Fix legend labels in plot_ppc to reflect prior or posterior. (#1967)

* Fix legend labels in plot_ppc to reflect prior or posterior. Legend labels were not tracking the selected group. In many instances they were hardcoded to "Posterior ...". * Appease black with formatting fix. * Update CHANGELOG
arviz-devs · Jan 20, 2022 · 9d07469 · 9d07469
1 parent a67d81c
commit 9d07469
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -11,6 +11,7 @@
 * Bokeh 3 compatibility. ([1919](https://github.com/arviz-devs/arviz/pull/1919))
 * Remove manual setting of 2d KDE limits ([1939](https://github.com/arviz-devs/arviz/pull/1939))
 * Pin to bokeh<3 version ([1954](https://github.com/arviz-devs/arviz/pull/1954))
+* Fix legend labels in plot_ppc to reflect prior or posterior. ([1967](https://github.com/arviz-devs/arviz/pull/1967))
 
 ### Deprecation
 

diff --git a/arviz/plots/backends/matplotlib/ppcplot.py b/arviz/plots/backends/matplotlib/ppcplot.py
@@ -257,15 +257,15 @@ def plot_ppc(
                     drawstyle=drawstyle,
                     linewidth=linewidth,
                 )
-            ax_i.plot([], color=colors[0], label="Posterior predictive")
+            ax_i.plot([], color=colors[0], label=f"{group.capitalize()} predictive")
             if mean:
                 ax_i.plot(
                     *_empirical_cdf(pp_vals.flatten()),
                     color=colors[2],
                     linestyle="--",
                     linewidth=linewidth * 1.5,
                     drawstyle=drawstyle,
-                    label="Posterior predictive mean",
+                    label=f"{group.capitalize()} predictive mean",
                 )
             ax_i.set_yticks([0, 0.5, 1])
 
@@ -280,7 +280,7 @@ def plot_ppc(
                             "linewidth": linewidth * 1.5,
                             "zorder": 3,
                         },
-                        label="Posterior predictive mean",
+                        label=f"{group.capitalize()} predictive mean",
                         ax=ax_i,
                         legend=legend,
                     )
@@ -294,7 +294,7 @@ def plot_ppc(
                         hist,
                         color=colors[2],
                         linewidth=linewidth * 1.5,
-                        label="Posterior predictive mean",
+                        label=f"{group.capitalize()} predictive mean",
                         zorder=3,
                         linestyle="--",
                         drawstyle="steps-pre",
@@ -350,7 +350,7 @@ def plot_ppc(
                         alpha=alpha,
                     )
 
-            ax_i.plot([], color=colors[0], marker="o", label="Posterior predictive")
+            ax_i.plot([], color=colors[0], marker="o", label=f"{group.capitalize()} predictive")
 
             ax_i.set_yticks([])