Hide keyboard shortcuts

Hot-keys on this page

r m x p   toggle line displays

j k   next/prev highlighted chunk

0   (zero) top of page

1   (one) first highlighted chunk

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

21

22

23

24

25

26

27

28

29

30

31

32

33

34

35

36

37

38

39

40

41

42

43

44

45

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

98

99

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

# See COPYRIGHT file at the top of the source tree. 

# 

# This file is part of fgcmcal. 

# 

# Developed for the LSST Data Management System. 

# This product includes software developed by the LSST Project 

# (https://www.lsst.org). 

# See the COPYRIGHT file at the top-level directory of this distribution 

# for details of code ownership. 

# 

# This program is free software: you can redistribute it and/or modify 

# it under the terms of the GNU General Public License as published by 

# the Free Software Foundation, either version 3 of the License, or 

# (at your option) any later version. 

# 

# This program is distributed in the hope that it will be useful, 

# but WITHOUT ANY WARRANTY; without even the implied warranty of 

# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

# GNU General Public License for more details. 

# 

# You should have received a copy of the GNU General Public License 

# along with this program. If not, see <https://www.gnu.org/licenses/>. 

"""Test the fgcm and fgcmcal (stack) chebyshev polynomial code. 

 

Run small tests to ensure that the two chebyshev implementations are 

equivalent. The fgcm chebyshev polynomial code 

(`fgcm.fgcmUtilities.Cheb2dField`) was developed independently of the stack 

`lsst.afw.math.ChebyshevBoundedField`, so as to avoid dependencies. 

""" 

 

import matplotlib 

matplotlib.use("Agg") # noqa E402 

 

import unittest 

import numpy as np 

 

import lsst.pex.exceptions 

import lsst.afw.math as afwMath 

import lsst.geom 

 

import fgcm 

 

 

class FgcmChebyshevTest(lsst.utils.tests.TestCase): 

""" 

Test the fgcm and fgcmcal (stack) chebyshev polynomial code. 

""" 

def setUp(self): 

""" 

Set up test class. 

""" 

self.xSize = 2000 

self.ySize = 4000 

self.nStar = 1000 

 

self.order = 2 

self.pars = np.zeros((self.order + 1, self.order + 1)) 

self.pars[0, 0] = 1.0 

self.pars[0, 1] = 3e-3 

self.pars[0, 2] = 1e-5 

self.pars[1, 0] = 5e-3 

self.pars[1, 1] = 7e-6 

self.pars[1, 2] = 0.0 

self.pars[2, 0] = 3e-5 

self.pars[2, 1] = 0.0 

self.pars[2, 2] = 0.0 

 

self.order2 = 1 

self.pars2 = np.zeros((self.order2 + 1, self.order2 + 1)) 

self.pars2[0, 0] = 0.98 

self.pars2[0, 1] = 5e-3 

self.pars2[1, 0] = 2e-2 

 

def test_chebyshev_evaluate(self, seed=1000): 

""" 

Test the evaluation of chebyshev polynomials. 

 

Parameters 

---------- 

seed: `int`, optional 

Numpy random seed 

""" 

# Set numpy seed for stability 

np.random.seed(seed=seed) 

 

xPos = self.xSize * np.random.rand(self.nStar) 

yPos = self.ySize * np.random.rand(self.nStar) 

 

bbox = lsst.geom.Box2I(lsst.geom.Point2I(0, 0), 

lsst.geom.Point2I(self.xSize - 1, self.ySize - 1)) 

 

# Compute the chebyshev values using the fgcm code 

fgcmField = fgcm.fgcmUtilities.Cheb2dField(self.xSize, self.ySize, 

self.pars) 

fgcmValues = fgcmField.evaluate(xPos, yPos) 

 

# Compute the chebyshev values using the afw code 

field = afwMath.ChebyshevBoundedField(bbox, self.pars) 

fieldValues = field.evaluate(xPos, yPos) 

 

self.assertFloatsAlmostEqual(fieldValues, fgcmValues, rtol=5e-15) 

 

def test_chebyshev_fit(self, seed=1000): 

""" 

Test the fitting of chebyshev polynomials. 

 

Parameters 

---------- 

seed: `int`, optional 

Numpy random seed 

""" 

# Set numpy seed for stability 

np.random.seed(seed=seed) 

 

# Generate some points to fit 

xPos = self.xSize * np.random.rand(self.nStar) 

yPos = self.ySize * np.random.rand(self.nStar) 

fgcmField = fgcm.fgcmUtilities.Cheb2dField(self.xSize, self.ySize, 

self.pars) 

fgcmValues = fgcmField.evaluate(xPos, yPos) 

 

# Fit the points using the fgcm code 

fgcmField = fgcm.fgcmUtilities.Cheb2dField.fit(self.xSize, self.ySize, 

self.order, xPos, yPos, 

fgcmValues) 

 

# Fit the points using the afw code 

bbox = lsst.geom.Box2I(lsst.geom.Point2I(0, 0), 

lsst.geom.Point2I(self.xSize - 1, self.ySize - 1)) 

 

ctrl = afwMath.ChebyshevBoundedFieldControl() 

ctrl.orderX = self.order 

ctrl.orderY = self.order 

ctrl.triangular = True 

field = afwMath.ChebyshevBoundedField.fit(bbox, xPos, yPos, 

fgcmValues, ctrl) 

 

# Compare the fit parameters 

# The tolerance here must be looser than the application, I believe 

# because of rounding errors in the fit implementations. But the 

# good news is that a tolerance of 1e-9 in parameters in these 

# tests yields a recovered tolerance of < 5e-15. 

self.assertFloatsAlmostEqual(fgcmField.pars, field.getCoefficients(), 

rtol=1e-9) 

 

# And compare the input and output 

fgcmValues2 = fgcmField.evaluate(xPos, yPos) 

fieldValues2 = field.evaluate(xPos, yPos) 

 

self.assertFloatsAlmostEqual(fgcmValues, fgcmValues2, rtol=5e-15) 

self.assertFloatsAlmostEqual(fgcmValues2, fieldValues2, rtol=5e-15) 

 

 

class TestMemory(lsst.utils.tests.MemoryTestCase): 

pass 

 

 

def setup_module(module): 

lsst.utils.tests.init() 

 

 

162 ↛ 163line 162 didn't jump to line 163, because the condition on line 162 was never trueif __name__ == "__main__": 

lsst.utils.tests.init() 

unittest.main()