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removed unnecessary imports from tests
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parent
bb9790acd7
commit
e46746e4ca
4 changed files with 12 additions and 22 deletions
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@ -1,16 +1,13 @@
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import autograd.numpy as np
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import os
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import random
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import string
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import copy
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import math
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import scipy.optimize
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from scipy.odr import ODR, Model, Data, RealData
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from scipy.odr import ODR, Model, RealData
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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_standard_fit():
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dim = 10 + int(30 * np.random.rand())
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x = np.arange(dim)
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@ -69,7 +66,7 @@ def test_odr_fit():
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data = RealData([o.value for o in ox], [o.value for o in oy], sx=[o.dvalue for o in ox], sy=[o.dvalue for o in oy])
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model = Model(func)
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odr = ODR(data, model, [0,0], partol=np.finfo(np.float64).eps)
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odr = ODR(data, model, [0, 0], partol=np.finfo(np.float64).eps)
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odr.set_job(fit_type=0, deriv=1)
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output = odr.run()
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@ -79,8 +76,8 @@ def test_odr_fit():
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for i in range(2):
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beta[i].gamma_method(e_tag=5, S=1.0)
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assert math.isclose(beta[i].value, output.beta[i], rel_tol=1e-5)
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assert math.isclose(output.cov_beta[i,i], beta[i].dvalue**2, rel_tol=2.5e-1), str(output.cov_beta[i,i]) + ' ' + str(beta[i].dvalue**2)
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assert math.isclose(pe.covariance(beta[0], beta[1]), output.cov_beta[0,1], rel_tol=2.5e-1)
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assert math.isclose(output.cov_beta[i, i], beta[i].dvalue ** 2, rel_tol=2.5e-1), str(output.cov_beta[i, i]) + ' ' + str(beta[i].dvalue ** 2)
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assert math.isclose(pe.covariance(beta[0], beta[1]), output.cov_beta[0, 1], rel_tol=2.5e-1)
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pe.Obs.e_tag_global = 0
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@ -94,7 +91,7 @@ def test_odr_derivatives():
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loc_xvalue = n + np.random.normal(0.0, x_err)
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x.append(pe.pseudo_Obs(loc_xvalue, x_err, str(n)))
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y.append(pe.pseudo_Obs((lambda x: x ** 2 - 1)(loc_xvalue) +
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np.random.normal(0.0, y_err), y_err, str(n)))
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np.random.normal(0.0, y_err), y_err, str(n)))
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def func(a, x):
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return a[0] + a[1] * x ** 2
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@ -103,4 +100,4 @@ def test_odr_derivatives():
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tfit = pe.fits.fit_general(x, y, func, base_step=0.1, step_ratio=1.1, num_steps=20)
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assert np.abs(np.max(np.array(list(fit1[1].deltas.values()))
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- np.array(list(tfit[1].deltas.values())))) < 10e-8
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- np.array(list(tfit[1].deltas.values())))) < 10e-8
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@ -1,18 +1,11 @@
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import sys
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sys.path.append('..')
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import autograd.numpy as np
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import os
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import random
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import math
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import string
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import copy
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import scipy.optimize
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from scipy.odr import ODR, Model, Data, RealData
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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_matrix_functions():
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dim = 3 + int(4 * np.random.rand())
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print(dim)
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@ -55,4 +48,3 @@ def test_matrix_functions():
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tmp[j].gamma_method()
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assert math.isclose(tmp[j].value, 0.0, abs_tol=1e-9), 'value ' + str(i) + ',' + str(j)
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assert math.isclose(tmp[j].dvalue, 0.0, abs_tol=1e-9), 'dvalue ' + str(i) + ',' + str(j)
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@ -8,6 +8,7 @@ import pytest
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np.random.seed(0)
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def test_dump():
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value = np.random.normal(5, 10)
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dvalue = np.abs(np.random.normal(0, 1))
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@ -38,8 +39,8 @@ def test_function_overloading():
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lambda x: np.sinh(x[0]), lambda x: np.cosh(x[0]), lambda x: np.tanh(x[0])]
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for i, f in enumerate(fs):
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t1 = f([a,b])
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t2 = pe.derived_observable(f, [a,b])
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t1 = f([a, b])
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t2 = pe.derived_observable(f, [a, b])
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c = t2 - t1
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assert c.value == 0.0, str(i)
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assert np.all(np.abs(c.deltas['e1']) < 1e-14), str(i)
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@ -4,6 +4,7 @@ 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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@ -16,4 +17,3 @@ def test_root_linear():
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assert np.isclose(my_root.value, value)
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difference = my_obs - my_root
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assert all(np.isclose(0.0, difference.deltas['t']))
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