mini improvements

Author: sborms

cobra/evaluation/plotting_utils.py

@@ -43,7 +43,7 @@ def plot_univariate_predictor_quality(df_metric: pd.DataFrame,
         fig, ax = plt.subplots(figsize=dim)
 
         ax = sns.barplot(x=metric, y="predictor", hue="split", data=df)
-        ax.set_title("Univariate Quality of Predictors")
+        ax.set_title("Univariate predictor quality", fontsize=20)
 
         # Set pretty axis
         sns.despine(ax=ax, right=True)
@@ -59,7 +59,7 @@ def plot_univariate_predictor_quality(df_metric: pd.DataFrame,
 def plot_correlation_matrix(df_corr: pd.DataFrame,
                             dim: tuple=(12, 8),
                             path: str=None):
-    """Plot correlation matrix amongst the predictors.
+    """Plot correlation matrix of the predictors.
 
     Parameters
     ----------
@@ -72,7 +72,7 @@ def plot_correlation_matrix(df_corr: pd.DataFrame,
     """
     fig, ax = plt.subplots(figsize=dim)
     ax = sns.heatmap(df_corr, cmap='Blues')
-    ax.set_title('Correlation Matrix')
+    ax.set_title("Correlation matrix", fontsize=20)
 
     if path is not None:
         plt.savefig(path, format="png", dpi=300, bbox_inches="tight")
@@ -166,7 +166,7 @@ def plot_variable_importance(df_variable_importance: pd.DataFrame,
     Parameters
     ----------
     df_variable_importance : pd.DataFrame
-        DataFrame containing columns predictor and importance.
+        DataFrame containing columns "predictor" and "importance".
     title : str, optional
         Title of the plot.
     dim : tuple, optional
@@ -180,9 +180,9 @@ def plot_variable_importance(df_variable_importance: pd.DataFrame,
                          data=df_variable_importance,
                          color="cornflowerblue")
         if title:
-            ax.set_title(title)
+            ax.set_title(title, fontsize=20)
         else:
-            ax.set_title("Variable importance")
+            ax.set_title("Variable importance", fontsize=20)
 
         # Set Axis - make them pretty
         sns.despine(ax=ax, right=True)