def getSymbolDependancicesDirect(self, sym, include_constants=False):
assert sym in self.terminal_symbols
if isinstance(sym, AssignedVariable):
sym = sym.assignment_rhs
d = VisitorFindDirectSymbolDependance()
return list(set(d.visit(sym)))
def getSymbolDependancicesDirect(self, sym, include_constants=False):
assert sym in self.terminal_symbols
if isinstance(sym, AssignedVariable):
sym = sym.assignment_rhs
d = VisitorFindDirectSymbolDependance()
return list(set(d.visit(sym)))
def getSymbolDependancicesDirect(self, sym, include_constants=False):
from neurounits.visitors.common.ast_symbol_dependancies import VisitorFindDirectSymbolDependance
assert sym in self.terminal_symbols
if isinstance(sym, AssignedVariable):
sym = self._eqn_assignment.get_single_obj_by(lhs=sym)
if isinstance(sym, StateVariable):
sym = self._eqn_time_derivatives.get_single_obj_by(lhs=sym)
d = VisitorFindDirectSymbolDependance()
return list(set(d.visit(sym)))
def getSymbolDependancicesDirect(self, sym, include_constants=False):
from neurounits.visitors.common.ast_symbol_dependancies import VisitorFindDirectSymbolDependance
assert sym in self.terminal_symbols
if isinstance(sym, AssignedVariable):
sym = self._eqn_assignment.get_single_obj_by(lhs=sym)
if isinstance(sym, StateVariable):
sym = self._eqn_time_derivatives.get_single_obj_by(lhs=sym)
d = VisitorFindDirectSymbolDependance()
return list(set(d.visit(sym)))
def ordered_assignments_by_dependancies(self,):
from neurounits.visitors.common.ast_symbol_dependancies import VisitorFindDirectSymbolDependance
#from neurounits.visitors.common.ast_symbol_dependancies import VisitorFindDirectSymbolDependance
#from neurounits.units_misc import LookUpDict
ordered_assigned_values = VisitorFindDirectSymbolDependance.get_assignment_dependancy_ordering(self)
ordered_assignments = [LookUpDict(self.assignments).get_single_obj_by(lhs=av) for av in ordered_assigned_values]
return ordered_assignments
def VisitEqnSet(self, eqnset, modfilecontents, build_parameters, **kwargs):
self.assigment_statements = {}
ASTActionerDefaultIgnoreMissing.VisitEqnSet(self,eqnset,modfilecontents=modfilecontents, build_parameters=build_parameters, **kwargs)
# The order of writing out assignments is important. There are 3 phases,
# 1. Initialisation
# 2. Pre-State Solving
# 3. Post-State Solving
# At this stage, we assume that there are no assignments dependant on states depending on
# further assignments. This can be resolved, but I have not done so here....
# 1. Initialisation:
# We perform all assignments in order:
assignments_ordered = VisitorFindDirectSymbolDependance.get_assignment_dependancy_ordering( eqnset)
for ass in assignments_ordered:
modfilecontents.section_INITIAL.append( self.assigment_statements[ass] )
# 2. Find which assignments are used by the states:
required_assignments = []
dependancies = VisitorFindDirectSymbolDependance()
dependancies.VisitEqnSet(eqnset)
for s in eqnset.timederivatives:
ass_deps = [d for d in dependancies.dependancies[s] if not isinstance(d, StateVariable) ]
required_assignments.extend( ass_deps)
all_deps = []
for i in required_assignments:
a = VisitorFindDirectSymbolDependance().get_assignment_dependancy_ordering_recursive(eqnset=eqnset, ass=i)
all_deps.extend(a)
all_deps.append(i)
for ass in unique(all_deps):
unexpected_deps = [d for d in dependancies.dependancies[ass] if not isinstance(d, (AssignedVariable, SymbolicConstant, SuppliedValue, Parameter)) ]
print unexpected_deps
print 'Unexpected:', [s.symbol for s in unexpected_deps]
assert not unexpected_deps, "Resolution of dependances in Neurounits can't support assignments need by timeerivatives which are dependanct on state variables (%s)"%(unexpected_deps)
modfilecontents.section_BREAKPOINT_pre_solve.append( self.assigment_statements[ass] )
# 3. Find the dependancies of the current variables:
all_deps = []
for c in build_parameters.currents:
a = VisitorFindDirectSymbolDependance().get_assignment_dependancy_ordering_recursive(eqnset=eqnset, ass=c)
all_deps.extend(a)
all_deps.append(c)
for ass in unique(all_deps):
modfilecontents.section_BREAKPOINT_post_solve.append( self.assigment_statements[ass] )
def ordered_assignments_by_dependancies(self, ):
from neurounits.visitors.common.ast_symbol_dependancies import VisitorFindDirectSymbolDependance
#from neurounits.visitors.common.ast_symbol_dependancies import VisitorFindDirectSymbolDependance
#from neurounits.units_misc import LookUpDict
ordered_assigned_values = VisitorFindDirectSymbolDependance.get_assignment_dependancy_ordering(
self)
ordered_assignments = [
LookUpDict(self.assignments).get_single_obj_by(lhs=av)
for av in ordered_assigned_values
]
return ordered_assignments
def VisitEqnSet(self, eqnset, modfilecontents, build_parameters, **kwargs):
self.assigment_statements = {}
ASTActionerDefaultIgnoreMissing.VisitEqnSet(self,eqnset,modfilecontents=modfilecontents, build_parameters=build_parameters, **kwargs)
# The order of writing out assignments is important. There are 3 phases,
# 1. Initialisation
# 2. Pre-State Solving
# 3. Post-State Solving
# At this stage, we assume that there are no assignments dependant on states depending on
# further assignments. This can be resolved, but I have not done so here....
# 1. Initialisation:
# We perform all assignments in order:
assignments_ordered = VisitorFindDirectSymbolDependance.get_assignment_dependancy_ordering( eqnset)
for ass in assignments_ordered:
modfilecontents.section_INITIAL.append( self.assigment_statements[ass] )
# 2. Find which assignments are used by the states:
required_assignments = []
dependancies = VisitorFindDirectSymbolDependance()
dependancies.VisitEqnSet(eqnset)
for s in eqnset.timederivatives:
ass_deps = [d for d in dependancies.dependancies[s] if not isinstance(d, StateVariable) ]
required_assignments.extend( ass_deps)
all_deps = []
for i in required_assignments:
a = VisitorFindDirectSymbolDependance().get_assignment_dependancy_ordering_recursive(eqnset=eqnset, ass=i)
all_deps.extend(a)
all_deps.append(i)
for ass in unique(all_deps):
unexpected_deps = [d for d in dependancies.dependancies[ass] if not isinstance(d, (AssignedVariable, SymbolicConstant, SuppliedValue, Parameter)) ]
print unexpected_deps
print 'Unexpected:', [s.symbol for s in unexpected_deps]
assert not unexpected_deps, "Resolution of dependances in Neurounits can't support assignments need by timeerivatives which are dependanct on state variables (%s)"%(unexpected_deps)
modfilecontents.section_BREAKPOINT_pre_solve.append( self.assigment_statements[ass] )
# 3. Find the dependancies of the current variables:
all_deps = []
for c in build_parameters.currents:
a = VisitorFindDirectSymbolDependance().get_assignment_dependancy_ordering_recursive(eqnset=eqnset, ass=c)
all_deps.extend(a)
all_deps.append(c)
for ass in unique(all_deps):
modfilecontents.section_BREAKPOINT_post_solve.append(self.assigment_statements[ass])
def build_analog_integration_blks(component):
# Build the original dependance graph:
graph = VisitorFindDirectSymbolDependance.build_direct_dependancy_graph(component)
# Also, add in the RT graphs, that aren't direct dependents of anything, so
# that the aprpriate AnalogIntegrationBlocks are created. (This might
# emit events, but nothing else for example)
for rt_graph in component.rt_graphs:
if not rt_graph in graph:
graph.add_node(rt_graph, label=repr(rt_graph), color='grey')
# Plot:
do_plot = True and False
if do_plot:
plot_networkx_graph(graph, show=False)
plt.show()
# Get the strongly connected components, and the dependancies between the
# nodes:
scc = nx.strongly_connected_components(graph)
cond = nx.condensation(graph, scc=scc)
#for node, node_data in cond.nodes_iter(data=True):
# print node, node_data
ordering = reversed( nx.topological_sort(cond) )
blks = []
for o in ordering:
objs = set(scc[0])
blk_deps = set()
for obj in scc[o]:
o_deps = set(graph.successors(obj)) - objs
blk_deps |= o_deps
print blk_deps
blk_deps = blk_deps - set(scc[o])
blk = AnalogIntegrationBlock( objs = scc[o], dependancies=blk_deps )
blks.append(blk)
return blks
def build_analog_integration_blks(component):
# Build the original dependance graph:
graph = VisitorFindDirectSymbolDependance.build_direct_dependancy_graph(
component)
# Also, add in the RT graphs, that aren't direct dependents of anything, so
# that the aprpriate AnalogIntegrationBlocks are created. (This might
# emit events, but nothing else for example)
for rt_graph in component.rt_graphs:
if not rt_graph in graph:
graph.add_node(rt_graph, label=repr(rt_graph), color='grey')
# Plot:
do_plot = True and False
if do_plot:
plot_networkx_graph(graph, show=False)
plt.show()
# Get the strongly connected components, and the dependancies between the
# nodes:
scc = nx.strongly_connected_components(graph)
cond = nx.condensation(graph, scc=scc)
#for node, node_data in cond.nodes_iter(data=True):
# print node, node_data
ordering = reversed(nx.topological_sort(cond))
blks = []
for o in ordering:
objs = set(scc[0])
blk_deps = set()
for obj in scc[o]:
o_deps = set(graph.successors(obj)) - objs
blk_deps |= o_deps
print blk_deps
blk_deps = blk_deps - set(scc[o])
blk = AnalogIntegrationBlock(objs=scc[o], dependancies=blk_deps)
blks.append(blk)
return blks
def build_event_blks(component, analog_blks):
# Find out what the rt_graphs are dependant on: events & triggers:
# =================================================================
# 1. Make a map dependancies 'rt_graph -> state_variable/assignments'
rt_graph_deps_triggers = defaultdict(set)
dep_finder = VisitorFindDirectSymbolDependance()
for tr in component._transitions_triggers:
#print 'TRANSITION:', repr(tr)
trigger_deps = dep_finder.visit(tr.trigger)
for tdep in trigger_deps:
if tdep.symbol != 't':
rt_graph_deps_triggers[tr.rt_graph].add(tdep)
# 2. Make a map dependancies 'rt_graph -> event_ports'
rt_graph_deps_events = defaultdict(set)
for tr in component._transitions_events:
#print 'TRANSITION:', repr(tr)
rt_graph_deps_events[tr.rt_graph].add(tr.port)
# Find out what transitions particular state-variables
# are dependant on because of assignments:
# =========================================
statevar_on_rt_deps = defaultdict(set)
for tr in component.transitions:
for action in tr.actions:
if isinstance(action, ast.OnEventStateAssignment):
statevar_on_rt_deps[action.lhs].add(tr.rt_graph)
# OK, now lets build a new dependancy graph to work out transition/event
# dependancies:
# A. Start with the analog graph:
graph = VisitorFindDirectSymbolDependance.build_direct_dependancy_graph(
component)
# B. Add the RT-graph nodes:
for rt_graph in component._rt_graphs:
graph.add_node(rt_graph, label=repr(rt_graph), color='orange')
# C. Add the dependance of rt_graphs on trigger-conditions:
for rt_graph, deps in rt_graph_deps_triggers.items():
for dep in deps:
graph.add_edge(
rt_graph,
dep,
)
# D. Add the dependance of state_varaibles on assignments in rt_graphs:
for sv, deps in statevar_on_rt_deps.items():
for dep in deps:
graph.add_edge(
sv,
dep,
)
# E. Event Dependancies:
# -- (Use the src event ports as the 'objects' in the graph:
for inp in component.input_event_port_lut:
graph.add_node(inp, label=repr(inp), color='brown')
for out in component.output_event_port_lut:
graph.add_node(out, label=repr(out), color='chocolate')
#Output events are dependant on their rt_graphs:
for tr in component.transitions:
for a in tr.actions:
if isinstance(a, ast.EmitEvent):
graph.add_edge(a.port, tr.rt_graph)
# -- RT graph dependance on input events:
for tr in component._transitions_events:
# The RT graph depends on the incoming events:
graph.add_edge(tr.rt_graph, tr.port)
# -- Input ports can depend on output ports:
for conn in component._event_port_connections:
graph.add_edge(conn.dst_port, conn.src_port)
statevar_on_rt_deps = defaultdict(set)
do_plot = False
if do_plot:
plot_networkx_graph(graph, show=False)
scc = nx.strongly_connected_components(graph)
cond = nx.condensation(graph, scc=scc)
#plot_networkx_graph(cond)
plt.figure()
nx.draw_graphviz(
cond,
font_size=10,
iteration=200,
)
# Build a dictionary mapping each state_variable to analog block that its in:
obj_to_analog_block = {}
for blk in analog_blks:
for obj in blk.objects:
assert not obj in obj_to_analog_block
obj_to_analog_block[obj] = blk
ordering = reversed(nx.topological_sort(cond))
all_uncovered_blks = set()
ev_blks = []
print 'Event Block ordering:'
print '====================='
for o in ordering:
print
print ' ---- %d ---- ' % o
print scc[o]
#for obj in scc[o]:
# print ' -- ', obj,
analog_blks = list(
set([obj_to_analog_block.get(obj, None) for obj in scc[o]]))
analog_blks = [blk for blk in analog_blks if blk is not None]
print 'Analog Blocks:', len(analog_blks)
# OK, whose not covered by the AnalogBlocks?
covered_objs = set(list(chain(*[blk.objects for blk in analog_blks])))
uncovered_objs = set(scc[o]) - covered_objs
uncovered_objs = set([
co for co in uncovered_objs
if not isinstance(co, (ast.InEventPort, ast.OutEventPort))
])
if uncovered_objs:
print 'UNcovered Objects:', uncovered_objs
all_uncovered_blks |= uncovered_objs
#assert False
if analog_blks:
ev = EventIntegrationBlock(analog_blks=analog_blks)
ev_blks.append(ev)
if all_uncovered_blks:
print all_uncovered_blks
assert False
return ev_blks
def build_event_blks(component, analog_blks):
# Find out what the rt_graphs are dependant on: events & triggers:
# =================================================================
# 1. Make a map dependancies 'rt_graph -> state_variable/assignments'
rt_graph_deps_triggers = defaultdict(set)
dep_finder = VisitorFindDirectSymbolDependance()
for tr in component._transitions_triggers:
#print 'TRANSITION:', repr(tr)
trigger_deps = dep_finder.visit(tr.trigger)
for tdep in trigger_deps:
if tdep.symbol != 't':
rt_graph_deps_triggers[tr.rt_graph].add(tdep)
# 2. Make a map dependancies 'rt_graph -> event_ports'
rt_graph_deps_events = defaultdict(set)
for tr in component._transitions_events:
#print 'TRANSITION:', repr(tr)
rt_graph_deps_events[tr.rt_graph].add(tr.port)
# Find out what transitions particular state-variables
# are dependant on because of assignments:
# =========================================
statevar_on_rt_deps= defaultdict(set)
for tr in component.transitions:
for action in tr.actions:
if isinstance(action, ast.OnEventStateAssignment):
statevar_on_rt_deps[action.lhs].add(tr.rt_graph)
# OK, now lets build a new dependancy graph to work out transition/event
# dependancies:
# A. Start with the analog graph:
graph = VisitorFindDirectSymbolDependance.build_direct_dependancy_graph(component)
# B. Add the RT-graph nodes:
for rt_graph in component._rt_graphs:
graph.add_node(rt_graph, label=repr(rt_graph), color='orange')
# C. Add the dependance of rt_graphs on trigger-conditions:
for rt_graph, deps in rt_graph_deps_triggers.items():
for dep in deps:
graph.add_edge(rt_graph,dep,)
# D. Add the dependance of state_varaibles on assignments in rt_graphs:
for sv, deps in statevar_on_rt_deps.items():
for dep in deps:
graph.add_edge(sv,dep,)
# E. Event Dependancies:
# -- (Use the src event ports as the 'objects' in the graph:
for inp in component.input_event_port_lut:
graph.add_node(inp, label=repr(inp), color='brown')
for out in component.output_event_port_lut:
graph.add_node(out, label=repr(out), color='chocolate')
#Output events are dependant on their rt_graphs:
for tr in component.transitions:
for a in tr.actions:
if isinstance(a, ast.EmitEvent ):
graph.add_edge(a.port, tr.rt_graph)
# -- RT graph dependance on input events:
for tr in component._transitions_events:
# The RT graph depends on the incoming events:
graph.add_edge(tr.rt_graph, tr.port )
# -- Input ports can depend on output ports:
for conn in component._event_port_connections:
graph.add_edge(conn.dst_port, conn.src_port)
statevar_on_rt_deps= defaultdict(set)
do_plot=False
if do_plot:
plot_networkx_graph(graph, show=False)
scc = nx.strongly_connected_components(graph)
cond = nx.condensation(graph, scc=scc)
#plot_networkx_graph(cond)
plt.figure()
nx.draw_graphviz(cond, font_size=10, iteration=200, )
# Build a dictionary mapping each state_variable to analog block that its in:
obj_to_analog_block = {}
for blk in analog_blks:
for obj in blk.objects:
assert not obj in obj_to_analog_block
obj_to_analog_block[obj] = blk
ordering = reversed( nx.topological_sort(cond) )
all_uncovered_blks = set()
ev_blks = []
print 'Event Block ordering:'
print '====================='
for o in ordering:
print
print ' ---- %d ---- ' % o
print scc[o]
#for obj in scc[o]:
# print ' -- ', obj,
analog_blks = list(set( [obj_to_analog_block.get(obj,None) for obj in scc[o] ] ) )
analog_blks = [blk for blk in analog_blks if blk is not None]
print 'Analog Blocks:', len(analog_blks)
# OK, whose not covered by the AnalogBlocks?
covered_objs = set( list(chain(*[blk.objects for blk in analog_blks])) )
uncovered_objs = set(scc[o]) - covered_objs
uncovered_objs = set( [co for co in uncovered_objs if not isinstance(co, (ast.InEventPort,ast.OutEventPort))])
if uncovered_objs:
print 'UNcovered Objects:', uncovered_objs
all_uncovered_blks |= uncovered_objs
#assert False
if analog_blks:
ev = EventIntegrationBlock(analog_blks=analog_blks)
ev_blks.append(ev)
if all_uncovered_blks:
print all_uncovered_blks
assert False
return ev_blks
