Deterministic plotting gallery

This gallery is a repository-owned visual catalog for the plotting functions exported by adata_science_tools._plotting. The coverage contract and asset filenames come from example_plotting_gallery/manifest.py: 39 renderers and 46 cases, split across maintained, compatibility, and deprecated APIs.

The examples are for rendering and API coverage. They are not benchmark datasets or evidence for biological conclusions.

Data and analysis provenance

The inputs in example_plotting_gallery/simulated_data.py are deterministic. Seeded builders create balanced independent groups, paired subjects, repeated measurements, continuous observations, and composition categories. Other builders return fixed survival curves and meta-analysis rows. These precomputed tables, and the deterministic continuous-effect curve and interval, are plotting inputs rather than estimates produced by the library.

Some examples deliberately consume analysis results produced by public library functions:

Library-derived result	Gallery consumers
`diff_test` effects and p-values, via `run_independent_diff_test`	`barh_l2fc_dotplot_column`, `barh_dotplot_dotplot_column`, `barh_dotplot_dotplot_dotplot_column`, `barh_4X_dotplot_column`, `l2fc_dotplot_column`, `l2fc_dotplot_single`, `qqplot`, and `volcano_plot_generic`; the deprecated `l2fc_pvalue_dotplot_gex`, `l2fc_pvalue_dotplot_protein_metabolite`, `plot_column_of_bar_h_2groups_with_l2fc_dotplot_GEX_adata`, `qqplot_pvalues`, and `volcano_plot_sns_single_comparison_generic` cases reuse the same results through their legacy contracts.
`fit_smf_ols_models_and_summarize_adata` coefficients, confidence intervals, p-values, and sample counts	Both `forest` cases, plus the adjusted OLS panels in `barh_dotplot_dotplot_dotplot_column` and `barh_4X_dotplot_column`.
`calculate_expectations`, `predict_expectation`, and `excess_expectation` fitted values and residuals	`residual_diagnostic`.
`pairwise_spearman_corr_matrix` rank-correlation matrix	Both `plot_heatmap` cases. The three `plot_rank_*` renderers instead calculate their displayed rank summaries from the deterministic ranked lists passed to them.

run_independent_diff_test never assigns a sorted or filtered result table directly to AnnData.var. It starts from a copy of the original AnnData and left-joins only result columns on the original variable index. This preserves the matrix-variable alignment and original variable order; a feature omitted by diff_test, such as the all-zero fixture, remains in var with missing analysis values.

Coverage boundaries

The manifest labels 30 renderers as maintained, 1 as a compatibility API, and 8 as deprecated. Compatibility and deprecated entries remain in the catalog so their current call paths and recommended replacements are visible; their screenshots do not change their support status.

Excluded Venn module

The gallery also excludes _plotting._venn_plots. That module is not re-exported by _plotting/__init__.py, and importing it requires the optional matplotlib-venn package, which is not installed in the gallery environment. The four non-exported functions are venn_plot_2list, venn_plot_3list, geneset_enrichment_venn, and geneset_enrichemnt_ol_ven_M_n_N_x. See _venn_plots.md for their source-level documentation.

Regenerate the assets

The plotting_gallery_params block in config/config.yaml controls the asset directory, log directory, selected renderer names, selected case IDs, and whether generation continues after an error. Null renderer and case selections generate all manifest cases. From the repository root, run:

bash scripts/000_generate_plotting_gallery.bash

The runner sources config/local_env.sh, activates POSTPROCESS_ENV, configures headless Matplotlib, writes a runner log under scripts/logs, and leaves analysis and output selection to the Python entry point and YAML config.

Catalog

The entries, order, case IDs, titles, statuses, replacements, and filenames below are derived from RENDERER_MANIFEST; the manifest remains authoritative if coverage changes.

Maintained renderers (30)

Renderer	Gallery cases
`adata_histograms` `_plotting._histograms`	`subgroup_kde` — Distributions by treatment `feature_group_collapse` — Grouped feature distributions
`barh_4X_dotplot_column` `_plotting._column_plots`	`five_panel` — Expression with four inferential summaries
`barh_column` `_plotting._column_plots`	`grouped_expression` — Feature abundance by treatment
`barh_dotplot_dotplot_column` `_plotting._column_plots`	`three_panel` — Expression with two differential summaries
`barh_dotplot_dotplot_dotplot_column` `_plotting._column_plots`	`four_panel` — Expression with three differential summaries
`barh_l2fc_dotplot_column` `_plotting._column_plots`	`two_panel` — Expression and differential effect
`category_composition` `_plotting._tabular_plots`	`percent_annotated` — Response composition by cohort
`continuous_effect_plot` `_plotting._analytical_plots`	`observed_categories` — Continuous exposure effect
`corr_dotplot` `_plotting._corr_dotplots`	`subgroup_marginals` — Correlation with subgroup fits and marginals `log1p_identity` — Correlation on synchronized log1p axes
`datapoints` `_plotting._datapoints`	`grouped_markers` — Feature values with independent marker and color encodings `feature_group_collapse` — Collapsed feature-group datapoints
`forest` `_plotting._forest`	`grouped_estimates` — Grouped model estimates `ratio_scale` — Ratio-scale effects
`kaplan_meier_plot` `_plotting._analytical_plots`	`grouped_risk_censor` — Survival curves with numbers at risk
`l2fc_dotplot_column` `_plotting._column_plots`	`multi_feature` — Differential effects by feature
`l2fc_dotplot_single` `_plotting._column_plots`	`single_axis` — Differential effect overview
`longitudinal_trajectories` `_plotting._longitudinal`	`markers_and_gaps` — Longitudinal trajectories with visit gaps
`meta_forest` `_plotting._meta_forest`	`study_summary_prediction` — Meta-analysis summary
`paired_datapoints` `_plotting._datapoints`	`paired_groups` — Paired changes by treatment `precomputed_pair_values` — Paired values from preserved source matrices
`plot_columns` `_plotting._row_plots`	`multi_metric` — Grouped covariate summaries
`plot_heatmap` `_plotting._corr_dotplots`	`clustered` — Clustered rank-correlation heatmap `fixed_order` — Fixed-order rank-correlation heatmap
`plot_rank_heatmap` `_plotting._corr_dotplots`	`rank_hexbin` — Rank agreement density
`plot_rank_scatter` `_plotting._corr_dotplots`	`rank_agreement` — Rank agreement
`plot_rank_scatter_density` `_plotting._corr_dotplots`	`rank_density` — Rank agreement with local density
`qqplot` `_plotting._plots`	`differential_pvalues` — Differential-test p-value QQ plot
`ranked_waterfall` `_plotting._tabular_plots`	`direction_colored` — Ranked feature effects
`residual_diagnostic` `_plotting._tabular_plots`	`log_fitted` — Residuals versus fitted abundance
`show_colors` `_plotting._utils`	`categorical_palette` — Categorical plotting palette
`show_tol_colors` `_plotting._utils`	`tol_palette` — Paul Tol plotting palette
`spearman_cor_dotplot_2` `_plotting._corr_dotplots`	`dual_hue` — Correlation under two categorical encodings
`timeseries_paired_datapoints` `_plotting._plots`	`faceted_time_series` — Paired time-series datapoints
`volcano_plot_generic` `_plotting._plots`	`significance` — Differential-test volcano plot `feature_class` — Volcano plot with feature-class highlighting

Compatibility renderers (1)

Renderer	Gallery cases
`spearman_cor_dotplot` `_plotting._corr_dotplots` Replacement: `corr_dotplot`	`spearman_fit` — Spearman correlation compatibility API

Deprecated renderers (8)

Renderer	Gallery cases
`corr_dotplot_dev` `_plotting._corr_dotplots` Replacement: `corr_dotplot`	`replacement_smoke` — Deprecated correlation wrapper
`l2fc_pvalue_dotplot_gex` `_plotting._plots_depreciated` Replacement: `l2fc_dotplot_single`	`replacement_smoke` — Legacy gene-expression effect dotplot
`l2fc_pvalue_dotplot_protein_metabolite` `_plotting._plots_depreciated` Replacement: `l2fc_dotplot_single`	`replacement_smoke` — Legacy protein/metabolite effect dotplot
`plot_column_of_bar_h_2groups_GEX_adata` `_plotting._plots_depreciated` Replacement: `barh_column`	`replacement_smoke` — Legacy grouped expression bars
`plot_column_of_bar_h_2groups_with_l2fc_dotplot_GEX_adata` `_plotting._plots_depreciated` Replacement: `barh_l2fc_dotplot_column`	`replacement_smoke` — Legacy expression and effect composite
`plot_paired_point_anndata` `_plotting._plots_depreciated` Replacement: `timeseries_paired_datapoints`	`replacement_smoke` — Legacy paired time-series datapoints
`qqplot_pvalues` `_plotting._plots_depreciated` Replacement: `qqplot`	`replacement_smoke` — Legacy p-value QQ plot
`volcano_plot_sns_single_comparison_generic` `_plotting._plots_depreciated` Replacement: `volcano_plot_generic`	`replacement_smoke` — Legacy adjusted-p volcano plot