Fixed Posterior plot errors with boolean array.

CHANGELOG.md

@@ -42,6 +42,7 @@
 * Fixed xarray related tests. ([1726](https://github.com/arviz-devs/arviz/pull/1726))
 * Fix Bokeh deprecation warnings ([1657](https://github.com/arviz-devs/arviz/pull/1657))
 * Fix credible inteval percentage in legend in `plot_loo_pit` ([1745](https://github.com/arviz-devs/arviz/pull/1745))
+* Fixed plot_posterior with boolean data ([1707](https://github.com/arviz-devs/arviz/pull/1707))
 
 ### Deprecation
 * Deprecated `index_origin` and `order` arguments in `az.summary` ([1201](https://github.com/arviz-devs/arviz/pull/1201))

arviz/plots/backends/bokeh/posteriorplot.py

@@ -286,18 +286,30 @@ def format_axes():
             show=False,
         )
         _, hist, edges = histogram(values, bins="auto")
-    else:
+    elif values.dtype.kind == "i" or (values.dtype.kind == "f" and kind == "hist"):
         if bins is None:
-            if values.dtype.kind == "i":
-                bins = get_bins(values)
-            else:
-                bins = "auto"
+            bins = get_bins(values)
         kwargs.setdefault("align", "left")
         kwargs.setdefault("color", "blue")
         _, hist, edges = histogram(values, bins=bins)
         ax.quad(
             top=hist, bottom=0, left=edges[:-1], right=edges[1:], fill_alpha=0.35, line_alpha=0.35
         )
+    elif values.dtype.kind == "b":
+        if bins is None:
+            bins = "auto"
+        kwargs.setdefault("color", "blue")
+
+        hist = np.array([(~values).sum(), values.sum()])
+        edges = np.array([-0.5, 0.5, 1.5])
+        ax.quad(
+            top=hist, bottom=0, left=edges[:-1], right=edges[1:], fill_alpha=0.35, line_alpha=0.35
+        )
+        hdi_prob = "hide"
+        ax.xaxis.ticker = [0, 1]
+        ax.xaxis.major_label_overrides = {0: "False", 1: "True"}
+    else:
+        raise TypeError("Values must be float, integer or boolean")
 
     format_axes()
     max_data = hist.max()

arviz/plots/backends/matplotlib/posteriorplot.py

@@ -319,18 +319,23 @@ def format_axes():
             rug=False,
             show=False,
         )
-    else:
+    elif values.dtype.kind == "i" or (values.dtype.kind == "f" and kind == "hist"):
         if bins is None:
-            if values.dtype.kind == "i":
-                xmin = values.min()
-                xmax = values.max()
-                bins = get_bins(values)
-                ax.set_xlim(xmin - 0.5, xmax + 0.5)
-            else:
-                bins = "auto"
+            xmin = values.min()
+            xmax = values.max()
+            bins = get_bins(values)
+            ax.set_xlim(xmin - 0.5, xmax + 0.5)
         kwargs.setdefault("align", "left")
         kwargs.setdefault("color", "C0")
         ax.hist(values, bins=bins, alpha=0.35, **kwargs)
+    elif values.dtype.kind == "b":
+        if bins is None:
+            bins = "auto"
+        kwargs.setdefault("color", "C0")
+        ax.bar(["False", "True"], [(~values).sum(), values.sum()], alpha=0.35, **kwargs)
+        hdi_prob = "hide"
+    else:
+        raise TypeError("Values must be float, integer or boolean")
 
     plot_height = ax.get_ylim()[1]
 

arviz/tests/base_tests/test_plots_bokeh.py

@@ -1018,6 +1018,17 @@ def test_plot_posterior_discrete(discrete_model, kwargs):
     assert axes.shape
 
 
+def test_plot_posterior_boolean():
+    data = np.random.choice(a=[False, True], size=(4, 100))
+    axes = plot_posterior(data, backend="bokeh", show=False)
+    assert axes.shape
+
+
+def test_plot_posterior_bad_type():
+    with pytest.raises(TypeError):
+        plot_posterior(np.array(["a", "b", "c"]), backend="bokeh", show=False)
+
+
 def test_plot_posterior_bad(models):
     with pytest.raises(ValueError):
         plot_posterior(models.model_1, backend="bokeh", show=False, rope="bad_value")

arviz/tests/base_tests/test_plots_matplotlib.py

@@ -951,12 +951,26 @@ def test_plot_posterior(models, kwargs):
         assert axes.shape
 
 
+def test_plot_posterior_boolean():
+    data = np.random.choice(a=[False, True], size=(4, 100))
+    axes = plot_posterior(data)
+    assert axes
+    plt.draw()
+    labels = [label.get_text() for label in axes.get_xticklabels()]
+    assert all(item in labels for item in ("True", "False"))
+
+
 @pytest.mark.parametrize("kwargs", [{}, {"point_estimate": "mode"}, {"bins": None, "kind": "hist"}])
 def test_plot_posterior_discrete(discrete_model, kwargs):
     axes = plot_posterior(discrete_model, **kwargs)
     assert axes.shape
 
-
+
+def test_plot_posterior_bad_type(models):
+    with pytest.raises(TypeError):
+        plot_posterior(np.array(["a", "b", "c"]))
+
+
 def test_plot_posterior_bad(models):
     with pytest.raises(ValueError):
         plot_posterior(models.model_1, rope="bad_value")