9114710863

Committed 16 May 2024 03:06PM UTC coverage: 91.635% (-0.03%) from 91.661%

Build # 9114710863

Build Type

Pull #104

github

Committed by

web-flow

Commit Message

Merge dd85a1027 into d3f5b518a

Pull Request Pull Request #104: Checks for negative entries in close and normalise functions of codata.py

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1 existing line in 1 file now uncovered.

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95.24

/pyrolite/util/plot/interpolation.py

"""
Line interpolation for matplotlib lines and paths.
"""

import matplotlib.collections
import matplotlib.path
import numpy as np
import scipy.interpolate

from ..log import Handle

logger = Handle(__name__)


def interpolate_path(
    path, resolution=100, periodic=False, aspath=True, closefirst=False, **kwargs
):
    """
    Obtain the interpolation of an existing path at a given
    resolution. Keyword arguments are forwarded to
    :func:`scipy.interpolate.splprep`.

    Parameters
    -----------
    path : :class:`matplotlib.path.Path`
        Path to interpolate.
    resolution :class:`int`
        Resolution at which to obtain the new path. The verticies of
        the new path will have shape (`resolution`, 2).
    periodic : :class:`bool`
        Whether to use a periodic spline.
    periodic : :class:`bool`
        Whether to return a :code:`matplotlib.path.Path`, or simply
        a tuple of x-y arrays.
    closefirst : :class:`bool`
        Whether to first close the path by appending the first point again.

    Returns
    --------
    :class:`matplotlib.path.Path` | :class:`tuple`
        Interpolated :class:`~matplotlib.path.Path` object, if
        `aspath` is :code:`True`, else a tuple of x-y arrays.
    """
    x, y = path.vertices.T
    if x.size > 4:
        if closefirst:
            x = np.append(x, x[0])
            y = np.append(y, y[0])
        # s=0 forces the interpolation to go through every point

        tck, _ = scipy.interpolate.splprep(
            [x[:-1], y[:-1]], s=0, per=periodic, **kwargs
        )
        xi, yi = scipy.interpolate.splev(np.linspace(0.0, 1.0, resolution), tck)
        # could get control points for path and construct codes here
        codes = None
        pth = matplotlib.path.Path(np.vstack([xi, yi]).T, codes=codes)
        if aspath:
            return pth
        else:
            return pth.vertices.T
    else:
        return path.vertices.T


def interpolated_patch_path(patch, resolution=100, **kwargs):
    """
    Obtain the periodic interpolation of the existing path of a patch at a
    given resolution.

    Parameters
    -----------
    patch : :class:`matplotlib.patches.Patch`
        Patch to obtain the original path from.
    resolution :class:`int`
        Resolution at which to obtain the new path. The verticies of the new path
        will have shape (`resolution`, 2).

    Returns
    --------
    :class:`matplotlib.path.Path`
        Interpolated :class:`~matplotlib.path.Path` object.
    """
    pth = patch.get_path()
    tfm = patch.get_transform()
    pathtfm = tfm.transform_path(pth)
    return interpolate_path(
        pathtfm, resolution=resolution, aspath=True, periodic=True, **kwargs
    )


def get_contour_paths(src, resolution=100, minsize=3):
    """
    Extract the paths of contours from a contour plot.

    Parameters
    ------------
    ax : :class:`matplotlib.axes.Axes` |
        Axes to extract contours from.
    resolution : :class:`int`
        Resolution of interpolated splines to return.

    Returns
    --------
    contourspaths : :class:`list` (:class:`list`)
        List of lists, each represnting one line collection (a single contour). In the
        case where this contour is multimodal, there will be multiple paths for each
        contour.
    contournames : :class:`list`
        List of names for contours, where they have been labelled, and there are no
        other text artists on the figure.
    contourstyles : :class:`list`
        List of styles for contours.

    Notes
    ------
        This method assumes that contours are the only
        :code:`matplotlib.collections.LineCollection` objects within an axes;
        and when this is not the case, additional non-contour objects will be returned.
    """
    if isinstance(src, matplotlib.axes.Axes):

        def _iscontour(c):
            # contours/default lines don't have markers - allows distinguishing scatter
            return (
                isinstance(c, matplotlib.collections.PathCollection)
                and c.get_sizes().size == 0
            ) or isinstance(c, matplotlib.collections.LineCollection)

        linecolls = [
            c for c in src.collections if (_iscontour(c) and len(c.get_paths()))
        ]
        names = [None for lc in linecolls]
        if all([len(a.get_text()) for a in src.texts]):
            if len(src.texts) == len(linecolls):
                names = [a.get_text() for a in src.texts]
            else:
                logger.debug("Can't line up labels/text with contours.")
    elif isinstance(src, matplotlib.contour.ContourSet):
        names = src.labelTexts
        linecolls = src.collections
        linecolls = [c for c in src.collections if len(c.get_paths())]

    rgba = [lc.get_edgecolors() for lc in linecolls]
    styles = [{"color": c} for c in rgba]
    return (
        [
            [
                interpolate_path(
                    p,
                    resolution=resolution,
                    periodic=True,
                    aspath=False,
                )
                for p in lc.get_paths()
            ]
            for lc in linecolls
        ],
        names,
        styles,
    )

1	"""
2	Line interpolation for matplotlib lines and paths.
3	"""
4
5	import matplotlib.collections	3✔
6	import matplotlib.path	3✔
7	import numpy as np	3✔
8	import scipy.interpolate	3✔
9
10	from ..log import Handle	3✔
11
12	logger = Handle(__name__)	3✔
13
14
15	def interpolate_path(	3✔
16	path, resolution=100, periodic=False, aspath=True, closefirst=False, **kwargs
17	):
18	"""
19	Obtain the interpolation of an existing path at a given
20	resolution. Keyword arguments are forwarded to
21	:func:`scipy.interpolate.splprep`.
22
23	Parameters
24	-----------
25	path : :class:`matplotlib.path.Path`
26	Path to interpolate.
27	resolution :class:`int`
28	Resolution at which to obtain the new path. The verticies of
29	the new path will have shape (`resolution`, 2).
30	periodic : :class:`bool`
31	Whether to use a periodic spline.
32	periodic : :class:`bool`
33	Whether to return a :code:`matplotlib.path.Path`, or simply
34	a tuple of x-y arrays.
35	closefirst : :class:`bool`
36	Whether to first close the path by appending the first point again.
37
38	Returns
39	--------
40	:class:`matplotlib.path.Path` \| :class:`tuple`
41	Interpolated :class:`~matplotlib.path.Path` object, if
42	`aspath` is :code:`True`, else a tuple of x-y arrays.
43	"""
44	x, y = path.vertices.T	3✔
45	if x.size > 4:	3✔
46	if closefirst:	3✔
47	x = np.append(x, x[0])	3✔
48	y = np.append(y, y[0])	3✔
49	# s=0 forces the interpolation to go through every point
50
51	tck, _ = scipy.interpolate.splprep(	3✔
52	[x[:-1], y[:-1]], s=0, per=periodic, **kwargs
53	)
54	xi, yi = scipy.interpolate.splev(np.linspace(0.0, 1.0, resolution), tck)	3✔
55	# could get control points for path and construct codes here
56	codes = None	3✔
57	pth = matplotlib.path.Path(np.vstack([xi, yi]).T, codes=codes)	3✔
58	if aspath:	3✔
59	return pth	3✔
60	else:
61	return pth.vertices.T	3✔
62	else:
63	return path.vertices.T	×
64
65
66	def interpolated_patch_path(patch, resolution=100, **kwargs):	3✔
67	"""
68	Obtain the periodic interpolation of the existing path of a patch at a
69	given resolution.
70
71	Parameters
72	-----------
73	patch : :class:`matplotlib.patches.Patch`
74	Patch to obtain the original path from.
75	resolution :class:`int`
76	Resolution at which to obtain the new path. The verticies of the new path
77	will have shape (`resolution`, 2).
78
79	Returns
80	--------
81	:class:`matplotlib.path.Path`
82	Interpolated :class:`~matplotlib.path.Path` object.
83	"""
84	pth = patch.get_path()	3✔
85	tfm = patch.get_transform()	3✔
86	pathtfm = tfm.transform_path(pth)	3✔
87	return interpolate_path(	3✔
88	pathtfm, resolution=resolution, aspath=True, periodic=True, **kwargs
89	)
90
91
92	def get_contour_paths(src, resolution=100, minsize=3):	3✔
93	"""
94	Extract the paths of contours from a contour plot.
95
96	Parameters
97	------------
98	ax : :class:`matplotlib.axes.Axes` \|
99	Axes to extract contours from.
100	resolution : :class:`int`
101	Resolution of interpolated splines to return.
102
103	Returns
104	--------
105	contourspaths : :class:`list` (:class:`list`)
106	List of lists, each represnting one line collection (a single contour). In the
107	case where this contour is multimodal, there will be multiple paths for each
108	contour.
109	contournames : :class:`list`
110	List of names for contours, where they have been labelled, and there are no
111	other text artists on the figure.
112	contourstyles : :class:`list`
113	List of styles for contours.
114
115	Notes
116	------
117	This method assumes that contours are the only
118	:code:`matplotlib.collections.LineCollection` objects within an axes;
119	and when this is not the case, additional non-contour objects will be returned.
120	"""
121	if isinstance(src, matplotlib.axes.Axes):	3✔
122
123	def _iscontour(c):	3✔
124	# contours/default lines don't have markers - allows distinguishing scatter
125	return (	3✔
126	isinstance(c, matplotlib.collections.PathCollection)
127	and c.get_sizes().size == 0
128	) or isinstance(c, matplotlib.collections.LineCollection)
129
130	linecolls = [	3✔
131	c for c in src.collections if (_iscontour(c) and len(c.get_paths()))
132	]
133	names = [None for lc in linecolls]	3✔
134	if all([len(a.get_text()) for a in src.texts]):	3✔
135	if len(src.texts) == len(linecolls):	3✔
136	names = [a.get_text() for a in src.texts]	3✔
137	else:
UNCOV 138	logger.debug("Can't line up labels/text with contours.")	×
139	elif isinstance(src, matplotlib.contour.ContourSet):	3✔
140	names = src.labelTexts	3✔
141	linecolls = src.collections	3✔
142	linecolls = [c for c in src.collections if len(c.get_paths())]	3✔
143
144	rgba = [lc.get_edgecolors() for lc in linecolls]	3✔
145	styles = [{"color": c} for c in rgba]	3✔
146	return (	3✔
147	[
148	[
149	interpolate_path(
150	p,
151	resolution=resolution,
152	periodic=True,
153	aspath=False,
154	)
155	for p in lc.get_paths()
156	]
157	for lc in linecolls
158	],
159	names,
160	styles,
161	)

morganjwilliams / pyrolite / 9114710863

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