Added some tests and updated summary bars to allow full ax span or start directly from the contrast object

Author: JAnns98

dabest/_effsize_objects.py

@@ -1197,7 +1197,7 @@ def plot(
             Pass a list of indices of the contrast objects to have summary bars displayed on the plot.
             For example, [0,1] will show summary bars for the first two contrast objects.
         summary_bars_kwargs: dict, default None
-            If None, the following keywords are passed: {"color": None, "alpha": 0.15}
+            If None, the following keywords are passed: {"span_ax": False, "color": None, "alpha": 0.15}
         delta_text : boolean, default True
             Whether or not to display the text deltas.
         delta_text_kwargs : dict, default None

dabest/misc_tools.py

@@ -350,6 +350,7 @@ def get_kwargs(plot_kwargs, ytick_color):
 
     # Summary bars kwargs.
     default_summary_bars_kwargs = {
+                    "span_ax": False,
                     "color": None, 
                     "alpha": 0.15
     }
@@ -617,23 +618,23 @@ def initialize_fig(plot_kwargs, dabest_obj, show_delta2, show_mini_meta, is_pair
         if show_delta2 or show_mini_meta:
             all_groups_count += 2
 
-        if is_paired and show_pairs and proportional is False:
-            frac = 0.8
-        else:
-            frac = 1
-        if float_contrast:
-            height_inches = 4
-            each_group_width_inches = 2.5 * frac
-        else:
-            height_inches = 6
-            each_group_width_inches = 1.5 * frac
-
-        width_inches = each_group_width_inches * all_groups_count
-        fig_size = (width_inches, height_inches) 
-
         if horizontal:
             frac = 0.3 if is_paired or show_mini_meta else 0.5
             fig_size = (7, 1 + (frac * all_groups_count))
+        else:
+            if is_paired and show_pairs and proportional is False:
+                frac = 0.8
+            else:
+                frac = 1
+            if float_contrast:
+                height_inches = 4
+                each_group_width_inches = 2.5 * frac
+            else:
+                height_inches = 6
+                each_group_width_inches = 1.5 * frac
+
+            width_inches = each_group_width_inches * all_groups_count
+            fig_size = (width_inches, height_inches) 
 
     init_fig_kwargs = dict(figsize=fig_size, dpi=plot_kwargs["dpi"], tight_layout=True)
 
@@ -701,6 +702,7 @@ def initialize_fig(plot_kwargs, dabest_obj, show_delta2, show_mini_meta, is_pair
                     ]
                 )
 
+            # Set axes
             contrast_axes = axins
             rawdata_axes.contrast_axes = axins
             table_axes = None
@@ -734,9 +736,12 @@ def initialize_fig(plot_kwargs, dabest_obj, show_delta2, show_mini_meta, is_pair
         fontsize_title = plot_kwargs["fontsize_title"]
         if title is not None:
             fig.suptitle(title, fontsize=fontsize_title)
+
+        # Set axes   
         rawdata_axes = axx[0]
         contrast_axes = axx[1]
         table_axes = axx[2] if horizontal and show_table else None
+
     rawdata_axes.set_frame_on(False)
     contrast_axes.set_frame_on(False)
     if horizontal and show_table:
@@ -783,17 +788,11 @@ def initialize_fig(plot_kwargs, dabest_obj, show_delta2, show_mini_meta, is_pair
                     contrast_axes.set_ylim(contrast_ylim)
 
     # Set raw axes y-label.
-    swarm_label = plot_kwargs["swarm_label"]
-    if swarm_label is None and yvar is None:
-        swarm_label = "value"
-    elif swarm_label is None and yvar is not None:
-        swarm_label = yvar
-
-    bar_label = plot_kwargs["bar_label"]
-    if bar_label is None and effect_size_type != "cohens_h":
-        bar_label = "proportion of success"
-    elif bar_label is None and effect_size_type == "cohens_h":
-        bar_label = "value"
+    swarm_label, bar_label = plot_kwargs["swarm_label"], plot_kwargs["bar_label"]
+    if swarm_label is None:
+        swarm_label = yvar if yvar is not None else "value"
+    if bar_label is None:
+        bar_label = "proportion of success" if effect_size_type != "cohens_h" else "value"
 
     fontsize_rawylabel = plot_kwargs["fontsize_rawylabel"]
     rawdata_label = bar_label if proportional else swarm_label

dabest/plot_tools.py

@@ -875,7 +875,7 @@ def sankeydiag(
 def summary_bars_plotter(summary_bars: list, results: object, ax_to_plot: object,
                  float_contrast: bool,summary_bars_kwargs: dict, ci_type: str,
                  ticks_to_plot: list, color_col: str, plot_palette_raw: dict, 
-                 proportional: bool, is_paired: bool):
+                 proportional: bool, is_paired: bool, horizontal: bool):
     """
     Add summary bars to the contrast plot. Currently only functional for Vertical plots.
 
@@ -903,6 +903,8 @@ def summary_bars_plotter(summary_bars: list, results: object, ax_to_plot: object
         Whether the data is proportional.
     is_paired : bool
         Whether the data is paired.
+    horizontal : bool
+        Whether the plot is horizontal.
     """
 # Begin checks        
     if not isinstance(summary_bars, list):
@@ -916,6 +918,8 @@ def summary_bars_plotter(summary_bars: list, results: object, ax_to_plot: object
 # End checks
     else:
         summary_xmin, summary_xmax = ax_to_plot.get_xlim()
+        summary_ymin, summary_ymax = ax_to_plot.get_ylim()
+
         summary_bars_colors = (
             [summary_bars_kwargs.get('color')]*int(max(ticks_to_plot)+1)
             if summary_bars_kwargs.get('color') is not None
@@ -924,6 +928,8 @@ def summary_bars_plotter(summary_bars: list, results: object, ax_to_plot: object
             else list(plot_palette_raw.values())
         )
         summary_bars_kwargs.pop('color')
+        span_ax = summary_bars_kwargs.pop("span_ax")
+
         for summary_index in summary_bars:
             if ci_type == "bca":
                 summary_ci_low = results.bca_low[summary_index]
@@ -932,12 +938,28 @@ def summary_bars_plotter(summary_bars: list, results: object, ax_to_plot: object
                 summary_ci_low = results.pct_low[summary_index]
                 summary_ci_high = results.pct_high[summary_index]
 
-            summary_color = summary_bars_colors[int(ticks_to_plot[summary_index])]
-
-            ax_to_plot.add_patch(mpatches.Rectangle((summary_xmin,summary_ci_low),summary_xmax+1, 
-            summary_ci_high-summary_ci_low, zorder=-2, color=summary_color, **summary_bars_kwargs))
+            if span_ax == True:
+                starting_location = summary_ymax if horizontal else summary_xmin
+            else:
+                starting_location = ticks_to_plot[summary_index]                
 
+            summary_color = summary_bars_colors[int(ticks_to_plot[summary_index])]
 
+            if horizontal:
+                ax_to_plot.add_patch(mpatches.Rectangle(
+                    (summary_ci_low, starting_location),
+                    summary_ci_high-summary_ci_low, summary_ymin+1, 
+                    zorder=-2, color=summary_color, 
+                    **summary_bars_kwargs)
+                    )
+            else:
+                ax_to_plot.add_patch(mpatches.Rectangle(
+                    (starting_location, summary_ci_low),
+                    summary_xmax+1, summary_ci_high-summary_ci_low, 
+                    zorder=-2, color=summary_color, 
+                    **summary_bars_kwargs)
+                    )
+                
 def contrast_bars_plotter(results: object, ax_to_plot: object,  swarm_plot_ax: object,
                           ticks_to_plot: list, contrast_bars_kwargs: dict, color_col: str, 
                           plot_palette_raw: dict, show_mini_meta: bool, mini_meta_delta: object, 

dabest/plotter.py

@@ -501,7 +501,7 @@ def effectsize_df_plotter(effectsize_df, **plot_kwargs):
 
     # Summary bars WIP
     summary_bars = plot_kwargs["summary_bars"]
-    if summary_bars is not None and not horizontal:
+    if summary_bars is not None:
         summary_bars_plotter(
                         summary_bars = summary_bars, 
                         results = results, 
@@ -513,7 +513,8 @@ def effectsize_df_plotter(effectsize_df, **plot_kwargs):
                         color_col = color_col,
                         plot_palette_raw = plot_palette_raw, 
                         proportional = proportional, 
-                        is_paired = is_paired
+                        is_paired = is_paired,
+                        horizontal = horizontal,
                         )
     # Delta text WIP
     delta_text = plot_kwargs["delta_text"]

nbs/API/effsize_objects.ipynb

@@ -1356,7 +1356,7 @@
     "            Pass a list of indices of the contrast objects to have summary bars displayed on the plot.\n",
     "            For example, [0,1] will show summary bars for the first two contrast objects.\n",
     "        summary_bars_kwargs: dict, default None\n",
-    "            If None, the following keywords are passed: {\"color\": None, \"alpha\": 0.15}\n",
+    "            If None, the following keywords are passed: {\"span_ax\": False, \"color\": None, \"alpha\": 0.15}\n",
     "        delta_text : boolean, default True\n",
     "            Whether or not to display the text deltas.\n",
     "        delta_text_kwargs : dict, default None\n",

nbs/API/misc_tools.ipynb

@@ -403,6 +403,7 @@
     "\n",
     "    # Summary bars kwargs.\n",
     "    default_summary_bars_kwargs = {\n",
+    "                    \"span_ax\": False,\n",
     "                    \"color\": None, \n",
     "                    \"alpha\": 0.15\n",
     "    }\n",
@@ -670,23 +671,23 @@
     "        if show_delta2 or show_mini_meta:\n",
     "            all_groups_count += 2\n",
     "   \n",
-    "        if is_paired and show_pairs and proportional is False:\n",
-    "            frac = 0.8\n",
-    "        else:\n",
-    "            frac = 1\n",
-    "        if float_contrast:\n",
-    "            height_inches = 4\n",
-    "            each_group_width_inches = 2.5 * frac\n",
-    "        else:\n",
-    "            height_inches = 6\n",
-    "            each_group_width_inches = 1.5 * frac\n",
-    "\n",
-    "        width_inches = each_group_width_inches * all_groups_count\n",
-    "        fig_size = (width_inches, height_inches) \n",
-    "\n",
     "        if horizontal:\n",
     "            frac = 0.3 if is_paired or show_mini_meta else 0.5\n",
     "            fig_size = (7, 1 + (frac * all_groups_count))\n",
+    "        else:\n",
+    "            if is_paired and show_pairs and proportional is False:\n",
+    "                frac = 0.8\n",
+    "            else:\n",
+    "                frac = 1\n",
+    "            if float_contrast:\n",
+    "                height_inches = 4\n",
+    "                each_group_width_inches = 2.5 * frac\n",
+    "            else:\n",
+    "                height_inches = 6\n",
+    "                each_group_width_inches = 1.5 * frac\n",
+    "\n",
+    "            width_inches = each_group_width_inches * all_groups_count\n",
+    "            fig_size = (width_inches, height_inches) \n",
     "\n",
     "    init_fig_kwargs = dict(figsize=fig_size, dpi=plot_kwargs[\"dpi\"], tight_layout=True)\n",
     "\n",
@@ -754,6 +755,7 @@
     "                    ]\n",
     "                )\n",
     "\n",
+    "            # Set axes\n",
     "            contrast_axes = axins\n",
     "            rawdata_axes.contrast_axes = axins\n",
     "            table_axes = None\n",
@@ -787,9 +789,12 @@
     "        fontsize_title = plot_kwargs[\"fontsize_title\"]\n",
     "        if title is not None:\n",
     "            fig.suptitle(title, fontsize=fontsize_title)\n",
+    "\n",
+    "        # Set axes   \n",
     "        rawdata_axes = axx[0]\n",
     "        contrast_axes = axx[1]\n",
     "        table_axes = axx[2] if horizontal and show_table else None\n",
+    "\n",
     "    rawdata_axes.set_frame_on(False)\n",
     "    contrast_axes.set_frame_on(False)\n",
     "    if horizontal and show_table:\n",
@@ -836,17 +841,11 @@
     "                    contrast_axes.set_ylim(contrast_ylim)\n",
     "\n",
     "    # Set raw axes y-label.\n",
-    "    swarm_label = plot_kwargs[\"swarm_label\"]\n",
-    "    if swarm_label is None and yvar is None:\n",
-    "        swarm_label = \"value\"\n",
-    "    elif swarm_label is None and yvar is not None:\n",
-    "        swarm_label = yvar\n",
-    "\n",
-    "    bar_label = plot_kwargs[\"bar_label\"]\n",
-    "    if bar_label is None and effect_size_type != \"cohens_h\":\n",
-    "        bar_label = \"proportion of success\"\n",
-    "    elif bar_label is None and effect_size_type == \"cohens_h\":\n",
-    "        bar_label = \"value\"\n",
+    "    swarm_label, bar_label = plot_kwargs[\"swarm_label\"], plot_kwargs[\"bar_label\"]\n",
+    "    if swarm_label is None:\n",
+    "        swarm_label = yvar if yvar is not None else \"value\"\n",
+    "    if bar_label is None:\n",
+    "        bar_label = \"proportion of success\" if effect_size_type != \"cohens_h\" else \"value\"\n",
     "\n",
     "    fontsize_rawylabel = plot_kwargs[\"fontsize_rawylabel\"]\n",
     "    rawdata_label = bar_label if proportional else swarm_label\n",

nbs/API/plot_tools.ipynb

@@ -925,7 +925,7 @@
     "def summary_bars_plotter(summary_bars: list, results: object, ax_to_plot: object,\n",
     "                 float_contrast: bool,summary_bars_kwargs: dict, ci_type: str,\n",
     "                 ticks_to_plot: list, color_col: str, plot_palette_raw: dict, \n",
-    "                 proportional: bool, is_paired: bool):\n",
+    "                 proportional: bool, is_paired: bool, horizontal: bool):\n",
     "    \"\"\"\n",
     "    Add summary bars to the contrast plot. Currently only functional for Vertical plots.\n",
     "\n",
@@ -953,6 +953,8 @@
     "        Whether the data is proportional.\n",
     "    is_paired : bool\n",
     "        Whether the data is paired.\n",
+    "    horizontal : bool\n",
+    "        Whether the plot is horizontal.\n",
     "    \"\"\"\n",
     "# Begin checks        \n",
     "    if not isinstance(summary_bars, list):\n",
@@ -966,6 +968,8 @@
     "# End checks\n",
     "    else:\n",
     "        summary_xmin, summary_xmax = ax_to_plot.get_xlim()\n",
+    "        summary_ymin, summary_ymax = ax_to_plot.get_ylim()\n",
+    "\n",
     "        summary_bars_colors = (\n",
     "            [summary_bars_kwargs.get('color')]*int(max(ticks_to_plot)+1)\n",
     "            if summary_bars_kwargs.get('color') is not None\n",
@@ -974,6 +978,8 @@
     "            else list(plot_palette_raw.values())\n",
     "        )\n",
     "        summary_bars_kwargs.pop('color')\n",
+    "        span_ax = summary_bars_kwargs.pop(\"span_ax\")\n",
+    "\n",
     "        for summary_index in summary_bars:\n",
     "            if ci_type == \"bca\":\n",
     "                summary_ci_low = results.bca_low[summary_index]\n",
@@ -982,12 +988,28 @@
     "                summary_ci_low = results.pct_low[summary_index]\n",
     "                summary_ci_high = results.pct_high[summary_index]\n",
     "\n",
-    "            summary_color = summary_bars_colors[int(ticks_to_plot[summary_index])]\n",
-    "\n",
-    "            ax_to_plot.add_patch(mpatches.Rectangle((summary_xmin,summary_ci_low),summary_xmax+1, \n",
-    "            summary_ci_high-summary_ci_low, zorder=-2, color=summary_color, **summary_bars_kwargs))\n",
+    "            if span_ax == True:\n",
+    "                starting_location = summary_ymax if horizontal else summary_xmin\n",
+    "            else:\n",
+    "                starting_location = ticks_to_plot[summary_index]                \n",
     "\n",
+    "            summary_color = summary_bars_colors[int(ticks_to_plot[summary_index])]\n",
     "\n",
+    "            if horizontal:\n",
+    "                ax_to_plot.add_patch(mpatches.Rectangle(\n",
+    "                    (summary_ci_low, starting_location),\n",
+    "                    summary_ci_high-summary_ci_low, summary_ymin+1, \n",
+    "                    zorder=-2, color=summary_color, \n",
+    "                    **summary_bars_kwargs)\n",
+    "                    )\n",
+    "            else:\n",
+    "                ax_to_plot.add_patch(mpatches.Rectangle(\n",
+    "                    (starting_location, summary_ci_low),\n",
+    "                    summary_xmax+1, summary_ci_high-summary_ci_low, \n",
+    "                    zorder=-2, color=summary_color, \n",
+    "                    **summary_bars_kwargs)\n",
+    "                    )\n",
+    "                \n",
     "def contrast_bars_plotter(results: object, ax_to_plot: object,  swarm_plot_ax: object,\n",
     "                          ticks_to_plot: list, contrast_bars_kwargs: dict, color_col: str, \n",
     "                          plot_palette_raw: dict, show_mini_meta: bool, mini_meta_delta: object, \n",

nbs/API/plotter.ipynb

@@ -558,7 +558,7 @@
     "\n",
     "    # Summary bars WIP\n",
     "    summary_bars = plot_kwargs[\"summary_bars\"]\n",
-    "    if summary_bars is not None and not horizontal:\n",
+    "    if summary_bars is not None:\n",
     "        summary_bars_plotter(\n",
     "                        summary_bars = summary_bars, \n",
     "                        results = results, \n",
@@ -570,7 +570,8 @@
     "                        color_col = color_col,\n",
     "                        plot_palette_raw = plot_palette_raw, \n",
     "                        proportional = proportional, \n",
-    "                        is_paired = is_paired\n",
+    "                        is_paired = is_paired,\n",
+    "                        horizontal = horizontal,\n",
     "                        )\n",
     "    # Delta text WIP\n",
     "    delta_text = plot_kwargs[\"delta_text\"]\n",