Merge pull request #3014 from plotly/pre_distfuncs

Extra tests, bugfix and finish histnorm labelling

Author: nicolaskruchten

packages/python/plotly/plotly/express/_core.py

@@ -147,19 +147,36 @@ def _is_continuous(df, col_name):
 
 
 def get_decorated_label(args, column, role):
-    label = get_label(args, column)
+    original_label = label = get_label(args, column)
     if "histfunc" in args and (
         (role == "z")
         or (role == "x" and "orientation" in args and args["orientation"] == "h")
         or (role == "y" and "orientation" in args and args["orientation"] == "v")
     ):
-        if label:
-            label = "%s of %s" % (args["histfunc"] or "count", label)
+        histfunc = args["histfunc"] or "count"
+        if histfunc != "count":
+            label = "%s of %s" % (histfunc, label)
         else:
             label = "count"
 
         if "histnorm" in args and args["histnorm"] is not None:
-            label = "%s of %s" % (args["histnorm"], label)
+            if label == "count":
+                label = args["histnorm"]
+            else:
+                histnorm = args["histnorm"]
+                if histfunc == "sum":
+                    if histnorm == "probability":
+                        label = "%s of %s" % ("fraction", label)
+                    elif histnorm == "percent":
+                        label = "%s of %s" % (histnorm, label)
+                    else:
+                        label = "%s weighted by %s" % (histnorm, original_label)
+                elif histnorm == "probability":
+                    label = "%s of sum of %s" % ("fraction", label)
+                elif histnorm == "percent":
+                    label = "%s of sum of %s" % ("percent", label)
+                else:
+                    label = "%s of %s" % (histnorm, label)
 
         if "barnorm" in args and args["barnorm"] is not None:
             label = "%s (normalized as %s)" % (label, args["barnorm"])
@@ -924,13 +941,6 @@ def apply_default_cascade(args):
                 "longdashdot",
             ]
 
-    # If both marginals and faceting are specified, faceting wins
-    if args.get("facet_col", None) is not None and args.get("marginal_y", None):
-        args["marginal_y"] = None
-
-    if args.get("facet_row", None) is not None and args.get("marginal_x", None):
-        args["marginal_x"] = None
-
 
 def _check_name_not_reserved(field_name, reserved_names):
     if field_name not in reserved_names:
@@ -1765,6 +1775,14 @@ def infer_config(args, constructor, trace_patch, layout_patch):
         args[position] = args["marginal"]
         args[other_position] = None
 
+    # If both marginals and faceting are specified, faceting wins
+    if args.get("facet_col", None) is not None and args.get("marginal_y", None):
+        args["marginal_y"] = None
+
+    if args.get("facet_row", None) is not None and args.get("marginal_x", None):
+        args["marginal_x"] = None
+
+    # facet_col_wrap only works if no marginals or row faceting is used
     if (
         args.get("marginal_x", None) is not None
         or args.get("marginal_y", None) is not None

packages/python/plotly/plotly/tests/test_core/test_px/test_facets.py

@@ -47,6 +47,53 @@ def test_facets():
     assert fig.layout.yaxis4.domain[0] - fig.layout.yaxis.domain[1] == approx(0.08)
 
 
+def test_facets_with_marginals():
+    df = px.data.tips()
+
+    fig = px.histogram(df, x="total_bill", facet_col="sex", marginal="rug")
+    assert len(fig.data) == 4
+    fig = px.histogram(df, x="total_bill", facet_row="sex", marginal="rug")
+    assert len(fig.data) == 2
+
+    fig = px.histogram(df, y="total_bill", facet_col="sex", marginal="rug")
+    assert len(fig.data) == 2
+    fig = px.histogram(df, y="total_bill", facet_row="sex", marginal="rug")
+    assert len(fig.data) == 4
+
+    fig = px.scatter(df, x="total_bill", y="tip", facet_col="sex", marginal_x="rug")
+    assert len(fig.data) == 4
+    fig = px.scatter(
+        df, x="total_bill", y="tip", facet_col="day", facet_col_wrap=2, marginal_x="rug"
+    )
+    assert len(fig.data) == 8  # ignore the wrap when marginal is used
+    fig = px.scatter(df, x="total_bill", y="tip", facet_col="sex", marginal_y="rug")
+    assert len(fig.data) == 2  # ignore the marginal in the facet direction
+
+    fig = px.scatter(df, x="total_bill", y="tip", facet_row="sex", marginal_x="rug")
+    assert len(fig.data) == 2  # ignore the marginal in the facet direction
+    fig = px.scatter(df, x="total_bill", y="tip", facet_row="sex", marginal_y="rug")
+    assert len(fig.data) == 4
+
+    fig = px.scatter(
+        df, x="total_bill", y="tip", facet_row="sex", marginal_y="rug", marginal_x="rug"
+    )
+    assert len(fig.data) == 4  # ignore the marginal in the facet direction
+    fig = px.scatter(
+        df, x="total_bill", y="tip", facet_col="sex", marginal_y="rug", marginal_x="rug"
+    )
+    assert len(fig.data) == 4  # ignore the marginal in the facet direction
+    fig = px.scatter(
+        df,
+        x="total_bill",
+        y="tip",
+        facet_row="sex",
+        facet_col="sex",
+        marginal_y="rug",
+        marginal_x="rug",
+    )
+    assert len(fig.data) == 2  # ignore all marginals
+
+
 @pytest.fixture
 def bad_facet_spacing_df():
     NROWS = 101

packages/python/plotly/plotly/tests/test_core/test_px/test_marginals.py

@@ -0,0 +1,26 @@
+import plotly.express as px
+import pytest
+
+
+@pytest.mark.parametrize("px_fn", [px.scatter, px.density_heatmap, px.density_contour])
+@pytest.mark.parametrize("marginal_x", [None, "histogram", "box", "violin"])
+@pytest.mark.parametrize("marginal_y", [None, "rug"])
+def test_xy_marginals(px_fn, marginal_x, marginal_y):
+    df = px.data.tips()
+
+    fig = px_fn(
+        df, x="total_bill", y="tip", marginal_x=marginal_x, marginal_y=marginal_y
+    )
+    assert len(fig.data) == 1 + (marginal_x is not None) + (marginal_y is not None)
+
+
+@pytest.mark.parametrize("px_fn", [px.histogram])
+@pytest.mark.parametrize("marginal", [None, "rug", "histogram", "box", "violin"])
+@pytest.mark.parametrize("orientation", ["h", "v"])
+def test_single_marginals(px_fn, marginal, orientation):
+    df = px.data.tips()
+
+    fig = px_fn(
+        df, x="total_bill", y="total_bill", marginal=marginal, orientation=orientation
+    )
+    assert len(fig.data) == 1 + (marginal is not None)

packages/python/plotly/plotly/tests/test_core/test_px/test_px_functions.py

@@ -379,18 +379,73 @@ def test_parcats_dimensions_max():
     assert [d.label for d in fig.data[0].dimensions] == ["sex", "smoker", "day", "size"]
 
 
-def test_histfunc_hoverlabels():
+@pytest.mark.parametrize("histfunc,y", [(None, None), ("count", "tip")])
+def test_histfunc_hoverlabels_univariate(histfunc, y):
+    def check_label(label, fig):
+        assert fig.layout.yaxis.title.text == label
+        assert label + "=" in fig.data[0].hovertemplate
+
     df = px.data.tips()
-    fig = px.histogram(df, x="total_bill")
-    label = "count"
-    assert fig.layout.yaxis.title.text == label
-    assert label + "=" in fig.data[0].hovertemplate
 
-    fig = px.histogram(df, x="total_bill", y="tip")
-    label = "sum of tip"
-    assert fig.layout.yaxis.title.text == label
-    assert label + "=" in fig.data[0].hovertemplate
+    # base case, just "count" (note count(tip) is same as count())
+    fig = px.histogram(df, x="total_bill", y=y, histfunc=histfunc)
+    check_label("count", fig)
+
+    # without y, label is just histnorm
+    for histnorm in ["probability", "percent", "density", "probability density"]:
+        fig = px.histogram(
+            df, x="total_bill", y=y, histfunc=histfunc, histnorm=histnorm
+        )
+        check_label(histnorm, fig)
+
+    for histnorm in ["probability", "percent", "density", "probability density"]:
+        for barnorm in ["percent", "fraction"]:
+            fig = px.histogram(
+                df,
+                x="total_bill",
+                y=y,
+                histfunc=histfunc,
+                histnorm=histnorm,
+                barnorm=barnorm,
+            )
+            check_label("%s (normalized as %s)" % (histnorm, barnorm), fig)
+
+
+def test_histfunc_hoverlabels_bivariate():
+    def check_label(label, fig):
+        assert fig.layout.yaxis.title.text == label
+        assert label + "=" in fig.data[0].hovertemplate
 
+    df = px.data.tips()
+
+    # with y, should be same as forcing histfunc to sum
+    fig = px.histogram(df, x="total_bill", y="tip")
+    check_label("sum of tip", fig)
+
+    # change probability to fraction when histfunc is sum
+    fig = px.histogram(df, x="total_bill", y="tip", histnorm="probability")
+    check_label("fraction of sum of tip", fig)
+
+    # percent is percent
+    fig = px.histogram(df, x="total_bill", y="tip", histnorm="percent")
+    check_label("percent of sum of tip", fig)
+
+    # the other two are "weighted by"
+    for histnorm in ["density", "probability density"]:
+        fig = px.histogram(df, x="total_bill", y="tip", histnorm=histnorm)
+        check_label("%s weighted by tip" % histnorm, fig)
+
+    # check a few "normalized by"
+    for histnorm in ["density", "probability density"]:
+        for barnorm in ["fraction", "percent"]:
+            fig = px.histogram(
+                df, x="total_bill", y="tip", histnorm=histnorm, barnorm=barnorm
+            )
+            check_label(
+                "%s weighted by tip (normalized as %s)" % (histnorm, barnorm), fig
+            )
+
+    # these next two are weird but OK...
     fig = px.histogram(
         df,
         x="total_bill",
@@ -399,9 +454,21 @@ def test_histfunc_hoverlabels():
         histnorm="probability",
         barnorm="percent",
     )
-    label = "probability of min of tip (normalized as percent)"
-    assert fig.layout.yaxis.title.text == label
-    assert label + "=" in fig.data[0].hovertemplate
+    check_label("fraction of sum of min of tip (normalized as percent)", fig)
+
+    fig = px.histogram(
+        df,
+        x="total_bill",
+        y="tip",
+        histfunc="avg",
+        histnorm="percent",
+        barnorm="fraction",
+    )
+    check_label("percent of sum of avg of tip (normalized as fraction)", fig)
+
+    # this next one is basically "never do this" but needs a defined behaviour
+    fig = px.histogram(df, x="total_bill", y="tip", histfunc="max", histnorm="density")
+    check_label("density of max of tip", fig)
 
 
 def test_timeline():