Make figures distinct

app.py

@@ -8,6 +8,7 @@ from pathlib import Path
 import pandas as pd
 import gradio as gr
 import seaborn as sns
+import matplotlib.pyplot as plt
 from datasets import load_dataset
 from scipy.special import expit
 
@@ -104,18 +105,19 @@ class DataPlotter:
         self.df = df
 
     def plot(self):
-        ax = self.draw()
+        fig = plt.figure()
+
+        ax = fig.gca()
+        self.draw(ax)
         ax.grid(visible=True,
                 axis='both',
                 alpha=0.25,
                 linestyle='dotted')
-
-        fig = ax.get_figure()
         fig.tight_layout()
 
         return fig
 
-    def draw(self):
+    def draw(self, ax):
         raise NotImplementedError()
 
 class RankPlotter(DataPlotter):
@@ -132,8 +134,8 @@ class RankPlotter(DataPlotter):
                 .sort_values(by=self._y, ascending=False))
         super().__init__(view)
 
-    def draw(self):
-        ax = self.df.plot.scatter('ability', self._y)
+    def draw(self, ax):
+        self.df.plot.scatter('ability', self._y, ax=ax)
         ax.hlines(self.y,
                   xmin=self.df['lower'],
                   xmax=self.df['upper'],
@@ -141,15 +143,13 @@ class RankPlotter(DataPlotter):
         ax.set_ylabel('')
         ax.set_yticks(self.y, self.df['model'])
 
-        return ax
-
 class ComparisonPlotter(DataPlotter):
     def __init__(self, df, model_1, model_2, ci=0.95):
         super().__init__(compare(df, model_1, model_2))
         self.interval = hdi(self.df, ci)
 
-    def draw(self):
-        ax = sns.ecdfplot(self.df)
+    def draw(self, ax):
+        sns.ecdfplot(self.df, ax=ax)
 
         (_, color, *_) = sns.color_palette()
         ax.axvline(x=self.df.median(),
@@ -161,8 +161,6 @@ class ComparisonPlotter(DataPlotter):
                    color=color)
         ax.set_xlabel('Pr(M$_{1}$ \u003E M$_{2}$)')
 
-        return ax
-
 def cplot(df, ci=0.95):
     def _plot(model_1, model_2):
         cp = ComparisonPlotter(df, model_1, model_2, ci)

requirements.txt

@@ -1,5 +1,6 @@
 datasets
 gradio
+matplotlib
 pandas
 scipy
 seaborn