Loading binarycpython/tests/main.py +10 −4 Original line number Diff line number Diff line # Main file for the tests. This file imports all the combined_test functions from all files. import unittest from test_c_bindings import * from test_functions import * from binarycpython.tests.test_c_bindings import * from binarycpython.tests.test_custom_logging import * from binarycpython.tests.test_distributions import * from binarycpython.tests.test_functions import * from binarycpython.tests.test_grid import * from binarycpython.tests.test_hpc_functions import * from binarycpython.tests.test_plot_functions import * from binarycpython.tests.test_run_system_wrapper import * from binarycpython.tests.test_spacing_functions import * from binarycpython.tests.test_useful_funcs import * if __name__ == '__main__': unittest.main() binarycpython/tests/test_distributions.py +188 −0 Original line number Diff line number Diff line """ Module containing the unittests for the distribution functions. """ import unittest from binarycpython.utils.distribution_functions import * from binarycpython.utils.useful_funcs import calc_sep_from_period class TestDistributions(unittest.TestCase): """ Unittest class # https://stackoverflow.com/questions/17353213/init-for-unittest-testcase """ def __init__(self, *args, **kwargs): super(TestDistributions, self).__init__(*args, **kwargs) # self.gen_stubs() self.mass_list = [0.1, 0.2, 1, 10, 15, 50] self.logper_list = [-2, -0.5, 1.6, 2.5, 5.3, 10] self.q_list = [0.01, 0.2, 0.4, 0.652, 0.823, 1] self.per_list = [10**logper for logper in self.logper_list] self.tolerance = 1e-5 def test_powerlaw(self): """ unittest for the powerlaw test """ perl_results = [0, 0, 1.30327367546194, 0.00653184128064016, 0.00257054805572128, 0.000161214690242696] python_results = [] for mass in self.mass_list: python_results.append(powerlaw(1, 100, -2.3, mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_three_part_power_law(self): """ unittest for three_part_power_law """ perl_results = [10.0001044752901, 2.03065220596677, 0.0501192469795434, 0.000251191267451594, 9.88540897458207e-05, 6.19974072148769e-06] python_results = [] for mass in self.mass_list: python_results.append(three_part_powerlaw (mass, 0.08, 0.1, 1, 300, -1.3, -2.3, -2.3)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_Kroupa2001(self): """ unittest for three_part_power_law """ perl_results = [5.71196495365248, 2.31977861075353, 0.143138195684851, 0.000717390363216896, 0.000282322598503135, 1.77061658757533e-05] python_results = [] for mass in self.mass_list: python_results.append(Kroupa2001(mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_ktg93(self): """ unittest for three_part_power_law """ perl_results = [5.79767807698379, 2.35458895566605, 0.155713799148675, 0.000310689875361984, 0.000103963454405194, 4.02817276824841e-06] python_results = [] for mass in self.mass_list: python_results.append(ktg93(mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_gaussian(self): """ unittest for three_part_power_law """ perl_results = [0.00218800520299544, 0.0121641269671571, 0.0657353455837751, 0.104951743573429, 0.16899534495487, 0.0134332780385336] python_results = [] for logper in self.logper_list: python_results.append(gaussian(logper, 4.8, 2.3, -2.0, 12.0)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_Arenou2010_binary_fraction(self): """ unittest for three_part_power_law """ perl_results = [0.123079723518677, 0.178895136157746, 0.541178340047153, 0.838798485820276, 0.838799998443204, 0.8388] python_results = [] for mass in self.mass_list: python_results.append(Arenou2010_binary_fraction(mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_raghavan2010_binary_fraction(self): """ unittest for three_part_power_law """ perl_results = [0.304872297931597, 0.334079955706623, 0.41024, 1, 1, 1] python_results = [] for mass in self.mass_list: python_results.append(raghavan2010_binary_fraction(mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_Izzard2012_period_distribution(self): """ unittest for three_part_power_law """ perl_results = [0, 0.00941322840619318, 0.0575068231479569, 0.0963349886047932, 0.177058537292581, 0.0165713385659234, 0, 0.00941322840619318, 0.0575068231479569, 0.0963349886047932, 0.177058537292581, 0.0165713385659234, 0, 0.00941322840619318, 0.0575068231479569, 0.0963349886047932, 0.177058537292581, 0.0165713385659234, 0, 7.61631504133159e-09, 0.168028727846997, 0.130936282216512, 0.0559170865520968, 0.0100358604460285, 0, 2.08432736869149e-21, 0.18713622563288, 0.143151383185002, 0.0676299576972089, 0.0192427864870784, 0, 1.1130335685003e-24, 0.194272603987661, 0.14771508552257, 0.0713078479280884, 0.0221093965810181] python_results = [] for mass in self.mass_list: for per in self.per_list: python_results.append(Izzard2012_period_distribution(per, mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_flatsections(self): """ unittest for three_part_power_law """ perl_results = [1.01010101010101, 1.01010101010101, 1.01010101010101, 1.01010101010101, 1.01010101010101, 1.01010101010101] python_results = [] for q in self.q_list: python_results.append(flatsections(q, [{'min': 0.01, 'max': 1.0, 'height': 1.0}])) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_sana12(self): """ unittest for three_part_power_law """ perl_results = [0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 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0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805, 0.481676471294883, 0.481676471294883, 0.131020615300798, 0.102503482445846, 0.0678037785559114, 0.066436408359805] python_results = [] for mass in self.mass_list: for q in self.q_list: for per in self.per_list: mass_2 = mass * q sep = calc_sep_from_period(mass, mass_2, per) sep_min = calc_sep_from_period(mass, mass_2, 10**0.15) sep_max = calc_sep_from_period(mass, mass_2, 10**5.5) python_results.append(sana12(mass, mass_2, sep, per, sep_min, sep_max, 0.15, 5.5, -0.55)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) if __name__ == '__main__': unittest.main() Loading
binarycpython/tests/main.py +10 −4 Original line number Diff line number Diff line # Main file for the tests. This file imports all the combined_test functions from all files. import unittest from test_c_bindings import * from test_functions import * from binarycpython.tests.test_c_bindings import * from binarycpython.tests.test_custom_logging import * from binarycpython.tests.test_distributions import * from binarycpython.tests.test_functions import * from binarycpython.tests.test_grid import * from binarycpython.tests.test_hpc_functions import * from binarycpython.tests.test_plot_functions import * from binarycpython.tests.test_run_system_wrapper import * from binarycpython.tests.test_spacing_functions import * from binarycpython.tests.test_useful_funcs import * if __name__ == '__main__': unittest.main()
binarycpython/tests/test_distributions.py +188 −0 Original line number Diff line number Diff line """ Module containing the unittests for the distribution functions. """ import unittest from binarycpython.utils.distribution_functions import * from binarycpython.utils.useful_funcs import calc_sep_from_period class TestDistributions(unittest.TestCase): """ Unittest class # https://stackoverflow.com/questions/17353213/init-for-unittest-testcase """ def __init__(self, *args, **kwargs): super(TestDistributions, self).__init__(*args, **kwargs) # self.gen_stubs() self.mass_list = [0.1, 0.2, 1, 10, 15, 50] self.logper_list = [-2, -0.5, 1.6, 2.5, 5.3, 10] self.q_list = [0.01, 0.2, 0.4, 0.652, 0.823, 1] self.per_list = [10**logper for logper in self.logper_list] self.tolerance = 1e-5 def test_powerlaw(self): """ unittest for the powerlaw test """ perl_results = [0, 0, 1.30327367546194, 0.00653184128064016, 0.00257054805572128, 0.000161214690242696] python_results = [] for mass in self.mass_list: python_results.append(powerlaw(1, 100, -2.3, mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_three_part_power_law(self): """ unittest for three_part_power_law """ perl_results = [10.0001044752901, 2.03065220596677, 0.0501192469795434, 0.000251191267451594, 9.88540897458207e-05, 6.19974072148769e-06] python_results = [] for mass in self.mass_list: python_results.append(three_part_powerlaw (mass, 0.08, 0.1, 1, 300, -1.3, -2.3, -2.3)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_Kroupa2001(self): """ unittest for three_part_power_law """ perl_results = [5.71196495365248, 2.31977861075353, 0.143138195684851, 0.000717390363216896, 0.000282322598503135, 1.77061658757533e-05] python_results = [] for mass in self.mass_list: python_results.append(Kroupa2001(mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_ktg93(self): """ unittest for three_part_power_law """ perl_results = [5.79767807698379, 2.35458895566605, 0.155713799148675, 0.000310689875361984, 0.000103963454405194, 4.02817276824841e-06] python_results = [] for mass in self.mass_list: python_results.append(ktg93(mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_gaussian(self): """ unittest for three_part_power_law """ perl_results = [0.00218800520299544, 0.0121641269671571, 0.0657353455837751, 0.104951743573429, 0.16899534495487, 0.0134332780385336] python_results = [] for logper in self.logper_list: python_results.append(gaussian(logper, 4.8, 2.3, -2.0, 12.0)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_Arenou2010_binary_fraction(self): """ unittest for three_part_power_law """ perl_results = [0.123079723518677, 0.178895136157746, 0.541178340047153, 0.838798485820276, 0.838799998443204, 0.8388] python_results = [] for mass in self.mass_list: python_results.append(Arenou2010_binary_fraction(mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_raghavan2010_binary_fraction(self): """ unittest for three_part_power_law """ perl_results = [0.304872297931597, 0.334079955706623, 0.41024, 1, 1, 1] python_results = [] for mass in self.mass_list: python_results.append(raghavan2010_binary_fraction(mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_Izzard2012_period_distribution(self): """ unittest for three_part_power_law """ perl_results = [0, 0.00941322840619318, 0.0575068231479569, 0.0963349886047932, 0.177058537292581, 0.0165713385659234, 0, 0.00941322840619318, 0.0575068231479569, 0.0963349886047932, 0.177058537292581, 0.0165713385659234, 0, 0.00941322840619318, 0.0575068231479569, 0.0963349886047932, 0.177058537292581, 0.0165713385659234, 0, 7.61631504133159e-09, 0.168028727846997, 0.130936282216512, 0.0559170865520968, 0.0100358604460285, 0, 2.08432736869149e-21, 0.18713622563288, 0.143151383185002, 0.0676299576972089, 0.0192427864870784, 0, 1.1130335685003e-24, 0.194272603987661, 0.14771508552257, 0.0713078479280884, 0.0221093965810181] python_results = [] for mass in self.mass_list: for per in self.per_list: python_results.append(Izzard2012_period_distribution(per, mass)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_flatsections(self): """ unittest for three_part_power_law """ perl_results = [1.01010101010101, 1.01010101010101, 1.01010101010101, 1.01010101010101, 1.01010101010101, 1.01010101010101] python_results = [] for q in self.q_list: python_results.append(flatsections(q, [{'min': 0.01, 'max': 1.0, 'height': 1.0}])) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) def test_sana12(self): """ unittest for three_part_power_law """ perl_results = [0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 0.121764808010258, 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calc_sep_from_period(mass, mass_2, per) sep_min = calc_sep_from_period(mass, mass_2, 10**0.15) sep_max = calc_sep_from_period(mass, mass_2, 10**5.5) python_results.append(sana12(mass, mass_2, sep, per, sep_min, sep_max, 0.15, 5.5, -0.55)) # GO over the results and check whether they are equal (within tolerance) for i in range(len(python_results)): self.assertLess(np.abs(python_results[i]-perl_results[i]), self.tolerance) if __name__ == '__main__': unittest.main()
