11624563836

Committed 01 Nov 2024 04:58AM UTC coverage: 91.367% (-0.2%) from 91.538%

Build # 11624563836

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push

github

Committed by

morganjwilliams

Commit Message

Update get_ionic_radii test

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86.67

/pyrolite/util/plot/transform.py

"""
Transformation utilites for matplotlib.
"""

import numpy as np

from ...comp.codata import close
from ..log import Handle

logger = Handle(__name__)


def affine_transform(mtx=np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])):
    """
    Construct a function which will perform a 2D affine transform based on
    a 3x3 affine matrix.

    Parameters
    -----------
    mtx : :class:`numpy.ndarray`
    """

    def tfm(data):
        xy = data[:, :2]
        return (mtx @ np.vstack((xy.T[:2], np.ones(xy.T.shape[1]))))[:2]

    return tfm


def tlr_to_xy(tlr):
    """
    Transform a ternary coordinate system (top-left-right) to an xy-cartesian
    coordinate system.

    Parameters
    ----------
    tlr : :class:`numpy.ndarray`
        Array of shape (n, 3) in the t-l-r coordinate system.

    Returns
    --------
    xy : :class:`numpy.ndarray`
        Array of shape (n, 2) in the x-y coordinate system.
    """
    shear = affine_transform(np.array([[1, 1 / 2, 0], [0, 1, 0], [0, 0, 1]]))
    return shear(close(np.array(tlr)[:, [2, 0, 1]])).T


def xy_to_tlr(xy):
    """

    Parameters
    -----------
    xy : :class:`numpy.ndarray`
        Array of shape (n, 2) in the x-y coordinate system.

    Returns
    --------
    tlr : :class:`numpy.ndarray`
        Array of shape (n, 3) in the t-l-r coordinate system.
    """
    shear = affine_transform(np.array([[1, -1 / 2, 0], [0, 1, 0], [0, 0, 1]]))
    r, t = shear(xy)
    l = 1.0 - (r + t)
    return np.vstack([t, l, r]).T


def ABC_to_xy(ABC, xscale=1.0, yscale=1.0):
    """
    Convert ternary compositional coordiantes to x-y coordinates
    for visualisation within a triangle.

    Parameters
    -----------
    ABC : :class:`numpy.ndarray`
        Ternary array (:code:`samples, 3`).
    xscale : :class:`float`
        Scale for x-axis.
    yscale : :class:`float`
        Scale for y-axis.

    Returns
    --------
    :class:`numpy.ndarray`
        Array of x-y coordinates (:code:`samples, 2`)
    """
    assert ABC.shape[-1] == 3
    # transform from ternary to xy cartesian
    scale = affine_transform(np.array([[xscale, 0, 0], [0, yscale, 0], [0, 0, 1]]))
    shear = affine_transform(np.array([[1, 1 / 2, 0], [0, 1, 0], [0, 0, 1]]))
    xy = scale(shear(close(ABC)).T)
    return xy.T


def xy_to_ABC(xy, xscale=1.0, yscale=1.0):
    """
    Convert x-y coordinates within a triangle to compositional ternary coordinates.

    Parameters
    -----------
    xy : :class:`numpy.ndarray`
        XY array (:code:`samples, 2`).
    xscale : :class:`float`
        Scale for x-axis.
    yscale : :class:`float`
        Scale for y-axis.

    Returns
    --------
    :class:`numpy.ndarray`
        Array of ternary coordinates (:code:`samples, 3`)
    """
    assert xy.shape[-1] == 2
    # transform from xy cartesian to ternary
    scale = affine_transform(
        np.array([[1 / xscale, 0, 0], [0, 1 / yscale, 0], [0, 0, 1]])
    )
    shear = affine_transform(np.array([[1, -1 / 2, 0], [0, 1, 0], [0, 0, 1]]))
    A, B = shear(scale(xy).T)
    C = 1.0 - (A + B)  # + (xscale-1) + (yscale-1)
    return np.vstack([A, B, C]).T

1	"""
2	Transformation utilites for matplotlib.
3	"""
4
5	import numpy as np	12✔
6
7	from ...comp.codata import close	12✔
8	from ..log import Handle	12✔
9
10	logger = Handle(__name__)	12✔
11
12
13	def affine_transform(mtx=np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]])):	12✔
14	"""
15	Construct a function which will perform a 2D affine transform based on
16	a 3x3 affine matrix.
17
18	Parameters
19	-----------
20	mtx : :class:`numpy.ndarray`
21	"""
22
23	def tfm(data):	12✔
24	xy = data[:, :2]	12✔
25	return (mtx @ np.vstack((xy.T[:2], np.ones(xy.T.shape[1]))))[:2]	12✔
26
27	return tfm	12✔
28
29
30	def tlr_to_xy(tlr):	12✔
31	"""
32	Transform a ternary coordinate system (top-left-right) to an xy-cartesian
33	coordinate system.
34
35	Parameters
36	----------
37	tlr : :class:`numpy.ndarray`
38	Array of shape (n, 3) in the t-l-r coordinate system.
39
40	Returns
41	--------
42	xy : :class:`numpy.ndarray`
43	Array of shape (n, 2) in the x-y coordinate system.
44	"""
45	shear = affine_transform(np.array([[1, 1 / 2, 0], [0, 1, 0], [0, 0, 1]]))	12✔
46	return shear(close(np.array(tlr)[:, [2, 0, 1]])).T	12✔
47
48
49	def xy_to_tlr(xy):	12✔
50	"""
51
52	Parameters
53	-----------
54	xy : :class:`numpy.ndarray`
55	Array of shape (n, 2) in the x-y coordinate system.
56
57	Returns
58	--------
59	tlr : :class:`numpy.ndarray`
60	Array of shape (n, 3) in the t-l-r coordinate system.
61	"""
62	shear = affine_transform(np.array([[1, -1 / 2, 0], [0, 1, 0], [0, 0, 1]]))	×
63	r, t = shear(xy)	×
64	l = 1.0 - (r + t)	×
65	return np.vstack([t, l, r]).T	×
66
67
68	def ABC_to_xy(ABC, xscale=1.0, yscale=1.0):	12✔
69	"""
70	Convert ternary compositional coordiantes to x-y coordinates
71	for visualisation within a triangle.
72
73	Parameters
74	-----------
75	ABC : :class:`numpy.ndarray`
76	Ternary array (:code:`samples, 3`).
77	xscale : :class:`float`
78	Scale for x-axis.
79	yscale : :class:`float`
80	Scale for y-axis.
81
82	Returns
83	--------
84	:class:`numpy.ndarray`
85	Array of x-y coordinates (:code:`samples, 2`)
86	"""
87	assert ABC.shape[-1] == 3	12✔
88	# transform from ternary to xy cartesian
89	scale = affine_transform(np.array([[xscale, 0, 0], [0, yscale, 0], [0, 0, 1]]))	12✔
90	shear = affine_transform(np.array([[1, 1 / 2, 0], [0, 1, 0], [0, 0, 1]]))	12✔
91	xy = scale(shear(close(ABC)).T)	12✔
92	return xy.T	12✔
93
94
95	def xy_to_ABC(xy, xscale=1.0, yscale=1.0):	12✔
96	"""
97	Convert x-y coordinates within a triangle to compositional ternary coordinates.
98
99	Parameters
100	-----------
101	xy : :class:`numpy.ndarray`
102	XY array (:code:`samples, 2`).
103	xscale : :class:`float`
104	Scale for x-axis.
105	yscale : :class:`float`
106	Scale for y-axis.
107
108	Returns
109	--------
110	:class:`numpy.ndarray`
111	Array of ternary coordinates (:code:`samples, 3`)
112	"""
113	assert xy.shape[-1] == 2	12✔
114	# transform from xy cartesian to ternary
115	scale = affine_transform(	12✔
116	np.array([[1 / xscale, 0, 0], [0, 1 / yscale, 0], [0, 0, 1]])
117	)
118	shear = affine_transform(np.array([[1, -1 / 2, 0], [0, 1, 0], [0, 0, 1]]))	12✔
119	A, B = shear(scale(xy).T)	12✔
120	C = 1.0 - (A + B) # + (xscale-1) + (yscale-1)	12✔
121	return np.vstack([A, B, C]).T	12✔

morganjwilliams / pyrolite / 11624563836

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