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Merge branch 'develop' into documentation

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fjosw 2022-07-01 15:46:56 +00:00
commit 40c27e98e8
5 changed files with 107 additions and 6 deletions
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5
tests/fits_test.py
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@ -61,7 +61,6 @@ def test_least_squares():
beta[i].gamma_method(S=1.0)
assert math.isclose(beta[i].value, popt[i], abs_tol=1e-5)
assert math.isclose(pcov[i, i], beta[i].dvalue ** 2, abs_tol=1e-3)
assert math.isclose(pe.covariance([beta[0], beta[1]])[0, 1], pcov[0, 1], abs_tol=1e-3)
chi2_pyerrors = np.sum(((f(x, *[o.value for o in beta]) - y) / yerr) ** 2) / (len(x) - 2)
chi2_scipy = np.sum(((f(x, *popt) - y) / yerr) ** 2) / (len(x) - 2)
@ -82,7 +81,6 @@ def test_least_squares():
betac[i].gamma_method(S=1.0)
assert math.isclose(betac[i].value, popt[i], abs_tol=1e-5)
assert math.isclose(pcov[i, i], betac[i].dvalue ** 2, abs_tol=1e-3)
assert math.isclose(pe.covariance([betac[0], betac[1]])[0, 1], pcov[0, 1], abs_tol=1e-3)
def test_alternative_solvers():
@ -243,7 +241,6 @@ def test_total_least_squares():
beta[i].gamma_method(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]])[0, 1], output.cov_beta[0, 1], rel_tol=3.5e-1)
out = pe.total_least_squares(ox, oy, func, const_par=[beta[1]])
@ -266,7 +263,6 @@ def test_total_least_squares():
betac[i].gamma_method(S=1.0)
assert math.isclose(betac[i].value, output.beta[i], rel_tol=1e-3)
assert math.isclose(output.cov_beta[i, i], betac[i].dvalue ** 2, rel_tol=2.5e-1), str(output.cov_beta[i, i]) + ' ' + str(betac[i].dvalue ** 2)
assert math.isclose(pe.covariance([betac[0], betac[1]])[0, 1], output.cov_beta[0, 1], rel_tol=3.5e-1)
outc = pe.total_least_squares(oxc, oyc, func, const_par=[betac[1]])
@ -281,7 +277,6 @@ def test_total_least_squares():
betac[i].gamma_method(S=1.0)
assert math.isclose(betac[i].value, output.beta[i], rel_tol=1e-3)
assert math.isclose(output.cov_beta[i, i], betac[i].dvalue ** 2, rel_tol=2.5e-1), str(output.cov_beta[i, i]) + ' ' + str(betac[i].dvalue ** 2)
assert math.isclose(pe.covariance([betac[0], betac[1]])[0, 1], output.cov_beta[0, 1], rel_tol=3.5e-1)
outc = pe.total_least_squares(oxc, oy, func, const_par=[betac[1]])

30
tests/pandas_test.py Normal file
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@ -0,0 +1,30 @@
import numpy as np
import pandas as pd
import pyerrors as pe
def test_df_export_import(tmp_path):
my_dict = {"int": 1,
"float": -0.01,
"Obs1": pe.pseudo_Obs(87, 21, "test_ensemble"),
"Obs2": pe.pseudo_Obs(-87, 21, "test_ensemble2")}
for gz in [True, False]:
my_df = pd.DataFrame([my_dict] * 10)
pe.input.pandas.dump_df(my_df, (tmp_path / 'df_output').as_posix(), gz=gz)
reconstructed_df = pe.input.pandas.load_df((tmp_path / 'df_output').as_posix(), auto_gamma=True, gz=gz)
assert np.all(my_df == reconstructed_df)
pe.input.pandas.load_df((tmp_path / 'df_output.csv').as_posix(), gz=gz)
def test_df_Corr(tmp_path):
my_corr = pe.Corr([pe.pseudo_Obs(-0.48, 0.04, "test"), pe.pseudo_Obs(-0.154, 0.03, "test")])
my_dict = {"int": 1,
"float": -0.01,
"Corr": my_corr}
my_df = pd.DataFrame([my_dict] * 5)
pe.input.pandas.dump_df(my_df, (tmp_path / 'df_output').as_posix())
reconstructed_df = pe.input.pandas.load_df((tmp_path / 'df_output').as_posix(), auto_gamma=True)