def calc_derivatives(self,
first=False,
second=False,
savebase=False,
required_inputs=None,
required_outputs=None):
""" Calculate derivatives and save baseline states for all components
in this workflow.
"""
self._stop = False
dgraph = self.derivative_graph(required_inputs, required_outputs)
comps = dgraph.edge_dict_to_comp_list(
edges_to_dict(dgraph.list_connections()))
for compname, data in comps.iteritems():
if '~' in compname:
comp = self._derivative_graph.node[compname]['pa_object']
elif compname.startswith('@'):
continue
else:
comp = self.scope.get(compname)
J = self._J_cache.get(compname)
if compname not in self._shape_cache:
self._shape_cache[compname] = {}
if J is None:
J = comp.calc_derivatives(first, second, savebase,
data['inputs'], data['outputs'])
if J is not None:
self._J_cache[compname] = J
if self._stop:
raise RunStopped('Stop requested')
def calc_derivatives(self, first=False, second=False, savebase=False,
required_inputs=None, required_outputs=None):
""" Calculate derivatives and save baseline states for all components
in this workflow.
"""
self._stop = False
dgraph = self.derivative_graph(required_inputs, required_outputs)
comps = dgraph.edge_dict_to_comp_list(edges_to_dict(dgraph.list_connections()))
for compname, data in comps.iteritems():
if '~' in compname:
comp = self._derivative_graph.node[compname]['pa_object']
elif compname.startswith('@'):
continue
else:
comp = self.scope.get(compname)
J = self._J_cache.get(compname)
if compname not in self._shape_cache:
self._shape_cache[compname] = {}
if J is None:
J = comp.calc_derivatives(first, second, savebase,
data['inputs'], data['outputs'])
if J is not None:
self._J_cache[compname] = J
if self._stop:
raise RunStopped('Stop requested')
def edge_list(self):
""" Return the list of edges for the derivatives of this workflow. """
if self._edges is None:
self._edges = edges_to_dict(self.derivative_graph().list_connections())
return self._edges
def edge_list(self):
""" Return the list of edges for the derivatives of this workflow. """
if self._edges is None:
self._edges = edges_to_dict(
self.derivative_graph().list_connections())
return self._edges
def get_inner_edges(graph, srcs, dests, wflow):
graph = graph.subgraph(graph.nodes())
# add @in and @out nodes, rewire input srcs, etc.
graph = mod_for_derivs(graph, srcs, dests, wflow)
# sort edges by src so that basevars occur before subvars
edges = sorted(graph.list_connections(), key=lambda e: e[0])
return edges_to_dict(edges)
def get_inner_edges(graph, srcs, dests, wflow):
graph = graph.subgraph(graph.nodes())
# add @in and @out nodes, rewire input srcs, etc.
graph = mod_for_derivs(graph, srcs, dests, wflow)
# sort edges by src so that basevars occur before subvars
edges = sorted(graph.list_connections(), key=lambda e: e[0])
return edges_to_dict(edges)
def test_get_inner_connections(self):
self.assertEqual(len(_get_inner_connections(self.dep, ['b'], ['c'])),
6)
self.assertEqual(
set(_get_inner_connections(self.dep, ['b'], ['c'])),
set([('b[3]', 'A.b'), ('A.d.z', 'B.b[4]'), ('A.c[2]', 'B.a.x.y'),
('B.c', 'C.a'), ('B.d', 'C.b'), ('C.c', 'c')]))
dep, scope = _make_graph(comps=['A', 'B'],
connections=[('A.c', 'B.a'), ('A.d', 'B.b')],
inputs=['a', 'b'],
outputs=['c', 'd'])
self.assertEqual(len(_get_inner_connections(dep, ['A.a'], ['B.c'])), 2)
self.assertEqual(set(_get_inner_connections(dep, ['A.a'], ['B.c'])),
set([('A.c', 'B.a'), ('A.d', 'B.b')]))
dep, scope = _make_graph(comps=['A', 'B', 'C'],
connections=[('A.c', 'B.a'), ('A.d', 'B.b'),
('B.d', 'C.a')],
inputs=['a', 'b'],
outputs=['c', 'd'])
self.assertEqual(set(_get_inner_connections(dep, ['A.a'], ['C.c'])),
set([('A.c', 'B.a'), ('A.d', 'B.b'), ('B.d', 'C.a')]))
# same output feeding two inputs
dep, scope = _make_graph(comps=['A', 'B', 'C'],
connections=[('A.d', 'B.a'), ('A.d', 'B.b'),
('B.d', 'C.a')],
inputs=['a', 'b'],
outputs=['c', 'd'])
edges = _get_inner_connections(dep, ['A.a'], ['C.c'])
self.assertEqual(set(edges),
set([('A.d', 'B.a'), ('A.d', 'B.b'), ('B.d', 'C.a')]))
edict = edges_to_dict(edges)
self.assertEqual(len(edict), 2)
self.assertEqual(set(edict['A.d']), set(['B.a', 'B.b']))
self.assertEqual(edict['B.d'], ['C.a'])
# loop
dep, scope = _make_graph(comps=['A', 'B', 'C'],
connections=[('A.d', 'B.a'), ('B.d', 'C.a'),
('C.d', 'A.a')],
inputs=['a', 'b'],
outputs=['c', 'd'])
self.assertEqual(set(_get_inner_connections(dep, ['A.a'], ['C.d'])),
set([('A.d', 'B.a'), ('B.d', 'C.a'), ('C.d', 'A.a')]))
def _pre_init(self, pa_name, group, dgraph, fd, boundary_params):
"""Return a tuple of the form (pa_inputs, pa_outputs, renames)
for the PseudoAssembly that would be created given the nodes in
group and the given graph.
"""
# First, find our group boundary
self._orig_group_nodes = list(group) + list(boundary_params)
allnodes = dgraph.find_prefixed_nodes(self._orig_group_nodes)
out_edges = nx.edge_boundary(dgraph, allnodes)
in_edges = nx.edge_boundary(dgraph,
set(dgraph.nodes()).difference(allnodes))
solver_states = []
if fd is False:
for comp in group:
# Keep any node marked 'solver_state'. Note, only inputs can
# be solver_states.
solver_states.extend([
node for node in dgraph.find_prefixed_nodes([comp])
if 'solver_state' in dgraph.node[node]
])
pa_inputs = edges_to_dict(in_edges).values()
pa_inputs.extend(solver_states)
pa_outputs = set([a[0] for a in out_edges])
renames = {}
# Add pseudoassy inputs
for varpath in list(flatten_list_of_iters(pa_inputs)) + \
list(pa_outputs):
varname = to_PA_var(varpath, pa_name)
if varpath in dgraph:
renames[varpath] = varname
old = dgraph.base_var(varpath)
if old != varpath:
renames[old] = to_PA_var(old, pa_name)
# make boundary params outputs of the PA
pa_outputs.update(boundary_params)
return pa_inputs, pa_outputs, renames
def _pre_init(self, pa_name, group, dgraph, fd, boundary_params):
"""Return a tuple of the form (pa_inputs, pa_outputs, renames)
for the PseudoAssembly that would be created given the nodes in
group and the given graph.
"""
# First, find our group boundary
self._orig_group_nodes = list(group) + list(boundary_params)
allnodes = dgraph.find_prefixed_nodes(self._orig_group_nodes)
out_edges = nx.edge_boundary(dgraph, allnodes)
in_edges = nx.edge_boundary(dgraph,
set(dgraph.nodes()).difference(allnodes))
solver_states = []
if fd is False:
for comp in group:
# Keep any node marked 'solver_state'. Note, only inputs can
# be solver_states.
solver_states.extend([node for node in dgraph.find_prefixed_nodes([comp])
if 'solver_state' in dgraph.node[node]])
pa_inputs = edges_to_dict(in_edges).values()
pa_inputs.extend(solver_states)
pa_outputs = set([a[0] for a in out_edges])
renames = {}
# Add pseudoassy inputs
for varpath in list(flatten_list_of_iters(pa_inputs)) + \
list(pa_outputs):
varname = to_PA_var(varpath, pa_name)
if varpath in dgraph:
renames[varpath] = varname
old = dgraph.base_var(varpath)
if old != varpath:
renames[old] = to_PA_var(old, pa_name)
# make boundary params outputs of the PA
pa_outputs.update(boundary_params)
return pa_inputs, pa_outputs, renames
def test_get_inner_connections(self):
self.assertEqual(len(_get_inner_connections(self.dep, ['b'], ['c'])), 6)
self.assertEqual(set(_get_inner_connections(self.dep, ['b'], ['c'])),
set([('b[3]','A.b'),('A.d.z','B.b[4]'),('A.c[2]','B.a.x.y'),
('B.c','C.a'),('B.d','C.b'),('C.c','c')]))
dep, scope = _make_graph(comps=['A','B'],
connections=[('A.c','B.a'),('A.d','B.b')],
inputs=['a','b'],
outputs=['c','d'])
self.assertEqual(len(_get_inner_connections(dep, ['A.a'], ['B.c'])), 2)
self.assertEqual(set(_get_inner_connections(dep, ['A.a'], ['B.c'])),
set([('A.c','B.a'),('A.d','B.b')]))
dep, scope = _make_graph(comps=['A','B', 'C'],
connections=[('A.c','B.a'),('A.d','B.b'),('B.d','C.a')],
inputs=['a','b'],
outputs=['c','d'])
self.assertEqual(set(_get_inner_connections(dep, ['A.a'], ['C.c'])),
set([('A.c','B.a'),('A.d','B.b'),('B.d','C.a')]))
# same output feeding two inputs
dep, scope = _make_graph(comps=['A','B', 'C'],
connections=[('A.d','B.a'),('A.d','B.b'),('B.d','C.a')],
inputs=['a','b'],
outputs=['c','d'])
edges = _get_inner_connections(dep, ['A.a'], ['C.c'])
self.assertEqual(set(edges), set([('A.d','B.a'),('A.d','B.b'),('B.d','C.a')]))
edict = edges_to_dict(edges)
self.assertEqual(len(edict), 2)
self.assertEqual(set(edict['A.d']), set(['B.a','B.b']))
self.assertEqual(edict['B.d'], ['C.a'])
# loop
dep, scope = _make_graph(comps=['A','B', 'C'],
connections=[('A.d','B.a'),('B.d','C.a'),('C.d','A.a')],
inputs=['a','b'],
outputs=['c','d'])
self.assertEqual(set(_get_inner_connections(dep, ['A.a'], ['C.d'])),
set([('A.d','B.a'),('B.d','C.a'),('C.d','A.a')]))
