Merge branch 'master' into jupyterlite_support

.github/workflows/test.yaml

@@ -42,7 +42,6 @@ jobs:
     env:
       HV_REQUIREMENTS: "-o flakes -o tests -o examples_tests"
       MPLBACKEND: "Agg"
-      CHANS_DEV: "-c pyviz/label/dev -c bokeh/label/dev -c conda-forge -c nodefaults"
       GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
     steps:
       - uses: actions/checkout@v3
@@ -55,50 +54,54 @@ jobs:
         run: git fetch --prune --tags --unshallow
       - name: conda setup
         run: |
-          eval "$(conda shell.bash hook)"
           conda update -n base -c defaults conda
-          conda config --prepend channels nodefaults
           conda config --prepend channels conda-forge
           conda config --prepend channels bokeh/label/dev
           conda config --prepend channels pyviz/label/dev
           conda config --remove channels defaults
+          conda config --set channel_priority strict
           conda create -n test-environment python=${{ matrix.python-version }} pyctdev
       - name: doit env_capture
         run: |
-          eval "$(conda shell.bash hook)"
           conda activate test-environment
           doit env_capture
       - name: doit develop_install
+        if: matrix.os != 'macos-latest'
         run: |
-          eval "$(conda shell.bash hook)"
           conda activate test-environment
           conda list
           doit develop_install ${{ env.HV_REQUIREMENTS }}
           python -c "from param import version; print(version.Version.setup_version('.', 'holoviews', archive_commit='$Format:%h$'))"
           echo "-----"
           git describe
+      # Temporary hacked step as on MacOS doit develop_install updated CPython leading to a pyctdev failure
+      - name: doit develop_install
+        if: matrix.os == 'macos-latest'
+        run: |
+          conda activate test-environment
+          conda list
+          doit develop_install ${{ env.HV_REQUIREMENTS }} || echo "Keep going"
+          pip install --no-deps --no-build-isolation -e .
+          python -c "from param import version; print(version.Version.setup_version('.', 'holoviews', archive_commit='$Format:%h$'))"
+          echo "-----"
+          git describe
       - name: doit env_capture
         run: |
-          eval "$(conda shell.bash hook)"
           conda activate test-environment
           doit env_capture
       - name: doit test_flakes
         run: |
-          eval "$(conda shell.bash hook)"
           conda activate test-environment
           doit test_flakes
       - name: doit test_unit
         run: |
-          eval "$(conda shell.bash hook)"
           conda activate test-environment
           doit test_unit
       - name: test examples
         run: |
-          eval "$(conda shell.bash hook)"
           conda activate test-environment
           doit test_examples
       - name: codecov
         run: |
-          eval "$(conda shell.bash hook)"
           conda activate test-environment
           codecov

holoviews/core/data/pandas.py

@@ -1,9 +1,12 @@
+from packaging.version import Version
+
 import numpy as np
 import pandas as pd
+from pandas.api.types import is_numeric_dtype
 
 from ...util._exception import deprecation_warning
 from .interface import Interface, DataError
-from ..dimension import dimension_name
+from ..dimension import dimension_name, Dimension
 from ..element import Element
 from ..dimension import OrderedDict as cyODict
 from ..ndmapping import NdMapping, item_check, sorted_context
@@ -56,7 +59,7 @@ def init(cls, eltype, data, kdims, vdims):
             elif kdims == [] and vdims is None:
                 vdims = list(data.columns[:nvdim if nvdim else None])
 
-            if any(not isinstance(d, str) for d in kdims+vdims):
+            if any(not isinstance(d, (str, Dimension)) for d in kdims+vdims):
                 deprecation_warning(
                     "Having a non-string as a column name in a DataFrame is deprecated "
                     "and will not be supported in Holoviews version 1.16."
@@ -220,6 +223,12 @@ def groupby(cls, dataset, dimensions, container_type, group_type, **kwargs):
         group_kwargs['dataset'] = dataset.dataset
 
         group_by = [d.name for d in index_dims]
+        if len(group_by) == 1 and Version(pd.__version__) >= Version("1.5.0"):
+            # Because of this deprecation warning from pandas 1.5.0:
+            # In a future version of pandas, a length 1 tuple will be returned
+            # when iterating over a groupby with a grouper equal to a list of length 1.
+            # Don't supply a list with a single grouper to avoid this warning.
+            group_by = group_by[0]
         data = [(k, group_type(v, **group_kwargs)) for k, v in
                 dataset.data.groupby(group_by, sort=False)]
         if issubclass(container_type, NdMapping):
@@ -242,8 +251,22 @@ def aggregate(cls, dataset, dimensions, function, **kwargs):
         else:
             fn = function
         if len(dimensions):
+            # The reason to use `numeric_cols` is to prepare for when pandas will not
+            # automatically drop columns that are not numerical for numerical
+            # functions, e.g., `np.mean`.
+            # pandas started warning about this in v1.5.0
+            if fn in [np.size]:
+                # np.size actually works with non-numerical columns
+                numeric_cols = [
+                    c for c in reindexed.columns if c not in cols
+                ]
+            else:
+                numeric_cols = [
+                    c for c, d in zip(reindexed.columns, reindexed.dtypes)
+                    if is_numeric_dtype(d) and c not in cols
+                ]
             grouped = reindexed.groupby(cols, sort=False)
-            df = grouped.aggregate(fn, **kwargs).reset_index()
+            df = grouped[numeric_cols].aggregate(fn, **kwargs).reset_index()
         else:
             agg = reindexed.apply(fn, **kwargs)
             data = dict(((col, [v]) for col, v in zip(agg.index, agg.values)))

holoviews/element/util.py

@@ -302,9 +302,10 @@ def connect_tri_edges_pd(trimesh):
     """
     edges = trimesh.dframe().copy()
     edges.index.name = 'trimesh_edge_index'
-    edges = edges.reset_index()
+    edges = edges.drop("color", errors="ignore", axis=1).reset_index()
     nodes = trimesh.nodes.dframe().copy()
     nodes.index.name = 'node_index'
+    nodes = nodes.drop("color", errors="ignore", axis=1)
     v1, v2, v3 = trimesh.kdims
     x, y, idx = trimesh.nodes.kdims[:3]
 

holoviews/plotting/mpl/chart3d.py

@@ -64,7 +64,12 @@ def _finalize_axis(self, key, **kwargs):
         self.handles['fig'].set_frameon(False)
         axis.grid(self.show_grid)
         axis.view_init(elev=self.elevation, azim=self.azimuth)
-        axis.dist = self.distance
+        try:
+            axis._dist = self.distance
+        except Exception:
+            # axis.dist is deprecated see here:
+            # https://github.com/matplotlib/matplotlib/pull/22084
+            axis.dist = self.distance
 
         if self.xaxis is None:
             axis.w_xaxis.line.set_lw(0.)

holoviews/plotting/mpl/element.py

@@ -544,7 +544,10 @@ def init_artists(self, ax, plot_args, plot_kwargs):
         if 'norm' in plot_kwargs: # vmin/vmax should now be exclusively in norm
              plot_kwargs.pop('vmin', None)
              plot_kwargs.pop('vmax', None)
-        artist = plot_fn(*plot_args, **plot_kwargs)
+        with warnings.catch_warnings():
+            # scatter have a default cmap and with an empty array will emit this warning
+            warnings.filterwarnings('ignore', "No data for colormapping provided via 'c'")
+            artist = plot_fn(*plot_args, **plot_kwargs)
         return {'artist': artist[0] if isinstance(artist, list) and
                 len(artist) == 1 else artist}
 

holoviews/plotting/mpl/graphs.py

@@ -1,3 +1,5 @@
+import warnings
+
 import param
 import numpy as np
 
@@ -168,7 +170,10 @@ def init_artists(self, ax, plot_args, plot_kwargs):
         xs, ys = plot_args['nodes']
         groups = [g for g in self._style_groups if g != 'node']
         node_opts = filter_styles(plot_kwargs, 'node', groups)
-        nodes = ax.scatter(xs, ys, **node_opts)
+        with warnings.catch_warnings():
+            # scatter have a default cmap and with an empty array will emit this warning
+            warnings.filterwarnings('ignore', "No data for colormapping provided via 'c'")
+            nodes = ax.scatter(xs, ys, **node_opts)
 
         return {'nodes': nodes, 'edges': edges}
 

holoviews/plotting/mpl/heatmap.py

@@ -349,7 +349,7 @@ def _pprint(dim_label, vals):
             for i in range(len(xvals))[::-1]:
                 xbin = np.rad2deg(bins_segment[i:i+2])
                 width = ybin[1]-ybin[0]
-                wedge = Wedge((0.5, 0.5), ybin[1], xbin[0], xbin[1], width)
+                wedge = Wedge((0.5, 0.5), ybin[1], xbin[0], xbin[1], width=width)
                 patches.append(wedge)
 
         angles = self._get_markers(segment_ticks, self.xmarks)

holoviews/plotting/plotly/element.py

@@ -520,10 +520,11 @@ def init_layout(self, key, element, ranges, is_geo=False):
                 x_delta = r - l
                 y_delta = t - b
 
-                max_x_zoom = (np.log2(max_delta / x_delta) -
-                              np.log2(mapbox_tile_size / viewport_width))
-                max_y_zoom = (np.log2(max_delta / y_delta) -
-                              np.log2(mapbox_tile_size / viewport_height))
+                with np.errstate(divide="ignore"):
+                    max_x_zoom = (np.log2(max_delta / x_delta) -
+                                np.log2(mapbox_tile_size / viewport_width))
+                    max_y_zoom = (np.log2(max_delta / y_delta) -
+                                np.log2(mapbox_tile_size / viewport_height))
                 mapbox["zoom"] = min(max_x_zoom, max_y_zoom)
             layout["mapbox"] = mapbox
 

holoviews/plotting/util.py

@@ -4,6 +4,7 @@
 import bisect
 
 from collections import defaultdict, namedtuple
+from packaging.version import Version
 
 import numpy as np
 import param
@@ -547,18 +548,27 @@ def mplcmap_to_palette(cmap, ncolors=None, categorical=False):
     """
     Converts a matplotlib colormap to palette of RGB hex strings."
     """
+    import matplotlib as mpl
     from matplotlib.colors import Colormap, ListedColormap
 
     ncolors = ncolors or 256
     if not isinstance(cmap, Colormap):
-        import matplotlib.cm as cm
         # Alias bokeh Category cmaps with mpl tab cmaps
         if cmap.startswith('Category'):
             cmap = cmap.replace('Category', 'tab')
-        try:
-            cmap = cm.get_cmap(cmap)
-        except:
-            cmap = cm.get_cmap(cmap.lower())
+
+        if Version(mpl.__version__) < Version("3.5"):
+            # This will stop working and can be removed
+            # when we do not support python 3.7
+            import matplotlib.cm as cm
+            try:
+                cmap = cm.get_cmap(cmap)
+            except:
+                cmap = cm.get_cmap(cmap.lower())
+        else:
+            from matplotlib import colormaps
+            cmap = colormaps.get(cmap, colormaps.get(cmap.lower()))
+
     if isinstance(cmap, ListedColormap):
         if categorical:
             palette = [rgb2hex(cmap.colors[i%cmap.N]) for i in range(ncolors)]

holoviews/tests/plotting/plotly/test_rgb.py

@@ -1,12 +1,22 @@
 import numpy as np
-
 import PIL.Image
-
 from holoviews.element import RGB, Tiles
+
 import plotly.graph_objs as go
 
 from .test_plot import TestPlotlyPlot, plotly_renderer
 
+try:
+    from PIL.Image import Transpose
+    FLIP_LEFT_RIGHT = Transpose.FLIP_LEFT_RIGHT
+    FLIP_TOP_BOTTOM = Transpose.FLIP_TOP_BOTTOM
+    ROTATE_90 = Transpose.ROTATE_90
+    ROTATE_270 = Transpose.ROTATE_270
+except ImportError:
+    # Gives following deprecation warning:
+    # deprecated and will be removed in Pillow 10 (2023-07-01)
+    from PIL.Image import FLIP_LEFT_RIGHT, FLIP_TOP_BOTTOM, ROTATE_90, ROTATE_270
+
 
 class TestRGBPlot(TestPlotlyPlot):
 
@@ -82,7 +92,7 @@ def test_rgb_invert_xaxis(self):
         pil_img = self.rgb_element_to_pil_img(rgb.data)
 
         # Flip left-to-right since x-axis is inverted
-        pil_img = pil_img.transpose(PIL.Image.FLIP_LEFT_RIGHT)
+        pil_img = pil_img.transpose(FLIP_LEFT_RIGHT)
 
         expected_source = go.layout.Image(source=pil_img).source
 
@@ -122,9 +132,7 @@ def test_rgb_invert_xaxis_and_yaxis(self):
         pil_img = self.rgb_element_to_pil_img(rgb.data)
 
         # Flip left-to-right and top-to-bottom since both x-axis and y-axis are inverted
-        pil_img = (pil_img
-                   .transpose(PIL.Image.FLIP_LEFT_RIGHT)
-                   .transpose(PIL.Image.FLIP_TOP_BOTTOM))
+        pil_img = pil_img.transpose(FLIP_LEFT_RIGHT).transpose(FLIP_TOP_BOTTOM)
 
         expected_source = go.layout.Image(source=pil_img).source
 
@@ -164,9 +172,7 @@ def test_rgb_invert_axes(self):
         pil_img = self.rgb_element_to_pil_img(rgb.data)
 
         # Flip left-to-right and top-to-bottom since both x-axis and y-axis are inverted
-        pil_img = (pil_img
-                   .transpose(PIL.Image.ROTATE_90)
-                   .transpose(PIL.Image.FLIP_LEFT_RIGHT))
+        pil_img = pil_img.transpose(ROTATE_90).transpose(FLIP_LEFT_RIGHT)
 
         expected_source = go.layout.Image(source=pil_img).source
 
@@ -206,9 +212,7 @@ def test_rgb_invert_xaxis_and_yaxis_and_axes(self):
         pil_img = self.rgb_element_to_pil_img(rgb.data)
 
         # Flip left-to-right and top-to-bottom since both x-axis and y-axis are inverted
-        pil_img = (pil_img
-                   .transpose(PIL.Image.ROTATE_270)
-                   .transpose(PIL.Image.FLIP_LEFT_RIGHT))
+        pil_img = pil_img.transpose(ROTATE_270).transpose(FLIP_LEFT_RIGHT)
 
         expected_source = go.layout.Image(source=pil_img).source
 

holoviews/tests/plotting/test_plotutils.py

@@ -476,8 +476,15 @@ def test_mpl_colormap_name_palette(self):
         self.assertEqual(colors, ['#ffffff', '#959595', '#000000'])
 
     def test_mpl_colormap_instance(self):
-        from matplotlib.cm import get_cmap
-        cmap = get_cmap('Greys')
+        try:
+            from matplotlib import colormaps
+            cmap = colormaps.get('Greys')
+        except ImportError:
+            # This will stop working and can be removed
+            # when we do not support python 3.7
+            from matplotlib.cm import get_cmap
+            cmap = get_cmap('Greys')
+
         colors = process_cmap(cmap, 3, provider='matplotlib')
         self.assertEqual(colors, ['#ffffff', '#959595', '#000000'])
 

holoviews/tests/test_annotators.py

@@ -1,7 +1,7 @@
 from holoviews import Overlay
 from holoviews.annotators import annotate, PointAnnotator, PathAnnotator
 from holoviews.element import Points, Path, Table
-from holoviews.element.tiles import Wikipedia, Tiles
+from holoviews.element.tiles import EsriStreet, Tiles
 
 from holoviews.tests.plotting.bokeh.test_plot import TestBokehPlot
 
@@ -25,7 +25,7 @@ def test_compose_annotators(self):
         self.assertEqual(len(tables), 3)
 
     def test_annotate_overlay(self):
-        layout = annotate(Wikipedia() * Points([]), annotations=['Label'])
+        layout = annotate(EsriStreet() * Points([]), annotations=['Label'])
 
         overlay = layout.DynamicMap.I[()]
         tables = layout.Annotator.PointAnnotator[()]

holoviews/tests/util/test_transform.py

@@ -3,6 +3,7 @@
 Unit tests for dim transforms
 """
 import pickle
+import warnings
 
 from collections import OrderedDict
 from unittest import skipIf
@@ -462,7 +463,13 @@ def test_pandas_str_accessor(self):
 
     def test_pandas_chained_methods(self):
         expr = dim('int').df.rolling(1).mean()
-        self.assert_apply(expr, self.linear_ints.rolling(1).mean())
+
+        with warnings.catch_warnings():
+            # The kwargs is {'axis': None} and is already handled by the code.
+            # This context manager can be removed, when it raises an TypeError instead of warning.
+            warnings.simplefilter("ignore", "Passing additional kwargs to Rolling.mean")
+            self.assert_apply(expr, self.linear_ints.rolling(1).mean())
+
 
     @xr_skip
     def test_xarray_namespace_method_repr(self):