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scipy-1.11.4-openblas-0.3.26.log
=================================== FAILURES ===================================
______________________________ test_verify_cases _______________________________
[gw12] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/linalg/tests/test_decomp_polar.py:89: in test_verify_cases
verify_polar(a)
a = [[1, 2, 3]]
lib/python3.11/site-packages/scipy/linalg/tests/test_decomp_polar.py:77: in verify_polar
evals = eigh(p, eigvals_only=True)
a = [[1, 2, 3]]
aa = array([[1, 2, 3]])
evals = array([-2.33173715e-16, 9.43958368e-17, 3.74165739e+00])
m = 1
n = 3
nonzero_evals = array([3.74165739])
p = array([[3.74165739]])
product_atol = 1.4901161193847656e-08
u = array([[0.26726124, 0.53452248, 0.80178373]])
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'N'
a = array([[3.74165739]])
a1 = array([[3.74165739]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 0, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = True
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_____________________________ test_inplace_warning _____________________________
[gw0] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py:490: in test_inplace_warning
eigvals, _ = lobpcg(A, X, maxiter=2, verbosityLevel=1)
A = <6x6 sparse matrix of type '<class 'numpy.complex128'>'
with 6 stored elements (1 diagonals) in DIAgonal format>
X = array([[ 0.47669462],
[ 0.10813329],
[ 0.26448146],
[ 0.60554991],
[ 0.50466465],
[-0.2640869 ]])
m = 1
n = 6
rnd = RandomState(MT19937) at 0x7FFF94BAF340
vals = array([-1, -2, -3, -4, -5, -6])
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff941b1a80>
B = None
M = None
X = array([[ 0.47669462],
[ 0.10813329],
[ 0.26448146],
[ 0.60554991],
[ 0.50466465],
[-0.2640869 ]])
Y = None
_ = array([[0.27022703]])
aux = ('Solving standard eigenvalue problem without preconditioning\n'
'\n'
'matrix size 6\n'
'block size 1\n'
'\n'
'No constraints\n'
'\n')
bestIterationNumber = 2
bestblockVectorX = array([[ 0.47669462],
[ 0.10813329],
[ 0.26448146],
[ 0.60554991],
[ 0.50466465],
[-0.2640869 ]])
blockVectorAX = array([[-0.47669462+0.j],
[-0.21626659+0.j],
[-0.79344437+0.j],
[-2.42219964+0.j],
[-2.52332323+0.j],
[ 1.58452138+0.j]])
blockVectorBX = array([[ 0.47669462],
[ 0.10813329],
[ 0.26448146],
[ 0.60554991],
[ 0.50466465],
[-0.2640869 ]])
blockVectorX = array([[ 0.47669462],
[ 0.10813329],
[ 0.26448146],
[ 0.60554991],
[ 0.50466465],
[-0.2640869 ]])
blockVectorY = None
gramXAX = array([[-3.61912083+0.j]])
largest = True
maxiter = 2
n = 6
residualTolerance = 8.940696716308594e-08
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = None
verbosityLevel = 1
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (lrwork>=max(24*n,1)||lrwork==-1) failed for 10th keyword lrwork: zheevr:lrwork=1
_job = 'V'
a = array([[-3.61912083+0.j]])
a1 = array([[-3.61912083+0.j]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = True
driver = 'evr'
drv = <fortran function zheevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function zheevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1, 1)
lwork_args = {'liwork': 1, 'lrwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'he'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
----------------------------- Captured stdout call -----------------------------
Solving standard eigenvalue problem without preconditioning
matrix size 6
block size 1
No constraints
_________________________ Test_SVDS_LOBPCG.test_svd_v0 _________________________
[gw0] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py:344: in test_svd_v0
res1a = svds(A, k, v0=v0a, solver=self.solver, random_state=0)
A = array([[0.63696169, 0.26978671, 0.04097352, ..., 0.97262881, 0.88993556,
0.82237383],
[0.47998792, 0.23237292, 0.80188058, ..., 0.7726492 , 0.97826571,
0.58987003],
[0.31968164, 0.18750772, 0.67252663, ..., 0.93376891, 0.68405045,
0.82378136],
...,
[0.18400687, 0.43688732, 0.7695516 , ..., 0.13820355, 0.66263843,
0.46152281],
[0.9259518 , 0.07598897, 0.44222873, ..., 0.97826589, 0.25880505,
0.71360413],
[0.67703467, 0.06811606, 0.11610553, ..., 0.18551999, 0.9356096 ,
0.02193656]])
k = 1
n = 100
rng = Generator(PCG64) at 0x7FFF94E29E00
self = <scipy.sparse.linalg._eigen.tests.test_svds.Test_SVDS_LOBPCG object at 0x7fffa2329e10>
v0a = array([0.09422648, 0.15966649, 0.12710552, 0.13820803, 0.09446335,
0.1007917 , 0.10437159, 0.04411627, 0.10351591, 0.16158866,
0.1324151 , 0.06175413, 0.1211073 , 0.04628453, 0.16383881,
0.03761041, 0.14407871, 0.14670478, 0.03097541, 0.1035359 ,
0.0364846 , 0.14604693, 0.06732288, 0.00652372, 0.07797881,
0.04615499, 0.1429362 , 0.12603507, 0.07345032, 0.14678045,
0.12544691, 0.01802259, 0.14545075, 0.16047391, 0.01436059,
0.10713282, 0.12387333, 0.10629194, 0.11418953, 0.00959721,
0.14877258, 0.08037087, 0.04837191, 0.02491765, 0.07686582,
0.06508633, 0.12602076, 0.06367208, 0.07827231, 0.09464819,
0.05652832, 0.05303302, 0.05348119, 0.11447295, 0.07544694,
0.09496378, 0.16299311, 0.03846222, 0.01121782, 0.03890377,
0.11647391, 0.12521497, 0.03145551, 0.06365 , 0.07082139,
0.06854904, 0.11728414, 0.16123468, 0.03590033, 0.07893857,
0.08042879, 0.02963547, 0.08565422, 0.03720429, 0.0960794 ,
0.05121417, 0.05217356, 0.07986218, 0.15651494, 0.14653069,
0.11121368, 0.16445218, 0.05734768, 0.0064408 , 0.05908752,
0.07498081, 0.08067586, 0.13779528, 0.05192075, 0.0860317 ,
0.14217742, 0.03028264, 0.15081926, 0.02273174, 0.11481698,
0.15771828, 0.10070903, 0.11362856, 0.1273228 , 0.04002785])
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/_svds.py:487: in svds
_, eigvec = lobpcg(XH_X, X, tol=tol ** 2, maxiter=maxiter,
A = <100x100 MatrixLinearOperator with dtype=float64>
X = array([[0.09422648],
[0.15966649],
[0.12710552],
[0.13820803],
[0.09446335],
[0.1007917 ],
[0.10437159],
[0.04411627],
[0.10351591],
[0.16158866],
[0.1324151 ],
[0.06175413],
[0.1211073 ],
[0.04628453],
[0.16383881],
[0.03761041],
[0.14407871],
[0.14670478],
[0.03097541],
[0.1035359 ],
[0.0364846 ],
[0.14604693],
[0.06732288],
[0.00652372],
[0.07797881],
[0.04615499],
[0.1429362 ],
[0.12603507],
[0.07345032],
[0.14678045],
[0.12544691],
[0.01802259],
[0.14545075],
[0.16047391],
[0.01436059],
[0.10713282],
[0.12387333],
[0.10629194],
[0.11418953],
[0.00959721],
[0.14877258],
[0.08037087],
[0.04837191],
[0.02491765],
[0.07686582],
[0.06508633],
[0.12602076],
[0.06367208],
[0.07827231],
[0.09464819],
[0.05652832],
[0.05303302],
[0.05348119],
[0.11447295],
[0.07544694],
[0.09496378],
[0.16299311],
[0.03846222],
[0.01121782],
[0.03890377],
[0.11647391],
[0.12521497],
[0.03145551],
[0.06365 ],
[0.07082139],
[0.06854904],
[0.11728414],
[0.16123468],
[0.03590033],
[0.07893857],
[0.08042879],
[0.02963547],
[0.08565422],
[0.03720429],
[0.0960794 ],
[0.05121417],
[0.05217356],
[0.07986218],
[0.15651494],
[0.14653069],
[0.11121368],
[0.16445218],
[0.05734768],
[0.0064408 ],
[0.05908752],
[0.07498081],
[0.08067586],
[0.13779528],
[0.05192075],
[0.0860317 ],
[0.14217742],
[0.03028264],
[0.15081926],
[0.02273174],
[0.11481698],
[0.15771828],
[0.10070903],
[0.11362856],
[0.1273228 ],
[0.04002785]])
XH_X = <100x100 _CustomLinearOperator with dtype=float64>
XH_dot = <bound method LinearOperator.rmatvec of <100x100 MatrixLinearOperator with dtype=float64>>
XH_mat = <bound method LinearOperator.rmatmat of <100x100 MatrixLinearOperator with dtype=float64>>
X_dot = <bound method LinearOperator.matvec of <100x100 MatrixLinearOperator with dtype=float64>>
X_matmat = <bound method LinearOperator.matmat of <100x100 MatrixLinearOperator with dtype=float64>>
args = (<100x100 MatrixLinearOperator with dtype=float64>,
1,
None,
0.0,
'LM',
array([0.09422648, 0.15966649, 0.12710552, 0.13820803, 0.09446335,
0.1007917 , 0.10437159, 0.04411627, 0.10351591, 0.16158866,
0.1324151 , 0.06175413, 0.1211073 , 0.04628453, 0.16383881,
0.03761041, 0.14407871, 0.14670478, 0.03097541, 0.1035359 ,
0.0364846 , 0.14604693, 0.06732288, 0.00652372, 0.07797881,
0.04615499, 0.1429362 , 0.12603507, 0.07345032, 0.14678045,
0.12544691, 0.01802259, 0.14545075, 0.16047391, 0.01436059,
0.10713282, 0.12387333, 0.10629194, 0.11418953, 0.00959721,
0.14877258, 0.08037087, 0.04837191, 0.02491765, 0.07686582,
0.06508633, 0.12602076, 0.06367208, 0.07827231, 0.09464819,
0.05652832, 0.05303302, 0.05348119, 0.11447295, 0.07544694,
0.09496378, 0.16299311, 0.03846222, 0.01121782, 0.03890377,
0.11647391, 0.12521497, 0.03145551, 0.06365 , 0.07082139,
0.06854904, 0.11728414, 0.16123468, 0.03590033, 0.07893857,
0.08042879, 0.02963547, 0.08565422, 0.03720429, 0.0960794 ,
0.05121417, 0.05217356, 0.07986218, 0.15651494, 0.14653069,
0.11121368, 0.16445218, 0.05734768, 0.0064408 , 0.05908752,
0.07498081, 0.08067586, 0.13779528, 0.05192075, 0.0860317 ,
0.14217742, 0.03028264, 0.15081926, 0.02273174, 0.11481698,
0.15771828, 0.10070903, 0.11362856, 0.1273228 , 0.04002785]),
None,
True,
'lobpcg',
RandomState(MT19937) at 0x7FFF94DE3740)
k = 1
largest = True
m = 100
matmat_XH_X = <function svds.<locals>.matmat_XH_X at 0x7fff942fb7e0>
matvec_XH_X = <function svds.<locals>.matvec_XH_X at 0x7fff942fb600>
maxiter = None
n = 100
ncv = None
options = None
random_state = RandomState(MT19937) at 0x7FFF94DE3740
return_singular_vectors = True
solver = 'lobpcg'
tol = 0.0
transpose = False
v0 = array([0.09422648, 0.15966649, 0.12710552, 0.13820803, 0.09446335,
0.1007917 , 0.10437159, 0.04411627, 0.10351591, 0.16158866,
0.1324151 , 0.06175413, 0.1211073 , 0.04628453, 0.16383881,
0.03761041, 0.14407871, 0.14670478, 0.03097541, 0.1035359 ,
0.0364846 , 0.14604693, 0.06732288, 0.00652372, 0.07797881,
0.04615499, 0.1429362 , 0.12603507, 0.07345032, 0.14678045,
0.12544691, 0.01802259, 0.14545075, 0.16047391, 0.01436059,
0.10713282, 0.12387333, 0.10629194, 0.11418953, 0.00959721,
0.14877258, 0.08037087, 0.04837191, 0.02491765, 0.07686582,
0.06508633, 0.12602076, 0.06367208, 0.07827231, 0.09464819,
0.05652832, 0.05303302, 0.05348119, 0.11447295, 0.07544694,
0.09496378, 0.16299311, 0.03846222, 0.01121782, 0.03890377,
0.11647391, 0.12521497, 0.03145551, 0.06365 , 0.07082139,
0.06854904, 0.11728414, 0.16123468, 0.03590033, 0.07893857,
0.08042879, 0.02963547, 0.08565422, 0.03720429, 0.0960794 ,
0.05121417, 0.05217356, 0.07986218, 0.15651494, 0.14653069,
0.11121368, 0.16445218, 0.05734768, 0.0064408 , 0.05908752,
0.07498081, 0.08067586, 0.13779528, 0.05192075, 0.0860317 ,
0.14217742, 0.03028264, 0.15081926, 0.02273174, 0.11481698,
0.15771828, 0.10070903, 0.11362856, 0.1273228 , 0.04002785])
which = 'LM'
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff942fba60>
B = None
M = None
X = array([[0.09422648],
[0.15966649],
[0.12710552],
[0.13820803],
[0.09446335],
[0.1007917 ],
[0.10437159],
[0.04411627],
[0.10351591],
[0.16158866],
[0.1324151 ],
[0.06175413],
[0.1211073 ],
[0.04628453],
[0.16383881],
[0.03761041],
[0.14407871],
[0.14670478],
[0.03097541],
[0.1035359 ],
[0.0364846 ],
[0.14604693],
[0.06732288],
[0.00652372],
[0.07797881],
[0.04615499],
[0.1429362 ],
[0.12603507],
[0.07345032],
[0.14678045],
[0.12544691],
[0.01802259],
[0.14545075],
[0.16047391],
[0.01436059],
[0.10713282],
[0.12387333],
[0.10629194],
[0.11418953],
[0.00959721],
[0.14877258],
[0.08037087],
[0.04837191],
[0.02491765],
[0.07686582],
[0.06508633],
[0.12602076],
[0.06367208],
[0.07827231],
[0.09464819],
[0.05652832],
[0.05303302],
[0.05348119],
[0.11447295],
[0.07544694],
[0.09496378],
[0.16299311],
[0.03846222],
[0.01121782],
[0.03890377],
[0.11647391],
[0.12521497],
[0.03145551],
[0.06365 ],
[0.07082139],
[0.06854904],
[0.11728414],
[0.16123468],
[0.03590033],
[0.07893857],
[0.08042879],
[0.02963547],
[0.08565422],
[0.03720429],
[0.0960794 ],
[0.05121417],
[0.05217356],
[0.07986218],
[0.15651494],
[0.14653069],
[0.11121368],
[0.16445218],
[0.05734768],
[0.0064408 ],
[0.05908752],
[0.07498081],
[0.08067586],
[0.13779528],
[0.05192075],
[0.0860317 ],
[0.14217742],
[0.03028264],
[0.15081926],
[0.02273174],
[0.11481698],
[0.15771828],
[0.10070903],
[0.11362856],
[0.1273228 ],
[0.04002785]])
Y = None
_ = array([[0.16588966]])
bestIterationNumber = 20
bestblockVectorX = array([[0.09422648],
[0.15966649],
[0.12710552],
[0.13820803],
[0.09446335],
[0.1007917 ],
[0.10437159],
[0.04411627],
[0.10351591],
[0.16158866],
[0.1324151 ],
[0.06175413],
[0.1211073 ],
[0.04628453],
[0.16383881],
[0.03761041],
[0.14407871],
[0.14670478],
[0.03097541],
[0.1035359 ],
[0.0364846 ],
[0.14604693],
[0.06732288],
[0.00652372],
[0.07797881],
[0.04615499],
[0.1429362 ],
[0.12603507],
[0.07345032],
[0.14678045],
[0.12544691],
[0.01802259],
[0.14545075],
[0.16047391],
[0.01436059],
[0.10713282],
[0.12387333],
[0.10629194],
[0.11418953],
[0.00959721],
[0.14877258],
[0.08037087],
[0.04837191],
[0.02491765],
[0.07686582],
[0.06508633],
[0.12602076],
[0.06367208],
[0.07827231],
[0.09464819],
[0.05652832],
[0.05303302],
[0.05348119],
[0.11447295],
[0.07544694],
[0.09496378],
[0.16299311],
[0.03846222],
[0.01121782],
[0.03890377],
[0.11647391],
[0.12521497],
[0.03145551],
[0.06365 ],
[0.07082139],
[0.06854904],
[0.11728414],
[0.16123468],
[0.03590033],
[0.07893857],
[0.08042879],
[0.02963547],
[0.08565422],
[0.03720429],
[0.0960794 ],
[0.05121417],
[0.05217356],
[0.07986218],
[0.15651494],
[0.14653069],
[0.11121368],
[0.16445218],
[0.05734768],
[0.0064408 ],
[0.05908752],
[0.07498081],
[0.08067586],
[0.13779528],
[0.05192075],
[0.0860317 ],
[0.14217742],
[0.03028264],
[0.15081926],
[0.02273174],
[0.11481698],
[0.15771828],
[0.10070903],
[0.11362856],
[0.1273228 ],
[0.04002785]])
blockVectorAX = array([[226.00249061],
[211.52396405],
[220.34556592],
[207.88083466],
[225.16834581],
[229.99040618],
[236.71601236],
[204.60418131],
[198.52832033],
[247.50487263],
[219.22799987],
[222.63105394],
[221.96205454],
[228.03128659],
[223.23643401],
[224.93720551],
[235.76312471],
[220.95285741],
[204.93240802],
[226.77038253],
[217.15220196],
[218.14274439],
[215.15152975],
[234.9590262 ],
[219.46329939],
[211.10378592],
[248.51912086],
[207.01072337],
[227.8759245 ],
[227.70742983],
[239.31674689],
[208.85217332],
[212.14714391],
[222.46847319],
[230.84910239],
[226.24455292],
[240.01359387],
[248.21021039],
[210.84296405],
[221.37244662],
[228.93033697],
[197.3415848 ],
[224.82102745],
[233.73441362],
[239.53232273],
[224.44298858],
[218.88851246],
[226.27109117],
[220.27622423],
[231.78150936],
[203.92843245],
[220.10733836],
[238.29100836],
[218.99970218],
[218.49155309],
[221.5252675 ],
[244.30365313],
[222.84243298],
[236.76409552],
[228.4459975 ],
[237.92616886],
[212.37998628],
[217.85718464],
[229.64593069],
[221.26833819],
[238.7461052 ],
[217.92964689],
[215.01231883],
[208.61269441],
[246.86443097],
[220.90126291],
[229.71197409],
[213.0459193 ],
[218.35242861],
[237.20301206],
[227.87091481],
[249.26619371],
[182.48327486],
[226.01869796],
[223.19413352],
[238.01962041],
[214.68360911],
[210.20972862],
[223.09269398],
[240.42012281],
[235.68462609],
[209.05125309],
[231.96739165],
[203.94132349],
[234.49274821],
[216.78904824],
[213.04721296],
[207.61747985],
[224.62092358],
[224.08137584],
[228.13590509],
[218.46344638],
[233.68446977],
[237.0646684 ],
[236.95163647]])
blockVectorBX = array([[0.09422648],
[0.15966649],
[0.12710552],
[0.13820803],
[0.09446335],
[0.1007917 ],
[0.10437159],
[0.04411627],
[0.10351591],
[0.16158866],
[0.1324151 ],
[0.06175413],
[0.1211073 ],
[0.04628453],
[0.16383881],
[0.03761041],
[0.14407871],
[0.14670478],
[0.03097541],
[0.1035359 ],
[0.0364846 ],
[0.14604693],
[0.06732288],
[0.00652372],
[0.07797881],
[0.04615499],
[0.1429362 ],
[0.12603507],
[0.07345032],
[0.14678045],
[0.12544691],
[0.01802259],
[0.14545075],
[0.16047391],
[0.01436059],
[0.10713282],
[0.12387333],
[0.10629194],
[0.11418953],
[0.00959721],
[0.14877258],
[0.08037087],
[0.04837191],
[0.02491765],
[0.07686582],
[0.06508633],
[0.12602076],
[0.06367208],
[0.07827231],
[0.09464819],
[0.05652832],
[0.05303302],
[0.05348119],
[0.11447295],
[0.07544694],
[0.09496378],
[0.16299311],
[0.03846222],
[0.01121782],
[0.03890377],
[0.11647391],
[0.12521497],
[0.03145551],
[0.06365 ],
[0.07082139],
[0.06854904],
[0.11728414],
[0.16123468],
[0.03590033],
[0.07893857],
[0.08042879],
[0.02963547],
[0.08565422],
[0.03720429],
[0.0960794 ],
[0.05121417],
[0.05217356],
[0.07986218],
[0.15651494],
[0.14653069],
[0.11121368],
[0.16445218],
[0.05734768],
[0.0064408 ],
[0.05908752],
[0.07498081],
[0.08067586],
[0.13779528],
[0.05192075],
[0.0860317 ],
[0.14217742],
[0.03028264],
[0.15081926],
[0.02273174],
[0.11481698],
[0.15771828],
[0.10070903],
[0.11362856],
[0.1273228 ],
[0.04002785]])
blockVectorX = array([[0.09422648],
[0.15966649],
[0.12710552],
[0.13820803],
[0.09446335],
[0.1007917 ],
[0.10437159],
[0.04411627],
[0.10351591],
[0.16158866],
[0.1324151 ],
[0.06175413],
[0.1211073 ],
[0.04628453],
[0.16383881],
[0.03761041],
[0.14407871],
[0.14670478],
[0.03097541],
[0.1035359 ],
[0.0364846 ],
[0.14604693],
[0.06732288],
[0.00652372],
[0.07797881],
[0.04615499],
[0.1429362 ],
[0.12603507],
[0.07345032],
[0.14678045],
[0.12544691],
[0.01802259],
[0.14545075],
[0.16047391],
[0.01436059],
[0.10713282],
[0.12387333],
[0.10629194],
[0.11418953],
[0.00959721],
[0.14877258],
[0.08037087],
[0.04837191],
[0.02491765],
[0.07686582],
[0.06508633],
[0.12602076],
[0.06367208],
[0.07827231],
[0.09464819],
[0.05652832],
[0.05303302],
[0.05348119],
[0.11447295],
[0.07544694],
[0.09496378],
[0.16299311],
[0.03846222],
[0.01121782],
[0.03890377],
[0.11647391],
[0.12521497],
[0.03145551],
[0.06365 ],
[0.07082139],
[0.06854904],
[0.11728414],
[0.16123468],
[0.03590033],
[0.07893857],
[0.08042879],
[0.02963547],
[0.08565422],
[0.03720429],
[0.0960794 ],
[0.05121417],
[0.05217356],
[0.07986218],
[0.15651494],
[0.14653069],
[0.11121368],
[0.16445218],
[0.05734768],
[0.0064408 ],
[0.05908752],
[0.07498081],
[0.08067586],
[0.13779528],
[0.05192075],
[0.0860317 ],
[0.14217742],
[0.03028264],
[0.15081926],
[0.02273174],
[0.11481698],
[0.15771828],
[0.10070903],
[0.11362856],
[0.1273228 ],
[0.04002785]])
blockVectorY = None
gramXAX = array([[2002.35682113]])
largest = True
maxiter = 20
n = 100
residualTolerance = 1.4901161193847656e-06
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = 0.0
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[2002.35682113]])
a1 = array([[2002.35682113]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
____________________ Test_SVDS_LOBPCG.test_svd_random_state ____________________
[gw0] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py:379: in test_svd_random_state
res1a = svds(A, k, solver=self.solver, random_state=0)
A = array([[0.63696169, 0.26978671, 0.04097352, ..., 0.97262881, 0.88993556,
0.82237383],
[0.47998792, 0.23237292, 0.80188058, ..., 0.7726492 , 0.97826571,
0.58987003],
[0.31968164, 0.18750772, 0.67252663, ..., 0.93376891, 0.68405045,
0.82378136],
...,
[0.18400687, 0.43688732, 0.7695516 , ..., 0.13820355, 0.66263843,
0.46152281],
[0.9259518 , 0.07598897, 0.44222873, ..., 0.97826589, 0.25880505,
0.71360413],
[0.67703467, 0.06811606, 0.11610553, ..., 0.18551999, 0.9356096 ,
0.02193656]])
k = 1
n = 100
rng = Generator(PCG64) at 0x7FFF94E2A6C0
self = <scipy.sparse.linalg._eigen.tests.test_svds.Test_SVDS_LOBPCG object at 0x7fffa2330ed0>
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/_svds.py:487: in svds
_, eigvec = lobpcg(XH_X, X, tol=tol ** 2, maxiter=maxiter,
A = <100x100 MatrixLinearOperator with dtype=float64>
X = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
XH_X = <100x100 _CustomLinearOperator with dtype=float64>
XH_dot = <bound method LinearOperator.rmatvec of <100x100 MatrixLinearOperator with dtype=float64>>
XH_mat = <bound method LinearOperator.rmatmat of <100x100 MatrixLinearOperator with dtype=float64>>
X_dot = <bound method LinearOperator.matvec of <100x100 MatrixLinearOperator with dtype=float64>>
X_matmat = <bound method LinearOperator.matmat of <100x100 MatrixLinearOperator with dtype=float64>>
args = (<100x100 MatrixLinearOperator with dtype=float64>,
1,
None,
0.0,
'LM',
None,
None,
True,
'lobpcg',
RandomState(MT19937) at 0x7FFF94DE3C40)
k = 1
largest = True
m = 100
matmat_XH_X = <function svds.<locals>.matmat_XH_X at 0x7fff945dc720>
matvec_XH_X = <function svds.<locals>.matvec_XH_X at 0x7fff942fbce0>
maxiter = None
n = 100
ncv = None
options = None
random_state = RandomState(MT19937) at 0x7FFF94DE3C40
return_singular_vectors = True
solver = 'lobpcg'
tol = 0.0
transpose = False
v0 = None
which = 'LM'
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff945dc0e0>
B = None
M = None
X = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
Y = None
_ = array([[0.09904371]])
bestIterationNumber = 20
bestblockVectorX = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
blockVectorAX = array([[17.85795678],
[16.41821394],
[16.56441059],
[16.53294983],
[18.72733471],
[15.2339849 ],
[19.44469379],
[16.66818406],
[15.50107752],
[19.57047836],
[16.78551783],
[18.82160251],
[18.14880091],
[17.55387095],
[16.33372348],
[16.01382394],
[18.45724266],
[16.29502033],
[15.23245231],
[16.30574909],
[14.34570611],
[16.30819942],
[15.7639297 ],
[15.825672 ],
[18.24499336],
[14.34943216],
[18.878873 ],
[15.8621151 ],
[19.18186734],
[18.1797662 ],
[17.68543877],
[15.57526809],
[15.82803575],
[15.45488928],
[16.19125881],
[17.01129729],
[18.22776208],
[18.72410468],
[15.76381254],
[14.93932254],
[17.57170691],
[13.84658358],
[16.21994993],
[18.70077541],
[17.2174117 ],
[14.50982325],
[15.43829062],
[16.73425317],
[15.81726976],
[17.54512829],
[15.87488053],
[15.80511438],
[18.51902122],
[13.85791756],
[16.94153028],
[16.45739521],
[18.01476033],
[16.90530611],
[17.29287223],
[16.73285333],
[17.56466838],
[16.41634457],
[14.95480967],
[15.66555681],
[16.52184512],
[18.17846869],
[15.48969831],
[17.18709945],
[15.58974862],
[17.24950652],
[16.85828342],
[18.49760144],
[17.15662023],
[16.03152581],
[16.50845952],
[16.85407683],
[17.88861132],
[12.43284823],
[16.68150782],
[15.94893941],
[16.10474836],
[15.70459332],
[15.62734457],
[15.28318144],
[17.45612147],
[20.03568266],
[15.40239608],
[16.82237683],
[14.84495691],
[17.90246631],
[16.77553592],
[17.14096916],
[16.40741294],
[17.39724322],
[16.78619663],
[17.30486211],
[15.60133588],
[20.19410569],
[17.67484104],
[17.94013161]])
blockVectorBX = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
blockVectorX = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
blockVectorY = None
gramXAX = array([[18.35030357]])
largest = True
maxiter = 20
n = 100
residualTolerance = 1.4901161193847656e-06
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = 0.0
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[18.35030357]])
a1 = array([[18.35030357]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_________________ Test_SVDS_LOBPCG.test_svd_random_state_2[0] __________________
[gw0] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py:414: in test_svd_random_state_2
res1a = svds(A, k, solver=self.solver, random_state=random_state)
A = array([[0.63696169, 0.26978671, 0.04097352, ..., 0.97262881, 0.88993556,
0.82237383],
[0.47998792, 0.23237292, 0.80188058, ..., 0.7726492 , 0.97826571,
0.58987003],
[0.31968164, 0.18750772, 0.67252663, ..., 0.93376891, 0.68405045,
0.82378136],
...,
[0.18400687, 0.43688732, 0.7695516 , ..., 0.13820355, 0.66263843,
0.46152281],
[0.9259518 , 0.07598897, 0.44222873, ..., 0.97826589, 0.25880505,
0.71360413],
[0.67703467, 0.06811606, 0.11610553, ..., 0.18551999, 0.9356096 ,
0.02193656]])
k = 1
n = 100
random_state = 0
random_state_2 = 0
rng = Generator(PCG64) at 0x7FFF94E2AEA0
self = <scipy.sparse.linalg._eigen.tests.test_svds.Test_SVDS_LOBPCG object at 0x7fffa2331790>
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/_svds.py:487: in svds
_, eigvec = lobpcg(XH_X, X, tol=tol ** 2, maxiter=maxiter,
A = <100x100 MatrixLinearOperator with dtype=float64>
X = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
XH_X = <100x100 _CustomLinearOperator with dtype=float64>
XH_dot = <bound method LinearOperator.rmatvec of <100x100 MatrixLinearOperator with dtype=float64>>
XH_mat = <bound method LinearOperator.rmatmat of <100x100 MatrixLinearOperator with dtype=float64>>
X_dot = <bound method LinearOperator.matvec of <100x100 MatrixLinearOperator with dtype=float64>>
X_matmat = <bound method LinearOperator.matmat of <100x100 MatrixLinearOperator with dtype=float64>>
args = (<100x100 MatrixLinearOperator with dtype=float64>,
1,
None,
0.0,
'LM',
None,
None,
True,
'lobpcg',
RandomState(MT19937) at 0x7FFF9433C340)
k = 1
largest = True
m = 100
matmat_XH_X = <function svds.<locals>.matmat_XH_X at 0x7fff945dc180>
matvec_XH_X = <function svds.<locals>.matvec_XH_X at 0x7fff945dcb80>
maxiter = None
n = 100
ncv = None
options = None
random_state = RandomState(MT19937) at 0x7FFF9433C340
return_singular_vectors = True
solver = 'lobpcg'
tol = 0.0
transpose = False
v0 = None
which = 'LM'
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff945dcfe0>
B = None
M = None
X = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
Y = None
_ = array([[0.09904371]])
bestIterationNumber = 20
bestblockVectorX = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
blockVectorAX = array([[17.85795678],
[16.41821394],
[16.56441059],
[16.53294983],
[18.72733471],
[15.2339849 ],
[19.44469379],
[16.66818406],
[15.50107752],
[19.57047836],
[16.78551783],
[18.82160251],
[18.14880091],
[17.55387095],
[16.33372348],
[16.01382394],
[18.45724266],
[16.29502033],
[15.23245231],
[16.30574909],
[14.34570611],
[16.30819942],
[15.7639297 ],
[15.825672 ],
[18.24499336],
[14.34943216],
[18.878873 ],
[15.8621151 ],
[19.18186734],
[18.1797662 ],
[17.68543877],
[15.57526809],
[15.82803575],
[15.45488928],
[16.19125881],
[17.01129729],
[18.22776208],
[18.72410468],
[15.76381254],
[14.93932254],
[17.57170691],
[13.84658358],
[16.21994993],
[18.70077541],
[17.2174117 ],
[14.50982325],
[15.43829062],
[16.73425317],
[15.81726976],
[17.54512829],
[15.87488053],
[15.80511438],
[18.51902122],
[13.85791756],
[16.94153028],
[16.45739521],
[18.01476033],
[16.90530611],
[17.29287223],
[16.73285333],
[17.56466838],
[16.41634457],
[14.95480967],
[15.66555681],
[16.52184512],
[18.17846869],
[15.48969831],
[17.18709945],
[15.58974862],
[17.24950652],
[16.85828342],
[18.49760144],
[17.15662023],
[16.03152581],
[16.50845952],
[16.85407683],
[17.88861132],
[12.43284823],
[16.68150782],
[15.94893941],
[16.10474836],
[15.70459332],
[15.62734457],
[15.28318144],
[17.45612147],
[20.03568266],
[15.40239608],
[16.82237683],
[14.84495691],
[17.90246631],
[16.77553592],
[17.14096916],
[16.40741294],
[17.39724322],
[16.78619663],
[17.30486211],
[15.60133588],
[20.19410569],
[17.67484104],
[17.94013161]])
blockVectorBX = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
blockVectorX = array([[ 0.17471829],
[ 0.03963306],
[ 0.09693784],
[ 0.22194638],
[ 0.18496988],
[-0.09679323],
[ 0.09410028],
[-0.01499098],
[-0.01022318],
[ 0.0406672 ],
[ 0.01426661],
[ 0.14403665],
[ 0.075376 ],
[ 0.01205115],
[ 0.04396186],
[ 0.03304834],
[ 0.14797914],
[-0.02031964],
[ 0.03100739],
[-0.08459281],
[-0.25285759],
[ 0.06473681],
[ 0.08561697],
[-0.07350678],
[ 0.22480493],
[-0.14404578],
[ 0.00453209],
[-0.01853938],
[ 0.15181215],
[ 0.14553075],
[ 0.01534657],
[ 0.03745462],
[-0.0879296 ],
[-0.19618544],
[-0.03445851],
[ 0.01548538],
[ 0.12185256],
[ 0.11908817],
[-0.03836229],
[-0.02994119],
[-0.10385258],
[-0.14064385],
[-0.16899534],
[ 0.19321204],
[-0.05047784],
[-0.04338851],
[-0.1240815 ],
[ 0.07700553],
[-0.15984644],
[-0.02107059],
[-0.08869033],
[ 0.03832026],
[-0.05059204],
[-0.1169342 ],
[-0.00279127],
[ 0.04242358],
[ 0.00658811],
[ 0.02995794],
[-0.06282562],
[-0.03592723],
[-0.06660298],
[-0.03561148],
[-0.08053703],
[-0.17097744],
[ 0.01757294],
[-0.03979388],
[-0.1614609 ],
[ 0.04583567],
[-0.0898622 ],
[ 0.00514486],
[ 0.07221184],
[ 0.01277495],
[ 0.11285047],
[-0.12230173],
[ 0.03984941],
[-0.06782613],
[-0.08624698],
[-0.05733142],
[-0.03085732],
[ 0.00556282],
[-0.11540077],
[ 0.0892212 ],
[ 0.04612094],
[-0.15215528],
[ 0.14740202],
[ 0.1877759 ],
[ 0.11675071],
[-0.01782042],
[-0.10605132],
[ 0.10443681],
[-0.03993214],
[ 0.1210755 ],
[ 0.02062833],
[ 0.09672996],
[ 0.03529585],
[ 0.06998163],
[ 0.00103996],
[ 0.17687925],
[ 0.01256984],
[ 0.03981452]])
blockVectorY = None
gramXAX = array([[18.35030357]])
largest = True
maxiter = 20
n = 100
residualTolerance = 1.4901161193847656e-06
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = 0.0
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[18.35030357]])
a1 = array([[18.35030357]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_________________ Test_SVDS_LOBPCG.test_svd_random_state_2[1] __________________
[gw0] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py:414: in test_svd_random_state_2
res1a = svds(A, k, solver=self.solver, random_state=random_state)
A = array([[0.63696169, 0.26978671, 0.04097352, ..., 0.97262881, 0.88993556,
0.82237383],
[0.47998792, 0.23237292, 0.80188058, ..., 0.7726492 , 0.97826571,
0.58987003],
[0.31968164, 0.18750772, 0.67252663, ..., 0.93376891, 0.68405045,
0.82378136],
...,
[0.18400687, 0.43688732, 0.7695516 , ..., 0.13820355, 0.66263843,
0.46152281],
[0.9259518 , 0.07598897, 0.44222873, ..., 0.97826589, 0.25880505,
0.71360413],
[0.67703467, 0.06811606, 0.11610553, ..., 0.18551999, 0.9356096 ,
0.02193656]])
k = 1
n = 100
random_state = 1
random_state_2 = 1
rng = Generator(PCG64) at 0x7FFF94E2B760
self = <scipy.sparse.linalg._eigen.tests.test_svds.Test_SVDS_LOBPCG object at 0x7fffa23318d0>
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/_svds.py:487: in svds
_, eigvec = lobpcg(XH_X, X, tol=tol ** 2, maxiter=maxiter,
A = <100x100 MatrixLinearOperator with dtype=float64>
X = array([[ 0.18308114],
[-0.06895151],
[-0.05953062],
[-0.12093507],
[ 0.09754072],
[-0.25940809],
[ 0.196659 ],
[-0.08579618],
[ 0.03595913],
[-0.02810672],
[ 0.16479524],
[-0.23219995],
[-0.03633988],
[-0.04328704],
[ 0.12778797],
[-0.12396954],
[-0.01943451],
[-0.09894406],
[ 0.00475794],
[ 0.06568952],
[-0.12405158],
[ 0.12902264],
[ 0.10161894],
[ 0.0566365 ],
[ 0.10153613],
[-0.07706346],
[-0.01385105],
[-0.10547125],
[-0.03019386],
[ 0.05977675],
[-0.07795758],
[-0.04471838],
[-0.07745173],
[-0.09526374],
[-0.07565664],
[-0.00142744],
[-0.12593286],
[ 0.02642116],
[ 0.1870775 ],
[ 0.08363633],
[-0.02162192],
[-0.1000453 ],
[-0.08421275],
[ 0.19075778],
[ 0.00572658],
[-0.07179624],
[ 0.02151822],
[ 0.23672127],
[ 0.0135432 ],
[ 0.06956541],
[ 0.03383241],
[-0.03970233],
[-0.12877405],
[-0.03937467],
[-0.02354462],
[ 0.06611872],
[ 0.09456243],
[ 0.10494519],
[ 0.03218875],
[ 0.0997649 ],
[-0.08502874],
[ 0.14121168],
[ 0.05781269],
[-0.03359826],
[ 0.05506123],
[-0.00851774],
[ 0.12754677],
[ 0.17129965],
[ 0.24633778],
[-0.15740011],
[-0.16276711],
[-0.05685871],
[ 0.01803789],
[ 0.09875363],
[ 0.03557544],
[-0.22792376],
[-0.03451248],
[ 0.09332162],
[ 0.02593414],
[ 0.08588683],
[-0.02505877],
[-0.02262759],
[ 0.02102747],
[ 0.04621722],
[ 0.0223505 ],
[ 0.01341355],
[-0.07559083],
[ 0.04255549],
[ 0.01373056],
[ 0.12730495],
[ 0.1351309 ],
[ 0.02086911],
[-0.04229864],
[-0.07199177],
[ 0.04773235],
[ 0.00871706],
[-0.038756 ],
[ 0.00491383],
[-0.06988074],
[ 0.0786757 ]])
XH_X = <100x100 _CustomLinearOperator with dtype=float64>
XH_dot = <bound method LinearOperator.rmatvec of <100x100 MatrixLinearOperator with dtype=float64>>
XH_mat = <bound method LinearOperator.rmatmat of <100x100 MatrixLinearOperator with dtype=float64>>
X_dot = <bound method LinearOperator.matvec of <100x100 MatrixLinearOperator with dtype=float64>>
X_matmat = <bound method LinearOperator.matmat of <100x100 MatrixLinearOperator with dtype=float64>>
args = (<100x100 MatrixLinearOperator with dtype=float64>,
1,
None,
0.0,
'LM',
None,
None,
True,
'lobpcg',
RandomState(MT19937) at 0x7FFF9433C740)
k = 1
largest = True
m = 100
matmat_XH_X = <function svds.<locals>.matmat_XH_X at 0x7fff945dc900>
matvec_XH_X = <function svds.<locals>.matvec_XH_X at 0x7fff945ddbc0>
maxiter = None
n = 100
ncv = None
options = None
random_state = RandomState(MT19937) at 0x7FFF9433C740
return_singular_vectors = True
solver = 'lobpcg'
tol = 0.0
transpose = False
v0 = None
which = 'LM'
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff945dce00>
B = None
M = None
X = array([[ 0.18308114],
[-0.06895151],
[-0.05953062],
[-0.12093507],
[ 0.09754072],
[-0.25940809],
[ 0.196659 ],
[-0.08579618],
[ 0.03595913],
[-0.02810672],
[ 0.16479524],
[-0.23219995],
[-0.03633988],
[-0.04328704],
[ 0.12778797],
[-0.12396954],
[-0.01943451],
[-0.09894406],
[ 0.00475794],
[ 0.06568952],
[-0.12405158],
[ 0.12902264],
[ 0.10161894],
[ 0.0566365 ],
[ 0.10153613],
[-0.07706346],
[-0.01385105],
[-0.10547125],
[-0.03019386],
[ 0.05977675],
[-0.07795758],
[-0.04471838],
[-0.07745173],
[-0.09526374],
[-0.07565664],
[-0.00142744],
[-0.12593286],
[ 0.02642116],
[ 0.1870775 ],
[ 0.08363633],
[-0.02162192],
[-0.1000453 ],
[-0.08421275],
[ 0.19075778],
[ 0.00572658],
[-0.07179624],
[ 0.02151822],
[ 0.23672127],
[ 0.0135432 ],
[ 0.06956541],
[ 0.03383241],
[-0.03970233],
[-0.12877405],
[-0.03937467],
[-0.02354462],
[ 0.06611872],
[ 0.09456243],
[ 0.10494519],
[ 0.03218875],
[ 0.0997649 ],
[-0.08502874],
[ 0.14121168],
[ 0.05781269],
[-0.03359826],
[ 0.05506123],
[-0.00851774],
[ 0.12754677],
[ 0.17129965],
[ 0.24633778],
[-0.15740011],
[-0.16276711],
[-0.05685871],
[ 0.01803789],
[ 0.09875363],
[ 0.03557544],
[-0.22792376],
[-0.03451248],
[ 0.09332162],
[ 0.02593414],
[ 0.08588683],
[-0.02505877],
[-0.02262759],
[ 0.02102747],
[ 0.04621722],
[ 0.0223505 ],
[ 0.01341355],
[-0.07559083],
[ 0.04255549],
[ 0.01373056],
[ 0.12730495],
[ 0.1351309 ],
[ 0.02086911],
[-0.04229864],
[-0.07199177],
[ 0.04773235],
[ 0.00871706],
[-0.038756 ],
[ 0.00491383],
[-0.06988074],
[ 0.0786757 ]])
Y = None
_ = array([[0.11271072]])
bestIterationNumber = 20
bestblockVectorX = array([[ 0.18308114],
[-0.06895151],
[-0.05953062],
[-0.12093507],
[ 0.09754072],
[-0.25940809],
[ 0.196659 ],
[-0.08579618],
[ 0.03595913],
[-0.02810672],
[ 0.16479524],
[-0.23219995],
[-0.03633988],
[-0.04328704],
[ 0.12778797],
[-0.12396954],
[-0.01943451],
[-0.09894406],
[ 0.00475794],
[ 0.06568952],
[-0.12405158],
[ 0.12902264],
[ 0.10161894],
[ 0.0566365 ],
[ 0.10153613],
[-0.07706346],
[-0.01385105],
[-0.10547125],
[-0.03019386],
[ 0.05977675],
[-0.07795758],
[-0.04471838],
[-0.07745173],
[-0.09526374],
[-0.07565664],
[-0.00142744],
[-0.12593286],
[ 0.02642116],
[ 0.1870775 ],
[ 0.08363633],
[-0.02162192],
[-0.1000453 ],
[-0.08421275],
[ 0.19075778],
[ 0.00572658],
[-0.07179624],
[ 0.02151822],
[ 0.23672127],
[ 0.0135432 ],
[ 0.06956541],
[ 0.03383241],
[-0.03970233],
[-0.12877405],
[-0.03937467],
[-0.02354462],
[ 0.06611872],
[ 0.09456243],
[ 0.10494519],
[ 0.03218875],
[ 0.0997649 ],
[-0.08502874],
[ 0.14121168],
[ 0.05781269],
[-0.03359826],
[ 0.05506123],
[-0.00851774],
[ 0.12754677],
[ 0.17129965],
[ 0.24633778],
[-0.15740011],
[-0.16276711],
[-0.05685871],
[ 0.01803789],
[ 0.09875363],
[ 0.03557544],
[-0.22792376],
[-0.03451248],
[ 0.09332162],
[ 0.02593414],
[ 0.08588683],
[-0.02505877],
[-0.02262759],
[ 0.02102747],
[ 0.04621722],
[ 0.0223505 ],
[ 0.01341355],
[-0.07559083],
[ 0.04255549],
[ 0.01373056],
[ 0.12730495],
[ 0.1351309 ],
[ 0.02086911],
[-0.04229864],
[-0.07199177],
[ 0.04773235],
[ 0.00871706],
[-0.038756 ],
[ 0.00491383],
[-0.06988074],
[ 0.0786757 ]])
blockVectorAX = array([[17.73881725],
[15.25915026],
[16.37087405],
[14.71649155],
[17.75858905],
[13.41332186],
[19.25734308],
[13.78425934],
[13.66838023],
[18.23192681],
[15.99504249],
[13.88820427],
[16.32967709],
[15.64433504],
[17.07394255],
[14.66539911],
[16.44203289],
[13.9656198 ],
[16.02078169],
[15.67015216],
[14.72539803],
[15.18828696],
[15.74277507],
[17.76912659],
[15.48956345],
[12.76129064],
[17.66634183],
[15.16510606],
[17.64682811],
[15.92323854],
[15.44546216],
[14.77801411],
[15.05341302],
[15.20332736],
[17.39178651],
[15.28368538],
[16.68887923],
[17.44860325],
[18.96143484],
[15.54612204],
[15.37232443],
[13.76921432],
[15.11770351],
[16.4154635 ],
[15.79248881],
[15.56873316],
[15.12245667],
[17.11805788],
[16.67168943],
[17.62365032],
[14.52616538],
[15.47096603],
[16.40616715],
[16.26932885],
[15.16708284],
[15.70113026],
[17.81473828],
[17.08190096],
[17.41084682],
[16.38819845],
[16.63022936],
[16.6264706 ],
[15.23746488],
[14.9051472 ],
[16.26707183],
[16.39908441],
[16.77075497],
[16.78218247],
[18.22473005],
[16.54589672],
[14.87209284],
[17.2014801 ],
[15.06687988],
[17.09087854],
[19.54271653],
[13.63372044],
[18.08420174],
[14.02072246],
[16.76747729],
[16.69960782],
[16.92178541],
[15.1993603 ],
[16.18671197],
[17.83242436],
[17.07485645],
[17.24212704],
[14.65790784],
[16.18443791],
[14.3762624 ],
[17.15414486],
[16.87745128],
[16.6279133 ],
[14.08097342],
[13.69001265],
[16.42039415],
[17.45991304],
[13.99387698],
[17.65870468],
[15.75382969],
[17.78439904]])
blockVectorBX = array([[ 0.18308114],
[-0.06895151],
[-0.05953062],
[-0.12093507],
[ 0.09754072],
[-0.25940809],
[ 0.196659 ],
[-0.08579618],
[ 0.03595913],
[-0.02810672],
[ 0.16479524],
[-0.23219995],
[-0.03633988],
[-0.04328704],
[ 0.12778797],
[-0.12396954],
[-0.01943451],
[-0.09894406],
[ 0.00475794],
[ 0.06568952],
[-0.12405158],
[ 0.12902264],
[ 0.10161894],
[ 0.0566365 ],
[ 0.10153613],
[-0.07706346],
[-0.01385105],
[-0.10547125],
[-0.03019386],
[ 0.05977675],
[-0.07795758],
[-0.04471838],
[-0.07745173],
[-0.09526374],
[-0.07565664],
[-0.00142744],
[-0.12593286],
[ 0.02642116],
[ 0.1870775 ],
[ 0.08363633],
[-0.02162192],
[-0.1000453 ],
[-0.08421275],
[ 0.19075778],
[ 0.00572658],
[-0.07179624],
[ 0.02151822],
[ 0.23672127],
[ 0.0135432 ],
[ 0.06956541],
[ 0.03383241],
[-0.03970233],
[-0.12877405],
[-0.03937467],
[-0.02354462],
[ 0.06611872],
[ 0.09456243],
[ 0.10494519],
[ 0.03218875],
[ 0.0997649 ],
[-0.08502874],
[ 0.14121168],
[ 0.05781269],
[-0.03359826],
[ 0.05506123],
[-0.00851774],
[ 0.12754677],
[ 0.17129965],
[ 0.24633778],
[-0.15740011],
[-0.16276711],
[-0.05685871],
[ 0.01803789],
[ 0.09875363],
[ 0.03557544],
[-0.22792376],
[-0.03451248],
[ 0.09332162],
[ 0.02593414],
[ 0.08588683],
[-0.02505877],
[-0.02262759],
[ 0.02102747],
[ 0.04621722],
[ 0.0223505 ],
[ 0.01341355],
[-0.07559083],
[ 0.04255549],
[ 0.01373056],
[ 0.12730495],
[ 0.1351309 ],
[ 0.02086911],
[-0.04229864],
[-0.07199177],
[ 0.04773235],
[ 0.00871706],
[-0.038756 ],
[ 0.00491383],
[-0.06988074],
[ 0.0786757 ]])
blockVectorX = array([[ 0.18308114],
[-0.06895151],
[-0.05953062],
[-0.12093507],
[ 0.09754072],
[-0.25940809],
[ 0.196659 ],
[-0.08579618],
[ 0.03595913],
[-0.02810672],
[ 0.16479524],
[-0.23219995],
[-0.03633988],
[-0.04328704],
[ 0.12778797],
[-0.12396954],
[-0.01943451],
[-0.09894406],
[ 0.00475794],
[ 0.06568952],
[-0.12405158],
[ 0.12902264],
[ 0.10161894],
[ 0.0566365 ],
[ 0.10153613],
[-0.07706346],
[-0.01385105],
[-0.10547125],
[-0.03019386],
[ 0.05977675],
[-0.07795758],
[-0.04471838],
[-0.07745173],
[-0.09526374],
[-0.07565664],
[-0.00142744],
[-0.12593286],
[ 0.02642116],
[ 0.1870775 ],
[ 0.08363633],
[-0.02162192],
[-0.1000453 ],
[-0.08421275],
[ 0.19075778],
[ 0.00572658],
[-0.07179624],
[ 0.02151822],
[ 0.23672127],
[ 0.0135432 ],
[ 0.06956541],
[ 0.03383241],
[-0.03970233],
[-0.12877405],
[-0.03937467],
[-0.02354462],
[ 0.06611872],
[ 0.09456243],
[ 0.10494519],
[ 0.03218875],
[ 0.0997649 ],
[-0.08502874],
[ 0.14121168],
[ 0.05781269],
[-0.03359826],
[ 0.05506123],
[-0.00851774],
[ 0.12754677],
[ 0.17129965],
[ 0.24633778],
[-0.15740011],
[-0.16276711],
[-0.05685871],
[ 0.01803789],
[ 0.09875363],
[ 0.03557544],
[-0.22792376],
[-0.03451248],
[ 0.09332162],
[ 0.02593414],
[ 0.08588683],
[-0.02505877],
[-0.02262759],
[ 0.02102747],
[ 0.04621722],
[ 0.0223505 ],
[ 0.01341355],
[-0.07559083],
[ 0.04255549],
[ 0.01373056],
[ 0.12730495],
[ 0.1351309 ],
[ 0.02086911],
[-0.04229864],
[-0.07199177],
[ 0.04773235],
[ 0.00871706],
[-0.038756 ],
[ 0.00491383],
[-0.06988074],
[ 0.0786757 ]])
blockVectorY = None
gramXAX = array([[18.374728]])
largest = True
maxiter = 20
n = 100
residualTolerance = 1.4901161193847656e-06
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = 0.0
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[18.374728]])
a1 = array([[18.374728]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
___________ Test_SVDS_LOBPCG.test_svd_random_state_2[random_state2] ____________
[gw0] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py:414: in test_svd_random_state_2
res1a = svds(A, k, solver=self.solver, random_state=random_state)
A = array([[0.63696169, 0.26978671, 0.04097352, ..., 0.97262881, 0.88993556,
0.82237383],
[0.47998792, 0.23237292, 0.80188058, ..., 0.7726492 , 0.97826571,
0.58987003],
[0.31968164, 0.18750772, 0.67252663, ..., 0.93376891, 0.68405045,
0.82378136],
...,
[0.18400687, 0.43688732, 0.7695516 , ..., 0.13820355, 0.66263843,
0.46152281],
[0.9259518 , 0.07598897, 0.44222873, ..., 0.97826589, 0.25880505,
0.71360413],
[0.67703467, 0.06811606, 0.11610553, ..., 0.18551999, 0.9356096 ,
0.02193656]])
k = 1
n = 100
random_state = RandomState(MT19937) at 0x7FFFA2A8BC40
random_state_2 = RandomState(MT19937) at 0x7FFF9433CB40
rng = Generator(PCG64) at 0x7FFF943102E0
self = <scipy.sparse.linalg._eigen.tests.test_svds.Test_SVDS_LOBPCG object at 0x7fffa2331b10>
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/_svds.py:487: in svds
_, eigvec = lobpcg(XH_X, X, tol=tol ** 2, maxiter=maxiter,
A = <100x100 MatrixLinearOperator with dtype=float64>
X = array([[ 0.1814364 ],
[-0.12985289],
[-0.12240774],
[ 0.09339871],
[-0.11302722],
[ 0.18726257],
[-0.03985105],
[-0.07201522],
[ 0.18527019],
[ 0.14264354],
[ 0.17993418],
[ 0.08729492],
[-0.08297673],
[ 0.18402951],
[-0.02582139],
[ 0.07731447],
[ 0.09126513],
[-0.0149348 ],
[ 0.05916486],
[ 0.08885208],
[ 0.03626757],
[-0.10592425],
[ 0.02873443],
[ 0.12779364],
[-0.06691971],
[-0.01441688],
[-0.04192585],
[ 0.17817148],
[ 0.06477375],
[ 0.03925783],
[-0.0741793 ],
[ 0.05195518],
[-0.0649701 ],
[ 0.00306679],
[-0.06126202],
[ 0.06517249],
[ 0.05555294],
[-0.02006901],
[ 0.03815416],
[-0.10531348],
[-0.14367858],
[ 0.04233418],
[ 0.01605853],
[ 0.06118354],
[ 0.22960946],
[ 0.09099801],
[-0.08794792],
[ 0.10762145],
[-0.12678407],
[-0.04447241],
[-0.00657489],
[ 0.16507587],
[-0.07175508],
[-0.07962508],
[-0.00948563],
[-0.06392431],
[ 0.10854828],
[-0.10404844],
[-0.11055545],
[-0.04218276],
[-0.04798406],
[ 0.18590512],
[ 0.09147409],
[ 0.00843532],
[-0.11806735],
[ 0.08135205],
[-0.096368 ],
[-0.14883445],
[ 0.11446341],
[ 0.03053655],
[ 0.08872222],
[ 0.03070853],
[ 0.08255328],
[-0.06272453],
[-0.09964646],
[ 0.06566976],
[-0.07740632],
[-0.06643623],
[-0.04388931],
[ 0.00168407],
[-0.03410634],
[-0.13247278],
[-0.06201087],
[-0.21421879],
[ 0.06023933],
[-0.15435386],
[-0.1064043 ],
[ 0.00502596],
[-0.07125486],
[ 0.14866522],
[-0.12456321],
[ 0.02572962],
[-0.00378479],
[-0.1125426 ],
[ 0.05041627],
[-0.01652802],
[ 0.0743599 ],
[ 0.07934236],
[ 0.20842185],
[ 0.1287708 ]])
XH_X = <100x100 _CustomLinearOperator with dtype=float64>
XH_dot = <bound method LinearOperator.rmatvec of <100x100 MatrixLinearOperator with dtype=float64>>
XH_mat = <bound method LinearOperator.rmatmat of <100x100 MatrixLinearOperator with dtype=float64>>
X_dot = <bound method LinearOperator.matvec of <100x100 MatrixLinearOperator with dtype=float64>>
X_matmat = <bound method LinearOperator.matmat of <100x100 MatrixLinearOperator with dtype=float64>>
args = (<100x100 MatrixLinearOperator with dtype=float64>,
1,
None,
0.0,
'LM',
None,
None,
True,
'lobpcg',
RandomState(MT19937) at 0x7FFFA2A8BC40)
k = 1
largest = True
m = 100
matmat_XH_X = <function svds.<locals>.matmat_XH_X at 0x7fff945de7a0>
matvec_XH_X = <function svds.<locals>.matvec_XH_X at 0x7fff945de160>
maxiter = None
n = 100
ncv = None
options = None
random_state = RandomState(MT19937) at 0x7FFFA2A8BC40
return_singular_vectors = True
solver = 'lobpcg'
tol = 0.0
transpose = False
v0 = None
which = 'LM'
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff945dd580>
B = None
M = None
X = array([[ 0.1814364 ],
[-0.12985289],
[-0.12240774],
[ 0.09339871],
[-0.11302722],
[ 0.18726257],
[-0.03985105],
[-0.07201522],
[ 0.18527019],
[ 0.14264354],
[ 0.17993418],
[ 0.08729492],
[-0.08297673],
[ 0.18402951],
[-0.02582139],
[ 0.07731447],
[ 0.09126513],
[-0.0149348 ],
[ 0.05916486],
[ 0.08885208],
[ 0.03626757],
[-0.10592425],
[ 0.02873443],
[ 0.12779364],
[-0.06691971],
[-0.01441688],
[-0.04192585],
[ 0.17817148],
[ 0.06477375],
[ 0.03925783],
[-0.0741793 ],
[ 0.05195518],
[-0.0649701 ],
[ 0.00306679],
[-0.06126202],
[ 0.06517249],
[ 0.05555294],
[-0.02006901],
[ 0.03815416],
[-0.10531348],
[-0.14367858],
[ 0.04233418],
[ 0.01605853],
[ 0.06118354],
[ 0.22960946],
[ 0.09099801],
[-0.08794792],
[ 0.10762145],
[-0.12678407],
[-0.04447241],
[-0.00657489],
[ 0.16507587],
[-0.07175508],
[-0.07962508],
[-0.00948563],
[-0.06392431],
[ 0.10854828],
[-0.10404844],
[-0.11055545],
[-0.04218276],
[-0.04798406],
[ 0.18590512],
[ 0.09147409],
[ 0.00843532],
[-0.11806735],
[ 0.08135205],
[-0.096368 ],
[-0.14883445],
[ 0.11446341],
[ 0.03053655],
[ 0.08872222],
[ 0.03070853],
[ 0.08255328],
[-0.06272453],
[-0.09964646],
[ 0.06566976],
[-0.07740632],
[-0.06643623],
[-0.04388931],
[ 0.00168407],
[-0.03410634],
[-0.13247278],
[-0.06201087],
[-0.21421879],
[ 0.06023933],
[-0.15435386],
[-0.1064043 ],
[ 0.00502596],
[-0.07125486],
[ 0.14866522],
[-0.12456321],
[ 0.02572962],
[-0.00378479],
[-0.1125426 ],
[ 0.05041627],
[-0.01652802],
[ 0.0743599 ],
[ 0.07934236],
[ 0.20842185],
[ 0.1287708 ]])
Y = None
_ = array([[0.09634725]])
bestIterationNumber = 20
bestblockVectorX = array([[ 0.1814364 ],
[-0.12985289],
[-0.12240774],
[ 0.09339871],
[-0.11302722],
[ 0.18726257],
[-0.03985105],
[-0.07201522],
[ 0.18527019],
[ 0.14264354],
[ 0.17993418],
[ 0.08729492],
[-0.08297673],
[ 0.18402951],
[-0.02582139],
[ 0.07731447],
[ 0.09126513],
[-0.0149348 ],
[ 0.05916486],
[ 0.08885208],
[ 0.03626757],
[-0.10592425],
[ 0.02873443],
[ 0.12779364],
[-0.06691971],
[-0.01441688],
[-0.04192585],
[ 0.17817148],
[ 0.06477375],
[ 0.03925783],
[-0.0741793 ],
[ 0.05195518],
[-0.0649701 ],
[ 0.00306679],
[-0.06126202],
[ 0.06517249],
[ 0.05555294],
[-0.02006901],
[ 0.03815416],
[-0.10531348],
[-0.14367858],
[ 0.04233418],
[ 0.01605853],
[ 0.06118354],
[ 0.22960946],
[ 0.09099801],
[-0.08794792],
[ 0.10762145],
[-0.12678407],
[-0.04447241],
[-0.00657489],
[ 0.16507587],
[-0.07175508],
[-0.07962508],
[-0.00948563],
[-0.06392431],
[ 0.10854828],
[-0.10404844],
[-0.11055545],
[-0.04218276],
[-0.04798406],
[ 0.18590512],
[ 0.09147409],
[ 0.00843532],
[-0.11806735],
[ 0.08135205],
[-0.096368 ],
[-0.14883445],
[ 0.11446341],
[ 0.03053655],
[ 0.08872222],
[ 0.03070853],
[ 0.08255328],
[-0.06272453],
[-0.09964646],
[ 0.06566976],
[-0.07740632],
[-0.06643623],
[-0.04388931],
[ 0.00168407],
[-0.03410634],
[-0.13247278],
[-0.06201087],
[-0.21421879],
[ 0.06023933],
[-0.15435386],
[-0.1064043 ],
[ 0.00502596],
[-0.07125486],
[ 0.14866522],
[-0.12456321],
[ 0.02572962],
[-0.00378479],
[-0.1125426 ],
[ 0.05041627],
[-0.01652802],
[ 0.0743599 ],
[ 0.07934236],
[ 0.20842185],
[ 0.1287708 ]])
blockVectorAX = array([[22.35918457],
[19.50299231],
[18.27557592],
[18.24770514],
[20.16057146],
[23.98651873],
[23.46815634],
[19.1041044 ],
[19.68350248],
[24.99282748],
[21.12235306],
[23.68588061],
[18.54329611],
[22.01054568],
[20.80793527],
[21.791311 ],
[22.33882382],
[20.23445955],
[20.83884923],
[22.29287548],
[20.41319972],
[19.74337818],
[20.09566524],
[23.11167451],
[19.86793804],
[20.20434328],
[23.28056228],
[21.09667918],
[21.70427594],
[21.86787074],
[23.29025154],
[21.15337599],
[17.65175287],
[21.04867922],
[22.24520598],
[22.87062369],
[22.53112779],
[22.53210693],
[21.08865443],
[20.01823025],
[22.00231011],
[18.37706422],
[23.91607328],
[24.37085344],
[24.98254785],
[21.89054344],
[19.99749943],
[20.90992946],
[17.83097805],
[21.5224568 ],
[19.51240824],
[22.26319402],
[22.77022882],
[20.09776399],
[20.33333464],
[18.89331805],
[24.4880488 ],
[19.64354774],
[19.23585188],
[21.85650326],
[21.12543176],
[20.99277606],
[22.55654215],
[21.48783197],
[19.98658798],
[23.14665524],
[19.40715955],
[17.99840266],
[20.05935986],
[22.26003721],
[21.79816565],
[23.37037702],
[21.05246378],
[18.08349737],
[21.23062716],
[23.4627629 ],
[21.92757768],
[17.03697117],
[20.62674056],
[20.50684077],
[23.33012951],
[17.85722101],
[17.98199683],
[18.05764967],
[23.76370234],
[20.49662686],
[18.55352224],
[22.4139547 ],
[18.89410989],
[22.84870842],
[19.21909588],
[20.68293372],
[19.56266865],
[21.45147812],
[20.76973937],
[19.83233892],
[21.5445793 ],
[21.37492267],
[24.47771635],
[22.21826341]])
blockVectorBX = array([[ 0.1814364 ],
[-0.12985289],
[-0.12240774],
[ 0.09339871],
[-0.11302722],
[ 0.18726257],
[-0.03985105],
[-0.07201522],
[ 0.18527019],
[ 0.14264354],
[ 0.17993418],
[ 0.08729492],
[-0.08297673],
[ 0.18402951],
[-0.02582139],
[ 0.07731447],
[ 0.09126513],
[-0.0149348 ],
[ 0.05916486],
[ 0.08885208],
[ 0.03626757],
[-0.10592425],
[ 0.02873443],
[ 0.12779364],
[-0.06691971],
[-0.01441688],
[-0.04192585],
[ 0.17817148],
[ 0.06477375],
[ 0.03925783],
[-0.0741793 ],
[ 0.05195518],
[-0.0649701 ],
[ 0.00306679],
[-0.06126202],
[ 0.06517249],
[ 0.05555294],
[-0.02006901],
[ 0.03815416],
[-0.10531348],
[-0.14367858],
[ 0.04233418],
[ 0.01605853],
[ 0.06118354],
[ 0.22960946],
[ 0.09099801],
[-0.08794792],
[ 0.10762145],
[-0.12678407],
[-0.04447241],
[-0.00657489],
[ 0.16507587],
[-0.07175508],
[-0.07962508],
[-0.00948563],
[-0.06392431],
[ 0.10854828],
[-0.10404844],
[-0.11055545],
[-0.04218276],
[-0.04798406],
[ 0.18590512],
[ 0.09147409],
[ 0.00843532],
[-0.11806735],
[ 0.08135205],
[-0.096368 ],
[-0.14883445],
[ 0.11446341],
[ 0.03053655],
[ 0.08872222],
[ 0.03070853],
[ 0.08255328],
[-0.06272453],
[-0.09964646],
[ 0.06566976],
[-0.07740632],
[-0.06643623],
[-0.04388931],
[ 0.00168407],
[-0.03410634],
[-0.13247278],
[-0.06201087],
[-0.21421879],
[ 0.06023933],
[-0.15435386],
[-0.1064043 ],
[ 0.00502596],
[-0.07125486],
[ 0.14866522],
[-0.12456321],
[ 0.02572962],
[-0.00378479],
[-0.1125426 ],
[ 0.05041627],
[-0.01652802],
[ 0.0743599 ],
[ 0.07934236],
[ 0.20842185],
[ 0.1287708 ]])
blockVectorX = array([[ 0.1814364 ],
[-0.12985289],
[-0.12240774],
[ 0.09339871],
[-0.11302722],
[ 0.18726257],
[-0.03985105],
[-0.07201522],
[ 0.18527019],
[ 0.14264354],
[ 0.17993418],
[ 0.08729492],
[-0.08297673],
[ 0.18402951],
[-0.02582139],
[ 0.07731447],
[ 0.09126513],
[-0.0149348 ],
[ 0.05916486],
[ 0.08885208],
[ 0.03626757],
[-0.10592425],
[ 0.02873443],
[ 0.12779364],
[-0.06691971],
[-0.01441688],
[-0.04192585],
[ 0.17817148],
[ 0.06477375],
[ 0.03925783],
[-0.0741793 ],
[ 0.05195518],
[-0.0649701 ],
[ 0.00306679],
[-0.06126202],
[ 0.06517249],
[ 0.05555294],
[-0.02006901],
[ 0.03815416],
[-0.10531348],
[-0.14367858],
[ 0.04233418],
[ 0.01605853],
[ 0.06118354],
[ 0.22960946],
[ 0.09099801],
[-0.08794792],
[ 0.10762145],
[-0.12678407],
[-0.04447241],
[-0.00657489],
[ 0.16507587],
[-0.07175508],
[-0.07962508],
[-0.00948563],
[-0.06392431],
[ 0.10854828],
[-0.10404844],
[-0.11055545],
[-0.04218276],
[-0.04798406],
[ 0.18590512],
[ 0.09147409],
[ 0.00843532],
[-0.11806735],
[ 0.08135205],
[-0.096368 ],
[-0.14883445],
[ 0.11446341],
[ 0.03053655],
[ 0.08872222],
[ 0.03070853],
[ 0.08255328],
[-0.06272453],
[-0.09964646],
[ 0.06566976],
[-0.07740632],
[-0.06643623],
[-0.04388931],
[ 0.00168407],
[-0.03410634],
[-0.13247278],
[-0.06201087],
[-0.21421879],
[ 0.06023933],
[-0.15435386],
[-0.1064043 ],
[ 0.00502596],
[-0.07125486],
[ 0.14866522],
[-0.12456321],
[ 0.02572962],
[-0.00378479],
[-0.1125426 ],
[ 0.05041627],
[-0.01652802],
[ 0.0743599 ],
[ 0.07934236],
[ 0.20842185],
[ 0.1287708 ]])
blockVectorY = None
gramXAX = array([[27.08029181]])
largest = True
maxiter = 20
n = 100
residualTolerance = 1.4901161193847656e-06
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = 0.0
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[27.08029181]])
a1 = array([[27.08029181]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
___________ Test_SVDS_LOBPCG.test_svd_random_state_2[random_state3] ____________
[gw0] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py:414: in test_svd_random_state_2
res1a = svds(A, k, solver=self.solver, random_state=random_state)
A = array([[0.63696169, 0.26978671, 0.04097352, ..., 0.97262881, 0.88993556,
0.82237383],
[0.47998792, 0.23237292, 0.80188058, ..., 0.7726492 , 0.97826571,
0.58987003],
[0.31968164, 0.18750772, 0.67252663, ..., 0.93376891, 0.68405045,
0.82378136],
...,
[0.18400687, 0.43688732, 0.7695516 , ..., 0.13820355, 0.66263843,
0.46152281],
[0.9259518 , 0.07598897, 0.44222873, ..., 0.97826589, 0.25880505,
0.71360413],
[0.67703467, 0.06811606, 0.11610553, ..., 0.18551999, 0.9356096 ,
0.02193656]])
k = 1
n = 100
random_state = Generator(PCG64) at 0x7FFFA240AB20
random_state_2 = Generator(PCG64) at 0x7FFF94310E40
rng = Generator(PCG64) at 0x7FFF94310BA0
self = <scipy.sparse.linalg._eigen.tests.test_svds.Test_SVDS_LOBPCG object at 0x7fffa2331dd0>
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/_svds.py:487: in svds
_, eigvec = lobpcg(XH_X, X, tol=tol ** 2, maxiter=maxiter,
A = <100x100 MatrixLinearOperator with dtype=float64>
X = array([[ 0.0525248 ],
[ 0.10341406],
[-0.01716697],
[-0.11225924],
[ 0.09122325],
[-0.133787 ],
[-0.07450773],
[ 0.0648895 ],
[-0.23511486],
[ 0.04037135],
[-0.06077503],
[ 0.01141852],
[-0.00790997],
[ 0.02111872],
[ 0.07253329],
[-0.07924125],
[ 0.1484769 ],
[ 0.07586877],
[ 0.08816073],
[ 0.1217154 ],
[ 0.08229426],
[ 0.08819688],
[ 0.0078987 ],
[-0.14908208],
[-0.01411072],
[-0.08040577],
[-0.14866078],
[ 0.02700546],
[-0.05940713],
[-0.10760317],
[-0.10898207],
[ 0.02804662],
[ 0.03747725],
[ 0.13818218],
[-0.00145393],
[ 0.10886073],
[ 0.14652116],
[ 0.12017959],
[-0.24714809],
[ 0.12838386],
[ 0.03548653],
[ 0.04427942],
[ 0.03878916],
[ 0.03999389],
[ 0.03337525],
[-0.03750247],
[-0.19869985],
[-0.01138038],
[-0.08398109],
[ 0.11286513],
[-0.03017291],
[ 0.00872225],
[-0.08877442],
[-0.0533544 ],
[-0.00120508],
[-0.15520527],
[ 0.03141827],
[-0.01108338],
[-0.1238946 ],
[-0.2505888 ],
[ 0.05360827],
[-0.03109424],
[-0.05538002],
[-0.02467555],
[ 0.18980164],
[-0.00520365],
[ 0.00905075],
[-0.15538266],
[ 0.17212871],
[ 0.09586734],
[ 0.11148289],
[ 0.00498127],
[ 0.09578028],
[ 0.03875984],
[ 0.06407148],
[-0.01590248],
[-0.15400499],
[ 0.1075039 ],
[-0.20218188],
[-0.02507073],
[-0.02137034],
[-0.10896735],
[ 0.06406459],
[-0.02093224],
[-0.04564791],
[ 0.05431771],
[-0.04979724],
[ 0.14513304],
[ 0.03672317],
[-0.04956255],
[-0.20315418],
[-0.13664574],
[ 0.11356179],
[-0.00528756],
[-0.02958344],
[ 0.17170162],
[-0.13402266],
[-0.06119476],
[-0.04938018],
[ 0.06126576]])
XH_X = <100x100 _CustomLinearOperator with dtype=float64>
XH_dot = <bound method LinearOperator.rmatvec of <100x100 MatrixLinearOperator with dtype=float64>>
XH_mat = <bound method LinearOperator.rmatmat of <100x100 MatrixLinearOperator with dtype=float64>>
X_dot = <bound method LinearOperator.matvec of <100x100 MatrixLinearOperator with dtype=float64>>
X_matmat = <bound method LinearOperator.matmat of <100x100 MatrixLinearOperator with dtype=float64>>
args = (<100x100 MatrixLinearOperator with dtype=float64>,
1,
None,
0.0,
'LM',
None,
None,
True,
'lobpcg',
Generator(PCG64) at 0x7FFFA240AB20)
k = 1
largest = True
m = 100
matmat_XH_X = <function svds.<locals>.matmat_XH_X at 0x7fff945dea20>
matvec_XH_X = <function svds.<locals>.matvec_XH_X at 0x7fff945de200>
maxiter = None
n = 100
ncv = None
options = None
random_state = Generator(PCG64) at 0x7FFFA240AB20
return_singular_vectors = True
solver = 'lobpcg'
tol = 0.0
transpose = False
v0 = None
which = 'LM'
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff945dd940>
B = None
M = None
X = array([[ 0.0525248 ],
[ 0.10341406],
[-0.01716697],
[-0.11225924],
[ 0.09122325],
[-0.133787 ],
[-0.07450773],
[ 0.0648895 ],
[-0.23511486],
[ 0.04037135],
[-0.06077503],
[ 0.01141852],
[-0.00790997],
[ 0.02111872],
[ 0.07253329],
[-0.07924125],
[ 0.1484769 ],
[ 0.07586877],
[ 0.08816073],
[ 0.1217154 ],
[ 0.08229426],
[ 0.08819688],
[ 0.0078987 ],
[-0.14908208],
[-0.01411072],
[-0.08040577],
[-0.14866078],
[ 0.02700546],
[-0.05940713],
[-0.10760317],
[-0.10898207],
[ 0.02804662],
[ 0.03747725],
[ 0.13818218],
[-0.00145393],
[ 0.10886073],
[ 0.14652116],
[ 0.12017959],
[-0.24714809],
[ 0.12838386],
[ 0.03548653],
[ 0.04427942],
[ 0.03878916],
[ 0.03999389],
[ 0.03337525],
[-0.03750247],
[-0.19869985],
[-0.01138038],
[-0.08398109],
[ 0.11286513],
[-0.03017291],
[ 0.00872225],
[-0.08877442],
[-0.0533544 ],
[-0.00120508],
[-0.15520527],
[ 0.03141827],
[-0.01108338],
[-0.1238946 ],
[-0.2505888 ],
[ 0.05360827],
[-0.03109424],
[-0.05538002],
[-0.02467555],
[ 0.18980164],
[-0.00520365],
[ 0.00905075],
[-0.15538266],
[ 0.17212871],
[ 0.09586734],
[ 0.11148289],
[ 0.00498127],
[ 0.09578028],
[ 0.03875984],
[ 0.06407148],
[-0.01590248],
[-0.15400499],
[ 0.1075039 ],
[-0.20218188],
[-0.02507073],
[-0.02137034],
[-0.10896735],
[ 0.06406459],
[-0.02093224],
[-0.04564791],
[ 0.05431771],
[-0.04979724],
[ 0.14513304],
[ 0.03672317],
[-0.04956255],
[-0.20315418],
[-0.13664574],
[ 0.11356179],
[-0.00528756],
[-0.02958344],
[ 0.17170162],
[-0.13402266],
[-0.06119476],
[-0.04938018],
[ 0.06126576]])
Y = None
_ = array([[0.10448894]])
bestIterationNumber = 20
bestblockVectorX = array([[ 0.0525248 ],
[ 0.10341406],
[-0.01716697],
[-0.11225924],
[ 0.09122325],
[-0.133787 ],
[-0.07450773],
[ 0.0648895 ],
[-0.23511486],
[ 0.04037135],
[-0.06077503],
[ 0.01141852],
[-0.00790997],
[ 0.02111872],
[ 0.07253329],
[-0.07924125],
[ 0.1484769 ],
[ 0.07586877],
[ 0.08816073],
[ 0.1217154 ],
[ 0.08229426],
[ 0.08819688],
[ 0.0078987 ],
[-0.14908208],
[-0.01411072],
[-0.08040577],
[-0.14866078],
[ 0.02700546],
[-0.05940713],
[-0.10760317],
[-0.10898207],
[ 0.02804662],
[ 0.03747725],
[ 0.13818218],
[-0.00145393],
[ 0.10886073],
[ 0.14652116],
[ 0.12017959],
[-0.24714809],
[ 0.12838386],
[ 0.03548653],
[ 0.04427942],
[ 0.03878916],
[ 0.03999389],
[ 0.03337525],
[-0.03750247],
[-0.19869985],
[-0.01138038],
[-0.08398109],
[ 0.11286513],
[-0.03017291],
[ 0.00872225],
[-0.08877442],
[-0.0533544 ],
[-0.00120508],
[-0.15520527],
[ 0.03141827],
[-0.01108338],
[-0.1238946 ],
[-0.2505888 ],
[ 0.05360827],
[-0.03109424],
[-0.05538002],
[-0.02467555],
[ 0.18980164],
[-0.00520365],
[ 0.00905075],
[-0.15538266],
[ 0.17212871],
[ 0.09586734],
[ 0.11148289],
[ 0.00498127],
[ 0.09578028],
[ 0.03875984],
[ 0.06407148],
[-0.01590248],
[-0.15400499],
[ 0.1075039 ],
[-0.20218188],
[-0.02507073],
[-0.02137034],
[-0.10896735],
[ 0.06406459],
[-0.02093224],
[-0.04564791],
[ 0.05431771],
[-0.04979724],
[ 0.14513304],
[ 0.03672317],
[-0.04956255],
[-0.20315418],
[-0.13664574],
[ 0.11356179],
[-0.00528756],
[-0.02958344],
[ 0.17170162],
[-0.13402266],
[-0.06119476],
[-0.04938018],
[ 0.06126576]])
blockVectorAX = array([[-13.50164956],
[-13.04134198],
[-14.71157105],
[-12.57442113],
[-11.79501089],
[-13.81944034],
[-15.46006051],
[-10.78935858],
[-13.75867003],
[-14.17500664],
[-14.6087925 ],
[-13.69127244],
[-14.23230312],
[-13.94479385],
[-12.24857667],
[-14.09595019],
[-14.04433189],
[-12.13432375],
[-10.88079125],
[-10.9147541 ],
[-11.89467854],
[-12.50152173],
[-12.64174436],
[-15.02951979],
[-11.80913464],
[-12.23096245],
[-16.24634396],
[-12.48217588],
[-14.19296707],
[-13.92090684],
[-15.51327786],
[-11.80386508],
[-11.5938195 ],
[-12.88333541],
[-14.62052148],
[-13.69264533],
[-13.33921954],
[-13.6448975 ],
[-15.09191873],
[-12.96367727],
[-13.87687135],
[-12.59932579],
[-12.1427995 ],
[-13.51082827],
[-14.59754141],
[-13.86078832],
[-13.3215048 ],
[-12.7458097 ],
[-13.19047345],
[-13.01301411],
[-12.02372727],
[-13.3668746 ],
[-14.51173627],
[-12.45151724],
[-13.11507488],
[-13.81354829],
[-15.42329471],
[-13.32490144],
[-15.27925434],
[-15.02563159],
[-13.61757245],
[-13.04691842],
[-13.90632227],
[-14.01461741],
[-10.96700243],
[-14.02030932],
[-12.95534613],
[-13.76404469],
[ -9.61284174],
[-15.07888303],
[-12.720474 ],
[-13.98444443],
[-12.12527735],
[-13.77661907],
[-13.76569832],
[-13.63288615],
[-15.98871388],
[-11.34859422],
[-14.45482077],
[-14.48371179],
[-14.71304299],
[-13.00572886],
[-11.78620347],
[-13.30873624],
[-13.42802951],
[-14.56089827],
[-12.57406453],
[-12.71175158],
[-12.0034389 ],
[-13.97381352],
[-14.48648093],
[-13.62981603],
[ -9.98720996],
[-14.03566228],
[-13.25164668],
[-12.44567382],
[-13.14615999],
[-13.1139597 ],
[-13.04818871],
[-14.06667381]])
blockVectorBX = array([[ 0.0525248 ],
[ 0.10341406],
[-0.01716697],
[-0.11225924],
[ 0.09122325],
[-0.133787 ],
[-0.07450773],
[ 0.0648895 ],
[-0.23511486],
[ 0.04037135],
[-0.06077503],
[ 0.01141852],
[-0.00790997],
[ 0.02111872],
[ 0.07253329],
[-0.07924125],
[ 0.1484769 ],
[ 0.07586877],
[ 0.08816073],
[ 0.1217154 ],
[ 0.08229426],
[ 0.08819688],
[ 0.0078987 ],
[-0.14908208],
[-0.01411072],
[-0.08040577],
[-0.14866078],
[ 0.02700546],
[-0.05940713],
[-0.10760317],
[-0.10898207],
[ 0.02804662],
[ 0.03747725],
[ 0.13818218],
[-0.00145393],
[ 0.10886073],
[ 0.14652116],
[ 0.12017959],
[-0.24714809],
[ 0.12838386],
[ 0.03548653],
[ 0.04427942],
[ 0.03878916],
[ 0.03999389],
[ 0.03337525],
[-0.03750247],
[-0.19869985],
[-0.01138038],
[-0.08398109],
[ 0.11286513],
[-0.03017291],
[ 0.00872225],
[-0.08877442],
[-0.0533544 ],
[-0.00120508],
[-0.15520527],
[ 0.03141827],
[-0.01108338],
[-0.1238946 ],
[-0.2505888 ],
[ 0.05360827],
[-0.03109424],
[-0.05538002],
[-0.02467555],
[ 0.18980164],
[-0.00520365],
[ 0.00905075],
[-0.15538266],
[ 0.17212871],
[ 0.09586734],
[ 0.11148289],
[ 0.00498127],
[ 0.09578028],
[ 0.03875984],
[ 0.06407148],
[-0.01590248],
[-0.15400499],
[ 0.1075039 ],
[-0.20218188],
[-0.02507073],
[-0.02137034],
[-0.10896735],
[ 0.06406459],
[-0.02093224],
[-0.04564791],
[ 0.05431771],
[-0.04979724],
[ 0.14513304],
[ 0.03672317],
[-0.04956255],
[-0.20315418],
[-0.13664574],
[ 0.11356179],
[-0.00528756],
[-0.02958344],
[ 0.17170162],
[-0.13402266],
[-0.06119476],
[-0.04938018],
[ 0.06126576]])
blockVectorX = array([[ 0.0525248 ],
[ 0.10341406],
[-0.01716697],
[-0.11225924],
[ 0.09122325],
[-0.133787 ],
[-0.07450773],
[ 0.0648895 ],
[-0.23511486],
[ 0.04037135],
[-0.06077503],
[ 0.01141852],
[-0.00790997],
[ 0.02111872],
[ 0.07253329],
[-0.07924125],
[ 0.1484769 ],
[ 0.07586877],
[ 0.08816073],
[ 0.1217154 ],
[ 0.08229426],
[ 0.08819688],
[ 0.0078987 ],
[-0.14908208],
[-0.01411072],
[-0.08040577],
[-0.14866078],
[ 0.02700546],
[-0.05940713],
[-0.10760317],
[-0.10898207],
[ 0.02804662],
[ 0.03747725],
[ 0.13818218],
[-0.00145393],
[ 0.10886073],
[ 0.14652116],
[ 0.12017959],
[-0.24714809],
[ 0.12838386],
[ 0.03548653],
[ 0.04427942],
[ 0.03878916],
[ 0.03999389],
[ 0.03337525],
[-0.03750247],
[-0.19869985],
[-0.01138038],
[-0.08398109],
[ 0.11286513],
[-0.03017291],
[ 0.00872225],
[-0.08877442],
[-0.0533544 ],
[-0.00120508],
[-0.15520527],
[ 0.03141827],
[-0.01108338],
[-0.1238946 ],
[-0.2505888 ],
[ 0.05360827],
[-0.03109424],
[-0.05538002],
[-0.02467555],
[ 0.18980164],
[-0.00520365],
[ 0.00905075],
[-0.15538266],
[ 0.17212871],
[ 0.09586734],
[ 0.11148289],
[ 0.00498127],
[ 0.09578028],
[ 0.03875984],
[ 0.06407148],
[-0.01590248],
[-0.15400499],
[ 0.1075039 ],
[-0.20218188],
[-0.02507073],
[-0.02137034],
[-0.10896735],
[ 0.06406459],
[-0.02093224],
[-0.04564791],
[ 0.05431771],
[-0.04979724],
[ 0.14513304],
[ 0.03672317],
[-0.04956255],
[-0.20315418],
[-0.13664574],
[ 0.11356179],
[-0.00528756],
[-0.02958344],
[ 0.17170162],
[-0.13402266],
[-0.06119476],
[-0.04938018],
[ 0.06126576]])
blockVectorY = None
gramXAX = array([[13.67702326]])
largest = True
maxiter = 20
n = 100
residualTolerance = 1.4901161193847656e-06
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = 0.0
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[13.67702326]])
a1 = array([[13.67702326]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
______________________ Test_SVDS_LOBPCG.test_svd_maxiter _______________________
[gw0] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py:462: in test_svd_maxiter
svds(A, k, maxiter=1, solver=self.solver)
A = array([[0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 1., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 2., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 3., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 4., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 5., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 6., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 7., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 8.]])
k = 1
s = array([8.])
self = <scipy.sparse.linalg._eigen.tests.test_svds.Test_SVDS_LOBPCG object at 0x7fffa2332450>
u = array([[0.],
[0.],
[0.],
[0.],
[0.],
[0.],
[0.],
[0.],
[1.]])
vh = array([[0., 0., 0., 0., 0., 0., 0., 0., 1.]])
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/_svds.py:487: in svds
_, eigvec = lobpcg(XH_X, X, tol=tol ** 2, maxiter=maxiter,
A = <9x9 MatrixLinearOperator with dtype=float64>
X = array([[ 0.33119592],
[-0.59100724],
[ 0.1398967 ],
[-0.27356884],
[-0.10948264],
[ 0.3836148 ],
[-0.3627781 ],
[-0.37671771],
[-0.11805832]])
XH_X = <9x9 _CustomLinearOperator with dtype=float64>
XH_dot = <bound method LinearOperator.rmatvec of <9x9 MatrixLinearOperator with dtype=float64>>
XH_mat = <bound method LinearOperator.rmatmat of <9x9 MatrixLinearOperator with dtype=float64>>
X_dot = <bound method LinearOperator.matvec of <9x9 MatrixLinearOperator with dtype=float64>>
X_matmat = <bound method LinearOperator.matmat of <9x9 MatrixLinearOperator with dtype=float64>>
args = (<9x9 MatrixLinearOperator with dtype=float64>,
1,
None,
0.0,
'LM',
None,
1,
True,
'lobpcg',
RandomState(MT19937) at 0x7FFFF4ABD340)
k = 1
largest = True
m = 9
matmat_XH_X = <function svds.<locals>.matmat_XH_X at 0x7fff945deb60>
matvec_XH_X = <function svds.<locals>.matvec_XH_X at 0x7fff945de0c0>
maxiter = 1
n = 9
ncv = None
options = None
random_state = RandomState(MT19937) at 0x7FFFF4ABD340
return_singular_vectors = True
solver = 'lobpcg'
tol = 0.0
transpose = False
v0 = None
which = 'LM'
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff945df600>
B = None
M = None
X = array([[ 0.33119592],
[-0.59100724],
[ 0.1398967 ],
[-0.27356884],
[-0.10948264],
[ 0.3836148 ],
[-0.3627781 ],
[-0.37671771],
[-0.11805832]])
Y = None
_ = array([[0.28377569]])
bestIterationNumber = 1
bestblockVectorX = array([[ 0.33119592],
[-0.59100724],
[ 0.1398967 ],
[-0.27356884],
[-0.10948264],
[ 0.3836148 ],
[-0.3627781 ],
[-0.37671771],
[-0.11805832]])
blockVectorAX = array([[ 0. ],
[ -0.59100724],
[ 0.5595868 ],
[ -2.4621196 ],
[ -1.75172225],
[ 9.59036999],
[-13.06001157],
[-18.45916758],
[ -7.55573232]])
blockVectorBX = array([[ 0.33119592],
[-0.59100724],
[ 0.1398967 ],
[-0.27356884],
[-0.10948264],
[ 0.3836148 ],
[-0.3627781 ],
[-0.37671771],
[-0.11805832]])
blockVectorX = array([[ 0.33119592],
[-0.59100724],
[ 0.1398967 ],
[-0.27356884],
[-0.10948264],
[ 0.3836148 ],
[-0.3627781 ],
[-0.37671771],
[-0.11805832]])
blockVectorY = None
gramXAX = array([[17.55572263]])
largest = True
maxiter = 1
n = 9
residualTolerance = 1.341104507446289e-07
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = 0.0
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[17.55572263]])
a1 = array([[17.55572263]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_______________________________ test_regression ________________________________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py:191: in test_regression
w, _ = lobpcg(A, X)
A = array([[1., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 1., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 1., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 1., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 1., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 1., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 1., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 1., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 1., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 1.]])
X = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
n = 10
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff950ac5e0>
B = None
M = None
X = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
Y = None
_ = array([[0.31622777]])
bestIterationNumber = 20
bestblockVectorX = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
blockVectorAX = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
blockVectorBX = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
blockVectorX = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
blockVectorY = None
gramXAX = array([[1.]])
largest = True
maxiter = 20
n = 10
residualTolerance = 1.4901161193847656e-07
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = None
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_________________ test_failure_to_run_iterations_nonsymmetric __________________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py:358: in test_failure_to_run_iterations_nonsymmetric
eigenvalues, _ = lobpcg(A, Q, maxiter=20)
A = array([[0., 1., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])
Q = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff950afec0>
B = None
M = None
X = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
Y = None
_ = array([[0.31622777]])
bestIterationNumber = 20
bestblockVectorX = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
blockVectorAX = array([[0.31622777],
[0. ],
[0. ],
[0. ],
[0. ],
[0. ],
[0. ],
[0. ],
[0. ],
[0. ]])
blockVectorBX = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
blockVectorX = array([[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777],
[0.31622777]])
blockVectorY = None
gramXAX = array([[0.1]])
largest = True
maxiter = 20
n = 10
residualTolerance = 1.4901161193847656e-07
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = None
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[0.1]])
a1 = array([[0.1]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
________________________________ test_hermitian ________________________________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py:394: in test_hermitian
w, v = lobpcg(H, X, B, maxiter=99, verbosityLevel=0)
B = array([[17.95762782-8.01727053e-17j, 6.5963015 -2.38586620e+00j,
5.99199405-1.76426313e+00j, 5.7334948 -2.34197732e+00j,
6.23375885-1.77046431e+00j, 5.83150644-2.37411976e+00j,
6.025081 -1.93716369e+00j, 6.49128189-4.24486312e+00j,
5.73966873-2.92033384e+00j, 5.53837614-2.61698767e+00j,
5.57306167-2.08640923e+00j, 4.59244633-2.69176919e+00j],
[ 6.5963015 +2.38586620e+00j, 19.07051231+6.46373319e-18j,
7.08709523+2.46199764e-01j, 7.00506202-5.47130983e-01j,
6.52095976+1.68308562e-01j, 6.31282381-7.25671624e-02j,
6.16640018+1.29388156e+00j, 7.54838169-1.80014313e+00j,
6.73676986-1.35543150e+00j, 6.5635997 +1.09871008e-01j,
5.56185634+1.33848156e+00j, 5.84864344+1.13839516e+00j],
[ 5.99199405+1.76426313e+00j, 7.08709523-2.46199764e-01j,
18.38466066-9.46025179e-17j, 6.81118162-4.46089400e-01j,
5.71178049-3.02434097e-01j, 6.30547559-1.43470160e+00j,
5.70446566+7.74505606e-02j, 7.29129557-2.23402049e+00j,
6.33390463-1.55068107e+00j, 7.21049632-2.69615528e-01j,
5.92159622+7.30450732e-03j, 5.6643947 -6.11990260e-01j],
[ 5.7334948 +2.34197732e+00j, 7.00506202+5.47130983e-01j,
6.81118162+4.46089400e-01j, 19.17041622-1.43996625e-17j,
6.57530516+3.49614241e-02j, 5.5586956 -6.98729828e-01j,
5.99988913+1.09614944e+00j, 8.42679974+1.08750000e-01j,
6.62053395-3.30847208e-01j, 6.68782303-2.45507127e-01j,
6.47031048+1.47753629e-01j, 5.53865152+8.84592727e-01j],
[ 6.23375885+1.77046431e+00j, 6.52095976-1.68308562e-01j,
5.71178049+3.02434097e-01j, 6.57530516-3.49614241e-02j,
17.7071095 +2.57504619e-17j, 4.96713856-7.48174532e-01j,
5.24984726+9.06430591e-01j, 7.11872464-1.01272251e+00j,
4.97684068-1.15287602e+00j, 5.75428293+1.88435851e-01j,
5.67844699-3.08778952e-01j, 4.73307565+2.70030012e-01j],
[ 5.83150644+2.37411976e+00j, 6.31282381+7.25671624e-02j,
6.30547559+1.43470160e+00j, 5.5586956 +6.98729828e-01j,
4.96713856+7.48174532e-01j, 18.12302909-2.55192745e-17j,
6.31879642+1.21672818e+00j, 6.72850833-3.90016991e-01j,
6.66142904-9.50628237e-02j, 5.67059975+5.05242454e-01j,
5.19372805+1.09623084e+00j, 6.23053486-1.16801377e-01j],
[ 6.025081 +1.93716369e+00j, 6.16640018-1.29388156e+00j,
5.70446566-7.74505606e-02j, 5.99988913-1.09614944e+00j,
5.24984726-9.06430591e-01j, 6.31879642-1.21672818e+00j,
17.75849104+5.94630099e-17j, 7.36538446-1.81797035e+00j,
5.88724945-1.17688547e+00j, 6.95832861-8.05347425e-01j,
5.6384689 +2.29199598e-01j, 5.93368982-1.86191268e+00j],
[ 6.49128189+4.24486312e+00j, 7.54838169+1.80014313e+00j,
7.29129557+2.23402049e+00j, 8.42679974-1.08750000e-01j,
7.11872464+1.01272251e+00j, 6.72850833+3.90016991e-01j,
7.36538446+1.81797035e+00j, 20.65647092+2.13732881e-17j,
7.53127229+5.02841768e-01j, 7.36509759+1.20912633e+00j,
6.46697633+7.30861384e-01j, 6.76033818+2.87181579e-01j],
[ 5.73966873+2.92033384e+00j, 6.73676986+1.35543150e+00j,
6.33390463+1.55068107e+00j, 6.62053395+3.30847208e-01j,
4.97684068+1.15287602e+00j, 6.66142904+9.50628237e-02j,
5.88724945+1.17688547e+00j, 7.53127229-5.02841768e-01j,
17.92726651-3.31724574e-17j, 5.81393245+3.82310335e-01j,
5.41883563+1.06880305e+00j, 5.09483675+2.80192853e-01j],
[ 5.53837614+2.61698767e+00j, 6.5635997 -1.09871008e-01j,
7.21049632+2.69615528e-01j, 6.68782303+2.45507127e-01j,
5.75428293-1.88435851e-01j, 5.67059975-5.05242454e-01j,
6.95832861+8.05347425e-01j, 7.36509759-1.20912633e+00j,
5.81393245-3.82310335e-01j, 18.7690018 -7.89391421e-17j,
6.25892991+9.47764077e-01j, 5.70078967-5.23889062e-01j],
[ 5.57306167+2.08640923e+00j, 5.56185634-1.33848156e+00j,
5.92159622-7.30450732e-03j, 6.47031048-1.47753629e-01j,
5.67844699+3.08778952e-01j, 5.19372805-1.09623084e+00j,
5.6384689 -2.29199598e-01j, 6.46697633-7.30861384e-01j,
5.41883563-1.06880305e+00j, 6.25892991-9.47764077e-01j,
17.18152171+1.04172999e-17j, 5.36468441-7.02549128e-01j],
[ 4.59244633+2.69176919e+00j, 5.84864344-1.13839516e+00j,
5.6643947 +6.11990260e-01j, 5.53865152-8.84592727e-01j,
4.73307565-2.70030012e-01j, 6.23053486+1.16801377e-01j,
5.93368982+1.86191268e+00j, 6.76033818-2.87181579e-01j,
5.09483675-2.80192853e-01j, 5.70078967+5.23889062e-01j,
5.36468441+7.02549128e-01j, 17.73920372-8.30354535e-17j]])
H = array([[11.38749405+0.j , 1.34633711+0.22754789j,
0.28073607+0.23983187j, 0.78296277+0.02738613j,
1.08101553-0.7172966j , 1.34835736-0.4335326j ,
1.26009338+0.57716474j, 1.68247534+0.00567585j,
1.43918105+0.15782584j, 1.31596766+0.62814256j,
1.10756161+0.08828549j, 0.8067513 -0.36888078j],
[ 1.34633711-0.22754789j, 10.07148537+0.j ,
0.87244494-0.78816231j, 1.33313669-0.56967192j,
0.88399866-0.29022271j, 1.74225588-0.13198612j,
1.35155477-0.42468507j, 1.24993106-0.70021391j,
0.87607588-0.09356736j, 0.82683627+0.11855832j,
0.7476219 -0.4428528j , 1.23125909-0.46249571j],
[ 0.28073607-0.23983187j, 0.87244494+0.78816231j,
10.58435473+0.j , 1.64352629+0.45451781j,
1.02410614-0.48457814j, 0.94536619-0.66236455j,
1.03349795-0.10599327j, 1.02535626-0.07828621j,
0.39857239+0.04661364j, 1.74008884+0.25227005j,
1.54699457-0.30949384j, 0.70079285+0.19700897j],
[ 0.78296277-0.02738613j, 1.33313669+0.56967192j,
1.64352629-0.45451781j, 10.30472897+0.j ,
1.7652268 -0.51940534j, 0.13736304+0.02650657j,
1.26756308+0.144446j , 1.07545901-0.24983096j,
0.80664041+0.07090809j, 1.45542708+0.10777364j,
0.70770113-0.29297195j, 1.89593155-0.11399522j],
[ 1.08101553+0.7172966j , 0.88399866+0.29022271j,
1.02410614+0.48457814j, 1.7652268 +0.51940534j,
11.4237409 +0.j , 0.06798506+0.28771147j,
1.06209414-0.18630827j, 0.33636194+0.15967796j,
1.58849496+0.71583906j, 1.28076649-0.46674216j,
1.75639703+0.83308422j, 1.93230938+0.10226578j],
[ 1.34835736+0.4335326j , 1.74225588+0.13198612j,
0.94536619+0.66236455j, 0.13736304-0.02650657j,
0.06798506-0.28771147j, 10.68420775+0.j ,
1.22435128-0.15894865j, 1.24019733+0.18511116j,
1.64949596-0.47769247j, 0.84000125+0.22971725j,
0.48905007-0.1154104j , 1.53340948+0.58715737j],
[ 1.26009338-0.57716474j, 1.35155477+0.42468507j,
1.03349795+0.10599327j, 1.26756308-0.144446j ,
1.06209414+0.18630827j, 1.22435128+0.15894865j,
11.53638933+0.j , 0.94149495-0.06806433j,
0.94550549-0.89157406j, 1.21533857+0.2464858j ,
0.76045251+0.23879031j, 1.1498176 +0.46576563j],
[ 1.68247534-0.00567585j, 1.24993106+0.70021391j,
1.02535626+0.07828621j, 1.07545901+0.24983096j,
0.33636194-0.15967796j, 1.24019733-0.18511116j,
0.94149495+0.06806433j, 11.37276046+0.j ,
1.06310204+0.31606016j, 0.33998334-0.75944299j,
0.89593712-0.72953573j, 1.79568065-0.58953577j],
[ 1.43918105-0.15782584j, 0.87607588+0.09356736j,
0.39857239-0.04661364j, 0.80664041-0.07090809j,
1.58849496-0.71583906j, 1.64949596+0.47769247j,
0.94550549+0.89157406j, 1.06310204-0.31606016j,
10.57430543+0.j , 0.69565638+0.23373377j,
1.18889693+0.87537176j, 1.62691565+0.45022531j],
[ 1.31596766-0.62814256j, 0.82683627-0.11855832j,
1.74008884-0.25227005j, 1.45542708-0.10777364j,
1.28076649+0.46674216j, 0.84000125-0.22971725j,
1.21533857-0.2464858j , 0.33998334+0.75944299j,
0.69565638-0.23373377j, 11.51257446+0.j ,
0.42864794-0.33291739j, 1.28119365+0.68700726j],
[ 1.10756161-0.08828549j, 0.7476219 +0.4428528j ,
1.54699457+0.30949384j, 0.70770113+0.29297195j,
1.75639703-0.83308422j, 0.48905007+0.1154104j ,
0.76045251-0.23879031j, 0.89593712+0.72953573j,
1.18889693-0.87537176j, 0.42864794+0.33291739j,
10.20221498+0.j , 0.63196955-0.40721617j],
[ 0.8067513 +0.36888078j, 1.23125909+0.46249571j,
0.70079285-0.19700897j, 1.89593155+0.11399522j,
1.93230938-0.10226578j, 1.53340948-0.58715737j,
1.1498176 -0.46576563j, 1.79568065+0.58953577j,
1.62691565-0.45022531j, 1.28119365-0.68700726j,
0.63196955+0.40721617j, 10.73107806+0.j ]])
X = array([[ 0.0115282 -0.09240449j],
[ 0.04844442+0.02708474j],
[ 0.04409443-0.04116974j],
[-0.01912956-0.09014714j],
[-0.01271432+0.07278989j],
[ 0.05162032+0.02976078j],
[-0.0079671 -0.05231398j],
[-0.02342536-0.05577675j],
[ 0.06395756+0.04000277j],
[ 0.04765571-0.04032468j],
[ 0.0008631 +0.05953141j],
[-0.02727185+0.02831362j]])
_ = array([[ 0.53617513+0.j , 0.7731143 +0.j ,
-0.338837 -0.j ],
[-0.7732897 -0.17908408j, 0.32869965+0.04121778j,
-0.47366768-0.18933688j],
[ 0.28669256-0.01660321j, -0.5371946 -0.06303769j,
-0.7720393 -0.17010413j]], dtype=complex64)
db = True
dh = True
dx = True
gen = True
gens = [True, False]
j = 1
k = 1
ks = [1, 2]
rnd = RandomState(MT19937) at 0x7FFF93D16B40
s = 12
sizes = [3, 12]
v = array([[-0.33883694+0.j , 0.77311456+0.j ],
[-0.47366762-0.18933687j, 0.3286995 +0.04121774j],
[-0.77203923-0.17010412j, -0.5371945 -0.06303769j]],
dtype=complex64)
vx = array([ 0.77311456+0.j , 0.3286995 +0.04121774j,
-0.5371945 -0.06303769j], dtype=complex64)
w = array([11.93122 , 10.563231], dtype=float32)
w0 = array([ 9.474301, 10.563232, 11.93122 ], dtype=float32)
wb = array([11.93121968, 10.56323195])
wx = 10.563231
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff94f84180>
B = <function _makeMatMat.<locals>.<lambda> at 0x7fff94f84360>
M = None
X = array([[ 0.0115282 -0.09240449j],
[ 0.04844442+0.02708474j],
[ 0.04409443-0.04116974j],
[-0.01912956-0.09014714j],
[-0.01271432+0.07278989j],
[ 0.05162032+0.02976078j],
[-0.0079671 -0.05231398j],
[-0.02342536-0.05577675j],
[ 0.06395756+0.04000277j],
[ 0.04765571-0.04032468j],
[ 0.0008631 +0.05953141j],
[-0.02727185+0.02831362j]])
Y = None
_ = array([[0.04592942-0.j]])
bestIterationNumber = 99
bestblockVectorX = array([[ 0.0115282 -0.09240449j],
[ 0.04844442+0.02708474j],
[ 0.04409443-0.04116974j],
[-0.01912956-0.09014714j],
[-0.01271432+0.07278989j],
[ 0.05162032+0.02976078j],
[-0.0079671 -0.05231398j],
[-0.02342536-0.05577675j],
[ 0.06395756+0.04000277j],
[ 0.04765571-0.04032468j],
[ 0.0008631 +0.05953141j],
[-0.02727185+0.02831362j]])
blockVectorAX = array([[ 0.46003042-0.9923471j ],
[ 0.52447959+0.05120631j],
[ 0.63863157-0.52635752j],
[-0.01568868-0.92473499j],
[ 0.03589382+0.72098758j],
[ 0.85792326+0.17160332j],
[ 0.0473663 -0.74127261j],
[-0.02978209-0.72604548j],
[ 0.74584526+0.40505394j],
[ 0.60921579-0.73062222j],
[ 0.33194254+0.4994115j ],
[-0.03683406+0.05538922j]])
blockVectorBX = array([[1.0674054 -2.1997665j ],
[1.86957368-0.63237422j],
[1.87043811-1.45569803j],
[1.16499462-1.98280906j],
[1.05999133-0.09142133j],
[2.02913158-0.31726484j],
[1.16804683-1.57068254j],
[1.38139462-1.38149784j],
[2.10924881-0.25796863j],
[1.93481588-1.3902961j ],
[1.18113551-0.31428349j],
[0.96737004-0.33163694j]])
blockVectorX = array([[ 0.0115282 -0.09240449j],
[ 0.04844442+0.02708474j],
[ 0.04409443-0.04116974j],
[-0.01912956-0.09014714j],
[-0.01271432+0.07278989j],
[ 0.05162032+0.02976078j],
[-0.0079671 -0.05231398j],
[-0.02342536-0.05577675j],
[ 0.06395756+0.04000277j],
[ 0.04765571-0.04032468j],
[ 0.0008631 +0.05953141j],
[-0.02727185+0.02831362j]])
blockVectorY = None
gramXAX = array([[0.59329174-9.75781955e-18j]])
largest = True
maxiter = 99
n = 12
residualTolerance = 1.7881393432617188e-07
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = None
verbosityLevel = 0
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (lrwork>=max(24*n,1)||lrwork==-1) failed for 10th keyword lrwork: zheevr:lrwork=1
_job = 'V'
a = array([[0.59329174-9.75781955e-18j]])
a1 = array([[0.59329174-9.75781955e-18j]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = True
driver = 'evr'
drv = <fortran function zheevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function zheevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1, 1)
lwork_args = {'liwork': 1, 'lrwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'he'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
________________________________ test_verbosity ________________________________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py:433: in test_verbosity
_, _ = lobpcg(A, Q, maxiter=3, verbosityLevel=9)
A = array([[14.79920401, 3.42395794, 1.11801536, -4.7827952 , -1.46884083,
-5.10772534, -6.77429909, 0.42197369, -2.06446699, 2.03698005],
[ 3.42395794, 6.13984945, 1.00419995, 1.28177262, -6.00453977,
0.18025203, -4.36294474, -0.36823381, 3.1651521 , 1.73667183],
[ 1.11801536, 1.00419995, 20.05555765, -1.66947272, -4.6828298 ,
0.72790446, 1.57151526, 1.70700038, 5.72250433, 1.51617025],
[-4.7827952 , 1.28177262, -1.66947272, 8.22496312, -2.85697891,
3.6772828 , 2.66314185, -0.31454383, 3.89820981, 0.25640658],
[-1.46884083, -6.00453977, -4.6828298 , -2.85697891, 15.10836347,
0.03741818, 3.17647392, -4.07395203, -5.55081048, 0.83053424],
[-5.10772534, 0.18025203, 0.72790446, 3.6772828 , 0.03741818,
3.42049004, 3.32764111, -0.08753149, 4.05858414, 0.18171656],
[-6.77429909, -4.36294474, 1.57151526, 2.66314185, 3.17647392,
3.32764111, 8.1132507 , 2.45230704, 1.25663944, -1.52929893],
[ 0.42197369, -0.36823381, 1.70700038, -0.31454383, -4.07395203,
-0.08753149, 2.45230704, 5.19565616, 0.46521361, -2.50529166],
[-2.06446699, 3.1651521 , 5.72250433, 3.89820981, -5.55081048,
4.05858414, 1.25663944, 0.46521361, 14.23551289, 2.01659191],
[ 2.03698005, 1.73667183, 1.51617025, 0.25640658, 0.83053424,
0.18171656, -1.52929893, -2.50529166, 2.01659191, 6.64751432]])
Q = array([[ 0.42438871],
[-0.30373232],
[-0.28631776],
[ 0.2184642 ],
[-0.26437626],
[ 0.4380164 ],
[-0.09321358],
[-0.16844716],
[ 0.43335612],
[ 0.33365028]])
X = array([[ 1.76405235, 0.40015721, 0.97873798, 2.2408932 , 1.86755799,
-0.97727788, 0.95008842, -0.15135721, -0.10321885, 0.4105985 ],
[ 0.14404357, 1.45427351, 0.76103773, 0.12167502, 0.44386323,
0.33367433, 1.49407907, -0.20515826, 0.3130677 , -0.85409574],
[-2.55298982, 0.6536186 , 0.8644362 , -0.74216502, 2.26975462,
-1.45436567, 0.04575852, -0.18718385, 1.53277921, 1.46935877],
[ 0.15494743, 0.37816252, -0.88778575, -1.98079647, -0.34791215,
0.15634897, 1.23029068, 1.20237985, -0.38732682, -0.30230275],
[-1.04855297, -1.42001794, -1.70627019, 1.9507754 , -0.50965218,
-0.4380743 , -1.25279536, 0.77749036, -1.61389785, -0.21274028],
[-0.89546656, 0.3869025 , -0.51080514, -1.18063218, -0.02818223,
0.42833187, 0.06651722, 0.3024719 , -0.63432209, -0.36274117],
[-0.67246045, -0.35955316, -0.81314628, -1.7262826 , 0.17742614,
-0.40178094, -1.63019835, 0.46278226, -0.90729836, 0.0519454 ],
[ 0.72909056, 0.12898291, 1.13940068, -1.23482582, 0.40234164,
-0.68481009, -0.87079715, -0.57884966, -0.31155253, 0.05616534],
[-1.16514984, 0.90082649, 0.46566244, -1.53624369, 1.48825219,
1.89588918, 1.17877957, -0.17992484, -1.07075262, 1.05445173],
[-0.40317695, 1.22244507, 0.20827498, 0.97663904, 0.3563664 ,
0.70657317, 0.01050002, 1.78587049, 0.12691209, 0.40198936]])
rnd = RandomState(MT19937) at 0x7FFF93D17940
lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/lobpcg.py:622: in lobpcg
_lambda, eigBlockVector = eigh(gramXAX, check_finite=False)
A = <function _makeMatMat.<locals>.<lambda> at 0x7fff94f84ae0>
B = None
M = None
X = array([[ 0.42438871],
[-0.30373232],
[-0.28631776],
[ 0.2184642 ],
[-0.26437626],
[ 0.4380164 ],
[-0.09321358],
[-0.16844716],
[ 0.43335612],
[ 0.33365028]])
Y = None
_ = array([[0.22536099]])
aux = ('Solving standard eigenvalue problem without preconditioning\n'
'\n'
'matrix size 10\n'
'block size 1\n'
'\n'
'No constraints\n'
'\n')
bestIterationNumber = 3
bestblockVectorX = array([[ 0.42438871],
[-0.30373232],
[-0.28631776],
[ 0.2184642 ],
[-0.26437626],
[ 0.4380164 ],
[-0.09321358],
[-0.16844716],
[ 0.43335612],
[ 0.33365028]])
blockVectorAX = array([[ 2.37209637],
[ 3.66692337],
[-1.82892717],
[ 3.80141345],
[-3.79907434],
[ 1.38487675],
[-1.93517115],
[-0.96588971],
[ 7.26728148],
[ 3.47532665]])
blockVectorBX = array([[ 0.42438871],
[-0.30373232],
[-0.28631776],
[ 0.2184642 ],
[-0.26437626],
[ 0.4380164 ],
[-0.09321358],
[-0.16844716],
[ 0.43335612],
[ 0.33365028]])
blockVectorX = array([[ 0.42438871],
[-0.30373232],
[-0.28631776],
[ 0.2184642 ],
[-0.26437626],
[ 0.4380164 ],
[-0.09321358],
[-0.16844716],
[ 0.43335612],
[ 0.33365028]])
blockVectorY = None
gramXAX = array([[7.50998893]])
largest = True
maxiter = 3
n = 10
residualTolerance = 1.4901161193847656e-07
restartControl = 20
retLambdaHistory = False
retResidualNormsHistory = False
sizeX = 1
sizeY = 0
tol = None
verbosityLevel = 9
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[7.50998893]])
a1 = array([[7.50998893]])
b = None
check_finite = False
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
----------------------------- Captured stdout call -----------------------------
Solving standard eigenvalue problem without preconditioning
matrix size 10
block size 1
No constraints
________ TestDunnett.test_critical_values[0.5-1-10-2.23-0.05-two-sided] ________
[gw13] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py:204: in test_critical_values
res = _pvalue_dunnett(
alternative = 'two-sided'
df = 10
n_groups = 1
pvalue = 0.05
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF8AD398C0
self = <scipy.stats.tests.test_multicomp.TestDunnett object at 0x7fff957eb790>
statistic = array(2.23)
lib/python3.11/site-packages/scipy/stats/_multicomp.py:450: in _pvalue_dunnett
mvt = stats.multivariate_t(shape=rho, df=df, seed=rng)
alternative = 'two-sided'
df = 10
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF8AD398C0
statistic = array([[2.23]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 10
loc = None
seed = Generator(PCG64) at 0x7FFF8AD398C0
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 10
dim = 1
loc = array([0.])
seed = Generator(PCG64) at 0x7FFF8AD398C0
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff8ac72290>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff8ac73dd0>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_________ TestDunnett.test_critical_values[0.5-1-10-1.81-0.05-greater] _________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py:204: in test_critical_values
res = _pvalue_dunnett(
alternative = 'greater'
df = 10
n_groups = 1
pvalue = 0.05
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF958FAA40
self = <scipy.stats.tests.test_multicomp.TestDunnett object at 0x7fff95a3c9d0>
statistic = array(1.81)
lib/python3.11/site-packages/scipy/stats/_multicomp.py:450: in _pvalue_dunnett
mvt = stats.multivariate_t(shape=rho, df=df, seed=rng)
alternative = 'greater'
df = 10
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF958FAA40
statistic = array([[1.81]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 10
loc = None
seed = Generator(PCG64) at 0x7FFF958FAA40
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 10
dim = 1
loc = array([0.])
seed = Generator(PCG64) at 0x7FFF958FAA40
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff940ed250>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff940d64d0>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
____________________ TestDunnett.test_ttest_ind[two-sided] _____________________
[gw13] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py:242: in test_ttest_ind
res = stats.dunnett(
_ = 0
alternative = 'two-sided'
control = array([-30, 67, 33, -33, -6, 36, -44, -96, 23, 48])
rng = Generator(PCG64) at 0x7FFF8AD3B5A0
sample = array([ 31, -30, 92, -29, 93, -8, 86, 38, 68, 98])
self = <scipy.stats.tests.test_multicomp.TestDunnett object at 0x7fff957c3550>
lib/python3.11/site-packages/scipy/stats/_multicomp.py:342: in dunnett
pvalue = _pvalue_dunnett(
alternative = 'two-sided'
control = array([-30, 67, 33, -33, -6, 36, -44, -96, 23, 48])
control_ = array([-30, 67, 33, -33, -6, 36, -44, -96, 23, 48])
df = 18
mean_control = -0.2
mean_samples = array([43.9])
n_control = 10
n_group = 1
n_samples = array([10])
random_state = Generator(PCG64) at 0x7FFF8AD3B5A0
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF8AD3B5A0
samples = (array([ 31, -30, 92, -29, 93, -8, 86, 38, 68, 98]),)
samples_ = [array([ 31, -30, 92, -29, 93, -8, 86, 38, 68, 98])]
statistic = array([1.93892207])
std = 50.85846373351572
lib/python3.11/site-packages/scipy/stats/_multicomp.py:450: in _pvalue_dunnett
mvt = stats.multivariate_t(shape=rho, df=df, seed=rng)
alternative = 'two-sided'
df = 18
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF8AD3B5A0
statistic = array([[1.93892207]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 18
loc = None
seed = Generator(PCG64) at 0x7FFF8AD3B5A0
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 18
dim = 1
loc = array([0.])
seed = Generator(PCG64) at 0x7FFF8AD3B5A0
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff8ac71d50>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff8ac73510>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
______________ TestMultivariateNormal.test_logpdf_default_values _______________
[gw11] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:346: in test_logpdf_default_values
d1 = multivariate_normal.logpdf(x)
self = <scipy.stats.tests.test_multivariate.TestMultivariateNormal object at 0x7fff959aca90>
x = array([ 0.47143516, -1.19097569, 1.43270697, -0.3126519 , -0.72058873])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:557: in logpdf
params = self._process_parameters(mean, cov, allow_singular)
allow_singular = False
cov = 1
mean = None
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
x = array([ 0.47143516, -1.19097569, 1.43270697, -0.3126519 , -0.72058873])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:422: in _process_parameters
psd = _PSD(cov, allow_singular=allow_singular)
allow_singular = False
cov = array([[1.]])
dim = 1
mean = array([0.])
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff942a52d0>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_______________________ TestDunnett.test_ttest_ind[less] _______________________
[gw13] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py:242: in test_ttest_ind
res = stats.dunnett(
_ = 0
alternative = 'less'
control = array([-30, 67, 33, -33, -6, 36, -44, -96, 23, 48])
rng = Generator(PCG64) at 0x7FFF8AD3BBC0
sample = array([ 31, -30, 92, -29, 93, -8, 86, 38, 68, 98])
self = <scipy.stats.tests.test_multicomp.TestDunnett object at 0x7fff957c3890>
lib/python3.11/site-packages/scipy/stats/_multicomp.py:342: in dunnett
pvalue = _pvalue_dunnett(
alternative = 'less'
control = array([-30, 67, 33, -33, -6, 36, -44, -96, 23, 48])
control_ = array([-30, 67, 33, -33, -6, 36, -44, -96, 23, 48])
df = 18
mean_control = -0.2
mean_samples = array([43.9])
n_control = 10
n_group = 1
n_samples = array([10])
random_state = Generator(PCG64) at 0x7FFF8AD3BBC0
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF8AD3BBC0
samples = (array([ 31, -30, 92, -29, 93, -8, 86, 38, 68, 98]),)
samples_ = [array([ 31, -30, 92, -29, 93, -8, 86, 38, 68, 98])]
statistic = array([1.93892207])
std = 50.85846373351572
lib/python3.11/site-packages/scipy/stats/_multicomp.py:450: in _pvalue_dunnett
mvt = stats.multivariate_t(shape=rho, df=df, seed=rng)
alternative = 'less'
df = 18
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF8AD3BBC0
statistic = array([[1.93892207]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 18
loc = None
seed = Generator(PCG64) at 0x7FFF8AD3BBC0
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 18
dim = 1
loc = array([0.])
seed = Generator(PCG64) at 0x7FFF8AD3BBC0
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff8a762790>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff8a762010>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
______________ TestMultivariateNormal.test_logcdf_default_values _______________
[gw11] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:369: in test_logcdf_default_values
d1 = multivariate_normal.logcdf(x)
self = <scipy.stats.tests.test_multivariate.TestMultivariateNormal object at 0x7fff959ada10>
x = array([ 0.47143516, -1.19097569, 1.43270697, -0.3126519 , -0.72058873])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:678: in logcdf
params = self._process_parameters(mean, cov, allow_singular)
abseps = 1e-05
allow_singular = False
cov = 1
lower_limit = None
maxpts = None
mean = None
releps = 1e-05
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
x = array([ 0.47143516, -1.19097569, 1.43270697, -0.3126519 , -0.72058873])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:422: in _process_parameters
psd = _PSD(cov, allow_singular=allow_singular)
allow_singular = False
cov = array([[1.]])
dim = 1
mean = array([0.])
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff93d91c10>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_____________________ TestDunnett.test_ttest_ind[greater] ______________________
[gw13] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py:242: in test_ttest_ind
res = stats.dunnett(
_ = 0
alternative = 'greater'
control = array([-30, 67, 33, -33, -6, 36, -44, -96, 23, 48])
rng = Generator(PCG64) at 0x7FFF8AFA5000
sample = array([ 31, -30, 92, -29, 93, -8, 86, 38, 68, 98])
self = <scipy.stats.tests.test_multicomp.TestDunnett object at 0x7fff957c3350>
lib/python3.11/site-packages/scipy/stats/_multicomp.py:342: in dunnett
pvalue = _pvalue_dunnett(
alternative = 'greater'
control = array([-30, 67, 33, -33, -6, 36, -44, -96, 23, 48])
control_ = array([-30, 67, 33, -33, -6, 36, -44, -96, 23, 48])
df = 18
mean_control = -0.2
mean_samples = array([43.9])
n_control = 10
n_group = 1
n_samples = array([10])
random_state = Generator(PCG64) at 0x7FFF8AFA5000
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF8AFA5000
samples = (array([ 31, -30, 92, -29, 93, -8, 86, 38, 68, 98]),)
samples_ = [array([ 31, -30, 92, -29, 93, -8, 86, 38, 68, 98])]
statistic = array([1.93892207])
std = 50.85846373351572
lib/python3.11/site-packages/scipy/stats/_multicomp.py:450: in _pvalue_dunnett
mvt = stats.multivariate_t(shape=rho, df=df, seed=rng)
alternative = 'greater'
df = 18
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF8AFA5000
statistic = array([[1.93892207]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 18
loc = None
seed = Generator(PCG64) at 0x7FFF8AFA5000
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 18
dim = 1
loc = array([0.])
seed = Generator(PCG64) at 0x7FFF8AFA5000
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff8a365790>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff8a366bd0>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_____________ TestMultivariateNormal.test_degenerate_distributions _____________
[gw11] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:411: in test_degenerate_distributions
distn_kk = multivariate_normal(np.zeros(k), cov_kk,
cov_kk = array([[0.00033449]])
cov_nn = array([[0.00033449, 0. ],
[0. , 0. ]])
cov_rr = array([[6.93140447e-06, 4.76494748e-05],
[4.76494748e-05, 3.27563116e-04]])
k = 1
n = 2
s = array([[0.01828919]])
self = <scipy.stats.tests.test_multivariate.TestMultivariateNormal object at 0x7fff959ae490>
u = array([[-0.14395147, -0.98958475],
[-0.98958475, 0.14395147]])
x = array([-0.89715678, 0. ])
y = array([0.12914704, 0.88781267])
z = array([-0.89715678, -0.13679483])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:398: in __call__
return multivariate_normal_frozen(mean, cov,
allow_singular = True
cov = array([[0.00033449]])
mean = array([0.])
seed = None
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:839: in __init__
self._dist._process_parameters(mean, cov, allow_singular))
abseps = 1e-05
allow_singular = True
cov = array([[0.00033449]])
maxpts = None
mean = array([0.])
releps = 1e-05
seed = None
self = <scipy.stats._multivariate.multivariate_normal_frozen object at 0x7fff86828350>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:422: in _process_parameters
psd = _PSD(cov, allow_singular=allow_singular)
allow_singular = True
cov = array([[0.00033449]])
dim = 1
mean = array([0.])
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fff95fa6d90>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[0.00033449]])
allow_singular = True
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff95fa70d0>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[0.00033449]])
a1 = array([[0.00033449]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_______________ TestMultivariateT.test_mvt_with_df_one_is_cauchy _______________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2270: in test_mvt_with_df_one_is_cauchy
val = multivariate_t.pdf(x, df=1)
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff9636bd10>
x = [9, 7, 4, 1, -3, 9, 0, -3, -1, 3]
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4400: in pdf
shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 1
dim = 1
loc = array([0.])
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = array([[1.]])
x = array([[ 9.],
[ 7.],
[ 4.],
[ 1.],
[-3.],
[ 9.],
[ 0.],
[-3.],
[-1.],
[ 3.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff94accc50>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
____________________ TestMultivariateNormal.test_normal_1D _____________________
[gw11] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:517: in test_normal_1D
d2 = multivariate_normal.pdf(x, mean, cov)
cov = 0.9
d1 = array([0.18895275, 0.24723974, 0.30623422, 0.35905383, 0.39850686,
0.41868022, 0.41638923, 0.39200077, 0.34933714, 0.29469515])
mean = 1.2
scale = 0.9486832980505138
self = <scipy.stats.tests.test_multivariate.TestMultivariateNormal object at 0x7fff95c68050>
x = array([0. , 0.22222222, 0.44444444, 0.66666667, 0.88888889,
1.11111111, 1.33333333, 1.55555556, 1.77777778, 2. ])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:585: in pdf
params = self._process_parameters(mean, cov, allow_singular)
allow_singular = False
cov = 0.9
mean = 1.2
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
x = array([0. , 0.22222222, 0.44444444, 0.66666667, 0.88888889,
1.11111111, 1.33333333, 1.55555556, 1.77777778, 2. ])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:422: in _process_parameters
psd = _PSD(cov, allow_singular=allow_singular)
allow_singular = False
cov = array([[0.9]])
dim = 1
mean = array([1.2])
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[0.9]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff86844c50>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[0.9]])
a1 = array([[0.9]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
___________ TestMultivariateT.test_mvt_with_high_df_is_approx_normal ___________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2281: in test_mvt_with_high_df_is_approx_normal
dist = multivariate_t(0, 1, df=100000, seed=1)
P_VAL_MIN = 0.1
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff96350050>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 100000
loc = 0
seed = 1
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = 1
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 100000
dim = 1
loc = array([0.])
seed = 1
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff94baedd0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff94baeb50>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
____________________ TestMultivariateNormal.test_rvs_shape _____________________
[gw11] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:720: in test_rvs_shape
u = multivariate_normal(mean=0, cov=1)
N = 300
d = 4
sample = array([[-3.21568384e-01, 3.54297713e-01],
[-4.74769379e-01, -6.98867254e-01],
[ 1.95009529e+00, 1.70966855e+00],
[ 3.07170795e-01, 1.94320393e-01],
[-2.05256381e+00, -8.02436170e-01],
[ 1.07934351e+00, 3.66258204e-02],
[ 1.84594440e-01, 2.11357591e-01],
[-6.98064652e-02, 7.57719035e-01],
[ 1.49272192e+00, -2.76746920e-01],
[-1.12684337e+00, 4.03490884e-01],
[-3.53264928e+00, -1.41324742e+00],
[-2.29745464e-01, -3.22947236e-01],
[ 1.09380243e+00, 1.22863710e+00],
[-2.87649139e-01, 1.17398833e+00],
[ 5.35731292e-01, 4.87204120e-01],
[-6.84781617e-01, -1.67905196e+00],
[ 5.34679099e-01, 4.37992637e-01],
[ 2.93879599e+00, -6.21210150e-01],
[ 1.85620473e+00, 2.34366332e-01],
[-3.61972250e+00, 2.19593334e-01],
[ 1.60659184e+00, -1.59260947e-02],
[ 7.70309483e-02, 5.09544149e-01],
[-4.18812704e-01, -9.18062673e-01],
[ 2.09110191e+00, 7.51817886e-01],
[-1.19829499e+00, -7.40087365e-01],
[ 1.26564977e-01, -1.45033221e-01],
[-3.48186059e-01, 7.84545199e-01],
[ 8.34523895e-01, 1.26433789e+00],
[ 2.27302239e+00, -1.21263490e+00],
[-2.34893197e+00, -8.43507768e-01],
[ 1.02959784e+00, -4.47123165e-01],
[-9.09337958e-01, -9.82800178e-01],
[-1.75878677e+00, 3.65578857e-01],
[ 6.31974717e-01, 4.44405597e-01],
[ 3.32771156e-01, -3.24851452e-01],
[-1.54374893e+00, 1.77682677e+00],
[ 2.67819731e-01, -1.01730640e+00],
[-3.32429730e+00, 4.10898596e-01],
[ 2.89082466e-01, 1.12589583e+00],
[-1.15423390e+00, -9.33702069e-01],
[-9.51090710e-01, 5.43860090e-01],
[ 1.23908491e-01, 5.84904780e-01],
[-6.87845445e-01, 2.03746915e+00],
[ 2.65207724e+00, -1.30495713e+00],
[-1.43003249e+00, -5.31131504e-01],
[-3.41343657e+00, -1.18965954e+00],
[-1.25328970e-01, -1.25342748e+00],
[-1.17320614e+00, 3.00916137e+00],
[-1.12863746e+00, 1.98338395e+00],
[-1.41333871e+00, -8.00614776e-01],
[ 2.64390946e+00, 1.77190700e+00],
[-7.83918397e-01, -3.11544545e-01],
[ 1.87986204e+00, 9.25519206e-01],
[-2.19549215e+00, 1.90073122e+00],
[-7.10158967e-01, -1.17725432e+00],
[ 1.81356712e-01, 5.24651943e-01],
[ 8.99101903e-02, -4.96676181e-01],
[ 7.65053849e-02, -7.53732991e-01],
[ 6.66533084e-01, 2.87102180e-01],
[ 1.75405335e-01, -1.55149274e+00],
[ 2.14403192e-01, 3.13056353e+00],
[ 7.83363690e-01, 1.05519179e+00],
[-1.20039916e-01, -9.93416240e-01],
[ 3.61435401e-01, 1.53081112e+00],
[-1.81099848e-01, -7.85406838e-01],
[ 4.44371317e-01, 4.16374771e-01],
[-5.72744156e-01, 1.38270198e+00],
[-6.09798390e-01, 2.04329669e+00],
[ 8.45831376e-01, 8.62031060e-01],
[ 9.58746199e-01, 1.41839934e-01],
[ 1.01931689e+00, 4.11641647e-01],
[ 2.42910668e-01, 1.61116802e+00],
[ 1.29559754e+00, 1.50180973e+00],
[-9.82771138e-01, 4.58366311e-01],
[ 5.97936124e-01, 1.52518455e-01],
[ 4.66566278e-01, -5.40282134e-01],
[-1.10457734e-01, -6.65190841e-01],
[-1.40532638e+00, 7.00004536e-01],
[ 9.07953891e-01, 4.31785643e-01],
[ 1.49509263e+00, -7.45428444e-01],
[-3.15363039e+00, -2.17351423e+00],
[ 9.65114387e-01, -5.96672860e-01],
[ 4.47404107e-01, -1.85293479e+00],
[-8.21920901e-01, -5.44736517e-02],
[-1.07121232e+00, 5.09435633e-01],
[ 1.68628023e+00, -1.34116817e+00],
[-1.69928043e+00, 8.54572950e-01],
[ 5.06162981e-01, -4.88286423e-01],
[ 1.57229872e-01, -3.81864644e-01],
[ 3.57456142e-01, 9.83837287e-01],
[ 7.90467044e-01, -2.18035850e-01],
[-3.56437418e-02, 1.39538606e+00],
[-9.29417071e-01, -9.55617703e-01],
[ 1.39530514e-01, -7.36945760e-01],
[ 9.62856381e-01, -5.85612465e-01],
[ 2.15462563e+00, -1.55539308e-01],
[ 4.85525366e-01, 1.75448511e-01],
[-8.03462989e-01, 6.68205717e-01],
[ 1.20391235e+00, -5.13413677e-01],
[ 6.97496885e-01, -6.17787705e-01],
[-3.42390403e-01, 4.46358255e-01],
[-1.17953366e-01, -8.01703110e-01],
[ 4.89683400e-01, 6.06100231e-01],
[-4.91001121e-01, 1.87186388e-02],
[ 9.58067778e-01, -8.15647380e-01],
[-3.05797372e+00, -3.53348790e-01],
[-2.26813682e+00, 5.71488686e-01],
[ 9.52550575e-01, -1.77620040e+00],
[ 9.68269957e-01, -1.68754401e+00],
[-5.31240614e-02, -4.79751355e-01],
[-2.47031226e-01, -1.13527796e+00],
[ 2.08719522e-01, -8.15800798e-01],
[ 5.00984135e-01, 9.02833596e-01],
[-8.43166276e-01, -3.22033512e-01],
[ 1.44631362e+00, 5.76606661e-01],
[-2.60626587e+00, 9.39458674e-01],
[ 1.38462405e+00, -3.31501389e-01],
[ 1.62294659e+00, 1.74083513e+00],
[ 7.20263610e-01, 7.21072394e-01],
[-1.36164422e+00, 1.69500209e+00],
[-1.98672404e-01, -1.86824938e+00],
[ 1.08408366e+00, -1.60361573e-01],
[-8.82058141e-01, -1.74475435e-01],
[ 1.14152030e-01, -1.56503239e-01],
[-9.77152417e-01, 5.23618079e-01],
[-3.17473766e-01, 1.12849679e+00],
[ 1.46155836e+00, 4.09475024e-01],
[ 8.22244264e-01, 1.40216275e+00],
[ 1.43341216e+00, -6.65416368e-01],
[ 3.73140810e-01, 9.53946789e-01],
[ 3.56419637e-01, 9.58016109e-01],
[ 1.07009288e+00, 2.04081614e+00],
[-1.40229216e+00, 9.27269861e-01],
[ 2.87647824e+00, -1.12306183e+00],
[-2.47095084e+00, 8.90992985e-01],
[-4.22328593e-01, -6.88850095e-01],
[ 1.63363639e+00, -1.70884091e+00],
[-7.55745848e-01, -1.87929144e+00],
[-1.70944060e+00, 4.94525530e-01],
[-2.60750042e-01, 3.87754065e-01],
[-1.69138723e+00, -3.43584572e-01],
[-1.39170868e+00, 4.95568018e-01],
[ 1.15757626e-01, 4.69414438e-01],
[ 8.30662741e-01, 4.67499949e-01],
[-3.89266369e-01, -2.62682219e-01],
[-1.63591889e+00, 8.49301520e-01],
[-1.40322828e+00, -2.00960943e+00],
[-1.71791021e-01, -7.93521619e-01],
[ 5.50315480e-01, -1.18579008e+00],
[ 7.50844325e-01, -2.80094573e-01],
[ 1.43712360e+00, 5.35937823e-01],
[ 3.58889561e-01, 1.34857919e+00],
[-2.24754005e+00, -4.41738276e-01],
[ 4.62093663e-01, 3.47077475e-01],
[ 3.82802660e-01, -6.24465101e-01],
[-1.40301504e+00, 1.05178283e+00],
[ 1.89899646e-01, -3.39499128e-01],
[-8.43003450e-01, 3.08173850e-01],
[-6.48075989e-01, 6.43618542e-01],
[ 1.39958472e+00, 1.70328461e+00],
[-7.20920826e-01, -8.08676971e-01],
[ 7.86098136e-01, 5.35741754e-01],
[ 4.42435831e-03, -1.20530105e-01],
[ 3.46242646e-01, 1.58717820e+00],
[-2.03634942e-01, 9.75562356e-01],
[ 7.53856096e-02, 1.00758650e+00],
[ 5.62936056e-01, 2.27980663e-01],
[-1.30618142e+00, 1.04689492e+00],
[-8.05946702e-01, 3.92115090e-01],
[-2.68084395e-02, 8.99697922e-02],
[ 7.94154894e-01, -8.89920517e-01],
[-4.18822108e-01, -4.31514981e-02],
[-1.65756800e+00, 1.92491909e+00],
[ 4.24637846e-01, -1.54245746e+00],
[-3.42134337e+00, -1.57789301e+00],
[ 1.75923291e+00, -1.60997713e-01],
[-5.86068117e-01, -6.98523513e-01],
[-2.47825004e+00, -3.31059811e-01],
[-2.25498866e+00, -7.67343322e-01],
[ 1.45638445e+00, 3.98802440e-01],
[ 2.41503338e+00, 7.90424054e-01],
[-2.12287310e+00, 1.11138320e+00],
[ 2.92504041e+00, 1.31325913e+00],
[-1.10013941e+00, -7.43866562e-01],
[ 3.22457736e+00, -6.48115731e-01],
[-1.04240998e+00, 1.82626503e+00],
[ 1.13140803e+00, 4.24029741e-01],
[ 1.03502647e+00, 8.42504822e-01],
[ 7.51412286e-01, -1.31068350e+00],
[ 1.51929835e-01, -7.43721428e-01],
[ 9.58559350e-01, -1.36453514e-01],
[-4.82052896e-01, 3.62815584e-01],
[-1.47796939e+00, 1.06831862e+00],
[ 1.67899632e+00, 1.76309894e+00],
[ 9.70163628e-01, 8.01914578e-01],
[ 1.34844204e+00, 1.22476307e+00],
[-8.29214183e-01, 1.24424319e+00],
[-1.19576396e+00, -2.60040569e-02],
[-1.74062349e+00, 1.89706669e+00],
[-1.30349344e+00, -6.21925097e-01],
[ 1.25354902e+00, -8.61582777e-01],
[ 2.11885754e+00, 1.69760638e+00],
[-1.04356721e+00, -2.52710162e+00],
[-5.17983065e-01, 4.23882998e-01],
[-3.11100290e-01, 1.82004476e-01],
[-2.97959941e+00, 1.77610080e+00],
[ 1.71459124e+00, -6.92252196e-01],
[ 1.22445126e+00, -5.46684213e-01],
[ 5.17452056e-01, 7.13544058e-02],
[ 1.17761611e+00, -4.88575644e-02],
[-1.14406810e+00, 1.18250804e+00],
[ 7.90013838e-01, -3.85121213e-01],
[ 3.24450034e-01, -1.10710366e+00],
[ 1.34137697e+00, 1.84654060e-01],
[ 2.45105511e-01, -3.59670417e-01],
[-1.72668042e+00, 4.29272081e-02],
[ 6.81533050e-02, 9.51601692e-01],
[ 9.06463125e-02, 1.72313254e+00],
[-7.92332239e-02, 4.46242928e-01],
[-4.14117740e-01, 2.64787650e-01],
[ 5.09210195e-01, 4.74546008e-01],
[-3.36272675e-01, 3.96046909e-01],
[-1.89921494e+00, -3.53654912e-01],
[-1.22402413e-01, 1.82468316e+00],
[ 2.93867925e+00, 2.52860215e-01],
[ 9.59081657e-01, -1.10692302e-01],
[-7.39683085e-01, -2.68578028e+00],
[ 5.31630823e-02, -1.72984707e-01],
[ 2.09335461e-01, -1.18411036e+00],
[ 5.37966712e+00, 1.50706779e+00],
[-7.57490021e-01, 1.67679091e+00],
[-6.67502978e-01, -2.36972944e-01],
[-1.11826413e+00, 5.19002148e-01],
[-1.35345588e+00, 1.99955036e+00],
[-5.12797658e-01, 1.74792167e+00],
[ 2.25221471e+00, 3.41716535e-01],
[-1.25543285e+00, 1.71194008e+00],
[ 8.06581405e-01, -1.03435861e-01],
[ 1.31937205e+00, 9.05600380e-01],
[ 7.18570779e-01, 1.27965390e+00],
[ 2.36252145e+00, -1.00260382e+00],
[-1.80313999e+00, -1.16911501e-01],
[-3.65023748e-01, -1.89673502e+00],
[ 1.13899667e+00, -2.55918243e-01],
[-1.59354333e+00, -2.75101551e-01],
[-1.11105797e+00, 7.10727034e-02],
[ 1.25372076e+00, 5.19187519e-01],
[ 3.34949525e-01, -7.57065037e-01],
[-1.70976308e+00, -4.45019107e-01],
[-1.86042706e-01, 8.92551655e-01],
[-2.23330066e-01, -7.18540033e-01],
[ 2.79304374e+00, -8.67790994e-02],
[ 1.29421198e+00, 1.00539912e+00],
[ 7.90796771e-01, -2.05301068e+00],
[-1.83528252e+00, -1.66100982e+00],
[ 8.06105704e-01, -3.12028276e-01],
[ 2.77746255e-01, 1.06180140e+00],
[ 9.73926730e-01, 4.70262912e-01],
[ 1.74443970e+00, 1.44944217e+00],
[-1.48045921e+00, -2.71622269e-02],
[ 3.04278737e-02, 3.41708798e-01],
[ 3.73261538e-01, -6.87651796e-01],
[-1.11058073e-01, 6.65752073e-01],
[-6.67206576e-01, 2.88126513e-01],
[-2.46779680e+00, -9.28587258e-01],
[ 1.20243701e+00, -5.04790671e-01],
[-2.48780899e-01, 1.30325324e+00],
[ 6.81305064e-01, -4.28227287e-02],
[-4.47465511e-01, -7.46671219e-01],
[ 1.80410926e+00, -8.98106134e-01],
[ 1.18716371e+00, 1.07389313e+00],
[ 1.98194512e+00, -6.64273412e-01],
[ 1.19178988e+00, 4.41295066e-01],
[ 1.36660611e+00, -1.98636499e+00],
[-1.65188889e+00, -5.79463159e-01],
[-3.90807479e-01, 3.68997148e-01],
[-1.69519925e+00, 5.06358789e-01],
[ 1.29104421e+00, 8.25970987e-01],
[-1.55445226e-01, -2.78155152e-01],
[-3.58940563e-01, -2.75957964e-01],
[ 1.96261767e+00, 1.21628739e+00],
[-9.50318677e-01, -1.18375471e+00],
[-1.87730912e+00, 1.54436683e+00],
[ 1.34508975e+00, 5.75749103e-01],
[ 1.48934910e-01, 9.67349925e-01],
[ 3.01956836e-02, 8.01776835e-01],
[ 1.23242394e+00, 4.28634234e-01],
[ 1.82635942e+00, -1.37433550e+00],
[ 4.96683397e-02, 1.82246825e+00],
[-1.39146537e-01, 1.06913643e+00],
[ 3.52075138e-02, 3.03207531e-01],
[-9.43881255e-01, -6.06145003e-02],
[ 3.26571828e+00, 6.00548013e-01],
[ 2.20090107e+00, 2.40585902e+00],
[-9.61649434e-01, 4.81185804e-02],
[-5.85348399e-01, 9.36476780e-01],
[-1.05151573e+00, 5.24036302e-01],
[ 8.78486883e-02, -1.56373285e-01],
[ 2.74824256e-01, -6.48808376e-02],
[ 1.70752479e+00, 6.56358333e-01]])
self = <scipy.stats.tests.test_multivariate.TestMultivariateNormal object at 0x7fff95c6b050>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:398: in __call__
return multivariate_normal_frozen(mean, cov,
allow_singular = False
cov = 1
mean = 0
seed = None
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:839: in __init__
self._dist._process_parameters(mean, cov, allow_singular))
abseps = 1e-05
allow_singular = False
cov = 1
maxpts = None
mean = 0
releps = 1e-05
seed = None
self = <scipy.stats._multivariate.multivariate_normal_frozen object at 0x7fff86845e10>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:422: in _process_parameters
psd = _PSD(cov, allow_singular=allow_singular)
allow_singular = False
cov = array([[1.]])
dim = 1
mean = array([0.])
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fff86845390>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff868466d0>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_____________ TestMultivariateT.test_mvt_with_inf_df_calls_normal ______________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2294: in test_mvt_with_inf_df_calls_normal
dist = multivariate_t(0, 1, df=np.inf, seed=7)
mock = <MagicMock name='_logpdf' id='140735677872784'>
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff96350350>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4368: in __call__
return multivariate_normal_frozen(mean=loc, cov=shape,
allow_singular = False
df = inf
loc = 0
seed = 7
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = 1
lib/python3.11/site-packages/scipy/stats/_multivariate.py:839: in __init__
self._dist._process_parameters(mean, cov, allow_singular))
abseps = 1e-05
allow_singular = False
cov = 1
maxpts = None
mean = 0
releps = 1e-05
seed = 7
self = <scipy.stats._multivariate.multivariate_normal_frozen object at 0x7fff941602d0>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:422: in _process_parameters
psd = _PSD(cov, allow_singular=allow_singular)
allow_singular = False
cov = array([[1.]])
dim = 1
mean = array([0.])
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fff94160390>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff94161a10>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
___________________ TestMultivariateT.test_shape_correctness ___________________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2324: in test_shape_correctness
res = multivariate_t(np.zeros(1), np.eye(1), 1).rvs()
df = 4.5
dim = 4
loc = array([0., 0., 0., 0.])
n_samples = 7
res = array([-4.68742839, -4.40403816, -3.53200907, -3.78975354, -5.11967169,
-5.02429073, -4.90326889])
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff96350650>
shape = array([[1., 0., 0., 0.],
[0., 1., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]])
x = array([[0.04303899, 0.79979432, 0.70951175, 0.76190274],
[0.63636186, 0.66081095, 0.68532005, 0.11207342],
[0.2340987 , 0.10089908, 0.37478727, 0.19510788],
[0.64100701, 0.31395131, 0.00653718, 0.17490999],
[0.82820553, 0.96244028, 0.8075685 , 0.35708977],
[0.86754733, 0.4104457 , 0.57562735, 0.99322485],
[0.01696633, 0.87422474, 0.95539621, 0.61026047]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 1
loc = array([0.])
seed = None
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 1
dim = 1
loc = array([0.])
seed = None
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff93e35490>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff93e348d0>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
__________________________ test_random_state_property __________________________
[gw10] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:3184: in test_random_state_property
check_random_state_property(distfn, args)
args = ()
distfn = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
dists = [[<scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>,
()],
[<scipy.stats._multivariate.dirichlet_gen object at 0x7fffa84afad0>,
(array([1.]),)],
[<scipy.stats._multivariate.wishart_gen object at 0x7fffa84af890>,
(10,
array([[1. , 0.5, 0. ],
[0.5, 1. , 0. ],
[0. , 0. , 1. ]]))],
[<scipy.stats._multivariate.invwishart_gen object at 0x7fffa84afc10>,
(10,
array([[1. , 0.5, 0. ],
[0.5, 1. , 0. ],
[0. , 0. , 1. ]]))],
[<scipy.stats._multivariate.multinomial_gen object at 0x7fffa84afe50>,
(5, [0.5, 0.4, 0.1])],
[<scipy.stats._multivariate.ortho_group_gen object at 0x7fffa84bc290>, (2,)],
[<scipy.stats._multivariate.special_ortho_group_gen object at 0x7fffa84aff50>,
(2,)]]
scale = array([[1. , 0.5, 0. ],
[0.5, 1. , 0. ],
[0. , 0. , 1. ]])
lib/python3.11/site-packages/scipy/stats/tests/common_tests.py:202: in check_random_state_property
r0 = distfn.rvs(*args, size=8)
args = ()
distfn = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
rndm = RandomState(MT19937) at 0x7FFFF4ABD340
lib/python3.11/site-packages/scipy/stats/_multivariate.py:753: in rvs
dim, mean, cov_object = self._process_parameters(mean, cov)
cov = 1
mean = None
random_state = None
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
size = 8
lib/python3.11/site-packages/scipy/stats/_multivariate.py:422: in _process_parameters
psd = _PSD(cov, allow_singular=allow_singular)
allow_singular = True
cov = array([[1.]])
dim = 1
mean = array([0.])
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = True
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff93e6eb10>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_____________________ TestMatrixNormal.test_default_inputs _____________________
[gw11] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:893: in test_default_inputs
assert_equal(matrix_normal(rowcov=U).mean, Zr)
I1 = array([[1.]])
Ic = array([[1., 0., 0.],
[0., 1., 0.],
[0., 0., 1.]])
Ir = array([[1., 0., 0., 0.],
[0., 1., 0., 0.],
[0., 0., 1., 0.],
[0., 0., 0., 1.]])
M = array([[0.3, 0.3, 0.3],
[0.3, 0.3, 0.3],
[0.3, 0.3, 0.3],
[0.3, 0.3, 0.3]])
U = array([[1. , 0.5, 0.5, 0.5],
[0.5, 1. , 0.5, 0.5],
[0.5, 0.5, 1. , 0.5],
[0.5, 0.5, 0.5, 1. ]])
V = array([[1. , 0.3, 0.3],
[0.3, 1. , 0.3],
[0.3, 0.3, 1. ]])
Z = array([[0., 0., 0.],
[0., 0., 0.],
[0., 0., 0.],
[0., 0., 0.]])
Zc = array([[0., 0., 0.]])
Zr = array([[0.],
[0.],
[0.],
[0.]])
num_cols = 3
num_rows = 4
self = <scipy.stats.tests.test_multivariate.TestMatrixNormal object at 0x7fff959a5fd0>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:1053: in __call__
return matrix_normal_frozen(mean, rowcov, colcov, seed=seed)
colcov = 1
mean = None
rowcov = array([[1. , 0.5, 0.5, 0.5],
[0.5, 1. , 0.5, 0.5],
[0.5, 0.5, 1. , 0.5],
[0.5, 0.5, 0.5, 1. ]])
seed = None
self = <scipy.stats._multivariate.matrix_normal_gen object at 0x7fffa84af6d0>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:1336: in __init__
self.colpsd = _PSD(self.colcov, allow_singular=False)
colcov = 1
mean = None
rowcov = array([[1. , 0.5, 0.5, 0.5],
[0.5, 1. , 0.5, 0.5],
[0.5, 0.5, 1. , 0.5],
[0.5, 0.5, 0.5, 1. ]])
seed = None
self = <scipy.stats._multivariate.matrix_normal_frozen object at 0x7fff94253090>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff94c6a0d0>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
___________________ TestMultivariateT.test_default_arguments ___________________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2334: in test_default_arguments
dist = multivariate_t()
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff96350b50>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 1
loc = None
seed = None
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = 1
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 1
dim = 1
loc = array([0.])
seed = None
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff93f6a510>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff93f6af50>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
__________________ TestMatrixNormal.test_frozen_matrix_normal __________________
[gw11] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:930: in test_frozen_matrix_normal
frozen = matrix_normal(mean=M, rowcov=U, colcov=V)
M = array([[0.3]])
U = array([[1.]])
V = array([[1.]])
i = 1
j = 1
self = <scipy.stats.tests.test_multivariate.TestMatrixNormal object at 0x7fff959a47d0>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:1053: in __call__
return matrix_normal_frozen(mean, rowcov, colcov, seed=seed)
colcov = array([[1.]])
mean = array([[0.3]])
rowcov = array([[1.]])
seed = None
self = <scipy.stats._multivariate.matrix_normal_gen object at 0x7fffa84af6d0>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:1335: in __init__
self.rowpsd = _PSD(self.rowcov, allow_singular=False)
colcov = array([[1.]])
mean = array([[0.3]])
rowcov = array([[1.]])
seed = None
self = <scipy.stats._multivariate.matrix_normal_frozen object at 0x7fff94bbdf90>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff94bbe110>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_____________________ TestMultivariateT.test_entropy_1d[1] _____________________
[gw12] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2595: in test_entropy_1d
mvt_entropy = stats.multivariate_t.entropy(shape=1., df=df)
df = 1
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff96085410>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4588: in entropy
return self._entropy(dim, df, shape)
df = 1
dim = 1
loc = array([0.])
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4565: in _entropy
shape_info = _PSD(shape)
df = 1
dim = 1
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = True
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff883cb7d0>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
____________________ TestMultivariateT.test_entropy_1d[10] _____________________
[gw12] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2595: in test_entropy_1d
mvt_entropy = stats.multivariate_t.entropy(shape=1., df=df)
df = 10
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff96085650>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4588: in entropy
return self._entropy(dim, df, shape)
df = 10
dim = 1
loc = array([0.])
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4565: in _entropy
shape_info = _PSD(shape)
df = 10
dim = 1
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = True
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff94be4690>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
__________________ TestMatrixNormal.test_matches_multivariate __________________
[gw11] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:956: in test_matches_multivariate
frozen = matrix_normal(mean=M, rowcov=U, colcov=V)
M = array([[0.3]])
U = array([[1.]])
V = array([[1.]])
i = 1
j = 1
self = <scipy.stats.tests.test_multivariate.TestMatrixNormal object at 0x7fff95c9c7d0>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:1053: in __call__
return matrix_normal_frozen(mean, rowcov, colcov, seed=seed)
colcov = array([[1.]])
mean = array([[0.3]])
rowcov = array([[1.]])
seed = None
self = <scipy.stats._multivariate.matrix_normal_gen object at 0x7fffa84af6d0>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:1335: in __init__
self.rowpsd = _PSD(self.rowcov, allow_singular=False)
colcov = array([[1.]])
mean = array([[0.3]])
rowcov = array([[1.]])
seed = None
self = <scipy.stats._multivariate.matrix_normal_frozen object at 0x7fff94bbfa90>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff94bbef10>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
__________ TestMultivariateT.test_default_args[None-None-None-0-1-1] ___________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2352: in test_default_args
dist = multivariate_t(loc=loc, shape=shape, df=df)
df = None
df_ans = 1
loc = None
loc_ans = 0
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff963529d0>
shape = None
shape_ans = 1
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = None
loc = None
seed = None
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = None
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 1
dim = 1
loc = array([0.])
seed = None
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff95bdab90>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff9635ad10>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
____________________ TestMultivariateT.test_entropy_1d[100] ____________________
[gw12] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2595: in test_entropy_1d
mvt_entropy = stats.multivariate_t.entropy(shape=1., df=df)
df = 100
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff96085910>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4588: in entropy
return self._entropy(dim, df, shape)
df = 100
dim = 1
loc = array([0.])
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4565: in _entropy
shape_info = _PSD(shape)
df = 100
dim = 1
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = True
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff93f5e850>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
____________ TestMultivariateT.test_default_args[None-None-7-0-1-7] ____________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2352: in test_default_args
dist = multivariate_t(loc=loc, shape=shape, df=df)
df = 7
df_ans = 7
loc = None
loc_ans = 0
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff96352c10>
shape = None
shape_ans = 1
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 7
loc = None
seed = None
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = None
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 7
dim = 1
loc = array([0.])
seed = None
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff94f1fc10>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff96350750>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_ TestMultivariateT.test_scalar_list_and_ndarray_arguments[-1-2-3-loc_ans0-shape_ans0-3] _
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2365: in test_scalar_list_and_ndarray_arguments
dist = multivariate_t(loc, shape, df)
df = 3
df_ans = 3
loc = -1
loc_ans = [-1]
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff963c1490>
shape = 2
shape_ans = [[2]]
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 3
loc = -1
seed = None
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = 2
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 3
dim = 1
loc = array([-1.])
seed = None
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff95ba3790>
shape = array([[2.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[2.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff95ba2c10>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[2.]])
a1 = array([[2.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
__________________________ TestDunnett.test_shapes[1] __________________________
[gw13] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py:399: in test_shapes
res = stats.dunnett(*samples, control=control, random_state=rng)
control = array([ 0.93062923, 1.05923736, 0.7813561 , 0.10179298, 1.81350281,
-1.64822219, 0.5840277 , -1.05764498, 0.69409434, 0.61506521])
n_samples = 1
rng = Generator(PCG64) at 0x7FFF95A76880
samples = array([[ 0.46969572, -0.44605399, -1.91769557, -0.21277653, -1.25400888,
0.79578597, 0.93654687, -0.06268451, 0.02250545, -0.93265 ]])
self = <scipy.stats.tests.test_multicomp.TestDunnett object at 0x7fff95d67a90>
lib/python3.11/site-packages/scipy/stats/_multicomp.py:342: in dunnett
pvalue = _pvalue_dunnett(
alternative = 'two-sided'
control = array([ 0.93062923, 1.05923736, 0.7813561 , 0.10179298, 1.81350281,
-1.64822219, 0.5840277 , -1.05764498, 0.69409434, 0.61506521])
control_ = array([ 0.93062923, 1.05923736, 0.7813561 , 0.10179298, 1.81350281,
-1.64822219, 0.5840277 , -1.05764498, 0.69409434, 0.61506521])
df = 18
mean_control = 0.3873838573606143
mean_samples = array([-0.26013355])
n_control = 10
n_group = 1
n_samples = array([10])
random_state = Generator(PCG64) at 0x7FFF95A76880
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF95A76880
samples = (array([ 0.46969572, -0.44605399, -1.91769557, -0.21277653, -1.25400888,
0.79578597, 0.93654687, -0.06268451, 0.02250545, -0.93265 ]),)
samples_ = [array([ 0.46969572, -0.44605399, -1.91769557, -0.21277653, -1.25400888,
0.79578597, 0.93654687, -0.06268451, 0.02250545, -0.93265 ])]
statistic = array([-1.49620252])
std = 0.9677118679306033
lib/python3.11/site-packages/scipy/stats/_multicomp.py:450: in _pvalue_dunnett
mvt = stats.multivariate_t(shape=rho, df=df, seed=rng)
alternative = 'two-sided'
df = 18
rho = array([[1.]])
rng = Generator(PCG64) at 0x7FFF95A76880
statistic = array([[-1.49620252]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 18
loc = None
seed = Generator(PCG64) at 0x7FFF95A76880
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84bc5d0>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 18
dim = 1
loc = array([0.])
seed = Generator(PCG64) at 0x7FFF95A76880
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff8aaee250>
shape = array([[1.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[1.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff8aaecf90>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[1.]])
a1 = array([[1.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_ TestMultivariateT.test_scalar_list_and_ndarray_arguments[loc1-shape1-3-loc_ans1-shape_ans1-3] _
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2365: in test_scalar_list_and_ndarray_arguments
dist = multivariate_t(loc, shape, df)
df = 3
df_ans = 3
loc = [-1]
loc_ans = [-1]
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff963c16d0>
shape = [2]
shape_ans = [[2]]
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 3
loc = [-1]
seed = None
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = [2]
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 3
dim = 1
loc = array([-1.])
seed = None
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff94fea850>
shape = array([[2.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[2.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff94feb790>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[2.]])
a1 = array([[2.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
__________________ TestMultivariateNormal.test_scalar_values ___________________
[gw13] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:309: in test_scalar_values
pdf = multivariate_normal.pdf(x, mean, cov)
cov = 2.5
mean = 1.7
self = <scipy.stats.tests.test_multivariate.TestMultivariateNormal object at 0x7fff95978090>
x = 1.5
lib/python3.11/site-packages/scipy/stats/_multivariate.py:585: in pdf
params = self._process_parameters(mean, cov, allow_singular)
allow_singular = False
cov = 2.5
mean = 1.7
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
x = 1.5
lib/python3.11/site-packages/scipy/stats/_multivariate.py:422: in _process_parameters
psd = _PSD(cov, allow_singular=allow_singular)
allow_singular = False
cov = array([[2.5]])
dim = 1
mean = array([1.7])
self = <scipy.stats._multivariate.multivariate_normal_gen object at 0x7fffa84af510>
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[2.5]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff8ac42450>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[2.5]])
a1 = array([[2.5]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_ TestMultivariateT.test_scalar_list_and_ndarray_arguments[loc2-shape2-3-loc_ans2-shape_ans2-3] _
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2365: in test_scalar_list_and_ndarray_arguments
dist = multivariate_t(loc, shape, df)
df = 3
df_ans = 3
loc = array([-1])
loc_ans = [-1]
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff963c1a10>
shape = array([2])
shape_ans = [[2]]
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4371: in __call__
return multivariate_t_frozen(loc=loc, shape=shape, df=df,
allow_singular = False
df = 3
loc = array([-1])
seed = None
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = array([2])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4739: in __init__
self.shape_info = _PSD(shape, allow_singular=allow_singular)
allow_singular = False
df = 3
dim = 1
loc = array([-1.])
seed = None
self = <scipy.stats._multivariate.multivariate_t_frozen object at 0x7fff93fabe50>
shape = array([[2.]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[2.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff93faad10>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[2.]])
a1 = array([[2.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
__________ TestMultivariateT.test_cdf_against_multivariate_normal[1] ___________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2433: in test_cdf_against_multivariate_normal
self.cdf_against_mvn_test(dim)
dim = 1
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff9638bb10>
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2452: in cdf_against_mvn_test
res = stats.multivariate_t.cdf(b, mean, cov, df=10000, lower_limit=a,
a = array([[-16.11339478],
[ -1.74179477],
[-39.1786543 ]])
b = array([[-0.67133314],
[ 3.95045666],
[ 4.87454129]])
cov = array([[0.06728406]])
dim = 1
mean = array([-0.78954894])
n = 3
rng = Generator(PCG64) at 0x7FFF93D9F060
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff9638bb10>
singular = False
w = array([0.06728406])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4556: in cdf
shape = _PSD(shape, allow_singular=allow_singular)._M
allow_singular = True
df = 10000
dim = 1
loc = array([-0.78954894])
lower_limit = array([[-16.11339478],
[ -1.74179477],
[-39.1786543 ]])
maxpts = None
random_state = Generator(PCG64) at 0x7FFF93D9F060
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = array([[0.06728406]])
x = array([[-0.67133314],
[ 3.95045666],
[ 4.87454129]])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[0.06728406]])
allow_singular = True
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff95028890>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[0.06728406]])
a1 = array([[0.06728406]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
_______________ TestMultivariateT.test_cdf_against_univariate_t ________________
[gw2] linux -- Python 3.11.7 /nix/store/asiphbpiy2gmidfm3xbwcikayhs66289-python3-3.11.7/bin/python3.11
lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py:2465: in test_cdf_against_univariate_t
res = stats.multivariate_t.cdf(x, mean, cov, df, lower_limit=-np.inf,
cov = 2
df = 3
mean = 0
rng = Generator(PCG64) at 0x7FFFF472BD80
self = <scipy.stats.tests.test_multivariate.TestMultivariateT object at 0x7fff96395a50>
x = array([ 1.01348544, -0.55614742, 0.57961414, -0.39793036, 1.52203638,
-1.33620624, 2.32672934, 0.2287321 , -1.0862379 , 1.17607499])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:4556: in cdf
shape = _PSD(shape, allow_singular=allow_singular)._M
allow_singular = False
df = 3
dim = 1
loc = array([0.])
lower_limit = -inf
maxpts = None
random_state = Generator(PCG64) at 0x7FFFF472BD80
self = <scipy.stats._multivariate.multivariate_t_gen object at 0x7fffa84e0550>
shape = array([[2.]])
x = array([ 1.01348544, -0.55614742, 0.57961414, -0.39793036, 1.52203638,
-1.33620624, 2.32672934, 0.2287321 , -1.0862379 , 1.17607499])
lib/python3.11/site-packages/scipy/stats/_multivariate.py:167: in __init__
s, u = scipy.linalg.eigh(M, lower=lower, check_finite=check_finite)
M = array([[2.]])
allow_singular = False
check_finite = True
cond = None
lower = True
rcond = None
self = <scipy.stats._multivariate._PSD object at 0x7fff9484ab90>
lib/python3.11/site-packages/scipy/linalg/_decomp.py:560: in eigh
w, v, *other_args, info = drv(a=a1, **drv_args, **lwork_args)
E _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword liwork: dsyevr:liwork=1
_job = 'V'
a = array([[2.]])
a1 = array([[2.]])
b = None
check_finite = True
clw_args = {'lower': True, 'n': 1}
cplx = False
driver = 'evr'
drv = <fortran function dsyevr>
drv_args = {'compute_v': 1, 'lower': True, 'overwrite_a': False}
drv_str = [None, 'ev', 'evd', 'evr', 'evx', 'gv', 'gvd', 'gvx']
drvlw = <fortran function dsyevr_lwork>
eigvals = None
eigvals_only = False
lower = True
lw = (33, 1)
lwork_args = {'liwork': 1, 'lwork': 33}
lwork_spec = {'heevd': ['lwork', 'liwork', 'lrwork'],
'heevr': ['lwork', 'lrwork', 'liwork'],
'syevd': ['lwork', 'liwork'],
'syevr': ['lwork', 'liwork']}
n = 1
overwrite_a = False
overwrite_b = False
pfx = 'sy'
subset = False
subset_by_index = None
subset_by_value = None
turbo = False
type = 1
uplo = 'L'
=========================== short test summary info ============================
FAILED lib/python3.11/site-packages/scipy/linalg/tests/test_decomp_polar.py::test_verify_cases - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py::test_inplace_warning - _flapack.error: (lrwork>=max(24*n,1)||lrwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py::Test_SVDS_LOBPCG::test_svd_v0 - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py::Test_SVDS_LOBPCG::test_svd_random_state - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py::Test_SVDS_LOBPCG::test_svd_random_state_2[0] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py::Test_SVDS_LOBPCG::test_svd_random_state_2[1] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py::Test_SVDS_LOBPCG::test_svd_random_state_2[random_state2] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py::Test_SVDS_LOBPCG::test_svd_random_state_2[random_state3] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/tests/test_svds.py::Test_SVDS_LOBPCG::test_svd_maxiter - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py::test_regression - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py::test_failure_to_run_iterations_nonsymmetric - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py::test_hermitian - _flapack.error: (lrwork>=max(24*n,1)||lrwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/sparse/linalg/_eigen/lobpcg/tests/test_lobpcg.py::test_verbosity - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py::TestDunnett::test_critical_values[0.5-1-10-2.23-0.05-two-sided] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py::TestDunnett::test_critical_values[0.5-1-10-1.81-0.05-greater] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py::TestDunnett::test_ttest_ind[two-sided] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateNormal::test_logpdf_default_values - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py::TestDunnett::test_ttest_ind[less] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateNormal::test_logcdf_default_values - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py::TestDunnett::test_ttest_ind[greater] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateNormal::test_degenerate_distributions - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_mvt_with_df_one_is_cauchy - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateNormal::test_normal_1D - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_mvt_with_high_df_is_approx_normal - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateNormal::test_rvs_shape - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_mvt_with_inf_df_calls_normal - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_shape_correctness - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::test_random_state_property - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMatrixNormal::test_default_inputs - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_default_arguments - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMatrixNormal::test_frozen_matrix_normal - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_entropy_1d[1] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_entropy_1d[10] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMatrixNormal::test_matches_multivariate - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_default_args[None-None-None-0-1-1] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_entropy_1d[100] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_default_args[None-None-7-0-1-7] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_scalar_list_and_ndarray_arguments[-1-2-3-loc_ans0-shape_ans0-3] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multicomp.py::TestDunnett::test_shapes[1] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_scalar_list_and_ndarray_arguments[loc1-shape1-3-loc_ans1-shape_ans1-3] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateNormal::test_scalar_values - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_scalar_list_and_ndarray_arguments[loc2-shape2-3-loc_ans2-shape_ans2-3] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_cdf_against_multivariate_normal[1] - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
FAILED lib/python3.11/site-packages/scipy/stats/tests/test_multivariate.py::TestMultivariateT::test_cdf_against_univariate_t - _flapack.error: (liwork>=max(1,10*n)||liwork==-1) failed for 10th keyword l...
= 44 failed, 42429 passed, 2825 skipped, 135 xfailed, 11 xpassed in 127.02s (0:02:07) =
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