getCurrentMostLikelyMetricMap(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> mrpt.pymrpt.mrpt.maps.CMultiMetricMap Returns a pointer to the current most likely map (associated to the most likely particle) C++: mrpt::maps::CMultiMetricMapPDF::getCurrentMostLikelyMetricMap() const --> const class mrpt::maps::CMultiMetricMap *

getEstimatedPosePDF(...)
getEstimatedPosePDF(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, out_estimation: mrpt.pymrpt.mrpt.poses.CPose3DPDFParticles) -> None Returns the current estimate of the robot pose, as a particles PDF. getEstimatedPosePDFAtTime C++: mrpt::maps::CMultiMetricMapPDF::getEstimatedPosePDF(class mrpt::poses::CPose3DPDFParticles &) const --> void

getEstimatedPosePDFAtTime(...)
getEstimatedPosePDFAtTime(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, timeStep: int, out_estimation: mrpt.pymrpt.mrpt.poses.CPose3DPDFParticles) -> None Returns the estimate of the robot pose as a particles PDF for the instant of time "timeStep", from 0 to N-1. getEstimatedPosePDF C++: mrpt::maps::CMultiMetricMapPDF::getEstimatedPosePDFAtTime(size_t, class mrpt::poses::CPose3DPDFParticles &) const --> void

getLastPose(...)
getLastPose(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, i: int, pose_is_valid: bool) -> mrpt.pymrpt.mrpt.math.TPose3D                 @{ C++: mrpt::maps::CMultiMetricMapPDF::getLastPose(size_t, bool &) const --> struct mrpt::math::TPose3D

getNumberOfObservationsInSimplemap(...)
getNumberOfObservationsInSimplemap(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> int Get the number of CSensoryFrame inserted into the internal member SFs C++: mrpt::maps::CMultiMetricMapPDF::getNumberOfObservationsInSimplemap() const --> size_t

getPath(...)
getPath(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, i: int, out_path: List[mrpt.pymrpt.mrpt.math.TPose3D]) -> None Return the path (in absolute coordinate poses) for the i'th particle. On index out of bounds C++: mrpt::maps::CMultiMetricMapPDF::getPath(size_t, class std::deque<struct mrpt::math::TPose3D> &) const --> void

insertObservation(...)
insertObservation(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool Insert an observation to the map, at each particle's pose and to each particle's metric map. The SF to be inserted true if any may was updated, false otherwise C++: mrpt::maps::CMultiMetricMapPDF::insertObservation(class mrpt::obs::CSensoryFrame &) --> bool

saveCurrentPathEstimationToTextFile(...)
saveCurrentPathEstimationToTextFile(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF, fil: str) -> None A logging utility: saves the current path estimation for each particle in a text file (a row per particle, each 3-column-entry is a set [x,y,phi], respectively). C++: mrpt::maps::CMultiMetricMapPDF::saveCurrentPathEstimationToTextFile(const std::string &) --> void

updateSensoryFrameSequence(...)
updateSensoryFrameSequence(self: mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF) -> None Update the poses estimation of the member "SFs" according to the current path belief. C++: mrpt::maps::CMultiMetricMapPDF::updateSensoryFrameSequence() --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CMultiMetricMapPDF::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMultiMetricMapPDF::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

options

Data and other attributes defined here:

TPredictionParams = <class 'mrpt.pymrpt.mrpt.maps.CMultiMetricMapPDF.TPredictionParams'>
The struct for passing extra simulation parameters to the prediction/update stage    when running a particle filter. prediction_and_update

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t:

clearParticles(...)
clearParticles(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t) -> None C++: mrpt::bayes::CParticleFilterData<mrpt::maps::CRBPFParticleData, mrpt::bayes::particle_storage_mode::POINTER>::clearParticles() --> void

Data descriptors inherited from mrpt.pymrpt.mrpt.bayes.CParticleFilterData_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t:

m_particles

Methods inherited from mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t:

ESS(...)
ESS(*args, **kwargs) Overloaded function. 1. ESS(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t) -> float C++: mrpt::bayes::CParticleFilterDataImpl<mrpt::maps::CMultiMetricMapPDF, std::deque<mrpt::bayes::CProbabilityParticle<mrpt::maps::CRBPFParticleData, mrpt::bayes::particle_storage_mode::POINTER>>>::ESS() const --> double 2. ESS(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t) -> float Returns the normalized ESS (Estimated Sample Size), in the range [0,1].   Note that you do NOT need to normalize the weights before calling this. C++: mrpt::bayes::CParticleFilterCapable::ESS() const --> double

derived(...)
derived(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t) -> mrpt::maps::CMultiMetricMapPDF C++: mrpt::bayes::CParticleFilterDataImpl<mrpt::maps::CMultiMetricMapPDF, std::deque<mrpt::bayes::CProbabilityParticle<mrpt::maps::CRBPFParticleData, mrpt::bayes::particle_storage_mode::POINTER>>>::derived() --> class mrpt::maps::CMultiMetricMapPDF &

fastDrawSample(...)
fastDrawSample(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, PF_options: mrpt.pymrpt.mrpt.bayes.CParticleFilter.TParticleFilterOptions) -> int Draws a random sample from the particle filter, in such a way that each particle has a probability proportional to its weight (in the standard PF algorithm).    This method can be used to generate a variable number of m_particles when resampling: to vary the number of m_particles in the filter.    See prepareFastDrawSample for more information, or the *href="http://www.mrpt.org/Particle_Filters" >Particle Filter tutorial. NOTES:                 - You MUST call "prepareFastDrawSample" ONCE before calling this method. That method must be called after modifying the particle filter (executing one step, resampling, etc...)                 - This method returns ONE index for the selected ("drawn") particle, in the range [0,M-1]                 - You do not need to call "normalizeWeights" before calling this. prepareFastDrawSample C++: mrpt::bayes::CParticleFilterCapable::fastDrawSample(const struct mrpt::bayes::CParticleFilter::TParticleFilterOptions &) const --> size_t

getW(...)
getW(*args, **kwargs) Overloaded function. 1. getW(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, i: int) -> float C++: mrpt::bayes::CParticleFilterDataImpl<mrpt::maps::CMultiMetricMapPDF, std::deque<mrpt::bayes::CProbabilityParticle<mrpt::maps::CRBPFParticleData, mrpt::bayes::particle_storage_mode::POINTER>>>::getW(size_t) const --> double 2. getW(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, i: int) -> float Access to i'th particle (logarithm) weight, where first one is index 0. C++: mrpt::bayes::CParticleFilterCapable::getW(size_t) const --> double

normalizeWeights(...)
normalizeWeights(*args, **kwargs) Overloaded function. 1. normalizeWeights(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t) -> float 2. normalizeWeights(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, out_max_log_w: float) -> float C++: mrpt::bayes::CParticleFilterDataImpl<mrpt::maps::CMultiMetricMapPDF, std::deque<mrpt::bayes::CProbabilityParticle<mrpt::maps::CRBPFParticleData, mrpt::bayes::particle_storage_mode::POINTER>>>::normalizeWeights(double *) --> double 3. normalizeWeights(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterCapable) -> float 4. normalizeWeights(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, out_max_log_w: float) -> float Normalize the (logarithmic) weights, such as the maximum weight is zero. If provided, will return with the maximum log_w before normalizing, such as new_weights = old_weights - max_log_w. The max/min ratio of weights ("dynamic range") C++: mrpt::bayes::CParticleFilterCapable::normalizeWeights(double *) --> double

particlesCount(...)
particlesCount(*args, **kwargs) Overloaded function. 1. particlesCount(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t) -> int C++: mrpt::bayes::CParticleFilterDataImpl<mrpt::maps::CMultiMetricMapPDF, std::deque<mrpt::bayes::CProbabilityParticle<mrpt::maps::CRBPFParticleData, mrpt::bayes::particle_storage_mode::POINTER>>>::particlesCount() const --> size_t 2. particlesCount(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t) -> int Get the m_particles count. C++: mrpt::bayes::CParticleFilterCapable::particlesCount() const --> size_t

performResampling(...)
performResampling(*args, **kwargs) Overloaded function. 1. performResampling(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterCapable, PF_options: mrpt.pymrpt.mrpt.bayes.CParticleFilter.TParticleFilterOptions) -> None 2. performResampling(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, PF_options: mrpt.pymrpt.mrpt.bayes.CParticleFilter.TParticleFilterOptions, out_particle_count: int) -> None Performs a resample of the m_particles, using the method selected in the constructor. After computing the surviving samples, this method internally calls "performSubstitution" to actually perform the particle replacement. This method is called automatically by CParticleFilter::execute, andshould not be invoked manually normally. To just obtaining the sequence of resampled indexes from a sequence of weights, use "resample" The desired number of output particles after resampling; 0 means don't modify the current number. resample C++: mrpt::bayes::CParticleFilterCapable::performResampling(const struct mrpt::bayes::CParticleFilter::TParticleFilterOptions &, size_t) --> void

prediction_and_update(...)
prediction_and_update(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, action: mrpt.pymrpt.mrpt.obs.CActionCollection, observation: mrpt.pymrpt.mrpt.obs.CSensoryFrame, PF_options: mrpt.pymrpt.mrpt.bayes.CParticleFilter.TParticleFilterOptions) -> None Performs the prediction stage of the Particle Filter.   This method simply selects the appropiate protected method according to the particle filter algorithm to run. prediction_and_update_pfStandardProposal,prediction_and_update_pfAuxiliaryPFStandard,prediction_and_update_pfOptimalProposal,prediction_and_update_pfAuxiliaryPFOptimal C++: mrpt::bayes::CParticleFilterCapable::prediction_and_update(const class mrpt::obs::CActionCollection *, const class mrpt::obs::CSensoryFrame *, const struct mrpt::bayes::CParticleFilter::TParticleFilterOptions &) --> void

setW(...)
setW(*args, **kwargs) Overloaded function. 1. setW(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, i: int, w: float) -> None C++: mrpt::bayes::CParticleFilterDataImpl<mrpt::maps::CMultiMetricMapPDF, std::deque<mrpt::bayes::CProbabilityParticle<mrpt::maps::CRBPFParticleData, mrpt::bayes::particle_storage_mode::POINTER>>>::setW(size_t, double) --> void 2. setW(self: mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t, i: int, w: float) -> None Modifies i'th particle (logarithm) weight, where first one is index 0. C++: mrpt::bayes::CParticleFilterCapable::setW(size_t, double) --> void

Static methods inherited from mrpt.pymrpt.mrpt.bayes.CParticleFilterDataImpl_mrpt_maps_CMultiMetricMapPDF_std_deque_mrpt_bayes_CProbabilityParticle_mrpt_maps_CRBPFParticleData_mrpt_bayes_particle_storage_mode_POINTER_t:

defaultEvaluator(...) from builtins.PyCapsule
defaultEvaluator(PF_options: mrpt.pymrpt.mrpt.bayes.CParticleFilter.TParticleFilterOptions, obj: mrpt.pymrpt.mrpt.bayes.CParticleFilterCapable, index: int, action: capsule, observation: capsule) -> float The default evaluator function, which simply returns the particle weight.   The action and the observation are declared as "void*" for a greater flexibility. prepareFastDrawSample C++: mrpt::bayes::CParticleFilterCapable::defaultEvaluator(const struct mrpt::bayes::CParticleFilter::TParticleFilterOptions &, const class mrpt::bayes::CParticleFilterCapable *, size_t, const void *, const void *) --> double

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class COccupancyGridMap2D(CMetricMap, CLogOddsGridMap2D_signed_char_t)

    A class for storing an occupancy grid map.   COccupancyGridMap2D is a class for storing a metric map    representation in the form of a probabilistic occupancy    grid map: value of 0 means certainly occupied, 1 means    a certainly empty cell. Initially 0.5 means uncertainty. The cells keep the log-odd representation of probabilities instead of the probabilities themselves.   More details can be found at https://www.mrpt.org/Occupancy_Grids The algorithm for updating the grid from a laser scanner can optionally take into account the progressive widening of the beams, as    described in [this page](http://www.mrpt.org/Occupancy_Grids)    Some implemented methods are:                 - Update of individual cells                 - Insertion of observations                 - Voronoi diagram and critical points (                 - Saving and loading from/to a bitmap                 - Laser scans simulation for the map contents                 - Entropy and information methods (See computeEntropy)

Method resolution order:

COccupancyGridMap2D

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

CLogOddsGridMap2D_signed_char_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::COccupancyGridMap2D::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, arg0: float) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, arg0: float, arg1: float) -> None doc 4. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, arg0: float, arg1: float, arg2: float) -> None doc 5. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, arg0: float, arg1: float, arg2: float, arg3: float) -> None doc 6. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, min_x: float, max_x: float, min_y: float, max_y: float, resolution: float) -> None 7. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> None 8. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> None

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> str Returns a short description of the map. C++: mrpt::maps::COccupancyGridMap2D::asString() const --> std::string

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, : mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D C++: mrpt::maps::COccupancyGridMap2D::operator=(const class mrpt::maps::COccupancyGridMap2D &) --> class mrpt::maps::COccupancyGridMap2D &

buildVoronoiDiagram(...)
buildVoronoiDiagram(*args, **kwargs) Overloaded function. 1. buildVoronoiDiagram(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, threshold: float, robot_size: float) -> None 2. buildVoronoiDiagram(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, threshold: float, robot_size: float, x1: int) -> None 3. buildVoronoiDiagram(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, threshold: float, robot_size: float, x1: int, x2: int) -> None 4. buildVoronoiDiagram(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, threshold: float, robot_size: float, x1: int, x2: int, y1: int) -> None 5. buildVoronoiDiagram(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, threshold: float, robot_size: float, x1: int, x2: int, y1: int, y2: int) -> None Build the Voronoi diagram of the grid map. The threshold for binarizing the map. Size in "units" (meters) of robot, approx. Left coordinate of area to be computed. Default, entire map. Right coordinate of area to be computed. Default, entire map. Top coordinate of area to be computed. Default, entire map. Bottom coordinate of area to be computed. Default, entire map. findCriticalPoints C++: mrpt::maps::COccupancyGridMap2D::buildVoronoiDiagram(float, float, int, int, int, int) --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::COccupancyGridMap2D::clone() const --> class mrpt::rtti::CObject *

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float See docs in base class: in this class this always returns 0 C++: mrpt::maps::COccupancyGridMap2D::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

computeClearance(...)
computeClearance(*args, **kwargs) Overloaded function. 1. computeClearance(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, cx: int, cy: int, basis_x: int, basis_y: int, nBasis: int) -> int 2. computeClearance(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, cx: int, cy: int, basis_x: int, basis_y: int, nBasis: int, GetContourPoint: bool) -> int Compute the clearance of a given cell, and returns its two first    basis (closest obstacle) points.Used to build Voronoi and critical points. The clearance of the cell, in 1/100 of "cell". The cell index The cell index Target buffer for coordinates of basis, having a size of two "ints". Target buffer for coordinates of basis, having a size of two "ints". The number of found basis: Can be 0,1 or 2. If "true" the basis are not returned, but the closest free cells.Default at false. Build_VoronoiDiagram C++: mrpt::maps::COccupancyGridMap2D::computeClearance(int, int, int *, int *, int *, bool) const --> int 3. computeClearance(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, y: float, maxSearchDistance: float) -> float An alternative method for computing the clearance of a given location (in meters).    The clearance (distance to closest OCCUPIED cell), in meters. C++: mrpt::maps::COccupancyGridMap2D::computeClearance(float, float, float) const --> float

computeEntropy(...)
computeEntropy(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, info: mrpt::maps::COccupancyGridMap2D::TEntropyInfo) -> None Computes the entropy and related values of this grid map.   The entropy is computed as the summed entropy of each cell, taking them as discrete random variables following a Bernoulli distribution: The output information is returned here C++: mrpt::maps::COccupancyGridMap2D::computeEntropy(struct mrpt::maps::COccupancyGridMap2D::TEntropyInfo &) const --> void

computeLikelihoodField_II(...)
computeLikelihoodField_II(*args, **kwargs) Overloaded function. 1. computeLikelihoodField_II(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, pm: mrpt.pymrpt.mrpt.maps.CPointsMap) -> float 2. computeLikelihoodField_II(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, pm: mrpt.pymrpt.mrpt.maps.CPointsMap, relativePose: mrpt.pymrpt.mrpt.poses.CPose2D) -> float Computes the likelihood [0,1] of a set of points, given the current grid map as reference. The points map The relative pose of the points map in this map's coordinates, or nullptr for (0,0,0).   See "likelihoodOptions" for configuration parameters. C++: mrpt::maps::COccupancyGridMap2D::computeLikelihoodField_II(const class mrpt::maps::CPointsMap *, const class mrpt::poses::CPose2D *) const --> double

computeLikelihoodField_Thrun(...)
computeLikelihoodField_Thrun(*args, **kwargs) Overloaded function. 1. computeLikelihoodField_Thrun(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, pm: mrpt.pymrpt.mrpt.maps.CPointsMap) -> float 2. computeLikelihoodField_Thrun(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, pm: mrpt.pymrpt.mrpt.maps.CPointsMap, relativePose: mrpt.pymrpt.mrpt.poses.CPose2D) -> float Computes the likelihood [0,1] of a set of points, given the current grid map as reference. The points map The relative pose of the points map in this map's coordinates, or nullptr for (0,0,0).   See "likelihoodOptions" for configuration parameters. C++: mrpt::maps::COccupancyGridMap2D::computeLikelihoodField_Thrun(const class mrpt::maps::CPointsMap *, const class mrpt::poses::CPose2D *) const --> double

computePathCost(...)
computePathCost(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x1: float, y1: float, x2: float, y2: float) -> float Compute the 'cost' of traversing a segment of the map according to the occupancy of traversed cells.    This returns '1-mean(traversed cells occupancy)', i.e. 0.5 for unknown cells, 1 for a free path. C++: mrpt::maps::COccupancyGridMap2D::computePathCost(float, float, float, float) const --> float

copyMapContentFrom(...)
copyMapContentFrom(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, otherMap: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> None copy the gridmap contents, but not all the options, from another map instance C++: mrpt::maps::COccupancyGridMap2D::copyMapContentFrom(const class mrpt::maps::COccupancyGridMap2D &) --> void

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None See the base class for more details: In this class it is implemented as correspondences of the passed points map to occupied cells. NOTICE: That the "z" dimension is ignored in the points. Clip the points as appropiated if needed before calling this method. computeMatching3DWith C++: mrpt::maps::COccupancyGridMap2D::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

fill(...)
fill(*args, **kwargs) Overloaded function. 1. fill(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> None 2. fill(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, default_value: float) -> None Fills all the cells with a default value. C++: mrpt::maps::COccupancyGridMap2D::fill(float) --> void

findCriticalPoints(...)
findCriticalPoints(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, filter_distance: float) -> None Builds a list with the critical points from Voronoi diagram, which must     must be built before calling this method. The minimum distance between two critical points. buildVoronoiDiagram C++: mrpt::maps::COccupancyGridMap2D::findCriticalPoints(float) --> void

getArea(...)
getArea(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> float Returns the area of the gridmap, in square meters C++: mrpt::maps::COccupancyGridMap2D::getArea() const --> double

getAsImage(...)
getAsImage(*args, **kwargs) Overloaded function. 1. getAsImage(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage) -> None 2. getAsImage(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage, verticalFlip: bool) -> None 3. getAsImage(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage, verticalFlip: bool, forceRGB: bool) -> None 4. getAsImage(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage, verticalFlip: bool, forceRGB: bool, tricolor: bool) -> None Returns the grid as a 8-bit graylevel image, where each pixel is a cell (output image is RGB only if forceRGB is true)   If "tricolor" is true, only three gray levels will appear in the image: gray for unobserved cells, and black/white for occupied/empty cells respectively. getAsImageFiltered C++: mrpt::maps::COccupancyGridMap2D::getAsImage(class mrpt::img::CImage &, bool, bool, bool) const --> void

getAsImageFiltered(...)
getAsImageFiltered(*args, **kwargs) Overloaded function. 1. getAsImageFiltered(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage) -> None 2. getAsImageFiltered(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage, verticalFlip: bool) -> None 3. getAsImageFiltered(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage, verticalFlip: bool, forceRGB: bool) -> None Returns the grid as a 8-bit graylevel image, where each pixel is a cell (output image is RGB only if forceRGB is true) - This method filters the image for easy feature detection   If "tricolor" is true, only three gray levels will appear in the image: gray for unobserved cells, and black/white for occupied/empty cells respectively. getAsImage C++: mrpt::maps::COccupancyGridMap2D::getAsImageFiltered(class mrpt::img::CImage &, bool, bool) const --> void

getAsPointCloud(...)
getAsPointCloud(*args, **kwargs) Overloaded function. 1. getAsPointCloud(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, pm: mrpt::maps::CSimplePointsMap) -> None 2. getAsPointCloud(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, pm: mrpt::maps::CSimplePointsMap, occup_threshold: float) -> None Get a point cloud with all (border) occupied cells as points C++: mrpt::maps::COccupancyGridMap2D::getAsPointCloud(class mrpt::maps::CSimplePointsMap &, const float) const --> void

getBasisCell(...)
getBasisCell(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: int, y: int) -> int Reads a cell in the "basis" maps.Used for Voronoi calculation C++: mrpt::maps::COccupancyGridMap2D::getBasisCell(int, int) const --> unsigned char

getBasisMap(...)
getBasisMap(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> mrpt.pymrpt.mrpt.containers.CDynamicGrid_unsigned_char_t Return the auxiliary "basis" map built while building the Voronoi diagram buildVoronoiDiagram C++: mrpt::maps::COccupancyGridMap2D::getBasisMap() const --> const class mrpt::containers::CDynamicGrid<unsigned char> &

getCell(...)
getCell(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: int, y: int) -> float Read the real valued [0,1] contents of a cell, given its index C++: mrpt::maps::COccupancyGridMap2D::getCell(int, int) const --> float

getPos(...)
getPos(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, y: float) -> float Read the real valued [0,1] contents of a cell, given its coordinates C++: mrpt::maps::COccupancyGridMap2D::getPos(float, float) const --> float

getResolution(...)
getResolution(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> float Returns the resolution of the grid map C++: mrpt::maps::COccupancyGridMap2D::getResolution() const --> float

getRow(...)
getRow(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, cy: int) -> int Access to a "row": mainly used for drawing grid as a bitmap efficiently, do not use it normally C++: mrpt::maps::COccupancyGridMap2D::getRow(int) --> signed char *

getSizeX(...)
getSizeX(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> int Returns the horizontal size of grid map in cells count C++: mrpt::maps::COccupancyGridMap2D::getSizeX() const --> unsigned int

getSizeY(...)
getSizeY(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> int Returns the vertical size of grid map in cells count C++: mrpt::maps::COccupancyGridMap2D::getSizeY() const --> unsigned int

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns a 3D plane with its texture being the occupancy grid and transparency proportional to "uncertainty" (i.e. a value of 0.5 is fully transparent) C++: mrpt::maps::COccupancyGridMap2D::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

getVoroniClearance(...)
getVoroniClearance(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, cx: int, cy: int) -> int Reads a the clearance of a cell (in centimeters), after building the Voronoi diagram with   C++: mrpt::maps::COccupancyGridMap2D::getVoroniClearance(int, int) const --> uint16_t

getVoronoiDiagram(...)
getVoronoiDiagram(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> mrpt.pymrpt.mrpt.containers.CDynamicGrid_unsigned_short_t Return the Voronoi diagram; each cell contains the distance to its closer obstacle, or 0 if not part of the Voronoi diagram buildVoronoiDiagram C++: mrpt::maps::COccupancyGridMap2D::getVoronoiDiagram() const --> const class mrpt::containers::CDynamicGrid<unsigned short> &

getXMax(...)
getXMax(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> float Returns the "x" coordinate of right side of grid map C++: mrpt::maps::COccupancyGridMap2D::getXMax() const --> float

getXMin(...)
getXMin(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> float Returns the "x" coordinate of left side of grid map C++: mrpt::maps::COccupancyGridMap2D::getXMin() const --> float

getYMax(...)
getYMax(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> float Returns the "y" coordinate of bottom side of grid map C++: mrpt::maps::COccupancyGridMap2D::getYMax() const --> float

getYMin(...)
getYMin(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> float Returns the "y" coordinate of top side of grid map C++: mrpt::maps::COccupancyGridMap2D::getYMin() const --> float

idx2x(...)
idx2x(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, cx: int) -> float Transform a cell index into a coordinate value C++: mrpt::maps::COccupancyGridMap2D::idx2x(size_t) const --> float

idx2y(...)
idx2y(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, cy: int) -> float C++: mrpt::maps::COccupancyGridMap2D::idx2y(size_t) const --> float

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D) -> bool Returns true upon map construction or after calling clear(), the return   changes to false upon successful insertObservation() or any other method to load data in the map. C++: mrpt::maps::COccupancyGridMap2D::isEmpty() const --> bool

isStaticCell(...)
isStaticCell(*args, **kwargs) Overloaded function. 1. isStaticCell(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, cx: int, cy: int) -> bool 2. isStaticCell(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, cx: int, cy: int, threshold: float) -> bool C++: mrpt::maps::COccupancyGridMap2D::isStaticCell(int, int, float) const --> bool

isStaticPos(...)
isStaticPos(*args, **kwargs) Overloaded function. 1. isStaticPos(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, y: float) -> bool 2. isStaticPos(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, y: float, threshold: float) -> bool Returns "true" if cell is "static", i.e.if its occupancy is below a given threshold C++: mrpt::maps::COccupancyGridMap2D::isStaticPos(float, float, float) const --> bool

laserScanSimulator(...)
laserScanSimulator(*args, **kwargs) Overloaded function. 1. laserScanSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_Scan: mrpt.pymrpt.mrpt.obs.CObservation2DRangeScan, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D) -> None 2. laserScanSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_Scan: mrpt.pymrpt.mrpt.obs.CObservation2DRangeScan, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D, threshold: float) -> None 3. laserScanSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_Scan: mrpt.pymrpt.mrpt.obs.CObservation2DRangeScan, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D, threshold: float, N: int) -> None 4. laserScanSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_Scan: mrpt.pymrpt.mrpt.obs.CObservation2DRangeScan, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D, threshold: float, N: int, noiseStd: float) -> None 5. laserScanSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_Scan: mrpt.pymrpt.mrpt.obs.CObservation2DRangeScan, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D, threshold: float, N: int, noiseStd: float, decimation: int) -> None 6. laserScanSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_Scan: mrpt.pymrpt.mrpt.obs.CObservation2DRangeScan, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D, threshold: float, N: int, noiseStd: float, decimation: int, angleNoiseStd: float) -> None Simulates a laser range scan into the current grid map.    The simulated scan is stored in a CObservation2DRangeScan object, which is also used     to pass some parameters: all previously stored characteristics (as aperture,...) are           taken into account for simulation. Only a few more parameters are needed. Additive gaussian noise can be optionally added to the simulated scan. [IN/OUT] This must be filled with desired parameters before calling, and will contain the scan samples on return. [IN] The robot pose in this map coordinates. Recall that sensor pose relative to this robot pose must be specified in the observation object. [IN] The minimum occupancy threshold to consider a cell to be occupied (Default: 0.5f) [IN] The count of range scan "rays", by default to 361. [IN] The standard deviation of measurement noise. If not desired, set to 0. [IN] The rays that will be simulated are at indexes: 0, D, 2D, 3D, ... Default is D=1 [IN] The sigma of an optional Gaussian noise added to the angles at which ranges are measured (in radians). laserScanSimulatorWithUncertainty(), sonarSimulator(), COccupancyGridMap2D::RAYTRACE_STEP_SIZE_IN_CELL_UNITS C++: mrpt::maps::COccupancyGridMap2D::laserScanSimulator(class mrpt::obs::CObservation2DRangeScan &, const class mrpt::poses::CPose2D &, float, size_t, float, unsigned int, float) const --> void

laserScanSimulatorWithUncertainty(...)
laserScanSimulatorWithUncertainty(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, in_params: mrpt::maps::COccupancyGridMap2D::TLaserSimulUncertaintyParams, out_results: mrpt::maps::COccupancyGridMap2D::TLaserSimulUncertaintyResult) -> None Like laserScanSimulatorWithUncertainty() (see it for a discussion of most parameters) but taking into account   the robot pose uncertainty and generating a vector of predicted variances for each ray.   Range uncertainty includes both, sensor noise and large non-linear effects caused by borders and discontinuities in the environment   as seen from different robot poses. [IN] Input settings. See TLaserSimulUncertaintyParams [OUT] Output range + uncertainty. laserScanSimulator(), COccupancyGridMap2D::RAYTRACE_STEP_SIZE_IN_CELL_UNITS C++: mrpt::maps::COccupancyGridMap2D::laserScanSimulatorWithUncertainty(const struct mrpt::maps::COccupancyGridMap2D::TLaserSimulUncertaintyParams &, struct mrpt::maps::COccupancyGridMap2D::TLaserSimulUncertaintyResult &) const --> void

loadFromBitmap(...)
loadFromBitmap(*args, **kwargs) Overloaded function. 1. loadFromBitmap(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage, resolution: float) -> bool 2. loadFromBitmap(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage, resolution: float, origin: mrpt::math::TPoint2D_<double>) -> bool Load the gridmap from a image in a file (the format can be any supported by CImage::loadFromFile).   See loadFromBitmapFile() for the meaning of parameters C++: mrpt::maps::COccupancyGridMap2D::loadFromBitmap(const class mrpt::img::CImage &, float, const struct mrpt::math::TPoint2D_<double> &) --> bool

loadFromBitmapFile(...)
loadFromBitmapFile(*args, **kwargs) Overloaded function. 1. loadFromBitmapFile(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, file: str, resolution: float) -> bool 2. loadFromBitmapFile(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, file: str, resolution: float, origin: mrpt::math::TPoint2D_<double>) -> bool Load the gridmap from a image in a file (the format can be any supported by CImage::loadFromFile). The file to be loaded. The size of a pixel (cell), in meters. Recall cells are always squared, so just a dimension is needed. The `x` (0=first, increases left to right on the image) and `y` (0=first, increases BOTTOM upwards on the image) coordinates for the pixel which will be taken at the origin of map coordinates (0,0). (Default=center of the image) False on any error. loadFromBitmap C++: mrpt::maps::COccupancyGridMap2D::loadFromBitmapFile(const std::string &, float, const struct mrpt::math::TPoint2D_<double> &) --> bool

loadFromROSMapServerYAML(...)
loadFromROSMapServerYAML(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, yamlFilePath: str) -> bool Loads this gridmap from a .yaml file and an accompanying image file   given in the   [map_server YAML](http://wiki.ros.org/map_server#YAML_format) file   format. Absolute or relative path to the `.yaml` file. false on error, true on success. FromROSMapServerYAML() C++: mrpt::maps::COccupancyGridMap2D::loadFromROSMapServerYAML(const std::string &) --> bool

resizeGrid(...)
resizeGrid(*args, **kwargs) Overloaded function. 1. resizeGrid(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float) -> None 2. resizeGrid(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, new_cells_default_value: float) -> None 3. resizeGrid(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, new_cells_default_value: float, additionalMargin: bool) -> None Change the size of gridmap, maintaining previous contents. The "x" coordinates of new left most side of grid. The "x" coordinates of new right most side of grid. The "y" coordinates of new top most side of grid. The "y" coordinates of new bottom most side of grid. The value of the new cells, tipically 0.5. If set to true (default), an additional margin of a few meters will be added to the grid, ONLY if the new coordinates are larger than current ones. setSize C++: mrpt::maps::COccupancyGridMap2D::resizeGrid(float, float, float, float, float, bool) --> void

saveAsBitmapFile(...)
saveAsBitmapFile(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, file: str) -> bool Saves the gridmap as a graphical file (BMP,PNG,...). The format will be derived from the file extension (see CImage::saveToFile ) False on any error. C++: mrpt::maps::COccupancyGridMap2D::saveAsBitmapFile(const std::string &) const --> bool

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface).   C++: mrpt::maps::COccupancyGridMap2D::saveMetricMapRepresentationToFile(const std::string &) const --> void

setBasisCell(...)
setBasisCell(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: int, y: int, value: int) -> None Change a cell in the "basis" maps.Used for Voronoi calculation C++: mrpt::maps::COccupancyGridMap2D::setBasisCell(int, int, uint8_t) --> void

setCell(...)
setCell(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: int, y: int, value: float) -> None Change the contents [0,1] of a cell, given its index C++: mrpt::maps::COccupancyGridMap2D::setCell(int, int, float) --> void

setPos(...)
setPos(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, y: float, value: float) -> None Change the contents [0,1] of a cell, given its coordinates C++: mrpt::maps::COccupancyGridMap2D::setPos(float, float, float) --> void

setSize(...)
setSize(*args, **kwargs) Overloaded function. 1. setSize(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 2. setSize(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float, default_value: float) -> None Change the size of gridmap, erasing all its previous contents. The "x" coordinates of left most side of grid. The "x" coordinates of right most side of grid. The "y" coordinates of top most side of grid. The "y" coordinates of bottom most side of grid. The new size of cells. The value of cells, tipically 0.5. ResizeGrid C++: mrpt::maps::COccupancyGridMap2D::setSize(float, float, float, float, float, float) --> void

simulateScanRay(...)
simulateScanRay(*args, **kwargs) Overloaded function. 1. simulateScanRay(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, y: float, angle_direction: float, out_range: float, out_valid: bool, max_range_meters: float) -> None 2. simulateScanRay(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, y: float, angle_direction: float, out_range: float, out_valid: bool, max_range_meters: float, threshold_free: float) -> None 3. simulateScanRay(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, y: float, angle_direction: float, out_range: float, out_valid: bool, max_range_meters: float, threshold_free: float, noiseStd: float) -> None 4. simulateScanRay(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, y: float, angle_direction: float, out_range: float, out_valid: bool, max_range_meters: float, threshold_free: float, noiseStd: float, angleNoiseStd: float) -> None Simulate just one "ray" in the grid map. This method is used internally to sonarSimulator and laserScanSimulator. COccupancyGridMap2D::RAYTRACE_STEP_SIZE_IN_CELL_UNITS C++: mrpt::maps::COccupancyGridMap2D::simulateScanRay(const double, const double, const double, float &, bool &, const double, const float, const double, const double) const --> void

sonarSimulator(...)
sonarSimulator(*args, **kwargs) Overloaded function. 1. sonarSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_observation: mrpt.pymrpt.mrpt.obs.CObservationRange, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D) -> None 2. sonarSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_observation: mrpt.pymrpt.mrpt.obs.CObservationRange, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D, threshold: float) -> None 3. sonarSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_observation: mrpt.pymrpt.mrpt.obs.CObservationRange, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D, threshold: float, rangeNoiseStd: float) -> None 4. sonarSimulator(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, inout_observation: mrpt.pymrpt.mrpt.obs.CObservationRange, robotPose: mrpt.pymrpt.mrpt.poses.CPose2D, threshold: float, rangeNoiseStd: float, angleNoiseStd: float) -> None Simulates the observations of a sonar rig into the current grid map.    The simulated ranges are stored in a CObservationRange object, which is also used     to pass in some needed parameters, as the poses of the sonar sensors onto the mobile robot. [IN/OUT] This must be filled with desired parameters before calling, and will contain the simulated ranges on return. [IN] The robot pose in this map coordinates. Recall that sensor pose relative to this robot pose must be specified in the observation object. [IN] The minimum occupancy threshold to consider a cell to be occupied (Default: 0.5f) [IN] The standard deviation of measurement noise. If not desired, set to 0. [IN] The sigma of an optional Gaussian noise added to the angles at which ranges are measured (in radians). laserScanSimulator(), COccupancyGridMap2D::RAYTRACE_STEP_SIZE_IN_CELL_UNITS C++: mrpt::maps::COccupancyGridMap2D::sonarSimulator(class mrpt::obs::CObservationRange &, const class mrpt::poses::CPose2D &, float, float, float) const --> void

subSample(...)
subSample(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, downRatio: int) -> None Performs a downsampling of the gridmap, by a given factor: resolution/=ratio C++: mrpt::maps::COccupancyGridMap2D::subSample(int) --> void

updateCell(...)
updateCell(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: int, y: int, v: float) -> None Performs the Bayesian fusion of a new observation of a cell   updateInfoChangeOnly, updateCell_fast_occupied, updateCell_fast_free C++: mrpt::maps::COccupancyGridMap2D::updateCell(int, int, float) --> void

x2idx(...)
x2idx(*args, **kwargs) Overloaded function. 1. x2idx(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float) -> int Transform a coordinate value into a cell index C++: mrpt::maps::COccupancyGridMap2D::x2idx(float) const --> int 2. x2idx(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float) -> int C++: mrpt::maps::COccupancyGridMap2D::x2idx(double) const --> int 3. x2idx(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, x: float, xmin: float) -> int Transform a coordinate value into a cell index, using a diferent "x_min" value C++: mrpt::maps::COccupancyGridMap2D::x2idx(float, float) const --> int

y2idx(...)
y2idx(*args, **kwargs) Overloaded function. 1. y2idx(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, y: float) -> int C++: mrpt::maps::COccupancyGridMap2D::y2idx(float) const --> int 2. y2idx(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, y: float) -> int C++: mrpt::maps::COccupancyGridMap2D::y2idx(double) const --> int 3. y2idx(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, y: float, ymin: float) -> int C++: mrpt::maps::COccupancyGridMap2D::y2idx(float, float) const --> int

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::COccupancyGridMap2D::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

FromROSMapServerYAML(...) from builtins.PyCapsule
FromROSMapServerYAML(yamlFilePath: str) -> mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D Creates a gridmap from a .yaml file and an accompanying image file   given in the   [map_server YAML](http://wiki.ros.org/map_server#YAML_format) file   format. Absolute or relative path to the `.yaml` file. loadFromROSMapServerYAML() std::exception On error loading or parsing the files. C++: mrpt::maps::COccupancyGridMap2D::FromROSMapServerYAML(const std::string &) --> class mrpt::maps::COccupancyGridMap2D

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::COccupancyGridMap2D::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

l2p(...) from builtins.PyCapsule
l2p(l: int) -> float Scales an integer representation of the log-odd into a real valued probability in [0,1], using p=exp(l)/(1+exp(l))   C++: mrpt::maps::COccupancyGridMap2D::l2p(const signed char) --> float

l2p_255(...) from builtins.PyCapsule
l2p_255(l: int) -> int Scales an integer representation of the log-odd into a linear scale [0,255], using p=exp(l)/(1+exp(l)) C++: mrpt::maps::COccupancyGridMap2D::l2p_255(const signed char) --> uint8_t

p2l(...) from builtins.PyCapsule
p2l(p: float) -> int Scales a real valued probability in [0,1] to an integer representation of: log(p)-log(1-p)  in the valid range of cellType C++: mrpt::maps::COccupancyGridMap2D::p2l(const float) --> signed char

saveAsBitmapTwoMapsWithCorrespondences(...) from builtins.PyCapsule
saveAsBitmapTwoMapsWithCorrespondences(fileName: str, m1: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, m2: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, corrs: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t) -> bool Saves a composite image with two gridmaps and lines representing a set of correspondences between them. saveAsEMFTwoMapsWithCorrespondences False on any error. C++: mrpt::maps::COccupancyGridMap2D::saveAsBitmapTwoMapsWithCorrespondences(const std::string &, const class mrpt::maps::COccupancyGridMap2D *, const class mrpt::maps::COccupancyGridMap2D *, const class mrpt::tfest::TMatchingPairListTempl<float> &) --> bool

saveAsEMFTwoMapsWithCorrespondences(...) from builtins.PyCapsule
saveAsEMFTwoMapsWithCorrespondences(fileName: str, m1: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, m2: mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D, corrs: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t) -> bool Saves a composite image with two gridmaps and numbers for the correspondences between them. saveAsBitmapTwoMapsWithCorrespondences False on any error. C++: mrpt::maps::COccupancyGridMap2D::saveAsEMFTwoMapsWithCorrespondences(const std::string &, const class mrpt::maps::COccupancyGridMap2D *, const class mrpt::maps::COccupancyGridMap2D *, const class mrpt::tfest::TMatchingPairListTempl<float> &) --> bool

Data descriptors defined here:

CriticalPointsList

insertionOptions

likelihoodOptions

likelihoodOutputs

updateInfoChangeOnly

Data and other attributes defined here:

TCriticalPointsList = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TCriticalPointsList'>
The structure used to store the set of Voronoi diagram    critical points. findCriticalPoints

TEntropyInfo = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TEntropyInfo'>
Used for returning entropy related information computeEntropy

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TInsertionOptions'>
With this struct options are provided to the observation insertion process. CObservation::insertIntoGridMap

TLaserSimulUncertaintyMethod = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TLaserSimulUncertaintyMethod'>

TLaserSimulUncertaintyParams = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TLaserSimulUncertaintyParams'>
Input params for laserScanSimulatorWithUncertainty()

TLaserSimulUncertaintyResult = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TLaserSimulUncertaintyResult'>
Output params for laserScanSimulatorWithUncertainty()

TLikelihoodMethod = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TLikelihoodMethod'>

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TLikelihoodOptions'>
With this struct options are provided to the observation likelihood computation process

TLikelihoodOutput = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TLikelihoodOutput'>
Some members of this struct will contain intermediate or output data after calling "computeObservationLikelihood" for some likelihood functions

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TMapDefinitionBase'>

TUpdateCellsInfoChangeOnly = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap2D.TUpdateCellsInfoChangeOnly'>
An internal structure for storing data related to counting the new information apported by some observation

lmCellsDifference = <TLikelihoodMethod.lmCellsDifference: 3>

lmConsensus = <TLikelihoodMethod.lmConsensus: 2>

lmConsensusOWA = <TLikelihoodMethod.lmConsensusOWA: 6>

lmLikelihoodField_II = <TLikelihoodMethod.lmLikelihoodField_II: 5>

lmLikelihoodField_Thrun = <TLikelihoodMethod.lmLikelihoodField_Thrun: 4>

lmMeanInformation = <TLikelihoodMethod.lmMeanInformation: 0>

lmRayTracing = <TLikelihoodMethod.lmRayTracing: 1>

sumMonteCarlo = <TLaserSimulUncertaintyMethod.sumMonteCarlo: 1>

sumUnscented = <TLaserSimulUncertaintyMethod.sumUnscented: 0>

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from CLogOddsGridMap2D_signed_char_t:

updateCell_fast_occupied(...)
updateCell_fast_occupied(*args, **kwargs) Overloaded function. 1. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t, x: int, y: int, logodd_obs: int, thres: int, mapArray: int, _size_x: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_occupied(const unsigned int, const unsigned int, const signed char, const signed char, signed char *, const unsigned int) --> void 2. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t, theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_occupied(signed char *, const signed char, const signed char) --> void

Static methods inherited from CLogOddsGridMap2D_signed_char_t:

updateCell_fast_free(...) from builtins.PyCapsule
updateCell_fast_free(*args, **kwargs) Overloaded function. 1. updateCell_fast_free(x: int, y: int, logodd_obs: int, thres: int, mapArray: int, _size_x: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_free(const unsigned int, const unsigned int, const signed char, const signed char, signed char *, const unsigned int) --> void 2. updateCell_fast_free(theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_free(signed char *, const signed char, const signed char) --> void

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class COccupancyGridMap3D(CMetricMap, CLogOddsGridMap3D_signed_char_t)

    A 3D occupancy grid map with a regular, even distribution of voxels. This is a faster alternative to COctoMap, but use with caution with limited map extensions, since it could easily exaust available memory. Each voxel follows a Bernoulli probability distribution: a value of 0 means certainly occupied, 1 means a certainly empty voxel. Initially 0.5 means uncertainty.

Method resolution order:

COccupancyGridMap3D

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

CLogOddsGridMap3D_signed_char_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::COccupancyGridMap3D::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, arg0: mrpt::math::TPoint3D_<double>) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, arg0: mrpt::math::TPoint3D_<double>, arg1: mrpt::math::TPoint3D_<double>) -> None doc 4. __init__(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, corner_min: mrpt::math::TPoint3D_<double>, corner_max: mrpt::math::TPoint3D_<double>, resolution: float) -> None

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D) -> str Returns a short description of the map. C++: mrpt::maps::COccupancyGridMap3D::asString() const --> std::string

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, : mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D) -> mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D C++: mrpt::maps::COccupancyGridMap3D::operator=(const class mrpt::maps::COccupancyGridMap3D &) --> class mrpt::maps::COccupancyGridMap3D &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::COccupancyGridMap3D::clone() const --> class mrpt::rtti::CObject *

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float See docs in base class: in this class this always returns 0 C++: mrpt::maps::COccupancyGridMap3D::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None See docs in base class: in this class this always returns 0 C++: mrpt::maps::COccupancyGridMap3D::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

fill(...)
fill(*args, **kwargs) Overloaded function. 1. fill(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D) -> None 2. fill(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, default_value: float) -> None Fills all the voxels with a default value. C++: mrpt::maps::COccupancyGridMap3D::fill(float) --> void

getAsOctoMapVoxels(...)
getAsOctoMapVoxels(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, gl_obj: mrpt.pymrpt.mrpt.opengl.COctoMapVoxels) -> None renderingOptions C++: mrpt::maps::COccupancyGridMap3D::getAsOctoMapVoxels(class mrpt::opengl::COctoMapVoxels &) const --> void

getCellFreeness(...)
getCellFreeness(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, cx: int, cy: int, cz: int) -> float Read the real valued [0,1] (0:occupied, 1:free) contents of a voxel, given its index C++: mrpt::maps::COccupancyGridMap3D::getCellFreeness(unsigned int, unsigned int, unsigned int) const --> float

getFreenessByPos(...)
getFreenessByPos(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, x: float, y: float, z: float) -> float Read the real valued [0,1] contents of a voxel, given its coordinates C++: mrpt::maps::COccupancyGridMap3D::getFreenessByPos(float, float, float) const --> float

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns a 3D object representing the map. renderingOptions C++: mrpt::maps::COccupancyGridMap3D::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

insertPointCloud(...)
insertPointCloud(*args, **kwargs) Overloaded function. 1. insertPointCloud(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, sensorCenter: mrpt::math::TPoint3D_<double>, pts: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. insertPointCloud(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, sensorCenter: mrpt::math::TPoint3D_<double>, pts: mrpt.pymrpt.mrpt.maps.CPointsMap, maxValidRange: float) -> None Calls insertRay() for each point in the point cloud, using as sensor central point (the origin of all rays), the given `sensorCenter`. If a point has larger distance from `sensorCenter` than `maxValidRange`, it will be considered a non-echo, and NO occupied voxel will be created at the end of the segment. insertionOptions parameters are observed in this method. C++: mrpt::maps::COccupancyGridMap3D::insertPointCloud(const struct mrpt::math::TPoint3D_<double> &, const class mrpt::maps::CPointsMap &, const float) --> void

insertRay(...)
insertRay(*args, **kwargs) Overloaded function. 1. insertRay(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, sensor: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>) -> None 2. insertRay(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, sensor: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>, endIsOccupied: bool) -> None Increases the freeness of a ray segment, and the occupancy of the voxel at its end point (unless endIsOccupied=false). Normally, users would prefer the higher-level method CMetricMap::insertObservation() C++: mrpt::maps::COccupancyGridMap3D::insertRay(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, bool) --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D) -> bool Returns true upon map construction or after calling clear(), the return   changes to false upon successful insertObservation() or any other method to load data in the map. C++: mrpt::maps::COccupancyGridMap3D::isEmpty() const --> bool

resizeGrid(...)
resizeGrid(*args, **kwargs) Overloaded function. 1. resizeGrid(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, corner_min: mrpt::math::TPoint3D_<double>, corner_max: mrpt::math::TPoint3D_<double>) -> None 2. resizeGrid(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, corner_min: mrpt::math::TPoint3D_<double>, corner_max: mrpt::math::TPoint3D_<double>, new_voxels_default_value: float) -> None Change the size of gridmap, maintaining previous contents. Value of new voxels, tipically 0.5 setSize() C++: mrpt::maps::COccupancyGridMap3D::resizeGrid(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, float) --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, f: str) -> None C++: mrpt::maps::COccupancyGridMap3D::saveMetricMapRepresentationToFile(const std::string &) const --> void

setCellFreeness(...)
setCellFreeness(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, cx: int, cy: int, cz: int, value: float) -> None Change the contents [0,1] (0:occupied, 1:free) of a voxel, given its index. C++: mrpt::maps::COccupancyGridMap3D::setCellFreeness(unsigned int, unsigned int, unsigned int, float) --> void

setFreenessByPos(...)
setFreenessByPos(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, x: float, y: float, z: float, value: float) -> None Change the contents [0,1] of a voxel, given its coordinates C++: mrpt::maps::COccupancyGridMap3D::setFreenessByPos(float, float, float, float) --> void

setSize(...)
setSize(*args, **kwargs) Overloaded function. 1. setSize(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, corner_min: mrpt::math::TPoint3D_<double>, corner_max: mrpt::math::TPoint3D_<double>, resolution: float) -> None 2. setSize(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, corner_min: mrpt::math::TPoint3D_<double>, corner_max: mrpt::math::TPoint3D_<double>, resolution: float, default_value: float) -> None Change the size of gridmap, erasing all its previous contents. The new size of voxels. The value of voxels, tipically 0.5. ResizeGrid C++: mrpt::maps::COccupancyGridMap3D::setSize(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, double, float) --> void

updateCell(...)
updateCell(self: mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D, cx_idx: int, cy_idx: int, cz_idx: int, v: float) -> None Performs the Bayesian fusion of a new observation of a cell   updateInfoChangeOnly, updateCell_fast_occupied, updateCell_fast_free C++: mrpt::maps::COccupancyGridMap3D::updateCell(int, int, int, float) --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::COccupancyGridMap3D::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::COccupancyGridMap3D::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

l2p(...) from builtins.PyCapsule
l2p(l: int) -> float Scales an integer representation of the log-odd into a real valued probability in [0,1], using p=exp(l)/(1+exp(l))   C++: mrpt::maps::COccupancyGridMap3D::l2p(const signed char) --> float

l2p_255(...) from builtins.PyCapsule
l2p_255(l: int) -> int Scales an integer representation of the log-odd into a linear scale [0,255], using p=exp(l)/(1+exp(l)) C++: mrpt::maps::COccupancyGridMap3D::l2p_255(const signed char) --> uint8_t

p2l(...) from builtins.PyCapsule
p2l(p: float) -> int Scales a real valued probability in [0,1] to an integer representation of: log(p)-log(1-p)  in the valid range of voxelType C++: mrpt::maps::COccupancyGridMap3D::p2l(const float) --> signed char

Data descriptors defined here:

insertionOptions

likelihoodOptions

renderingOptions

Data and other attributes defined here:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D.TInsertionOptions'>
With this struct options are provided to the observation insertion process. CObservation::insertIntoGridMap

TLikelihoodMethod = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D.TLikelihoodMethod'>

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D.TLikelihoodOptions'>
With this struct options are provided to the observation likelihood computation process

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D.TMapDefinitionBase'>

TRenderingOptions = <class 'mrpt.pymrpt.mrpt.maps.COccupancyGridMap3D.TRenderingOptions'>
Options for the conversion of a mrpt::maps::COccupancyGridMap3D into a mrpt::opengl::COctoMapVoxels

lmLikelihoodField_Thrun = <TLikelihoodMethod.lmLikelihoodField_Thrun: 0>

lmRayTracing = <TLikelihoodMethod.lmRayTracing: 1>

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from CLogOddsGridMap3D_signed_char_t:

updateCell_fast_free(...)
updateCell_fast_free(*args, **kwargs) Overloaded function. 1. updateCell_fast_free(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t, theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap3D<signed char>::updateCell_fast_free(signed char *, const signed char, const signed char) --> void 2. updateCell_fast_free(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t, x: int, y: int, z: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap3D<signed char>::updateCell_fast_free(const unsigned int, const unsigned int, const unsigned int, const signed char, const signed char) --> void

updateCell_fast_occupied(...)
updateCell_fast_occupied(*args, **kwargs) Overloaded function. 1. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t, theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap3D<signed char>::updateCell_fast_occupied(signed char *, const signed char, const signed char) --> void 2. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap3D_signed_char_t, x: int, y: int, z: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap3D<signed char>::updateCell_fast_occupied(const unsigned int, const unsigned int, const unsigned int, const signed char, const signed char) --> void

Data descriptors inherited from CLogOddsGridMap3D_signed_char_t:

m_grid

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class COctoMap(COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t)

    A three-dimensional probabilistic occupancy grid, implemented as an octo-tree with the "octomap" C++ library. This version only stores occupancy information at each octree node. See the base class mrpt::maps::COctoMapBase. CMetricMap, the example in "MRPT/samples/octomap_simple"

Method resolution order:

COctoMap

COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::COctoMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.COctoMap, resolution: float) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.COctoMap, arg0: mrpt.pymrpt.mrpt.maps.COctoMap) -> None 4. __init__(self: mrpt.pymrpt.mrpt.maps.COctoMap, arg0: mrpt.pymrpt.mrpt.maps.COctoMap) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.COctoMap, : mrpt.pymrpt.mrpt.maps.COctoMap) -> mrpt.pymrpt.mrpt.maps.COctoMap C++: mrpt::maps::COctoMap::operator=(const class mrpt::maps::COctoMap &) --> class mrpt::maps::COctoMap &

calcNumNodes(...)
calcNumNodes(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> int Traverses the tree to calculate the total number of nodes C++: mrpt::maps::COctoMap::calcNumNodes() const --> size_t

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::COctoMap::clone() const --> class mrpt::rtti::CObject *

getAsOctoMapVoxels(...)
getAsOctoMapVoxels(self: mrpt.pymrpt.mrpt.maps.COctoMap, gl_obj: mrpt.pymrpt.mrpt.opengl.COctoMapVoxels) -> None C++: mrpt::maps::COctoMap::getAsOctoMapVoxels(class mrpt::opengl::COctoMapVoxels &) const --> void

getClampingThresMax(...)
getClampingThresMax(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getClampingThresMax() const --> double

getClampingThresMaxLog(...)
getClampingThresMaxLog(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getClampingThresMaxLog() const --> float

getClampingThresMin(...)
getClampingThresMin(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getClampingThresMin() const --> double

getClampingThresMinLog(...)
getClampingThresMinLog(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getClampingThresMinLog() const --> float

getMetricMax(...)
getMetricMax(self: mrpt.pymrpt.mrpt.maps.COctoMap, x: float, y: float, z: float) -> None maximum value of the bounding box of all known space in x, y, z C++: mrpt::maps::COctoMap::getMetricMax(double &, double &, double &) --> void

getMetricMin(...)
getMetricMin(self: mrpt.pymrpt.mrpt.maps.COctoMap, x: float, y: float, z: float) -> None minimum value of the bounding box of all known space in x, y, z C++: mrpt::maps::COctoMap::getMetricMin(double &, double &, double &) --> void

getMetricSize(...)
getMetricSize(self: mrpt.pymrpt.mrpt.maps.COctoMap, x: float, y: float, z: float) -> None Size of OcTree (all known space) in meters for x, y and z dimension C++: mrpt::maps::COctoMap::getMetricSize(double &, double &, double &) --> void

getNumLeafNodes(...)
getNumLeafNodes(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> int Traverses the tree to calculate the total number of leaf nodes C++: mrpt::maps::COctoMap::getNumLeafNodes() const --> size_t

getOccupancyThres(...)
getOccupancyThres(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getOccupancyThres() const --> double

getOccupancyThresLog(...)
getOccupancyThresLog(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getOccupancyThresLog() const --> float

getProbHit(...)
getProbHit(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getProbHit() const --> double

getProbHitLog(...)
getProbHitLog(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getProbHitLog() const --> float

getProbMiss(...)
getProbMiss(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getProbMiss() const --> double

getProbMissLog(...)
getProbMissLog(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getProbMissLog() const --> float

getResolution(...)
getResolution(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::getResolution() const --> double

getTreeDepth(...)
getTreeDepth(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> int C++: mrpt::maps::COctoMap::getTreeDepth() const --> unsigned int

insertRay(...)
insertRay(self: mrpt.pymrpt.mrpt.maps.COctoMap, end_x: float, end_y: float, end_z: float, sensor_x: float, sensor_y: float, sensor_z: float) -> None Just like insertPointCloud but with a single ray. C++: mrpt::maps::COctoMap::insertRay(const float, const float, const float, const float, const float, const float) --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> bool Returns true if the map is empty/no observation has been inserted C++: mrpt::maps::COctoMap::isEmpty() const --> bool

isPointWithinOctoMap(...)
isPointWithinOctoMap(self: mrpt.pymrpt.mrpt.maps.COctoMap, x: float, y: float, z: float) -> bool Check whether the given point lies within the volume covered by the octomap (that is, whether it is "mapped") C++: mrpt::maps::COctoMap::isPointWithinOctoMap(const float, const float, const float) const --> bool

memoryFullGrid(...)
memoryFullGrid(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> int Memory usage of a full grid of the same size as the OcTree in bytes (for comparison) C++: mrpt::maps::COctoMap::memoryFullGrid() const --> size_t

memoryUsage(...)
memoryUsage(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> int Memory usage of the complete octree in bytes (may vary between architectures) C++: mrpt::maps::COctoMap::memoryUsage() const --> size_t

memoryUsageNode(...)
memoryUsageNode(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> int Memory usage of the a single octree node C++: mrpt::maps::COctoMap::memoryUsageNode() const --> size_t

setClampingThresMax(...)
setClampingThresMax(self: mrpt.pymrpt.mrpt.maps.COctoMap, thresProb: float) -> None C++: mrpt::maps::COctoMap::setClampingThresMax(double) --> void

setClampingThresMin(...)
setClampingThresMin(self: mrpt.pymrpt.mrpt.maps.COctoMap, thresProb: float) -> None C++: mrpt::maps::COctoMap::setClampingThresMin(double) --> void

setOccupancyThres(...)
setOccupancyThres(self: mrpt.pymrpt.mrpt.maps.COctoMap, prob: float) -> None C++: mrpt::maps::COctoMap::setOccupancyThres(double) --> void

setProbHit(...)
setProbHit(self: mrpt.pymrpt.mrpt.maps.COctoMap, prob: float) -> None C++: mrpt::maps::COctoMap::setProbHit(double) --> void

setProbMiss(...)
setProbMiss(self: mrpt.pymrpt.mrpt.maps.COctoMap, prob: float) -> None C++: mrpt::maps::COctoMap::setProbMiss(double) --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> int The number of nodes in the tree C++: mrpt::maps::COctoMap::size() const --> size_t

updateVoxel(...)
updateVoxel(self: mrpt.pymrpt.mrpt.maps.COctoMap, x: float, y: float, z: float, occupied: bool) -> None Manually updates the occupancy of the voxel at (x,y,z) as being occupied (true) or free (false), using the log-odds parameters in C++: mrpt::maps::COctoMap::updateVoxel(const double, const double, const double, bool) --> void

volume(...)
volume(self: mrpt.pymrpt.mrpt.maps.COctoMap) -> float C++: mrpt::maps::COctoMap::volume() --> double

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::COctoMap::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::COctoMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data and other attributes defined here:

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.COctoMap.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.COctoMap.TMapDefinitionBase'>

Methods inherited from COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t:

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> str C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::asString() const --> std::string

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

castRay(...)
castRay(*args, **kwargs) Overloaded function. 1. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>) -> bool 2. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>, ignoreUnknownCells: bool) -> bool 3. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>, ignoreUnknownCells: bool, maxRange: float) -> bool C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::castRay(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, struct mrpt::math::TPoint3D_<double> &, bool, double) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float Computes the ratio in [0,1] of correspondences between "this" and the "otherMap" map, whose 6D pose relative to "this" is "otherMapPose"    In the case of a multi-metric map, this returns the average between the maps. This method always return 0 for grid maps.       [IN] The other map to compute the matching with.   [IN] The 6D pose of the other map as seen from "this".         [IN] Matching parameters The matching ratio [0,1] determineMatching2D C++: mrpt::maps::CMetricMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

getPointOccupancy(...)
getPointOccupancy(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, x: float, y: float, z: float, prob_occupancy: float) -> bool C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getPointOccupancy(const float, const float, const float, double &) const --> bool

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, o: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

insertPointCloud(...)
insertPointCloud(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, ptMap: mrpt.pymrpt.mrpt.maps.CPointsMap, sensor_x: float, sensor_y: float, sensor_z: float) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::insertPointCloud(const class mrpt::maps::CPointsMap &, const float, const float, const float) --> void

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, Map: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, Map: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(*args, **kwargs) Overloaded function. 1. saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, filNamePrefix: str) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::saveMetricMapRepresentationToFile(const std::string &) const --> void 2. saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface). C++: mrpt::maps::CMetricMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t:

genericMapParams

insertionOptions

likelihoodOptions

renderingOptions

Data and other attributes inherited from COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t.TInsertionOptions'>

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t.TLikelihoodOptions'>

TRenderingOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t.TRenderingOptions'>

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t(CMetricMap)


Method resolution order:

COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMetricMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(self, /, *args, **kwargs)
Initialize self.  See help(type(self)) for accurate signature.

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> str C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::asString() const --> std::string

assign(...)
assign(*args, **kwargs) Overloaded function. 1. assign(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, : mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::operator=(const class mrpt::maps::COctoMapBase<class octomap::ColorOcTree, class octomap::ColorOcTreeNode> &) --> class mrpt::maps::COctoMapBase<class octomap::ColorOcTree, class octomap::ColorOcTreeNode> & 2. assign(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, : mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt.pymrpt.mrpt.maps.CMetricMap C++: mrpt::maps::CMetricMap::operator=(const class mrpt::maps::CMetricMap &) --> class mrpt::maps::CMetricMap &

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

castRay(...)
castRay(*args, **kwargs) Overloaded function. 1. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>) -> bool 2. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>, ignoreUnknownCells: bool) -> bool 3. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>, ignoreUnknownCells: bool, maxRange: float) -> bool C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::castRay(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, struct mrpt::math::TPoint3D_<double> &, bool, double) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float Computes the ratio in [0,1] of correspondences between "this" and the "otherMap" map, whose 6D pose relative to "this" is "otherMapPose"    In the case of a multi-metric map, this returns the average between the maps. This method always return 0 for grid maps.       [IN] The other map to compute the matching with.   [IN] The 6D pose of the other map as seen from "this".         [IN] Matching parameters The matching ratio [0,1] determineMatching2D C++: mrpt::maps::CMetricMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsOctoMapVoxels(...)
getAsOctoMapVoxels(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, gl_obj: mrpt.pymrpt.mrpt.opengl.COctoMapVoxels) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getAsOctoMapVoxels(class mrpt::opengl::COctoMapVoxels &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

getClampingThresMax(...)
getClampingThresMax(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getClampingThresMax() const --> double

getClampingThresMaxLog(...)
getClampingThresMaxLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getClampingThresMaxLog() const --> float

getClampingThresMin(...)
getClampingThresMin(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getClampingThresMin() const --> double

getClampingThresMinLog(...)
getClampingThresMinLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getClampingThresMinLog() const --> float

getOccupancyThres(...)
getOccupancyThres(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getOccupancyThres() const --> double

getOccupancyThresLog(...)
getOccupancyThresLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getOccupancyThresLog() const --> float

getPointOccupancy(...)
getPointOccupancy(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, x: float, y: float, z: float, prob_occupancy: float) -> bool C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getPointOccupancy(const float, const float, const float, double &) const --> bool

getProbHit(...)
getProbHit(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getProbHit() const --> double

getProbHitLog(...)
getProbHitLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getProbHitLog() const --> float

getProbMiss(...)
getProbMiss(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getProbMiss() const --> double

getProbMissLog(...)
getProbMissLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getProbMissLog() const --> float

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, o: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

insertPointCloud(...)
insertPointCloud(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, ptMap: mrpt.pymrpt.mrpt.maps.CPointsMap, sensor_x: float, sensor_y: float, sensor_z: float) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::insertPointCloud(const class mrpt::maps::CPointsMap &, const float, const float, const float) --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CMetricMap::isEmpty() const --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, Map: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, Map: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(*args, **kwargs) Overloaded function. 1. saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, filNamePrefix: str) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::saveMetricMapRepresentationToFile(const std::string &) const --> void 2. saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface). C++: mrpt::maps::CMetricMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

setClampingThresMax(...)
setClampingThresMax(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, thresProb: float) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::setClampingThresMax(double) --> void

setClampingThresMin(...)
setClampingThresMin(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, thresProb: float) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::setClampingThresMin(double) --> void

setOccupancyThres(...)
setOccupancyThres(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, prob: float) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::setOccupancyThres(double) --> void

setProbHit(...)
setProbHit(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, prob: float) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::setProbHit(double) --> void

setProbMiss(...)
setProbMiss(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, prob: float) -> None C++: mrpt::maps::COctoMapBase<octomap::ColorOcTree, octomap::ColorOcTreeNode>::setProbMiss(double) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_ColorOcTree_octomap_ColorOcTreeNode_t, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Static methods defined here:

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMetricMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

genericMapParams

insertionOptions

likelihoodOptions

renderingOptions

Data and other attributes defined here:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octom...ree_octomap_ColorOcTreeNode_t.TInsertionOptions'>

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octom...ee_octomap_ColorOcTreeNode_t.TLikelihoodOptions'>

TRenderingOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octom...ree_octomap_ColorOcTreeNode_t.TRenderingOptions'>

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

clone(...)
clone(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Returns a deep copy (clone) of the object, indepently of its class. C++: mrpt::rtti::CObject::clone() const --> class mrpt::rtti::CObject *

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t(CMetricMap)


Method resolution order:

COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMetricMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(self, /, *args, **kwargs)
Initialize self.  See help(type(self)) for accurate signature.

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> str C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::asString() const --> std::string

assign(...)
assign(*args, **kwargs) Overloaded function. 1. assign(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, : mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::operator=(const class mrpt::maps::COctoMapBase<class octomap::OcTree, class octomap::OcTreeNode> &) --> class mrpt::maps::COctoMapBase<class octomap::OcTree, class octomap::OcTreeNode> & 2. assign(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, : mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt.pymrpt.mrpt.maps.CMetricMap C++: mrpt::maps::CMetricMap::operator=(const class mrpt::maps::CMetricMap &) --> class mrpt::maps::CMetricMap &

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

castRay(...)
castRay(*args, **kwargs) Overloaded function. 1. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>) -> bool 2. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>, ignoreUnknownCells: bool) -> bool 3. castRay(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, origin: mrpt::math::TPoint3D_<double>, direction: mrpt::math::TPoint3D_<double>, end: mrpt::math::TPoint3D_<double>, ignoreUnknownCells: bool, maxRange: float) -> bool C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::castRay(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, struct mrpt::math::TPoint3D_<double> &, bool, double) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float Computes the ratio in [0,1] of correspondences between "this" and the "otherMap" map, whose 6D pose relative to "this" is "otherMapPose"    In the case of a multi-metric map, this returns the average between the maps. This method always return 0 for grid maps.       [IN] The other map to compute the matching with.   [IN] The 6D pose of the other map as seen from "this".         [IN] Matching parameters The matching ratio [0,1] determineMatching2D C++: mrpt::maps::CMetricMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsOctoMapVoxels(...)
getAsOctoMapVoxels(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, gl_obj: mrpt.pymrpt.mrpt.opengl.COctoMapVoxels) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getAsOctoMapVoxels(class mrpt::opengl::COctoMapVoxels &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

getClampingThresMax(...)
getClampingThresMax(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getClampingThresMax() const --> double

getClampingThresMaxLog(...)
getClampingThresMaxLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getClampingThresMaxLog() const --> float

getClampingThresMin(...)
getClampingThresMin(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getClampingThresMin() const --> double

getClampingThresMinLog(...)
getClampingThresMinLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getClampingThresMinLog() const --> float

getOccupancyThres(...)
getOccupancyThres(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getOccupancyThres() const --> double

getOccupancyThresLog(...)
getOccupancyThresLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getOccupancyThresLog() const --> float

getPointOccupancy(...)
getPointOccupancy(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, x: float, y: float, z: float, prob_occupancy: float) -> bool C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getPointOccupancy(const float, const float, const float, double &) const --> bool

getProbHit(...)
getProbHit(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getProbHit() const --> double

getProbHitLog(...)
getProbHitLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getProbHitLog() const --> float

getProbMiss(...)
getProbMiss(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getProbMiss() const --> double

getProbMissLog(...)
getProbMissLog(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> float C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getProbMissLog() const --> float

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, o: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, sf: mrpt.pymrpt.mrpt.obs.CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

insertPointCloud(...)
insertPointCloud(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, ptMap: mrpt.pymrpt.mrpt.maps.CPointsMap, sensor_x: float, sensor_y: float, sensor_z: float) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::insertPointCloud(const class mrpt::maps::CPointsMap &, const float, const float, const float) --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CMetricMap::isEmpty() const --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, Map: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, Map: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(*args, **kwargs) Overloaded function. 1. saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, filNamePrefix: str) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::saveMetricMapRepresentationToFile(const std::string &) const --> void 2. saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface). C++: mrpt::maps::CMetricMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

setClampingThresMax(...)
setClampingThresMax(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, thresProb: float) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::setClampingThresMax(double) --> void

setClampingThresMin(...)
setClampingThresMin(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, thresProb: float) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::setClampingThresMin(double) --> void

setOccupancyThres(...)
setOccupancyThres(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, prob: float) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::setOccupancyThres(double) --> void

setProbHit(...)
setProbHit(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, prob: float) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::setProbHit(double) --> void

setProbMiss(...)
setProbMiss(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, prob: float) -> None C++: mrpt::maps::COctoMapBase<octomap::OcTree, octomap::OcTreeNode>::setProbMiss(double) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Static methods defined here:

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CMetricMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

genericMapParams

insertionOptions

likelihoodOptions

renderingOptions

Data and other attributes defined here:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t.TInsertionOptions'>

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t.TLikelihoodOptions'>

TRenderingOptions = <class 'mrpt.pymrpt.mrpt.maps.COctoMapBase_octomap_OcTree_octomap_OcTreeNode_t.TRenderingOptions'>

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

clone(...)
clone(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Returns a deep copy (clone) of the object, indepently of its class. C++: mrpt::rtti::CObject::clone() const --> class mrpt::rtti::CObject *

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CPointCloudFilterBase(pybind11_builtins.pybind11_object)

    Virtual base class for all point-cloud filtering algorithm. See derived classes for implementations. CPointsMap

Method resolution order:

CPointCloudFilterBase

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase, arg0: mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase, : mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase) -> mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase C++: mrpt::maps::CPointCloudFilterBase::operator=(const class mrpt::maps::CPointCloudFilterBase &) --> class mrpt::maps::CPointCloudFilterBase &

filter(...)
filter(*args, **kwargs) Overloaded function. 1. filter(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase, inout_pointcloud: mrpt.pymrpt.mrpt.maps.CPointsMap, pc_timestamp: mrpt.pymrpt.std.chrono.time_point_mrpt_Clock_std_chrono_duration_long_std_ratio_1_10000000_t, pc_reference_pose: mrpt.pymrpt.mrpt.poses.CPose3D) -> None 2. filter(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase, inout_pointcloud: mrpt.pymrpt.mrpt.maps.CPointsMap, pc_timestamp: mrpt.pymrpt.std.chrono.time_point_mrpt_Clock_std_chrono_duration_long_std_ratio_1_10000000_t, pc_reference_pose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt::maps::CPointCloudFilterBase::TExtraFilterParams) -> None Apply the filtering algorithm to the pointcloud. C++: mrpt::maps::CPointCloudFilterBase::filter(class mrpt::maps::CPointsMap *, const mrpt::Clock::time_point, const class mrpt::poses::CPose3D &, struct mrpt::maps::CPointCloudFilterBase::TExtraFilterParams *) --> void

Data and other attributes defined here:

TExtraFilterParams = <class 'mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase.TExtraFilterParams'>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CPointCloudFilterByDistance(CPointCloudFilterBase)

    Implementation of pointcloud filtering based on requisities for minimum neigbouring points in both,   the current timestamp and a previous one. CPointsMap

Method resolution order:

CPointCloudFilterByDistance

CPointCloudFilterBase

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance, arg0: mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance, arg0: mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance, : mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance) -> mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance C++: mrpt::maps::CPointCloudFilterByDistance::operator=(const class mrpt::maps::CPointCloudFilterByDistance &) --> class mrpt::maps::CPointCloudFilterByDistance &

filter(...)
filter(*args, **kwargs) Overloaded function. 1. filter(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance, inout_pointcloud: mrpt.pymrpt.mrpt.maps.CPointsMap, pc_timestamp: mrpt.pymrpt.std.chrono.time_point_mrpt_Clock_std_chrono_duration_long_std_ratio_1_10000000_t, pc_reference_pose: mrpt.pymrpt.mrpt.poses.CPose3D) -> None 2. filter(self: mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance, inout_pointcloud: mrpt.pymrpt.mrpt.maps.CPointsMap, pc_timestamp: mrpt.pymrpt.std.chrono.time_point_mrpt_Clock_std_chrono_duration_long_std_ratio_1_10000000_t, pc_reference_pose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase.TExtraFilterParams) -> None C++: mrpt::maps::CPointCloudFilterByDistance::filter(class mrpt::maps::CPointsMap *, const mrpt::Clock::time_point, const class mrpt::poses::CPose3D &, struct mrpt::maps::CPointCloudFilterBase::TExtraFilterParams *) --> void

Data descriptors defined here:

options

Data and other attributes defined here:

TOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointCloudFilterByDistance.TOptions'>

Data and other attributes inherited from CPointCloudFilterBase:

TExtraFilterParams = <class 'mrpt.pymrpt.mrpt.maps.CPointCloudFilterBase.TExtraFilterParams'>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CPointsMap(CMetricMap, mrpt.pymrpt.mrpt.opengl.PLY_Importer, mrpt.pymrpt.mrpt.opengl.PLY_Exporter)

    A cloud of points in 2D or 3D, which can be built from a sequence of laser scans or other sensors. This is a virtual class, thus only a derived class can be instantiated by the user. The user most usually wants to use CSimplePointsMap. This class implements generic version of mrpt::maps::CMetric::insertObservation() accepting these types of sensory data:   - mrpt::obs::CObservation2DRangeScan: 2D range scans   - mrpt::obs::CObservation3DRangeScan: 3D range scans (Kinect, etc...)   - mrpt::obs::CObservationRange: IRs, Sonars, etc.   - mrpt::obs::CObservationVelodyneScan   - mrpt::obs::CObservationPointCloud Loading and saving in the standard LAS LiDAR point cloud format is supported by installing `libLAS` and including the header `<mrpt/maps/CPointsMaps_liblas.h>` in your program. Since MRPT 1.5.0 there is no need to build MRPT against libLAS to use this feature. See LAS functions in CMetricMap, CPoint, CSerializable

Method resolution order:

CPointsMap

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.opengl.PLY_Importer

mrpt.pymrpt.mrpt.opengl.PLY_Exporter

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CPointsMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__iadd__(...)
__iadd__(self: mrpt.pymrpt.mrpt.maps.CPointsMap, anotherMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Inserts another map into this one. insertAnotherMap() C++: mrpt::maps::CPointsMap::operator+=(const class mrpt::maps::CPointsMap &) --> void

__init__(self, /, *args, **kwargs)
Initialize self.  See help(type(self)) for accurate signature.

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> str Returns a short description of the map. C++: mrpt::maps::CPointsMap::asString() const --> std::string

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CPointsMap, o: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.maps.CPointsMap C++: mrpt::maps::CPointsMap::operator=(const class mrpt::maps::CPointsMap &) --> class mrpt::maps::CPointsMap &

boundingBox(...)
boundingBox(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.math.TBoundingBox_float_t Computes the bounding box of all the points, or (0,0 ,0,0, 0,0) if there are no points.   Results are cached unless the map is somehow modified to avoid repeated calculations. C++: mrpt::maps::CPointsMap::boundingBox() const --> struct mrpt::math::TBoundingBox_<float>

changeCoordinatesReference(...)
changeCoordinatesReference(*args, **kwargs) Overloaded function. 1. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose2D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose2D &) --> void 2. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose3D &) --> void 3. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, other: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Copy all the points from "other" map to "this", replacing each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::maps::CPointsMap &, const class mrpt::poses::CPose3D &) --> void

clipOutOfRange(...)
clipOutOfRange(self: mrpt.pymrpt.mrpt.maps.CPointsMap, point: mrpt::math::TPoint2D_<double>, maxRange: float) -> None Delete points which are more far than "maxRange" away from the given "point". C++: mrpt::maps::CPointsMap::clipOutOfRange(const struct mrpt::math::TPoint2D_<double> &, float) --> void

clipOutOfRangeInZ(...)
clipOutOfRangeInZ(self: mrpt.pymrpt.mrpt.maps.CPointsMap, zMin: float, zMax: float) -> None Delete points out of the given "z" axis range have been removed. C++: mrpt::maps::CPointsMap::clipOutOfRangeInZ(float, float) --> void

compute3DDistanceToMesh(...)
compute3DDistanceToMesh(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap2: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, maxDistForCorrespondence: float, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, correspondencesRatio: float) -> None Computes the matchings between this and another 3D points map.            This method matches each point in the other map with the centroid of the          3 closest points in 3D            from this map (if the distance is below a defined threshold).                                           [IN] The other map to compute the          matching with.                                   [IN] The pose of the other map as seen          from "this".    [IN] Maximum 2D linear distance          between two points to be matched.                           [OUT] The detected matchings pairs.                   [OUT] The ratio [0,1] of points in          otherMap with at least one correspondence. determineMatching3D C++: mrpt::maps::CPointsMap::compute3DDistanceToMesh(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, float, class mrpt::tfest::TMatchingPairListTempl<float> &, float &) --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float C++: mrpt::maps::CPointsMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

empty(...)
empty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool STL-like method to check whether the map is empty: C++: mrpt::maps::CPointsMap::empty() const --> bool

enableFilterByHeight(...)
enableFilterByHeight(*args, **kwargs) Overloaded function. 1. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, enable: bool) -> None Enable/disable the filter-by-height functionality setHeightFilterLevels Default upon construction is disabled. C++: mrpt::maps::CPointsMap::enableFilterByHeight(bool) --> void

extractCylinder(...)
extractCylinder(self: mrpt.pymrpt.mrpt.maps.CPointsMap, center: mrpt::math::TPoint2D_<double>, radius: float, zmin: float, zmax: float, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Extracts the points in the map within a cylinder in 3D defined the provided radius and zmin/zmax values. C++: mrpt::maps::CPointsMap::extractCylinder(const struct mrpt::math::TPoint2D_<double> &, const double, const double, const double, class mrpt::maps::CPointsMap *) --> void

extractPoints(...)
extractPoints(*args, **kwargs) Overloaded function. 1. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float) -> None 3. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float) -> None 4. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float, B: float) -> None Extracts the points in the map within the area defined by two corners.   The points are coloured according the R,G,B input data. C++: mrpt::maps::CPointsMap::extractPoints(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, class mrpt::maps::CPointsMap *, double, double, double) --> void

getHeightFilterLevels(...)
getHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Get the min/max Z levels for points to be actually inserted in the map enableFilterByHeight, setHeightFilterLevels C++: mrpt::maps::CPointsMap::getHeightFilterLevels(double &, double &) const --> void

getLargestDistanceFromOrigin(...)
getLargestDistanceFromOrigin(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> float This method returns the largest distance from the origin to any of the points, such as a sphere centered at the origin with this radius cover ALL the points in the map (the results are buffered, such as, if the map is not modified, the second call will be much faster than the first one). C++: mrpt::maps::CPointsMap::getLargestDistanceFromOrigin() const --> float

getLargestDistanceFromOriginNoRecompute(...)
getLargestDistanceFromOriginNoRecompute(self: mrpt.pymrpt.mrpt.maps.CPointsMap, output_is_valid: bool) -> float Like  but returns in = false if the distance was not already computed, skipping its computation then, unlike getLargestDistanceFromOrigin() C++: mrpt::maps::CPointsMap::getLargestDistanceFromOriginNoRecompute(bool &) const --> float

getPoint(...)
getPoint(*args, **kwargs) Overloaded function. 1. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Access to a given point from map, as a 2D point. First index is 0. Throws std::exception on index out of bound. setPoint, getPointFast C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &, float &) const --> void 2. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &) const --> void 3. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &, double &) const --> void 4. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &) const --> void 5. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint2D_<double> &) const --> void 6. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint3D_<double> &) const --> void

getPointFast(...)
getPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Just like  but without checking out-of-bound index and without returning the point weight, just XYZ. C++: mrpt::maps::CPointsMap::getPointFast(size_t, float &, float &, float &) const --> void

getPointRGB(...)
getPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float, R: float, G: float, B: float) -> None Access to a given point from map, and its colors, if the map defines them (othersise, R=G=B=1.0). First index is 0. The return value is the weight of the point (the times it has been fused) Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMap::getPointRGB(size_t, float &, float &, float &, float &, float &, float &) const --> void

getPointWeight(...)
getPointWeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int) -> int Gets the point weight, which is ignored in all classes (defaults to 1) but in those which actually store that field (Note: No checks are done for out-of-bounds index).   setPointWeight C++: mrpt::maps::CPointsMap::getPointWeight(size_t) const --> unsigned int

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CPointsMap, outObj: mrpt::opengl::CSetOfObjects) -> None Returns a 3D object representing the map.   The color of the points is controlled by renderOptions C++: mrpt::maps::CPointsMap::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

hasColorPoints(...)
hasColorPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Returns true if the point map has a color field for each point C++: mrpt::maps::CPointsMap::hasColorPoints() const --> bool

insertAnotherMap(...)
insertAnotherMap(*args, **kwargs) Overloaded function. 1. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> None 2. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D, filterOutPointsAtZero: bool) -> None Insert the contents of another map into this one with some geometric transformation, without fusing close points. The other map whose points are to be inserted into this one. The pose of the other map in the coordinates of THIS map If true, points at (0,0,0) (in the frame of reference of `otherMap`) will be assumed to be invalid and will not be copied. fuseWith, addFrom C++: mrpt::maps::CPointsMap::insertAnotherMap(const class mrpt::maps::CPointsMap *, const class mrpt::poses::CPose3D &, const bool) --> void

insertPoint(...)
insertPoint(*args, **kwargs) Overloaded function. 1. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float) -> None 2. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float, z: float) -> None Provides a way to insert (append) individual points into the map: the missing fields of child classes (color, weight, etc) are left to their default values C++: mrpt::maps::CPointsMap::insertPoint(float, float, float) --> void 3. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::insertPoint(const struct mrpt::math::TPoint3D_<double> &) --> void

insertPointFast(...)
insertPointFast(*args, **kwargs) Overloaded function. 1. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float) -> None 2. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float, z: float) -> None The virtual method for  *without* calling mark_as_modified()    C++: mrpt::maps::CPointsMap::insertPointFast(float, float, float) --> void

insertPointRGB(...)
insertPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float, z: float, R: float, G: float, B: float) -> None overload (RGB data is ignored in classes without color information) C++: mrpt::maps::CPointsMap::insertPointRGB(float, float, float, float, float, float) --> void

internal_computeObservationLikelihood(...)
internal_computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CPointsMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float @} C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

internal_computeObservationLikelihoodPointCloud3D(...)
internal_computeObservationLikelihoodPointCloud3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, pc_in_map: mrpt.pymrpt.mrpt.poses.CPose3D, xs: float, ys: float, zs: float, num_pts: int) -> float C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihoodPointCloud3D(const class mrpt::poses::CPose3D &, const float *, const float *, const float *, const unsigned long) const --> double

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CPointsMap::isEmpty() const --> bool

isFilterByHeightEnabled(...)
isFilterByHeightEnabled(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Return whether filter-by-height is enabled enableFilterByHeight C++: mrpt::maps::CPointsMap::isFilterByHeightEnabled() const --> bool

kdtree_distance(...)
kdtree_distance(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p1: float, idx_p2: int, size: int) -> float Returns the distance between the vector "p1[0:size-1]" and the data point with index "idx_p2" stored in the class: C++: mrpt::maps::CPointsMap::kdtree_distance(const float *, size_t, size_t) const --> float

kdtree_get_point_count(...)
kdtree_get_point_count(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Must return the number of data points C++: mrpt::maps::CPointsMap::kdtree_get_point_count() const --> size_t

kdtree_get_pt(...)
kdtree_get_pt(self: mrpt.pymrpt.mrpt.maps.CPointsMap, idx: int, dim: int) -> float Returns the dim'th component of the idx'th point in the class: C++: mrpt::maps::CPointsMap::kdtree_get_pt(size_t, int) const --> float

load2D_from_text_file(...)
load2D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y" coordinate pair, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load2D_from_text_file(const std::string &) --> bool

load2Dor3D_from_text_file(...)
load2Dor3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str, is_3D: bool) -> bool 2D or 3D generic implementation of  and load3D_from_text_file C++: mrpt::maps::CPointsMap::load2Dor3D_from_text_file(const std::string &, const bool) --> bool

load3D_from_text_file(...)
load3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y Z" coordinate tuple, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load3D_from_text_file(const std::string &) --> bool

mark_as_modified(...)
mark_as_modified(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Users normally don't need to call this. Called by this class or children classes, set m_largestDistanceFromOriginIsUpdated=false, invalidates the kd-tree cache, and such. C++: mrpt::maps::CPointsMap::mark_as_modified() const --> void

reserve(...)
reserve(self: mrpt.pymrpt.mrpt.maps.CPointsMap, newLength: int) -> None Reserves memory for a given number of points: the size of the map does not change, it only reserves the memory.   This is useful for situations where it is approximately known the final size of the map. This method is more   efficient than constantly increasing the size of the buffers. Refer to the STL C++ library's "reserve" methods. C++: mrpt::maps::CPointsMap::reserve(size_t) --> void

resize(...)
resize(self: mrpt.pymrpt.mrpt.maps.CPointsMap, newLength: int) -> None Resizes all point buffers so they can hold the given number of points: newly created points are set to default values,   and old contents are not changed. reserve, setPoint, setPointFast, setSize C++: mrpt::maps::CPointsMap::resize(size_t) --> void

save2D_to_text_file(...)
save2D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y" point coordinates.                 Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save2D_to_text_file(const std::string &) const --> bool

save3D_to_text_file(...)
save3D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y Z" point coordinates.      Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save3D_to_text_file(const std::string &) const --> bool

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CPointsMap, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface) C++: mrpt::maps::CPointsMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

setHeightFilterLevels(...)
setHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Set the min/max Z levels for points to be actually inserted in the map (only if  was called before). C++: mrpt::maps::CPointsMap::setHeightFilterLevels(const double, const double) --> void

setPoint(...)
setPoint(*args, **kwargs) Overloaded function. 1. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes a given point from map, with Z defaulting to 0 if not provided. Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float, float) --> void 2. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint2D_<double> &) --> void 3. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint3D_<double> &) --> void 4. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float) --> void

setPointFast(...)
setPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes the coordinates of the given point (0-based index), *without* checking for out-of-bounds and *without* calling mark_as_modified(). Also, color, intensity, or other data is left unchanged. setPoint C++: mrpt::maps::CPointsMap::setPointFast(size_t, float, float, float) --> void

setPointRGB(...)
setPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float, R: float, G: float, B: float) -> None overload (RGB data is ignored in classes without color information) C++: mrpt::maps::CPointsMap::setPointRGB(size_t, float, float, float, float, float, float) --> void

setPointWeight(...)
setPointWeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, w: int) -> None Sets the point weight, which is ignored in all classes but those which actually store that field (Note: No checks are done for out-of-bounds index). getPointWeight C++: mrpt::maps::CPointsMap::setPointWeight(size_t, unsigned long) --> void

setSize(...)
setSize(self: mrpt.pymrpt.mrpt.maps.CPointsMap, newLength: int) -> None Resizes all point buffers so they can hold the given number of points, *erasing* all previous contents   and leaving all points to default values. reserve, setPoint, setPointFast, setSize C++: mrpt::maps::CPointsMap::setSize(size_t) --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Returns the number of stored points in the map. C++: mrpt::maps::CPointsMap::size() const --> size_t

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondence(float, float) const --> float

squareDistanceToClosestCorrespondenceT(...)
squareDistanceToClosestCorrespondenceT(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p0: mrpt::math::TPoint2D_<double>) -> float C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondenceT(const struct mrpt::math::TPoint2D_<double> &) const --> float

Static methods defined here:

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CPointsMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

insertionOptions

likelihoodOptions

renderOptions

Data and other attributes defined here:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TInsertionOptions'>
With this struct options are provided to the observation insertion process. CObservation::insertIntoPointsMap

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TLikelihoodOptions'>
Options used when evaluating "computeObservationLikelihood" in the derived classes. CObservation::computeObservationLikelihood

TRenderOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TRenderOptions'>
Rendering options, used in getAs3DObject()

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

clone(...)
clone(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Returns a deep copy (clone) of the object, indepently of its class. C++: mrpt::rtti::CObject::clone() const --> class mrpt::rtti::CObject *

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Importer:

getLoadPLYErrorString(...)
getLoadPLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Importer::getLoadPLYErrorString() const --> std::string

loadFromPlyFile(...)
loadFromPlyFile(*args, **kwargs) Overloaded function. 1. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str) -> bool 2. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str]) -> bool 3. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str], file_obj_info: List[str]) -> bool Loads from a PLY file. The filename to open. It can be either in binary or text format. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error in the file format or reading it. To obtain more details on the error you can call getLoadPLYErrorString() C++: mrpt::opengl::PLY_Importer::loadFromPlyFile(const std::string &, class std::vector<std::string > *, class std::vector<std::string > *) --> bool

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Exporter:

getSavePLYErrorString(...)
getSavePLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Exporter::getSavePLYErrorString() const --> std::string

saveToPlyFile(...)
saveToPlyFile(*args, **kwargs) Overloaded function. 1. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str) -> bool 2. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool) -> bool 3. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str]) -> bool 4. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str], file_obj_info: List[str]) -> bool Saves to a PLY file. The filename to be saved. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error writing the file. To obtain more details on the error you can call getSavePLYErrorString() C++: mrpt::opengl::PLY_Exporter::saveToPlyFile(const std::string &, bool, const class std::vector<std::string > &, const class std::vector<std::string > &) const --> bool

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CPointsMapXYZI(CPointsMap)

    A map of 3D points with reflectance/intensity (float). mrpt::maps::CPointsMap, mrpt::maps::CMetricMap

Method resolution order:

CPointsMapXYZI

CPointsMap

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.opengl.PLY_Importer

mrpt.pymrpt.mrpt.opengl.PLY_Exporter

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CPointsMapXYZI::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, o: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, arg0: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI) -> None 4. __init__(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, arg0: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI) -> None

assign(...)
assign(*args, **kwargs) Overloaded function. 1. assign(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, o: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.maps.CPointsMapXYZI C++: mrpt::maps::CPointsMapXYZI::operator=(const class mrpt::maps::CPointsMap &) --> class mrpt::maps::CPointsMapXYZI & 2. assign(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, o: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI) -> mrpt.pymrpt.mrpt.maps.CPointsMapXYZI C++: mrpt::maps::CPointsMapXYZI::operator=(const class mrpt::maps::CPointsMapXYZI &) --> class mrpt::maps::CPointsMapXYZI &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CPointsMapXYZI::clone() const --> class mrpt::rtti::CObject *

getPointIntensity(...)
getPointIntensity(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, index: int) -> float Retrieves a point intensity (range [0,1]) C++: mrpt::maps::CPointsMapXYZI::getPointIntensity(size_t) const --> float

getPointIntensity_fast(...)
getPointIntensity_fast(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, index: int) -> float Like  but without checking for out-of-index erors C++: mrpt::maps::CPointsMapXYZI::getPointIntensity_fast(size_t) const --> float

getPointRGB(...)
getPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, index: int, x: float, y: float, z: float, R_intensity: float, G_intensity: float, B_intensity: float) -> None Retrieves a point and its color (colors range is [0,1]) C++: mrpt::maps::CPointsMapXYZI::getPointRGB(size_t, float &, float &, float &, float &, float &, float &) const --> void

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Override of the default 3D scene builder to account for the individual points' color. C++: mrpt::maps::CPointsMapXYZI::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

hasColorPoints(...)
hasColorPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI) -> bool Returns true if the point map has a color field for each point C++: mrpt::maps::CPointsMapXYZI::hasColorPoints() const --> bool

insertPointFast(...)
insertPointFast(*args, **kwargs) Overloaded function. 1. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, x: float, y: float) -> None 2. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, x: float, y: float, z: float) -> None The virtual method for  *without* calling mark_as_modified()    C++: mrpt::maps::CPointsMapXYZI::insertPointFast(float, float, float) --> void

insertPointRGB(...)
insertPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, x: float, y: float, z: float, R_intensity: float, G_ignored: float, B_ignored: float) -> None Adds a new point given its coordinates and color (colors range is [0,1]) C++: mrpt::maps::CPointsMapXYZI::insertPointRGB(float, float, float, float, float, float) --> void

loadFromKittiVelodyneFile(...)
loadFromKittiVelodyneFile(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, filename: str) -> bool Loads from a Kitti dataset Velodyne scan binary file. The file can be gz compressed (only enabled if the filename ends in ".gz" to prevent spurious false autodetection of gzip files). true on success C++: mrpt::maps::CPointsMapXYZI::loadFromKittiVelodyneFile(const std::string &) --> bool

loadXYZI_from_text_file(...)
loadXYZI_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, file: str) -> bool Loads from a text file, each line having "X Y Z I", I in [0,1]. Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMapXYZI::loadXYZI_from_text_file(const std::string &) --> bool

reserve(...)
reserve(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, newLength: int) -> None from CPointsMap         @{ C++: mrpt::maps::CPointsMapXYZI::reserve(size_t) --> void

resize(...)
resize(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, newLength: int) -> None C++: mrpt::maps::CPointsMapXYZI::resize(size_t) --> void

saveToKittiVelodyneFile(...)
saveToKittiVelodyneFile(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, filename: str) -> bool C++: mrpt::maps::CPointsMapXYZI::saveToKittiVelodyneFile(const std::string &) const --> bool

saveXYZI_to_text_file(...)
saveXYZI_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, file: str) -> bool Save to a text file. In each line contains X Y Z (meters) I (intensity) Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMapXYZI::saveXYZI_to_text_file(const std::string &) const --> bool

setPointColor_fast(...)
setPointColor_fast(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, index: int, R: float, G: float, B: float) -> None Like  but without checking for out-of-index erors C++: mrpt::maps::CPointsMapXYZI::setPointColor_fast(size_t, float, float, float) --> void

setPointIntensity(...)
setPointIntensity(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, index: int, intensity: float) -> None Changes the intensity of a given point from the map. First index is 0. Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMapXYZI::setPointIntensity(size_t, float) --> void

setPointRGB(...)
setPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, index: int, x: float, y: float, z: float, R_intensity: float, G_ignored: float, B_ignored: float) -> None Changes a given point from map. First index is 0. Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMapXYZI::setPointRGB(size_t, float, float, float, float, float, float) --> void

setSize(...)
setSize(self: mrpt.pymrpt.mrpt.maps.CPointsMapXYZI, newLength: int) -> None C++: mrpt::maps::CPointsMapXYZI::setSize(size_t) --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CPointsMapXYZI::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CPointsMapXYZI::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data and other attributes defined here:

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CPointsMapXYZI.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CPointsMapXYZI.TMapDefinitionBase'>

Methods inherited from CPointsMap:

__iadd__(...)
__iadd__(self: mrpt.pymrpt.mrpt.maps.CPointsMap, anotherMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Inserts another map into this one. insertAnotherMap() C++: mrpt::maps::CPointsMap::operator+=(const class mrpt::maps::CPointsMap &) --> void

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> str Returns a short description of the map. C++: mrpt::maps::CPointsMap::asString() const --> std::string

boundingBox(...)
boundingBox(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.math.TBoundingBox_float_t Computes the bounding box of all the points, or (0,0 ,0,0, 0,0) if there are no points.   Results are cached unless the map is somehow modified to avoid repeated calculations. C++: mrpt::maps::CPointsMap::boundingBox() const --> struct mrpt::math::TBoundingBox_<float>

changeCoordinatesReference(...)
changeCoordinatesReference(*args, **kwargs) Overloaded function. 1. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose2D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose2D &) --> void 2. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose3D &) --> void 3. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, other: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Copy all the points from "other" map to "this", replacing each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::maps::CPointsMap &, const class mrpt::poses::CPose3D &) --> void

clipOutOfRange(...)
clipOutOfRange(self: mrpt.pymrpt.mrpt.maps.CPointsMap, point: mrpt::math::TPoint2D_<double>, maxRange: float) -> None Delete points which are more far than "maxRange" away from the given "point". C++: mrpt::maps::CPointsMap::clipOutOfRange(const struct mrpt::math::TPoint2D_<double> &, float) --> void

clipOutOfRangeInZ(...)
clipOutOfRangeInZ(self: mrpt.pymrpt.mrpt.maps.CPointsMap, zMin: float, zMax: float) -> None Delete points out of the given "z" axis range have been removed. C++: mrpt::maps::CPointsMap::clipOutOfRangeInZ(float, float) --> void

compute3DDistanceToMesh(...)
compute3DDistanceToMesh(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap2: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, maxDistForCorrespondence: float, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, correspondencesRatio: float) -> None Computes the matchings between this and another 3D points map.            This method matches each point in the other map with the centroid of the          3 closest points in 3D            from this map (if the distance is below a defined threshold).                                           [IN] The other map to compute the          matching with.                                   [IN] The pose of the other map as seen          from "this".    [IN] Maximum 2D linear distance          between two points to be matched.                           [OUT] The detected matchings pairs.                   [OUT] The ratio [0,1] of points in          otherMap with at least one correspondence. determineMatching3D C++: mrpt::maps::CPointsMap::compute3DDistanceToMesh(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, float, class mrpt::tfest::TMatchingPairListTempl<float> &, float &) --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float C++: mrpt::maps::CPointsMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

empty(...)
empty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool STL-like method to check whether the map is empty: C++: mrpt::maps::CPointsMap::empty() const --> bool

enableFilterByHeight(...)
enableFilterByHeight(*args, **kwargs) Overloaded function. 1. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, enable: bool) -> None Enable/disable the filter-by-height functionality setHeightFilterLevels Default upon construction is disabled. C++: mrpt::maps::CPointsMap::enableFilterByHeight(bool) --> void

extractCylinder(...)
extractCylinder(self: mrpt.pymrpt.mrpt.maps.CPointsMap, center: mrpt::math::TPoint2D_<double>, radius: float, zmin: float, zmax: float, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Extracts the points in the map within a cylinder in 3D defined the provided radius and zmin/zmax values. C++: mrpt::maps::CPointsMap::extractCylinder(const struct mrpt::math::TPoint2D_<double> &, const double, const double, const double, class mrpt::maps::CPointsMap *) --> void

extractPoints(...)
extractPoints(*args, **kwargs) Overloaded function. 1. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float) -> None 3. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float) -> None 4. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float, B: float) -> None Extracts the points in the map within the area defined by two corners.   The points are coloured according the R,G,B input data. C++: mrpt::maps::CPointsMap::extractPoints(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, class mrpt::maps::CPointsMap *, double, double, double) --> void

getHeightFilterLevels(...)
getHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Get the min/max Z levels for points to be actually inserted in the map enableFilterByHeight, setHeightFilterLevels C++: mrpt::maps::CPointsMap::getHeightFilterLevels(double &, double &) const --> void

getLargestDistanceFromOrigin(...)
getLargestDistanceFromOrigin(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> float This method returns the largest distance from the origin to any of the points, such as a sphere centered at the origin with this radius cover ALL the points in the map (the results are buffered, such as, if the map is not modified, the second call will be much faster than the first one). C++: mrpt::maps::CPointsMap::getLargestDistanceFromOrigin() const --> float

getLargestDistanceFromOriginNoRecompute(...)
getLargestDistanceFromOriginNoRecompute(self: mrpt.pymrpt.mrpt.maps.CPointsMap, output_is_valid: bool) -> float Like  but returns in = false if the distance was not already computed, skipping its computation then, unlike getLargestDistanceFromOrigin() C++: mrpt::maps::CPointsMap::getLargestDistanceFromOriginNoRecompute(bool &) const --> float

getPoint(...)
getPoint(*args, **kwargs) Overloaded function. 1. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Access to a given point from map, as a 2D point. First index is 0. Throws std::exception on index out of bound. setPoint, getPointFast C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &, float &) const --> void 2. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &) const --> void 3. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &, double &) const --> void 4. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &) const --> void 5. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint2D_<double> &) const --> void 6. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint3D_<double> &) const --> void

getPointFast(...)
getPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Just like  but without checking out-of-bound index and without returning the point weight, just XYZ. C++: mrpt::maps::CPointsMap::getPointFast(size_t, float &, float &, float &) const --> void

getPointWeight(...)
getPointWeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int) -> int Gets the point weight, which is ignored in all classes (defaults to 1) but in those which actually store that field (Note: No checks are done for out-of-bounds index).   setPointWeight C++: mrpt::maps::CPointsMap::getPointWeight(size_t) const --> unsigned int

insertAnotherMap(...)
insertAnotherMap(*args, **kwargs) Overloaded function. 1. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> None 2. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D, filterOutPointsAtZero: bool) -> None Insert the contents of another map into this one with some geometric transformation, without fusing close points. The other map whose points are to be inserted into this one. The pose of the other map in the coordinates of THIS map If true, points at (0,0,0) (in the frame of reference of `otherMap`) will be assumed to be invalid and will not be copied. fuseWith, addFrom C++: mrpt::maps::CPointsMap::insertAnotherMap(const class mrpt::maps::CPointsMap *, const class mrpt::poses::CPose3D &, const bool) --> void

insertPoint(...)
insertPoint(*args, **kwargs) Overloaded function. 1. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float) -> None 2. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float, z: float) -> None Provides a way to insert (append) individual points into the map: the missing fields of child classes (color, weight, etc) are left to their default values C++: mrpt::maps::CPointsMap::insertPoint(float, float, float) --> void 3. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::insertPoint(const struct mrpt::math::TPoint3D_<double> &) --> void

internal_computeObservationLikelihood(...)
internal_computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CPointsMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float @} C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

internal_computeObservationLikelihoodPointCloud3D(...)
internal_computeObservationLikelihoodPointCloud3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, pc_in_map: mrpt.pymrpt.mrpt.poses.CPose3D, xs: float, ys: float, zs: float, num_pts: int) -> float C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihoodPointCloud3D(const class mrpt::poses::CPose3D &, const float *, const float *, const float *, const unsigned long) const --> double

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CPointsMap::isEmpty() const --> bool

isFilterByHeightEnabled(...)
isFilterByHeightEnabled(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Return whether filter-by-height is enabled enableFilterByHeight C++: mrpt::maps::CPointsMap::isFilterByHeightEnabled() const --> bool

kdtree_distance(...)
kdtree_distance(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p1: float, idx_p2: int, size: int) -> float Returns the distance between the vector "p1[0:size-1]" and the data point with index "idx_p2" stored in the class: C++: mrpt::maps::CPointsMap::kdtree_distance(const float *, size_t, size_t) const --> float

kdtree_get_point_count(...)
kdtree_get_point_count(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Must return the number of data points C++: mrpt::maps::CPointsMap::kdtree_get_point_count() const --> size_t

kdtree_get_pt(...)
kdtree_get_pt(self: mrpt.pymrpt.mrpt.maps.CPointsMap, idx: int, dim: int) -> float Returns the dim'th component of the idx'th point in the class: C++: mrpt::maps::CPointsMap::kdtree_get_pt(size_t, int) const --> float

load2D_from_text_file(...)
load2D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y" coordinate pair, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load2D_from_text_file(const std::string &) --> bool

load2Dor3D_from_text_file(...)
load2Dor3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str, is_3D: bool) -> bool 2D or 3D generic implementation of  and load3D_from_text_file C++: mrpt::maps::CPointsMap::load2Dor3D_from_text_file(const std::string &, const bool) --> bool

load3D_from_text_file(...)
load3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y Z" coordinate tuple, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load3D_from_text_file(const std::string &) --> bool

mark_as_modified(...)
mark_as_modified(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Users normally don't need to call this. Called by this class or children classes, set m_largestDistanceFromOriginIsUpdated=false, invalidates the kd-tree cache, and such. C++: mrpt::maps::CPointsMap::mark_as_modified() const --> void

save2D_to_text_file(...)
save2D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y" point coordinates.                 Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save2D_to_text_file(const std::string &) const --> bool

save3D_to_text_file(...)
save3D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y Z" point coordinates.      Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save3D_to_text_file(const std::string &) const --> bool

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CPointsMap, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface) C++: mrpt::maps::CPointsMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

setHeightFilterLevels(...)
setHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Set the min/max Z levels for points to be actually inserted in the map (only if  was called before). C++: mrpt::maps::CPointsMap::setHeightFilterLevels(const double, const double) --> void

setPoint(...)
setPoint(*args, **kwargs) Overloaded function. 1. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes a given point from map, with Z defaulting to 0 if not provided. Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float, float) --> void 2. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint2D_<double> &) --> void 3. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint3D_<double> &) --> void 4. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float) --> void

setPointFast(...)
setPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes the coordinates of the given point (0-based index), *without* checking for out-of-bounds and *without* calling mark_as_modified(). Also, color, intensity, or other data is left unchanged. setPoint C++: mrpt::maps::CPointsMap::setPointFast(size_t, float, float, float) --> void

setPointWeight(...)
setPointWeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, w: int) -> None Sets the point weight, which is ignored in all classes but those which actually store that field (Note: No checks are done for out-of-bounds index). getPointWeight C++: mrpt::maps::CPointsMap::setPointWeight(size_t, unsigned long) --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Returns the number of stored points in the map. C++: mrpt::maps::CPointsMap::size() const --> size_t

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondence(float, float) const --> float

squareDistanceToClosestCorrespondenceT(...)
squareDistanceToClosestCorrespondenceT(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p0: mrpt::math::TPoint2D_<double>) -> float C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondenceT(const struct mrpt::math::TPoint2D_<double> &) const --> float

Data descriptors inherited from CPointsMap:

insertionOptions

likelihoodOptions

renderOptions

Data and other attributes inherited from CPointsMap:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TInsertionOptions'>
With this struct options are provided to the observation insertion process. CObservation::insertIntoPointsMap

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TLikelihoodOptions'>
Options used when evaluating "computeObservationLikelihood" in the derived classes. CObservation::computeObservationLikelihood

TRenderOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TRenderOptions'>
Rendering options, used in getAs3DObject()

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Importer:

getLoadPLYErrorString(...)
getLoadPLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Importer::getLoadPLYErrorString() const --> std::string

loadFromPlyFile(...)
loadFromPlyFile(*args, **kwargs) Overloaded function. 1. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str) -> bool 2. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str]) -> bool 3. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str], file_obj_info: List[str]) -> bool Loads from a PLY file. The filename to open. It can be either in binary or text format. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error in the file format or reading it. To obtain more details on the error you can call getLoadPLYErrorString() C++: mrpt::opengl::PLY_Importer::loadFromPlyFile(const std::string &, class std::vector<std::string > *, class std::vector<std::string > *) --> bool

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Exporter:

getSavePLYErrorString(...)
getSavePLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Exporter::getSavePLYErrorString() const --> std::string

saveToPlyFile(...)
saveToPlyFile(*args, **kwargs) Overloaded function. 1. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str) -> bool 2. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool) -> bool 3. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str]) -> bool 4. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str], file_obj_info: List[str]) -> bool Saves to a PLY file. The filename to be saved. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error writing the file. To obtain more details on the error you can call getSavePLYErrorString() C++: mrpt::opengl::PLY_Exporter::saveToPlyFile(const std::string &, bool, const class std::vector<std::string > &, const class std::vector<std::string > &) const --> bool

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CRBPFParticleData(mrpt.pymrpt.mrpt.serialization.CSerializable)

    Auxiliary class used in mrpt::maps::CMultiMetricMapPDF

Method resolution order:

CRBPFParticleData

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CRBPFParticleData) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CRBPFParticleData::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CRBPFParticleData) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CRBPFParticleData, mapsInit: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CRBPFParticleData, arg0: mrpt.pymrpt.mrpt.maps.CRBPFParticleData) -> None 4. __init__(self: mrpt.pymrpt.mrpt.maps.CRBPFParticleData, arg0: mrpt.pymrpt.mrpt.maps.CRBPFParticleData) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CRBPFParticleData, : mrpt.pymrpt.mrpt.maps.CRBPFParticleData) -> mrpt.pymrpt.mrpt.maps.CRBPFParticleData C++: mrpt::maps::CRBPFParticleData::operator=(const class mrpt::maps::CRBPFParticleData &) --> class mrpt::maps::CRBPFParticleData &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CRBPFParticleData) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CRBPFParticleData::clone() const --> class mrpt::rtti::CObject *

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CRBPFParticleData::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CRBPFParticleData::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

mapTillNow

robotPath

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CRandomFieldGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t)

    CRandomFieldGridMap2D represents a 2D grid map where each cell is associated one real-valued property which is estimated by this map, either    as a simple value or as a probility distribution (for each cell).   There are a number of methods available to build the MRF grid-map, depending on the value of     `TMapRepresentation maptype` passed in the constructor.   The following papers describe the mapping alternatives implemented here:                 - `mrKernelDM`: A Gaussian kernel-based method. See:                         - "Building gas concentration gridmaps with a mobile robot", Lilienthal, A. and Duckett, T., Robotics and Autonomous Systems, v.48, 2004.                 - `mrKernelDMV`: A kernel-based method. See:                         - "A Statistical Approach to Gas Distribution Modelling with Mobile Robots--The Kernel DM+ V Algorithm", Lilienthal, A.J. and Reggente, M. and Trincavelli, M. and Blanco, J.L. and Gonzalez, J., IROS 2009.                 - `mrKalmanFilter`: A "brute-force" approach to estimate the entire map with a dense (linear) Kalman filter. Will be very slow for mid or large maps. It's provided just for comparison purposes, not useful in practice.                 - `mrKalmanApproximate`: A compressed/sparse Kalman filter approach. See:                         - "A Kalman Filter Based Approach to Probabilistic Gas Distribution Mapping", JL Blanco, JG Monroy, J Gonzalez-Jimenez, A Lilienthal, 28th Symposium On Applied Computing (SAC), 2013.                 - `mrGMRF_SD`: A Gaussian Markov Random Field (GMRF) estimator, with these constraints:                         - `mrGMRF_SD`: Each cell only connected to its 4 immediate neighbors (Up, down, left, right).                         - (Removed in MRPT 1.5.0: `mrGMRF_G`: Each cell connected to a square area of neighbors cells)                         - See papers:                                 - "Time-variant gas distribution mapping with obstacle information", Monroy, J. G., Blanco, J. L., & Gonzalez-Jimenez, J. Autonomous Robots, 40(1), 1-16, 2016.   Note that this class is virtual, since derived classes still have to implement:                 - mrpt::maps::CMetricMap::internal_computeObservationLikelihood()                 - mrpt::maps::CMetricMap::internal_insertObservation()                 - Serialization methods: writeToStream() and readFromStream() [GMRF only] A custom connectivity pattern between cells can be defined by calling setCellsConnectivity(). mrpt::maps::CGasConcentrationGridMap2D, mrpt::maps::CWirelessPowerGridMap2D, mrpt::maps::CMetricMap, mrpt::containers::CDynamicGrid, The application icp-slam, mrpt::maps::CMultiMetricMap

Method resolution order:

CRandomFieldGridMap2D

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CRandomFieldGridMap2D::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(self, /, *args, **kwargs)
Initialize self.  See help(type(self)) for accurate signature.

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> str Returns a short description of the map. C++: mrpt::maps::CRandomFieldGridMap2D::asString() const --> std::string

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, : mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D C++: mrpt::maps::CRandomFieldGridMap2D::operator=(const class mrpt::maps::CRandomFieldGridMap2D &) --> class mrpt::maps::CRandomFieldGridMap2D &

cell2float(...)
cell2float(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, c: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float C++: mrpt::maps::CRandomFieldGridMap2D::cell2float(const struct mrpt::maps::TRandomFieldCell &) const --> float

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None Calls the base CMetricMap::clear Declared here to avoid ambiguity between the two clear() in both base classes. C++: mrpt::maps::CRandomFieldGridMap2D::clear() --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float See docs in base class: in this class this always returns 0 C++: mrpt::maps::CRandomFieldGridMap2D::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

enableProfiler(...)
enableProfiler(*args, **kwargs) Overloaded function. 1. enableProfiler(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None 2. enableProfiler(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, enable: bool) -> None C++: mrpt::maps::CRandomFieldGridMap2D::enableProfiler(bool) --> void

enableVerbose(...)
enableVerbose(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, enable_verbose: bool) -> None C++: mrpt::maps::CRandomFieldGridMap2D::enableVerbose(bool) --> void

getAs3DObject(...)
getAs3DObject(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, meanObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects, varObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns two 3D objects representing the mean and variance maps C++: mrpt::maps::CRandomFieldGridMap2D::getAs3DObject(class mrpt::opengl::CSetOfObjects &, class mrpt::opengl::CSetOfObjects &) const --> void

getAsBitmapFile(...)
getAsBitmapFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_img: mrpt.pymrpt.mrpt.img.CImage) -> None Returns an image just as described in   C++: mrpt::maps::CRandomFieldGridMap2D::getAsBitmapFile(class mrpt::img::CImage &) const --> void

getAsMatrix(...)
getAsMatrix(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_mat: mrpt.pymrpt.mrpt.math.CMatrixDynamic_double_t) -> None Like saveAsBitmapFile(), but returns the data in matrix form (first row in the matrix is the upper (y_max) part of the map) C++: mrpt::maps::CRandomFieldGridMap2D::getAsMatrix(class mrpt::math::CMatrixDynamic<double> &) const --> void

getMapType(...)
getMapType(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation Return the type of the random-field grid map, according to parameters passed on construction. C++: mrpt::maps::CRandomFieldGridMap2D::getMapType() --> enum mrpt::maps::CRandomFieldGridMap2D::TMapRepresentation

getMeanAndCov(...)
getMeanAndCov(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_cov: mrpt.pymrpt.mrpt.math.CMatrixDynamic_double_t) -> None Return the mean and covariance vector of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::getMeanAndCov(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CMatrixDynamic<double> &) const --> void

getMeanAndSTD(...)
getMeanAndSTD(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_STD: mrpt::math::CVectorDynamic<double>) -> None Return the mean and STD vectors of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::getMeanAndSTD(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CVectorDynamic<double> &) const --> void

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns a 3D object representing the map (mean) C++: mrpt::maps::CRandomFieldGridMap2D::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

insertIndividualReading(...)
insertIndividualReading(*args, **kwargs) Overloaded function. 1. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>) -> None 2. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool) -> None 3. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool, time_invariant: bool) -> None 4. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool, time_invariant: bool, reading_stddev: float) -> None Direct update of the map with a reading in a given position of the map, using   the appropriate method according to mapType passed in the constructor. This is a direct way to update the map, an alternative to the generic insertObservation() method which works with mrpt::obs::CObservation objects. C++: mrpt::maps::CRandomFieldGridMap2D::insertIndividualReading(const double, const struct mrpt::math::TPoint2D_<double> &, const bool, const bool, const double) --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool Returns true if the map is empty/no observation has been inserted (in this class it always return false, unless redefined otherwise in base classes) C++: mrpt::maps::CRandomFieldGridMap2D::isEmpty() const --> bool

isEnabledVerbose(...)
isEnabledVerbose(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool C++: mrpt::maps::CRandomFieldGridMap2D::isEnabledVerbose() const --> bool

isProfilerEnabled(...)
isProfilerEnabled(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool C++: mrpt::maps::CRandomFieldGridMap2D::isProfilerEnabled() const --> bool

predictMeasurement(...)
predictMeasurement(*args, **kwargs) Overloaded function. 1. predictMeasurement(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x: float, y: float, out_predict_response: float, out_predict_response_variance: float, do_sensor_normalization: bool) -> None 2. predictMeasurement(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x: float, y: float, out_predict_response: float, out_predict_response_variance: float, do_sensor_normalization: bool, interp_method: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TGridInterpolationMethod) -> None Returns the prediction of the measurement at some (x,y) coordinates, and its certainty (in the form of the expected variance).   C++: mrpt::maps::CRandomFieldGridMap2D::predictMeasurement(const double, const double, double &, double &, bool, const enum mrpt::maps::CRandomFieldGridMap2D::TGridInterpolationMethod) --> void

resize(...)
resize(*args, **kwargs) Overloaded function. 1. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> None 2. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt.pymrpt.mrpt.maps.TRandomFieldCell, additionalMarginMeters: float) -> None Changes the size of the grid, maintaining previous contents. setSize C++: mrpt::maps::CRandomFieldGridMap2D::resize(double, double, double, double, const struct mrpt::maps::TRandomFieldCell &, double) --> void

saveAsBitmapFile(...)
saveAsBitmapFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filName: str) -> None Save the current map as a graphical file (BMP,PNG,...). The file format will be derived from the file extension (see CImage::saveToFile )   It depends on the map representation model:                 mrAchim: Each pixel is the ratio                 mrKalmanFilter: Each pixel is the mean value of the Gaussian that represents each cell.           C++: mrpt::maps::CRandomFieldGridMap2D::saveAsBitmapFile(const std::string &) const --> void

saveAsMatlab3DGraph(...)
saveAsMatlab3DGraph(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filName: str) -> None Save a matlab ".m" file which represents as 3D surfaces the mean and a given confidence level for the concentration of each cell.   This method can only be called in a KF map model. C++: mrpt::maps::CRandomFieldGridMap2D::saveAsMatlab3DGraph(const std::string &) const --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filNamePrefix: str) -> None The implementation in this class just calls all the corresponding method of the contained metric maps C++: mrpt::maps::CRandomFieldGridMap2D::saveMetricMapRepresentationToFile(const std::string &) const --> void

setCellsConnectivity(...)
setCellsConnectivity(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_connectivity_descriptor: mrpt::maps::CRandomFieldGridMap2D::ConnectivityDescriptor) -> None Sets a custom object to define the connectivity between cells. Must call clear() or setSize() afterwards for the changes to take place. C++: mrpt::maps::CRandomFieldGridMap2D::setCellsConnectivity(const class std::shared_ptr<struct mrpt::maps::CRandomFieldGridMap2D::ConnectivityDescriptor> &) --> void

setMeanAndSTD(...)
setMeanAndSTD(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_STD: mrpt::math::CVectorDynamic<double>) -> None Load the mean and STD vectors of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::setMeanAndSTD(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CVectorDynamic<double> &) --> void

setSize(...)
setSize(*args, **kwargs) Overloaded function. 1. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 2. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float, fill_value: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> None Changes the size of the grid, erasing previous contents.    Optional user-supplied object that will visit all grid cells to define their connectivity with neighbors and the strength of existing edges. If present, it overrides all options in insertionOptions resize C++: mrpt::maps::CRandomFieldGridMap2D::setSize(const double, const double, const double, const double, const double, const struct mrpt::maps::TRandomFieldCell *) --> void

updateMapEstimation(...)
updateMapEstimation(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None Run the method-specific procedure required to ensure that the mean & variances are up-to-date with all inserted observations. C++: mrpt::maps::CRandomFieldGridMap2D::updateMapEstimation() --> void

Static methods defined here:

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CRandomFieldGridMap2D::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data and other attributes defined here:

ConnectivityDescriptor = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.ConnectivityDescriptor'>
Base class for user-supplied objects capable of describing cells connectivity, used to build prior factors of the MRF graph. setCellsConnectivity()

TGridInterpolationMethod = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TGridInterpolationMethod'>

TInsertionOptionsCommon = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TInsertionOptionsCommon'>
Parameters common to any derived class. Derived classes should derive a new struct from this one, plus "public CLoadableOptions", and call the internal_* methods where appropiate to deal with the variables declared here. Derived classes instantions of their "TInsertionOptions" MUST set the pointer "m_insertOptions_common" upon construction.

TMapRepresentation = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation'>

gimBilinear = <TGridInterpolationMethod.gimBilinear: 1>

gimNearest = <TGridInterpolationMethod.gimNearest: 0>

mrAchim = <TMapRepresentation.mrKernelDM: 0>

mrGMRF_SD = <TMapRepresentation.mrGMRF_SD: 4>

mrKalmanApproximate = <TMapRepresentation.mrKalmanApproximate: 2>

mrKalmanFilter = <TMapRepresentation.mrKalmanFilter: 1>

mrKernelDM = <TMapRepresentation.mrKernelDM: 0>

mrKernelDMV = <TMapRepresentation.mrKernelDMV: 3>

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

clone(...)
clone(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Returns a deep copy (clone) of the object, indepently of its class. C++: mrpt::rtti::CObject::clone() const --> class mrpt::rtti::CObject *

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t:

cellByIndex(...)
cellByIndex(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cx: int, cy: int) -> mrpt::maps::TRandomFieldCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::cellByIndex(unsigned int, unsigned int) --> struct mrpt::maps::TRandomFieldCell *

cellByPos(...)
cellByPos(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float, y: float) -> mrpt::maps::TRandomFieldCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::cellByPos(double, double) --> struct mrpt::maps::TRandomFieldCell *

fill(...)
fill(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, value: mrpt::maps::TRandomFieldCell) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::fill(const struct mrpt::maps::TRandomFieldCell &) --> void

getResolution(...)
getResolution(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getResolution() const --> double

getSizeX(...)
getSizeX(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getSizeX() const --> size_t

getSizeY(...)
getSizeY(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getSizeY() const --> size_t

getXMax(...)
getXMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getXMax() const --> double

getXMin(...)
getXMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getXMin() const --> double

getYMax(...)
getYMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getYMax() const --> double

getYMin(...)
getYMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getYMin() const --> double

idx2cxcy(...)
idx2cxcy(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, idx: int, cx: int, cy: int) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2cxcy(int, int &, int &) const --> void

idx2x(...)
idx2x(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cx: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2x(int) const --> double

idx2y(...)
idx2y(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cy: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2y(int) const --> double

saveToTextFile(...)
saveToTextFile(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, fileName: str) -> bool C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::saveToTextFile(const std::string &) const --> bool

x2idx(...)
x2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::x2idx(double) const --> int

xy2idx(...)
xy2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::xy2idx(double, double) const --> int

y2idx(...)
y2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::y2idx(double) const --> int

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CRandomFieldGridMap3D(mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, mrpt.pymrpt.mrpt.serialization.CSerializable)

    CRandomFieldGridMap3D represents a 3D regular grid where each voxel is associated one real-valued property which is to be estimated by this class. This class implements a Gaussian Markov Random Field (GMRF) estimator, with each voxel being connected to its   6 immediate neighbors (Up, down, left, right, front, back). - See papers:    - "Time-variant gas distribution mapping with obstacle information", Monroy, J. G., Blanco, J. L., & Gonzalez-Jimenez, J. Autonomous Robots, 40(1), 1-16, 2016. Note that this class does not derive from mrpt::maps::CMetricMap since the estimated values do not have sensor-especific semantics, i.e. the grid can be used to estimate temperature, gas concentration, etc. Usage: - Define grid size with either constructor or via `setSize()`. - Initialize the map with `initialize()`. This resets the contents of the map, so previously-added observations will be lost. - Add observations of 3D voxels with `insertIndividualReading()` Custom connectivity patterns can be defined with setVoxelsConnectivity(). mrpt::maps::CRandomFieldGridMap3D

Method resolution order:

CRandomFieldGridMap3D

mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CRandomFieldGridMap3D::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, arg0: float) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, arg0: float, arg1: float) -> None doc 4. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, arg0: float, arg1: float, arg2: float) -> None doc 5. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, arg0: float, arg1: float, arg2: float, arg3: float) -> None doc 6. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, arg0: float, arg1: float, arg2: float, arg3: float, arg4: float) -> None doc 7. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, arg0: float, arg1: float, arg2: float, arg3: float, arg4: float, arg5: float) -> None doc 8. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, arg0: float, arg1: float, arg2: float, arg3: float, arg4: float, arg5: float, arg6: float) -> None doc 9. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, x_min: float, x_max: float, y_min: float, y_max: float, z_min: float, z_max: float, voxel_size: float, call_initialize_now: bool) -> None 10. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D) -> None 11. __init__(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, : mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D) -> mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D C++: mrpt::maps::CRandomFieldGridMap3D::operator=(const class mrpt::maps::CRandomFieldGridMap3D &) --> class mrpt::maps::CRandomFieldGridMap3D &

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D) -> None Erases all added observations and start again with an empty gridmap. C++: mrpt::maps::CRandomFieldGridMap3D::clear() --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CRandomFieldGridMap3D::clone() const --> class mrpt::rtti::CObject *

insertIndividualReading(...)
insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, sensorReading: float, sensorVariance: float, point: mrpt::math::TPoint3D_<double>, method: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D.TVoxelInterpolationMethod, update_map: bool) -> bool Direct update of the map with a reading in a given position of the map. false if point is out of the grid extension. C++: mrpt::maps::CRandomFieldGridMap3D::insertIndividualReading(const double, const double, const struct mrpt::math::TPoint3D_<double> &, const enum mrpt::maps::CRandomFieldGridMap3D::TVoxelInterpolationMethod, const bool) --> bool

resize(...)
resize(*args, **kwargs) Overloaded function. 1. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, new_z_min: float, new_z_max: float, defaultValueNewvoxels: mrpt.pymrpt.mrpt.maps.TRandomFieldVoxel) -> None 2. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, new_z_min: float, new_z_max: float, defaultValueNewvoxels: mrpt.pymrpt.mrpt.maps.TRandomFieldVoxel, additionalMarginMeters: float) -> None Changes the size of the grid, maintaining previous contents. setSize C++: mrpt::maps::CRandomFieldGridMap3D::resize(double, double, double, double, double, double, const struct mrpt::maps::TRandomFieldVoxel &, double) --> void

saveAsCSV(...)
saveAsCSV(*args, **kwargs) Overloaded function. 1. saveAsCSV(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, filName_mean: str) -> bool 2. saveAsCSV(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, filName_mean: str, filName_stddev: str) -> bool Save the current estimated mean values to a CSV file (compatible with Paraview) with fields `x y z mean_value`. Optionally, std deviations can be also saved to another file with fields `x y z stddev_value`, if `filName_stddev` is provided. false on error writing to file C++: mrpt::maps::CRandomFieldGridMap3D::saveAsCSV(const std::string &, const std::string &) const --> bool

setSize(...)
setSize(*args, **kwargs) Overloaded function. 1. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, x_min: float, x_max: float, y_min: float, y_max: float, z_min: float, z_max: float, resolution_xy: float) -> None 2. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, x_min: float, x_max: float, y_min: float, y_max: float, z_min: float, z_max: float, resolution_xy: float, resolution_z: float) -> None 3. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, x_min: float, x_max: float, y_min: float, y_max: float, z_min: float, z_max: float, resolution_xy: float, resolution_z: float, fill_value: mrpt.pymrpt.mrpt.maps.TRandomFieldVoxel) -> None Changes the size of the grid, erasing previous contents.If `resolution_z`<0, the same resolution will be used for all dimensions x,y,z as given in `resolution_xy` resize. C++: mrpt::maps::CRandomFieldGridMap3D::setSize(const double, const double, const double, const double, const double, const double, const double, const double, const struct mrpt::maps::TRandomFieldVoxel *) --> void

setVoxelsConnectivity(...)
setVoxelsConnectivity(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D, new_connectivity_descriptor: mrpt::maps::CRandomFieldGridMap3D::ConnectivityDescriptor) -> None Sets a custom object to define the connectivity between voxels. Must call clear() or setSize() afterwards for the changes to take place. C++: mrpt::maps::CRandomFieldGridMap3D::setVoxelsConnectivity(const class std::shared_ptr<struct mrpt::maps::CRandomFieldGridMap3D::ConnectivityDescriptor> &) --> void

updateMapEstimation(...)
updateMapEstimation(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D) -> None Run the method-specific procedure required to ensure that the mean & variances are up-to-date with all inserted observations, using parameters in insertionOptions C++: mrpt::maps::CRandomFieldGridMap3D::updateMapEstimation() --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CRandomFieldGridMap3D::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CRandomFieldGridMap3D::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

insertionOptions

Data and other attributes defined here:

ConnectivityDescriptor = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D.ConnectivityDescriptor'>
Base class for user-supplied objects capable of describing voxels connectivity, used to build prior factors of the MRF graph. setvoxelsConnectivity()

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D.TInsertionOptions'>
Parameters common to any derived class. Derived classes should derive a new struct from this one, plus mrpt::config::CLoadableOptions, and call the internal_* methods where appropiate to deal with the variables declared here. Derived classes instantions of their "TInsertionOptions" MUST set the pointer "m_insertOptions_common" upon construction.

TVoxelInterpolationMethod = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap3D.TVoxelInterpolationMethod'>

gimBilinear = <TVoxelInterpolationMethod.gimBilinear: 1>

gimNearest = <TVoxelInterpolationMethod.gimNearest: 0>

Methods inherited from mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t:

cellAbsIndexFromCXCYCZ(...)
cellAbsIndexFromCXCYCZ(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, cx: int, cy: int, cz: int) -> int C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::cellAbsIndexFromCXCYCZ(const int, const int, const int) const --> size_t

cellByIndex(...)
cellByIndex(*args, **kwargs) Overloaded function. 1. cellByIndex(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, cx: int, cy: int, cz: int) -> mrpt::maps::TRandomFieldVoxel C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::cellByIndex(unsigned int, unsigned int, unsigned int) --> struct mrpt::maps::TRandomFieldVoxel * 2. cellByIndex(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, cidx: int) -> mrpt::maps::TRandomFieldVoxel C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::cellByIndex(size_t) --> struct mrpt::maps::TRandomFieldVoxel *

cellByPos(...)
cellByPos(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, x: float, y: float, z: float) -> mrpt::maps::TRandomFieldVoxel C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::cellByPos(double, double, double) --> struct mrpt::maps::TRandomFieldVoxel *

cellRefByPos(...)
cellRefByPos(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, x: float, y: float, z: float) -> mrpt::maps::TRandomFieldVoxel C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::cellRefByPos(double, double, double) --> struct mrpt::maps::TRandomFieldVoxel &

fill(...)
fill(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, value: mrpt::maps::TRandomFieldVoxel) -> None C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::fill(const struct mrpt::maps::TRandomFieldVoxel &) --> void

getResolutionXY(...)
getResolutionXY(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getResolutionXY() const --> double

getResolutionZ(...)
getResolutionZ(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getResolutionZ() const --> double

getSizeX(...)
getSizeX(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> int C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getSizeX() const --> size_t

getSizeY(...)
getSizeY(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> int C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getSizeY() const --> size_t

getSizeZ(...)
getSizeZ(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> int C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getSizeZ() const --> size_t

getVoxelCount(...)
getVoxelCount(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> int C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getVoxelCount() const --> size_t

getXMax(...)
getXMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getXMax() const --> double

getXMin(...)
getXMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getXMin() const --> double

getYMax(...)
getYMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getYMax() const --> double

getYMin(...)
getYMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getYMin() const --> double

getZMax(...)
getZMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getZMax() const --> double

getZMin(...)
getZMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::getZMin() const --> double

idx2x(...)
idx2x(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, cx: int) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::idx2x(int) const --> double

idx2y(...)
idx2y(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, cy: int) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::idx2y(int) const --> double

idx2z(...)
idx2z(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, cz: int) -> float C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::idx2z(int) const --> double

isOutOfBounds(...)
isOutOfBounds(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, cx: int, cy: int, cz: int) -> bool C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::isOutOfBounds(const int, const int, const int) const --> bool

x2idx(...)
x2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, x: float) -> int C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::x2idx(double) const --> int

y2idx(...)
y2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, y: float) -> int C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::y2idx(double) const --> int

z2idx(...)
z2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid3D_mrpt_maps_TRandomFieldVoxel_double_t, z: float) -> int C++: mrpt::containers::CDynamicGrid3D<mrpt::maps::TRandomFieldVoxel>::z2idx(double) const --> int

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CReflectivityGridMap2D(CMetricMap, mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, CLogOddsGridMap2D_signed_char_t)

    A 2D grid map representing the reflectivity of the environment (for example, measured with an IR proximity sensor).   Important implemented features are:                 - Insertion of mrpt::obs::CObservationReflectivity observations.                 - Probability estimation of observations. See base class.                 - Rendering as 3D object: a 2D textured plane.                 - Automatic resizing of the map limits when inserting observations close to the border.    Each cell contains the up-to-date average height from measured falling in that cell. Algorithms that can be used:                 - mrSimpleAverage: Each cell only stores the current average value.

Method resolution order:

CReflectivityGridMap2D

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t

CLogOddsGridMap2D_signed_char_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CReflectivityGridMap2D::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, arg0: float) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, arg0: float, arg1: float) -> None doc 4. __init__(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, arg0: float, arg1: float, arg2: float) -> None doc 5. __init__(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, arg0: float, arg1: float, arg2: float, arg3: float) -> None doc 6. __init__(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 7. __init__(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D) -> None 8. __init__(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D) -> None

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D) -> str Returns a short description of the map. C++: mrpt::maps::CReflectivityGridMap2D::asString() const --> std::string

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, : mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D) -> mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D C++: mrpt::maps::CReflectivityGridMap2D::operator=(const class mrpt::maps::CReflectivityGridMap2D &) --> class mrpt::maps::CReflectivityGridMap2D &

cell2float(...)
cell2float(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, c: int) -> float C++: mrpt::maps::CReflectivityGridMap2D::cell2float(const signed char &) const --> float

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D) -> None Calls the base CMetricMap::clear Declared here to avoid ambiguity between the two clear() in both base classes. C++: mrpt::maps::CReflectivityGridMap2D::clear() --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CReflectivityGridMap2D::clone() const --> class mrpt::rtti::CObject *

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float See docs in base class: in this class this always returns 0 C++: mrpt::maps::CReflectivityGridMap2D::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

getAsImage(...)
getAsImage(*args, **kwargs) Overloaded function. 1. getAsImage(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage) -> None 2. getAsImage(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage, verticalFlip: bool) -> None 3. getAsImage(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, img: mrpt.pymrpt.mrpt.img.CImage, verticalFlip: bool, forceRGB: bool) -> None Returns the grid as a 8-bit graylevel image, where each pixel is a cell (output image is RGB only if forceRGB is true) C++: mrpt::maps::CReflectivityGridMap2D::getAsImage(class mrpt::img::CImage &, bool, bool) const --> void

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None C++: mrpt::maps::CReflectivityGridMap2D::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CReflectivityGridMap2D::isEmpty() const --> bool

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D, filNamePrefix: str) -> None C++: mrpt::maps::CReflectivityGridMap2D::saveMetricMapRepresentationToFile(const std::string &) const --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CReflectivityGridMap2D::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CReflectivityGridMap2D::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

insertionOptions

Data and other attributes defined here:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D.TInsertionOptions'>
Parameters related with inserting observations into the map.

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CReflectivityGridMap2D.TMapDefinitionBase'>

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t:

cellByIndex(...)
cellByIndex(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, cx: int, cy: int) -> int C++: mrpt::containers::CDynamicGrid<signed char>::cellByIndex(unsigned int, unsigned int) --> signed char *

cellByPos(...)
cellByPos(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, x: float, y: float) -> int C++: mrpt::containers::CDynamicGrid<signed char>::cellByPos(double, double) --> signed char *

fill(...)
fill(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, value: int) -> None C++: mrpt::containers::CDynamicGrid<signed char>::fill(const signed char &) --> void

getResolution(...)
getResolution(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t) -> float C++: mrpt::containers::CDynamicGrid<signed char>::getResolution() const --> double

getSizeX(...)
getSizeX(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t) -> int C++: mrpt::containers::CDynamicGrid<signed char>::getSizeX() const --> size_t

getSizeY(...)
getSizeY(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t) -> int C++: mrpt::containers::CDynamicGrid<signed char>::getSizeY() const --> size_t

getXMax(...)
getXMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t) -> float C++: mrpt::containers::CDynamicGrid<signed char>::getXMax() const --> double

getXMin(...)
getXMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t) -> float C++: mrpt::containers::CDynamicGrid<signed char>::getXMin() const --> double

getYMax(...)
getYMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t) -> float C++: mrpt::containers::CDynamicGrid<signed char>::getYMax() const --> double

getYMin(...)
getYMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t) -> float C++: mrpt::containers::CDynamicGrid<signed char>::getYMin() const --> double

idx2cxcy(...)
idx2cxcy(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, idx: int, cx: int, cy: int) -> None C++: mrpt::containers::CDynamicGrid<signed char>::idx2cxcy(int, int &, int &) const --> void

idx2x(...)
idx2x(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, cx: int) -> float C++: mrpt::containers::CDynamicGrid<signed char>::idx2x(int) const --> double

idx2y(...)
idx2y(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, cy: int) -> float C++: mrpt::containers::CDynamicGrid<signed char>::idx2y(int) const --> double

resize(...)
resize(*args, **kwargs) Overloaded function. 1. resize(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: int) -> None 2. resize(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: int, additionalMarginMeters: float) -> None C++: mrpt::containers::CDynamicGrid<signed char>::resize(double, double, double, double, const signed char &, double) --> void

saveToTextFile(...)
saveToTextFile(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, fileName: str) -> bool C++: mrpt::containers::CDynamicGrid<signed char>::saveToTextFile(const std::string &) const --> bool

setSize(...)
setSize(*args, **kwargs) Overloaded function. 1. setSize(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 2. setSize(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float, fill_value: int) -> None C++: mrpt::containers::CDynamicGrid<signed char>::setSize(const double, const double, const double, const double, const double, const signed char *) --> void

x2idx(...)
x2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, x: float) -> int C++: mrpt::containers::CDynamicGrid<signed char>::x2idx(double) const --> int

xy2idx(...)
xy2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, x: float, y: float) -> int C++: mrpt::containers::CDynamicGrid<signed char>::xy2idx(double, double) const --> int

y2idx(...)
y2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_signed_char_t, y: float) -> int C++: mrpt::containers::CDynamicGrid<signed char>::y2idx(double) const --> int

Methods inherited from CLogOddsGridMap2D_signed_char_t:

updateCell_fast_occupied(...)
updateCell_fast_occupied(*args, **kwargs) Overloaded function. 1. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t, x: int, y: int, logodd_obs: int, thres: int, mapArray: int, _size_x: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_occupied(const unsigned int, const unsigned int, const signed char, const signed char, signed char *, const unsigned int) --> void 2. updateCell_fast_occupied(self: mrpt.pymrpt.mrpt.maps.CLogOddsGridMap2D_signed_char_t, theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_occupied(signed char *, const signed char, const signed char) --> void

Static methods inherited from CLogOddsGridMap2D_signed_char_t:

updateCell_fast_free(...) from builtins.PyCapsule
updateCell_fast_free(*args, **kwargs) Overloaded function. 1. updateCell_fast_free(x: int, y: int, logodd_obs: int, thres: int, mapArray: int, _size_x: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_free(const unsigned int, const unsigned int, const signed char, const signed char, signed char *, const unsigned int) --> void 2. updateCell_fast_free(theCell: int, logodd_obs: int, thres: int) -> None C++: mrpt::maps::CLogOddsGridMap2D<signed char>::updateCell_fast_free(signed char *, const signed char, const signed char) --> void

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CSimpleMap(mrpt.pymrpt.mrpt.serialization.CSerializable)

    A view-based representation of a metric map. This comprises a list of `<ProbabilisticPose,SensoryFrame>` pairs, that is, the **poses** (keyframes) from which a set of **observations** where gathered: - Poses, in the global `map` frame of reference, are stored as probabilistic PDFs over SE(3) as instances of mrpt::poses::CPose3DPDF - Observations are stored as mrpt::obs::CSensoryFrame. Note that in order to generate an actual metric map (occupancy grid, point cloud, octomap, etc.) from a "simple map", you must instantiate the desired metric map class and invoke its virtual method mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(). Objects of this class are serialized into GZ-compressed       files with the extension `.simplemap`.       See [Robotics file formats](robotics_file_formats.html). mrpt::obs::CSensoryFrame, mrpt::poses::CPose3DPDF, mrpt::maps::CMetricMap

Method resolution order:

CSimpleMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CSimpleMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, arg0: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, arg0: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, o: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> mrpt.pymrpt.mrpt.maps.CSimpleMap Copy, making a deep copy of all data. C++: mrpt::maps::CSimpleMap::operator=(const class mrpt::maps::CSimpleMap &) --> class mrpt::maps::CSimpleMap &

changeCoordinatesOrigin(...)
changeCoordinatesOrigin(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, newOrigin: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Change the coordinate origin of all stored poses, that is, translates and rotates the map such that the old SE(3) origin (identity transformation) becomes the new provided one. C++: mrpt::maps::CSimpleMap::changeCoordinatesOrigin(const class mrpt::poses::CPose3D &) --> void

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> None Remove all stored pairs.   remove C++: mrpt::maps::CSimpleMap::clear() --> void

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CSimpleMap::clone() const --> class mrpt::rtti::CObject *

empty(...)
empty(self: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> bool Returns size()!=0 C++: mrpt::maps::CSimpleMap::empty() const --> bool

get(...)
get(*args, **kwargs) Overloaded function. 1. get(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, index: int, out_posePDF: mrpt.pymrpt.mrpt.poses.CPose3DPDF, out_SF: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> None Access to the 0-based index i'th pair. std::exception On index out of bounds. C++: mrpt::maps::CSimpleMap::get(size_t, class std::shared_ptr<const class mrpt::poses::CPose3DPDF> &, class std::shared_ptr<const class mrpt::obs::CSensoryFrame> &) const --> void 2. get(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, index: int, out_posePDF: mrpt.pymrpt.mrpt.poses.CPose3DPDF, out_SF: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> None C++: mrpt::maps::CSimpleMap::get(size_t, class std::shared_ptr<class mrpt::poses::CPose3DPDF> &, class std::shared_ptr<class mrpt::obs::CSensoryFrame> &) --> void 3. get(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, index: int) -> Tuple[mrpt.pymrpt.mrpt.poses.CPose3DPDF, mrpt.pymrpt.mrpt.obs.CSensoryFrame] C++: mrpt::maps::CSimpleMap::get(size_t) --> class std::tuple<class std::shared_ptr<class mrpt::poses::CPose3DPDF>, class std::shared_ptr<class mrpt::obs::CSensoryFrame> >

getAsPair(...)
getAsPair(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, index: int) -> mrpt::maps::CSimpleMap::Pair C++: mrpt::maps::CSimpleMap::getAsPair(size_t) --> struct mrpt::maps::CSimpleMap::Pair &

insert(...)
insert(*args, **kwargs) Overloaded function. 1. insert(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, in_posePDF: mrpt.pymrpt.mrpt.poses.CPose3DPDF, in_SF: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> None Adds a new keyframe (SE(3) pose) to the view-based map, making a deep copy of the pose PDF (observations within the SF are always copied as `shared_ptr`s). C++: mrpt::maps::CSimpleMap::insert(const class mrpt::poses::CPose3DPDF &, const class mrpt::obs::CSensoryFrame &) --> void 2. insert(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, in_posePDF: mrpt.pymrpt.mrpt.poses.CPose3DPDF, in_SF: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> None Adds a new keyframe (SE(3) pose) to the view-based map.   Both shared pointers are copied (shallow object copies). C++: mrpt::maps::CSimpleMap::insert(const class std::shared_ptr<class mrpt::poses::CPose3DPDF> &, const class std::shared_ptr<class mrpt::obs::CSensoryFrame> &) --> void 3. insert(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, poseSF: mrpt::maps::CSimpleMap::Pair) -> None C++: mrpt::maps::CSimpleMap::insert(const struct mrpt::maps::CSimpleMap::Pair &) --> void 4. insert(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, in_posePDF: mrpt.pymrpt.mrpt.poses.CPosePDF, in_SF: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> None Adds a new keyframe (SE(2) pose) to the view-based map, making a deep copy of the pose PDF (observations within the SF are always copied as `shared_ptr`s). C++: mrpt::maps::CSimpleMap::insert(const class mrpt::poses::CPosePDF &, const class mrpt::obs::CSensoryFrame &) --> void 5. insert(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, in_posePDF: mrpt.pymrpt.mrpt.poses.CPosePDF, in_SF: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> None Adds a new keyframe (SE(2) pose) to the view-based map.   Both shared pointers are copied (shallow object copies). C++: mrpt::maps::CSimpleMap::insert(const class std::shared_ptr<class mrpt::poses::CPosePDF> &, const class std::shared_ptr<class mrpt::obs::CSensoryFrame> &) --> void

loadFromFile(...)
loadFromFile(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, filName: str) -> bool Load the contents of this object from a .simplemap binary file (possibly compressed with gzip) See [Robotics file formats](robotics_file_formats.html). saveToFile() false on any error. C++: mrpt::maps::CSimpleMap::loadFromFile(const std::string &) --> bool

remove(...)
remove(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, index: int) -> None Deletes the 0-based index i'th pair. std::exception On index out of bounds. insert, get, set C++: mrpt::maps::CSimpleMap::remove(size_t) --> void

saveToFile(...)
saveToFile(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, filName: str) -> bool Save this object to a .simplemap binary file (compressed with gzip) See [Robotics file formats](robotics_file_formats.html). loadFromFile() false on any error. C++: mrpt::maps::CSimpleMap::saveToFile(const std::string &) const --> bool

set(...)
set(*args, **kwargs) Overloaded function. 1. set(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, index: int, in_posePDF: mrpt.pymrpt.mrpt.poses.CPose3DPDF, in_SF: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> None Changes the 0-based index i'th pair.   If one of either `in_posePDF` or `in_SF` are empty `shared_ptr`s, the corresponding field in the map is not modified. std::exception On index out of bounds. insert, get, remove C++: mrpt::maps::CSimpleMap::set(size_t, const class std::shared_ptr<class mrpt::poses::CPose3DPDF> &, const class std::shared_ptr<class mrpt::obs::CSensoryFrame> &) --> void 2. set(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, index: int, poseSF: mrpt::maps::CSimpleMap::Pair) -> None C++: mrpt::maps::CSimpleMap::set(size_t, const struct mrpt::maps::CSimpleMap::Pair &) --> void 3. set(self: mrpt.pymrpt.mrpt.maps.CSimpleMap, index: int, in_posePDF: mrpt.pymrpt.mrpt.poses.CPosePDF, in_SF: mrpt.pymrpt.mrpt.obs.CSensoryFrame) -> None C++: mrpt::maps::CSimpleMap::set(size_t, const class std::shared_ptr<class mrpt::poses::CPosePDF> &, const class std::shared_ptr<class mrpt::obs::CSensoryFrame> &) --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.CSimpleMap) -> int Returns the count of (pose,sensoryFrame) pairs C++: mrpt::maps::CSimpleMap::size() const --> size_t

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CSimpleMap::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CSimpleMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data and other attributes defined here:

ConstPair = <class 'mrpt.pymrpt.mrpt.maps.CSimpleMap.ConstPair'>

Pair = <class 'mrpt.pymrpt.mrpt.maps.CSimpleMap.Pair'>

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CSimplePointsMap(CPointsMap)

    A cloud of points in 2D or 3D, which can be built from a sequence of laser scans.    This class only stores the coordinates (x,y,z) of each point. See mrpt::maps::CPointsMap and derived classes for other point cloud classes. CMetricMap, CWeightedPointsMap, CPoint, mrpt::serialization::CSerializable

Method resolution order:

CSimplePointsMap

CPointsMap

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.opengl.PLY_Importer

mrpt.pymrpt.mrpt.opengl.PLY_Exporter

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CSimplePointsMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, o: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, arg0: mrpt.pymrpt.mrpt.maps.CSimplePointsMap) -> None 4. __init__(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, arg0: mrpt.pymrpt.mrpt.maps.CSimplePointsMap) -> None

assign(...)
assign(*args, **kwargs) Overloaded function. 1. assign(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, o: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.maps.CSimplePointsMap C++: mrpt::maps::CSimplePointsMap::operator=(const class mrpt::maps::CPointsMap &) --> class mrpt::maps::CSimplePointsMap & 2. assign(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, o: mrpt.pymrpt.mrpt.maps.CSimplePointsMap) -> mrpt.pymrpt.mrpt.maps.CSimplePointsMap C++: mrpt::maps::CSimplePointsMap::operator=(const class mrpt::maps::CSimplePointsMap &) --> class mrpt::maps::CSimplePointsMap &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CSimplePointsMap::clone() const --> class mrpt::rtti::CObject *

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap) -> mrpt.pymrpt.mrpt.maps.CSimplePointsMap @} C++: mrpt::maps::CSimplePointsMap::getAsSimplePointsMap() const --> const class mrpt::maps::CSimplePointsMap *

insertPointFast(...)
insertPointFast(*args, **kwargs) Overloaded function. 1. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, x: float, y: float) -> None 2. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, x: float, y: float, z: float) -> None The virtual method for  *without* calling mark_as_modified()    C++: mrpt::maps::CSimplePointsMap::insertPointFast(float, float, float) --> void

reserve(...)
reserve(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, newLength: int) -> None            from CPointsMap                 @{ C++: mrpt::maps::CSimplePointsMap::reserve(size_t) --> void

resize(...)
resize(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, newLength: int) -> None C++: mrpt::maps::CSimplePointsMap::resize(size_t) --> void

setSize(...)
setSize(self: mrpt.pymrpt.mrpt.maps.CSimplePointsMap, newLength: int) -> None C++: mrpt::maps::CSimplePointsMap::setSize(size_t) --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CSimplePointsMap::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CSimplePointsMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data and other attributes defined here:

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CSimplePointsMap.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CSimplePointsMap.TMapDefinitionBase'>

Methods inherited from CPointsMap:

__iadd__(...)
__iadd__(self: mrpt.pymrpt.mrpt.maps.CPointsMap, anotherMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Inserts another map into this one. insertAnotherMap() C++: mrpt::maps::CPointsMap::operator+=(const class mrpt::maps::CPointsMap &) --> void

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> str Returns a short description of the map. C++: mrpt::maps::CPointsMap::asString() const --> std::string

boundingBox(...)
boundingBox(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.math.TBoundingBox_float_t Computes the bounding box of all the points, or (0,0 ,0,0, 0,0) if there are no points.   Results are cached unless the map is somehow modified to avoid repeated calculations. C++: mrpt::maps::CPointsMap::boundingBox() const --> struct mrpt::math::TBoundingBox_<float>

changeCoordinatesReference(...)
changeCoordinatesReference(*args, **kwargs) Overloaded function. 1. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose2D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose2D &) --> void 2. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose3D &) --> void 3. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, other: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Copy all the points from "other" map to "this", replacing each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::maps::CPointsMap &, const class mrpt::poses::CPose3D &) --> void

clipOutOfRange(...)
clipOutOfRange(self: mrpt.pymrpt.mrpt.maps.CPointsMap, point: mrpt::math::TPoint2D_<double>, maxRange: float) -> None Delete points which are more far than "maxRange" away from the given "point". C++: mrpt::maps::CPointsMap::clipOutOfRange(const struct mrpt::math::TPoint2D_<double> &, float) --> void

clipOutOfRangeInZ(...)
clipOutOfRangeInZ(self: mrpt.pymrpt.mrpt.maps.CPointsMap, zMin: float, zMax: float) -> None Delete points out of the given "z" axis range have been removed. C++: mrpt::maps::CPointsMap::clipOutOfRangeInZ(float, float) --> void

compute3DDistanceToMesh(...)
compute3DDistanceToMesh(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap2: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, maxDistForCorrespondence: float, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, correspondencesRatio: float) -> None Computes the matchings between this and another 3D points map.            This method matches each point in the other map with the centroid of the          3 closest points in 3D            from this map (if the distance is below a defined threshold).                                           [IN] The other map to compute the          matching with.                                   [IN] The pose of the other map as seen          from "this".    [IN] Maximum 2D linear distance          between two points to be matched.                           [OUT] The detected matchings pairs.                   [OUT] The ratio [0,1] of points in          otherMap with at least one correspondence. determineMatching3D C++: mrpt::maps::CPointsMap::compute3DDistanceToMesh(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, float, class mrpt::tfest::TMatchingPairListTempl<float> &, float &) --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float C++: mrpt::maps::CPointsMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

empty(...)
empty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool STL-like method to check whether the map is empty: C++: mrpt::maps::CPointsMap::empty() const --> bool

enableFilterByHeight(...)
enableFilterByHeight(*args, **kwargs) Overloaded function. 1. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, enable: bool) -> None Enable/disable the filter-by-height functionality setHeightFilterLevels Default upon construction is disabled. C++: mrpt::maps::CPointsMap::enableFilterByHeight(bool) --> void

extractCylinder(...)
extractCylinder(self: mrpt.pymrpt.mrpt.maps.CPointsMap, center: mrpt::math::TPoint2D_<double>, radius: float, zmin: float, zmax: float, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Extracts the points in the map within a cylinder in 3D defined the provided radius and zmin/zmax values. C++: mrpt::maps::CPointsMap::extractCylinder(const struct mrpt::math::TPoint2D_<double> &, const double, const double, const double, class mrpt::maps::CPointsMap *) --> void

extractPoints(...)
extractPoints(*args, **kwargs) Overloaded function. 1. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float) -> None 3. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float) -> None 4. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float, B: float) -> None Extracts the points in the map within the area defined by two corners.   The points are coloured according the R,G,B input data. C++: mrpt::maps::CPointsMap::extractPoints(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, class mrpt::maps::CPointsMap *, double, double, double) --> void

getHeightFilterLevels(...)
getHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Get the min/max Z levels for points to be actually inserted in the map enableFilterByHeight, setHeightFilterLevels C++: mrpt::maps::CPointsMap::getHeightFilterLevels(double &, double &) const --> void

getLargestDistanceFromOrigin(...)
getLargestDistanceFromOrigin(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> float This method returns the largest distance from the origin to any of the points, such as a sphere centered at the origin with this radius cover ALL the points in the map (the results are buffered, such as, if the map is not modified, the second call will be much faster than the first one). C++: mrpt::maps::CPointsMap::getLargestDistanceFromOrigin() const --> float

getLargestDistanceFromOriginNoRecompute(...)
getLargestDistanceFromOriginNoRecompute(self: mrpt.pymrpt.mrpt.maps.CPointsMap, output_is_valid: bool) -> float Like  but returns in = false if the distance was not already computed, skipping its computation then, unlike getLargestDistanceFromOrigin() C++: mrpt::maps::CPointsMap::getLargestDistanceFromOriginNoRecompute(bool &) const --> float

getPoint(...)
getPoint(*args, **kwargs) Overloaded function. 1. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Access to a given point from map, as a 2D point. First index is 0. Throws std::exception on index out of bound. setPoint, getPointFast C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &, float &) const --> void 2. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &) const --> void 3. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &, double &) const --> void 4. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &) const --> void 5. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint2D_<double> &) const --> void 6. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint3D_<double> &) const --> void

getPointFast(...)
getPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Just like  but without checking out-of-bound index and without returning the point weight, just XYZ. C++: mrpt::maps::CPointsMap::getPointFast(size_t, float &, float &, float &) const --> void

getPointRGB(...)
getPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float, R: float, G: float, B: float) -> None Access to a given point from map, and its colors, if the map defines them (othersise, R=G=B=1.0). First index is 0. The return value is the weight of the point (the times it has been fused) Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMap::getPointRGB(size_t, float &, float &, float &, float &, float &, float &) const --> void

getPointWeight(...)
getPointWeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int) -> int Gets the point weight, which is ignored in all classes (defaults to 1) but in those which actually store that field (Note: No checks are done for out-of-bounds index).   setPointWeight C++: mrpt::maps::CPointsMap::getPointWeight(size_t) const --> unsigned int

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CPointsMap, outObj: mrpt::opengl::CSetOfObjects) -> None Returns a 3D object representing the map.   The color of the points is controlled by renderOptions C++: mrpt::maps::CPointsMap::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

hasColorPoints(...)
hasColorPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Returns true if the point map has a color field for each point C++: mrpt::maps::CPointsMap::hasColorPoints() const --> bool

insertAnotherMap(...)
insertAnotherMap(*args, **kwargs) Overloaded function. 1. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> None 2. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D, filterOutPointsAtZero: bool) -> None Insert the contents of another map into this one with some geometric transformation, without fusing close points. The other map whose points are to be inserted into this one. The pose of the other map in the coordinates of THIS map If true, points at (0,0,0) (in the frame of reference of `otherMap`) will be assumed to be invalid and will not be copied. fuseWith, addFrom C++: mrpt::maps::CPointsMap::insertAnotherMap(const class mrpt::maps::CPointsMap *, const class mrpt::poses::CPose3D &, const bool) --> void

insertPoint(...)
insertPoint(*args, **kwargs) Overloaded function. 1. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float) -> None 2. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float, z: float) -> None Provides a way to insert (append) individual points into the map: the missing fields of child classes (color, weight, etc) are left to their default values C++: mrpt::maps::CPointsMap::insertPoint(float, float, float) --> void 3. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::insertPoint(const struct mrpt::math::TPoint3D_<double> &) --> void

insertPointRGB(...)
insertPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float, z: float, R: float, G: float, B: float) -> None overload (RGB data is ignored in classes without color information) C++: mrpt::maps::CPointsMap::insertPointRGB(float, float, float, float, float, float) --> void

internal_computeObservationLikelihood(...)
internal_computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CPointsMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float @} C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

internal_computeObservationLikelihoodPointCloud3D(...)
internal_computeObservationLikelihoodPointCloud3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, pc_in_map: mrpt.pymrpt.mrpt.poses.CPose3D, xs: float, ys: float, zs: float, num_pts: int) -> float C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihoodPointCloud3D(const class mrpt::poses::CPose3D &, const float *, const float *, const float *, const unsigned long) const --> double

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CPointsMap::isEmpty() const --> bool

isFilterByHeightEnabled(...)
isFilterByHeightEnabled(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Return whether filter-by-height is enabled enableFilterByHeight C++: mrpt::maps::CPointsMap::isFilterByHeightEnabled() const --> bool

kdtree_distance(...)
kdtree_distance(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p1: float, idx_p2: int, size: int) -> float Returns the distance between the vector "p1[0:size-1]" and the data point with index "idx_p2" stored in the class: C++: mrpt::maps::CPointsMap::kdtree_distance(const float *, size_t, size_t) const --> float

kdtree_get_point_count(...)
kdtree_get_point_count(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Must return the number of data points C++: mrpt::maps::CPointsMap::kdtree_get_point_count() const --> size_t

kdtree_get_pt(...)
kdtree_get_pt(self: mrpt.pymrpt.mrpt.maps.CPointsMap, idx: int, dim: int) -> float Returns the dim'th component of the idx'th point in the class: C++: mrpt::maps::CPointsMap::kdtree_get_pt(size_t, int) const --> float

load2D_from_text_file(...)
load2D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y" coordinate pair, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load2D_from_text_file(const std::string &) --> bool

load2Dor3D_from_text_file(...)
load2Dor3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str, is_3D: bool) -> bool 2D or 3D generic implementation of  and load3D_from_text_file C++: mrpt::maps::CPointsMap::load2Dor3D_from_text_file(const std::string &, const bool) --> bool

load3D_from_text_file(...)
load3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y Z" coordinate tuple, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load3D_from_text_file(const std::string &) --> bool

mark_as_modified(...)
mark_as_modified(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Users normally don't need to call this. Called by this class or children classes, set m_largestDistanceFromOriginIsUpdated=false, invalidates the kd-tree cache, and such. C++: mrpt::maps::CPointsMap::mark_as_modified() const --> void

save2D_to_text_file(...)
save2D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y" point coordinates.                 Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save2D_to_text_file(const std::string &) const --> bool

save3D_to_text_file(...)
save3D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y Z" point coordinates.      Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save3D_to_text_file(const std::string &) const --> bool

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CPointsMap, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface) C++: mrpt::maps::CPointsMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

setHeightFilterLevels(...)
setHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Set the min/max Z levels for points to be actually inserted in the map (only if  was called before). C++: mrpt::maps::CPointsMap::setHeightFilterLevels(const double, const double) --> void

setPoint(...)
setPoint(*args, **kwargs) Overloaded function. 1. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes a given point from map, with Z defaulting to 0 if not provided. Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float, float) --> void 2. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint2D_<double> &) --> void 3. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint3D_<double> &) --> void 4. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float) --> void

setPointFast(...)
setPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes the coordinates of the given point (0-based index), *without* checking for out-of-bounds and *without* calling mark_as_modified(). Also, color, intensity, or other data is left unchanged. setPoint C++: mrpt::maps::CPointsMap::setPointFast(size_t, float, float, float) --> void

setPointRGB(...)
setPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float, R: float, G: float, B: float) -> None overload (RGB data is ignored in classes without color information) C++: mrpt::maps::CPointsMap::setPointRGB(size_t, float, float, float, float, float, float) --> void

setPointWeight(...)
setPointWeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, w: int) -> None Sets the point weight, which is ignored in all classes but those which actually store that field (Note: No checks are done for out-of-bounds index). getPointWeight C++: mrpt::maps::CPointsMap::setPointWeight(size_t, unsigned long) --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Returns the number of stored points in the map. C++: mrpt::maps::CPointsMap::size() const --> size_t

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondence(float, float) const --> float

squareDistanceToClosestCorrespondenceT(...)
squareDistanceToClosestCorrespondenceT(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p0: mrpt::math::TPoint2D_<double>) -> float C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondenceT(const struct mrpt::math::TPoint2D_<double> &) const --> float

Data descriptors inherited from CPointsMap:

insertionOptions

likelihoodOptions

renderOptions

Data and other attributes inherited from CPointsMap:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TInsertionOptions'>
With this struct options are provided to the observation insertion process. CObservation::insertIntoPointsMap

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TLikelihoodOptions'>
Options used when evaluating "computeObservationLikelihood" in the derived classes. CObservation::computeObservationLikelihood

TRenderOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TRenderOptions'>
Rendering options, used in getAs3DObject()

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Importer:

getLoadPLYErrorString(...)
getLoadPLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Importer::getLoadPLYErrorString() const --> std::string

loadFromPlyFile(...)
loadFromPlyFile(*args, **kwargs) Overloaded function. 1. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str) -> bool 2. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str]) -> bool 3. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str], file_obj_info: List[str]) -> bool Loads from a PLY file. The filename to open. It can be either in binary or text format. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error in the file format or reading it. To obtain more details on the error you can call getLoadPLYErrorString() C++: mrpt::opengl::PLY_Importer::loadFromPlyFile(const std::string &, class std::vector<std::string > *, class std::vector<std::string > *) --> bool

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Exporter:

getSavePLYErrorString(...)
getSavePLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Exporter::getSavePLYErrorString() const --> std::string

saveToPlyFile(...)
saveToPlyFile(*args, **kwargs) Overloaded function. 1. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str) -> bool 2. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool) -> bool 3. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str]) -> bool 4. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str], file_obj_info: List[str]) -> bool Saves to a PLY file. The filename to be saved. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error writing the file. To obtain more details on the error you can call getSavePLYErrorString() C++: mrpt::opengl::PLY_Exporter::saveToPlyFile(const std::string &, bool, const class std::vector<std::string > &, const class std::vector<std::string > &) const --> bool

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CWeightedPointsMap(CPointsMap)

    A cloud of points in 2D or 3D, which can be built from a sequence of laser scans.    This class stores the coordinates (x,y,z) and a "weight", or counter of how many times that point has been seen, used only if points fusion is enabled in the options structure. CMetricMap, CPoint, mrpt::serialization::CSerializable, CSimplePointsMap

Method resolution order:

CWeightedPointsMap

CPointsMap

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.opengl.PLY_Importer

mrpt.pymrpt.mrpt.opengl.PLY_Exporter

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CWeightedPointsMap::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, o: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, arg0: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap) -> None 4. __init__(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, arg0: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap) -> None

assign(...)
assign(*args, **kwargs) Overloaded function. 1. assign(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, o: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.maps.CWeightedPointsMap C++: mrpt::maps::CWeightedPointsMap::operator=(const class mrpt::maps::CPointsMap &) --> class mrpt::maps::CWeightedPointsMap & 2. assign(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, o: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap) -> mrpt.pymrpt.mrpt.maps.CWeightedPointsMap C++: mrpt::maps::CWeightedPointsMap::operator=(const class mrpt::maps::CWeightedPointsMap &) --> class mrpt::maps::CWeightedPointsMap &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CWeightedPointsMap::clone() const --> class mrpt::rtti::CObject *

getPointWeight(...)
getPointWeight(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, index: int) -> int Gets the point weight, which is ignored in all classes (defaults to 1) but in those which actually store that field (Note: No checks are done for out-of-bounds index).   setPointWeight C++: mrpt::maps::CWeightedPointsMap::getPointWeight(size_t) const --> unsigned int

insertPointFast(...)
insertPointFast(*args, **kwargs) Overloaded function. 1. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, x: float, y: float) -> None 2. insertPointFast(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, x: float, y: float, z: float) -> None The virtual method for  *without* calling mark_as_modified()    C++: mrpt::maps::CWeightedPointsMap::insertPointFast(float, float, float) --> void

reserve(...)
reserve(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, newLength: int) -> None            from CPointsMap                 @{ C++: mrpt::maps::CWeightedPointsMap::reserve(size_t) --> void

resize(...)
resize(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, newLength: int) -> None C++: mrpt::maps::CWeightedPointsMap::resize(size_t) --> void

setPointWeight(...)
setPointWeight(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, index: int, w: int) -> None Sets the point weight, which is ignored in all classes but those which actually store that field (Note: No checks are done for out-of-bounds index). getPointWeight C++: mrpt::maps::CWeightedPointsMap::setPointWeight(size_t, unsigned long) --> void

setSize(...)
setSize(self: mrpt.pymrpt.mrpt.maps.CWeightedPointsMap, newLength: int) -> None C++: mrpt::maps::CWeightedPointsMap::setSize(size_t) --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CWeightedPointsMap::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CWeightedPointsMap::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data and other attributes defined here:

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CWeightedPointsMap.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CWeightedPointsMap.TMapDefinitionBase'>

Methods inherited from CPointsMap:

__iadd__(...)
__iadd__(self: mrpt.pymrpt.mrpt.maps.CPointsMap, anotherMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Inserts another map into this one. insertAnotherMap() C++: mrpt::maps::CPointsMap::operator+=(const class mrpt::maps::CPointsMap &) --> void

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> str Returns a short description of the map. C++: mrpt::maps::CPointsMap::asString() const --> std::string

boundingBox(...)
boundingBox(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> mrpt.pymrpt.mrpt.math.TBoundingBox_float_t Computes the bounding box of all the points, or (0,0 ,0,0, 0,0) if there are no points.   Results are cached unless the map is somehow modified to avoid repeated calculations. C++: mrpt::maps::CPointsMap::boundingBox() const --> struct mrpt::math::TBoundingBox_<float>

changeCoordinatesReference(...)
changeCoordinatesReference(*args, **kwargs) Overloaded function. 1. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose2D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose2D &) --> void 2. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Replace each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::poses::CPose3D &) --> void 3. changeCoordinatesReference(self: mrpt.pymrpt.mrpt.maps.CPointsMap, other: mrpt.pymrpt.mrpt.maps.CPointsMap, b: mrpt.pymrpt.mrpt.poses.CPose3D) -> None Copy all the points from "other" map to "this", replacing each point by (pose compounding operator). C++: mrpt::maps::CPointsMap::changeCoordinatesReference(const class mrpt::maps::CPointsMap &, const class mrpt::poses::CPose3D &) --> void

clipOutOfRange(...)
clipOutOfRange(self: mrpt.pymrpt.mrpt.maps.CPointsMap, point: mrpt::math::TPoint2D_<double>, maxRange: float) -> None Delete points which are more far than "maxRange" away from the given "point". C++: mrpt::maps::CPointsMap::clipOutOfRange(const struct mrpt::math::TPoint2D_<double> &, float) --> void

clipOutOfRangeInZ(...)
clipOutOfRangeInZ(self: mrpt.pymrpt.mrpt.maps.CPointsMap, zMin: float, zMax: float) -> None Delete points out of the given "z" axis range have been removed. C++: mrpt::maps::CPointsMap::clipOutOfRangeInZ(float, float) --> void

compute3DDistanceToMesh(...)
compute3DDistanceToMesh(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap2: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, maxDistForCorrespondence: float, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, correspondencesRatio: float) -> None Computes the matchings between this and another 3D points map.            This method matches each point in the other map with the centroid of the          3 closest points in 3D            from this map (if the distance is below a defined threshold).                                           [IN] The other map to compute the          matching with.                                   [IN] The pose of the other map as seen          from "this".    [IN] Maximum 2D linear distance          between two points to be matched.                           [OUT] The detected matchings pairs.                   [OUT] The ratio [0,1] of points in          otherMap with at least one correspondence. determineMatching3D C++: mrpt::maps::CPointsMap::compute3DDistanceToMesh(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, float, class mrpt::tfest::TMatchingPairListTempl<float> &, float &) --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float C++: mrpt::maps::CPointsMap::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None C++: mrpt::maps::CPointsMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

empty(...)
empty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool STL-like method to check whether the map is empty: C++: mrpt::maps::CPointsMap::empty() const --> bool

enableFilterByHeight(...)
enableFilterByHeight(*args, **kwargs) Overloaded function. 1. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. enableFilterByHeight(self: mrpt.pymrpt.mrpt.maps.CPointsMap, enable: bool) -> None Enable/disable the filter-by-height functionality setHeightFilterLevels Default upon construction is disabled. C++: mrpt::maps::CPointsMap::enableFilterByHeight(bool) --> void

extractCylinder(...)
extractCylinder(self: mrpt.pymrpt.mrpt.maps.CPointsMap, center: mrpt::math::TPoint2D_<double>, radius: float, zmin: float, zmax: float, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Extracts the points in the map within a cylinder in 3D defined the provided radius and zmin/zmax values. C++: mrpt::maps::CPointsMap::extractCylinder(const struct mrpt::math::TPoint2D_<double> &, const double, const double, const double, class mrpt::maps::CPointsMap *) --> void

extractPoints(...)
extractPoints(*args, **kwargs) Overloaded function. 1. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None 2. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float) -> None 3. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float) -> None 4. extractPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap, corner1: mrpt::math::TPoint3D_<double>, corner2: mrpt::math::TPoint3D_<double>, outMap: mrpt.pymrpt.mrpt.maps.CPointsMap, R: float, G: float, B: float) -> None Extracts the points in the map within the area defined by two corners.   The points are coloured according the R,G,B input data. C++: mrpt::maps::CPointsMap::extractPoints(const struct mrpt::math::TPoint3D_<double> &, const struct mrpt::math::TPoint3D_<double> &, class mrpt::maps::CPointsMap *, double, double, double) --> void

getHeightFilterLevels(...)
getHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Get the min/max Z levels for points to be actually inserted in the map enableFilterByHeight, setHeightFilterLevels C++: mrpt::maps::CPointsMap::getHeightFilterLevels(double &, double &) const --> void

getLargestDistanceFromOrigin(...)
getLargestDistanceFromOrigin(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> float This method returns the largest distance from the origin to any of the points, such as a sphere centered at the origin with this radius cover ALL the points in the map (the results are buffered, such as, if the map is not modified, the second call will be much faster than the first one). C++: mrpt::maps::CPointsMap::getLargestDistanceFromOrigin() const --> float

getLargestDistanceFromOriginNoRecompute(...)
getLargestDistanceFromOriginNoRecompute(self: mrpt.pymrpt.mrpt.maps.CPointsMap, output_is_valid: bool) -> float Like  but returns in = false if the distance was not already computed, skipping its computation then, unlike getLargestDistanceFromOrigin() C++: mrpt::maps::CPointsMap::getLargestDistanceFromOriginNoRecompute(bool &) const --> float

getPoint(...)
getPoint(*args, **kwargs) Overloaded function. 1. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Access to a given point from map, as a 2D point. First index is 0. Throws std::exception on index out of bound. setPoint, getPointFast C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &, float &) const --> void 2. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, float &, float &) const --> void 3. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &, double &) const --> void 4. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, double &, double &) const --> void 5. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint2D_<double> &) const --> void 6. getPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::getPoint(size_t, struct mrpt::math::TPoint3D_<double> &) const --> void

getPointFast(...)
getPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Just like  but without checking out-of-bound index and without returning the point weight, just XYZ. C++: mrpt::maps::CPointsMap::getPointFast(size_t, float &, float &, float &) const --> void

getPointRGB(...)
getPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float, R: float, G: float, B: float) -> None Access to a given point from map, and its colors, if the map defines them (othersise, R=G=B=1.0). First index is 0. The return value is the weight of the point (the times it has been fused) Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMap::getPointRGB(size_t, float &, float &, float &, float &, float &, float &) const --> void

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CPointsMap, outObj: mrpt::opengl::CSetOfObjects) -> None Returns a 3D object representing the map.   The color of the points is controlled by renderOptions C++: mrpt::maps::CPointsMap::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

hasColorPoints(...)
hasColorPoints(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Returns true if the point map has a color field for each point C++: mrpt::maps::CPointsMap::hasColorPoints() const --> bool

insertAnotherMap(...)
insertAnotherMap(*args, **kwargs) Overloaded function. 1. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> None 2. insertAnotherMap(self: mrpt.pymrpt.mrpt.maps.CPointsMap, otherMap: mrpt.pymrpt.mrpt.maps.CPointsMap, otherPose: mrpt.pymrpt.mrpt.poses.CPose3D, filterOutPointsAtZero: bool) -> None Insert the contents of another map into this one with some geometric transformation, without fusing close points. The other map whose points are to be inserted into this one. The pose of the other map in the coordinates of THIS map If true, points at (0,0,0) (in the frame of reference of `otherMap`) will be assumed to be invalid and will not be copied. fuseWith, addFrom C++: mrpt::maps::CPointsMap::insertAnotherMap(const class mrpt::maps::CPointsMap *, const class mrpt::poses::CPose3D &, const bool) --> void

insertPoint(...)
insertPoint(*args, **kwargs) Overloaded function. 1. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float) -> None 2. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float, z: float) -> None Provides a way to insert (append) individual points into the map: the missing fields of child classes (color, weight, etc) are left to their default values C++: mrpt::maps::CPointsMap::insertPoint(float, float, float) --> void 3. insertPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::insertPoint(const struct mrpt::math::TPoint3D_<double> &) --> void

insertPointRGB(...)
insertPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x: float, y: float, z: float, R: float, G: float, B: float) -> None overload (RGB data is ignored in classes without color information) C++: mrpt::maps::CPointsMap::insertPointRGB(float, float, float, float, float, float) --> void

internal_computeObservationLikelihood(...)
internal_computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CPointsMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float @} C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

internal_computeObservationLikelihoodPointCloud3D(...)
internal_computeObservationLikelihoodPointCloud3D(self: mrpt.pymrpt.mrpt.maps.CPointsMap, pc_in_map: mrpt.pymrpt.mrpt.poses.CPose3D, xs: float, ys: float, zs: float, num_pts: int) -> float C++: mrpt::maps::CPointsMap::internal_computeObservationLikelihoodPointCloud3D(const class mrpt::poses::CPose3D &, const float *, const float *, const float *, const unsigned long) const --> double

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Returns true if the map is empty/no observation has been inserted. C++: mrpt::maps::CPointsMap::isEmpty() const --> bool

isFilterByHeightEnabled(...)
isFilterByHeightEnabled(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> bool Return whether filter-by-height is enabled enableFilterByHeight C++: mrpt::maps::CPointsMap::isFilterByHeightEnabled() const --> bool

kdtree_distance(...)
kdtree_distance(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p1: float, idx_p2: int, size: int) -> float Returns the distance between the vector "p1[0:size-1]" and the data point with index "idx_p2" stored in the class: C++: mrpt::maps::CPointsMap::kdtree_distance(const float *, size_t, size_t) const --> float

kdtree_get_point_count(...)
kdtree_get_point_count(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Must return the number of data points C++: mrpt::maps::CPointsMap::kdtree_get_point_count() const --> size_t

kdtree_get_pt(...)
kdtree_get_pt(self: mrpt.pymrpt.mrpt.maps.CPointsMap, idx: int, dim: int) -> float Returns the dim'th component of the idx'th point in the class: C++: mrpt::maps::CPointsMap::kdtree_get_pt(size_t, int) const --> float

load2D_from_text_file(...)
load2D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y" coordinate pair, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load2D_from_text_file(const std::string &) --> bool

load2Dor3D_from_text_file(...)
load2Dor3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str, is_3D: bool) -> bool 2D or 3D generic implementation of  and load3D_from_text_file C++: mrpt::maps::CPointsMap::load2Dor3D_from_text_file(const std::string &, const bool) --> bool

load3D_from_text_file(...)
load3D_from_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Load from a text file. Each line should contain an "X Y Z" coordinate tuple, separated by whitespaces.    Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::load3D_from_text_file(const std::string &) --> bool

mark_as_modified(...)
mark_as_modified(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> None Users normally don't need to call this. Called by this class or children classes, set m_largestDistanceFromOriginIsUpdated=false, invalidates the kd-tree cache, and such. C++: mrpt::maps::CPointsMap::mark_as_modified() const --> void

save2D_to_text_file(...)
save2D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y" point coordinates.                 Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save2D_to_text_file(const std::string &) const --> bool

save3D_to_text_file(...)
save3D_to_text_file(self: mrpt.pymrpt.mrpt.maps.CPointsMap, file: str) -> bool Save to a text file. Each line will contain "X Y Z" point coordinates.      Returns false if any error occured, true elsewere. C++: mrpt::maps::CPointsMap::save3D_to_text_file(const std::string &) const --> bool

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CPointsMap, filNamePrefix: str) -> None This virtual method saves the map to a file "filNamePrefix"+< some_file_extension >, as an image or in any other applicable way (Notice that other methods to save the map may be implemented in classes implementing this virtual interface) C++: mrpt::maps::CPointsMap::saveMetricMapRepresentationToFile(const std::string &) const --> void

setHeightFilterLevels(...)
setHeightFilterLevels(self: mrpt.pymrpt.mrpt.maps.CPointsMap, _z_min: float, _z_max: float) -> None Set the min/max Z levels for points to be actually inserted in the map (only if  was called before). C++: mrpt::maps::CPointsMap::setHeightFilterLevels(const double, const double) --> void

setPoint(...)
setPoint(*args, **kwargs) Overloaded function. 1. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes a given point from map, with Z defaulting to 0 if not provided. Throws std::exception on index out of bound. C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float, float) --> void 2. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint2D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint2D_<double> &) --> void 3. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, p: mrpt::math::TPoint3D_<double>) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, const struct mrpt::math::TPoint3D_<double> &) --> void 4. setPoint(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float) -> None C++: mrpt::maps::CPointsMap::setPoint(size_t, float, float) --> void

setPointFast(...)
setPointFast(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float) -> None Changes the coordinates of the given point (0-based index), *without* checking for out-of-bounds and *without* calling mark_as_modified(). Also, color, intensity, or other data is left unchanged. setPoint C++: mrpt::maps::CPointsMap::setPointFast(size_t, float, float, float) --> void

setPointRGB(...)
setPointRGB(self: mrpt.pymrpt.mrpt.maps.CPointsMap, index: int, x: float, y: float, z: float, R: float, G: float, B: float) -> None overload (RGB data is ignored in classes without color information) C++: mrpt::maps::CPointsMap::setPointRGB(size_t, float, float, float, float, float, float) --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.CPointsMap) -> int Returns the number of stored points in the map. C++: mrpt::maps::CPointsMap::size() const --> size_t

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CPointsMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondence(float, float) const --> float

squareDistanceToClosestCorrespondenceT(...)
squareDistanceToClosestCorrespondenceT(self: mrpt.pymrpt.mrpt.maps.CPointsMap, p0: mrpt::math::TPoint2D_<double>) -> float C++: mrpt::maps::CPointsMap::squareDistanceToClosestCorrespondenceT(const struct mrpt::math::TPoint2D_<double> &) const --> float

Data descriptors inherited from CPointsMap:

insertionOptions

likelihoodOptions

renderOptions

Data and other attributes inherited from CPointsMap:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TInsertionOptions'>
With this struct options are provided to the observation insertion process. CObservation::insertIntoPointsMap

TLikelihoodOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TLikelihoodOptions'>
Options used when evaluating "computeObservationLikelihood" in the derived classes. CObservation::computeObservationLikelihood

TRenderOptions = <class 'mrpt.pymrpt.mrpt.maps.CPointsMap.TRenderOptions'>
Rendering options, used in getAs3DObject()

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None Erase all the contents of the map C++: mrpt::maps::CMetricMap::clear() --> void

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Importer:

getLoadPLYErrorString(...)
getLoadPLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Importer::getLoadPLYErrorString() const --> std::string

loadFromPlyFile(...)
loadFromPlyFile(*args, **kwargs) Overloaded function. 1. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str) -> bool 2. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str]) -> bool 3. loadFromPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Importer, filename: str, file_comments: List[str], file_obj_info: List[str]) -> bool Loads from a PLY file. The filename to open. It can be either in binary or text format. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error in the file format or reading it. To obtain more details on the error you can call getLoadPLYErrorString() C++: mrpt::opengl::PLY_Importer::loadFromPlyFile(const std::string &, class std::vector<std::string > *, class std::vector<std::string > *) --> bool

Methods inherited from mrpt.pymrpt.mrpt.opengl.PLY_Exporter:

getSavePLYErrorString(...)
getSavePLYErrorString(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter) -> str Return a description of the error if loadFromPlyFile() returned false, or an empty string if the file was loaded without problems. C++: mrpt::opengl::PLY_Exporter::getSavePLYErrorString() const --> std::string

saveToPlyFile(...)
saveToPlyFile(*args, **kwargs) Overloaded function. 1. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str) -> bool 2. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool) -> bool 3. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str]) -> bool 4. saveToPlyFile(self: mrpt.pymrpt.mrpt.opengl.PLY_Exporter, filename: str, save_in_binary: bool, file_comments: List[str], file_obj_info: List[str]) -> bool Saves to a PLY file. The filename to be saved. If provided (!=nullptr) the list of comment strings stored in the file will be returned. If provided (!=nullptr) the list of "object info" strings stored in the file will be returned. false on any error writing the file. To obtain more details on the error you can call getSavePLYErrorString() C++: mrpt::opengl::PLY_Exporter::saveToPlyFile(const std::string &, bool, const class std::vector<std::string > &, const class std::vector<std::string > &) const --> bool

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class CWirelessPowerGridMap2D(CRandomFieldGridMap2D)

    CWirelessPowerGridMap2D represents a PDF of wifi concentrations over a 2D area. There are a number of methods available to build the wifi grid-map, depending on the value of    "TMapRepresentation maptype" passed in the constructor (see CRandomFieldGridMap2D for a discussion). Update the map with insertIndividualReading() or insertObservation() mrpt::maps::CRandomFieldGridMap2D, mrpt::maps::CMetricMap, mrpt::containers::CDynamicGrid, The application icp-slam, mrpt::maps::CMultiMetricMap

Method resolution order:

CWirelessPowerGridMap2D

CRandomFieldGridMap2D

CMetricMap

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

mrpt.pymrpt.mrpt.system.CObservable

mrpt.pymrpt.mrpt.Stringifyable

mrpt.pymrpt.mrpt.opengl.Visualizable

mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CWirelessPowerGridMap2D::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float) -> None doc 4. __init__(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float) -> None doc 5. __init__(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float, arg3: float) -> None doc 6. __init__(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, arg1: float, arg2: float, arg3: float, arg4: float) -> None doc 7. __init__(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, mapType: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 8. __init__(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D) -> None 9. __init__(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, arg0: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, : mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D) -> mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D C++: mrpt::maps::CWirelessPowerGridMap2D::operator=(const class mrpt::maps::CWirelessPowerGridMap2D &) --> class mrpt::maps::CWirelessPowerGridMap2D &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CWirelessPowerGridMap2D::clone() const --> class mrpt::rtti::CObject *

getVisualizationInto(...)
getVisualizationInto(self: mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D, outObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns a 3D object representing the map   C++: mrpt::maps::CWirelessPowerGridMap2D::getVisualizationInto(class mrpt::opengl::CSetOfObjects &) const --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::CWirelessPowerGridMap2D::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::CWirelessPowerGridMap2D::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

insertionOptions

Data and other attributes defined here:

TInsertionOptions = <class 'mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D.TInsertionOptions'>
Parameters related with inserting observations into the map:

TMapDefinition = <class 'mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D.TMapDefinition'>

TMapDefinitionBase = <class 'mrpt.pymrpt.mrpt.maps.CWirelessPowerGridMap2D.TMapDefinitionBase'>

Methods inherited from CRandomFieldGridMap2D:

asString(...)
asString(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> str Returns a short description of the map. C++: mrpt::maps::CRandomFieldGridMap2D::asString() const --> std::string

cell2float(...)
cell2float(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, c: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float C++: mrpt::maps::CRandomFieldGridMap2D::cell2float(const struct mrpt::maps::TRandomFieldCell &) const --> float

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None Calls the base CMetricMap::clear Declared here to avoid ambiguity between the two clear() in both base classes. C++: mrpt::maps::CRandomFieldGridMap2D::clear() --> void

compute3DMatchingRatio(...)
compute3DMatchingRatio(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, params: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> float See docs in base class: in this class this always returns 0 C++: mrpt::maps::CRandomFieldGridMap2D::compute3DMatchingRatio(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, const struct mrpt::maps::TMatchingRatioParams &) const --> float

enableProfiler(...)
enableProfiler(*args, **kwargs) Overloaded function. 1. enableProfiler(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None 2. enableProfiler(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, enable: bool) -> None C++: mrpt::maps::CRandomFieldGridMap2D::enableProfiler(bool) --> void

enableVerbose(...)
enableVerbose(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, enable_verbose: bool) -> None C++: mrpt::maps::CRandomFieldGridMap2D::enableVerbose(bool) --> void

getAs3DObject(...)
getAs3DObject(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, meanObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects, varObj: mrpt.pymrpt.mrpt.opengl.CSetOfObjects) -> None Returns two 3D objects representing the mean and variance maps C++: mrpt::maps::CRandomFieldGridMap2D::getAs3DObject(class mrpt::opengl::CSetOfObjects &, class mrpt::opengl::CSetOfObjects &) const --> void

getAsBitmapFile(...)
getAsBitmapFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_img: mrpt.pymrpt.mrpt.img.CImage) -> None Returns an image just as described in   C++: mrpt::maps::CRandomFieldGridMap2D::getAsBitmapFile(class mrpt::img::CImage &) const --> void

getAsMatrix(...)
getAsMatrix(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_mat: mrpt.pymrpt.mrpt.math.CMatrixDynamic_double_t) -> None Like saveAsBitmapFile(), but returns the data in matrix form (first row in the matrix is the upper (y_max) part of the map) C++: mrpt::maps::CRandomFieldGridMap2D::getAsMatrix(class mrpt::math::CMatrixDynamic<double> &) const --> void

getMapType(...)
getMapType(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation Return the type of the random-field grid map, according to parameters passed on construction. C++: mrpt::maps::CRandomFieldGridMap2D::getMapType() --> enum mrpt::maps::CRandomFieldGridMap2D::TMapRepresentation

getMeanAndCov(...)
getMeanAndCov(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_cov: mrpt.pymrpt.mrpt.math.CMatrixDynamic_double_t) -> None Return the mean and covariance vector of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::getMeanAndCov(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CMatrixDynamic<double> &) const --> void

getMeanAndSTD(...)
getMeanAndSTD(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_STD: mrpt::math::CVectorDynamic<double>) -> None Return the mean and STD vectors of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::getMeanAndSTD(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CVectorDynamic<double> &) const --> void

insertIndividualReading(...)
insertIndividualReading(*args, **kwargs) Overloaded function. 1. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>) -> None 2. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool) -> None 3. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool, time_invariant: bool) -> None 4. insertIndividualReading(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, sensorReading: float, point: mrpt::math::TPoint2D_<double>, update_map: bool, time_invariant: bool, reading_stddev: float) -> None Direct update of the map with a reading in a given position of the map, using   the appropriate method according to mapType passed in the constructor. This is a direct way to update the map, an alternative to the generic insertObservation() method which works with mrpt::obs::CObservation objects. C++: mrpt::maps::CRandomFieldGridMap2D::insertIndividualReading(const double, const struct mrpt::math::TPoint2D_<double> &, const bool, const bool, const double) --> void

isEmpty(...)
isEmpty(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool Returns true if the map is empty/no observation has been inserted (in this class it always return false, unless redefined otherwise in base classes) C++: mrpt::maps::CRandomFieldGridMap2D::isEmpty() const --> bool

isEnabledVerbose(...)
isEnabledVerbose(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool C++: mrpt::maps::CRandomFieldGridMap2D::isEnabledVerbose() const --> bool

isProfilerEnabled(...)
isProfilerEnabled(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> bool C++: mrpt::maps::CRandomFieldGridMap2D::isProfilerEnabled() const --> bool

predictMeasurement(...)
predictMeasurement(*args, **kwargs) Overloaded function. 1. predictMeasurement(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x: float, y: float, out_predict_response: float, out_predict_response_variance: float, do_sensor_normalization: bool) -> None 2. predictMeasurement(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x: float, y: float, out_predict_response: float, out_predict_response_variance: float, do_sensor_normalization: bool, interp_method: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TGridInterpolationMethod) -> None Returns the prediction of the measurement at some (x,y) coordinates, and its certainty (in the form of the expected variance).   C++: mrpt::maps::CRandomFieldGridMap2D::predictMeasurement(const double, const double, double &, double &, bool, const enum mrpt::maps::CRandomFieldGridMap2D::TGridInterpolationMethod) --> void

resize(...)
resize(*args, **kwargs) Overloaded function. 1. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> None 2. resize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_x_min: float, new_x_max: float, new_y_min: float, new_y_max: float, defaultValueNewCells: mrpt.pymrpt.mrpt.maps.TRandomFieldCell, additionalMarginMeters: float) -> None Changes the size of the grid, maintaining previous contents. setSize C++: mrpt::maps::CRandomFieldGridMap2D::resize(double, double, double, double, const struct mrpt::maps::TRandomFieldCell &, double) --> void

saveAsBitmapFile(...)
saveAsBitmapFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filName: str) -> None Save the current map as a graphical file (BMP,PNG,...). The file format will be derived from the file extension (see CImage::saveToFile )   It depends on the map representation model:                 mrAchim: Each pixel is the ratio                 mrKalmanFilter: Each pixel is the mean value of the Gaussian that represents each cell.           C++: mrpt::maps::CRandomFieldGridMap2D::saveAsBitmapFile(const std::string &) const --> void

saveAsMatlab3DGraph(...)
saveAsMatlab3DGraph(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filName: str) -> None Save a matlab ".m" file which represents as 3D surfaces the mean and a given confidence level for the concentration of each cell.   This method can only be called in a KF map model. C++: mrpt::maps::CRandomFieldGridMap2D::saveAsMatlab3DGraph(const std::string &) const --> void

saveMetricMapRepresentationToFile(...)
saveMetricMapRepresentationToFile(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, filNamePrefix: str) -> None The implementation in this class just calls all the corresponding method of the contained metric maps C++: mrpt::maps::CRandomFieldGridMap2D::saveMetricMapRepresentationToFile(const std::string &) const --> void

setCellsConnectivity(...)
setCellsConnectivity(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, new_connectivity_descriptor: mrpt::maps::CRandomFieldGridMap2D::ConnectivityDescriptor) -> None Sets a custom object to define the connectivity between cells. Must call clear() or setSize() afterwards for the changes to take place. C++: mrpt::maps::CRandomFieldGridMap2D::setCellsConnectivity(const class std::shared_ptr<struct mrpt::maps::CRandomFieldGridMap2D::ConnectivityDescriptor> &) --> void

setMeanAndSTD(...)
setMeanAndSTD(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, out_means: mrpt::math::CVectorDynamic<double>, out_STD: mrpt::math::CVectorDynamic<double>) -> None Load the mean and STD vectors of the full Kalman filter estimate (works for all KF-based methods). C++: mrpt::maps::CRandomFieldGridMap2D::setMeanAndSTD(class mrpt::math::CVectorDynamic<double> &, class mrpt::math::CVectorDynamic<double> &) --> void

setSize(...)
setSize(*args, **kwargs) Overloaded function. 1. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float) -> None 2. setSize(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D, x_min: float, x_max: float, y_min: float, y_max: float, resolution: float, fill_value: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> None Changes the size of the grid, erasing previous contents.    Optional user-supplied object that will visit all grid cells to define their connectivity with neighbors and the strength of existing edges. If present, it overrides all options in insertionOptions resize C++: mrpt::maps::CRandomFieldGridMap2D::setSize(const double, const double, const double, const double, const double, const struct mrpt::maps::TRandomFieldCell *) --> void

updateMapEstimation(...)
updateMapEstimation(self: mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D) -> None Run the method-specific procedure required to ensure that the mean & variances are up-to-date with all inserted observations. C++: mrpt::maps::CRandomFieldGridMap2D::updateMapEstimation() --> void

Data and other attributes inherited from CRandomFieldGridMap2D:

ConnectivityDescriptor = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.ConnectivityDescriptor'>
Base class for user-supplied objects capable of describing cells connectivity, used to build prior factors of the MRF graph. setCellsConnectivity()

TGridInterpolationMethod = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TGridInterpolationMethod'>

TInsertionOptionsCommon = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TInsertionOptionsCommon'>
Parameters common to any derived class. Derived classes should derive a new struct from this one, plus "public CLoadableOptions", and call the internal_* methods where appropiate to deal with the variables declared here. Derived classes instantions of their "TInsertionOptions" MUST set the pointer "m_insertOptions_common" upon construction.

TMapRepresentation = <class 'mrpt.pymrpt.mrpt.maps.CRandomFieldGridMap2D.TMapRepresentation'>

gimBilinear = <TGridInterpolationMethod.gimBilinear: 1>

gimNearest = <TGridInterpolationMethod.gimNearest: 0>

mrAchim = <TMapRepresentation.mrKernelDM: 0>

mrGMRF_SD = <TMapRepresentation.mrGMRF_SD: 4>

mrKalmanApproximate = <TMapRepresentation.mrKalmanApproximate: 2>

mrKalmanFilter = <TMapRepresentation.mrKalmanFilter: 1>

mrKernelDM = <TMapRepresentation.mrKernelDM: 0>

mrKernelDMV = <TMapRepresentation.mrKernelDMV: 3>

Methods inherited from CMetricMap:

auxParticleFilterCleanUp(...)
auxParticleFilterCleanUp(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> None This method is called at the end of each "prediction-update-map insertion" cycle within "mrpt::slam::CMetricMapBuilderRBPF::processActionObservation".   This method should normally do nothing, but in some cases can be used to free auxiliary cached variables. C++: mrpt::maps::CMetricMap::auxParticleFilterCleanUp() --> void

canComputeObservationLikelihood(...)
canComputeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observation. computeObservationLikelihood, genericMapParams.enableObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationLikelihood(const class mrpt::obs::CObservation &) const --> bool

canComputeObservationsLikelihood(...)
canComputeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool Returns true if this map is able to compute a sensible likelihood function for this observation (i.e. an occupancy grid map cannot with an image). See: The observations. canComputeObservationLikelihood C++: mrpt::maps::CMetricMap::canComputeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &) const --> bool

computeObservationLikelihood(...)
computeObservationLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Computes the log-likelihood of a given observation given an arbitrary robot 3D pose. See: The robot's pose the observation is supposed to be taken from. The observation. This method returns a log-likelihood. Used in particle filter algorithms, see: CMultiMetricMapPDF::update C++: mrpt::maps::CMetricMap::computeObservationLikelihood(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D &) const --> double

computeObservationsLikelihood(...)
computeObservationsLikelihood(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, takenFrom: mrpt.pymrpt.mrpt.poses.CPose3D) -> float Returns the sum of the log-likelihoods of each individual observation within a mrpt::obs::CSensoryFrame. See: The robot's pose the observation is supposed to be taken from. The set of observations in a CSensoryFrame. This method returns a log-likelihood. canComputeObservationsLikelihood C++: mrpt::maps::CMetricMap::computeObservationsLikelihood(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D &) --> double

determineMatching2D(...)
determineMatching2D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose2D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matching between this and another 2D point map, which includes finding:    - The set of points pairs in each map    - The mean squared distance between corresponding pairs.    The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.    This method is the most time critical one into ICP-like algorithms.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching2D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose2D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

determineMatching3D(...)
determineMatching3D(self: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMap: mrpt.pymrpt.mrpt.maps.CMetricMap, otherMapPose: mrpt.pymrpt.mrpt.poses.CPose3D, correspondences: mrpt.pymrpt.mrpt.tfest.TMatchingPairListTempl_float_t, params: mrpt.pymrpt.mrpt.maps.TMatchingParams, extraResults: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None Computes the matchings between this and another 3D points map - method used in 3D-ICP.   This method finds the set of point pairs in each map.   The method is the most time critical one into ICP-like algorithms.   The algorithm is:                 - For each point in "otherMap":                         - Transform the point according to otherMapPose                         - Search with a KD-TREE the closest correspondences in "this" map.                         - Add to the set of candidate matchings, if it passes all the thresholds in params.         [IN] The other map to compute the matching with.     [IN] The pose of the other map as seen from "this".           [IN] Parameters for the determination of pairings. [OUT] The detected matchings pairs.     [OUT] Other results. compute3DMatchingRatio C++: mrpt::maps::CMetricMap::determineMatching3D(const class mrpt::maps::CMetricMap *, const class mrpt::poses::CPose3D &, class mrpt::tfest::TMatchingPairListTempl<float> &, const struct mrpt::maps::TMatchingParams &, struct mrpt::maps::TMatchingExtraResults &) const --> void

getAsSimplePointsMap(...)
getAsSimplePointsMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap) -> mrpt::maps::CSimplePointsMap C++: mrpt::maps::CMetricMap::getAsSimplePointsMap() --> class mrpt::maps::CSimplePointsMap *

insertObs(...)
insertObs(*args, **kwargs) Overloaded function. 1. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation) -> bool 2. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, obs: mrpt.pymrpt.mrpt.obs.CObservation, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CObservation &, const class mrpt::poses::CPose3D *) --> bool 3. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame) -> bool 4. insertObs(self: mrpt.pymrpt.mrpt.maps.CMetricMap, sf: mrpt::obs::CSensoryFrame, robotPose: mrpt.pymrpt.mrpt.poses.CPose3D) -> bool C++: mrpt::maps::CMetricMap::insertObs(const class mrpt::obs::CSensoryFrame &, const class mrpt::poses::CPose3D *) --> bool

loadFromProbabilisticPosesAndObservations(...)
loadFromProbabilisticPosesAndObservations(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None Load the map contents from a CSimpleMap object, erasing all previous content of the map. This is done invoking `insertObservation()` for each observation at the mean 3D robot pose of each pose-observations pair in the CSimpleMap object. insertObservation, CSimpleMap std::exception Some internal steps in invoked methods can raise exceptions on invalid parameters, etc... C++: mrpt::maps::CMetricMap::loadFromProbabilisticPosesAndObservations(const class mrpt::maps::CSimpleMap &) --> void

loadFromSimpleMap(...)
loadFromSimpleMap(self: mrpt.pymrpt.mrpt.maps.CMetricMap, Map: mrpt::maps::CSimpleMap) -> None ! C++: mrpt::maps::CMetricMap::loadFromSimpleMap(const class mrpt::maps::CSimpleMap &) --> void

squareDistanceToClosestCorrespondence(...)
squareDistanceToClosestCorrespondence(self: mrpt.pymrpt.mrpt.maps.CMetricMap, x0: float, y0: float) -> float Returns the square distance from the 2D point (x0,y0) to the closest correspondence in the map. C++: mrpt::maps::CMetricMap::squareDistanceToClosestCorrespondence(float, float) const --> float

Data descriptors inherited from CMetricMap:

genericMapParams

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Methods inherited from mrpt.pymrpt.mrpt.opengl.Visualizable:

getVisualization(...)
getVisualization(self: mrpt.pymrpt.mrpt.opengl.Visualizable) -> mrpt::opengl::CSetOfObjects Creates 3D primitives representing this objects. This is equivalent to getVisualizationInto() but creating, and returning by value, a new rpt::opengl::CSetOfObjects::Ptr shared pointer. getVisualizationInto() C++: mrpt::opengl::Visualizable::getVisualization() const --> class std::shared_ptr<class mrpt::opengl::CSetOfObjects>

Methods inherited from mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t:

cellByIndex(...)
cellByIndex(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cx: int, cy: int) -> mrpt::maps::TRandomFieldCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::cellByIndex(unsigned int, unsigned int) --> struct mrpt::maps::TRandomFieldCell *

cellByPos(...)
cellByPos(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float, y: float) -> mrpt::maps::TRandomFieldCell C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::cellByPos(double, double) --> struct mrpt::maps::TRandomFieldCell *

fill(...)
fill(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, value: mrpt::maps::TRandomFieldCell) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::fill(const struct mrpt::maps::TRandomFieldCell &) --> void

getResolution(...)
getResolution(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getResolution() const --> double

getSizeX(...)
getSizeX(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getSizeX() const --> size_t

getSizeY(...)
getSizeY(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getSizeY() const --> size_t

getXMax(...)
getXMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getXMax() const --> double

getXMin(...)
getXMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getXMin() const --> double

getYMax(...)
getYMax(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getYMax() const --> double

getYMin(...)
getYMin(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::getYMin() const --> double

idx2cxcy(...)
idx2cxcy(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, idx: int, cx: int, cy: int) -> None C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2cxcy(int, int &, int &) const --> void

idx2x(...)
idx2x(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cx: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2x(int) const --> double

idx2y(...)
idx2y(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, cy: int) -> float C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::idx2y(int) const --> double

saveToTextFile(...)
saveToTextFile(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, fileName: str) -> bool C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::saveToTextFile(const std::string &) const --> bool

x2idx(...)
x2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::x2idx(double) const --> int

xy2idx(...)
xy2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, x: float, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::xy2idx(double, double) const --> int

y2idx(...)
y2idx(self: mrpt.pymrpt.mrpt.containers.CDynamicGrid_mrpt_maps_TRandomFieldCell_t, y: float) -> int C++: mrpt::containers::CDynamicGrid<mrpt::maps::TRandomFieldCell>::y2idx(double) const --> int

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class OccGridCellTraits(pybind11_builtins.pybind11_object)


Method resolution order:

OccGridCellTraits

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(self: mrpt.pymrpt.mrpt.maps.OccGridCellTraits) -> None

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class THeightGridmapCell(pybind11_builtins.pybind11_object)

    The contents of each cell in a CHeightGridMap2D map

Method resolution order:

THeightGridmapCell

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(self: mrpt.pymrpt.mrpt.maps.THeightGridmapCell) -> None

Data descriptors defined here:

h

u

v

var

w

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class TMapGenericParams(mrpt.pymrpt.mrpt.config.CLoadableOptions, mrpt.pymrpt.mrpt.serialization.CSerializable)

    Common params to all maps derived from mrpt::maps::CMetricMap

Method resolution order:

TMapGenericParams

mrpt.pymrpt.mrpt.config.CLoadableOptions

mrpt.pymrpt.mrpt.serialization.CSerializable

mrpt.pymrpt.mrpt.rtti.CObject

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

GetRuntimeClass(...)
GetRuntimeClass(self: mrpt.pymrpt.mrpt.maps.TMapGenericParams) -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::TMapGenericParams::GetRuntimeClass() const --> const struct mrpt::rtti::TRuntimeClassId *

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.TMapGenericParams, arg0: mrpt.pymrpt.mrpt.maps.TMapGenericParams) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.TMapGenericParams, arg0: mrpt.pymrpt.mrpt.maps.TMapGenericParams) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.TMapGenericParams) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.TMapGenericParams, : mrpt.pymrpt.mrpt.maps.TMapGenericParams) -> mrpt.pymrpt.mrpt.maps.TMapGenericParams C++: mrpt::maps::TMapGenericParams::operator=(const class mrpt::maps::TMapGenericParams &) --> class mrpt::maps::TMapGenericParams &

clone(...)
clone(self: mrpt.pymrpt.mrpt.maps.TMapGenericParams) -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::TMapGenericParams::clone() const --> class mrpt::rtti::CObject *

loadFromConfigFile(...)
loadFromConfigFile(self: mrpt.pymrpt.mrpt.maps.TMapGenericParams, source: mrpt::config::CConfigFileBase, sectionNamePrefix: str) -> None C++: mrpt::maps::TMapGenericParams::loadFromConfigFile(const class mrpt::config::CConfigFileBase &, const std::string &) --> void

saveToConfigFile(...)
saveToConfigFile(self: mrpt.pymrpt.mrpt.maps.TMapGenericParams, target: mrpt::config::CConfigFileBase, section: str) -> None C++: mrpt::maps::TMapGenericParams::saveToConfigFile(class mrpt::config::CConfigFileBase &, const std::string &) const --> void

Static methods defined here:

CreateObject(...) from builtins.PyCapsule
CreateObject() -> mrpt.pymrpt.mrpt.rtti.CObject C++: mrpt::maps::TMapGenericParams::CreateObject() --> class std::shared_ptr<class mrpt::rtti::CObject>

GetRuntimeClassIdStatic(...) from builtins.PyCapsule
GetRuntimeClassIdStatic() -> mrpt.pymrpt.mrpt.rtti.TRuntimeClassId C++: mrpt::maps::TMapGenericParams::GetRuntimeClassIdStatic() --> const struct mrpt::rtti::TRuntimeClassId &

Data descriptors defined here:

enableObservationInsertion

enableObservationLikelihood

enableSaveAs3DObject

Methods inherited from mrpt.pymrpt.mrpt.config.CLoadableOptions:

dumpToConsole(...)
dumpToConsole(self: mrpt.pymrpt.mrpt.config.CLoadableOptions) -> None Just like  but sending the text to the console (std::cout) C++: mrpt::config::CLoadableOptions::dumpToConsole() const --> void

loadFromConfigFileName(...)
loadFromConfigFileName(self: mrpt.pymrpt.mrpt.config.CLoadableOptions, config_file: str, section: str) -> None Behaves like loadFromConfigFile, but you can pass directly a file name and a temporary CConfigFile object will be created automatically to load the file. loadFromConfigFile C++: mrpt::config::CLoadableOptions::loadFromConfigFileName(const std::string &, const std::string &) --> void

saveToConfigFileName(...)
saveToConfigFileName(self: mrpt.pymrpt.mrpt.config.CLoadableOptions, config_file: str, section: str) -> None Behaves like saveToConfigFile, but you can pass directly a file name and a temporary CConfigFile object will be created automatically to save the file. saveToConfigFile, loadFromConfigFileName C++: mrpt::config::CLoadableOptions::saveToConfigFileName(const std::string &, const std::string &) const --> void

Methods inherited from mrpt.pymrpt.mrpt.rtti.CObject:

duplicateGetSmartPtr(...)
duplicateGetSmartPtr(self: mrpt.pymrpt.mrpt.rtti.CObject) -> mrpt.pymrpt.mrpt.rtti.CObject Makes a deep copy of the object and returns a smart pointer to it C++: mrpt::rtti::CObject::duplicateGetSmartPtr() const --> class std::shared_ptr<class mrpt::rtti::CObject>

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class TMatchingExtraResults(pybind11_builtins.pybind11_object)

    Additional results from the determination of matchings between point clouds, etc., apart from the pairings themselves CMetricMap::determineMatching2D, CMetricMap::determineMatching3D

Method resolution order:

TMatchingExtraResults

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(self: mrpt.pymrpt.mrpt.maps.TMatchingExtraResults) -> None

Data descriptors defined here:

correspondencesRatio

sumSqrDist

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class TMatchingParams(pybind11_builtins.pybind11_object)

    Parameters for the determination of matchings between point clouds, etc. CMetricMap::determineMatching2D, CMetricMap::determineMatching3D

Method resolution order:

TMatchingParams

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(self: mrpt.pymrpt.mrpt.maps.TMatchingParams) -> None

Data descriptors defined here:

angularDistPivotPoint

decimation_other_map_points

maxAngularDistForCorrespondence

maxDistForCorrespondence

offset_other_map_points

onlyKeepTheClosest

onlyUniqueRobust

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class TMatchingRatioParams(pybind11_builtins.pybind11_object)

    Parameters for CMetricMap::compute3DMatchingRatio()

Method resolution order:

TMatchingRatioParams

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams, arg0: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.TMatchingRatioParams, : mrpt.pymrpt.mrpt.maps.TMatchingRatioParams) -> mrpt.pymrpt.mrpt.maps.TMatchingRatioParams C++: mrpt::maps::TMatchingRatioParams::operator=(const struct mrpt::maps::TMatchingRatioParams &) --> struct mrpt::maps::TMatchingRatioParams &

Data descriptors defined here:

maxDistForCorr

maxMahaDistForCorr

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class TRandomFieldCell(pybind11_builtins.pybind11_object)

    The contents of each cell in a CRandomFieldGridMap2D map.

Method resolution order:

TRandomFieldCell

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.TRandomFieldCell, kfmean_dm_mean: float) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.TRandomFieldCell, kfmean_dm_mean: float, kfstd_dmmeanw: float) -> None

dm_mean(...)
dm_mean(self: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float [Kernel-methods only] The cumulative weighted readings of this cell C++: mrpt::maps::TRandomFieldCell::dm_mean() --> double &

dm_mean_w(...)
dm_mean_w(self: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float [Kernel-methods only] The cumulative weights (concentration = alpha * dm_mean / dm_mean_w + (1-alpha)*r0 ) C++: mrpt::maps::TRandomFieldCell::dm_mean_w() --> double &

gmrf_mean(...)
gmrf_mean(self: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float [GMRF only] The mean value of this cell C++: mrpt::maps::TRandomFieldCell::gmrf_mean() --> double &

gmrf_std(...)
gmrf_std(self: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float C++: mrpt::maps::TRandomFieldCell::gmrf_std() --> double &

kf_mean(...)
kf_mean(self: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float [KF-methods only] The mean value of this cell C++: mrpt::maps::TRandomFieldCell::kf_mean() --> double &

kf_std(...)
kf_std(self: mrpt.pymrpt.mrpt.maps.TRandomFieldCell) -> float [KF-methods only] The standard deviation value of this cell C++: mrpt::maps::TRandomFieldCell::kf_std() --> double &

Data descriptors defined here:

dmv_var_mean

last_updated

param1_

param2_

updated_std

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class TRandomFieldVoxel(pybind11_builtins.pybind11_object)


Method resolution order:

TRandomFieldVoxel

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.TRandomFieldVoxel) -> None doc 2. __init__(self: mrpt.pymrpt.mrpt.maps.TRandomFieldVoxel, _mean_value: float) -> None doc 3. __init__(self: mrpt.pymrpt.mrpt.maps.TRandomFieldVoxel, _mean_value: float, _stddev_value: float) -> None

Data descriptors defined here:

mean_value

stddev_value

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class TSetOfMetricMapInitializers(mrpt.pymrpt.mrpt.config.CLoadableOptions)

    A set of TMetricMapInitializer structures, passed to the constructor CMultiMetricMap::CMultiMetricMap See the comments for TSetOfMetricMapInitializers::loadFromConfigFile, and "CMultiMetricMap::setListOfMaps" for   effectively creating the list of desired maps. CMultiMetricMap::CMultiMetricMap, CLoadableOptions

Method resolution order:

TSetOfMetricMapInitializers

mrpt.pymrpt.mrpt.config.CLoadableOptions

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers, arg0: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers) -> None 3. __init__(self: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers, arg0: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers, : mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers) -> mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers C++: mrpt::maps::TSetOfMetricMapInitializers::operator=(const class mrpt::maps::TSetOfMetricMapInitializers &) --> class mrpt::maps::TSetOfMetricMapInitializers &

clear(...)
clear(self: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers) -> None C++: mrpt::maps::TSetOfMetricMapInitializers::clear() --> void

loadFromConfigFile(...)
loadFromConfigFile(self: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers, source: mrpt::config::CConfigFileBase, sectionName: str) -> None Loads the configuration for the set of internal maps from a textual definition in an INI-like file.   The format of the ini file is defined in CConfigFile. The list of maps and their options    will be loaded from a handle of sections:      Where:                 - ##: Represents the index of the map (e.g. "00","01",...)                 - By default, the variables into each "TOptions" structure of the maps are defined in textual form by the same name of the corresponding C++ variable (e.g. "float resolution;" -> "resolution=0.10") Examples of map definitions can be found in the '.ini' files provided in the demo directories: "share/mrpt/config-files/" C++: mrpt::maps::TSetOfMetricMapInitializers::loadFromConfigFile(const class mrpt::config::CConfigFileBase &, const std::string &) --> void

saveToConfigFile(...)
saveToConfigFile(self: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers, target: mrpt::config::CConfigFileBase, section: str) -> None C++: mrpt::maps::TSetOfMetricMapInitializers::saveToConfigFile(class mrpt::config::CConfigFileBase &, const std::string &) const --> void

size(...)
size(self: mrpt.pymrpt.mrpt.maps.TSetOfMetricMapInitializers) -> int C++: mrpt::maps::TSetOfMetricMapInitializers::size() const --> size_t

Methods inherited from mrpt.pymrpt.mrpt.config.CLoadableOptions:

dumpToConsole(...)
dumpToConsole(self: mrpt.pymrpt.mrpt.config.CLoadableOptions) -> None Just like  but sending the text to the console (std::cout) C++: mrpt::config::CLoadableOptions::dumpToConsole() const --> void

loadFromConfigFileName(...)
loadFromConfigFileName(self: mrpt.pymrpt.mrpt.config.CLoadableOptions, config_file: str, section: str) -> None Behaves like loadFromConfigFile, but you can pass directly a file name and a temporary CConfigFile object will be created automatically to load the file. loadFromConfigFile C++: mrpt::config::CLoadableOptions::loadFromConfigFileName(const std::string &, const std::string &) --> void

saveToConfigFileName(...)
saveToConfigFileName(self: mrpt.pymrpt.mrpt.config.CLoadableOptions, config_file: str, section: str) -> None Behaves like saveToConfigFile, but you can pass directly a file name and a temporary CConfigFile object will be created automatically to save the file. saveToConfigFile, loadFromConfigFileName C++: mrpt::config::CLoadableOptions::saveToConfigFileName(const std::string &, const std::string &) const --> void

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class mrptEventMetricMapClear(mrpt.pymrpt.mrpt.system.mrptEvent)

    Event emitted by a metric up upon call of clear() CMetricMap

Method resolution order:

mrptEventMetricMapClear

mrpt.pymrpt.mrpt.system.mrptEvent

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(self: mrpt.pymrpt.mrpt.maps.mrptEventMetricMapClear, smap: mrpt::maps::CMetricMap) -> None

assign(...)
assign(self: mrpt.pymrpt.mrpt.maps.mrptEventMetricMapClear, : mrpt.pymrpt.mrpt.maps.mrptEventMetricMapClear) -> mrpt.pymrpt.mrpt.maps.mrptEventMetricMapClear C++: mrpt::maps::mrptEventMetricMapClear::operator=(const class mrpt::maps::mrptEventMetricMapClear &) --> class mrpt::maps::mrptEventMetricMapClear &

Data descriptors inherited from mrpt.pymrpt.mrpt.system.mrptEvent:

timestamp

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.

class mrptEventMetricMapInsert(mrpt.pymrpt.mrpt.system.mrptEvent)

    Event emitted by a metric up upon a succesful call to insertObservation() CMetricMap

Method resolution order:

mrptEventMetricMapInsert

mrpt.pymrpt.mrpt.system.mrptEvent

pybind11_builtins.pybind11_object

builtins.object

Methods defined here:

__init__(...)
__init__(*args, **kwargs) Overloaded function. 1. __init__(self: mrpt.pymrpt.mrpt.maps.mrptEventMetricMapInsert, arg0: mrpt.pymrpt.mrpt.maps.mrptEventMetricMapInsert) -> None 2. __init__(self: mrpt.pymrpt.mrpt.maps.mrptEventMetricMapInsert, arg0: mrpt.pymrpt.mrpt.maps.mrptEventMetricMapInsert) -> None

Readonly properties defined here:

inserted_robotPose

Methods inherited from mrpt.pymrpt.mrpt.system.mrptEvent:

assign(...)
assign(self: mrpt.pymrpt.mrpt.system.mrptEvent, : mrpt.pymrpt.mrpt.system.mrptEvent) -> mrpt.pymrpt.mrpt.system.mrptEvent C++: mrpt::system::mrptEvent::operator=(const class mrpt::system::mrptEvent &) --> class mrpt::system::mrptEvent &

Data descriptors inherited from mrpt.pymrpt.mrpt.system.mrptEvent:

timestamp

Static methods inherited from pybind11_builtins.pybind11_object:

__new__(*args, **kwargs) from pybind11_builtins.pybind11_type
Create and return a new object.  See help(type) for accurate signature.