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After removing rows with only NaN interactions, none remain. #840
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Description
Description
...
Minimal reproducible example
import numpy as np
import os
import scanpy as sc
import squidpy as sq
sc.logging.print_header()
print(f"squidpy=={sq.__version__}")
adata = sc.read_h5ad('seqfish.h5ad')
sq.pl.spatial_scatter(
adata, color="celltype_mapped_refined", shape=None, figsize=(10, 10)
)
sq.gr.spatial_neighbors(adata, coord_type="generic")
sq.gr.nhood_enrichment(adata, cluster_key="celltype_mapped_refined")
sq.pl.nhood_enrichment(adata, cluster_key="celltype_mapped_refined", method="ward")
sq.gr.co_occurrence(adata, cluster_key="celltype_mapped_refined")
sq.pl.co_occurrence(
adata,
cluster_key="celltype_mapped_refined",
clusters="Lateral plate mesoderm",
figsize=(10, 5),
)
sq.gr.ligrec(
adata,
n_perms=100,
cluster_key="celltype_mapped_refined",
)
sq.pl.ligrec(
adata,
cluster_key="celltype_mapped_refined",
source_groups="Lateral plate mesoderm",
target_groups=["Intermediate mesoderm", "Allantois"],
means_range=(0.3, np.inf),
alpha=1e-4,
swap_axes=True,
)Traceback
Details
...Version
scanpy==1.9.5 anndata==0.9.2 umap==0.5.6 numpy==1.24.3 scipy==1.11.3 pandas==2.2.2 scikit-learn==1.3.0 statsmodels==0.14.1 igraph==0.11.5 pynndescent==0.5.12
squidpy==1.5.0
...
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