17569144994

Committed 09 Sep 2025 01:39AM UTC coverage: 90.14% (+0.06%) from 90.077%

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morganjwilliams

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Update example for interactive plotting API

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/pyrolite/util/plot/plotly.py

"""
Plotly backend for a pandas-based pyrolite plot accessor.

Todo
-----
* Make margins smaller
* Enable passing labels to markers
* Make plot variant for density plots
"""

import warnings

import matplotlib.colors
import numpy as np
import plotly.graph_objects as go

from ... import geochem
from ...comp.codata import ILR, close
from ...plot.color import process_color
from ..distributions import get_scaler, sample_kde
from ..log import Handle
from ..meta import get_additional_params, subkwargs
from ..pd import _check_components, to_frame

logger = Handle(__name__)


def to_plotly_color(color, alpha=1):
    # note that alpha isn't 255 scaled
    return "rgba" + str(
        tuple([int(i * 255) for i in matplotlib.colors.to_rgb(color)] + [alpha])
    )


class pyroplot_plotly(object):
    def __init__(self, obj):
        """
        Custom dataframe accessor for pyrolite plotting.

        Notes
        -----
            This accessor enables the coexistence of array-based plotting functions and
            methods for pandas objects. This enables some separation of concerns.
        """
        self._validate(obj)
        self._obj = obj

    @staticmethod
    def _validate(obj):
        pass

    def scatter(self, color="black", alpha=1, **kwargs):
        if self._obj.columns.size == 3:
            return self._ternary(color=color, alpha=alpha, **kwargs)
        else:
            layout = dict(width=600, plot_bgcolor="white")
            fig = go.Figure()
            marker = dict(color=to_plotly_color(color, alpha=alpha))
            traces = [
                go.Scatter(
                    x=self._obj.iloc[:, 0],
                    y=self._obj.iloc[:, 1],
                    mode="markers",
                    marker=marker,
                    showlegend=False,
                    text=self._obj.index.map("Sample {}".format),
                )
            ]
            fig.add_traces(traces)
            fig.update_layout(layout)
            fig.update_xaxes(
                linecolor="black", mirror=True, title=self._obj.columns[0]
            )  # todo: add this to layout
            fig.update_yaxes(
                linecolor="black", mirror=True, title=self._obj.columns[1]
            )  # todo: add this to layout
            return fig

    def _ternary(self, color="black", alpha=1, **kwargs):
        layout = dict(
            width=600,
            plot_bgcolor="white",
            ternary={
                **{
                    a: {
                        "title": c,
                        "showgrid": False,
                        "linecolor": "black",
                    }
                    for a, c in zip(["aaxis", "baxis", "caxis"], self._obj.columns)
                },
                "bgcolor": "white",
            },
        )
        layout.update(kwargs)
        marker = {"color": to_plotly_color(color, alpha=alpha)}
        data = {
            "mode": "markers",
            **dict(zip("abc", [self._obj[c] for c in self._obj.columns])),
            "text": self._obj.index.values,
            "marker": marker,
        }
        fig = go.Figure(go.Scatterternary(data))

        fig.update_layout(layout)
        return fig

    def spider(self, color="black", unity_line=True, alpha=1, text=None, **kwargs):
        layout = dict(width=600, plot_bgcolor="white")
        fig = go.Figure()
        line = dict(color=to_plotly_color(color, alpha=alpha))
        # hovertemplate = "%{text}<br><extra></extra>" if (text is not None) else None
        traces = [
            go.Scatter(
                x=self._obj.columns,
                y=row,
                mode="lines+markers",
                line=line,
                showlegend=False,
                hoverinfo="text",
                # hovertemplate =hovertemplate if (text is not None) else None,
                text=None if text is None else text[idx],
                name="Sample {}".format(idx),
            )
            for idx, row in self._obj.iterrows()
        ]
        if unity_line:
            traces += [
                go.Scatter(
                    x=self._obj.columns,
                    y=np.ones(self._obj.columns.size),
                    mode="lines",
                    showlegend=False,
                    name=None,
                    line={"color": "black", "dash": "dot", "width": 0.5},
                )
            ]
        fig.add_traces(traces)
        fig.update_layout(**layout)
        fig.update_yaxes(
            type="log", linecolor="black", mirror=True
        )  # todo: add this to layout
        fig.update_xaxes(linecolor="black", mirror=True)  # todo: add this to layout
        return fig


# class pyroplot_plotly(object):
#     def __init__(self, obj):
#         """
#         Custom dataframe accessor for pyrolite plotting.

#         Notes
#         -----
#             This accessor enables the coexistence of array-based plotting functions and
#             methods for pandas objects. This enables some separation of concerns.
#         """
#         self._validate(obj)
#         self._obj = obj

#     @staticmethod
#     def _validate(obj):
#         pass

#     def heatscatter(
#         self,
#         components: list = None,
#         ax=None,
#         axlabels=True,
#         logx=False,
#         logy=False,
#         **kwargs,
#     ):
#         r"""
#         Heatmapped scatter plots using the pyroplot API. See further parameters
#         for `matplotlib.pyplot.scatter` function below.

#         Parameters
#         ----------
#         components : :class:`list`, :code:`None`
#             Elements or compositional components to plot.
#         ax : :class:`matplotlib.axes.Axes`, :code:`None`
#             The subplot to draw on.
#         axlabels : :class:`bool`, :code:`True`
#             Whether to add x-y axis labels.
#         logx : :class:`bool`, `False`
#             Whether to log-transform x values before the KDE for bivariate plots.
#         logy : :class:`bool`, `False`
#             Whether to log-transform y values before the KDE for bivariate plots.

#         {otherparams}

#         Returns
#         -------
#         :class:`matplotlib.axes.Axes`
#             Axes on which the heatmapped scatterplot is added.

#         """
#         obj = to_frame(self._obj)
#         components = _check_components(obj, components=components)
#         data, samples = (
#             obj.reindex(columns=components).values,
#             obj.reindex(columns=components).values,
#         )
#         kdetfm = [  # log transforms
#             get_scaler([None, np.log][logx], [None, np.log][logy]),
#             lambda x: ILR(close(x)),
#         ][len(components) == 3]
#         zi = sample_kde(
#             data, samples, transform=kdetfm, **subkwargs(kwargs, sample_kde)
#         )
#         kwargs.update({"c": zi})
#         ax = obj.reindex(columns=components).pyroplot.scatter(
#             ax=ax, axlabels=axlabels, **kwargs
#         )
#         return ax

#     def plot(self, components: list = None, ax=None, axlabels=True, **kwargs):
#         r"""
#         Convenience method for line plots using the pyroplot API. See
#         further parameters for `matplotlib.pyplot.scatter` function below.

#         Parameters
#         ----------
#         components : :class:`list`, :code:`None`
#             Elements or compositional components to plot.
#         ax : :class:`matplotlib.axes.Axes`, :code:`None`
#             The subplot to draw on.
#         axlabels : :class:`bool`, :code:`True`
#             Whether to add x-y axis labels.
#         {otherparams}

#         Returns
#         -------
#         :class:`matplotlib.axes.Axes`
#             Axes on which the plot is added.

#         """
#         obj = to_frame(self._obj)
#         components = _check_components(obj, components=components)
#         projection = [None, "ternary"][len(components) == 3]
#         # ax = init_axes(ax=ax, projection=projection, **kwargs)
#         # kw = linekwargs(kwargs)
#         ax.plot(*obj.reindex(columns=components).values.T, **kw)
#         # if color is multi, could update line colors here
#         # if axlabels:
#         #    label_axes(ax, labels=components)

#         ax.tick_params("both")
#         # ax.grid()
#         # ax.set_aspect("equal")
#         return ax

#     def REE(
#         self,
#         index="elements",
#         ax=None,
#         mode="plot",
#         dropPm=True,
#         scatter_kw={},
#         line_kw={},
#         **kwargs,
#     ):
#         """Pass the pandas object to :func:`pyrolite.plot.spider.REE_v_radii`.

#         Parameters
#         ----------
#         ax : :class:`matplotlib.axes.Axes`, :code:`None`
#             The subplot to draw on.
#         index : :class:`str`
#             Whether to plot radii ('radii') on the principal x-axis, or elements
#             ('elements').
#         mode : :class:`str`, :code`["plot", "fill", "binkde", "ckde", "kde", "hist"]`
#             Mode for plot. Plot will produce a line-scatter diagram. Fill will return
#             a filled range. Density will return a conditional density diagram.
#         dropPm : :class:`bool`
#             Whether to exclude the (almost) non-existent element Promethium from the REE
#             list.
#         scatter_kw : :class:`dict`
#             Keyword parameters to be passed to the scatter plotting function.
#         line_kw : :class:`dict`
#             Keyword parameters to be passed to the line plotting function.
#         {otherparams}

#         Returns
#         -------
#         :class:`matplotlib.axes.Axes`
#             Axes on which the REE plot is added.

#         """
#         obj = to_frame(self._obj)
#         ree = [i for i in geochem.ind.REE(dropPm=dropPm) if i in obj.columns]

#         ax = spider.REE_v_radii(
#             obj.reindex(columns=ree).astype(float).values,
#             index=index,
#             ree=ree,
#             mode=mode,
#             ax=ax,
#             scatter_kw=scatter_kw,
#             line_kw=line_kw,
#             **kwargs,
#         )
#         ax.set_ylabel(r"$\mathrm{X / X_{Reference}}$")
#         return ax

#     def scatter(self, components: list = None, ax=None, axlabels=True, **kwargs):
#         r"""
#         Convenience method for scatter plots using the pyroplot API. See
#         further parameters for `matplotlib.pyplot.scatter` function below.

#         Parameters
#         ----------
#         components : :class:`list`, :code:`None`
#             Elements or compositional components to plot.
#         ax : :class:`matplotlib.axes.Axes`, :code:`None`
#             The subplot to draw on.
#         axlabels : :class:`bool`, :code:`True`
#             Whether to add x-y axis labels.
#         {otherparams}

#         Returns
#         -------
#         :class:`matplotlib.axes.Axes`
#             Axes on which the scatterplot is added.

#         """
#         obj = to_frame(self._obj)
#         components = _check_components(obj, components=components)

#         projection = [None, "ternary"][len(components) == 3]
#         # ax = init_axes(ax=ax, projection=projection, **kwargs)
#         size = obj.index.size
#         kw = process_color(size=size, **kwargs)
#         with warnings.catch_warnings():
#             # ternary transform where points add to zero will give an unnecessary
#             # warning; here we supress it
#             warnings.filterwarnings(
#                 "ignore", message="invalid value encountered in divide"
#             )
#             ax.scatter(*obj.reindex(columns=components).values.T, **kw)

#         # if axlabels:
#         #    label_axes(ax, labels=components)

#         ax.tick_params("both")
#         # ax.grid()
#         # ax.set_aspect("equal")
#         return ax

#     def spider(
#         self,
#         components: list = None,
#         indexes: list = None,
#         ax=None,
#         mode="plot",
#         index_order=None,
#         autoscale=True,
#         scatter_kw={},
#         line_kw={},
#         **kwargs,
#     ):
#         r"""
#         Method for spider plots. Convenience access function to
#         :func:`~pyrolite.plot.spider.spider` (see `Other Parameters`, below), where
#         further parameters for relevant `matplotlib` functions are also listed.

#         Parameters
#         ----------
#         components : :class:`list`, `None`
#             Elements or compositional components to plot.
#         indexes :  :class:`list`, `None`
#             Elements or compositional components to plot.
#         ax : :class:`matplotlib.axes.Axes`, :code:`None`
#             The subplot to draw on.
#         index_order
#             Function to order spider plot indexes (e.g. by incompatibility).
#         autoscale : :class:`bool`
#             Whether to autoscale the y-axis limits for standard spider plots.
#         mode : :class:`str`, :code`["plot", "fill", "binkde", "ckde", "kde", "hist"]`
#             Mode for plot. Plot will produce a line-scatter diagram. Fill will return
#             a filled range. Density will return a conditional density diagram.
#         scatter_kw : :class:`dict`
#             Keyword parameters to be passed to the scatter plotting function.
#         line_kw : :class:`dict`
#             Keyword parameters to be passed to the line plotting function.
#         {otherparams}

#         Returns
#         -------
#         :class:`matplotlib.axes.Axes`
#             Axes on which the spider diagram is plotted.

#         Todo
#         ----
#             * Add 'compositional data' filter for default components if None is given

#         """
#         obj = to_frame(self._obj)

#         if components is None:  # default to plotting elemental data
#             components = [
#                 el for el in obj.columns if el in geochem.ind.common_elements()
#             ]

#         assert len(components) != 0

#         if index_order is not None:
#             if isinstance(index_order, str):
#                 try:
#                     index_order = geochem.ind.ordering[index_order]
#                 except KeyError:
#                     msg = (
#                         "Ordering not applied, as parameter '{}' not recognized."
#                         " Select from: {}"
#                     ).format(index_order, ", ".join(list(geochem.ind.ordering.keys())))
#                     logger.warning(msg)
#                 components = index_order(components)
#             else:
#                 components = index_order(components)

#         # ax = init_axes(ax=ax, **kwargs)

#         if hasattr(ax, "_pyrolite_components"):
#             # TODO: handle spider diagrams which have specified components
#             pass

#         ax = spider.spider(
#             obj.reindex(columns=components).astype(float).values,
#             indexes=indexes,
#             ax=ax,
#             mode=mode,
#             autoscale=autoscale,
#             scatter_kw=scatter_kw,
#             line_kw=line_kw,
#             **kwargs,
#         )
#         ax._pyrolite_components = components
#         ax.set_xticklabels(components, rotation=60)
#         return ax

1	"""
2	Plotly backend for a pandas-based pyrolite plot accessor.
3
4	Todo
5	-----
6	* Make margins smaller
7	* Enable passing labels to markers
8	* Make plot variant for density plots
9	"""
10
11	import warnings	×
12
13	import matplotlib.colors	×
14	import numpy as np	×
15	import plotly.graph_objects as go	×
16
17	from ... import geochem	×
18	from ...comp.codata import ILR, close	×
19	from ...plot.color import process_color	×
20	from ..distributions import get_scaler, sample_kde	×
21	from ..log import Handle	×
22	from ..meta import get_additional_params, subkwargs	×
23	from ..pd import _check_components, to_frame	×
24
25	logger = Handle(__name__)	×
26
27
28	def to_plotly_color(color, alpha=1):	×
29	# note that alpha isn't 255 scaled
30	return "rgba" + str(	×
31	tuple([int(i * 255) for i in matplotlib.colors.to_rgb(color)] + [alpha])
32	)
33
34
35	class pyroplot_plotly(object):	×
36	def __init__(self, obj):	×
37	"""
38	Custom dataframe accessor for pyrolite plotting.
39
40	Notes
41	-----
42	This accessor enables the coexistence of array-based plotting functions and
43	methods for pandas objects. This enables some separation of concerns.
44	"""
45	self._validate(obj)	×
46	self._obj = obj	×
47
48	@staticmethod	×
49	def _validate(obj):	×
50	pass	×
51
52	def scatter(self, color="black", alpha=1, **kwargs):	×
NEW 53	if self._obj.columns.size == 3:	×
NEW 54	return self._ternary(color=color, alpha=alpha, **kwargs)	×
55	else:
NEW 56	layout = dict(width=600, plot_bgcolor="white")	×
NEW 57	fig = go.Figure()	×
NEW 58	marker = dict(color=to_plotly_color(color, alpha=alpha))	×
NEW 59	traces = [	×
60	go.Scatter(
61	x=self._obj.iloc[:, 0],
62	y=self._obj.iloc[:, 1],
63	mode="markers",
64	marker=marker,
65	showlegend=False,
66	text=self._obj.index.map("Sample {}".format),
67	)
68	]
NEW 69	fig.add_traces(traces)	×
NEW 70	fig.update_layout(layout)	×
NEW 71	fig.update_xaxes(	×
72	linecolor="black", mirror=True, title=self._obj.columns[0]
73	) # todo: add this to layout
NEW 74	fig.update_yaxes(	×
75	linecolor="black", mirror=True, title=self._obj.columns[1]
76	) # todo: add this to layout
NEW 77	return fig	×
78
NEW 79	def _ternary(self, color="black", alpha=1, **kwargs):	×
UNCOV 80	layout = dict(	×
81	width=600,
82	plot_bgcolor="white",
83	ternary={
84	**{
85	a: {
86	"title": c,
87	"showgrid": False,
88	"linecolor": "black",
89	}
90	for a, c in zip(["aaxis", "baxis", "caxis"], self._obj.columns)
91	},
92	"bgcolor": "white",
93	},
94	)
UNCOV 95	layout.update(kwargs)	×
UNCOV 96	marker = {"color": to_plotly_color(color, alpha=alpha)}	×
UNCOV 97	data = {	×
98	"mode": "markers",
99	**dict(zip("abc", [self._obj[c] for c in self._obj.columns])),
100	"text": self._obj.index.values,
101	"marker": marker,
102	}
UNCOV 103	fig = go.Figure(go.Scatterternary(data))	×
104
UNCOV 105	fig.update_layout(layout)	×
106	return fig	×
107
108	def spider(self, color="black", unity_line=True, alpha=1, text=None, **kwargs):	×
109	layout = dict(width=600, plot_bgcolor="white")	×
UNCOV 110	fig = go.Figure()	×
111	line = dict(color=to_plotly_color(color, alpha=alpha))	×
112	# hovertemplate = "%{text}<br><extra></extra>" if (text is not None) else None
113	traces = [	×
114	go.Scatter(
115	x=self._obj.columns,
116	y=row,
117	mode="lines+markers",
118	line=line,
119	showlegend=False,
120	hoverinfo="text",
121	# hovertemplate =hovertemplate if (text is not None) else None,
122	text=None if text is None else text[idx],
123	name="Sample {}".format(idx),
124	)
125	for idx, row in self._obj.iterrows()
126	]
UNCOV 127	if unity_line:	×
UNCOV 128	traces += [	×
129	go.Scatter(
130	x=self._obj.columns,
131	y=np.ones(self._obj.columns.size),
132	mode="lines",
133	showlegend=False,
134	name=None,
135	line={"color": "black", "dash": "dot", "width": 0.5},
136	)
137	]
UNCOV 138	fig.add_traces(traces)	×
UNCOV 139	fig.update_layout(**layout)	×
UNCOV 140	fig.update_yaxes(	×
141	type="log", linecolor="black", mirror=True
142	) # todo: add this to layout
143	fig.update_xaxes(linecolor="black", mirror=True) # todo: add this to layout	×
UNCOV 144	return fig	×
145
146
147	# class pyroplot_plotly(object):
148	# def __init__(self, obj):
149	# """
150	# Custom dataframe accessor for pyrolite plotting.
151
152	# Notes
153	# -----
154	# This accessor enables the coexistence of array-based plotting functions and
155	# methods for pandas objects. This enables some separation of concerns.
156	# """
157	# self._validate(obj)
158	# self._obj = obj
159
160	# @staticmethod
161	# def _validate(obj):
162	# pass
163
164	# def heatscatter(
165	# self,
166	# components: list = None,
167	# ax=None,
168	# axlabels=True,
169	# logx=False,
170	# logy=False,
171	# **kwargs,
172	# ):
173	# r"""
174	# Heatmapped scatter plots using the pyroplot API. See further parameters
175	# for `matplotlib.pyplot.scatter` function below.
176
177	# Parameters
178	# ----------
179	# components : :class:`list`, :code:`None`
180	# Elements or compositional components to plot.
181	# ax : :class:`matplotlib.axes.Axes`, :code:`None`
182	# The subplot to draw on.
183	# axlabels : :class:`bool`, :code:`True`
184	# Whether to add x-y axis labels.
185	# logx : :class:`bool`, `False`
186	# Whether to log-transform x values before the KDE for bivariate plots.
187	# logy : :class:`bool`, `False`
188	# Whether to log-transform y values before the KDE for bivariate plots.
189
190	# {otherparams}
191
192	# Returns
193	# -------
194	# :class:`matplotlib.axes.Axes`
195	# Axes on which the heatmapped scatterplot is added.
196
197	# """
198	# obj = to_frame(self._obj)
199	# components = _check_components(obj, components=components)
200	# data, samples = (
201	# obj.reindex(columns=components).values,
202	# obj.reindex(columns=components).values,
203	# )
204	# kdetfm = [ # log transforms
205	# get_scaler([None, np.log][logx], [None, np.log][logy]),
206	# lambda x: ILR(close(x)),
207	# ][len(components) == 3]
208	# zi = sample_kde(
209	# data, samples, transform=kdetfm, **subkwargs(kwargs, sample_kde)
210	# )
211	# kwargs.update({"c": zi})
212	# ax = obj.reindex(columns=components).pyroplot.scatter(
213	# ax=ax, axlabels=axlabels, **kwargs
214	# )
215	# return ax
216
217	# def plot(self, components: list = None, ax=None, axlabels=True, **kwargs):
218	# r"""
219	# Convenience method for line plots using the pyroplot API. See
220	# further parameters for `matplotlib.pyplot.scatter` function below.
221
222	# Parameters
223	# ----------
224	# components : :class:`list`, :code:`None`
225	# Elements or compositional components to plot.
226	# ax : :class:`matplotlib.axes.Axes`, :code:`None`
227	# The subplot to draw on.
228	# axlabels : :class:`bool`, :code:`True`
229	# Whether to add x-y axis labels.
230	# {otherparams}
231
232	# Returns
233	# -------
234	# :class:`matplotlib.axes.Axes`
235	# Axes on which the plot is added.
236
237	# """
238	# obj = to_frame(self._obj)
239	# components = _check_components(obj, components=components)
240	# projection = [None, "ternary"][len(components) == 3]
241	# # ax = init_axes(ax=ax, projection=projection, **kwargs)
242	# # kw = linekwargs(kwargs)
243	# ax.plot(obj.reindex(columns=components).values.T, *kw)
244	# # if color is multi, could update line colors here
245	# # if axlabels:
246	# # label_axes(ax, labels=components)
247
248	# ax.tick_params("both")
249	# # ax.grid()
250	# # ax.set_aspect("equal")
251	# return ax
252
253	# def REE(
254	# self,
255	# index="elements",
256	# ax=None,
257	# mode="plot",
258	# dropPm=True,
259	# scatter_kw={},
260	# line_kw={},
261	# **kwargs,
262	# ):
263	# """Pass the pandas object to :func:`pyrolite.plot.spider.REE_v_radii`.
264
265	# Parameters
266	# ----------
267	# ax : :class:`matplotlib.axes.Axes`, :code:`None`
268	# The subplot to draw on.
269	# index : :class:`str`
270	# Whether to plot radii ('radii') on the principal x-axis, or elements
271	# ('elements').
272	# mode : :class:`str`, :code`["plot", "fill", "binkde", "ckde", "kde", "hist"]`
273	# Mode for plot. Plot will produce a line-scatter diagram. Fill will return
274	# a filled range. Density will return a conditional density diagram.
275	# dropPm : :class:`bool`
276	# Whether to exclude the (almost) non-existent element Promethium from the REE
277	# list.
278	# scatter_kw : :class:`dict`
279	# Keyword parameters to be passed to the scatter plotting function.
280	# line_kw : :class:`dict`
281	# Keyword parameters to be passed to the line plotting function.
282	# {otherparams}
283
284	# Returns
285	# -------
286	# :class:`matplotlib.axes.Axes`
287	# Axes on which the REE plot is added.
288
289	# """
290	# obj = to_frame(self._obj)
291	# ree = [i for i in geochem.ind.REE(dropPm=dropPm) if i in obj.columns]
292
293	# ax = spider.REE_v_radii(
294	# obj.reindex(columns=ree).astype(float).values,
295	# index=index,
296	# ree=ree,
297	# mode=mode,
298	# ax=ax,
299	# scatter_kw=scatter_kw,
300	# line_kw=line_kw,
301	# **kwargs,
302	# )
303	# ax.set_ylabel(r"$\mathrm{X / X_{Reference}}$")
304	# return ax
305
306	# def scatter(self, components: list = None, ax=None, axlabels=True, **kwargs):
307	# r"""
308	# Convenience method for scatter plots using the pyroplot API. See
309	# further parameters for `matplotlib.pyplot.scatter` function below.
310
311	# Parameters
312	# ----------
313	# components : :class:`list`, :code:`None`
314	# Elements or compositional components to plot.
315	# ax : :class:`matplotlib.axes.Axes`, :code:`None`
316	# The subplot to draw on.
317	# axlabels : :class:`bool`, :code:`True`
318	# Whether to add x-y axis labels.
319	# {otherparams}
320
321	# Returns
322	# -------
323	# :class:`matplotlib.axes.Axes`
324	# Axes on which the scatterplot is added.
325
326	# """
327	# obj = to_frame(self._obj)
328	# components = _check_components(obj, components=components)
329
330	# projection = [None, "ternary"][len(components) == 3]
331	# # ax = init_axes(ax=ax, projection=projection, **kwargs)
332	# size = obj.index.size
333	# kw = process_color(size=size, **kwargs)
334	# with warnings.catch_warnings():
335	# # ternary transform where points add to zero will give an unnecessary
336	# # warning; here we supress it
337	# warnings.filterwarnings(
338	# "ignore", message="invalid value encountered in divide"
339	# )
340	# ax.scatter(obj.reindex(columns=components).values.T, *kw)
341
342	# # if axlabels:
343	# # label_axes(ax, labels=components)
344
345	# ax.tick_params("both")
346	# # ax.grid()
347	# # ax.set_aspect("equal")
348	# return ax
349
350	# def spider(
351	# self,
352	# components: list = None,
353	# indexes: list = None,
354	# ax=None,
355	# mode="plot",
356	# index_order=None,
357	# autoscale=True,
358	# scatter_kw={},
359	# line_kw={},
360	# **kwargs,
361	# ):
362	# r"""
363	# Method for spider plots. Convenience access function to
364	# :func:`~pyrolite.plot.spider.spider` (see `Other Parameters`, below), where
365	# further parameters for relevant `matplotlib` functions are also listed.
366
367	# Parameters
368	# ----------
369	# components : :class:`list`, `None`
370	# Elements or compositional components to plot.
371	# indexes : :class:`list`, `None`
372	# Elements or compositional components to plot.
373	# ax : :class:`matplotlib.axes.Axes`, :code:`None`
374	# The subplot to draw on.
375	# index_order
376	# Function to order spider plot indexes (e.g. by incompatibility).
377	# autoscale : :class:`bool`
378	# Whether to autoscale the y-axis limits for standard spider plots.
379	# mode : :class:`str`, :code`["plot", "fill", "binkde", "ckde", "kde", "hist"]`
380	# Mode for plot. Plot will produce a line-scatter diagram. Fill will return
381	# a filled range. Density will return a conditional density diagram.
382	# scatter_kw : :class:`dict`
383	# Keyword parameters to be passed to the scatter plotting function.
384	# line_kw : :class:`dict`
385	# Keyword parameters to be passed to the line plotting function.
386	# {otherparams}
387
388	# Returns
389	# -------
390	# :class:`matplotlib.axes.Axes`
391	# Axes on which the spider diagram is plotted.
392
393	# Todo
394	# ----
395	# * Add 'compositional data' filter for default components if None is given
396
397	# """
398	# obj = to_frame(self._obj)
399
400	# if components is None: # default to plotting elemental data
401	# components = [
402	# el for el in obj.columns if el in geochem.ind.common_elements()
403	# ]
404
405	# assert len(components) != 0
406
407	# if index_order is not None:
408	# if isinstance(index_order, str):
409	# try:
410	# index_order = geochem.ind.ordering[index_order]
411	# except KeyError:
412	# msg = (
413	# "Ordering not applied, as parameter '{}' not recognized."
414	# " Select from: {}"
415	# ).format(index_order, ", ".join(list(geochem.ind.ordering.keys())))
416	# logger.warning(msg)
417	# components = index_order(components)
418	# else:
419	# components = index_order(components)
420
421	# # ax = init_axes(ax=ax, **kwargs)
422
423	# if hasattr(ax, "_pyrolite_components"):
424	# # TODO: handle spider diagrams which have specified components
425	# pass
426
427	# ax = spider.spider(
428	# obj.reindex(columns=components).astype(float).values,
429	# indexes=indexes,
430	# ax=ax,
431	# mode=mode,
432	# autoscale=autoscale,
433	# scatter_kw=scatter_kw,
434	# line_kw=line_kw,
435	# **kwargs,
436	# )
437	# ax._pyrolite_components = components
438	# ax.set_xticklabels(components, rotation=60)
439	# return ax

morganjwilliams / pyrolite / 17569144994

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