Merge 4eb409a into 27da6a3

.github/workflows/build.yml

@@ -89,9 +89,15 @@ jobs:
           eval "$(conda shell.bash hook)"
           conda activate test-environment
           doit develop_install $CHANS_DEV -o unit_tests
+          # See https://github.com/holoviz/holoviews/issues/5167
           conda install $CHANS_DEV "nbconvert<6"
           pip uninstall -y holoviews
           doit pip_on_conda
+      - name: doit env_capture
+        run: |
+          eval "$(conda shell.bash hook)"
+          conda activate test-environment
+          doit env_capture
       - name: pip build
         run: |
           eval "$(conda shell.bash hook)"

holoviews/core/data/__init__.py

@@ -800,7 +800,7 @@ def sample(self, samples=[], bounds=None, closest=True, **kwargs):
         # may be replaced with more general handling
         # see https://github.com/ioam/holoviews/issues/1173
         from ...element import Table, Curve
-        datatype = ['dataframe', 'dictionary', 'dask', 'ibis']
+        datatype = ['dataframe', 'dictionary', 'dask', 'ibis', 'cuDF']
         if len(samples) == 1:
             sel = {kd.name: s for kd, s in zip(self.kdims, samples[0])}
             dims = [kd for kd, v in sel.items() if not np.isscalar(v)]

holoviews/core/data/cudf.py

@@ -247,7 +247,7 @@ def select(cls, dataset, selection_mask=None, **selection):
 
         indexed = cls.indexed(dataset, selection)
         if selection_mask is not None:
-            df = df.loc[selection_mask]
+            df = df.iloc[selection_mask]
         if indexed and len(df) == 1 and len(dataset.vdims) == 1:
             return df[dataset.vdims[0].name].iloc[0]
         return df
@@ -284,7 +284,13 @@ def aggregate(cls, dataset, dimensions, function, **kwargs):
             if not hasattr(reindexed, agg):
                 raise ValueError('%s aggregation is not supported on cudf DataFrame.' % agg)
             agg = getattr(reindexed, agg)()
-            data = dict(((col, [v]) for col, v in zip(agg.index.values_host, agg.to_array())))
+            try:
+                data = dict(((col, [v]) for col, v in zip(agg.index.values_host, agg.to_numpy())))
+            except Exception:
+                # Give FutureWarning: 'The to_array method will be removed in a future cuDF release.
+                # Consider using `to_numpy` instead.'
+                # Seen in cudf=21.12.01
+                data = dict(((col, [v]) for col, v in zip(agg.index.values_host, agg.to_array())))
             df = util.pd.DataFrame(data, columns=list(agg.index.values_host))
 
         dropped = []

holoviews/core/data/ibis.py

@@ -34,8 +34,11 @@ def has_rowid(cls):
 
     @classmethod
     def is_rowid_zero_indexed(cls, data):
-        from ibis.client import find_backends, validate_backends
-        (backend,) = validate_backends(list(find_backends(data)))
+        try:
+            from ibis.client import find_backends, validate_backends
+            (backend,) = validate_backends(list(find_backends(data)))
+        except Exception:
+            backend = data._find_backend()
         return type(backend).__module__ in cls.zero_indexed_backend_modules
 
     @classmethod

holoviews/core/data/pandas.py

@@ -164,7 +164,7 @@ def range(cls, dataset, dimension):
         column = dataset.data[dimension.name]
         if column.dtype.kind == 'O':
             if (not isinstance(dataset.data, pd.DataFrame) or
-                util.LooseVersion(pd.__version__) < '0.17.0'):
+                util.LooseVersion(pd.__version__) < util.LooseVersion('0.17.0')):
                 column = column.sort(inplace=False)
             else:
                 column = column.sort_values()
@@ -187,7 +187,7 @@ def range(cls, dataset, dimension):
 
     @classmethod
     def concat_fn(cls, dataframes, **kwargs):
-        if util.pandas_version >= '0.23.0':
+        if util.pandas_version >= util.LooseVersion('0.23.0'):
             kwargs['sort'] = False
         return pd.concat(dataframes, **kwargs)
 
@@ -292,7 +292,7 @@ def sort(cls, dataset, by=[], reverse=False):
         cols = [dataset.get_dimension(d, strict=True).name for d in by]
 
         if (not isinstance(dataset.data, pd.DataFrame) or
-            util.LooseVersion(pd.__version__) < '0.17.0'):
+            util.LooseVersion(pd.__version__) < util.LooseVersion('0.17.0')):
             return dataset.data.sort(columns=cols, ascending=not reverse)
         return dataset.data.sort_values(by=cols, ascending=not reverse)
 

holoviews/core/data/xarray.py

@@ -217,9 +217,17 @@ def retrieve_unit_and_label(dim):
             # not need to be canonicalized
             if any(len(da.coords[c].shape) > 1 for c in da.coords):
                 continue
-            undeclared = [
-                c for c in da.coords if c not in kdims and len(da[c].shape) == 1 and
-                da[c].shape[0] > 1]
+            undeclared = []
+            for c in da.coords:
+                if c in kdims or len(da[c].shape) != 1 or da[c].shape[0] <= 1:
+                    # Skip if coord is declared, represents irregular coordinates or is constant
+                    continue
+                elif all(d in kdims for d in da[c].dims):
+                    continue # Skip if coord is alias for another dimension
+                elif any(all(d in da[kd.name].dims for d in da[c].dims) for kd in kdims):
+                    # Skip if all the dims on the coord are present on another coord
+                    continue
+                undeclared.append(c)
             if undeclared:
                 raise DataError(
                     'The coordinates on the %r DataArray do not match the '

holoviews/core/util.py

@@ -11,7 +11,7 @@
 
 from collections import defaultdict, OrderedDict
 from contextlib import contextmanager
-from distutils.version import LooseVersion as _LooseVersion
+from packaging.version import Version as LooseVersion
 from functools import partial
 from threading import Thread, Event
 from types import FunctionType
@@ -37,7 +37,6 @@
     RecursionError = RecursionError if sys.version_info.minor > 4 else RuntimeError # noqa
     _getargspec = inspect.getfullargspec
     get_keywords = operator.attrgetter('varkw')
-    LooseVersion = _LooseVersion
 else:
     import __builtin__ as builtins # noqa (compatibility)
     from collections import Iterable # noqa (compatibility)
@@ -50,23 +49,6 @@
     _getargspec = inspect.getargspec
     get_keywords = operator.attrgetter('keywords')
 
-    class LooseVersion(_LooseVersion):
-        """
-        Subclassed to avoid unicode issues in python2
-        """
-
-        def __init__ (self, vstring=None):
-            if isinstance(vstring, unicode):
-                vstring = str(vstring)
-            self.parse(vstring)
-
-        def __cmp__(self, other):
-            if isinstance(other, unicode):
-                other = str(other)
-            if isinstance(other, basestring):
-                other = LooseVersion(other)
-            return cmp(self.version, other.version)
-
 numpy_version = LooseVersion(np.__version__)
 param_version = LooseVersion(param.__version__)
 
@@ -83,13 +65,13 @@ def __cmp__(self, other):
 if pd:
     pandas_version = LooseVersion(pd.__version__)
     try:
-        if pandas_version >= '1.3.0':
+        if pandas_version >= LooseVersion('1.3.0'):
             from pandas.core.dtypes.dtypes import DatetimeTZDtype as DatetimeTZDtypeType
             from pandas.core.dtypes.generic import ABCSeries, ABCIndex as ABCIndexClass
-        elif pandas_version >= '0.24.0':
+        elif pandas_version >= LooseVersion('0.24.0'):
             from pandas.core.dtypes.dtypes import DatetimeTZDtype as DatetimeTZDtypeType
             from pandas.core.dtypes.generic import ABCSeries, ABCIndexClass
-        elif pandas_version > '0.20.0':
+        elif pandas_version > LooseVersion('0.20.0'):
             from pandas.core.dtypes.dtypes import DatetimeTZDtypeType
             from pandas.core.dtypes.generic import ABCSeries, ABCIndexClass
         else:
@@ -100,10 +82,10 @@ def __cmp__(self, other):
         datetime_types = datetime_types + pandas_datetime_types
         timedelta_types = timedelta_types + pandas_timedelta_types
         arraylike_types = arraylike_types + (ABCSeries, ABCIndexClass)
-        if pandas_version > '0.23.0':
+        if pandas_version > LooseVersion('0.23.0'):
             from pandas.core.dtypes.generic import ABCExtensionArray
             arraylike_types = arraylike_types + (ABCExtensionArray,)
-        if pandas_version > '1.0':
+        if pandas_version > LooseVersion('1.0'):
             from pandas.core.arrays.masked import BaseMaskedArray
             masked_types = (BaseMaskedArray,)
     except Exception as e:
@@ -864,7 +846,7 @@ def isnat(val):
     """
     if (isinstance(val, (np.datetime64, np.timedelta64)) or
         (isinstance(val, np.ndarray) and val.dtype.kind == 'M')):
-        if numpy_version >= '1.13':
+        if numpy_version >= LooseVersion('1.13'):
             return np.isnat(val)
         else:
             return val.view('i8') == nat_as_integer
@@ -902,15 +884,15 @@ def isfinite(val):
         elif val.dtype.kind in 'US':
             return ~pd.isna(val) if pd else np.ones_like(val, dtype=bool)
         finite = np.isfinite(val)
-        if pd and pandas_version >= '1.0.0':
+        if pd and pandas_version >= LooseVersion('1.0.0'):
             finite &= ~pd.isna(val)
         return finite
     elif isinstance(val, datetime_types+timedelta_types):
         return not isnat(val)
     elif isinstance(val, (basestring, bytes)):
         return True
     finite = np.isfinite(val)
-    if pd and pandas_version >= '1.0.0':
+    if pd and pandas_version >= LooseVersion('1.0.0'):
         if finite is pd.NA:
             return False
         return finite & (~pd.isna(val))
@@ -1569,17 +1551,27 @@ def is_param_method(obj, has_deps=False):
 def resolve_dependent_value(value):
     """Resolves parameter dependencies on the supplied value
 
-    Resolves parameter values, Parameterized instance methods and
-    parameterized functions with dependencies on the supplied value.
+    Resolves parameter values, Parameterized instance methods,
+    parameterized functions with dependencies on the supplied value,
+    including such parameters embedded in a list, tuple, or dictionary.
 
     Args:
        value: A value which will be resolved
 
     Returns:
-       A new dictionary where any parameter dependencies have been
+       A new value where any parameter dependencies have been
        resolved.
     """
     range_widget = False
+    if isinstance(value, list):
+        value = [resolve_dependent_value(v) for v in value]
+    elif isinstance(value, tuple):
+        value = tuple(resolve_dependent_value(v) for v in value)
+    elif isinstance(value, dict):
+        value = {
+            resolve_dependent_value(k): resolve_dependent_value(v) for k, v in value.items()
+        }
+
     if 'panel' in sys.modules:
         from panel.widgets import RangeSlider, Widget
         range_widget = isinstance(value, RangeSlider)
@@ -1614,7 +1606,7 @@ def resolve_dependent_kwargs(kwargs):
        kwargs (dict): A dictionary of keyword arguments
 
     Returns:
-       A new dictionary with where any parameter dependencies have been
+       A new dictionary where any parameter dependencies have been
        resolved.
     """
     return {k: resolve_dependent_value(v) for k, v in kwargs.items()}
@@ -2294,3 +2286,30 @@ def cast_array_to_int64(array):
             category=FutureWarning,
         )
         return array.astype('int64')
+
+
+def flatten(line):
+    """
+    Flatten an arbitrarily nested sequence.
+
+    Inspired by: pd.core.common.flatten
+
+    Parameters
+    ----------
+    line : sequence
+        The sequence to flatten
+
+    Notes
+    -----
+    This only flattens list, tuple, and dict sequences.
+
+    Returns
+    -------
+    flattened : generator
+    """
+
+    for element in line:
+        if any(isinstance(element, tp) for tp in (list, tuple, dict)):
+            yield from flatten(element)
+        else:
+            yield element

holoviews/operation/datashader.py

@@ -2,7 +2,7 @@
 
 import warnings
 
-from collections import Callable
+from collections.abc import Callable
 from functools import partial
 
 import param
@@ -489,13 +489,13 @@ def _process(self, element, key=None):
 
         if agg.ndim == 2:
             # Replacing x and y coordinates to avoid numerical precision issues
-            eldata = agg if ds_version > '0.5.0' else (xs, ys, agg.data)
+            eldata = agg if ds_version > LooseVersion('0.5.0') else (xs, ys, agg.data)
             return self.p.element_type(eldata, **params)
         else:
             layers = {}
             for c in agg.coords[agg_fn.column].data:
                 cagg = agg.sel(**{agg_fn.column: c})
-                eldata = cagg if ds_version > '0.5.0' else (xs, ys, cagg.data)
+                eldata = cagg if ds_version > LooseVersion('0.5.0') else (xs, ys, cagg.data)
                 layers[c] = self.p.element_type(eldata, **params)
             return NdOverlay(layers, kdims=[data.get_dimension(agg_fn.column)])
 
@@ -791,13 +791,13 @@ def _process(self, element, key=None):
 
         if agg.ndim == 2:
             # Replacing x and y coordinates to avoid numerical precision issues
-            eldata = agg if ds_version > '0.5.0' else (xs, ys, agg.data)
+            eldata = agg if ds_version > LooseVersion('0.5.0') else (xs, ys, agg.data)
             return self.p.element_type(eldata, **params)
         else:
             layers = {}
             for c in agg.coords[agg_fn.column].data:
                 cagg = agg.sel(**{agg_fn.column: c})
-                eldata = cagg if ds_version > '0.5.0' else (xs, ys, cagg.data)
+                eldata = cagg if ds_version > LooseVersion('0.5.0') else (xs, ys, cagg.data)
                 layers[c] = self.p.element_type(eldata, **params)
             return NdOverlay(layers, kdims=[element.get_dimension(agg_fn.column)])
 
@@ -895,7 +895,7 @@ def _get_xarrays(self, element, coords, xtype, ytype):
 
 
     def _process(self, element, key=None):
-        if ds_version <= '0.5.0':
+        if ds_version <= LooseVersion('0.5.0'):
             raise RuntimeError('regrid operation requires datashader>=0.6.0')
 
         # Compute coords, anges and size
@@ -1057,7 +1057,7 @@ def _process(self, element, key=None):
         precompute = self.p.precompute
         if interp == 'linear': interp = 'bilinear'
         wireframe = False
-        if (not (element.vdims or (isinstance(element, TriMesh) and element.nodes.vdims))) and ds_version <= '0.6.9':
+        if (not (element.vdims or (isinstance(element, TriMesh) and element.nodes.vdims))) and ds_version <= LooseVersion('0.6.9'):
             self.p.aggregator = ds.any() if isinstance(agg, ds.any) or agg == 'any' else ds.count()
             return aggregate._process(self, element, key)
         elif ((not interp and (isinstance(agg, (ds.any, ds.count)) or
@@ -1114,11 +1114,11 @@ class quadmesh_rasterize(trimesh_rasterize):
     """
 
     def _precompute(self, element, agg):
-        if ds_version <= '0.7.0':
+        if ds_version <= LooseVersion('0.7.0'):
             return super(quadmesh_rasterize, self)._precompute(element.trimesh(), agg)
 
     def _process(self, element, key=None):
-        if ds_version <= '0.7.0':
+        if ds_version <= LooseVersion('0.7.0'):
             return super(quadmesh_rasterize, self)._process(element, key)
 
         if element.interface.datatype != 'xarray':
@@ -1347,7 +1347,7 @@ def _process(self, element, key=None):
 
         if self.p.clims:
             shade_opts['span'] = self.p.clims
-        elif ds_version > '0.5.0' and cnorm != 'eq_hist':
+        elif ds_version > LooseVersion('0.5.0') and self.p.cnorm != 'eq_hist':
             shade_opts['span'] = element.range(vdim)
 
         params = dict(get_param_values(element), kdims=kdims,
@@ -1602,7 +1602,7 @@ class SpreadingOperation(LinkableOperation):
     to make sparse plots more visible.
     """
 
-    how = param.ObjectSelector(default='source' if ds_version <= '0.11.1' else None,
+    how = param.ObjectSelector(default='source' if ds_version <= LooseVersion('0.11.1') else None,
             objects=[None, 'source', 'over', 'saturate', 'add', 'max', 'min'], doc="""
         The name of the compositing operator to use when combining
         pixels. Default of None uses 'over' operator for RGB elements