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Merge pull request #255 from Sichao25/restore
Restore contour.py
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"""Written by @Jinerhal, adapted by @Xiaojieqiu. | ||
""" | ||
from typing import Dict, Optional, Tuple, Union | ||
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import cv2 | ||
import numpy as np | ||
from anndata import AnnData | ||
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from ...configuration import SKM | ||
from .utils import save_return_show_fig_utils | ||
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@SKM.check_adata_is_type(SKM.ADATA_UMI_TYPE, "adata") | ||
def spatial_domains( | ||
adata: AnnData, | ||
bin_size: Optional[int] = None, | ||
spatial_key: str = "spatial", | ||
label_key: str = "cluster_img_label", | ||
plot_size=(3, 3), | ||
save_img="spatial_domains.png", | ||
): | ||
"""Generate an image with contours of each spatial domains. | ||
Args: | ||
adata: The adata object used to create the image. | ||
bin_size: The size of the binning. Default to None. | ||
spatial_key: The key name of the spatial coordinates. Default to "spatial". | ||
label_key: The key name of the image label values. Default to "cluster_img_label". | ||
plot_size: figsize for showing the image. | ||
save_img: path to saving image file. | ||
""" | ||
import matplotlib.pyplot as plt | ||
from numpngw import write_png | ||
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label_list = np.unique(adata.obs[label_key]) | ||
labels = np.zeros(len(adata)) | ||
for i in range(len(label_list)): | ||
labels[adata.obs[label_key] == label_list[i]] = i + 1 | ||
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if bin_size is None: | ||
bin_size = adata.uns["bin_size"] | ||
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label_img = np.zeros( | ||
( | ||
int(max(adata.obsm[spatial_key][:, 0] // bin_size)) + 1, | ||
int(max(adata.obsm[spatial_key][:, 1] // bin_size)) + 1, | ||
) | ||
) | ||
for i in range(len(adata)): | ||
label_img[ | ||
int(adata.obsm[spatial_key][i, 0] // bin_size), int(adata.obsm[spatial_key][i, 1] // bin_size) | ||
] = labels[i] | ||
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contour_img = label_img.copy() | ||
contour_img[:, :] = 255 | ||
for i in np.unique(label_img): | ||
if i == 0: | ||
continue | ||
label_img_gray = np.where(label_img == i, 0, 1).astype("uint8") | ||
_, thresh = cv2.threshold(label_img_gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU) | ||
contour, _ = cv2.findContours(thresh, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_NONE) | ||
contour_img = cv2.drawContours(contour_img, contour[:], -1, 0.5, 1) | ||
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fig = plt.figure() | ||
fig.set_size_inches(plot_size[0], plot_size[1]) | ||
plt.imshow(contour_img, cmap="tab20", origin="lower") | ||
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write_png(save_img, contour_img.astype("uint8")) |