Fix plot_multicomparison_fc with default figsize#966
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Fixes scverse#755 The function failed when seaborn's heatmap didn't display tick labels (which happens with certain figsize values). This occurred because the code assumed tick labels would always be present when plotting significance markers. The fix ensures xticklabels=True and yticklabels=True are set by default, while still allowing users to override via heatmap_kwargs. Changes: - Set default xticklabels=True and yticklabels=True in heatmap call - Add regression test for default figsize behavior
…red labels Previous approach extracted tick labels from the rendered plot, which failed when seaborn hid labels (small figsize, many genes, or explicit xticklabels=False). New approach calculates positions directly from DataFrame structure: - Seaborn places cell centers at 0.5, 1.5, 2.5, etc. - Works regardless of label visibility - Faster (no DOM extraction) - Immune to matplotlib rendering changes Test updated to actually reproduce the bug (50 genes + small figsize).
Gemini review noted that position calculation assumes non-clustered heatmap. If future maintainer changes to clustermap, marker positions would be wrong. Added comment to make this assumption explicit.
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Could you please fix the merge conflicts? Thank you |
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Closed during rebase (branch delete + recreate). Replaced by #970. |
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Fixes #755.
Seaborn heatmap suppresses tick labels when the figure is too narrow, causing plot_multicomparison_fc to crash with ValueError when trying to position significance markers (the code looks up gene names in x_labels, but those labels are missing).
This sets xticklabels=True and yticklabels=True as defaults so tick labels are always visible. Users can still override via heatmap_kwargs if needed.
Also adds a comment noting that the marker positioning assumes a non-clustered heatmap (if a future maintainer switches to clustermap, marker positions would be wrong).