FastMarching

Inheritance diagram

Inheritance diagram of ORSModel.ors.FastMarching, ORSModel.ors.Unmanaged, ORSModel.ors.ORSBaseClass

Classes

FastMarching

class ORSModel.ors.FastMarching

Bases: ORSModel.ors.Unmanaged

cleanSpeedMapChannel(self, outputChannel: ORSModel.ors.Channel) → None

Remove boundary or non reached value from a speed mapChannel.

Parameters:outputChannel (ORSModel.ors.Channel) – a distance map Channel (an Channel)
continueDistanceMapForNBIteration(self, lOutputChannelSpeedMap: ORSModel.ors.Channel, forNbIteration: int, autoUpdateROI: bool) → None
Parameters:
  • lOutputChannelSpeedMap (ORSModel.ors.Channel) –
  • forNbIteration (int) –
  • autoUpdateROI (bool) –
createDistanceMap(self, inChannelDistanceMap: ORSModel.ors.Channel, positionTripleInSourceRef: int, nbPosition: int, lMaskChannel: ORSModel.ors.Channel, traceBackChannel: ORSModel.ors.Channel) → Channel
Parameters:
Returns:

output (ORSModel.ors.Channel) –

createDistanceMapForNBIteration(self, lOutputChannelSpeedMap: ORSModel.ors.Channel, forNbIteration: int, autoUpdateROI: bool, lMaskChannel: ORSModel.ors.Channel) → None
Parameters:
createDistanceMapWithMask(self, inChannelDistanceMap: ORSModel.ors.Channel, lMaskChannel: ORSModel.ors.Channel) → Channel
Parameters:
Returns:

output (ORSModel.ors.Channel) –

getClassNameStatic() → str

getClassNameStatic

Returns:output (str) –
getEuclideanBias(self) → float

get the Euclidean bias that will be the minimumDijkstra distance between voxels

Note

Neighbor of distance 1 will have a bias of spacialTerm

Note

Neighbor of distance sqrt(2) will have a bias of sqrt(2)*spacialTerm

Note

Neighbor of distance sqrt(3) will have a bias of sqrt(3)*spacialTerm

Returns:output (float) – the minimum distance between voxel (a double)
getForcedMeanValue(self) → float
Returns:output (float) –
getIndexOfStopPointReach(self) → int
Returns:output (int) –
getMaxValueToConsider(self) → float
Returns:output (float) –
getMinValueToConsider(self) → float
Returns:output (float) –
getROI(self, index: int) → ROI

Retrieves a particularROI from the index specified slot.

Note

A maximum of 10 ROIs can be provided. The ROIs provided must be of the same shape as the input channel.

Parameters:index (int) – the slot index (an unsigned char)
Returns:output (ORSModel.ors.ROI) – the ROI associated with this slot index (an ROI), or NULL if no ROI is at that slot
getROICount(self) → int

Returns the number of ROIs that have been set as sources.

Note

A maximum of 10 ROI can be provided.

Returns:output (int) – the number of ROIs that have been provided (an char)
getStopValue(self) → float
Returns:output (float) –
getStopWhenValueIsEncountered(self) → bool
Returns:output (bool) –
getUsedForcedMean(self) → bool
Returns:output (bool) –
none() → FastMarching
Returns:output (FastMarching) –
recomputeValueWindow(self, aVolumeROI: ORSModel.ors.ROI) → None
Parameters:aVolumeROI (ORSModel.ors.ROI) –
resetROIs(self) → None

Empties all the sourceROI slots.

setEuclideanBias(self, EuclideanBias: float) → None

Provides an Euclidean bias that will be the minimumDijkstra distance between voxels.

Note

Neighbors of distance 1 will have a bias of spacialTerm.

Note

Neighbors of distance sqrt(2) will have a bias of sqrt(2)*spacialTerm.

Note

Neighbors of distance sqrt(3) will have a bias of sqrt(3)*spacialTerm.

Parameters:EuclideanBias (float) – the minimum distance between voxels (a double)
setForcedMeanValue(self, aVal: float) → None
Parameters:aVal (float) –
setInputChannelAndWorkingArea(self, inputChannel: ORSModel.ors.Channel, minX: int, minY: int, minZ: int, maxX: int, maxY: int, maxZ: int, currentT: int) → None

Sets the channel that will be used by theFastMarching algorithm to calculate distance.

Note

The min and max boundaries must not describe a space bigger than the input channel.

Parameters:
  • inputChannel (ORSModel.ors.Channel) – the input channel (an Channel)
  • minX (int) – the minimum X index in the input channel (an integer)
  • minY (int) – the minimum Y index in the input channel (an integer) TODO DOCUMENT_ME: Should this be removed?
  • minZ (int) – the minimum Z index in the input channel (an unsigned short)
  • maxX (int) – the maximum X index in the input channel (an integer)
  • maxY (int) – the maximum Y index in the input channel (an integer) TODO DOCUMENT_ME
  • maxZ (int) – the maximum Z index in the input channel (an unsigned short)
  • currentT (int) – the current time point (an unsigned short)
setMaxValueToConsider(self, maxValue: float) → None
Parameters:maxValue (float) –
setMinValueToConsider(self, minValue: float) → None
Parameters:minValue (float) –
setROI(self, index: int, aVolROI: ORSModel.ors.ROI) → None

Fills a particularROI slot to be used as a source for the Dijkstra algorithm.

Note

A maximum of 10 ROIs can be provided. The ROIs provided must be of the same shape as the input channel.

Parameters:
  • index (int) – the slot index (an unsigned char)
  • aVolROI (ORSModel.ors.ROI) – the ROI associated with this slot index (an ROI)
setStopPosition(self, xP: int, yP: int, zP: int) → None
Parameters:
  • xP (int) –
  • yP (int) –
  • zP (int) –
setStopValue(self, stopValue: float) → None
Parameters:stopValue (float) –
setStopWhenValueIsEncountered(self, aF: bool) → None
Parameters:aF (bool) –
setUseValueWindow(self, aF: bool) → None
Parameters:aF (bool) –
setUsedForcedMean(self, aF: bool) → None
Parameters:aF (bool) –
useDijkstraMetric(self, aF: bool) → None
Parameters:aF (bool) –

Unmanaged

class ORSModel.ors.Unmanaged

Bases: ORSModel.ors.ORSBaseClass

brief_description: Abstract class for objects that are not managed by the core library. author: Eric Fournier. All other members of ORS participated. version: 1.0 date: Jan 2005

atomicLoad(sFilename: str) → Unmanaged

Creates an object from a file where an object was saved.

Parameters:sFilename (str) – path of the file to load
Returns:output (Unmanaged) – a managed object, or none() if the load fails
atomicSave(self, aFilename: str) → int

Saves the object to a file.

Parameters:aFilename (str) – path of the file to save
Returns:output (int) – 0 if successful, otherwise an error code
createFromPythonRepresentation(aPythonRepresentation: str) → Unmanaged

Create aUnmanaged Object from a python representation a static method.

Parameters:aPythonRepresentation (str) –
Returns:output (ORSModel.ors.Unmanaged) –
fromPythonRepresentation(self, aPythonRepresentation: str) → bool

Create aUnmanaged object from a Python string representation.

Parameters:aPythonRepresentation (str) – a Python evaluable string representation (a string)
Returns:output (bool) – TRUE if parsing worked, FALSE otherwise (a bool)
classmethod getAllSubclasses(outputCollection=None)
classmethod getClassDenomination()
static getClassFromProgId(progId)
getClassName(self) → str

Retrieves the class name of the core object wrapped by this Interface object.

Returns:output (str) –
getClassNameStatic() → str

getClassNameStatic

Returns:output (str) –
getDataChecksum(self) → str
Returns:output (str) –
getIsInstanceOf(self, pProgId: str) → bool

Queries the object to know if it is an instance of a certain class.

Parameters:pProgId (str) –
Returns:output (bool) –
classmethod getIsSubclassOf(parentClass)
getPythonRepresentation(self) → str

Gets a Python evaluable string representation.

Returns:output (str) –
isNone(self) → bool

Checks if the receiver is none.

Returns:output (bool) –
isNotNone(self) → bool

Checks if the receiver is not none.

Returns:output (bool) –
none() → Unmanaged
Returns:output (Unmanaged) –

ORSBaseClass

class ORSModel.ors.ORSBaseClass

brief_description: An abstract class from which all objects issued from the author: Eric Fournier. All other members of ORS participated. version: 1.0 date: Jan 2005

getPythonTraceBack() → typing.List[str]

Set the python traceback for a call from python.

Returns:output (typing.List[str]) –
isManaged(self) → bool
Returns:output (bool) –
isNone(self) → bool
Returns:output (bool) –
setPythonTraceBack(tb: ORSModel.ors.typing.List[str]) → None

Set the python traceback for a call from python.

Parameters:tb (typing.List[str]) –