In [ ]:
import anndata as ad
import ACTIONet as anet
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%load_ext autoreload
%autoreload 2
%aimport ACTIONet
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adata = ad.read_h5ad("../data/pfc5k_ACTIONet_v2_python.h5ad")
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anet.pl.plot_ACTIONet(adata, "Celltype")
Out[ ]:
<AxesSubplot:title={'center':'__annotations__'}, xlabel='actionet2d1', ylabel='actionet2d2'>
In [ ]:
import numpy as np

from random import sample
l = adata.obs["Celltype"].copy()
perm = sample(list(np.arange(adata.shape[0])), 3000)
l[perm] = None
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anet.pl.plot_ACTIONet(adata, l)
Out[ ]:
<AxesSubplot:title={'center':'__annotations__'}, xlabel='actionet2d1', ylabel='actionet2d2'>
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l2 = anet.po.cells.infer_missing_labels(adata, initial_labels=l, return_raw=True)
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anet.pl.plot_ACTIONet(adata, l2)
Out[ ]:
<AxesSubplot:title={'center':'__annotations__'}, xlabel='actionet2d1', ylabel='actionet2d2'>
In [ ]:
l3 = anet.po.cells.correct_labels(adata, initial_labels="Celltype", return_raw=True)
In [ ]:
anet.pl.plot_ACTIONet(adata, l3)
Out[ ]:
<AxesSubplot:title={'center':'__annotations__'}, xlabel='actionet2d1', ylabel='actionet2d2'>