20546482500

Committed 29 Oct 2024 02:20AM UTC coverage: 91.571% (-0.07%) from 91.64%

Build # 20546482500

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github

Committed by

morganjwilliams

Commit Message

Merge branch 'release/0.3.6' into main

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53 of 62 new or added lines in 12 files covered. (85.48%)

3 existing lines in 2 files now uncovered.

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89.69

/pyrolite/plot/density/grid.py

import numpy as np

from ...util.distributions import sample_kde
from ...util.log import Handle
from ...util.math import flattengrid, linrng_, linspc_, logrng_, logspc_
from ...util.plot.grid import bin_centres_to_edges

logger = Handle(__name__)


class DensityGrid(object):
    def __init__(
        self, x, y, extent=None, bins=50, logx=False, logy=False, coverage_scale=1.2
    ):
        """
        Build a grid of x-y coordinates for use in evaluating KDE functions.

        Parameters
        -----------
        x : :class:`np.ndarray`
        y : :class:`np.ndarray`
        extent : :class:`list`
            Optionally-specified extent for the grid in the form (xmin, xmax, ymin, ymax).
        bins : :class:`int` | :class:`tuple`
            Number of bins for the grid. Can optionally specify
            a tuple with (xbins, ybins).
        logx : :class:`bool`
            Whether to use a log-spaced index for the x dimension of the grid.
        logy: :class:`bool`
            Whether to use a log-spaced index for the y dimension of the grid.
        coverage_scale : :class:`float`
            Multiplier for the range of the grid relative to the data. If >1, the grid
            will extend beyond the data.
        """
        # limits
        self.logx = logx
        self.logy = logy
        if not isinstance(bins, int):
            assert len(bins) == 2  # x-y bins
            self.xbins, self.ybins = bins
        else:
            self.xbins, self.ybins = bins, bins
        self.coverage_scale = coverage_scale

        if extent is None:
            self.xmin, self.xmax, self.ymin, self.ymax = self.extent_from_xy(x, y)
        else:
            self.xmin, self.xmax, self.ymin, self.ymax = extent
            # validation
            self.xmin, self.xmax = (
                min([self.xmin, self.xmax]),
                max([self.xmin, self.xmax]),
            )
            self.ymin, self.ymax = (
                min([self.ymin, self.ymax]),
                max([self.ymin, self.ymax]),
            )

        self.xstep = self.get_xstep()
        self.ystep = self.get_ystep()

        if self.logx:
            assert self.xmin > 0.0
            assert (self.xmin / self.xstep) > 0.0
        if self.logy:
            assert self.ymin > 0.0
            assert (self.ymin / self.ystep) > 0.0

        self.calculate_grid()

    def calculate_grid(self):
        self.get_centre_grid()
        self.get_edge_grid()

    def get_ystep(self):
        if self.logy:
            step = (self.ymax / self.ymin) / self.ybins
        else:
            step = (self.ymax - self.ymin) / self.ybins
        return step

    def get_xstep(self):
        if self.logx:
            step = (self.xmax / self.xmin) / self.xbins
        else:
            step = (self.xmax - self.xmin) / self.xbins
        return step

    def extent_from_xy(self, x, y, coverage_scale=None):
        cov = coverage_scale or self.coverage_scale
        expand_grid = (cov - 1.0) / 2
        return [
            *[linrng_, logrng_][self.logx](x, exp=expand_grid),
            *[linrng_, logrng_][self.logy](y, exp=expand_grid),
        ]

    def get_xrange(self):
        return self.xmin, self.xmax

    def get_yrange(self):
        return self.ymin, self.ymax

    def get_extent(self):
        return [*self.get_xrange(), *self.get_yrange()]

    def get_range(self):
        return [[*self.get_xrange()], [*self.get_yrange()]]

    def update_grid_centre_ticks(self):
        if self.logx:
            self.grid_xc = logspc_(self.xmin, self.xmax, 1.0, self.xbins)
        else:
            self.grid_xc = linspc_(self.xmin, self.xmax, self.xstep, self.xbins)

        if self.logy:
            self.grid_yc = logspc_(self.ymin, self.ymax, 1.0, self.ybins)
        else:
            self.grid_yc = linspc_(self.ymin, self.ymax, self.ystep, self.ybins)

    def update_grid_edge_ticks(self):
        self.update_grid_centre_ticks()
        if self.logx:
            self.grid_xe = np.exp(bin_centres_to_edges(np.log(np.sort(self.grid_xc))))
        else:
            self.grid_xe = bin_centres_to_edges(np.sort(self.grid_xc))

        if self.logy:
            self.grid_ye = np.exp(bin_centres_to_edges(np.log(np.sort(self.grid_yc))))
        else:
            self.grid_ye = bin_centres_to_edges(np.sort(self.grid_yc))

    def get_centre_grid(self):
        self.update_grid_centre_ticks()
        self.grid_xci, self.grid_yci = np.meshgrid(self.grid_xc, self.grid_yc)

    def get_edge_grid(self):
        self.update_grid_edge_ticks()
        self.grid_xei, self.grid_yei = np.meshgrid(self.grid_xe, self.grid_ye)

    def get_hex_extent(self):
        if self.logx:
            xex = [np.log(self.xmin / self.xstep), np.log(self.xmax * self.xstep)]
        else:
            xex = [self.xmin - self.xstep, self.xmax + self.xstep]

        if self.logy:
            yex = [np.log(self.ymin / self.ystep), np.log(self.ymax * self.ystep)]
        else:
            yex = [self.ymin - self.ystep, self.ymax + self.ystep]
        return xex + yex

    def kdefrom(
        self,
        xy,
        xtransform=lambda x: x,
        ytransform=lambda x: x,
        mode="centres",
        bw_method=None,
    ):
        """
        Take an x-y array and sample a KDE on the grid.
        """
        arr = xy.copy()
        # generate x grid over range spanned by log(x)
        arr[:, 0] = xtransform(xy[:, 0])
        # generate y grid over range spanned by log(y)
        arr[:, 1] = ytransform(xy[:, 1])
        if mode == "centres":
            assert np.isfinite(self.grid_xc).all() and np.isfinite(self.grid_yc).all()
            zi = sample_kde(
                arr,
                flattengrid(
                    np.meshgrid(xtransform(self.grid_xc), ytransform(self.grid_yc))
                ),
                bw_method=bw_method,
            )
            zi = zi.reshape(self.grid_xci.shape)
        elif mode == "edges":
            assert np.isfinite(self.grid_xe).all() and np.isfinite(self.grid_ye).all()
            zi = sample_kde(
                arr,
                flattengrid(
                    np.meshgrid(xtransform(self.grid_xe), ytransform(self.grid_ye))
                ),
                bw_method=bw_method,
            )
            zi = zi.reshape(self.grid_xei.shape)
        else:
            raise NotImplementedError("Valid modes are 'centres' and 'edges'.")
        return zi

1	import numpy as np	6✔
2
3	from ...util.distributions import sample_kde	6✔
4	from ...util.log import Handle	6✔
5	from ...util.math import flattengrid, linrng_, linspc_, logrng_, logspc_	6✔
6	from ...util.plot.grid import bin_centres_to_edges	6✔
7
8	logger = Handle(__name__)	6✔
9
10
11	class DensityGrid(object):	6✔
12	def __init__(	6✔
13	self, x, y, extent=None, bins=50, logx=False, logy=False, coverage_scale=1.2
14	):
15	"""
16	Build a grid of x-y coordinates for use in evaluating KDE functions.
17
18	Parameters
19	-----------
20	x : :class:`np.ndarray`
21	y : :class:`np.ndarray`
22	extent : :class:`list`
23	Optionally-specified extent for the grid in the form (xmin, xmax, ymin, ymax).
24	bins : :class:`int` \| :class:`tuple`
25	Number of bins for the grid. Can optionally specify
26	a tuple with (xbins, ybins).
27	logx : :class:`bool`
28	Whether to use a log-spaced index for the x dimension of the grid.
29	logy: :class:`bool`
30	Whether to use a log-spaced index for the y dimension of the grid.
31	coverage_scale : :class:`float`
32	Multiplier for the range of the grid relative to the data. If >1, the grid
33	will extend beyond the data.
34	"""
35	# limits
36	self.logx = logx	6✔
37	self.logy = logy	6✔
38	if not isinstance(bins, int):	6✔
39	assert len(bins) == 2 # x-y bins	×
40	self.xbins, self.ybins = bins	×
41	else:
42	self.xbins, self.ybins = bins, bins	6✔
43	self.coverage_scale = coverage_scale	6✔
44
45	if extent is None:	6✔
46	self.xmin, self.xmax, self.ymin, self.ymax = self.extent_from_xy(x, y)	6✔
47	else:
48	self.xmin, self.xmax, self.ymin, self.ymax = extent	×
49	# validation
NEW 50	self.xmin, self.xmax = (	×
51	min([self.xmin, self.xmax]),
52	max([self.xmin, self.xmax]),
53	)
NEW 54	self.ymin, self.ymax = (	×
55	min([self.ymin, self.ymax]),
56	max([self.ymin, self.ymax]),
57	)
58
59	self.xstep = self.get_xstep()	6✔
60	self.ystep = self.get_ystep()	6✔
61
62	if self.logx:	6✔
63	assert self.xmin > 0.0	6✔
64	assert (self.xmin / self.xstep) > 0.0	6✔
65	if self.logy:	6✔
66	assert self.ymin > 0.0	6✔
67	assert (self.ymin / self.ystep) > 0.0	6✔
68
69	self.calculate_grid()	6✔
70
71	def calculate_grid(self):	6✔
72	self.get_centre_grid()	6✔
73	self.get_edge_grid()	6✔
74
75	def get_ystep(self):	6✔
76	if self.logy:	6✔
77	step = (self.ymax / self.ymin) / self.ybins	6✔
78	else:
79	step = (self.ymax - self.ymin) / self.ybins	6✔
80	return step	6✔
81
82	def get_xstep(self):	6✔
83	if self.logx:	6✔
84	step = (self.xmax / self.xmin) / self.xbins	6✔
85	else:
86	step = (self.xmax - self.xmin) / self.xbins	6✔
87	return step	6✔
88
89	def extent_from_xy(self, x, y, coverage_scale=None):	6✔
90	cov = coverage_scale or self.coverage_scale	6✔
91	expand_grid = (cov - 1.0) / 2	6✔
92	return [	6✔
93	*[linrng_, logrng_][self.logx](x, exp=expand_grid),
94	*[linrng_, logrng_][self.logy](y, exp=expand_grid),
95	]
96
97	def get_xrange(self):	6✔
98	return self.xmin, self.xmax	6✔
99
100	def get_yrange(self):	6✔
101	return self.ymin, self.ymax	6✔
102
103	def get_extent(self):	6✔
104	return [self.get_xrange(), self.get_yrange()]	×
105
106	def get_range(self):	6✔
107	return [[self.get_xrange()], [self.get_yrange()]]	6✔
108
109	def update_grid_centre_ticks(self):	6✔
110	if self.logx:	6✔
111	self.grid_xc = logspc_(self.xmin, self.xmax, 1.0, self.xbins)	6✔
112	else:
113	self.grid_xc = linspc_(self.xmin, self.xmax, self.xstep, self.xbins)	6✔
114
115	if self.logy:	6✔
116	self.grid_yc = logspc_(self.ymin, self.ymax, 1.0, self.ybins)	6✔
117	else:
118	self.grid_yc = linspc_(self.ymin, self.ymax, self.ystep, self.ybins)	6✔
119
120	def update_grid_edge_ticks(self):	6✔
121	self.update_grid_centre_ticks()	6✔
122	if self.logx:	6✔
123	self.grid_xe = np.exp(bin_centres_to_edges(np.log(np.sort(self.grid_xc))))	6✔
124	else:
125	self.grid_xe = bin_centres_to_edges(np.sort(self.grid_xc))	6✔
126
127	if self.logy:	6✔
128	self.grid_ye = np.exp(bin_centres_to_edges(np.log(np.sort(self.grid_yc))))	6✔
129	else:
130	self.grid_ye = bin_centres_to_edges(np.sort(self.grid_yc))	6✔
131
132	def get_centre_grid(self):	6✔
133	self.update_grid_centre_ticks()	6✔
134	self.grid_xci, self.grid_yci = np.meshgrid(self.grid_xc, self.grid_yc)	6✔
135
136	def get_edge_grid(self):	6✔
137	self.update_grid_edge_ticks()	6✔
138	self.grid_xei, self.grid_yei = np.meshgrid(self.grid_xe, self.grid_ye)	6✔
139
140	def get_hex_extent(self):	6✔
141	if self.logx:	6✔
142	xex = [np.log(self.xmin / self.xstep), np.log(self.xmax * self.xstep)]	6✔
143	else:
144	xex = [self.xmin - self.xstep, self.xmax + self.xstep]	6✔
145
146	if self.logy:	6✔
147	yex = [np.log(self.ymin / self.ystep), np.log(self.ymax * self.ystep)]	6✔
148	else:
149	yex = [self.ymin - self.ystep, self.ymax + self.ystep]	6✔
150	return xex + yex	6✔
151
152	def kdefrom(	6✔
153	self,
154	xy,
155	xtransform=lambda x: x,
156	ytransform=lambda x: x,
157	mode="centres",
158	bw_method=None,
159	):
160	"""
161	Take an x-y array and sample a KDE on the grid.
162	"""
163	arr = xy.copy()	6✔
164	# generate x grid over range spanned by log(x)
165	arr[:, 0] = xtransform(xy[:, 0])	6✔
166	# generate y grid over range spanned by log(y)
167	arr[:, 1] = ytransform(xy[:, 1])	6✔
168	if mode == "centres":	6✔
169	assert np.isfinite(self.grid_xc).all() and np.isfinite(self.grid_yc).all()	×
170	zi = sample_kde(	×
171	arr,
172	flattengrid(
173	np.meshgrid(xtransform(self.grid_xc), ytransform(self.grid_yc))
174	),
175	bw_method=bw_method,
176	)
177	zi = zi.reshape(self.grid_xci.shape)	×
178	elif mode == "edges":	6✔
179	assert np.isfinite(self.grid_xe).all() and np.isfinite(self.grid_ye).all()	6✔
180	zi = sample_kde(	6✔
181	arr,
182	flattengrid(
183	np.meshgrid(xtransform(self.grid_xe), ytransform(self.grid_ye))
184	),
185	bw_method=bw_method,
186	)
187	zi = zi.reshape(self.grid_xei.shape)	6✔
188	else:
189	raise NotImplementedError("Valid modes are 'centres' and 'edges'.")	×
190	return zi	6✔

morganjwilliams / pyrolite / 20546482500

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