PartSegCore.analysis.measurement_calculation

class PartSegCore.analysis.measurement_calculation.ColocalizationMeasurement

Bases: MeasurementMethodBase

This algorithm has following parameters:

• channel_fst (Channel)- Channel 1

• channel_scd (Channel)- Channel 2

• colocalization (CorrelationEnum)- Colocalization

• randomize (bool)- Randomize channel, If randomize orders of pixels in one channel

• randomize_repeat (int)- Randomize num, Number of repetitions for mean_calculate

classmethod calculate_property(area_array, colocalization, randomize=False, randomize_repeat=10, channel_fst=0, channel_scd=1, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

Return type:

symbols

class PartSegCore.analysis.measurement_calculation.ColocalizationMeasurementParameters(**data)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class PartSegCore.analysis.measurement_calculation.Compactness

Bases: MeasurementMethodBase

static calculate_property(**kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.ComponentBoundingBox

Bases: MeasurementMethodBase

static calculate_property(bounds_info, _component_num, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_starting_leaf()

This leaf is put on a default list

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.ComponentsInfo(roi_components: ndarray, mask_components: ndarray, components_translation: dict[int, list[int]])

Bases: NamedTuple

Class for storage information about relation between roi components and mask components

Variables:

• roi_components (numpy.ndarray) – list of roi components

• mask_components (numpy.ndarray) – list of mask components

• components_translation (Dict[int, List[int]]) – mapping from roi components to mask components base on intersections

components_translation: dict[int, list[int]]

Alias for field number 2

mask_components: ndarray

Alias for field number 1

roi_components: ndarray

Alias for field number 0

class PartSegCore.analysis.measurement_calculation.ComponentsNumber

Bases: MeasurementMethodBase

static calculate_property(area_array, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.CorrelationEnum(*values)

Bases: str, Enum

class PartSegCore.analysis.measurement_calculation.Diameter

Bases: MeasurementMethodBase

Class for calculate diameter of ROI in fast way. From Malandain, G., & Boissonnat, J. (2002). Computing the diameter of a point set, 12(6), 489-509. https://doi.org/10.1142/S0218195902001006

static calculate_property(area_array, voxel_size, result_scalar, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.DiameterOld

Bases: MeasurementMethodBase

n**2 calculate diameter of ROI

static calculate_property(area_array, voxel_size, result_scalar, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.DistanceMaskROI

Bases: MeasurementMethodBase

This algorithm has following parameters:

• distance_from_mask (DistancePoint)- Distance from mask

• distance_to_roi (DistancePoint)- Distance to ROI

static area_type(area)

Map chosen area type to proper area type. Allow to correct Area type.

classmethod calculate_property(channel, area_array, mask, voxel_size, result_scalar, distance_from_mask, distance_to_roi, *args, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_starting_leaf()

This leaf is put on a default list

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.DistanceMaskROIParameters(**data)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class PartSegCore.analysis.measurement_calculation.DistancePoint(*values)

Bases: Enum

class PartSegCore.analysis.measurement_calculation.DistanceROIROI

Bases: DistanceMaskROI

This algorithm has following parameters:

• profile (ROIExtractionProfile)- ROI extraction profile

• distance_from_new_roi (DistancePoint)- Distance new ROI

• distance_to_roi (DistancePoint)- Distance to ROI

classmethod calculate_property(channel, image, area_array, profile, mask, voxel_size, result_scalar, distance_from_new_roi, distance_to_roi, **kwargs)

Main function for calculating measurement

Parameters:

• channel (ndarray) – main channel selected for measurement

• roi – array representing roi

• mask (Optional[ndarray]) – array representing mask (upper level roi)

• voxel_size (Sequence[float]) – size of single voxel in meters

• result_scalar (float) – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_starting_leaf()

This leaf is put on a default list

class PartSegCore.analysis.measurement_calculation.DistanceROIROIParameters(**data)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class PartSegCore.analysis.measurement_calculation.FirstPrincipalAxisLength

Bases: MeasurementMethodBase

static calculate_property(**kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.GetROIAnnotationType

Bases: MeasurementMethodBase

This algorithm has following parameters:

• name (str)- Name

static calculate_property(roi_annotation, name, _component_num, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_starting_leaf()

This leaf is put on a default list

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.GetROIAnnotationTypeParameters(**data)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class PartSegCore.analysis.measurement_calculation.Haralick

Bases: MeasurementMethodBase

This algorithm has following parameters:

• feature (HaralickEnum)- Feature

• distance (int)- Distance

classmethod calculate_property(area_array, channel, distance, feature, _cache=False, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

Return type:

symbols

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.HaralickEnum(*values)

Bases: Enum

class PartSegCore.analysis.measurement_calculation.HaralickParameters(**data)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

PartSegCore.analysis.measurement_calculation.MEASUREMENT_DICT = {'Colocalization': <class 'PartSegCore.analysis.measurement_calculation.ColocalizationMeasurement'>, 'Compactness': <class 'PartSegCore.analysis.measurement_calculation.Compactness'>, 'Component Bounding Box': <class 'PartSegCore.analysis.measurement_calculation.ComponentBoundingBox'>, 'Components number': <class 'PartSegCore.analysis.measurement_calculation.ComponentsNumber'>, 'Diameter': <class 'PartSegCore.analysis.measurement_calculation.Diameter'>, 'First principal axis length': <class 'PartSegCore.analysis.measurement_calculation.FirstPrincipalAxisLength'>, 'Haralick': <class 'PartSegCore.analysis.measurement_calculation.Haralick'>, 'Maximum pixel brightness': <class 'PartSegCore.analysis.measurement_calculation.MaximumPixelBrightness'>, 'Mean pixel brightness': <class 'PartSegCore.analysis.measurement_calculation.MeanPixelBrightness'>, 'Median pixel brightness': <class 'PartSegCore.analysis.measurement_calculation.MedianPixelBrightness'>, 'Minimum pixel brightness': <class 'PartSegCore.analysis.measurement_calculation.MinimumPixelBrightness'>, 'Moment': <class 'PartSegCore.analysis.measurement_calculation.Moment'>, 'Neighbourhood new ROI presence': <class 'PartSegCore.analysis.measurement_calculation.ROINeighbourhoodROI'>, 'Pixel brightness sum': <class 'PartSegCore.analysis.measurement_calculation.PixelBrightnessSum'>, 'ROI distance': <class 'PartSegCore.analysis.measurement_calculation.DistanceMaskROI'>, 'Second principal axis length': <class 'PartSegCore.analysis.measurement_calculation.SecondPrincipalAxisLength'>, 'Sphericity': <class 'PartSegCore.analysis.measurement_calculation.Sphericity'>, 'Standard deviation of pixel brightness': <class 'PartSegCore.analysis.measurement_calculation.StandardDeviationOfPixelBrightness'>, 'Surface': <class 'PartSegCore.analysis.measurement_calculation.Surface'>, 'Third principal axis length': <class 'PartSegCore.analysis.measurement_calculation.ThirdPrincipalAxisLength'>, 'Volume': <class 'PartSegCore.analysis.measurement_calculation.Volume'>, 'Voxel size': <class 'PartSegCore.analysis.measurement_calculation.VoxelSize'>, 'Voxels': <class 'PartSegCore.analysis.measurement_calculation.Voxels'>, 'annotation by name': <class 'PartSegCore.analysis.measurement_calculation.GetROIAnnotationType'>, 'distance splitting pixel brightness sum': <class 'PartSegCore.analysis.measurement_calculation.SplitOnPartPixelBrightnessSum'>, 'distance splitting volume': <class 'PartSegCore.analysis.measurement_calculation.SplitOnPartVolume'>, 'rim pixel brightness sum': <class 'PartSegCore.analysis.measurement_calculation.RimPixelBrightnessSum'>, 'rim volume': <class 'PartSegCore.analysis.measurement_calculation.RimVolume'>, 'to new ROI distance': <class 'PartSegCore.analysis.measurement_calculation.DistanceROIROI'>}

Register with all measurements algorithms

class PartSegCore.analysis.measurement_calculation.MaximumPixelBrightness

Bases: MeasurementMethodBase

static calculate_property(area_array, channel, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.MeanPixelBrightness

Bases: MeasurementMethodBase

static calculate_property(area_array, channel, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.MeasurementProfile(**data)

Bases: BaseModel

calculate(image, channel_num, roi, result_units, range_changed=<function empty_fun>, step_changed=<function empty_fun>, time=0)

Calculate measurements on given set of parameters

Parameters:

• image (Image) – image on which measurements should be calculated

• channel_num (int) – channel number on which measurements should be calculated

• roi (Union[ndarray, ROIInfo]) – array with segmentation labeled as positive integers

• result_units (Units) – units which should be used to present results.

• range_changed (Callable[[int, int], Any]) – callback function to set information about steps range

• step_changed (Callable[[int], Any]) – callback function for set information about steps done

• time (int) – which data point should be measured

Return type:

MeasurementResult

Returns:

measurements

calculate_tree(node, segmentation_mask_map, help_dict, kwargs)

Main function for calculation tree of measurements. It is executed recursively

Parameters:

• node (Union[Node, Leaf]) – measurement to calculate

• segmentation_mask_map (ComponentsInfo) – map from mask segmentation components to mask components. Needed for division

• help_dict (dict) – dict to cache calculation result. It reduce recalculations of same measurements.

• kwargs (dict) – additional info needed by measurements

Return type:

tuple[Union[float, ndarray], symbols, AreaType]

Returns:

measurement value

calculate_yield(image, channel_num, roi, result_units, segmentation_mask_map, time=0)

Calculate measurements on given set of parameters

Parameters:

• image (Image) – image on which measurements should be calculated

• roi (Union[ndarray, ROIInfo]) – array with segmentation labeled as positive integers

• result_units (Units) – units which should be used to present results.

• segmentation_mask_map (ComponentsInfo) – information which component of roi belongs to which mask component.

• time (int) – which data point should be measured

Return type:

Generator[tuple[Union[float, list[float], str], str, tuple[PerComponent, AreaType]], None, None]

Returns:

measurements

get_component_and_area_info()

For each measurement check if is per component and in which types

Return type:

list[tuple[PerComponent, AreaType]]

get_component_info(unit)

Returns:

list[((str, str), bool)]

static get_segmentation_to_mask_component(segmentation, mask)

Calculate map from segmentation component num to mask component num

Parameters:

• segmentation (ndarray) – numpy array with segmentation labeled as positive integers

• mask (Optional[ndarray]) – numpy array with mask labeled as positive integer

Return type:

ComponentsInfo

Returns:

map

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class PartSegCore.analysis.measurement_calculation.MeasurementResult(components_info)

Bases: MutableMapping[str, tuple[float | list[float] | str, str]]

Class for storage measurements info.

get_component_info(all_components=False)

Get information which type of components are in storage.

Return type:

tuple[bool, bool]

Returns:

has_mask_components, has_segmentation_components

get_global_names()

Get names for only parameters which are not ‘PerComponent.Yes’

get_global_parameters()

Get only parameters which are not ‘PerComponent.Yes’

get_labels(expand=True, all_components=False)

If expand is false return list of keys of this storage. Otherwise return labels for measurement. Base are keys of this storage. If has mask components, or has segmentation_components then add this labels

Return type:

list[str]

get_separated(all_components=False)

Get measurements separated for each component

Return type:

list[list[Union[float, list[float], str]]]

set_filename(path_fo_file)

Set name of file to be presented as first position.

class PartSegCore.analysis.measurement_calculation.MedianPixelBrightness

Bases: MeasurementMethodBase

static calculate_property(area_array, channel, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.MinimumPixelBrightness

Bases: MeasurementMethodBase

static calculate_property(area_array, channel, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.Moment

Bases: MeasurementMethodBase

static calculate_property(area_array, channel, voxel_size, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.PixelBrightnessSum

Bases: MeasurementMethodBase

static calculate_property(area_array, channel, **_)

Parameters:

• area_array (ndarray) – mask for area

• channel (ndarray) – data. same shape like area_type

Returns:

Pixels brightness sum on given area

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

exception PartSegCore.analysis.measurement_calculation.ProhibitedDivision

Bases: Exception

class PartSegCore.analysis.measurement_calculation.ROINeighbourhoodROI

Bases: DistanceMaskROI

This algorithm has following parameters:

• profile (ROIExtractionProfile)- ROI extraction profile

• distance (float)- Distance

• units (Units)- Units

classmethod calculate_property(image, area_array, profile, mask, voxel_size, distance, units, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask (Optional[ndarray]) – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_starting_leaf()

This leaf is put on a default list

class PartSegCore.analysis.measurement_calculation.ROINeighbourhoodROIParameters(**data)

Bases: BaseModel

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class PartSegCore.analysis.measurement_calculation.RimPixelBrightnessSum

Bases: MeasurementMethodBase

This algorithm has following parameters:

• distance (float)- Distance

• units (Units)- Units

static area_type(area)

Map chosen area type to proper area type. Allow to correct Area type.

static calculate_property(channel, area_array, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_starting_leaf()

This leaf is put on a default list

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.RimVolume

Bases: MeasurementMethodBase

This algorithm has following parameters:

• distance (float)- Distance

• units (Units)- Units

static area_type(area)

Map chosen area type to proper area type. Allow to correct Area type.

static calculate_property(area_array, voxel_size, result_scalar, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_starting_leaf()

This leaf is put on a default list

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.SecondPrincipalAxisLength

Bases: MeasurementMethodBase

static calculate_property(**kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.SettingsValue(function, help_message, arguments, is_component, default_area)

Bases: NamedTuple

arguments: dict | None

Alias for field number 2

default_area: AreaType | None

Alias for field number 4

function: Callable

Alias for field number 0

help_message: str

Alias for field number 1

is_component: bool

Alias for field number 3

class PartSegCore.analysis.measurement_calculation.Sphericity

Bases: MeasurementMethodBase

static calculate_property(**kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.SplitOnPartParameters(**data)

Bases: MaskDistanceSplitParameters

model_config: ClassVar[ConfigDict] = {'extra': 'forbid'}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class PartSegCore.analysis.measurement_calculation.SplitOnPartPixelBrightnessSum

Bases: MeasurementMethodBase

This algorithm has following parameters:

• num_of_parts (int)- Number of Parts

• equal_volume (bool)- Equal Volume, If split should be done in respect of parts volume of parts thickness.

• part_selection (int)- Which part (from border)

static area_type(area)

Map chosen area type to proper area type. Allow to correct Area type.

static calculate_property(part_selection, channel, area_array, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_starting_leaf()

This leaf is put on a default list

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.SplitOnPartVolume

Bases: MeasurementMethodBase

This algorithm has following parameters:

• num_of_parts (int)- Number of Parts

• equal_volume (bool)- Equal Volume, If split should be done in respect of parts volume of parts thickness.

• part_selection (int)- Which part (from border)

static area_type(area)

Map chosen area type to proper area type. Allow to correct Area type.

static calculate_property(part_selection, area_array, voxel_size, result_scalar, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_starting_leaf()

This leaf is put on a default list

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.StandardDeviationOfPixelBrightness

Bases: MeasurementMethodBase

static calculate_property(area_array, channel, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.Surface

Bases: MeasurementMethodBase

static calculate_property(area_array, voxel_size, result_scalar, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.ThirdPrincipalAxisLength

Bases: MeasurementMethodBase

static calculate_property(**kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

classmethod need_channel()

if need image data

class PartSegCore.analysis.measurement_calculation.Volume

Bases: MeasurementMethodBase

classmethod calculate_property(area_array, voxel_size, result_scalar, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

class PartSegCore.analysis.measurement_calculation.VoxelSize

Bases: MeasurementMethodBase

classmethod calculate_property(voxel_size, result_scalar, **kwargs)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

Return type:

symbols

class PartSegCore.analysis.measurement_calculation.Voxels

Bases: MeasurementMethodBase

classmethod calculate_property(area_array, **_)

Main function for calculating measurement

Parameters:

• channel – main channel selected for measurement

• roi – array representing roi

• mask – array representing mask (upper level roi)

• voxel_size – size of single voxel in meters

• result_scalar – scalar to get proper units in result

• roi_alternative – dict with alternative roi representation (for plugin specific mapping)

• roi_annotation – dict with roi annotations (for plugin specific mapping)

List incomplete.

classmethod get_units(ndim)

Return units for measurement. They are shown to user

PartSegCore.analysis.measurement_calculation.double_normal(point_index, point_positions, points_array)

Parameters:

• point_index (int) – index of starting points

• point_positions (ndarray) – points array of size (points_num, number of dimensions)

• points_array (ndarray) – bool matrix with information about which points are in set

Returns:

PartSegCore.analysis.measurement_calculation.empty_fun(_a0=None, _a1=None)

This function is being used as dummy reporting function.

PartSegCore.analysis.measurement_calculation.hash_fun_call_name(fun, arguments, area, per_component, channel, components_num)

Calculate string for properly cache measurements result.

Parameters:

• fun (Union[Callable, MeasurementMethodBase]) – method for which hash string should be calculated

• arguments (dict) – its additional arguments

• area (AreaType) – type of rea

• per_component (PerComponent) – If it is per component

• channel (Channel) – channel number on which calculation is performed

Return type:

str

Returns:

unique string for such set of arguments

PartSegCore.analysis.measurement_calculation.iterative_double_normal(points_positions)

Parameters:

points_positions (ndarray) – points array of size (points_num, number of dimensions)

Returns:

square power of diameter, 2-tuple of points index gave information which points ar chosen