Update dist_select plots

StatMixedML · Aug 29, 2023 · b22e976 · b22e976
1 parent ec43e67
commit b22e976
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Showing 4 changed files with 12 additions and 31 deletions.
diff --git a/xgboostlss/distributions/distribution_utils.py b/xgboostlss/distributions/distribution_utils.py
@@ -616,12 +616,11 @@ def dist_select(self,
                          }
                     )
                 dist_list.append(fit_df)
-                fit_df = pd.concat(dist_list).sort_values(by=self.loss_fn, ascending=True)
-                fit_df["rank"] = fit_df[self.loss_fn].rank().astype(int)
-                fit_df.set_index(fit_df["rank"], inplace=True)
                 pbar.update(1)
             pbar.set_description(f"Fitting of candidate distributions completed")
-
+            fit_df = pd.concat(dist_list).sort_values(by=self.loss_fn, ascending=True)
+            fit_df["rank"] = fit_df[self.loss_fn].rank().astype(int)
+            fit_df.set_index(fit_df["rank"], inplace=True)
         if plot:
             # Select best distribution
             best_dist = fit_df[fit_df["rank"] == 1].reset_index(drop=True)
@@ -652,7 +651,7 @@ def dist_select(self,
             sns.kdeplot(target.reshape(-1, ), label="Actual")
             sns.kdeplot(dist_samples.reshape(-1, ), label=f"Best-Fit: {best_dist['distribution'].values[0]}")
             plt.legend()
-            plt.title("Actual vs. Best-Fit Density")
+            plt.title("Actual vs. Best-Fit Density", fontweight="bold", fontsize=16)
             plt.show()
 
         fit_df.drop(columns=["rank", "params"], inplace=True)

diff --git a/xgboostlss/distributions/flow_utils.py b/xgboostlss/distributions/flow_utils.py
@@ -676,12 +676,11 @@ def flow_select(self,
                          }
                     )
                 flow_list.append(fit_df)
-                fit_df = pd.concat(flow_list).sort_values(by=flow_sel.loss_fn, ascending=True)
-                fit_df["rank"] = fit_df[flow_sel.loss_fn].rank().astype(int)
-                fit_df.set_index(fit_df["rank"], inplace=True)
                 pbar.update(1)
             pbar.set_description(f"Fitting of candidate normalizing flows completed")
-
+            fit_df = pd.concat(flow_list).sort_values(by=flow_sel.loss_fn, ascending=True)
+            fit_df["rank"] = fit_df[flow_sel.loss_fn].rank().astype(int)
+            fit_df.set_index(fit_df["rank"], inplace=True)
         if plot:
             # Select normalizing flow with the lowest loss
             best_flow = fit_df[fit_df["rank"] == 1].reset_index(drop=True)
@@ -706,7 +705,7 @@ def flow_select(self,
             sns.kdeplot(target.reshape(-1, ), label="Actual")
             sns.kdeplot(flow_samples.reshape(-1, ), label=f"Best-Fit: {best_flow['NormFlow'].values[0]}")
             plt.legend()
-            plt.title("Actual vs. Best-Fit Density")
+            plt.title("Actual vs. Best-Fit Density", fontweight="bold", fontsize=16)
             plt.show()
 
         fit_df.drop(columns=["rank", "params"], inplace=True)

diff --git a/xgboostlss/distributions/mixture_distribution_utils.py b/xgboostlss/distributions/mixture_distribution_utils.py
@@ -672,7 +672,7 @@ def dist_select(self,
             sns.kdeplot(target.reshape(-1,), label="Actual")
             sns.kdeplot(dist_samples.reshape(-1,), label=f"Best-Fit: {best_dist['distribution'].values[0]}")
             plt.legend()
-            plt.title("Actual vs. Best-Fit Density")
+            plt.title("Actual vs. Best-Fit Density", fontweight="bold", fontsize=16)
             plt.show()
 
         fit_df.drop(columns=["rank", "params", "dist_pos", "M"], inplace=True)

diff --git a/xgboostlss/distributions/multivariate_distribution_utils.py b/xgboostlss/distributions/multivariate_distribution_utils.py
@@ -568,12 +568,11 @@ def dist_select(self,
                         }
                     )
                 dist_list.append(fit_df)
-                fit_df = pd.concat(dist_list).sort_values(by=dist_sel.loss_fn, ascending=True)
-                fit_df["rank"] = fit_df[dist_sel.loss_fn].rank().astype(int)
-                fit_df.set_index(fit_df["rank"], inplace=True)
                 pbar.update(1)
             pbar.set_description(f"Fitting of candidate distributions completed")
-
+            fit_df = pd.concat(dist_list).sort_values(by=dist_sel.loss_fn, ascending=True)
+            fit_df["rank"] = fit_df[dist_sel.loss_fn].rank().astype(int)
+            fit_df.set_index(fit_df["rank"], inplace=True)
         if plot:
             warnings.simplefilter(action='ignore', category=UserWarning)
             # Select distribution
@@ -630,22 +629,6 @@ def dist_select(self,
             g.fig.suptitle("Actual vs. Best-Fit Density", weight="bold", fontsize=16)
             g.fig.tight_layout(rect=[0, 0, 1, 0.9])
 
-            # print(
-            #     ggplot(plot_df,
-            #            aes(x="value",
-            #                color="type")) +
-            #     geom_density(alpha=0.5) +
-            #     facet_wrap("target",
-            #                scales="free",
-            #                ncol=ncol) +
-            #     theme_bw(base_size=15) +
-            #     theme(figure_size=figure_size,
-            #           legend_position="right",
-            #           legend_title=element_blank(),
-            #           plot_title=element_text(hjust=0.5)) +
-            #     labs(title=f"Actual vs. Fitted Density")
-            # )
-
         fit_df.drop(columns=["rank", "params"], inplace=True)
 
         return fit_df