Heatmaps look for existing colors in adata.uns

[codyheiser]

The issue: I found that because cnv.pl.chromosome_heatmap and cv.pl.chromosome_heatmap_summary create a copy of the adata input in CNV-space, colors mapped to categorical adata.obs fields were not transferred to this tmp_adata and thus didn't make the plots.

The fix: I simply added a quick check for "{}_colors".format(groupby) in adata.uns, and add a tmp_adata.uns["{}_colors".format(groupby)] key with the corresponding colors from the original adata if so.

Minimal reproducible example: Adapted from tutorial_3k

Here's a PDF of a notebook containing the below code for convenience:
infercnvpy_heatmap_color_fix.pdf

import scanpy as sc
import infercnvpy as cnv
import matplotlib.pyplot as plt

sc.settings.set_figure_params(figsize=(5, 5))

adata = cnv.datasets.maynard2020_3k()

cnv.tl.infercnv(
    adata,
    reference_key="cell_type",
    reference_cat=[
        "B cell",
        "Macrophage",
        "Mast cell",
        "Monocyte",
        "NK cell",
        "Plasma cell",
        "T cell CD4",
        "T cell CD8",
        "T cell regulatory",
        "mDC",
        "pDC",
    ],
    window_size=250,
)

cnv.pl.chromosome_heatmap(adata, groupby="cell_type")

# these should match colors in above heatmap
adata.uns["cell_type_colors"]

# define custom color dictionary for a couple cell types
colordict = {
    "Epithelial cell":"#e377c2",  # pink
    "Endothelial cell":"#d62728",  # red
}
# let's change colors for cell_type in adata
for x in list(colordict.keys()):
    adata.uns["cell_type_colors"][list(adata.obs.cell_type.cat.categories).index(x)] = colordict[x]

# indexes 4 and 5 should be updated now
adata.uns["cell_type_colors"]

# now, Epithelial cell should be pink and Endothelial cell should be red
cnv.pl.chromosome_heatmap(adata, groupby="cell_type")

[grst]

Hi,
thanks a lot for putting this PR together! The changes look good to me!

Unfortunately the CI is currently broken (will be fixed by #42) and I would like to wait until this is merged before I am going to merge this PR and make a release. This will likely take a few more weeks.

Cheers,
Gregor

[codecov-commenter]

Codecov Report

Merging #46 (de7b62d) into main (2452241) will increase coverage by 0.33%.
The diff coverage is 100.00%.

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #46      +/-   ##
==========================================
+ Coverage   65.67%   66.01%   +0.33%     
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  Files          13       13              
  Lines         405      409       +4     
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+ Hits          266      270       +4     
  Misses        139      139              

Flag	Coverage Δ
unittests	66.01% <100.00%> (+0.33%)	⬆️

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Impacted Files	Coverage Δ
src/infercnvpy/pl/_chromosome_heatmap.py	96.00% <100.00%> (+0.34%)	⬆️