def test_param_serialize__from_HH_x_parameters(self):
HH_x = HH_Param({
'gamma_t': 1,
'a': 2,
'gamma_ref': 3,
'beta': 4,
's': 5,
'Gmax': 6,
'mu': 7,
'Tmax': 8,
'd': 9
})
HH_x_array = HH_x.serialize()
self.assertTrue(np.allclose(HH_x_array, [1, 2, 3, 4, 5, 6, 7, 8, 9]))
def test_plot_curves(self):
data = {
'gamma_t': 1,
'a': 2,
'gamma_ref': 3,
'beta': 4,
's': 5,
'Gmax': 6,
'mu': 7,
'Tmax': 8,
'd': 9
}
hhp = HH_Param(data)
hhp.plot_curves()
data_ = {'gamma_ref': 1, 'beta': 2, 's': 3, 'Gmax': 4}
mkzp = MKZ_Param(data_)
mkzp.plot_curves()
def test_get_damping__actual_HH_x_parameter_from_profile_350_750_01(self):
params = np.array([
0.014766, 1.00583, 0.0410009, 21.951, 0.620032, 6.44725, 151.838,
13.0971, 1
])
HH_x = HH_Param(hh.deserialize_array_to_params(params))
damping = HH_x.get_damping(strain_in_pct=np.logspace(-4, 1, num=50))
damping_bench = [
1.6815, 1.70007, 1.72351, 1.75306, 1.79029, 1.83716, 1.89609,
1.97005, 2.06272, 2.17854, 2.32286, 2.50202, 2.72343, 2.99551,
3.32759, 3.72957, 4.21139, 4.78223, 5.44944, 6.21726, 7.0856,
8.04891, 9.09572, 10.2088, 11.3664, 12.5435, 13.7147, 14.8555,
15.944, 16.9621, 17.8956, 18.7343, 19.4716, 20.104, 20.6311,
21.0548, 21.3791, 21.6099, 21.7542, 21.8197, 21.8147, 21.7478,
21.6271, 21.4606, 21.2554, 21.0184, 20.7555, 20.472, 20.1723,
19.8606
]
# The error could be high, due to curve-fitting errors of genetic algorithms
self.assertTrue(np.allclose(damping, damping_bench, atol=7.0,
rtol=0.0))
def test_get_GGmax__actual_HH_G_param_from_profile_350_750_01(self):
# Actual HH_G parameter from profile 350_750_01
params = np.array([
0.000116861, 100, 0.000314814, 1, 0.919, 9.04E+07, 0.0718012,
59528, 0.731508
])
HH_G = HH_Param(hh.deserialize_array_to_params(params))
GGmax = HH_G.get_GGmax(strain_in_pct=np.logspace(-4, 1, num=50))
GGmax_bench = [
0.994964, 0.993758, 0.992265, 0.990419, 0.988137, 0.985319,
0.981846, 0.977568, 0.972312, 0.965866, 0.957985, 0.948382,
0.936729, 0.922659, 0.905775, 0.885662, 0.861911, 0.83415,
0.802089, 0.765572, 0.724631, 0.669318, 0.612187, 0.557676,
0.50573, 0.456335, 0.409512, 0.365315, 0.323816, 0.285101,
0.249252, 0.216336, 0.186389, 0.15941, 0.13535, 0.114114,
0.0955634, 0.0795192, 0.0657761, 0.0541104, 0.0442915, 0.0360909,
0.02929, 0.0236855, 0.0190929, 0.0153483, 0.0123084, 0.00985001,
0.00786843, 0.00627576
]
self.assertTrue(np.allclose(GGmax, GGmax_bench, atol=1e-4, rtol=0.0))
def test_get_damping(self):
# Actual HH_x parameter from profile 350_750_01
params = np.array([
0.014766, 1.00583, 0.0410009, 21.951, 0.620032, 6.44725, 151.838,
13.0971, 1
])
HH_x = HH_Param(hh.deserialize_array_to_params(params))
damping = HH_x.get_damping(strain_in_pct=np.logspace(-4, 1, num=50))
damping_bench = [
1.6815, 1.70007, 1.72351, 1.75306, 1.79029, 1.83716, 1.89609,
1.97005, 2.06272, 2.17854, 2.32286, 2.50202, 2.72343, 2.99551,
3.32759, 3.72957, 4.21139, 4.78223, 5.44944, 6.21726, 7.0856,
8.04891, 9.09572, 10.2088, 11.3664, 12.5435, 13.7147, 14.8555,
15.944, 16.9621, 17.8956, 18.7343, 19.4716, 20.104, 20.6311,
21.0548, 21.3791, 21.6099, 21.7542, 21.8197, 21.8147, 21.7478,
21.6271, 21.4606, 21.2554, 21.0184, 20.7555, 20.472, 20.1723,
19.8606
]
# The error could be high, due to curve-fitting errors of genetic algorithms
self.assertTrue(np.allclose(damping, damping_bench, atol=7.0,
rtol=0.0))
# Actual H4_x parameter from IBRH17 (the 0th layer)
params = np.array([0.00062111, 0, 0.60001, 1.797])
H4_x = MKZ_Param(
mkz.deserialize_array_to_params(params, from_files=True))
damping = H4_x.get_damping(
strain_in_pct=np.geomspace(0.0001, 6, num=50))
damping_bench = [
2.3463, 2.3679, 2.3949, 2.4286, 2.4705, 2.5227, 2.5876, 2.6682,
2.768, 2.8913, 3.0433, 3.2299, 3.4578, 3.7348, 4.0692, 4.4697,
4.9449, 5.5026, 6.149, 6.8874, 7.7176, 8.6347, 9.6289, 10.686,
11.786, 12.909, 14.032, 15.134, 16.194, 17.195, 18.124, 18.971,
19.727, 20.389, 20.955, 21.425, 21.801, 22.089, 22.292, 22.417,
22.471, 22.462, 22.396, 22.282, 22.125, 21.933, 21.71, 21.463,
21.197, 20.914
]
self.assertTrue(np.allclose(damping, damping_bench, atol=7.0,
rtol=0.0))
def test_init(self):
# Test that invalid parameter names are blocked as expected
invalid_data = {'key': 1, 'lock': 2}
with self.assertRaises(KeyError,
msg='Invalid keys exist in your input'):
hhp = HH_Param(invalid_data)
# Test that querying a nonexistent parameter name produces KeyError
data = {
'gamma_t': 1,
'a': 2,
'gamma_ref': 3,
'beta': 4,
's': 5,
'Gmax': 6,
'mu': 7,
'Tmax': 8,
'd': 9
}
hhp = HH_Param(data)
with self.assertRaises(KeyError, msg="'haha'"):
hhp['haha']
def test_get_GGmax(self):
# Actual HH_G parameter from profile 350_750_01
params = np.array([
0.000116861, 100, 0.000314814, 1, 0.919, 9.04E+07, 0.0718012,
59528, 0.731508
])
HH_G = HH_Param(hh.deserialize_array_to_params(params))
GGmax = HH_G.get_GGmax(strain_in_pct=np.logspace(-4, 1, num=50))
GGmax_bench = [
0.994964, 0.993758, 0.992265, 0.990419, 0.988137, 0.985319,
0.981846, 0.977568, 0.972312, 0.965866, 0.957985, 0.948382,
0.936729, 0.922659, 0.905775, 0.885662, 0.861911, 0.83415,
0.802089, 0.765572, 0.724631, 0.669318, 0.612187, 0.557676,
0.50573, 0.456335, 0.409512, 0.365315, 0.323816, 0.285101,
0.249252, 0.216336, 0.186389, 0.15941, 0.13535, 0.114114,
0.0955634, 0.0795192, 0.0657761, 0.0541104, 0.0442915, 0.0360909,
0.02929, 0.0236855, 0.0190929, 0.0153483, 0.0123084, 0.00985001,
0.00786843, 0.00627576
]
self.assertTrue(np.allclose(GGmax, GGmax_bench, atol=1e-4, rtol=0.0))
# Actual H4_G parameter of IBRH17 (the 0th layer)
params = np.array([0.00028511, 0, 0.919, 1.7522])
H4_G = MKZ_Param(
mkz.deserialize_array_to_params(params, from_files=True))
GGmax = H4_G.get_GGmax(strain_in_pct=np.geomspace(0.0001, 6, num=50))
GGmax_bench = [
0.99038, 0.9882, 0.98553, 0.98228, 0.9783, 0.97346, 0.96758,
0.96044, 0.95182, 0.94142, 0.92895, 0.91406, 0.89641, 0.87562,
0.85135, 0.82331, 0.79127, 0.75514, 0.71502, 0.67118, 0.62415,
0.57465, 0.52361, 0.47207, 0.42112, 0.37179, 0.325, 0.28146,
0.24167, 0.20588, 0.17418, 0.14646, 0.1225, 0.10199, 0.084583,
0.069916, 0.057631, 0.047395, 0.038902, 0.03188, 0.026091, 0.02133,
0.017423, 0.01422, 0.0116, 0.0094575, 0.0077078, 0.0062797,
0.0051149, 0.0041652
]
self.assertTrue(np.allclose(GGmax, GGmax_bench, atol=1e-4, rtol=0.0))
def test_init__ensure_querying_nonexistent_parameter_name_raises_KeyError(
self):
data = {
'gamma_t': 1,
'a': 2,
'gamma_ref': 3,
'beta': 4,
's': 5,
'Gmax': 6,
'mu': 7,
'Tmax': 8,
'd': 9
}
hhp = HH_Param(data)
with self.assertRaisesRegex(KeyError, "'haha'"):
hhp['haha']
def test_init__ensure_invalid_parameter_names_are_blocked(self):
invalid_data = {'key': 1, 'lock': 2}
with self.assertRaisesRegex(KeyError,
'Invalid keys exist in your input'):
hhp = HH_Param(invalid_data)