Searched refs:np (Results 1 – 3 of 3) sorted by relevance
| /honee/tests/ |
| H A D | smartsim_regression_framework.py | 6 import numpy as np namespace
43 assert np.all(test == truth)
65 if not np.allclose(database_array, correct_array, atol=atol, rtol=rtol):
67 … total_tolerances = atol + rtol * np.abs(correct_array) # mimic np.allclose tolerance calculation
68 idx_notclose = np.where(np.abs(database_array - correct_array) > total_tolerances)
69 if not np.all(idx_notclose[1] == 4):
75 test_fail = False if np.allclose(-database_vorticity, correct_vorticity,
81 np.save(database_output_path, database_array)
146 assert_np_all(client.get_tensor("sizeInfo"), np.array([35, 12, 6, 1, 1, 0]))
163 correct_value = np.load(test_data_path)
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| /honee/tests/createPyTorchModel/ |
| H A D | update_weights.py | 5 import numpy as np namespace
12 weights.append(np.loadtxt(new_parameters_Path / 'w1.dat', skiprows=1).reshape(6, 20).T)
13 weights.append(np.loadtxt(new_parameters_Path / 'w2.dat', skiprows=1).reshape(20, 6).T)
14 biases.append(np.loadtxt(new_parameters_Path / 'b1.dat', skiprows=1))
15 biases.append(np.loadtxt(new_parameters_Path / 'b2.dat', skiprows=1))
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| /honee/examples/postprocess/ |
| H A D | vortexshedding.py | 4 import numpy as np namespace
9 S = np.pi * D * zspan # surface area
16 period = np.diff(sample["Time"].iloc[peaks])
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