Fixed coloring of summary bars and added delta text (WIP)

dabest/_effsize_objects.py

@@ -1024,6 +1024,8 @@ def plot(
         swarm_bars_kwargs=None,
         summary_bars=None,
         summary_bars_kwargs=None,
+        delta_text=True,
+        delta_text_kwargs=None,
     ):
         """
         Creates an estimation plot for the effect size of interest.
@@ -1186,6 +1188,14 @@ def 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}
+        delta_text : boolean, default True
+            Whether or not to display the text deltas.
+        delta_text_kwargs : dict, default None
+            Pass relevant keyword arguments to the delta text. Pass any keyword arguments accepted by
+            matplotlib.text.Text here, as a string. If None, the following keywords are passed:
+            {"color": None, "alpha": 1, "fontsize": 10, "ha": 'center', "va": 'center', "rotation": 0, 
+            "x_location": 'right', "x_coordinates": None, "y_coordinates": None}
+            Use "x_coordinates" and "y_coordinates" if you would like to specify the text locations manually.
 
         Returns
         -------

dabest/plot_tools.py

@@ -824,7 +824,7 @@ 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_bars_colors = [summary_bars_kwargs.get('color')]*(len(summary_bars)+1) if summary_bars_kwargs.get('color') is not None else ['black']*(max(summary_bars)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors
+        summary_bars_colors = [summary_bars_kwargs.get('color')]*(max(summary_bars)+1) if summary_bars_kwargs.get('color') is not None else ['black']*(max(summary_bars)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors
         summary_bars_kwargs.pop('color')
         for summary_index in summary_bars:
             if ci_type == "bca":
@@ -880,7 +880,7 @@ def contrast_bars_plotter(results: object, ax_to_plot: object,  swarm_plot_ax: o
     for j, tick in enumerate(ticks_to_plot):
         contrast_means.append(results.difference[j])
 
-    contrast_bars_colors = [contrast_bars_kwargs.get('color')]*(len(ticks_to_plot)+1) if contrast_bars_kwargs.get('color') is not None else ['black']*(max(ticks_to_plot)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors
+    contrast_bars_colors = [contrast_bars_kwargs.get('color')]*(max(ticks_to_plot)+1) if contrast_bars_kwargs.get('color') is not None else ['black']*(max(ticks_to_plot)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors
     contrast_bars_kwargs.pop('color')
     for contrast_bars_x,contrast_bars_y in zip(ticks_to_plot, contrast_means):
         ax_to_plot.add_patch(mpatches.Rectangle((contrast_bars_x-0.25,0),0.5, contrast_bars_y, zorder=-1, color=contrast_bars_colors[contrast_bars_x], **contrast_bars_kwargs))
@@ -929,7 +929,7 @@ def swarm_bars_plotter(plot_data: object, xvar: str, yvar: str, ax: object,
         swarm_bars_order = pd.unique(plot_data[xvar])
 
     swarm_means = plot_data.groupby(xvar)[yvar].mean().reindex(index=swarm_bars_order)
-    swarm_bars_colors = [swarm_bars_kwargs.get('color')]*(len(swarm_bars_order)+1) if swarm_bars_kwargs.get('color') is not None else ['black']*(len(swarm_bars_order)+1) if color_col is not None or is_paired else swarm_colors
+    swarm_bars_colors = [swarm_bars_kwargs.get('color')]*(max(swarm_bars_order)+1) if swarm_bars_kwargs.get('color') is not None else ['black']*(len(swarm_bars_order)+1) if color_col is not None or is_paired else swarm_colors
     swarm_bars_kwargs.pop('color')
     for swarm_bars_x,swarm_bars_y,c in zip(np.arange(0,len(swarm_bars_order)+1,1), swarm_means, swarm_bars_colors):
         ax.add_patch(mpatches.Rectangle((swarm_bars_x-0.25,0),

dabest/plotter.py

@@ -56,7 +56,7 @@ def effectsize_df_plotter(effectsize_df, **plot_kwargs):
         fontsize_delta2label=12,
         swarm_bars=True, swarm_bars_kwargs=None,
         contrast_bars=True, contrast_bars_kwargs=None,
-
+        delta_text=True, delta_text_kwargs=None,
     """
     from .misc_tools import merge_two_dicts
     from .plot_tools import (
@@ -1637,6 +1637,61 @@ def effectsize_df_plotter(effectsize_df, **plot_kwargs):
 
     ################################################### Swarm & Contrast & Summary Bars WIP END
 
+    ################################################### Delta numbers WIP START
+    delta_text = plot_kwargs["delta_text"]
+    if delta_text:
+        default_delta_text_kwargs = {"color": None, "alpha": 1, "fontsize": 10, "ha": 'center', "va": 'center', "rotation": 0, "x_location": 'right', "x_coordinates": None, "y_coordinates": None}
+        if plot_kwargs["delta_text_kwargs"] is None:
+            delta_text_kwargs = default_delta_text_kwargs
+        else:
+            delta_text_kwargs = merge_two_dicts(default_delta_text_kwargs, plot_kwargs["delta_text_kwargs"])
+
+        delta_text_x_location = delta_text_kwargs.get('x_location')
+        if delta_text_x_location != 'right' and delta_text_x_location != 'left':
+            raise ValueError("delta_text_kwargs['x_location'] must be either 'right' or 'left'.")
+        delta_text_kwargs.pop('x_location')
+
+        delta_text_colors = [delta_text_kwargs.get('color')]*(max(ticks_to_plot)+1) if delta_text_kwargs.get('color') is not None else ['black']*(max(ticks_to_plot)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors
+        delta_text_kwargs.pop('color')
+
+        Delta_Values = []
+        for j, tick in enumerate(ticks_to_plot):
+            Delta_Values.append(results.difference[j])
+
+        delta_text_x_coordinates = delta_text_kwargs.get('x_coordinates')
+        delta_text_y_coordinates = delta_text_kwargs.get('y_coordinates')
+
+        if delta_text_x_coordinates is not None:
+            if not isinstance(delta_text_x_coordinates, list):
+                raise TypeError("delta_text_kwargs['x_coordinates'] must be a list of x-coordinates.")
+            if len(delta_text_x_coordinates) != len(ticks_to_plot):
+                raise ValueError("delta_text_kwargs['x_coordinates'] must have the same length as the number of ticks to plot.")
+            delta_text_x_coordinates_default = False
+            delta_text_kwargs.pop('x_coordinates')
+        else:
+            delta_text_x_coordinates = ticks_to_plot
+            delta_text_x_coordinates_default = True
+            delta_text_kwargs.pop('x_coordinates')
+
+
+        if delta_text_y_coordinates is not None:
+            if not isinstance(delta_text_y_coordinates, list):
+                raise TypeError("delta_text_kwargs['y_coordinates'] must be a list of y-coordinates.")
+            if len(delta_text_y_coordinates) != len(ticks_to_plot):
+                raise ValueError("delta_text_kwargs['y_coordinates'] must have the same length as the number of ticks to plot.")
+            delta_text_kwargs.pop('y_coordinates')
+        else:
+            delta_text_y_coordinates = Delta_Values
+            delta_text_kwargs.pop('y_coordinates')
+
+        for x,y,t,tick in zip(delta_text_x_coordinates, delta_text_y_coordinates,Delta_Values,ticks_to_plot):
+            Delta_Text = '+'+'{0:.2f}'.format(t) if t > 0 else '{0:.2f}'.format(t)
+            X_Adjust = 0 if not delta_text_x_coordinates_default else 0.53 if delta_text_x_location == 'right' else -0.35
+            contrast_axes.text(x+X_Adjust, y, Delta_Text, color=delta_text_colors[tick],**delta_text_kwargs)
+
+    ################################################### Delta numbers WIP END
+
+
     # Make sure no stray ticks appear!
     rawdata_axes.xaxis.set_ticks_position("bottom")
     rawdata_axes.yaxis.set_ticks_position("left")

nbs/API/effsize_objects.ipynb

@@ -1185,6 +1185,8 @@
     "        swarm_bars_kwargs=None,\n",
     "        summary_bars=None,\n",
     "        summary_bars_kwargs=None,\n",
+    "        delta_text=True,\n",
+    "        delta_text_kwargs=None,\n",
     "    ):\n",
     "        \"\"\"\n",
     "        Creates an estimation plot for the effect size of interest.\n",
@@ -1347,6 +1349,14 @@
     "            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",
+    "        delta_text : boolean, default True\n",
+    "            Whether or not to display the text deltas.\n",
+    "        delta_text_kwargs : dict, default None\n",
+    "            Pass relevant keyword arguments to the delta text. Pass any keyword arguments accepted by\n",
+    "            matplotlib.text.Text here, as a string. If None, the following keywords are passed:\n",
+    "            {\"color\": None, \"alpha\": 1, \"fontsize\": 10, \"ha\": 'center', \"va\": 'center', \"rotation\": 0, \n",
+    "            \"x_location\": 'right', \"x_coordinates\": None, \"y_coordinates\": None}\n",
+    "            Use \"x_coordinates\" and \"y_coordinates\" if you would like to specify the text locations manually.\n",
     "\n",
     "        Returns\n",
     "        -------\n",
@@ -1949,13 +1959,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "DABESTDEV",
+   "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.8"
   }
  },
  "nbformat": 4,

nbs/API/plot_tools.ipynb

@@ -878,7 +878,7 @@
     "# End checks\n",
     "    else:\n",
     "        summary_xmin, summary_xmax = ax_to_plot.get_xlim()\n",
-    "        summary_bars_colors = [summary_bars_kwargs.get('color')]*(len(summary_bars)+1) if summary_bars_kwargs.get('color') is not None else ['black']*(max(summary_bars)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors\n",
+    "        summary_bars_colors = [summary_bars_kwargs.get('color')]*(max(summary_bars)+1) if summary_bars_kwargs.get('color') is not None else ['black']*(max(summary_bars)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors\n",
     "        summary_bars_kwargs.pop('color')\n",
     "        for summary_index in summary_bars:\n",
     "            if ci_type == \"bca\":\n",
@@ -934,7 +934,7 @@
     "    for j, tick in enumerate(ticks_to_plot):\n",
     "        contrast_means.append(results.difference[j])\n",
     "\n",
-    "    contrast_bars_colors = [contrast_bars_kwargs.get('color')]*(len(ticks_to_plot)+1) if contrast_bars_kwargs.get('color') is not None else ['black']*(max(ticks_to_plot)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors\n",
+    "    contrast_bars_colors = [contrast_bars_kwargs.get('color')]*(max(ticks_to_plot)+1) if contrast_bars_kwargs.get('color') is not None else ['black']*(max(ticks_to_plot)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors\n",
     "    contrast_bars_kwargs.pop('color')\n",
     "    for contrast_bars_x,contrast_bars_y in zip(ticks_to_plot, contrast_means):\n",
     "        ax_to_plot.add_patch(mpatches.Rectangle((contrast_bars_x-0.25,0),0.5, contrast_bars_y, zorder=-1, color=contrast_bars_colors[contrast_bars_x], **contrast_bars_kwargs))\n",
@@ -983,7 +983,7 @@
     "        swarm_bars_order = pd.unique(plot_data[xvar])\n",
     "\n",
     "    swarm_means = plot_data.groupby(xvar)[yvar].mean().reindex(index=swarm_bars_order)\n",
-    "    swarm_bars_colors = [swarm_bars_kwargs.get('color')]*(len(swarm_bars_order)+1) if swarm_bars_kwargs.get('color') is not None else ['black']*(len(swarm_bars_order)+1) if color_col is not None or is_paired else swarm_colors\n",
+    "    swarm_bars_colors = [swarm_bars_kwargs.get('color')]*(max(swarm_bars_order)+1) if swarm_bars_kwargs.get('color') is not None else ['black']*(len(swarm_bars_order)+1) if color_col is not None or is_paired else swarm_colors\n",
     "    swarm_bars_kwargs.pop('color')\n",
     "    for swarm_bars_x,swarm_bars_y,c in zip(np.arange(0,len(swarm_bars_order)+1,1), swarm_means, swarm_bars_colors):\n",
     "        ax.add_patch(mpatches.Rectangle((swarm_bars_x-0.25,0),\n",

nbs/API/plotter.ipynb

@@ -115,7 +115,7 @@
     "        fontsize_delta2label=12,\n",
     "        swarm_bars=True, swarm_bars_kwargs=None,\n",
     "        contrast_bars=True, contrast_bars_kwargs=None,\n",
-    "\n",
+    "        delta_text=True, delta_text_kwargs=None,\n",
     "    \"\"\"\n",
     "    from .misc_tools import merge_two_dicts\n",
     "    from .plot_tools import (\n",
@@ -1696,6 +1696,61 @@
     "    \n",
     "    ################################################### Swarm & Contrast & Summary Bars WIP END\n",
     "\n",
+    "    ################################################### Delta numbers WIP START\n",
+    "    delta_text = plot_kwargs[\"delta_text\"]\n",
+    "    if delta_text:\n",
+    "        default_delta_text_kwargs = {\"color\": None, \"alpha\": 1, \"fontsize\": 10, \"ha\": 'center', \"va\": 'center', \"rotation\": 0, \"x_location\": 'right', \"x_coordinates\": None, \"y_coordinates\": None}\n",
+    "        if plot_kwargs[\"delta_text_kwargs\"] is None:\n",
+    "            delta_text_kwargs = default_delta_text_kwargs\n",
+    "        else:\n",
+    "            delta_text_kwargs = merge_two_dicts(default_delta_text_kwargs, plot_kwargs[\"delta_text_kwargs\"])\n",
+    "\n",
+    "        delta_text_x_location = delta_text_kwargs.get('x_location')\n",
+    "        if delta_text_x_location != 'right' and delta_text_x_location != 'left':\n",
+    "            raise ValueError(\"delta_text_kwargs['x_location'] must be either 'right' or 'left'.\")\n",
+    "        delta_text_kwargs.pop('x_location')\n",
+    "\n",
+    "        delta_text_colors = [delta_text_kwargs.get('color')]*(max(ticks_to_plot)+1) if delta_text_kwargs.get('color') is not None else ['black']*(max(ticks_to_plot)+1) if color_col is not None or (proportional and is_paired) or is_paired else swarm_colors\n",
+    "        delta_text_kwargs.pop('color')\n",
+    "\n",
+    "        Delta_Values = []\n",
+    "        for j, tick in enumerate(ticks_to_plot):\n",
+    "            Delta_Values.append(results.difference[j])\n",
+    "\n",
+    "        delta_text_x_coordinates = delta_text_kwargs.get('x_coordinates')\n",
+    "        delta_text_y_coordinates = delta_text_kwargs.get('y_coordinates')\n",
+    "\n",
+    "        if delta_text_x_coordinates is not None:\n",
+    "            if not isinstance(delta_text_x_coordinates, list):\n",
+    "                raise TypeError(\"delta_text_kwargs['x_coordinates'] must be a list of x-coordinates.\")\n",
+    "            if len(delta_text_x_coordinates) != len(ticks_to_plot):\n",
+    "                raise ValueError(\"delta_text_kwargs['x_coordinates'] must have the same length as the number of ticks to plot.\")\n",
+    "            delta_text_x_coordinates_default = False\n",
+    "            delta_text_kwargs.pop('x_coordinates')\n",
+    "        else:\n",
+    "            delta_text_x_coordinates = ticks_to_plot\n",
+    "            delta_text_x_coordinates_default = True\n",
+    "            delta_text_kwargs.pop('x_coordinates')\n",
+    "\n",
+    "\n",
+    "        if delta_text_y_coordinates is not None:\n",
+    "            if not isinstance(delta_text_y_coordinates, list):\n",
+    "                raise TypeError(\"delta_text_kwargs['y_coordinates'] must be a list of y-coordinates.\")\n",
+    "            if len(delta_text_y_coordinates) != len(ticks_to_plot):\n",
+    "                raise ValueError(\"delta_text_kwargs['y_coordinates'] must have the same length as the number of ticks to plot.\")\n",
+    "            delta_text_kwargs.pop('y_coordinates')\n",
+    "        else:\n",
+    "            delta_text_y_coordinates = Delta_Values\n",
+    "            delta_text_kwargs.pop('y_coordinates')\n",
+    "\n",
+    "        for x,y,t,tick in zip(delta_text_x_coordinates, delta_text_y_coordinates,Delta_Values,ticks_to_plot):\n",
+    "            Delta_Text = '+'+'{0:.2f}'.format(t) if t > 0 else '{0:.2f}'.format(t)\n",
+    "            X_Adjust = 0 if not delta_text_x_coordinates_default else 0.53 if delta_text_x_location == 'right' else -0.35\n",
+    "            contrast_axes.text(x+X_Adjust, y, Delta_Text, color=delta_text_colors[tick],**delta_text_kwargs)\n",
+    "\n",
+    "    ################################################### Delta numbers WIP END\n",
+    "\n",
+    "\n",
     "    # Make sure no stray ticks appear!\n",
     "    rawdata_axes.xaxis.set_ticks_position(\"bottom\")\n",
     "    rawdata_axes.yaxis.set_ticks_position(\"left\")\n",
@@ -1717,10 +1772,6 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
-  },
-  "language_info": {
-   "name": "python",
-   "version": "3.11.8"
   }
  },
  "nbformat": 4,