scallops.visualize.composite.imcomposite

scallops.visualize.composite.imcomposite(image=None, labels=None, vmin=None, vmax=None, cmap=None, labels_cmap=None, labels_alpha=0.5, labels_contour=False, labels_contour_cmap=None, labels_contour_thickness=1, labels_contour_alpha=1, dim='c', facet=None, col_wrap=3, figsize=None, ax=None, rgb=False, mask=None)

Plot an image composite using additive blending.

Parameters:

• image (DataArray | ndarray | Array | None) – XArray with dimensions y, x and optionally dim.

• labels (DataArray | ndarray | Array | None) – Labels (e.g., segmentation labels).

• vmin (float | DataArray | ndarray | Array | None) – Lower color limit used for determining the colormap bounds. Default is the minimum of the image. If a list, must be the same length as the dimension being expanded.

• vmax (float | DataArray | ndarray | Array | None) – Upper color limit used for determining the colormap bounds. Default is the maximum of the image. If a list, must be the same length as the dimension being expanded.

• figsize (tuple[int, int]) – Figure size.

• cmap (Sequence[str | Colormap] | str | Colormap | None) – List that maps dimension index to colormap instance or registered colormap name used to map scalar data to colors.

• labels_cmap (str | ListedColormap | None) – ListedColormap instance or registered colormap name used to map label data to colors.

• labels_alpha (float) – Alpha value for labels.

• labels_contour (bool | ndarray | DataArray | Array) – If true, show label contours only. If an array, then segmentation labels to show as contour.

• labels_contour_cmap (str | ListedColormap | None) – ListedColormap instance or registered colormap name used to map label contour data to colors.

• labels_contour_thickness (int) – Labels contour thickness.

• labels_contour_alpha (float) – Alpha value for label contours.

• labels_cmap – ListedColormap instance or registered colormap name used to map label data to colors.

• dim (str | None) – Image dimension to blend.

• facet (str | None) – Image dimension to plot on different facet.

• col_wrap (int | None) – Wrap the facet variable at this width, so that the facet values span multiple rows.

• ax (Axes | Sequence[Axes] | None) – Matplotlib axes to plot to. If facet is provided, a one dimensional array of axes corresponding to

• rgb (bool)

• mask (ndarray | DataArray | Array)

Return type:

Axes | Sequence[Axes]

length of facet values :param rgb: Whether the image is RGB or RGBA. :param mask: Mask pixels where mask == 0

Example:

from matplotlib import pyplot as plt
import numpy as np
import xarray as xr
from scallops.visualize import imcomposite

# Generate synthetic data for testing
t, c, z, y, x = (
    1,
    3,
    1,
    10,
    10,
)  # emulate all possible dimensions (only 3D is accepted by single)
image_data = np.random.rand(t, c, z, y, x)
labels_data = np.random.randint(0, 2, size=(y, x))

image = xr.DataArray(image_data, dims=("t", "c", "z", "y", "x"))
labels = xr.DataArray(labels_data, dims=("y", "x"))

# Plot the composite image
ax = imcomposite(image.isel(t=0, z=0), labels, figsize=(8, 8), dim="c")
plt.show()

Parameters:

• image (DataArray | ndarray | Array | None)

• labels (DataArray | ndarray | Array | None)

• vmin (float | DataArray | ndarray | Array | None)

• vmax (float | DataArray | ndarray | Array | None)

• cmap (Sequence[str | Colormap] | str | Colormap | None)

• labels_cmap (str | ListedColormap | None)

• labels_alpha (float)

• labels_contour (bool | ndarray | DataArray | Array)

• labels_contour_cmap (str | ListedColormap | None)

• labels_contour_thickness (int)

• labels_contour_alpha (float)

• dim (str | None)

• facet (str | None)

• col_wrap (int | None)

• figsize (tuple[int, int])

• ax (Axes | Sequence[Axes] | None)

• rgb (bool)

• mask (ndarray | DataArray | Array)

Return type:

Axes | Sequence[Axes]