Address multiple deprecation warnings

CHANGELOG.md

@@ -5,11 +5,12 @@
 ### New features
 
 - Add new example data `rugby_field` and update `rugby` example data ([2322](https://github.com/arviz-devs/arviz/pull/2322))
-
-- Support for `pytree`s and robust to nested dictionaries. (2291)
+- Support for `pytree`s and robust to nested dictionaries. ([2291](https://github.com/arviz-devs/arviz/pull/2291))
 
 
 ### Maintenance and fixes
+- Fix deprecation warnings in multiple dependencies ([2329](https://github.com/arviz-devs/arviz/pull/2329),
+  [2332](https://github.com/arviz-devs/arviz/pull/2332) and [2333](https://github.com/arviz-devs/arviz/pull/2333))
 
 ### Deprecation
 

arviz/__init__.py

@@ -315,7 +315,8 @@ def _log(
 
 def _mpl_cm(name, colorlist):
     cmap = LinearSegmentedColormap.from_list(name, colorlist, N=256)
-    mpl.colormaps.register(cmap, name="cet_" + name)
+    if "cet_" + name not in mpl.colormaps():
+        mpl.colormaps.register(cmap, name="cet_" + name)
 
 
 try:

arviz/data/__init__.py

@@ -1,4 +1,5 @@
 """Code for loading and manipulating data structures."""
+
 from .base import CoordSpec, DimSpec, dict_to_dataset, numpy_to_data_array, pytree_to_dataset
 from .converters import convert_to_dataset, convert_to_inference_data
 from .datasets import clear_data_home, list_datasets, load_arviz_data

arviz/data/base.py

@@ -1,4 +1,5 @@
 """Low level converters usually used by other functions."""
+
 import datetime
 import functools
 import importlib

arviz/data/converters.py

@@ -1,4 +1,5 @@
 """High level conversion functions."""
+
 import numpy as np
 import tree
 import xarray as xr

arviz/data/datasets.py

@@ -1,4 +1,5 @@
 """Base IO code for all datasets. Heavily influenced by scikit-learn's implementation."""
+
 import hashlib
 import itertools
 import json

arviz/data/inference_data.py

@@ -394,8 +394,10 @@ def from_netcdf(
             )
 
         try:
-            with h5netcdf.File(filename, mode="r") if engine == "h5netcdf" else nc.Dataset(
-                filename, mode="r"
+            with (
+                h5netcdf.File(filename, mode="r")
+                if engine == "h5netcdf"
+                else nc.Dataset(filename, mode="r")
             ) as file_handle:
                 if base_group == "/":
                     data = file_handle
@@ -744,11 +746,11 @@ def to_dataframe(
         if len(dfs) > 1:
             for group, df in dfs.items():
                 df.columns = [
-                    col
-                    if col in ("draw", "chain")
-                    else (group, *col)
-                    if isinstance(col, tuple)
-                    else (group, col)
+                    (
+                        col
+                        if col in ("draw", "chain")
+                        else (group, *col) if isinstance(col, tuple) else (group, col)
+                    )
                     for col in df.columns
                 ]
             dfs, *dfs_tail = list(dfs.values())
@@ -1918,8 +1920,7 @@ def concat(
     copy: bool = True,
     inplace: "Literal[True]",
     reset_dim: bool = True,
-) -> None:
-    ...
+) -> None: ...
 
 
 @overload
@@ -1929,8 +1930,7 @@ def concat(
     copy: bool = True,
     inplace: "Literal[False]",
     reset_dim: bool = True,
-) -> InferenceData:
-    ...
+) -> InferenceData: ...
 
 
 @overload
@@ -1941,8 +1941,7 @@ def concat(
     copy: bool = True,
     inplace: "Literal[False]",
     reset_dim: bool = True,
-) -> InferenceData:
-    ...
+) -> InferenceData: ...
 
 
 @overload
@@ -1953,8 +1952,7 @@ def concat(
     copy: bool = True,
     inplace: "Literal[True]",
     reset_dim: bool = True,
-) -> None:
-    ...
+) -> None: ...
 
 
 @overload
@@ -1965,8 +1963,7 @@ def concat(
     copy: bool = True,
     inplace: bool = False,
     reset_dim: bool = True,
-) -> Optional[InferenceData]:
-    ...
+) -> Optional[InferenceData]: ...
 
 
 # pylint: disable=protected-access, inconsistent-return-statements

arviz/data/io_cmdstan.py

@@ -732,9 +732,7 @@ def _process_configuration(comments):
             key = (
                 "warmup_time_seconds"
                 if "(Warm-up)" in comment
-                else "sampling_time_seconds"
-                if "(Sampling)" in comment
-                else "total_time_seconds"
+                else "sampling_time_seconds" if "(Sampling)" in comment else "total_time_seconds"
             )
             results[key] = float(value)
         elif "=" in comment:

arviz/data/io_datatree.py

@@ -1,4 +1,5 @@
 """Conversion between InferenceData and DataTree."""
+
 from .inference_data import InferenceData
 
 

arviz/data/io_dict.py

@@ -1,4 +1,5 @@
 """Dictionary specific conversion code."""
+
 import warnings
 from typing import Optional
 
@@ -59,9 +60,7 @@ def __init__(
         self.coords = (
             coords
             if pred_coords is None
-            else pred_coords
-            if coords is None
-            else {**coords, **pred_coords}
+            else pred_coords if coords is None else {**coords, **pred_coords}
         )
         self.index_origin = index_origin
         self.coords = coords

arviz/data/io_emcee.py

@@ -1,4 +1,5 @@
 """emcee-specific conversion code."""
+
 import warnings
 from collections import OrderedDict
 

arviz/data/io_numpyro.py

@@ -1,4 +1,5 @@
 """NumPyro-specific conversion code."""
+
 import logging
 from typing import Callable, Optional
 

arviz/data/io_pyjags.py

@@ -1,4 +1,5 @@
 """Convert PyJAGS sample dictionaries to ArviZ inference data objects."""
+
 import typing as tp
 from collections import OrderedDict
 from collections.abc import Iterable

arviz/data/io_pyro.py

@@ -1,4 +1,5 @@
 """Pyro-specific conversion code."""
+
 import logging
 from typing import Callable, Optional
 import warnings

arviz/data/utils.py

@@ -1,4 +1,5 @@
 """Data specific utilities."""
+
 import warnings
 import numpy as np
 

arviz/plots/__init__.py

@@ -1,4 +1,5 @@
 """Plotting functions."""
+
 from .autocorrplot import plot_autocorr
 from .bpvplot import plot_bpv
 from .bfplot import plot_bf

arviz/plots/autocorrplot.py

@@ -1,4 +1,5 @@
 """Autocorrelation plot of data."""
+
 from ..data import convert_to_dataset
 from ..labels import BaseLabeller
 from ..sel_utils import xarray_var_iter

arviz/plots/backends/bokeh/autocorrplot.py

@@ -1,4 +1,5 @@
 """Bokeh Autocorrplot."""
+
 import numpy as np
 from bokeh.models import DataRange1d, BoxAnnotation
 from bokeh.models.annotations import Title

arviz/plots/backends/bokeh/bpvplot.py

@@ -1,4 +1,5 @@
 """Bokeh Bayesian p-value Posterior predictive plot."""
+
 import numpy as np
 from bokeh.models import BoxAnnotation
 from bokeh.models.annotations import Title

arviz/plots/backends/bokeh/compareplot.py

@@ -1,4 +1,5 @@
 """Bokeh Compareplot."""
+
 from bokeh.models import Span
 from bokeh.models.annotations import Title, Legend
 

arviz/plots/backends/bokeh/densityplot.py

@@ -1,4 +1,5 @@
 """Bokeh Densityplot."""
+
 from collections import defaultdict
 from itertools import cycle
 

arviz/plots/backends/bokeh/distplot.py

@@ -1,4 +1,5 @@
 """Bokeh Distplot."""
+
 import matplotlib.pyplot as plt
 import numpy as np
 

arviz/plots/backends/bokeh/dotplot.py

@@ -1,4 +1,5 @@
 """Bokeh dotplot."""
+
 import math
 import warnings
 import numpy as np

arviz/plots/backends/bokeh/ecdfplot.py

@@ -1,4 +1,5 @@
 """Bokeh ecdfplot."""
+
 from matplotlib.colors import to_hex
 
 from ...plot_utils import _scale_fig_size

arviz/plots/backends/bokeh/elpdplot.py

@@ -1,4 +1,5 @@
 """Bokeh ELPDPlot."""
+
 import warnings
 
 import bokeh.plotting as bkp

arviz/plots/backends/bokeh/energyplot.py

@@ -1,4 +1,5 @@
 """Bokeh energyplot."""
+
 from itertools import cycle
 
 import numpy as np

arviz/plots/backends/bokeh/hdiplot.py

@@ -1,4 +1,5 @@
 """Bokeh hdiplot."""
+
 import numpy as np
 
 from ...plot_utils import _scale_fig_size, vectorized_to_hex

arviz/plots/backends/bokeh/kdeplot.py

@@ -6,7 +6,7 @@
 import numpy as np
 from bokeh.models import ColumnDataSource
 from bokeh.models.glyphs import Scatter
-from matplotlib.cm import get_cmap
+from matplotlib import colormaps
 from matplotlib.colors import rgb2hex
 from matplotlib.pyplot import rcParams as mpl_rcParams
 
@@ -188,7 +188,7 @@ def plot_kde(
 
             cmap = contourf_kwargs.pop("cmap", "viridis")
             if isinstance(cmap, str):
-                cmap = get_cmap(cmap)
+                cmap = colormaps[cmap]
             if isinstance(cmap, Callable):
                 colors = [rgb2hex(item) for item in cmap(np.linspace(0, 1, len(levels_scaled) + 1))]
             else:
@@ -225,7 +225,7 @@ def plot_kde(
         else:
             cmap = pcolormesh_kwargs.pop("cmap", "viridis")
             if isinstance(cmap, str):
-                cmap = get_cmap(cmap)
+                cmap = colormaps[cmap]
             if isinstance(cmap, Callable):
                 colors = [rgb2hex(item) for item in cmap(np.linspace(0, 1, 256))]
             else:

arviz/plots/backends/bokeh/khatplot.py

@@ -1,4 +1,5 @@
 """Bokeh pareto shape plot."""
+
 from collections.abc import Iterable
 
 from matplotlib import cm

arviz/plots/backends/bokeh/lmplot.py

@@ -1,4 +1,5 @@
 """Bokeh linear regression plot."""
+
 import numpy as np
 from bokeh.models.annotations import Legend
 

arviz/plots/backends/bokeh/loopitplot.py

@@ -1,4 +1,5 @@
 """Bokeh loopitplot."""
+
 import numpy as np
 from bokeh.models import BoxAnnotation
 from matplotlib.colors import hsv_to_rgb, rgb_to_hsv, to_hex, to_rgb

arviz/plots/backends/bokeh/mcseplot.py

@@ -1,4 +1,5 @@
 """Bokeh mcseplot."""
+
 import numpy as np
 from bokeh.models import ColumnDataSource, Span
 from bokeh.models.glyphs import Scatter

arviz/plots/backends/bokeh/pairplot.py

@@ -1,4 +1,5 @@
 """Bokeh pairplot."""
+
 import warnings
 from copy import deepcopy
 from uuid import uuid4

arviz/plots/backends/bokeh/parallelplot.py

@@ -1,4 +1,5 @@
 """Bokeh Parallel coordinates plot."""
+
 import numpy as np
 from bokeh.models import DataRange1d
 from bokeh.models.tickers import FixedTicker

arviz/plots/backends/bokeh/posteriorplot.py

@@ -1,4 +1,5 @@
 """Bokeh Plot posterior densities."""
+
 from numbers import Number
 from typing import Optional
 

arviz/plots/backends/bokeh/ppcplot.py

@@ -1,4 +1,5 @@
 """Bokeh Posterior predictive plot."""
+
 import numpy as np
 from bokeh.models.annotations import Legend
 from bokeh.models.glyphs import Scatter

arviz/plots/backends/bokeh/rankplot.py

@@ -1,4 +1,5 @@
 """Bokeh rankplot."""
+
 import numpy as np
 
 from bokeh.models import Span

arviz/plots/backends/bokeh/separationplot.py

@@ -1,4 +1,5 @@
 """Bokeh separation plot."""
+
 import numpy as np
 
 from ...plot_utils import _scale_fig_size, vectorized_to_hex

arviz/plots/backends/bokeh/traceplot.py

@@ -1,4 +1,5 @@
 """Bokeh Traceplot."""
+
 import warnings
 from collections.abc import Iterable
 from itertools import cycle

arviz/plots/backends/bokeh/violinplot.py

@@ -1,4 +1,5 @@
 """Bokeh Violinplot."""
+
 import numpy as np
 from bokeh.models.annotations import Title
 

arviz/plots/backends/matplotlib/autocorrplot.py

@@ -1,4 +1,5 @@
 """Matplotlib Autocorrplot."""
+
 import matplotlib.pyplot as plt
 import numpy as np
 

arviz/plots/backends/matplotlib/bpvplot.py

@@ -1,4 +1,5 @@
 """Matplotib Bayesian p-value Posterior predictive plot."""
+
 import matplotlib.pyplot as plt
 import numpy as np
 from scipy import stats

arviz/plots/backends/matplotlib/compareplot.py

@@ -1,4 +1,5 @@
 """Matplotlib Compareplot."""
+
 import matplotlib.pyplot as plt
 
 from ...plot_utils import _scale_fig_size

arviz/plots/backends/matplotlib/densityplot.py

@@ -1,4 +1,5 @@
 """Matplotlib Densityplot."""
+
 from itertools import cycle
 
 import matplotlib.pyplot as plt