1 | from numpy.testing import TestCase, run_module_suite |
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2 | from numpy.testing import assert_equal, assert_almost_equal |
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3 | # WARNING: numpy also has an fft object |
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4 | from aubio import specdesc, cvec |
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5 | from numpy import array, shape, arange, zeros, log |
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6 | from math import pi |
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7 | |
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8 | class aubio_specdesc(TestCase): |
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9 | |
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10 | def test_members(self): |
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11 | o = specdesc() |
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12 | assert_equal ([o.buf_size, o.method], |
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13 | [1024, "default"]) |
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14 | |
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15 | def test_hfc(self): |
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16 | o = specdesc("hfc") |
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17 | c = cvec() |
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18 | assert_equal( 0., o(c)) |
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19 | a = arange(c.length, dtype='float32') |
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20 | c.norm = a |
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21 | assert_equal (a, c.norm) |
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22 | assert_equal ( sum(a*(a+1)), o(c)) |
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23 | |
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24 | def test_complex(self): |
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25 | o = specdesc("complex") |
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26 | c = cvec() |
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27 | assert_equal( 0., o(c)) |
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28 | a = arange(c.length, dtype='float32') |
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29 | c.norm = a |
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30 | assert_equal (a, c.norm) |
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31 | # the previous run was on zeros, so previous frames are still 0 |
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32 | # so we have sqrt ( abs ( r2 ^ 2) ) == r2 |
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33 | assert_equal ( sum(a), o(c)) |
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34 | # second time. c.norm = a, so, r1 = r2, and the euclidian distance is 0 |
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35 | assert_equal ( 0, o(c)) |
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36 | |
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37 | def test_phase(self): |
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38 | o = specdesc("phase") |
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39 | c = cvec() |
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40 | assert_equal( 0., o(c)) |
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41 | |
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42 | def test_kl(self): |
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43 | o = specdesc("kl") |
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44 | c = cvec() |
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45 | assert_equal( 0., o(c)) |
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46 | a = arange(c.length, dtype='float32') |
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47 | c.norm = a |
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48 | assert_almost_equal( sum(a * log(1.+ a/1.e-10 ) ) / o(c), 1., decimal=6) |
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49 | |
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50 | def test_mkl(self): |
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51 | o = specdesc("mkl") |
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52 | c = cvec() |
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53 | assert_equal( 0., o(c)) |
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54 | a = arange(c.length, dtype='float32') |
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55 | c.norm = a |
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56 | assert_almost_equal( sum(log(1.+ a/1.e-10 ) ) / o(c), 1, decimal=6) |
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57 | |
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58 | def test_specflux(self): |
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59 | o = specdesc("specflux") |
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60 | c = cvec() |
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61 | assert_equal( 0., o(c)) |
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62 | a = arange(c.length, dtype='float32') |
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63 | c.norm = a |
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64 | assert_equal( sum(a), o(c)) |
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65 | assert_equal( 0, o(c)) |
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66 | c.norm = zeros(c.length, dtype='float32') |
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67 | assert_equal( 0, o(c)) |
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68 | |
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69 | def test_centroid(self): |
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70 | o = specdesc("centroid") |
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71 | c = cvec() |
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72 | # make sure centroid of zeros is zero |
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73 | assert_equal( 0., o(c)) |
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74 | a = arange(c.length, dtype='float32') |
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75 | c.norm = a |
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76 | centroid = sum(a*a) / sum(a) |
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77 | assert_almost_equal (centroid, o(c), decimal = 2) |
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78 | |
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79 | c.norm = a * .5 |
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80 | assert_almost_equal (centroid, o(c), decimal = 2) |
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81 | |
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82 | def test_spread(self): |
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83 | o = specdesc("spread") |
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84 | c = cvec() |
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85 | assert_equal( 0., o(c)) |
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86 | a = arange(c.length, dtype='float32') |
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87 | c.norm = a |
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88 | centroid = sum(a*a) / sum(a) |
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89 | spread = sum( (a - centroid)**2 *a) / sum(a) |
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90 | assert_almost_equal (spread, o(c), decimal = 2) |
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91 | |
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92 | c.norm = a * 3 |
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93 | assert_almost_equal (spread, o(c), decimal = 2) |
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94 | |
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95 | def test_skewness(self): |
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96 | o = specdesc("skewness") |
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97 | c = cvec() |
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98 | assert_equal( 0., o(c)) |
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99 | a = arange(c.length, dtype='float32') |
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100 | c.norm = a |
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101 | centroid = sum(a*a) / sum(a) |
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102 | spread = sum( (a - centroid)**2 *a) / sum(a) |
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103 | skewness = sum( (a - centroid)**3 *a) / sum(a) / spread **1.5 |
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104 | assert_almost_equal (skewness, o(c), decimal = 2) |
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105 | |
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106 | c.norm = a * 3 |
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107 | assert_almost_equal (skewness, o(c), decimal = 2) |
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108 | |
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109 | def test_kurtosis(self): |
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110 | o = specdesc("kurtosis") |
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111 | c = cvec() |
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112 | assert_equal( 0., o(c)) |
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113 | a = arange(c.length, dtype='float32') |
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114 | c.norm = a |
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115 | centroid = sum(a*a) / sum(a) |
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116 | spread = sum( (a - centroid)**2 *a) / sum(a) |
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117 | kurtosis = sum( (a - centroid)**4 *a) / sum(a) / spread **2 |
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118 | assert_almost_equal (kurtosis, o(c), decimal = 2) |
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119 | |
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120 | def test_slope(self): |
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121 | o = specdesc("slope") |
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122 | c = cvec() |
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123 | assert_equal( 0., o(c)) |
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124 | a = arange(c.length * 2, 0, -2, dtype='float32') |
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125 | k = arange(c.length, dtype='float32') |
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126 | c.norm = a |
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127 | num = len(a) * sum(k*a) - sum(k)*sum(a) |
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128 | den = (len(a) * sum(k**2) - sum(k)**2) |
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129 | slope = num/den/sum(a) |
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130 | assert_almost_equal (slope, o(c), decimal = 5) |
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131 | |
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132 | a = arange(0, c.length * 2, +2, dtype='float32') |
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133 | c.norm = a |
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134 | num = len(a) * sum(k*a) - sum(k)*sum(a) |
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135 | den = (len(a) * sum(k**2) - sum(k)**2) |
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136 | slope = num/den/sum(a) |
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137 | assert_almost_equal (slope, o(c), decimal = 5) |
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138 | |
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139 | a = arange(0, c.length * 2, +2, dtype='float32') |
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140 | c.norm = a * 2 |
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141 | assert_almost_equal (slope, o(c), decimal = 5) |
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142 | |
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143 | def test_decrease(self): |
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144 | o = specdesc("decrease") |
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145 | c = cvec() |
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146 | assert_equal( 0., o(c)) |
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147 | a = arange(c.length * 2, 0, -2, dtype='float32') |
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148 | k = arange(c.length, dtype='float32') |
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149 | c.norm = a |
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150 | decrease = sum((a[1:] - a [0]) / k[1:]) / sum(a[1:]) |
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151 | assert_almost_equal (decrease, o(c), decimal = 5) |
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152 | |
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153 | a = arange(0, c.length * 2, +2, dtype='float32') |
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154 | c.norm = a |
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155 | decrease = sum((a[1:] - a [0]) / k[1:]) / sum(a[1:]) |
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156 | assert_almost_equal (decrease, o(c), decimal = 5) |
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157 | |
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158 | a = arange(0, c.length * 2, +2, dtype='float32') |
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159 | c.norm = a * 2 |
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160 | decrease = sum((a[1:] - a [0]) / k[1:]) / sum(a[1:]) |
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161 | assert_almost_equal (decrease, o(c), decimal = 5) |
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162 | |
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163 | def test_rolloff(self): |
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164 | o = specdesc("rolloff") |
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165 | c = cvec() |
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166 | assert_equal( 0., o(c)) |
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167 | a = arange(c.length * 2, 0, -2, dtype='float32') |
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168 | k = arange(c.length, dtype='float32') |
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169 | c.norm = a |
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170 | cumsum = .95*sum(a*a) |
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171 | i = 0; rollsum = 0 |
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172 | while rollsum < cumsum: |
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173 | rollsum += a[i]*a[i] |
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174 | i+=1 |
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175 | rolloff = i |
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176 | assert_equal (rolloff, o(c)) |
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177 | |
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178 | if __name__ == '__main__': |
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179 | from unittest import main |
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180 | main() |
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