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54 lines
1.2 KiB
Python
54 lines
1.2 KiB
Python
import numpy as np
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import pyerrors as pe
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import pytest
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np.random.seed(0)
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def test_root_linear():
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def root_function(x, d):
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return x - d
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value = np.random.normal(0, 100)
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my_obs = pe.pseudo_Obs(value, 0.1, 't')
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my_root = pe.roots.find_root(my_obs, root_function)
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assert np.isclose(my_root.value, value)
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assert np.isclose(my_root.value, my_root.r_values['t'])
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difference = my_obs - my_root
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assert difference.is_zero()
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def test_root_linear_idl():
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def root_function(x, d):
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return x - d
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my_obs = pe.Obs([np.random.rand(50)], ['t'], idl=[range(20, 120, 2)])
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my_root = pe.roots.find_root(my_obs, root_function)
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difference = my_obs - my_root
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assert difference.is_zero()
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def test_root_no_autograd():
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def root_function(x, d):
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return x - np.log(np.exp(d))
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value = np.random.normal(0, 100)
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my_obs = pe.pseudo_Obs(value, 0.1, 't')
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with pytest.raises(Exception):
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my_root = pe.roots.find_root(my_obs, root_function)
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def test_root_multi_parameter():
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o1 = pe.pseudo_Obs(1.1, 0.1, "test")
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o2 = pe.pseudo_Obs(1.3, 0.12, "test")
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f2 = lambda x, d: d[0] + d[1] * x
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assert f2(-o1 / o2, [o1, o2]) == 0
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assert pe.find_root([o1, o2], f2) == -o1 / o2
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