Add test suite for plot functions

.gitignore

@@ -1,4 +1,7 @@
 test/test_check_with_R_data.py
+__pycache__/
+**/__pycache__/
+*.pyc
 rawdata/snRNAseq_cellsWithSubtype.h5ad
 docs/source/notebooks/rawdata/snRNAseq_cellsWithSubtype.h5ad
 docs/source/notebooks/output/HMI_example/Human_Myocardial_Infarction_analysed.h5ad

test/test_plots.py

@@ -0,0 +1,218 @@
+import pandas as pd
+import numpy as np
+import scanpy as sc
+from anndata import AnnData
+import matplotlib
+matplotlib.use("Agg")  # headless backend
+import matplotlib.pyplot as plt
+from pycrosstalker import tools as cttl
+from pycrosstalker import plots as ctpl
+
+# Load and analyse data once for all tests
+with open("rawdata/humanBM.h5ad", "rb") as f:
+    paths = {
+        'CTR': "rawdata/CTR_LR.csv",
+        'EXP': "rawdata/EXP_LR.csv"
+    }
+    adata = sc.read_h5ad(f)
+    adata.uns['pycrosstalker'] = {}
+    adata.uns['pycrosstalker']['path'] = {}
+    for k, v in paths.items():
+        adata.uns['pycrosstalker']['path'][k] = pd.read_csv(v)
+    adata = cttl.analise_LR(adata, save=False)
+    data = adata.uns['pycrosstalker']['results']
+
+lrobj_tblPCA = {
+    'pca': data['pca'],
+    'rankings': data['rankings'],
+    'tables': data['tables'],
+}
+
+
+def test_plot_cci():
+    fig, ax = ctpl.plot.plot_cci(
+        graph=data["graphs"]["CTR"],
+        colors=data["colors"],
+        plt_name='Control',
+        coords=data["coords"],
+        emax=None,
+        leg=False,
+        low=0,
+        high=0,
+        ignore_alpha=False,
+        log=False,
+        efactor=6,
+        vfactor=12,
+        pg=data["rankings"]["CTR"]["Pagerank"],
+        scale_factor=2.0,
+        node_size=2.5,
+        return_figure=True
+    )
+    assert fig is not None
+    assert ax is not None
+    assert isinstance(ax, plt.Axes)
+    plt.close("all")
+
+
+def test_plot_cci_exp():
+    fig, ax = ctpl.plot.plot_cci(
+        graph=data["graphs"]["EXP"],
+        colors=data["colors"],
+        plt_name='Experimental',
+        coords=data["coords"],
+        emax=None,
+        leg=False,
+        low=0,
+        high=0,
+        ignore_alpha=False,
+        log=True,
+        efactor=6,
+        vfactor=12,
+        pg=data["rankings"]["EXP"]["Pagerank"],
+        scale_factor=2.0,
+        node_size=2.5,
+        return_figure=True
+    )
+    assert fig is not None
+    assert ax is not None
+    assert isinstance(ax, plt.Axes)
+    plt.close("all")
+
+
+def test_plot_pca_LR_comparative_ggi():
+    result = ctpl.plot.plot_pca_LR_comparative(
+        lrobj_tblPCA=lrobj_tblPCA,
+        pca_table='CTR_ggi',
+        dims=(1, 2),
+        ret=True,
+        ggi=True,
+        include_tf=False,
+        gene_types="all"
+    )
+    assert result is not None
+    assert 'CTR_ggi' in result
+    plt.close("all")
+
+
+def test_plot_pca_LR_comparative_no_ggi():
+    result = ctpl.plot.plot_pca_LR_comparative(
+        lrobj_tblPCA=lrobj_tblPCA,
+        pca_table='CTR',
+        dims=(1, 2),
+        ret=True,
+        ggi=False
+    )
+    assert result is not None
+    assert 'CTR' in result
+    plt.close("all")
+
+
+def test_plot_bar_rankings_cci():
+    ctpl.plot.plot_bar_rankings(
+        annData=adata,
+        table_name='EXP_x_CTR',
+        ranking='Pagerank',
+        type=None,
+        filter_sign=None,
+        mode='cci',
+        top_num=10
+    )
+    plt.close("all")
+
+
+def test_plot_bar_rankings_cgi():
+    ctpl.plot.plot_bar_rankings(
+        annData=adata,
+        table_name='EXP_x_CTR_ggi',
+        ranking='Pagerank',
+        type=None,
+        filter_sign=None,
+        mode='cgi',
+        top_num=10
+    )
+    plt.close("all")
+
+
+def test_plot_bar_rankings_with_type_filter():
+    result = ctpl.plot.plot_bar_rankings(
+        annData=adata,
+        table_name='EXP_x_CTR_ggi',
+        ranking='Pagerank',
+        type='LR',
+        filter_sign=None,
+        mode='cgi',
+        top_num=10
+    )
+    # May return "No entries" string if no matches, or None if plotted
+    assert result is None or isinstance(result, str)
+    plt.close("all")
+
+
+def test_plot_sankey():
+    ctpl.plot.plot_sankey(
+        lrobj_tbl=data['tables']['CTR'],
+        target=None,
+        ligand_cluster=None,
+        receptor_cluster=None,
+        plt_name='CTR Sankey',
+        threshold=50
+    )
+    plt.close("all")
+
+
+def test_plot_sankey_with_target():
+    # Use the first gene_B value from the CTR table as a receptor target
+    sample_gene = data['tables']['CTR']['gene_B'].iloc[0]
+    ctpl.plot.plot_sankey(
+        lrobj_tbl=data['tables']['CTR'],
+        target=sample_gene,
+        ligand_cluster=None,
+        receptor_cluster=None,
+        plt_name='Sankey with target',
+        threshold=50
+    )
+    plt.close("all")
+
+
+def test_plot_volcane_fisher():
+    stats_df = data['stats']['EXP_x_CTR'].copy()
+    ctpl.plot.plot_volcane(
+        df=stats_df,
+        method='fisher',
+        p_threshold=0.05,
+        fc_threshold=1,
+        figsize=(8, 6),
+        annot=True,
+        title='Volcano Plot (Fisher)'
+    )
+    plt.close("all")
+
+
+def test_plot_clustermap():
+    ctpl.plot.plot_clustermap(
+        data=data['tables']['CTR'],
+        title='CTR Clustermap',
+        annot=True,
+        return_figure=False
+    )
+    plt.close("all")
+
+
+def test_plot_graph_clustermap():
+    ctpl.plot.plot_graph_clustermap(
+        graph=data['graphs']['CTR'],
+        weight='LRScore',
+        title='CTR Graph Clustermap',
+        annot=True
+    )
+    plt.close("all")
+
+
+def test_plot_graph_clustermap_exp_x_ctr():
+    ctpl.plot.plot_graph_clustermap(
+        graph=data['graphs']['EXP_x_CTR'],
+        weight='LRScore',
+        title='EXP_x_CTR Graph Clustermap',
+        annot=True
+    )
+    plt.close("all")