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140 lines
4.0 KiB
Python
140 lines
4.0 KiB
Python
# Licensed to Elasticsearch B.V. under one or more contributor
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# license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright
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# ownership. Elasticsearch B.V. licenses this file to you under
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# the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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import numpy as np
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from pandas.core.dtypes.generic import ABCIndexClass
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from pandas.plotting._matplotlib import converter
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from pandas.plotting._matplotlib.tools import _flatten, _set_ticks_props, _subplots
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from eland.utils import try_sort
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def hist_series(
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self,
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by=None,
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ax=None,
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grid=True,
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xlabelsize=None,
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xrot=None,
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ylabelsize=None,
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yrot=None,
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figsize=None,
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bins=10,
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**kwds,
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):
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import matplotlib.pyplot as plt
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if by is None:
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if kwds.get("layout", None) is not None:
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raise ValueError(
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"The 'layout' keyword is not supported when " "'by' is None"
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)
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# hack until the plotting interface is a bit more unified
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fig = kwds.pop(
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"figure", plt.gcf() if plt.get_fignums() else plt.figure(figsize=figsize)
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)
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if figsize is not None and tuple(figsize) != tuple(fig.get_size_inches()):
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fig.set_size_inches(*figsize, forward=True)
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if ax is None:
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ax = fig.gca()
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elif ax.get_figure() != fig:
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raise AssertionError("passed axis not bound to passed figure")
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self_bins, self_weights = self._hist(num_bins=bins)
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# As this is a series, squeeze Series to arrays
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self_bins = self_bins.squeeze()
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self_weights = self_weights.squeeze()
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ax.hist(self_bins[:-1], bins=self_bins, weights=self_weights, **kwds)
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ax.grid(grid)
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axes = np.array([ax])
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_set_ticks_props(
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axes, xlabelsize=xlabelsize, xrot=xrot, ylabelsize=ylabelsize, yrot=yrot
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)
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else:
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raise NotImplementedError("TODO")
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if hasattr(axes, "ndim"):
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if axes.ndim == 1 and len(axes) == 1:
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return axes[0]
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return axes
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def hist_frame(
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data,
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column=None,
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by=None,
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grid=True,
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xlabelsize=None,
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xrot=None,
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ylabelsize=None,
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yrot=None,
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ax=None,
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sharex=False,
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sharey=False,
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figsize=None,
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layout=None,
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bins=10,
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**kwds,
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):
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# Start with empty pandas data frame derived from
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ed_df_bins, ed_df_weights = data._hist(num_bins=bins)
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converter._WARN = False # no warning for pandas plots
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if by is not None:
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raise NotImplementedError("TODO")
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if column is not None:
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if not isinstance(column, (list, np.ndarray, ABCIndexClass)):
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column = [column]
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ed_df_bins = ed_df_bins[column]
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ed_df_weights = ed_df_weights[column]
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naxes = len(ed_df_bins.columns)
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if naxes == 0:
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raise ValueError("hist method requires numerical columns, " "nothing to plot.")
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fig, axes = _subplots(
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naxes=naxes,
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ax=ax,
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squeeze=False,
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sharex=sharex,
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sharey=sharey,
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figsize=figsize,
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layout=layout,
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)
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_axes = _flatten(axes)
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for i, col in enumerate(try_sort(data.columns)):
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ax = _axes[i]
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ax.hist(
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ed_df_bins[col][:-1],
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bins=ed_df_bins[col],
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weights=ed_df_weights[col],
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**kwds,
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)
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ax.set_title(col)
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ax.grid(grid)
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_set_ticks_props(
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axes, xlabelsize=xlabelsize, xrot=xrot, ylabelsize=ylabelsize, yrot=yrot
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)
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fig.subplots_adjust(wspace=0.3, hspace=0.3)
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return axes
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