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 2021-12-07 08:15:42 +00:00
commit 97334aa841
3 changed files with 76 additions and 151 deletions
Download patch file Download diff file Expand all files Collapse all files

47
tests/linalg_test.py
View file

@ -29,25 +29,26 @@ def get_complex_matrix(dimension):
def test_matmul():
for dim in [4, 8]:
my_list = []
length = 1000 + np.random.randint(200)
for i in range(dim ** 2):
my_list.append(pe.Obs([np.random.rand(length), np.random.rand(length + 1)], ['t1', 't2']))
my_array = np.array(my_list).reshape((dim, dim))
tt = pe.linalg.matmul(my_array, my_array) - my_array @ my_array
for t, e in np.ndenumerate(tt):
assert e.is_zero(), t
for dim in [4, 6]:
for const in [1, pe.cov_Obs([1.0, 1.0], [[0.001,0.0001], [0.0001, 0.002]], 'norm')[1]]:
my_list = []
length = 100 + np.random.randint(200)
for i in range(dim ** 2):
my_list.append(pe.Obs([np.random.rand(length), np.random.rand(length + 1)], ['t1', 't2']))
my_array = const * np.array(my_list).reshape((dim, dim))
tt = pe.linalg.matmul(my_array, my_array) - my_array @ my_array
for t, e in np.ndenumerate(tt):
assert e.is_zero(), t
my_list = []
length = 1000 + np.random.randint(200)
for i in range(dim ** 2):
my_list.append(pe.CObs(pe.Obs([np.random.rand(length), np.random.rand(length + 1)], ['t1', 't2']),
pe.Obs([np.random.rand(length), np.random.rand(length + 1)], ['t1', 't2'])))
my_array = np.array(my_list).reshape((dim, dim))
tt = pe.linalg.matmul(my_array, my_array) - my_array @ my_array
for t, e in np.ndenumerate(tt):
assert e.is_zero(), t
my_list = []
length = 100 + np.random.randint(200)
for i in range(dim ** 2):
my_list.append(pe.CObs(pe.Obs([np.random.rand(length), np.random.rand(length + 1)], ['t1', 't2']),
pe.Obs([np.random.rand(length), np.random.rand(length + 1)], ['t1', 't2'])))
my_array = np.array(my_list).reshape((dim, dim)) * const
tt = pe.linalg.matmul(my_array, my_array) - my_array @ my_array
for t, e in np.ndenumerate(tt):
assert e.is_zero(), t
def test_jack_matmul():
@ -152,7 +153,7 @@ def test_multi_dot():
length = 1000 + np.random.randint(200)
for i in range(dim ** 2):
my_list.append(pe.Obs([np.random.rand(length), np.random.rand(length + 1)], ['t1', 't2']))
my_array = np.array(my_list).reshape((dim, dim))
my_array = pe.cov_Obs(1.0, 0.002, 'cov') * np.array(my_list).reshape((dim, dim))
tt = pe.linalg.matmul(my_array, my_array, my_array, my_array) - my_array @ my_array @ my_array @ my_array
for t, e in np.ndenumerate(tt):
assert e.is_zero(), t
@ -162,7 +163,7 @@ def test_multi_dot():
for i in range(dim ** 2):
my_list.append(pe.CObs(pe.Obs([np.random.rand(length), np.random.rand(length + 1)], ['t1', 't2']),
pe.Obs([np.random.rand(length), np.random.rand(length + 1)], ['t1', 't2'])))
my_array = np.array(my_list).reshape((dim, dim))
my_array = np.array(my_list).reshape((dim, dim)) * pe.cov_Obs(1.0, 0.002, 'cov')
tt = pe.linalg.matmul(my_array, my_array, my_array, my_array) - my_array @ my_array @ my_array @ my_array
for t, e in np.ndenumerate(tt):
assert e.is_zero(), t
@ -188,13 +189,13 @@ def test_matmul_irregular_histories():
standard_array = []
for i in range(dim ** 2):
standard_array.append(pe.Obs([np.random.normal(1.1, 0.2, length)], ['ens1']))
standard_matrix = np.array(standard_array).reshape((dim, dim))
standard_matrix = np.array(standard_array).reshape((dim, dim)) * pe.cov_Obs(1.0, 0.002, 'cov') * pe.pseudo_Obs(0.1, 0.002, 'qr')
for idl in [range(1, 501, 2), range(250, 273), [2, 8, 19, 20, 78]]:
irregular_array = []
for i in range(dim ** 2):
irregular_array.append(pe.Obs([np.random.normal(1.1, 0.2, len(idl))], ['ens1'], idl=[idl]))
irregular_matrix = np.array(irregular_array).reshape((dim, dim))
irregular_matrix = np.array(irregular_array).reshape((dim, dim)) * pe.cov_Obs([1.0, 1.0], [[0.001,0.0001], [0.0001, 0.002]], 'norm')[0]
t1 = standard_matrix @ irregular_matrix
t2 = pe.linalg.matmul(standard_matrix, irregular_matrix)
@ -212,7 +213,7 @@ def test_irregular_matrix_inverse():
irregular_array = []
for i in range(dim ** 2):
irregular_array.append(pe.Obs([np.random.normal(1.1, 0.2, len(idl)), np.random.normal(0.25, 0.1, 10)], ['ens1', 'ens2'], idl=[idl, range(1, 11)]))
irregular_matrix = np.array(irregular_array).reshape((dim, dim))
irregular_matrix = np.array(irregular_array).reshape((dim, dim)) * pe.cov_Obs(1.0, 0.002, 'cov') * pe.pseudo_Obs(1.0, 0.002, 'ens2|r23')
invertible_irregular_matrix = np.identity(dim) + irregular_matrix @ irregular_matrix.T