fix a bunch of flake8 warnings/errors

docs/conf.py

@@ -12,7 +12,8 @@
 # All configuration values have a default; values that are commented out
 # serve to show the default.
 
-import sys, os
+import os
+import sys
 
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the

krypy/deflation.py

@@ -625,12 +625,11 @@ def _auto():
 
         # perturbation
         # HACK until numpy.linal.svd (and thus numpy.linalg.norm) is fixed
-        from scipy.linalg import svd
         _, Rhsvd, _ = svd(Rh[:, :i])
         Rhnrm = numpy.max(Rhsvd)
         epsilon = PWAW_norm*(eta*(Hh_norm + G_norm) + G_norm) \
             + Rhnrm
-            #+ numpy.linalg.norm(Rh[:, :i], 2)
+            # + numpy.linalg.norm(Rh[:, :i], 2)
         if epsilon == 0:
             epsilon = 1e-16
 
@@ -798,8 +797,8 @@ def __init__(self, deflated_solver, mode='ritz'):
                 resnorm2 = Gy.T.conj().dot(S.dot(Gy))
                 self.resnorms[i] = numpy.sqrt(numpy.abs(resnorm2))
 
-        #elif isinstance(P, TODO):
-            #TODO
+        # elif isinstance(P, TODO):
+            # TODO
         else:
             raise utils.ArgumentError(
                 'Invalid projection used in deflated_solver. '

krypy/linsys.py

@@ -68,7 +68,7 @@ def __init__(self, A, b,
           (for debugging or research purposes). Defaults to ``None``.
         '''
         self.N = N = len(b)
-        '''Dimension :math:`N` of the space :math:`\mathbb{C}^N` where the
+        '''Dimension :math:`N` of the space :math:`\\mathbb{C}^N` where the
         linear system is defined.'''
         shape = (N, N)
 
@@ -117,7 +117,7 @@ def __init__(self, A, b,
 
         .. math::
 
-          \|M M_l b\|_{M^{-1}}
+          \\|M M_l b\\|_{M^{-1}}
         '''
 
     def get_residual(self, z, compute_norm=False):

krypy/recycling/evaluators.py

@@ -102,7 +102,7 @@ def _estimate_eval_intervals(ritz, indices, indices_remaining,
         mu_min = mu_ints.min_abs()
 
         # check gap assumption
-        #if delta_sel + delta_non_sel + eps_max - eps_min >= delta:
+        # if delta_sel + delta_non_sel + eps_max - eps_min >= delta:
         if delta_sel + eps_max - eps_min >= delta:
             raise utils.AssumptionError(
                 'delta_sel + delta_non_sel + eps_max - eps_min >= delta'
@@ -116,12 +116,12 @@ def _estimate_eval_intervals(ritz, indices, indices_remaining,
             raise utils.AssumptionError('mu_min == 0 not allowed')
 
         # compute eta
-        #eta = (delta_sel+eps_res)**2 * (
-        #    1/(delta-delta_non_sel-eps_max+eps_min)
-        #    + 1/mu_min
-        #    )
-        #left = - delta_non_sel + eps_min - eta
-        #right = delta_non_sel + eps_max + eta
+        # eta = (delta_sel+eps_res)**2 * (
+        #     1/(delta-delta_non_sel-eps_max+eps_min)
+        #     + 1/mu_min
+        #     )
+        # left = - delta_non_sel + eps_min - eta
+        # right = delta_non_sel + eps_max + eta
         eta = (delta_sel+eps_res)**2 * (
             1/(delta-eps_max+eps_min)
             + 1/mu_min
@@ -198,8 +198,8 @@ def evaluate(self, ritz, subset):
             **self.bound_pseudo_kwargs
             )
 
-        #from matplotlib import pyplot
-        #pyplot.semilogy(bound_pseudo)
+        # from matplotlib import pyplot
+        # pyplot.semilogy(bound_pseudo)
 
         if len(bound_pseudo) <= 1:
             raise utils.AssumptionError('no bound computed')
@@ -216,7 +216,7 @@ def evaluate(self, ritz, subset):
                 (bound_pseudo[1:]/bound_pseudo[0])
                 ** (1./numpy.array(range(1, len(bound_pseudo))))
                 )
-            if alpha >= 1 or alpha==0:
+            if alpha >= 1 or alpha == 0:
                 raise utils.AssumptionError(
                     'Cannot compute bound because alpha == {0} >= 1'.format(
                         alpha))

krypy/recycling/factories.py

@@ -1,8 +1,8 @@
 import numpy
 from .. import utils, deflation
-from . import generators, evaluators
+from . import generators
 
-#__all__ = ['_DeflationVectorFactory', 'RitzFactory']
+# __all__ = ['_DeflationVectorFactory', 'RitzFactory']
 
 
 class _DeflationVectorFactory(object):
@@ -101,7 +101,7 @@ def evaluate(_subset, _evaluations):
             overall_evaluations.update(evaluations)
 
         if len(overall_evaluations) > 0:
-        # if there was a successfull evaluation: pick the best one
+            # if there was a successfull evaluation: pick the best one
             selection = list(min(overall_evaluations,
                              key=overall_evaluations.get))
         else:

krypy/recycling/linsys.py

@@ -22,7 +22,7 @@ def __init__(self, DeflatedSolver,
 
            * ``'RitzApproxKrylov'``: uses the approximate Krylov subspace bound
              evaluator :py:class:`krypy.recycling.evaluators.RitzApproxKrylov`.
-           * ``'RitzAprioriCg'``: uses the CG :math:`\kappa`-bound
+           * ``'RitzAprioriCg'``: uses the CG :math:`\\kappa`-bound
              (:py:class:`krypy.utils.BoundCG`) as an a priori bound with
              :py:class:`krypy.recycling.evaluators.RitzApriori`.
            * ``'RitzAprioriMinres'``: uses the MINRES bound

krypy/tests/test_deflation.py

@@ -4,8 +4,7 @@
 import numpy
 import scipy.linalg
 import itertools
-from numpy.testing import assert_almost_equal, assert_array_almost_equal, \
-    assert_array_equal, assert_equal
+from numpy.testing import assert_almost_equal, assert_array_almost_equal
 
 
 def test_deflation_solver():
@@ -28,8 +27,8 @@ def test_deflation_solver():
                         'maxiter': 15,
                         'store_arnoldi': True}
 
-                    #if solver is krypy.deflation.DeflatedGmres:
-                    #    params['ortho'] = 'dmgs'
+                    # if solver is krypy.deflation.DeflatedGmres:
+                    #     params['ortho'] = 'dmgs'
 
                     yield run_deflation_solver, solver, ls, params
 
@@ -114,8 +113,8 @@ def check_Ritz(solver, ls):
                 numpy.ones(m+n))
 
             # check resnorms
-            #assert_array_almost_equal(ritz.resnorms[sort],
-            #                          cmp_resnorms, decimal=4)
+            # assert_array_almost_equal(ritz.resnorms[sort],
+            #                           cmp_resnorms, decimal=4)
 
 
 def test_Arnoldifyer():
@@ -200,7 +199,7 @@ def run_Arnoldifyer(ls, U, A_norm, Wt_sel):
                         / A_norm,
                         0, 7)
 
-    ## check projection
+    # check projection
     assert_array_almost_equal(krypy.utils.inner(Vh, (At+F)*Vh, ip_B=ip_Minv_B),
                               Hh,
                               7)
@@ -212,16 +211,16 @@ def run_Arnoldifyer(ls, U, A_norm, Wt_sel):
 
     # check norm of perturbation
     if Rh.size > 0:
-        #TODO: reenable once the numpy installation on travis is up-to-date!
-        #assert_almost_equal(numpy.linalg.norm(Rh, 2), numpy.linalg.norm(F, 2),
-        #                    8)
+        # TODO: reenable once the numpy installation on travis is up-to-date!
+        # assert_almost_equal(numpy.linalg.norm(Rh, 2), numpy.linalg.norm(F, 2),
+        #                     8)
         pass
 
     # check norm of vdiff
-    #PWb = PW*ls.b
-    #assert_array_almost_equal(krypy.utils.norm(ls.M*PW*,
-    #                                           ip_B=ls.get_ip_Minv_B()),
-    #                          vdiff_norm)
+    # PWb = PW*ls.b
+    # assert_array_almost_equal(krypy.utils.norm(ls.M*PW*,
+    #                                            ip_B=ls.get_ip_Minv_B()),
+    #                           vdiff_norm)
 
     # get orthonormal basis
     Q, _ = krypy.utils.qr(numpy.eye(N), ip_B=ls.get_ip_Minv_B())
@@ -235,7 +234,6 @@ def _get_op_norm(op):
                         )
 
 
-
 if __name__ == '__main__':
     import nose
     nose.main()

krypy/tests/test_linsys.py

@@ -2,8 +2,7 @@
 import krypy.tests.test_utils as test_utils
 import numpy
 import itertools
-from numpy.testing import assert_almost_equal, assert_array_almost_equal, \
-    assert_array_equal, assert_equal
+from numpy.testing import assert_almost_equal
 
 
 def dictproduct(d):
@@ -151,7 +150,7 @@ def check_solver(sol, solver, ls, params):
     Ml = krypy.utils.get_linearoperator(shape, ls.Ml)
 
     # maxiter respected?
-    if not 'max_restarts' in params:
+    if 'max_restarts' not in params:
         assert(len(sol.resnorms)-1 <= params['maxiter'])
     else:
         assert(len(sol.resnorms)-1 <=
@@ -203,9 +202,10 @@ def check_solver(sol, solver, ls, params):
     # has gmres (without restarts) found the solution after max N iterations?
     # (cg or minres may take longer because of roundoff errors)
     if solver == krypy.linsys.Gmres and \
-            ((not 'max_restarts' in params) or (params['max_restarts'] == 0)):
+            (('max_restarts' not in params) or (params['max_restarts'] == 0)):
         assert (len(sol.resnorms)-1 <= ls.b.shape[0])
 
+
 if __name__ == '__main__':
     import nose
     nose.main()

krypy/tests/test_recycling.py

@@ -1,5 +1,4 @@
 import krypy
-import krypy.tests.test_utils as test_utils
 import krypy.tests.test_linsys as test_linsys
 import numpy
 import itertools
@@ -35,29 +34,28 @@ def run_RitzFactorySimple(Solver, ls, which):
             assert(len(sols[-1].resnorms) <= len(sols[0].resnorms))
 
 
-#def test_SmallRitzGenerator():
+# def test_SmallRitzGenerator():
 #
-#    matrices = [test_utils.get_matrix_spd(),
-#                test_utils.get_matrix_hpd(),
-#                test_utils.get_symm_indef(),
-#                test_utils.get_herm_indef()]
-#    max_vectorss = [numpy.Inf, 2]
-#    for matrix, max_vectors in itertools.product(matrices, max_vectorss):
-#        yield run_SmallRitzGenerator, matrix, True, max_vectors
+#     matrices = [test_utils.get_matrix_spd(),
+#                 test_utils.get_matrix_hpd(),
+#                 test_utils.get_symm_indef(),
+#                 test_utils.get_herm_indef()]
+#     max_vectorss = [numpy.Inf, 2]
+#     for matrix, max_vectors in itertools.product(matrices, max_vectorss):
+#         yield run_SmallRitzGenerator, matrix, True, max_vectors
 #
 #
-#def _get_ritz(A, self_adjoint):
-#    linear_system = krypy.linsys.LinearSystem(A, numpy.ones((10, 1)),
-#                                              self_adjoint=True)
-#    deflated_solver = krypy.deflation.DeflatedGmres(linear_system,
-#                                                    store_arnoldi=True)
-#    return krypy.deflation.Ritz(deflated_solver)
+# def _get_ritz(A, self_adjoint):
+#     linear_system = krypy.linsys.LinearSystem(A, numpy.ones((10, 1)),
+#                                               self_adjoint=True)
+#     deflated_solver = krypy.deflation.DeflatedGmres(linear_system,
+#                                                     store_arnoldi=True)
+#     return krypy.deflation.Ritz(deflated_solver)
 #
-#def run_SmallRitzGenerator(A, self_adjoint, max_vectors):
-#    ritz = _get_ritz(A, self_adjoint)
-#    small = krypy.recycling.generators.SmallRitz(max_vectors=max_vectors)
-#    pass
-
+# def run_SmallRitzGenerator(A, self_adjoint, max_vectors):
+#     ritz = _get_ritz(A, self_adjoint)
+#     small = krypy.recycling.generators.SmallRitz(max_vectors=max_vectors)
+#     pass
 
 
 if __name__ == '__main__':

krypy/tests/test_utils.py

@@ -1,7 +1,6 @@
 import krypy
 import numpy
 import itertools
-from scipy.sparse import csr_matrix
 import scipy.linalg
 from numpy.testing import assert_almost_equal, assert_array_almost_equal, \
     assert_array_equal, assert_equal
@@ -337,14 +336,14 @@ def run_hegedus(A, b, x0, M, Ml, ip_B):
 
 
 def test_arnoldi():
-    #TODO: reactivate the complex tests once travis-ci uses newer
-    #      numpy/scipy versions.
+    # TODO: reactivate the complex tests once travis-ci uses newer
+    #       numpy/scipy versions.
     matrices = [get_matrix_spd(),
-                #get_matrix_hpd(),
+                # get_matrix_hpd(),
                 get_matrix_symm_indef(),
-                #get_matrix_herm_indef(),
+                # get_matrix_herm_indef(),
                 get_matrix_nonsymm(),
-                #get_matrix_comp_nonsymm()
+                # get_matrix_comp_nonsymm()
                 ]
     vs = [numpy.ones((10, 1)), numpy.eye(10, 1)]
     maxiters = [1, 5, 9, 10]
@@ -365,12 +364,12 @@ def test_arnoldi():
                 continue
             yield run_arnoldi, A, v, maxiter, ortho, M, ip_B, An
 
-    #TODO: reactivate the complex tests once travis-ci uses newer
-    #      numpy/scipy versions.
+    # TODO: reactivate the complex tests once travis-ci uses newer
+    #       numpy/scipy versions.
     matrices = [get_matrix_spd(),
-                #get_matrix_hpd(),
+                # get_matrix_hpd(),
                 get_matrix_symm_indef(),
-                #get_matrix_herm_indef()
+                # get_matrix_herm_indef()
                 ]
     for (matrix, v, maxiter, M, ip_B) in \
             itertools.product(matrices, vs, maxiters, Ms, ip_Bs):
@@ -408,7 +407,7 @@ def assert_arnoldi(A, v, V, H, P, maxiter, ortho, M, ip_B,
 
     k = H.shape[1]
 
-    #maxiter respected?
+    # maxiter respected?
     assert(k <= maxiter)
 
     invariant = H.shape[0] == k
@@ -486,9 +485,9 @@ def assert_arnoldi(A, v, V, H, P, maxiter, ortho, M, ip_B,
 def test_ritz():
     # Hermitian matrices
     matrices_herm = [get_matrix_spd(),
-                     #get_matrix_hpd(),
-                     #get_matrix_symm_indef(),
-                     #get_matrix_herm_indef(),
+                     # get_matrix_hpd(),
+                     # get_matrix_symm_indef(),
+                     # get_matrix_herm_indef(),
                      ]
     matrices_nonherm = [get_matrix_nonsymm(),
                         get_matrix_comp_nonsymm()