Added swarm_side for choosing of asymmetric side

Author: sunroofgod

dabest/plotter.py

@@ -547,7 +547,9 @@ def effectsize_df_plotter(effectsize_df, **plot_kwargs):
                             delta_df[yvar] = temp_df_exp[yvar] - temp_df_cont[yvar]
                             final_deltas = pd.concat([final_deltas, delta_df])
 
-                # Change jitter for Gardner-Altman plot
+                # swarmplot() plots swarms based on current size of ax
+                # Therefore, since the ax size for Gardner-Altman plot changes later on, there has to be decreased jitter
+                # TODO: to make jitter value more accurate and not just a hardcoded eyeball value
                 if float_contrast:
                     jitter = 0.6
                 else:
@@ -627,7 +629,13 @@ def effectsize_df_plotter(effectsize_df, **plot_kwargs):
     else:
         if not proportional:
             # Plot the raw data as a swarmplot.
-            asymmetric_side = "right"
+            asymmetric_side = (
+                plot_kwargs["swarm_side"] if plot_kwargs["swarm_side"] is not None else "right"
+            )  # Default asymmetric side is right
+
+            # swarmplot() plots swarms based on current size of ax
+            # Therefore, since the ax size for mini_meta and show_delta changes later on, there has to be increased jitter
+            # TODO: to make jitter value more accurate and not just a hardcoded eyeball value
             if show_mini_meta:
                 jitter = 1.25
             elif show_delta2:
@@ -698,6 +706,7 @@ def effectsize_df_plotter(effectsize_df, **plot_kwargs):
             for jj, c in enumerate(rawdata_axes.collections):
                 try:
                     if asymmetric_side == "right":
+                        # currently offset is hardcoded with value of -0.2
                         x_max_span = -0.2
                     else:
                         _, x_max, _, _ = get_swarm_spans(c)

nbs/API/plotter.ipynb

@@ -606,7 +606,9 @@
     "                            delta_df[yvar] = temp_df_exp[yvar] - temp_df_cont[yvar]\n",
     "                            final_deltas = pd.concat([final_deltas, delta_df])\n",
     "\n",
-    "                # Change jitter for Gardner-Altman plot\n",
+    "                # swarmplot() plots swarms based on current size of ax\n",
+    "                # Therefore, since the ax size for Gardner-Altman plot changes later on, there has to be decreased jitter\n",
+    "                # TODO: to make jitter value more accurate and not just a hardcoded eyeball value\n",
     "                if float_contrast:\n",
     "                    jitter = 0.6\n",
     "                else:\n",
@@ -686,7 +688,13 @@
     "    else:\n",
     "        if not proportional:\n",
     "            # Plot the raw data as a swarmplot.\n",
-    "            asymmetric_side = \"right\"\n",
+    "            asymmetric_side = (\n",
+    "                plot_kwargs[\"swarm_side\"] if plot_kwargs[\"swarm_side\"] is not None else \"right\"\n",
+    "            )  # Default asymmetric side is right\n",
+    "\n",
+    "            # swarmplot() plots swarms based on current size of ax\n",
+    "            # Therefore, since the ax size for mini_meta and show_delta changes later on, there has to be increased jitter\n",
+    "            # TODO: to make jitter value more accurate and not just a hardcoded eyeball value\n",
     "            if show_mini_meta:\n",
     "                jitter = 1.25\n",
     "            elif show_delta2:\n",
@@ -757,6 +765,7 @@
     "            for jj, c in enumerate(rawdata_axes.collections):\n",
     "                try:\n",
     "                    if asymmetric_side == \"right\":\n",
+    "                        # currently offset is hardcoded with value of -0.2\n",
     "                        x_max_span = -0.2\n",
     "                    else:\n",
     "                        _, x_max, _, _ = get_swarm_spans(c)\n",