Hi,
I noticed that a FutureWarning is displayed when creating a DynamicMap from an xarray DataArray (no warning is raised when creating a HoloMap, i.e. dynamic=False).
Here is a minimum working example (the problem initially came up in a more complex context):
import numpy as np
import xarray as xr
import holoviews as hv
nx = 10
ny = 15
nz = 20
xarray = xr.DataArray(
np.ones((nx, ny, nz)),
coords={'x': range(nx), 'y': range(ny), 'z': range(nz)},
name='data'
)
hv.Dataset(xarray).to(hv.Image, dynamic=True)
This creates the following warning:
~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/holoviews/core/util.py:1175: FutureWarning: unique with argument that is not not a Series, Index, ExtensionArray, or np.ndarray is deprecated and will raise in a future version.
return pd.unique(values)
Is this related to some of the HoloViews internals or a problem of my input data?
If it is related to HoloViews internals, is it safe to hide it using warnings.simplefilter?
System and software:
- Linux (Debian 11)
- Python 3.10 (from conda-forge)
- Packages installed from PyPI:
- xarray 2023.9.0
- numpy 1.26.0
- holoviews 1.17.1
- pandas 2.1.1
[Broader context: we include a HoloViews wrapper in a library for finite-difference scalar and vector fields (GitHub - ubermag/discretisedfield: Python package for the analysis and visualisation of finite-difference fields.) that we are working on and would not want our users to see this warning.]
Many thanks,
Martin
Appendix:
Raising an exception for the warning using:
warnings.simplefilter("error")
hv.Dataset(xarray).to(hv.Image, dynamic=True)
produces the following traceback:
---------------------------------------------------------------------------
FutureWarning Traceback (most recent call last)
Cell In[10], line 2
1 warnings.simplefilter("error")
----> 2 hv.Dataset(xarray).to(hv.Image, dynamic=True)
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/holoviews/core/data/__init__.py:144, in DataConversion.__call__(self, new_type, kdims, vdims, groupby, sort, **kwargs)
142 element = new_type(selected, **params)
143 return element.sort() if sort else element
--> 144 group = selected.groupby(groupby, container_type=HoloMap,
145 group_type=new_type, **params)
146 if sort:
147 return group.map(lambda x: x.sort(), [new_type])
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/holoviews/core/data/__init__.py:195, in PipelineMeta.pipelined.<locals>.pipelined_fn(*args, **kwargs)
192 inst._in_method = True
194 try:
--> 195 result = method_fn(*args, **kwargs)
196 if PipelineMeta.disable:
197 return result
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/holoviews/core/data/__init__.py:986, in Dataset.groupby(self, dimensions, container_type, group_type, dynamic, **kwargs)
984 data = data.columns()
985 return group_type(data, **group_kwargs)
--> 986 dynamic_dims = [d.clone(values=list(self.interface.values(self, d.name, False)))
987 for d in dimensions]
988 return DynamicMap(load_subset, kdims=dynamic_dims)
990 return self.interface.groupby(self, dim_names, container_type,
991 group_type, **kwargs)
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/holoviews/core/data/__init__.py:986, in <listcomp>(.0)
984 data = data.columns()
985 return group_type(data, **group_kwargs)
--> 986 dynamic_dims = [d.clone(values=list(self.interface.values(self, d.name, False)))
987 for d in dimensions]
988 return DynamicMap(load_subset, kdims=dynamic_dims)
990 return self.interface.groupby(self, dim_names, container_type,
991 group_type, **kwargs)
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/holoviews/core/dimension.py:331, in Dimension.clone(self, spec, **overrides)
327 self.param.warning(
328 f'Using label as supplied by keyword ({overrides["label"]!r}), '
329 f'ignoring tuple value {spec[1]!r}')
330 spec = (spec[0], overrides['label'])
--> 331 return self.__class__(spec, **{k:v for k,v in settings.items()
332 if k not in ['name', 'label']})
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/holoviews/core/dimension.py:287, in Dimension.__init__(self, spec, **params)
283 self.param.warning("The 'initial' string for dimension values "
284 "is no longer supported.")
285 values = []
--> 287 all_params['values'] = list(util.unique_array(values))
288 super().__init__(**all_params)
289 if self.default is not None:
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/holoviews/core/util.py:1175, in unique_array(arr)
1173 v = pd.Timestamp(v).to_datetime64()
1174 values.append(v)
-> 1175 return pd.unique(values)
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/pandas/core/algorithms.py:401, in unique(values)
307 def unique(values):
308 """
309 Return unique values based on a hash table.
310
(...)
399 array([('a', 'b'), ('b', 'a'), ('a', 'c')], dtype=object)
400 """
--> 401 return unique_with_mask(values)
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/pandas/core/algorithms.py:429, in unique_with_mask(values, mask)
427 def unique_with_mask(values, mask: npt.NDArray[np.bool_] | None = None):
428 """See algorithms.unique for docs. Takes a mask for masked arrays."""
--> 429 values = _ensure_arraylike(values, func_name="unique")
431 if isinstance(values.dtype, ExtensionDtype):
432 # Dispatch to extension dtype's unique.
433 return values.unique()
File ~/miniconda3/envs/ubermagdev310/lib/python3.10/site-packages/pandas/core/algorithms.py:225, in _ensure_arraylike(values, func_name)
221 if not isinstance(values, (ABCIndex, ABCSeries, ABCExtensionArray, np.ndarray)):
222 # GH#52986
223 if func_name != "isin-targets":
224 # Make an exception for the comps argument in isin.
--> 225 warnings.warn(
226 f"{func_name} with argument that is not not a Series, Index, "
227 "ExtensionArray, or np.ndarray is deprecated and will raise in a "
228 "future version.",
229 FutureWarning,
230 stacklevel=find_stack_level(),
231 )
233 inferred = lib.infer_dtype(values, skipna=False)
234 if inferred in ["mixed", "string", "mixed-integer"]:
235 # "mixed-integer" to ensure we do not cast ["ss", 42] to str GH#22160
FutureWarning: unique with argument that is not not a Series, Index, ExtensionArray, or np.ndarray is deprecated and will raise in a future version.