Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

fix: corrected bug that prevented combined fits with multiple x-obs in some cases #241

Merged
merged 5 commits into from
Sep 13, 2024
Merged

fix: corrected bug that prevented combined fits with multiple x-obs in some cases #241

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
a86e769
fix: corrected bug that prevented combined fits with multiple x-obs i…
Sep 13, 2024
c163268
made test more complex
Sep 13, 2024
0bce9a5
[Fix] Slightly increase tolerance for matrix function test.
fjosw Sep 13, 2024
7dcee70
Adapt test_merge_idx to compare lists
Sep 13, 2024
5d48df6
Merge branch 'fix/combined_xerr' of github.com:s-kuberski/pyerrors in…
Sep 13, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion pyerrors/fits.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -256,7 +256,7 @@ def func_b(a, x):
if sorted(list(funcd.keys())) != key_ls:
raise ValueError('x and func dictionaries do not contain the same keys.')

x_all = np.concatenate([np.array(xd[key]) for key in key_ls])
x_all = np.concatenate([np.array(xd[key]).transpose() for key in key_ls]).transpose()
y_all = np.concatenate([np.array(yd[key]) for key in key_ls])

y_f = [o.value for o in y_all]
Expand Down
14 changes: 14 additions & 0 deletions tests/fits_test.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1082,6 +1082,20 @@ def test_combined_resplot_qqplot():
fr = pe.least_squares(xd, yd, fd, resplot=True, qqplot=True)
plt.close('all')

def test_combined_fit_xerr():
fitd = {
'a' : lambda p, x: p[0] * x[0] + p[1] * x[1],
'b' : lambda p, x: p[0] * x[0] + p[2] * x[1],
'c' : lambda p, x: p[0] * x[0] + p[3] * x[1],
}
yd = {
'a': [pe.cov_Obs(3 + .1 * np.random.uniform(), .1**2, 'a' + str(i)) for i in range(5)],
'b': [pe.cov_Obs(1 + .1 * np.random.uniform(), .1**2, 'b' + str(i)) for i in range(6)],
'c': [pe.cov_Obs(3 + .1 * np.random.uniform(), .1**2, 'c' + str(i)) for i in range(3)],
}
xd = {k: np.transpose([[1 + .01 * np.random.uniform(), 2] for i in range(len(yd[k]))]) for k in fitd}
pe.fits.least_squares(xd, yd, fitd)


def test_x_multidim_fit():
x1 = np.arange(1, 10)
Expand Down
6 changes: 3 additions & 3 deletions tests/linalg_test.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -276,10 +276,10 @@ def test_matrix_functions():
for (i, j), entry in np.ndenumerate(check_inv):
entry.gamma_method()
if(i == j):
assert math.isclose(entry.value, 1.0, abs_tol=1e-9), 'value ' + str(i) + ',' + str(j) + ' ' + str(entry.value)
assert math.isclose(entry.value, 1.0, abs_tol=2e-9), 'value ' + str(i) + ',' + str(j) + ' ' + str(entry.value)
else:
assert math.isclose(entry.value, 0.0, abs_tol=1e-9), 'value ' + str(i) + ',' + str(j) + ' ' + str(entry.value)
assert math.isclose(entry.dvalue, 0.0, abs_tol=1e-9), 'dvalue ' + str(i) + ',' + str(j) + ' ' + str(entry.dvalue)
assert math.isclose(entry.value, 0.0, abs_tol=2e-9), 'value ' + str(i) + ',' + str(j) + ' ' + str(entry.value)
assert math.isclose(entry.dvalue, 0.0, abs_tol=2e-9), 'dvalue ' + str(i) + ',' + str(j) + ' ' + str(entry.dvalue)

# Check Cholesky decomposition
sym = np.dot(matrix, matrix.T)
Expand Down
6 changes: 3 additions & 3 deletions tests/obs_test.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -554,11 +554,11 @@ def test_merge_idx():

for j in range(5):
idll = [range(1, int(round(np.random.uniform(300, 700))), int(round(np.random.uniform(1, 14)))) for i in range(10)]
assert pe.obs._merge_idx(idll) == sorted(set().union(*idll))
assert list(pe.obs._merge_idx(idll)) == sorted(set().union(*idll))

for j in range(5):
idll = [range(int(round(np.random.uniform(1, 28))), int(round(np.random.uniform(300, 700))), int(round(np.random.uniform(1, 14)))) for i in range(10)]
assert pe.obs._merge_idx(idll) == sorted(set().union(*idll))
assert list(pe.obs._merge_idx(idll)) == sorted(set().union(*idll))

idl = [list(np.arange(1, 14)) + list(range(16, 100, 4)), range(4, 604, 4), [2, 4, 5, 6, 8, 9, 12, 24], range(1, 20, 1), range(50, 789, 7)]
new_idx = pe.obs._merge_idx(idl)
Expand Down Expand Up @@ -1457,4 +1457,4 @@ def test_missing_replica():

for op in [[O1O2, O1O2b], [O1O2O3, O1O2O3b]]:
assert np.isclose(op[1].value, op[0].value)
assert np.isclose(op[1].dvalue, op[0].dvalue, atol=0, rtol=5e-2)
assert np.isclose(op[1].dvalue, op[0].dvalue, atol=0, rtol=5e-2)