Multiple variants on the same displot

benchmarks/scripts/analyze.py

@@ -216,7 +216,6 @@ def coverage(args):
 def case_variants(pattern, algname, ct_point_name, case_df):
     title = "{}[{}]:".format(algname, ct_point_name)
     df = case_df[case_df['variant'].str.contains(pattern, regex=True)].reset_index(drop=True)
-    num_records = len(df)
     rt_axes = get_rt_axes(df)
     rt_axes_values = extract_rt_axes_values(df)
 
@@ -231,54 +230,68 @@ def case_variants(pattern, algname, ct_point_name, case_df):
     for idx, val in enumerate(vertical_axis_values):
         vertical_axis_ids[val] = idx
 
-    if len(horizontal_axes) > 0:
-        def extract_horizontal_space(df):
-            values = []
-            for rt_axis in horizontal_axes:
-                values.append(["{}={}".format(rt_axis, v) for v in df[rt_axis].unique()])
-            return list(itertools.product(*values))
+    def extract_horizontal_space(df):
+        values = []
+        for rt_axis in horizontal_axes:
+            values.append(["{}={}".format(rt_axis, v) for v in df[rt_axis].unique()])
+        return list(itertools.product(*values))
 
+    if len(horizontal_axes) > 0:
         idx = 0
         horizontal_axis_ids = {}
         for point in extract_horizontal_space(df):
             horizontal_axis_ids[" / ".join(point)] = idx
             idx = idx + 1
 
     num_rows = len(vertical_axis_ids)
-    num_cols = num_records // num_rows
+    num_cols = max(1, len(extract_horizontal_space(df)))
     fig, axes = plt.subplots(nrows=num_rows, ncols=num_cols, gridspec_kw = {'wspace': 0, 'hspace': 0})
 
-    for _, row in df.iterrows():
-        description = row['variant']
-        data = {description: row['samples'],
-                'base': row['base_samples']}
 
-        vertical_val = row[vertical_axis_name]
+    for _, vertical_row_description in df[[vertical_axis_name]].drop_duplicates().iterrows():
+        vertical_val = vertical_row_description[vertical_axis_name]
         vertical_id = vertical_axis_ids[vertical_val]
         vertical_name = "{}={}".format(vertical_axis_name, vertical_val)
-        horizontal_id = 0
-
-        if len(horizontal_axes) > 0:
-            horizontal_point = []
-            for rt_axis in horizontal_axes:
-                horizontal_point.append("{}={}".format(rt_axis, row[rt_axis]))
-            horizontal_name = " / ".join(horizontal_point)
-            horizontal_id = horizontal_axis_ids[horizontal_name]
-            ax=axes[vertical_id, horizontal_id]
-        else:
-            ax=axes[vertical_id]
-            ax.set_ylabel(vertical_name)
 
-        sns.histplot(data, ax=ax, kde=True)
+        vertical_df = df[df[vertical_axis_name] == vertical_val]
 
-        if len(horizontal_axes) > 0:
-            ax=axes[vertical_id, horizontal_id]
-            if vertical_id == (num_rows - 1):
-                ax.set_xlabel(horizontal_name)
-            if horizontal_id == 0:
-                ax.set_ylabel(vertical_name)
+        for _, horizontal_row_description in vertical_df[horizontal_axes].drop_duplicates().iterrows():
+            horizontal_df = vertical_df
+
+            for axis in horizontal_axes:
+                horizontal_df = horizontal_df[horizontal_df[axis] == horizontal_row_description[axis]]
+
+            horizontal_id = 0
+
+            if len(horizontal_axes) > 0:
+                horizontal_point = []
+                for rt_axis in horizontal_axes:
+                    horizontal_point.append("{}={}".format(rt_axis, horizontal_row_description[rt_axis]))
+                horizontal_name = " / ".join(horizontal_point)
+                horizontal_id = horizontal_axis_ids[horizontal_name]
+                ax=axes[vertical_id, horizontal_id]
             else:
-                ax.set_ylabel('')
+                ax=axes[vertical_id]
+                ax.set_ylabel(vertical_name)
+
+            data = {}
+            for _, variant in horizontal_df[['variant']].drop_duplicates().iterrows():
+                variant_name = variant['variant']
+                if 'base' not in data:
+                    data['base'] = horizontal_df[horizontal_df['variant'] == variant_name].iloc[0]['base_samples']
+
+                data[variant_name] = horizontal_df[horizontal_df['variant'] == variant_name].iloc[0]['samples']
+
+            sns.histplot(data=data, ax=ax, kde=True)
+
+            if len(horizontal_axes) > 0:
+                ax=axes[vertical_id, horizontal_id]
+                if vertical_id == (num_rows - 1):
+                    ax.set_xlabel(horizontal_name)
+                if horizontal_id == 0:
+                    ax.set_ylabel(vertical_name)
+                else:
+                    ax.set_ylabel('')
 
     for ax in axes.flat:
         ax.set_xticklabels([])