Coverage for python/lsst/scarlet/lite/utils.py: 48%
47 statements
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1# This file is part of scarlet_lite.
2#
3# Developed for the LSST Data Management System.
4# This product includes software developed by the LSST Project
5# (https://www.lsst.org).
6# See the COPYRIGHT file at the top-level directory of this distribution
7# for details of code ownership.
8#
9# This program is free software: you can redistribute it and/or modify
10# it under the terms of the GNU General Public License as published by
11# the Free Software Foundation, either version 3 of the License, or
12# (at your option) any later version.
13#
14# This program is distributed in the hope that it will be useful,
15# but WITHOUT ANY WARRANTY; without even the implied warranty of
16# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17# GNU General Public License for more details.
18#
19# You should have received a copy of the GNU General Public License
20# along with this program. If not, see <https://www.gnu.org/licenses/>.
22import sys
24import numpy as np
25import numpy.typing as npt
26from scipy.special import erfc
28ScalarLike = bool | int | float | complex
29ScalarTypes = (bool, int, float, complex)
32sqrt2 = np.sqrt(2)
33sqrt_pi = np.sqrt(np.pi)
36def integrated_gaussian_value(x: np.ndarray, sigma: float) -> np.ndarray:
37 """A Gaussian function evaluated at `x`
39 Parameters
40 ----------
41 x:
42 The coordinates to evaluate the integrated Gaussian
43 (ie. the centers of pixels).
44 sigma:
45 The standard deviation of the Gaussian.
47 Returns
48 -------
49 gaussian:
50 A Gaussian function integrated over `x`
51 """
52 lhs = erfc((x - 0.5) / (sqrt2 * sigma))
53 rhs = erfc((x + 0.5) / (sqrt2 * sigma))
54 return sqrt_pi * 0.5 * sigma * (lhs - rhs)
57def integrated_circular_gaussian(
58 x: np.ndarray | None = None, y: np.ndarray | None = None, sigma: float = 0.8
59) -> np.ndarray:
60 """Create a circular Gaussian that is integrated over pixels
62 This is typically used for the model PSF,
63 working well with the default parameters.
65 Parameters
66 ----------
67 x, y:
68 The x,y-coordinates to evaluate the integrated Gaussian.
69 If `X` and `Y` are `None` then they will both be given the
70 default value `numpy.arange(-7, 8)`, resulting in a
71 `15x15` centered image.
72 sigma:
73 The standard deviation of the Gaussian.
75 Returns
76 -------
77 image:
78 A Gaussian function integrated over `X` and `Y`.
79 """
80 if x is None:
81 if y is None:
82 x = np.arange(-7, 8)
83 y = x
84 else:
85 raise ValueError(
86 f"Either X and Y must be specified, or neither must be specified, got {x=} and {y=}"
87 )
88 elif y is None:
89 raise ValueError(f"Either X and Y must be specified, or neither must be specified, got {x=} and {y=}")
91 _x = integrated_gaussian_value(np.abs(x), sigma)[None, :]
92 _y = integrated_gaussian_value(np.abs(y), sigma)[:, None]
93 result = _x * _y
94 return result / np.sum(result)
97def get_circle_mask(diameter: int, dtype: npt.DTypeLike = np.float64):
98 """Get a boolean image of a circle
100 Parameters
101 ----------
102 diameter:
103 The diameter of the circle and width
104 of the image.
105 dtype:
106 The `dtype` of the image.
108 Returns
109 -------
110 circle:
111 A boolean array with ones for the pixels with centers
112 inside of the circle and zeros
113 outside of the circle.
114 """
115 c = (diameter - 1) / 2
116 # The center of the circle and its radius are
117 # off by half a pixel for circles with
118 # even numbered diameter
119 if diameter % 2 == 0:
120 radius = diameter / 2
121 else:
122 radius = c
123 _x = np.arange(diameter)
124 x, y = np.meshgrid(_x, _x)
125 r = np.sqrt((x - c) ** 2 + (y - c) ** 2)
127 circle = np.ones((diameter, diameter), dtype=dtype)
128 circle[r > radius] = 0
129 return circle
132INTRINSIC_SPECIAL_ATTRIBUTES = frozenset(
133 (
134 "__qualname__",
135 "__module__",
136 "__metaclass__",
137 "__dict__",
138 "__weakref__",
139 "__class__",
140 "__subclasshook__",
141 "__name__",
142 "__doc__",
143 )
144)
147def is_attribute_safe_to_transfer(name, value):
148 """Return True if an attribute is safe to monkeypatch-transfer to another
149 class.
150 This rejects special methods that are defined automatically for all
151 classes, leaving only those explicitly defined in a class decorated by
152 `continueClass` or registered with an instance of `TemplateMeta`.
153 """
154 if name.startswith("__") and (
155 value is getattr(object, name, None) or name in INTRINSIC_SPECIAL_ATTRIBUTES
156 ):
157 return False
158 return True
161def continue_class(cls):
162 """Re-open the decorated class, adding any new definitions into the
163 original.
164 For example:
165 .. code-block:: python
166 class Foo:
167 pass
168 @continueClass
169 class Foo:
170 def run(self):
171 return None
172 is equivalent to:
173 .. code-block:: python
174 class Foo:
175 def run(self):
176 return None
177 .. warning::
178 Python's built-in `super` function does not behave properly in classes
179 decorated with `continue_class`. Base class methods must be invoked
180 directly using their explicit types instead.
182 This is copied directly from lsst.utils. If any additional functions are
183 used from that repo we should remove this function and make lsst.utils
184 a dependency. But for now, it is easier to copy this single wrapper
185 than to include lsst.utils and all of its dependencies.
186 """
187 orig = getattr(sys.modules[cls.__module__], cls.__name__)
188 for name in dir(cls):
189 # Common descriptors like classmethod and staticmethod can only be
190 # accessed without invoking their magic if we use __dict__; if we use
191 # getattr on those we'll get e.g. a bound method instance on the dummy
192 # class rather than a classmethod instance we can put on the target
193 # class.
194 attr = cls.__dict__.get(name, None) or getattr(cls, name)
195 if is_attribute_safe_to_transfer(name, attr):
196 setattr(orig, name, attr)
197 return orig