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tests: slightly reduced tolerance and good guess bad guess test.

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Fabian Joswig 2023-07-13 12:23:04 +01:00
parent 319232f964
commit 199e06c5f9
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1 changed files with 3 additions and 3 deletions
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6
tests/fits_test.py
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@ -235,12 +235,12 @@ def test_fit_corr_independent():
def test_linear_fit_guesses(): def test_linear_fit_guesses():
for err in [10, 0.1, 0.001]: for err in [1.2, 0.1, 0.001]:
xvals = [] xvals = []
yvals = [] yvals = []
for x in range(1, 8, 2): for x in range(1, 8, 2):
xvals.append(x) xvals.append(x)
yvals.append(pe.pseudo_Obs(x + np.random.normal(0.0, err), err, 'test1') + pe.pseudo_Obs(0, err / 100, 'test2', samples=87)) yvals.append(pe.pseudo_Obs(x + np.random.normal(0.0, err), err, 'test1') + pe.pseudo_Obs(0, err / 97, 'test2', samples=87))
lin_func = lambda a, x: a[0] + a[1] * x lin_func = lambda a, x: a[0] + a[1] * x
with pytest.raises(Exception): with pytest.raises(Exception):
pe.least_squares(xvals, yvals, lin_func) pe.least_squares(xvals, yvals, lin_func)
@ -251,7 +251,7 @@ def test_linear_fit_guesses():
bad_guess = pe.least_squares(xvals, yvals, lin_func, initial_guess=[999, 999]) bad_guess = pe.least_squares(xvals, yvals, lin_func, initial_guess=[999, 999])
good_guess = pe.least_squares(xvals, yvals, lin_func, initial_guess=[0, 1]) good_guess = pe.least_squares(xvals, yvals, lin_func, initial_guess=[0, 1])
assert np.isclose(bad_guess.chisquare, good_guess.chisquare, atol=1e-8) assert np.isclose(bad_guess.chisquare, good_guess.chisquare, atol=1e-8)
assert np.all([(go - ba).is_zero(atol=1e-6) for (go, ba) in zip(good_guess, bad_guess)]) assert np.all([(go - ba).is_zero(atol=5e-5) for (go, ba) in zip(good_guess, bad_guess)])
def test_total_least_squares(): def test_total_least_squares():