bin2cell.view_cell_labels

bin2cell.view_cell_labels(image_path, labels_npz_path, cdata, fill_key=None, border_key=None, crop=None, stardist_normalize=False, fill_label_weight=1, thicken_border=True, cat_cmap='tab20', cont_cmap='viridis')

Colour morphology segmentations by cell-level metadata or gene expression. Can do fills or borders. Returns image as np.array, and a dictionary of legends (as matplotlib figures) named after the keys it used.

Input

image_pathfilepath: Path to morphology image that was segmented.
labels_npz_pathfilepath: Path to sparse morphology labels generated by b2c.stardist().
cdataAnnData: Cell-level VisiumHD object with pertinent gene/metadata. Must have .obs_names unchanged from b2c.bin_to_cell() output.
fill_keystr or None, optional (default: None): .obs column (float/integer or categorical) or gene name (expression taken from .X) to colour the fill by. Skipped if None.
border_keystr or None, optional (default: None): .obs column (float/integer or categorical) or gene name (expression taken from .X) to colour the border by. Skipped if None.
cropNone or tuple of int, optional (default: None): A PIL-formatted crop specification - a four integer tuple, provided as (left, upper, right, lower) coordinates. If None, will render full segmentation results.
stardist_normalizebool, optional (default: False): If True, percentile normalise the input image prior to rendering the segmentation labels on it.
fill_label_weightfloat, optional (default: 1): Weight to assign the object fill render when constructing output. 0 is completely transparent, 1 is completely opaque.
thicken_borderbool, optional (default: True): The default identified border is thinner than that of b2c.view_labels(). Setting this to True, thickens it for ease of viewing.
cat_cmapstr, optional (default: "tab20"): Colormap name (must be understood by seaborn.color_palette()) to use for categoricals.
cont_cmapstr, optional (default: "viridis"): Colormap name (must be understood by matplotlib.colormaps.get_cmap()) to use for integers/floats.