spacr.measure

Module Contents

spacr.measure.get_components(cell_mask, nucleus_mask, pathogen_mask)[source]

Get the components (nucleus and pathogens) for each cell in the given masks.

Parameters:
  • cell_mask (ndarray) – Binary mask of cell labels.

  • nucleus_mask (ndarray) – Binary mask of nucleus labels.

  • pathogen_mask (ndarray) – Binary mask of pathogen labels.

Returns:

A tuple containing two dataframes - nucleus_df and pathogen_df.
nucleus_df (DataFrame): Dataframe with columns ‘cell_id’ and ‘nucleus’,

representing the mapping of each cell to its nucleus.

pathogen_df (DataFrame): Dataframe with columns ‘cell_id’ and ‘pathogen’,

representing the mapping of each cell to its pathogens.

Return type:

tuple

spacr.measure.save_and_add_image_to_grid(png_channels, img_path, grid, plot=False)[source]

Add an image to a grid and save it as PNG.

Parameters:
  • png_channels (ndarray) – The array representing the image channels.

  • img_path (str) – The path to save the image as PNG.

  • grid (list) – The grid of images to be plotted later.

Returns:

Updated grid with the new image added.

Return type:

grid (list)

spacr.measure.img_list_to_grid(grid, titles=None)[source]

Plot a grid of images with optional titles.

Parameters:
  • grid (list) – List of images to be plotted.

  • titles (list) – List of titles for the images.

Returns:

The matplotlib figure object containing the image grid.

Return type:

fig (Figure)

spacr.measure.measure_crop(settings)[source]

Measure the crop of an image based on the provided settings.

Parameters:

settings (dict) – The settings for measuring the crop.

Returns:

None

spacr.measure.process_meassure_crop_results(partial_results, settings)[source]

Process the results, display, and optionally save the figures.

Parameters:
  • partial_results (list) – List of partial results.

  • settings (dict) – Settings dictionary.

  • save_figures (bool) – Flag to save figures or not.

spacr.measure.generate_cellpose_train_set(folders, dst, min_objects=5)[source]
spacr.measure.get_object_counts(src)[source]