wrote script to create plot for decoy gene fractions across methods

src/dialect/utils/plotting.py

@@ -0,0 +1,97 @@
+import os
+import pandas as pd
+
+from itertools import product
+from matplotlib import rcParams
+from plotnine import (
+    ggplot,
+    aes,
+    geom_boxplot,
+    geom_point,
+    theme,
+    theme_tufte,
+    element_text,
+    labs,
+    scale_shape_manual,
+    scale_color_manual,
+    guides,
+    guide_legend,
+    position_jitter,
+)
+
+# ---------------------------------------------------------------------------- #
+#                          SET DEFAULT PLOTTING STYLE                          #
+# ---------------------------------------------------------------------------- #
+
+rcParams["font.family"] = "serif"
+rcParams["font.serif"] = ["Computer Modern"]
+rcParams["text.usetex"] = True  # Optional for LaTeX-like rendering
+
+
+# ---------------------------------------------------------------------------- #
+#                                 MAIN FUNCTION                                #
+# ---------------------------------------------------------------------------- #
+def plotnine_decoy_gene_fractions(data_filepath, out_dir):
+    df = pd.read_csv(data_filepath)
+
+    subtypes = df["Subtype"].unique()
+    colors = ["green", "blue", "red", "purple", "yellow", "orange", "black", "brown"]
+    shapes = ["o", "s", "^", "D"]  # Circle, square, triangle, diamond
+
+    color_shape_combinations = list(product(colors, shapes))
+    color_shape_mapping = {
+        subtypes[i]: color_shape_combinations[i] for i in range(len(subtypes))
+    }
+    color_mapping = {
+        subtype: combo[0] for subtype, combo in color_shape_mapping.items()
+    }
+    shape_mapping = {
+        subtype: combo[1] for subtype, combo in color_shape_mapping.items()
+    }
+
+    # Create the Plot
+    plot = (
+        ggplot(df, aes(x="Method", y="Fraction", color="Subtype", shape="Subtype"))
+        + geom_boxplot(
+            aes(group="Method"),
+            alpha=0.5,
+            outlier_alpha=0,
+            # TODO set y limit to 1
+            show_legend=False,
+        )
+        + geom_point(
+            position=position_jitter(width=0.25),
+            size=5,
+            alpha=0.75,
+            show_legend=True,
+        )
+        + scale_color_manual(values=color_mapping)  # Custom color mapping
+        + scale_shape_manual(values=shape_mapping)  # Custom shape mapping
+        + labs(
+            title="Proportion of Top-Ranked Pairs with Decoy Genes by Method",
+            x="Method",
+            y="Proportion of Top 100 Pairs with Decoy Genes",
+            color="Subtype",
+            shape="Subtype",
+        )
+        + theme_tufte(base_family="Computer Modern")
+        + theme(
+            figure_size=(12, 8),
+            plot_title=element_text(size=20, weight="bold"),
+            axis_title=element_text(size=18),
+            axis_text=element_text(size=16),
+            legend_title=element_text(size=14, hjust=0.5),
+            legend_text=element_text(size=12),
+            legend_position="bottom",
+            legend_box="horizontal",
+        )
+        + guides(
+            color=guide_legend(title="Subtypes", ncol=11),
+            shape=guide_legend(title="Subtypes", ncol=11),
+        )
+    )
+
+    # Step 4: Save Plot
+    os.makedirs(out_dir, exist_ok=True)
+    plot.save(f"{out_dir}/decoy_gene_fractions_boxplot_plotnine.svg", dpi=300)
+    print(f"Plot saved to {out_dir}/decoy_gene_fractions_boxplot_plotnine.svg")