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Merge branch 'develop' into documentation

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fjosw 2023-10-24 17:31:15 +00:00
commit bdb7c7e2ee
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47
tests/fits_test.py
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@ -1142,6 +1142,53 @@ def test_fit_dof():
assert cd[0] != cd[0] # Check for nan
assert np.all(np.array(cd[1:]) > 0)
N = 5
def fitf(a, x):
return a[0] + 0 * x
def fitf_multi(a, x):
return a[0] + 0 * x[0] + 0*x[1]
for priors in [None, [pe.cov_Obs(3, 1, 'p')]]:
if priors is None:
lp = 0
else:
lp = len(priors)
x = [1. for i in range(N)]
y = [pe.cov_Obs(i, .1, '%d' % (i)) for i in range(N)]
[o.gm() for o in y]
res = pe.fits.least_squares(x, y, fitf, expected_chisquare=True, priors=priors)
assert(res.dof == N - 1 + lp)
if priors is None:
assert(np.isclose(res.chisquare_by_expected_chisquare, res.chisquare_by_dof))
kl = ['a', 'b']
x = {k: [1. for i in range(N)] for k in kl}
y = {k: [pe.cov_Obs(i, .1, '%d%s' % (i, k)) for i in range(N)] for k in kl}
[[o.gm() for o in y[k]] for k in y]
res = pe.fits.least_squares(x, y, {k: fitf for k in kl}, expected_chisquare=True, priors=priors)
assert(res.dof == 2 * N - 1 + lp)
if priors is None:
assert(np.isclose(res.chisquare_by_expected_chisquare, res.chisquare_by_dof))
x = np.array([[1., 2.] for i in range(N)]).T
y = [pe.cov_Obs(i, .1, '%d' % (i)) for i in range(N)]
[o.gm() for o in y]
res = pe.fits.least_squares(x, y, fitf_multi, expected_chisquare=True, priors=priors)
assert(res.dof == N - 1 + lp)
if priors is None:
assert(np.isclose(res.chisquare_by_expected_chisquare, res.chisquare_by_dof))
x = {k: np.array([[1., 2.] for i in range(N)]).T for k in kl}
y = {k: [pe.cov_Obs(i, .1, '%d%s' % (i, k)) for i in range(N)] for k in kl}
[[o.gm() for o in y[k]] for k in y]
res = pe.fits.least_squares(x, y, {k: fitf_multi for k in kl}, expected_chisquare=True, priors=priors)
assert(res.dof == 2 * N - 1 + lp)
if priors is None:
assert(np.isclose(res.chisquare_by_expected_chisquare, res.chisquare_by_dof))
def test_combined_fit_constant_shape():
N1 = 16