enh: Small improvements to the Spread (#6883)

Author: hoxbro

examples/reference/elements/matplotlib/Spread.ipynb

@@ -9,7 +9,7 @@
     "  <dt>Title</dt> <dd> Spread Element</dd>\n",
     "  <dt>Dependencies</dt> <dd>Matplotlib</dd>\n",
     "  <dt>Backends</dt>\n",
-    "    <dd><a href='./Spread.ipynb'>Bokeh</a></dd>\n",
+    "    <dd><a href='../bokeh/Spread.ipynb'>Bokeh</a></dd>\n",
     "    <dd><a href='../matplotlib/Spread.ipynb'>Matplotlib</a></dd>\n",
     "    <dd><a href='../plotly/Spread.ipynb'>Plotly</a></dd>\n",
     "</dl>\n",

examples/reference/elements/plotly/Spread.ipynb

@@ -8,7 +8,10 @@
     "<dl class=\"dl-horizontal\">\n",
     "  <dt>Title</dt> <dd> Spread Element</dd>\n",
     "  <dt>Dependencies</dt> <dd>Plotly</dd>\n",
-    "  <dt>Backends</dt> <dd><a href='./Spread.ipynb'>Bokeh</a></dd> <dd><a href='../matplotlib/Spread.ipynb'>Matplotlib</a></dd> <dd><a href='../plotly/Spread.ipynb'>Plotly</a></dd>\n",
+    "  <dt>Backends</dt>\n",
+    "    <dd><a href='../bokeh/Spread.ipynb'>Bokeh</a></dd>\n",
+    "    <dd><a href='../matplotlib/Spread.ipynb'>Matplotlib</a></dd>\n",
+    "    <dd><a href='../plotly/Spread.ipynb'>Plotly</a></dd>\n",
     "</dl>\n",
     "</div>"
    ]

holoviews/plotting/bokeh/chart.py

@@ -811,13 +811,19 @@ class SpreadPlot(ElementPlot):
     _plot_methods = dict(single="patch")
     _stream_data = False  # Plot does not support streaming data
 
+    @staticmethod
+    def _create_nan(data):
+        if dtype_kind(data) in "mM":
+            return np.array(["nat"], dtype=data.dtype)
+        else:
+            return np.array([np.nan])
+
     def _split_area(self, xs, lower, upper):
         """Splits area plots at nans and returns x- and y-coordinates for
         each area separated by nans.
 
         """
-        xnan = np.array([np.datetime64("nat") if dtype_kind(xs) == "M" else np.nan])
-        ynan = np.array([np.datetime64("nat") if dtype_kind(lower) == "M" else np.nan])
+        xnan, ynan = self._create_nan(xs), self._create_nan(lower)
         split = np.where(~isfinite(xs) | ~isfinite(lower) | ~isfinite(upper))[0]
         xvals = np.split(xs, split)
         lower = np.split(lower, split)

holoviews/tests/plotting/bokeh/test_spreadplot.py

@@ -4,7 +4,6 @@
 
 import holoviews as hv
 from holoviews.streams import Buffer
-from holoviews.testing import assert_data_equal
 
 from .test_plot import TestBokehPlot, bokeh_renderer
 
@@ -16,8 +15,12 @@ def test_spread_stream_data(self):
         plot = bokeh_renderer.get_plot(dmap)
         buffer.send({"y": [1, 2, 1, 4], "yerror": [0.5, 0.2, 0.1, 0.5], "x": [0, 1, 2, 3]})
         cds = plot.handles["cds"]
-        assert_data_equal(cds.data["x"], np.array([0.0, 1.0, 2.0, 3.0, 3.0, 2.0, 1.0, 0.0]))
-        assert_data_equal(cds.data["y"], np.array([0.5, 1.8, 0.9, 3.5, 4.5, 1.1, 2.2, 1.5]))
+        np.testing.assert_array_equal(
+            cds.data["x"], np.array([0.0, 1.0, 2.0, 3.0, 3.0, 2.0, 1.0, 0.0])
+        )
+        np.testing.assert_array_equal(
+            cds.data["y"], np.array([0.5, 1.8, 0.9, 3.5, 4.5, 1.1, 2.2, 1.5])
+        )
 
     def test_spread_with_nans(self):
         spread = hv.Spread(
@@ -34,11 +37,11 @@ def test_spread_with_nans(self):
         )
         plot = bokeh_renderer.get_plot(spread)
         cds = plot.handles["cds"]
-        assert_data_equal(
+        np.testing.assert_array_equal(
             cds.data["x"],
             np.array([0.0, 1.0, 2.0, 2.0, 1.0, 0.0, np.nan, 4.0, 5.0, 6.0, 6.0, 5.0, 4.0]),
         )
-        assert_data_equal(
+        np.testing.assert_array_equal(
             cds.data["y"],
             np.array([0.0, 0.0, 0.0, 3.0, 2.0, 1.0, np.nan, 0.0, 0.0, 0.0, 7.0, 6.0, 5.0]),
         )
@@ -111,3 +114,61 @@ def test_spread_padding_logy(self):
         assert x_range.end == 3.2
         assert y_range.start == 0.41158562699652224
         assert y_range.end == 4.2518491541367327
+
+    def test_spread_datetime_x(self):
+        dates = np.array(["2020-01-01", "2020-01-02", "2020-01-03"], dtype="datetime64[ns]")
+        spread = hv.Spread((dates, [1.0, 2.0, 3.0], [0.5, 0.5, 0.5]))
+        plot = bokeh_renderer.get_plot(spread)
+        cds = plot.handles["cds"]
+        expected_x = np.array(
+            ["2020-01-01", "2020-01-02", "2020-01-03", "2020-01-03", "2020-01-02", "2020-01-01"],
+            dtype="datetime64[ns]",
+        )
+        expected_y = np.array([0.5, 1.5, 2.5, 3.5, 2.5, 1.5])
+        np.testing.assert_array_equal(cds.data["x"], expected_x)
+        np.testing.assert_array_equal(cds.data["y"], expected_y)
+
+    def test_spread_datetime_x_with_nat(self):
+        dates = np.array(
+            ["2020-01-01", "2020-01-02", "NaT", "2020-01-04", "2020-01-05"], dtype="datetime64[ns]"
+        )
+        spread = hv.Spread((dates, [1.0, 2.0, np.nan, 4.0, 5.0], [0.5, 0.5, np.nan, 0.5, 0.5]))
+        plot = bokeh_renderer.get_plot(spread)
+        cds = plot.handles["cds"]
+        expected_x = np.array(
+            [
+                "2020-01-01",
+                "2020-01-02",
+                "2020-01-02",
+                "2020-01-01",
+                "NaT",
+                "2020-01-04",
+                "2020-01-05",
+                "2020-01-05",
+                "2020-01-04",
+            ],
+            dtype="datetime64[ns]",
+        )
+        expected_y = np.array([0.5, 1.5, 2.5, 1.5, np.nan, 3.5, 4.5, 5.5, 4.5])
+        np.testing.assert_array_equal(cds.data["x"], expected_x)
+        np.testing.assert_array_equal(cds.data["y"], expected_y)
+
+    def test_spread_timedelta_x(self):
+        tds = np.array([0, 1, 2], dtype="timedelta64[D]")
+        spread = hv.Spread((tds, [1.0, 2.0, 3.0], [0.5, 0.5, 0.5]))
+        plot = bokeh_renderer.get_plot(spread)
+        cds = plot.handles["cds"]
+        expected_x = np.array([0, 1, 2, 2, 1, 0], dtype="timedelta64[D]")
+        expected_y = np.array([0.5, 1.5, 2.5, 3.5, 2.5, 1.5])
+        np.testing.assert_array_equal(cds.data["x"], expected_x)
+        np.testing.assert_array_equal(cds.data["y"], expected_y)
+
+    def test_spread_timedelta_x_with_nat(self):
+        tds = np.array([0, 1, "NaT", 3, 4], dtype="timedelta64[D]")
+        spread = hv.Spread((tds, [1.0, 2.0, np.nan, 4.0, 5.0], [0.5, 0.5, np.nan, 0.5, 0.5]))
+        plot = bokeh_renderer.get_plot(spread)
+        cds = plot.handles["cds"]
+        expected_x = np.array([0, 1, 1, 0, "NaT", 3, 4, 4, 3], dtype="timedelta64[D]")
+        expected_y = np.array([0.5, 1.5, 2.5, 1.5, np.nan, 3.5, 4.5, 5.5, 4.5])
+        np.testing.assert_array_equal(cds.data["x"], expected_x)
+        np.testing.assert_array_equal(cds.data["y"], expected_y)