lattice/pyerrors
1
0
Fork 0
mirror of https://github.com/fjosw/pyerrors.git synced 2025-05-15 03:53:41 +02:00
Code Issues Projects Releases Packages Wiki Activity

Merge branch 'develop' into documentation

Browse source
This commit is contained in:
fjosw 2023-01-10 10:34:57 +00:00
commit 9c3c270b58
2 changed files with 17 additions and 5 deletions
Download patch file Download diff file Expand all files Collapse all files

12
pyerrors/roots.py
View file

@ -27,15 +27,17 @@ def find_root(d, func, guess=1.0, **kwargs):
Obs Obs
`Obs` valued root of the function. `Obs` valued root of the function.
''' '''
root = scipy.optimize.fsolve(func, guess, d.value) d_val = np.vectorize(lambda x: x.value)(np.array(d))
root = scipy.optimize.fsolve(func, guess, d_val)
# Error propagation as detailed in arXiv:1809.01289 # Error propagation as detailed in arXiv:1809.01289
dx = jacobian(func)(root[0], d.value) dx = jacobian(func)(root[0], d_val)
try: try:
da = jacobian(lambda u, v: func(v, u))(d.value, root[0]) da = jacobian(lambda u, v: func(v, u))(d_val, root[0])
except TypeError: except TypeError:
raise Exception("It is required to use autograd.numpy instead of numpy within root functions, see the documentation for details.") from None raise Exception("It is required to use autograd.numpy instead of numpy within root functions, see the documentation for details.") from None
deriv = - da / dx deriv = - da / dx
res = derived_observable(lambda x, **kwargs: (x[0] + np.finfo(np.float64).eps) / (np.array(d).reshape(-1)[0].value + np.finfo(np.float64).eps) * root[0],
res = derived_observable(lambda x, **kwargs: (x[0] + np.finfo(np.float64).eps) / (d.value + np.finfo(np.float64).eps) * root[0], [d], man_grad=[deriv]) np.array(d).reshape(-1), man_grad=np.array(deriv).reshape(-1))
return res return res

10
tests/roots_test.py
View file

@ -42,3 +42,13 @@ def test_root_no_autograd():
with pytest.raises(Exception): with pytest.raises(Exception):
my_root = pe.roots.find_root(my_obs, root_function) my_root = pe.roots.find_root(my_obs, root_function)
def test_root_multi_parameter():
o1 = pe.pseudo_Obs(1.1, 0.1, "test")
o2 = pe.pseudo_Obs(1.3, 0.12, "test")
f2 = lambda x, d: d[0] + d[1] * x
assert f2(-o1 / o2, [o1, o2]) == 0
assert pe.find_root([o1, o2], f2) == -o1 / o2