Reorganisation into wpandas and lpandas

README.rst

@@ -2,7 +2,7 @@
 anesthetic: nested sampling post-processing
 ===========================================
 :Authors: Will Handley and Lukas Hergt
-:Version: 2.0.0-beta.27
+:Version: 2.0.0-beta.28
 :Homepage: https://github.com/handley-lab/anesthetic
 :Documentation: http://anesthetic.readthedocs.io/
 
@@ -130,8 +130,12 @@ and view the documentation by opening ``docs/build/html/index.html`` in a browse
 
 .. code:: bash
 
+    sphinx-apidoc -fM -t docs/templates/ -o docs/source/ wpandas/
+    sphinx-apidoc -fM -t docs/templates/ -o docs/source/ lpandas/
     sphinx-apidoc -fM -t docs/templates/ -o docs/source/ anesthetic/
 
+and modify/revert ``docs/source/modules.rst`` accordingly with any new modules.
+
 Citation
 --------
 

anesthetic/__init__.py

@@ -2,45 +2,12 @@
 import anesthetic.samples
 import anesthetic.plot
 import anesthetic.read.chain
+import anesthetic._version
 
-import pandas
-import pandas.plotting._core
-import pandas.plotting._misc
-from anesthetic._format import _DataFrameFormatter
-from anesthetic._version import __version__  # noqa: F401
-
-
-def _anesthetic_override(_get_plot_backend):
-    """Override the default backend.
-
-    When _get_plot_backend asks for 'matplotlib' it will be directed to
-    'anesthetic.plotting._matplotlib'. This is necessary since any users of
-    :class:`anesthetic.weighted_pandas.WeightedSamples` should not be using the
-    original backend.
-    """
-    def wrapper(backend=None):
-        if backend == 'matplotlib':
-            return _get_plot_backend('anesthetic.plotting._matplotlib')
-        return _get_plot_backend(backend)
-    return wrapper
-
-
-# Override the two places where _get_plot_backend is defined
-pandas.plotting._core._get_plot_backend = \
-        _anesthetic_override(pandas.plotting._core._get_plot_backend)
-pandas.plotting._misc._get_plot_backend = \
-        _anesthetic_override(pandas.plotting._misc._get_plot_backend)
-
-# Set anesthetic.plotting._matplotlib as the actual backend
-pandas.options.plotting.backend = 'anesthetic.plotting._matplotlib'
-
-pandas.io.formats.format.DataFrameFormatter = _DataFrameFormatter
-pandas.options.display.max_colwidth = 14
-
+__version__ = anesthetic._version.__version__
 Samples = anesthetic.samples.Samples
 MCMCSamples = anesthetic.samples.MCMCSamples
 NestedSamples = anesthetic.samples.NestedSamples
 make_2d_axes = anesthetic.plot.make_2d_axes
 make_1d_axes = anesthetic.plot.make_1d_axes
-
 read_chains = anesthetic.read.chain.read_chains

anesthetic/_version.py

@@ -1 +1 @@
-__version__ = '2.0.0b27'
+__version__ = '2.0.0b28'

anesthetic/plot.py

@@ -30,10 +30,11 @@
 from matplotlib.colors import LinearSegmentedColormap
 from matplotlib.transforms import Affine2D
 from anesthetic.utils import nest_level
-from anesthetic.utils import (sample_compression_1d, quantile,
+from anesthetic.utils import (sample_compression_1d,
                               triangular_sample_compression_2d,
                               iso_probability_contours,
                               match_contour_to_contourf)
+from wpandas.utils import quantile
 from anesthetic.boundary import cut_and_normalise_gaussian
 
 

anesthetic/plotting/__init__.py

@@ -3,3 +3,22 @@
 .. autoclass:: anesthetic.plotting.PlotAccessor
 """
 from anesthetic.plotting._core import PlotAccessor # noqa: 401
+from anesthetic.plotting._matplotlib.core import ScatterPlot2d
+from anesthetic.plotting._matplotlib.hist import (
+    Kde1dPlot,
+    FastKde1dPlot,
+    Kde2dPlot,
+    FastKde2dPlot,
+    Hist1dPlot,
+    Hist2dPlot,
+)
+
+import wpandas.plotting._matplotlib
+
+wpandas.plotting._matplotlib.PLOT_CLASSES['hist_1d'] = Hist1dPlot
+wpandas.plotting._matplotlib.PLOT_CLASSES['kde_1d'] = Kde1dPlot
+wpandas.plotting._matplotlib.PLOT_CLASSES['fastkde_1d'] = FastKde1dPlot
+wpandas.plotting._matplotlib.PLOT_CLASSES['hist_2d'] = Hist2dPlot
+wpandas.plotting._matplotlib.PLOT_CLASSES['kde_2d'] = Kde2dPlot
+wpandas.plotting._matplotlib.PLOT_CLASSES['fastkde_2d'] = FastKde2dPlot
+wpandas.plotting._matplotlib.PLOT_CLASSES['scatter_2d'] = ScatterPlot2d

anesthetic/plotting/_matplotlib/__init__.py

@@ -1,63 +1,46 @@
 """anesthetic override of matplotlib backend for weighted samples."""
-from pandas.plotting._matplotlib import (  # noqa: F401
-        PLOT_CLASSES,
-        __name__,
-        __all__,
-        plot,
-        register,
-        deregister
-)
-from anesthetic.plotting._matplotlib.boxplot import (  # noqa: F401
+from wpandas.plotting._matplotlib import (  # noqa: F401
+    PLOT_CLASSES,
+    __name__,
+    __all__,
+    plot,
+    register,
+    deregister,
+    bootstrap_plot,
+    scatter_matrix,
+    andrews_curves,
+    autocorrelation_plot,
+    lag_plot,
+    parallel_coordinates,
+    radviz,
+    table,
     BoxPlot,
     boxplot,
     boxplot_frame,
-)
-from pandas.plotting._matplotlib import boxplot_frame_groupby  # noqa: F401
-from anesthetic.plotting._matplotlib.core import (  # noqa: F401
     AreaPlot,
     BarhPlot,
     BarPlot,
     HexBinPlot,
     LinePlot,
     PiePlot,
     ScatterPlot,
+    boxplot_frame_groupby,
+    KdePlot,
+    HistPlot,
+    hist_frame,
+    hist_series,
+)
+from anesthetic.plotting._matplotlib.core import (  # noqa: F401
     ScatterPlot2d,
 )
 from anesthetic.plotting._matplotlib.hist import (  # noqa: F401
-    KdePlot,
     Kde1dPlot,
     FastKde1dPlot,
     Kde2dPlot,
     FastKde2dPlot,
-    HistPlot,
     Hist1dPlot,
     Hist2dPlot,
-    hist_frame,
-    hist_series,
-)
-from anesthetic.plotting._matplotlib.misc import (  # noqa: F401
-    bootstrap_plot,
-    scatter_matrix,
 )
-from pandas.plotting._matplotlib import (  # noqa: F401
-    andrews_curves,
-    autocorrelation_plot,
-    lag_plot,
-    parallel_coordinates,
-    radviz,
-    table,
-)
-
-PLOT_CLASSES["line"] = LinePlot
-PLOT_CLASSES["bar"] = BarPlot
-PLOT_CLASSES["barh"] = BarhPlot
-PLOT_CLASSES["box"] = BoxPlot
-PLOT_CLASSES["hist"] = HistPlot
-PLOT_CLASSES["kde"] = KdePlot
-PLOT_CLASSES["area"] = AreaPlot
-PLOT_CLASSES["pie"] = PiePlot
-PLOT_CLASSES["scatter"] = ScatterPlot
-PLOT_CLASSES["hexbin"] = HexBinPlot
 
 PLOT_CLASSES['hist_1d'] = Hist1dPlot
 PLOT_CLASSES['kde_1d'] = Kde1dPlot

anesthetic/plotting/_matplotlib/core.py

@@ -1,83 +1,10 @@
 from typing import Literal
-import numpy as np
 from matplotlib import pyplot as plt
-from pandas.core.dtypes.generic import ABCMultiIndex
-import pandas.core.common as com
-from pandas.plotting._matplotlib.core import (ScatterPlot as _ScatterPlot,
-                                              HexBinPlot as _HexBinPlot,
-                                              LinePlot as _LinePlot,
-                                              BarPlot as _BarPlot,
-                                              BarhPlot as _BarhPlot,
-                                              AreaPlot as _AreaPlot,
-                                              PiePlot as _PiePlot,
-                                              MPLPlot, PlanePlot)
+from pandas.plotting._matplotlib.core import PlanePlot
 from pandas.plotting._matplotlib.groupby import create_iter_data_given_by
 from pandas.io.formats.printing import pprint_thing
-from anesthetic.weighted_pandas import _WeightedObject
 from anesthetic.plot import scatter_plot_2d
-
-
-def _get_weights(kwargs, data):
-    if isinstance(data, _WeightedObject):
-        kwargs['weights'] = data.get_weights()
-
-
-class _WeightedMPLPlot(MPLPlot):
-
-    _default_rot = None
-
-    def __init__(self, data, *args, **kwargs):
-        _get_weights(kwargs, data)
-        super().__init__(data, *args, **kwargs)
-
-    def _get_index_name(self):
-        if isinstance(self.data, _WeightedObject):
-            if isinstance(self.data.drop_weights().index, ABCMultiIndex):
-                name = self.data.drop_weights().index.names
-                if com.any_not_none(*name):
-                    name = ",".join([pprint_thing(x) for x in name])
-                else:
-                    name = None
-            else:
-                name = self.data.drop_weights().index.name
-                if name is not None:
-                    name = pprint_thing(name)
-
-            # GH 45145, override the default axis label if one is provided.
-            index_name = self._get_custom_index_name()
-            if index_name is not None:
-                name = pprint_thing(index_name)
-
-            return name
-        else:
-            return super()._get_index_name()
-
-    def _get_xticks(self, convert_period: bool = False):
-        if isinstance(self.data, _WeightedObject):
-            return self.data.drop_weights().index._mpl_repr()
-        else:
-            return super()._get_xticks(convert_period)
-
-
-def _compress_weights(kwargs, data):
-    if isinstance(data, _WeightedObject):
-        return data.compress(kwargs.pop('ncompress', True))
-    else:
-        return data
-
-
-class _CompressedMPLPlot(MPLPlot):
-    def __init__(self, data, *args, **kwargs):
-        data = _compress_weights(kwargs, data)
-        super().__init__(data, *args, **kwargs)
-
-
-class ScatterPlot(_CompressedMPLPlot, _ScatterPlot):
-    # noqa: disable=D101
-    def __init__(self, data, x, y, s=None, c=None, **kwargs) -> None:
-        if isinstance(data, _WeightedObject):
-            kwargs['alpha'] = kwargs.get('alpha', 0.5)
-        super().__init__(data, x, y, s, c, **kwargs)
+from wpandas.plotting._matplotlib.core import _CompressedMPLPlot
 
 
 class _PlanePlot2d(PlanePlot):
@@ -115,50 +42,3 @@ def _kind(self) -> Literal["scatter_2d"]:
     @classmethod
     def _plot(cls, ax, x, y, **kwds):
         return scatter_plot_2d(ax, x, y, **kwds)
-
-
-class HexBinPlot(_HexBinPlot):
-    # noqa: disable=D101
-    def __init__(self, data, x, y, C=None, **kwargs) -> None:
-        if isinstance(data, _WeightedObject):
-            C = '__weights'
-            data[C] = data.get_weights()
-            kwargs['reduce_C_function'] = np.sum
-        super().__init__(data, x, y, C=C, **kwargs)
-
-
-class LinePlot(_LinePlot, _WeightedMPLPlot):
-    # noqa: disable=D101
-    pass
-
-
-class PiePlot(_PiePlot):
-    # noqa: disable=D101
-    def __init__(self, data, kind=None, **kwargs) -> None:
-        if isinstance(data, _WeightedObject):
-            labels = data.drop_weights().index._mpl_repr()
-            kwargs['labels'] = kwargs.get('labels', labels)
-        super().__init__(data, kind=kind, **kwargs)
-
-
-class BarPlot(_BarPlot, _WeightedMPLPlot):
-    # noqa: disable=D101
-    def _decorate_ticks(self, ax, name, ticklabels, start_edge, end_edge):
-        super()._decorate_ticks(ax, name, ticklabels, start_edge, end_edge)
-        if isinstance(self.data, _WeightedObject):
-            if self.xticks is None:
-                ax.set_xticklabels(self._get_xticks())
-
-
-class BarhPlot(_BarhPlot, _WeightedMPLPlot):
-    # noqa: disable=D101
-    def _decorate_ticks(self, ax, name, ticklabels, start_edge, end_edge):
-        super()._decorate_ticks(ax, name, ticklabels, start_edge, end_edge)
-        if isinstance(self.data, _WeightedObject):
-            if self.yticks is None:
-                ax.set_yticklabels(self._get_xticks())
-
-
-class AreaPlot(_AreaPlot, _WeightedMPLPlot):
-    # noqa: disable=D101
-    pass