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

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

from builtins import zip 

import matplotlib 

matplotlib.use("Agg") 

import numpy as np 

import unittest 

import lsst.sims.maf.metrics as metrics 

import lsst.utils.tests 

 

 

class TestSimpleMetrics(unittest.TestCase): 

 

def setUp(self): 

dv = np.arange(0, 10, .5) 

dv2 = np.arange(-10, 10.25, .5) 

self.dv = np.array(list(zip(dv)), dtype=[('testdata', 'float')]) 

self.dv2 = np.array(list(zip(dv2)), dtype=[('testdata', 'float')]) 

 

def testMaxMetric(self): 

"""Test max metric.""" 

testmetric = metrics.MaxMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), self.dv['testdata'].max()) 

 

def testMinMetric(self): 

"""Test min metric.""" 

testmetric = metrics.MinMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), self.dv['testdata'].min()) 

 

def testMeanMetric(self): 

"""Test mean metric.""" 

testmetric = metrics.MeanMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), self.dv['testdata'].mean()) 

 

def testMedianMetric(self): 

"""Test median metric.""" 

testmetric = metrics.MedianMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), np.median(self.dv['testdata'])) 

 

def testAbsMedianMetric(self): 

testmetric = metrics.AbsMedianMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), np.abs(np.median(self.dv['testdata']))) 

 

def testFullRangeMetric(self): 

"""Test full range metric.""" 

testmetric = metrics.FullRangeMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), self.dv['testdata'].max()-self.dv['testdata'].min()) 

 

def testCoaddm5Metric(self): 

"""Test coaddm5 metric.""" 

testmetric = metrics.Coaddm5Metric(m5Col='testdata') 

self.assertEqual(testmetric.run(self.dv), 1.25 * np.log10(np.sum(10.**(.8*self.dv['testdata'])))) 

 

def testRmsMetric(self): 

"""Test rms metric.""" 

testmetric = metrics.RmsMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), np.std(self.dv['testdata'])) 

 

def testSumMetric(self): 

"""Test Sum metric.""" 

testmetric = metrics.SumMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), self.dv['testdata'].sum()) 

 

def testCountUniqueMetric(self): 

"""Test CountUniqueMetric""" 

testmetric = metrics.CountUniqueMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), np.size(np.unique(self.dv['testdata']))) 

d2 = self.dv.copy() 

d2['testdata'][1] = d2['testdata'][0] 

self.assertEqual(testmetric.run(d2), np.size(np.unique(d2))) 

 

def testCountMetric(self): 

"""Test count metric.""" 

testmetric = metrics.CountMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), np.size(self.dv['testdata'])) 

 

def testCountRatioMetric(self): 

"""Test countratio metric.""" 

testmetric = metrics.CountRatioMetric('testdata', normVal=2.) 

self.assertEqual(testmetric.run(self.dv), np.size(self.dv['testdata'])/2.0) 

 

def testCountSubsetMetric(self): 

"""Test countsubset metric.""" 

testmetric = metrics.CountSubsetMetric('testdata', subset=0) 

self.assertEqual(testmetric.run(self.dv), 1) 

 

def testMaxPercentMetric(self): 

testmetric = metrics.MaxPercentMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), 1.0/len(self.dv)*100.0) 

self.assertEqual(testmetric.run(self.dv2), 1.0/len(self.dv2)*100.0) 

 

def testAbsMaxPercentMetric(self): 

testmetric = metrics.AbsMaxPercentMetric('testdata') 

self.assertEqual(testmetric.run(self.dv), 1./len(self.dv)*100.) 

self.assertEqual(testmetric.run(self.dv2), 2./len(self.dv2)*100.) 

 

def testRobustRmsMetric(self): 

"""Test Robust RMS metric.""" 

testmetric = metrics.RobustRmsMetric('testdata') 

rms_approx = (np.percentile(self.dv['testdata'], 75) - np.percentile(self.dv['testdata'], 25)) / 1.349 

self.assertEqual(testmetric.run(self.dv), rms_approx) 

 

def testFracAboveMetric(self): 

cutoff = 5.1 

testmetric = metrics.FracAboveMetric('testdata', cutoff=cutoff) 

self.assertEqual(testmetric.run(self.dv), 

np.size(np.where(self.dv['testdata'] >= cutoff)[0])/float(np.size(self.dv))) 

testmetric = metrics.FracAboveMetric('testdata', cutoff=cutoff, scale=2) 

self.assertEqual(testmetric.run(self.dv), 

2.0*np.size(np.where(self.dv['testdata'] >= cutoff)[0])/float(np.size(self.dv))) 

 

def testFracBelowMetric(self): 

cutoff = 5.1 

testmetric = metrics.FracBelowMetric('testdata', cutoff=cutoff) 

self.assertEqual(testmetric.run(self.dv), 

np.size(np.where(self.dv['testdata'] <= cutoff)[0])/float(np.size(self.dv))) 

testmetric = metrics.FracBelowMetric('testdata', cutoff=cutoff, scale=2) 

self.assertEqual(testmetric.run(self.dv), 

2.0*np.size(np.where(self.dv['testdata'] <= cutoff)[0])/float(np.size(self.dv))) 

 

def testNoutliersNsigma(self): 

data = self.dv 

testmetric = metrics.NoutliersNsigmaMetric('testdata', nSigma=1.) 

med = np.mean(data['testdata']) 

shouldBe = np.size(np.where(data['testdata'] > med + data['testdata'].std())[0]) 

self.assertEqual(shouldBe, testmetric.run(data)) 

testmetric = metrics.NoutliersNsigmaMetric('testdata', nSigma=-1.) 

shouldBe = np.size(np.where(data['testdata'] < med - data['testdata'].std())[0]) 

self.assertEqual(shouldBe, testmetric.run(data)) 

 

def testMeanAngleMetric(self): 

"""Test mean angle metric.""" 

rng = np.random.RandomState(6573) 

dv1 = np.arange(0, 32, 2.5) 

dv2 = (dv1 - 20.0) % 360. 

dv1 = np.array(list(zip(dv1)), dtype=[('testdata', 'float')]) 

dv2 = np.array(list(zip(dv2)), dtype=[('testdata', 'float')]) 

testmetric = metrics.MeanAngleMetric('testdata') 

result1 = testmetric.run(dv1) 

result2 = testmetric.run(dv2) 

self.assertAlmostEqual(result1, (result2+20)%360.) 

dv = rng.rand(10000)*360.0 

dv = dv 

dv = np.array(list(zip(dv)), dtype=[('testdata', 'float')]) 

result = testmetric.run(dv) 

result = result 

self.assertAlmostEqual(result, 180) 

 

def testFullRangeAngleMetric(self): 

"""Test full range angle metric.""" 

rng = np.random.RandomState(5422) 

dv1 = np.arange(0, 32, 2.5) 

dv2 = (dv1 - 20.0) % 360. 

dv1 = np.array(list(zip(dv1)), dtype=[('testdata', 'float')]) 

dv2 = np.array(list(zip(dv2)), dtype=[('testdata', 'float')]) 

testmetric = metrics.FullRangeAngleMetric('testdata') 

result1 = testmetric.run(dv1) 

result2 = testmetric.run(dv2) 

self.assertAlmostEqual(result1, result2) 

dv = np.arange(0, 358, 5) 

dv = np.array(list(zip(dv)), dtype=[('testdata', 'float')]) 

result = testmetric.run(dv) 

self.assertAlmostEqual(result, 355) 

dv = rng.rand(10000)*360.0 

dv = np.array(list(zip(dv)), dtype=[('testdata', 'float')]) 

result = testmetric.run(dv) 

result = result 

self.assertGreater(result, 355) 

 

 

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

pass 

 

 

def setup_module(module): 

lsst.utils.tests.init() 

 

 

177 ↛ 178line 177 didn't jump to line 178, because the condition on line 177 was never trueif __name__ == "__main__": 

lsst.utils.tests.init() 

unittest.main()