cell_map#

This module contains the class to analyze (detect) individual cells, e.g. to analyze immediate early gene expression data from iDISCO+ cleared tissue [Renier2016].

../_images/CellMap_pipeline.png — iDISCO+ and ClearMap: A Pipeline for Cell Detection, Registration, and Mapping in Intact Samples Using Light Sheet Microscopy.#

class CellDetector(preprocessor=None)[source]#

Bases: TabProcessor

atlas_align()[source]#: Atlas alignment and annotation

convert_cm2_to_cm2_1_fmt()[source]#: Atlas alignment and annotation

create_test_dataset(slicing)[source]#

export_as_csv()[source]#: Export the cell coordinates to csv

Deprecated since version 2.1: Use atlas_align() and export_collapsed_stats instead.

export_collapsed_stats(all_regions=True)[source]#

export_to_clearmap1_fmt()[source]#: ClearMap 1.0 export (will generate the files cells_ClearMap1_intensities, cells_ClearMap1_points_transformed, cells_ClearMap1_points necessaries to use the analysis script of ClearMap1. In ClearMap2 the ‘cells’ file contains already all this information) In order to align the coordinates when we have right and left hemispheres, if the orientation of the brain is left, will calculate the new coordinates for the Y axes, this change will not affect the orientation of the heatmaps, since these are generated from the ClearMap2 file ‘cells’

Deprecated since version 2.1: Use atlas_align() and export_collapsed_stats instead.

filter_cells()[source]#

get_cells_df()[source]#

get_coords(coord_type='filtered', aligned=False)[source]#

get_n_blocks(dim_size)[source]#

get_n_detected_cells()[source]#

get_n_filtered_cells()[source]#

get_voxelization_params(postfix='')[source]#

plot_background_subtracted_img()[source]#

plot_cells()[source]#

plot_cells_3d_scatter_w_atlas_colors(raw=False, parent=None)[source]#

plot_filtered_cells(parent=None, smarties=False)[source]#

plot_voxelized_counts(arrange=True, parent=None)[source]#

plot_voxelized_intensities(arrange=True)[source]#

post_process_cells()[source]#

preview_cell_detection(parent=None, arrange=True, sync=True)[source]#

remove_crust(coordinates, voxelization_parameter)[source]#

run()[source]#

run_cell_detection(tuning=False, save_shape=False)[source]#

setup(preprocessor)[source]#

transform_coordinates(coords)[source]#

voxelize(postfix='')[source]#

voxelize_unweighted(coordinates, voxelization_parameter)[source]#

Voxelize un weighted i.e. for cell counts

Parameters:

coordinates – str, array or Source Source of point of nxd coordinates.
voxelization_parameter – dict

Returns

voxelize_weighted(coordinates, source, voxelization_parameter)[source]#

Voxelize weighted i.e. for cell intensities

Parameters:

coordinates – np.array
source – Source.Source
voxelization_parameter – dict

Returns

property detected#

property df_path#