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I have been successfully running the Bayes factor analysis in struct-lmm but now want to run the same analysis on a subset of my data. I created all of the phenotype and environments files in the same way I had done previously (all of which work well). I am now getting the error numpy.linalg.LinAlgError: SVD did not converge and am at a loss for how to fix this. From other threads and wiki pages I started by looking for missing data or NAs and cannot find them in the data or the normalized data. The shape of the data look as expected and none of my environments have 0 variance. I appreciate any help with this.
Traceback:
Traceback (most recent call last):
File "", line 1, in
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix/model/struct_lmm/bf.py", line 82, in calc_bf
lml_model_1 = self.calc_lml(self.Env1)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix/model/struct_lmm/bf.py", line 73, in calc_lml
gp = GP2KronSumLR(Y=self.y, F=_covs, A=sp.eye(1), Cn=FreeFormCov(1), G=xoE)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix_core/gp/gp2kronSumLR.py", line 52, in init
covar = Cov2KronSumLR(Cn=Cn, G=G, rank=rank, Cr=Cr)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix_core/covar/cov2kronSumLR.py", line 41, in init
self.G = G
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix_core/covar/cov2kronSumLR.py", line 95, in G
_value, U, S, V = svd_reduce(value)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix_core/util/svd_utils.py", line 5, in svd_reduce
U, Sh, V = nla.svd(X, full_matrices=0)
File "<array_function internals>", line 6, in svd
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/numpy/linalg/linalg.py", line 1626, in svd
u, s, vh = gufunc(a, signature=signature, extobj=extobj)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/numpy/linalg/linalg.py", line 106, in _raise_linalgerror_svd_nonconvergence
raise LinAlgError("SVD did not converge")
numpy.linalg.LinAlgError: SVD did not converge
The text was updated successfully, but these errors were encountered:
I have been successfully running the Bayes factor analysis in struct-lmm but now want to run the same analysis on a subset of my data. I created all of the phenotype and environments files in the same way I had done previously (all of which work well). I am now getting the error numpy.linalg.LinAlgError: SVD did not converge and am at a loss for how to fix this. From other threads and wiki pages I started by looking for missing data or NAs and cannot find them in the data or the normalized data. The shape of the data look as expected and none of my environments have 0 variance. I appreciate any help with this.
Traceback:
Traceback (most recent call last):
File "", line 1, in
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix/model/struct_lmm/bf.py", line 82, in calc_bf
lml_model_1 = self.calc_lml(self.Env1)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix/model/struct_lmm/bf.py", line 73, in calc_lml
gp = GP2KronSumLR(Y=self.y, F=_covs, A=sp.eye(1), Cn=FreeFormCov(1), G=xoE)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix_core/gp/gp2kronSumLR.py", line 52, in init
covar = Cov2KronSumLR(Cn=Cn, G=G, rank=rank, Cr=Cr)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix_core/covar/cov2kronSumLR.py", line 41, in init
self.G = G
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix_core/covar/cov2kronSumLR.py", line 95, in G
_value, U, S, V = svd_reduce(value)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/limix_core/util/svd_utils.py", line 5, in svd_reduce
U, Sh, V = nla.svd(X, full_matrices=0)
File "<array_function internals>", line 6, in svd
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/numpy/linalg/linalg.py", line 1626, in svd
u, s, vh = gufunc(a, signature=signature, extobj=extobj)
File "/gpfs/loomis/project/polimanti/frw5/conda_envs/limix_env/lib/python3.7/site-packages/numpy/linalg/linalg.py", line 106, in _raise_linalgerror_svd_nonconvergence
raise LinAlgError("SVD did not converge")
numpy.linalg.LinAlgError: SVD did not converge
The text was updated successfully, but these errors were encountered: