diff --git a/python/dune/perftool/pdelab/driver.py b/python/dune/perftool/pdelab/driver.py
index aaf4c092503cbf76ab8747bd1d70dadf34a85e8d..7347f6f96a15bc50c1d8e438d6fdb5c696d1d922 100644
--- a/python/dune/perftool/pdelab/driver.py
+++ b/python/dune/perftool/pdelab/driver.py
@@ -1782,7 +1782,7 @@ def generate_driver(formdatas, data):
assert(any(_driver_data['form'].ufl_cell().cellname() in x for x in
["vertex", "interval", "quadrilateral", "hexahedron"]))
# In case of operator conunting we only assemble the matrix and evaluate the residual
- #assemble_matrix_timer()
+ # assemble_matrix_timer()
evaluate_residual_timer()
apply_jacobian_timer()
elif is_stationary():
diff --git a/python/dune/perftool/pdelab/geometry.py b/python/dune/perftool/pdelab/geometry.py
index 9da0f1ee86df3e836a8091cc55ddfe3d148e0ab0..58122feb41bfff935136536ba63f4679434c8763 100644
--- a/python/dune/perftool/pdelab/geometry.py
+++ b/python/dune/perftool/pdelab/geometry.py
@@ -290,7 +290,7 @@ def name_unit_inner_normal():
def type_jacobian_inverse_transposed(restriction):
if get_option('turn_off_diagonal_jacobian'):
dim = world_dimension()
- return "typename Dune::FieldMatrix<double,{},{}>".format(dim,dim)
+ return "typename Dune::FieldMatrix<double,{},{}>".format(dim, dim)
else:
geo = type_cell_geometry(restriction)
return "typename {}::JacobianInverseTransposed".format(geo)
diff --git a/python/dune/perftool/pdelab/localoperator.py b/python/dune/perftool/pdelab/localoperator.py
index 1a5f8faf52f78c1732412ee0f579f53b07a8482b..24f7e937af2a17e001117c519e052eb75cea934d 100644
--- a/python/dune/perftool/pdelab/localoperator.py
+++ b/python/dune/perftool/pdelab/localoperator.py
@@ -431,14 +431,14 @@ def visit_integrals(integrals):
domain = accterm.argument.argexpr.ufl_domain()
if measure == "cell":
set_subst_rule("integration_factor_cell1",
- uc.QuadratureWeight(domain)*uc.Abs(uc.JacobianDeterminant(domain)))
+ uc.QuadratureWeight(domain) * uc.Abs(uc.JacobianDeterminant(domain)))
set_subst_rule("integration_factor_cell2",
- uc.Abs(uc.JacobianDeterminant(domain))*uc.QuadratureWeight(domain))
+ uc.Abs(uc.JacobianDeterminant(domain)) * uc.QuadratureWeight(domain))
else:
set_subst_rule("integration_factor_facet1",
- uc.FacetJacobianDeterminant(domain)*uc.QuadratureWeight(domain))
+ uc.FacetJacobianDeterminant(domain) * uc.QuadratureWeight(domain))
set_subst_rule("integration_factor_facet2",
- uc.QuadratureWeight(domain)*uc.FacetJacobianDeterminant(domain))
+ uc.QuadratureWeight(domain) * uc.FacetJacobianDeterminant(domain))
get_backend(interface="accum_insn")(visitor, accterm, measure, subdomain_id)
diff --git a/python/dune/perftool/pdelab/tensors.py b/python/dune/perftool/pdelab/tensors.py
index aa154bdb1a41a8dfc54b8faf92043be5a4c0b78a..a3953799ecf0643ee559a8ba0836ebb77829c5ae 100644
--- a/python/dune/perftool/pdelab/tensors.py
+++ b/python/dune/perftool/pdelab/tensors.py
@@ -48,14 +48,14 @@ def define_identity(name, expr):
i = identity_iname("i", expr.ufl_shape[0])
j = identity_iname("j", expr.ufl_shape[1])
instruction(assignee=prim.Subscript(prim.Variable(name), (prim.Variable(i), prim.Variable(j))),
- expression=prim.If(prim.Comparison(prim.Variable(i),"==",prim.Variable(j)),1,0),
+ expression=prim.If(prim.Comparison(prim.Variable(i), "==", prim.Variable(j)), 1, 0),
forced_iname_deps_is_final=True,
)
@kernel_cached
def pymbolic_identity(expr):
- name = "identity_{}_{}".format(expr.ufl_shape[0],expr.ufl_shape[1])
+ name = "identity_{}_{}".format(expr.ufl_shape[0], expr.ufl_shape[1])
temporary_variable(name,
shape=expr.ufl_shape,
shape_impl=('fm',),
diff --git a/python/dune/perftool/sumfact/sumfact.py b/python/dune/perftool/sumfact/sumfact.py
index 73952843abd68e90ed4aa1d126872d879a1741fc..a91079f54ff2fb4ef1746e7d737d7fbc04f3456c 100644
--- a/python/dune/perftool/sumfact/sumfact.py
+++ b/python/dune/perftool/sumfact/sumfact.py
@@ -221,7 +221,6 @@ def generate_accumulation_instruction(visitor, accterm, measure, subdomain_id):
depends_on=insn_dep,
within_inames=frozenset(visitor.inames))})
-
inames = tuple(accum_iname((accterm.argument.restriction, restriction), mat.rows, i)
for i, mat in enumerate(a_matrices))
@@ -260,7 +259,6 @@ def generate_accumulation_instruction(visitor, accterm, measure, subdomain_id):
assert ft == 'jacobian'
direct_output = accum
-
# Add a sum factorization kernel that implements the multiplication
# with the test function (stage 3)
pref_pos = i if accterm.new_indices else None
@@ -298,8 +296,8 @@ def generate_accumulation_instruction(visitor, accterm, measure, subdomain_id):
if get_global_context_value("dry_run", False):
dummy = "dummy"
globalarg(dummy, dtype=np.float64)
- instruction(assignee = prim.Variable(dummy),
- expression = result,
+ instruction(assignee=prim.Variable(dummy),
+ expression=result,
forced_iname_deps=frozenset(inames),
forced_iname_deps_is_final=True,
depends_on=insn_dep,
@@ -350,29 +348,29 @@ def _sf_permutation_heuristic(permutations, stage):
"""
def cost(perm, stage):
cost = 0
- for i in range(0,len(perm)-2):
- if stage==1:
- if perm[i+1]>perm[i+2]:
+ for i in range(0, len(perm) - 2):
+ if stage == 1:
+ if perm[i + 1] > perm[i + 2]:
cost += 1
- if stage==3:
- if perm[0]>perm[i+1]:
+ if stage == 3:
+ if perm[0] > perm[i + 1]:
cost += 1
return cost
- perm = min(permutations, key=lambda i:cost(i,stage))
+ perm = min(permutations, key=lambda i: cost(i, stage))
return perm
def _sf_flop_cost(a_matrices):
"""Computational cost of sumfactorization with this list of a_matrices
"""
- cost = 0;
+ cost = 0
for l in range(len(a_matrices)):
cost_m = 1
cost_n = 1
- for i in range(l+1):
+ for i in range(l + 1):
cost_m *= a_matrices[i].rows
- for i in range(l,len(a_matrices)):
+ for i in range(l, len(a_matrices)):
cost_n *= a_matrices[i].cols
cost += cost_m * cost_n
return cost
@@ -393,12 +391,12 @@ def _sf_permutation_strategy(a_matrices, stage):
for permutation in itertools.permutations(perm_a_matrices):
perm, series = zip(*permutation)
cost = _sf_flop_cost(series)
- perm_cost.append((perm,cost))
+ perm_cost.append((perm, cost))
# Find minimal cost and all permutations with that cost
_, costs = zip(*perm_cost)
minimal_cost = min(costs)
- minimal_cost_permutations = [p[0] for p in perm_cost if p[1]==minimal_cost]
+ minimal_cost_permutations = [p[0] for p in perm_cost if p[1] == minimal_cost]
# Use heuristic to pic one of the minimal cost permutations
perm = _sf_permutation_heuristic(minimal_cost_permutations, stage)
@@ -413,7 +411,7 @@ def _permute_forward(t, perm):
def _permute_backward(t, perm):
- tmp = [None]*len(t)
+ tmp = [None] * len(t)
for i, pos in enumerate(perm):
tmp[pos] = t[i]
return tuple(tmp)
@@ -500,9 +498,9 @@ def sum_factorization_kernel(a_matrices,
if get_global_context_value("dry_run", False):
return SumfactKernel(a_matrices, buf, stage, preferred_position, restriction), frozenset()
- ftags = ",".join(["f"]*len(a_matrices))
+ ftags = ",".join(["f"] * len(a_matrices))
novec_ftags = ftags
- ctags = ",".join(["c"]*len(a_matrices))
+ ctags = ",".join(["c"] * len(a_matrices))
vec_shape = ()
if next(iter(a_matrices)).vectorized:
ftags = ftags + ",vec"
@@ -611,7 +609,7 @@ def sum_factorization_kernel(a_matrices,
#
# If we are in the last step we reverse the permutation.
output_shape = tuple(out_shape[1:]) + (out_shape[0],)
- if l == len(a_matrices)-1:
+ if l == len(a_matrices) - 1:
output_shape = _permute_backward(output_shape, perm)
out = get_buffer_temporary(buf,
shape=output_shape + vec_shape,
@@ -629,12 +627,12 @@ def sum_factorization_kernel(a_matrices,
# Here we also move the new direction (out_inames[0]) to the
# end and reverse permutation
output_inames = tuple(prim.Variable(i) for i in out_inames[1:]) + (prim.Variable(out_inames[0]),)
- if l == len(a_matrices)-1:
+ if l == len(a_matrices) - 1:
output_inames = _permute_backward(output_inames, perm)
# In case of direct output we directly accumulate the result
# of the Sumfactorization into some global data structure.
- if l == len(a_matrices)-1 and direct_output is not None:
+ if l == len(a_matrices) - 1 and direct_output is not None:
ft = get_global_context_value("form_type")
if ft == 'residual' or ft == 'jacobian_apply':
globalarg(direct_output, dtype=np.float64, shape=output_shape, dim_tags=novec_ftags)
@@ -644,7 +642,7 @@ def sum_factorization_kernel(a_matrices,
globalarg(direct_output,
dtype=np.float64,
shape=output_shape + output_shape,
- dim_tags = novec_ftags + "," + novec_ftags)
+ dim_tags=novec_ftags + "," + novec_ftags)
# TODO the next line should get its inames from
# elsewhere. This is *NOT* robust (but works right
# now)
diff --git a/python/dune/perftool/ufl/extract_accumulation_terms.py b/python/dune/perftool/ufl/extract_accumulation_terms.py
index 4dbebbb8233f06cbb42ac273a72d609dc8fb5059..15aef6882fc1202622a5fb3221b2ccfa9ff574d3 100644
--- a/python/dune/perftool/ufl/extract_accumulation_terms.py
+++ b/python/dune/perftool/ufl/extract_accumulation_terms.py
@@ -135,16 +135,16 @@ def split_into_accumulation_terms(expr):
# - Propagating the identity in step 4.
# - Replacing (\nabla v)_{k,l} by I_{k,l} after step 4.
if len(set(indexed_test_arg.index._indices)) < len(indexed_test_arg.index._indices):
- if len(indexed_test_arg.index._indices)>2:
+ if len(indexed_test_arg.index._indices) > 2:
raise NotImplementedError("Test argument with more than three indices and double occurence ist not implemented.")
mod_index_map = {indexed_test_arg.index: MultiIndex((newi[0], newi[1]))}
mod_indexed_test_arg = replace_expression(indexed_test_arg.expr,
- replacemap = mod_index_map)
+ replacemap=mod_index_map)
rep = Product(Indexed(Identity(2),
- MultiIndex((newi[0],indexed_test_arg.index[0]))),
+ MultiIndex((newi[0], indexed_test_arg.index[0]))),
mod_indexed_test_arg)
backmap.update({mod_indexed_test_arg:
- Indexed(Identity(2), MultiIndex((newi[0],newi[1])))})
+ Indexed(Identity(2), MultiIndex((newi[0], newi[1])))})
replacement.update({indexed_test_arg.expr: rep})
indexmap.update({indexed_test_arg.index[0]: newi[0]})
else:
diff --git a/python/dune/perftool/ufl/modified_terminals.py b/python/dune/perftool/ufl/modified_terminals.py
index b5d2f2c550d5fbfafd7c3aab7a76c6890dc04934..50dd331555e75416ef01cec00ade88de7291a410 100644
--- a/python/dune/perftool/ufl/modified_terminals.py
+++ b/python/dune/perftool/ufl/modified_terminals.py
@@ -168,7 +168,6 @@ class _ModifiedArgumentExtractor(MultiFunction):
else:
self.expr(o)
-
positive_restricted = pass_on
negative_restricted = pass_on
function_view = pass_on
diff --git a/python/dune/perftool/ufl/transformations/axiparallel.py b/python/dune/perftool/ufl/transformations/axiparallel.py
index 6d7e53e4a2468c0198dabb349017fc885915ef04..4ded73a773147f34a09ef9312dda4ea72f89a627 100644
--- a/python/dune/perftool/ufl/transformations/axiparallel.py
+++ b/python/dune/perftool/ufl/transformations/axiparallel.py
@@ -49,7 +49,6 @@ class LocalDiagonalJITReplacer(MultiFunction):
else:
return self.reuse_if_untouched(o, *tuple(self.call(op) for op in o.ufl_operands))
-
def index_sum(self, o):
# Check if we want to replace an index here and store it in
# local_replacemap
diff --git a/python/dune/perftool/ufl/visitor.py b/python/dune/perftool/ufl/visitor.py
index 711f92bf6b54a614ddcdd647409e55f310461c08..96f1cb85c89ee566882d04e56d386dac6df94d8c 100644
--- a/python/dune/perftool/ufl/visitor.py
+++ b/python/dune/perftool/ufl/visitor.py
@@ -296,7 +296,6 @@ class UFL2LoopyVisitor(ModifiedTerminalTracker):
return ret
-
#
# Handler for conditionals, use pymbolic base implementation
#