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[Fix] Removed the possibility to create an Obs from data on several replica

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This commit is contained in:
Simon Kuberski 2025-02-17 18:59:45 +01:00
parent 6ed6ce6113
commit f2fb69a79d
6 changed files with 67 additions and 29 deletions
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14
tests/linalg_test.py
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@ -34,7 +34,7 @@ def test_matmul():
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_list.append(pe.Obs([np.random.rand(length)], ['t1']) + pe.Obs([np.random.rand(length + 1)], ['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):
@ -43,8 +43,8 @@ def test_matmul():
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_list.append(pe.CObs(pe.Obs([np.random.rand(length)], ['t1']) + pe.Obs([np.random.rand(length + 1)], ['t2']),
pe.Obs([np.random.rand(length)], ['t1']) + pe.Obs([np.random.rand(length + 1)], ['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):
@ -151,7 +151,7 @@ def test_multi_dot():
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_list.append(pe.Obs([np.random.rand(length)], ['t1']) + pe.Obs([np.random.rand(length + 1)], ['t2']))
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):
@ -160,8 +160,8 @@ def test_multi_dot():
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_list.append(pe.CObs(pe.Obs([np.random.rand(length)], ['t1']) + pe.Obs([np.random.rand(length + 1)], ['t2']),
pe.Obs([np.random.rand(length)], ['t1']) + pe.Obs([np.random.rand(length + 1)], ['t2'])))
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):
@ -209,7 +209,7 @@ def test_irregular_matrix_inverse():
for idl in [range(8, 508, 10), range(250, 273), [2, 8, 19, 20, 78, 99, 828, 10548979]]:
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_array.append(pe.Obs([np.random.normal(1.1, 0.2, len(idl))], ['ens1'], idl=[idl]) + pe.Obs([np.random.normal(0.25, 0.1, 10)], ['ens2'], idl=[range(1, 11)]))
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