From f31bf783501dea4b421eee3846ac5fbf0e60f077 Mon Sep 17 00:00:00 2001 From: Fabian Joswig Date: Mon, 19 Jun 2023 13:36:11 +0100 Subject: [PATCH] style: multiple spaces after keyword removed. --- pyerrors/linalg.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/pyerrors/linalg.py b/pyerrors/linalg.py index cd026cf1..49c21327 100644 --- a/pyerrors/linalg.py +++ b/pyerrors/linalg.py @@ -262,7 +262,7 @@ def _mat_mat_op(op, obs, **kwargs): def eigh(obs, **kwargs): """Computes the eigenvalues and eigenvectors of a given hermitian matrix of Obs according to np.linalg.eigh.""" if version.parse(np.__version__) >= version.parse("1.25.0"): - raise NotImplementedError("eigh error propagation is not working with numpy>=1.25 and autograd==1.5.") + raise NotImplementedError("eigh error propagation is not working with numpy>=1.25 and autograd==1.5.") w = derived_observable(lambda x, **kwargs: anp.linalg.eigh(x)[0], obs) v = derived_observable(lambda x, **kwargs: anp.linalg.eigh(x)[1], obs) return w, v @@ -271,7 +271,7 @@ def eigh(obs, **kwargs): def eig(obs, **kwargs): """Computes the eigenvalues of a given matrix of Obs according to np.linalg.eig.""" if version.parse(np.__version__) >= version.parse("1.25.0"): - raise NotImplementedError("eig error propagation is not working with numpy>=1.25 and autograd==1.5.") + raise NotImplementedError("eig error propagation is not working with numpy>=1.25 and autograd==1.5.") w = derived_observable(lambda x, **kwargs: anp.real(anp.linalg.eig(x)[0]), obs) return w @@ -284,7 +284,7 @@ def pinv(obs, **kwargs): def svd(obs, **kwargs): """Computes the singular value decomposition of a matrix of Obs.""" if version.parse(np.__version__) >= version.parse("1.25.0"): - raise NotImplementedError("svd error propagation is not working with numpy>=1.25 and autograd==1.5.") + raise NotImplementedError("svd error propagation is not working with numpy>=1.25 and autograd==1.5.") u = derived_observable(lambda x, **kwargs: anp.linalg.svd(x, full_matrices=False)[0], obs) s = derived_observable(lambda x, **kwargs: anp.linalg.svd(x, full_matrices=False)[1], obs) vh = derived_observable(lambda x, **kwargs: anp.linalg.svd(x, full_matrices=False)[2], obs)