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removed unnecessary imports from tests

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This commit is contained in:
Fabian Joswig 2021-10-15 14:13:06 +01:00
parent bb9790acd7
commit e46746e4ca
4 changed files with 12 additions and 22 deletions
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17
tests/test_fits.py
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@ -1,16 +1,13 @@
import autograd.numpy as np
import os
import random
import string
import copy
import math
import scipy.optimize
from scipy.odr import ODR, Model, Data, RealData
from scipy.odr import ODR, Model, RealData
import pyerrors as pe
import pytest
np.random.seed(0)
def test_standard_fit():
dim = 10 + int(30 * np.random.rand())
x = np.arange(dim)
@ -69,7 +66,7 @@ def test_odr_fit():
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])
model = Model(func)
odr = ODR(data, model, [0,0], partol=np.finfo(np.float64).eps)
odr = ODR(data, model, [0, 0], partol=np.finfo(np.float64).eps)
odr.set_job(fit_type=0, deriv=1)
output = odr.run()
@ -79,8 +76,8 @@ def test_odr_fit():
for i in range(2):
beta[i].gamma_method(e_tag=5, S=1.0)
assert math.isclose(beta[i].value, output.beta[i], rel_tol=1e-5)
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)
assert math.isclose(pe.covariance(beta[0], beta[1]), output.cov_beta[0,1], rel_tol=2.5e-1)
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)
assert math.isclose(pe.covariance(beta[0], beta[1]), output.cov_beta[0, 1], rel_tol=2.5e-1)
pe.Obs.e_tag_global = 0
@ -94,7 +91,7 @@ def test_odr_derivatives():
loc_xvalue = n + np.random.normal(0.0, x_err)
x.append(pe.pseudo_Obs(loc_xvalue, x_err, str(n)))
y.append(pe.pseudo_Obs((lambda x: x ** 2 - 1)(loc_xvalue) +
np.random.normal(0.0, y_err), y_err, str(n)))
np.random.normal(0.0, y_err), y_err, str(n)))
def func(a, x):
return a[0] + a[1] * x ** 2
@ -103,4 +100,4 @@ def test_odr_derivatives():
tfit = pe.fits.fit_general(x, y, func, base_step=0.1, step_ratio=1.1, num_steps=20)
assert np.abs(np.max(np.array(list(fit1[1].deltas.values()))
- np.array(list(tfit[1].deltas.values())))) < 10e-8
- np.array(list(tfit[1].deltas.values())))) < 10e-8