def VisitLibrary(self, o, **kwargs):
removed = []
for aKey in o._eqn_assignment.keys():
a = o._eqn_assignment[aKey]
alhs = a.lhs
fixed_value = self.visit(a.rhs)
if fixed_value:
sym_suffix = '_as_symconst'
sym_suffix = ''
s = ast.SymbolicConstant(symbol=aKey.symbol
+ sym_suffix, value=fixed_value)
#assert False
#print 'Replacing Node:', a.lhs.symbol
ReplaceNode(a.lhs, s).visit(o)
#o._cache_nodes()
#print 'Done replacing symbol'
o._symbolicconstants[aKey.symbol] = s
del o._eqn_assignment[aKey]
removed.append(alhs)
# Double check they have gone:
for a in removed:
nc = EqnsetVisitorNodeCollector()
nc.visit(o)
assert not a in nc.all()
# Should be no more assignments:
assert len(o._eqn_assignment) == 0
def _res_assignments(self, o, **kwargs):
removed = []
for aKey in o._eqn_assignment.keys():
a = o._eqn_assignment[aKey]
alhs = a.lhs
fixed_value = self.visit(a.rhs_map)
if fixed_value:
sym_suffix = '_as_symconst'
sym_suffix = ''
s = ast.SymbolicConstant(symbol=aKey.symbol
+ sym_suffix, value=fixed_value)
#ReplaceNode(a.lhs, s).visit(o)
ReplaceNode.replace_and_check(srcObj=a.lhs, dstObj=s, root = o)
o._symbolicconstants[aKey.symbol] = s
from neurounits.misc import SeqUtils
old_ass = SeqUtils.filter_expect_single( o._eqn_assignment, lambda o:o.symbol == aKey.symbol )
del o._eqn_assignment[ old_ass ] #o.get_terminal_obj(aKey.symbol) ]
#del o._eqn_assignment[ o.get_terminal_obj(aKey.symbol) ]
removed.append(alhs)
# Double check they have gone:
for a in removed:
nc = EqnsetVisitorNodeCollector()
nc.visit(o)
assert not a in nc.all()
def _cache_nodes(self):
t = EqnsetVisitorNodeCollector()
t.visit(self)
self._parameters = t.nodes[Parameter]
self._supplied_values = t.nodes[SuppliedValue]
def InferFromEqnset(cls, eqnset):
currents = {}
supplied_values = {}
for io_info in [io_info for io_info in eqnset.io_data if io_info.iotype in (IOType.Output, IOType.Input)]:
if not io_info.metadata or not 'mf' in io_info.metadata:
continue
role = io_info.metadata['mf'].get('role', None)
if role:
if not eqnset.has_terminal_obj(io_info.symbol):
continue
obj = eqnset.get_terminal_obj(io_info.symbol)
# Outputs:
if role == "TRANSMEMBRANECURRENT":
assert io_info.iotype== IOType.Output
currents[obj] = NeuronMembraneCurrent( obj=obj, symbol=obj.symbol)
# Inputs (Supplied Values):
elif role == "MEMBRANEVOLTAGE":
assert io_info.iotype== IOType.Input
supplied_values[obj] = NeuronSuppliedValues.MembraneVoltage
elif role == "TIME":
assert io_info.iotype== IOType.Input
supplied_values[obj] = NeuronSuppliedValues.Time
elif role == "TEMPERATURE":
assert io_info.iotype== IOType.Input
supplied_values[obj] = NeuronSuppliedValues.Temperature
else:
assert False
if not currents:
raise ValueError('Mechanism does not expose any currents! %s'% eqnset.name)
# PointProcess or Distributed Process:
mech_type = currents.values()[0].getCurrentType()
for c in currents.values():
assert mech_type == c.getCurrentType(), 'Mixed Current types [Distributed/Point]'
# Work out the units of all the terminal symbols:
symbol_units = {}
objs = eqnset.terminal_symbols
n = EqnsetVisitorNodeCollector()
n.visit(eqnset)
objs = n.all()
for s in objs:
if s in currents:
symbol_units[s] = NEURONMappings.current_units[mech_type]
elif s in supplied_values:
t = supplied_values[s]
if t in NeuronSuppliedValues.All:
symbol_units[s] = NEURONMappings.supplied_value_units[t] #NeuroUnitParser.Unit("mV")
else:
print 'Unknown supplied value:', t
assert False
else:
if isinstance(s,(EqnTimeDerivativeByRegime, EqnAssignmentByRegime, EqnSet, ConstValue)):
continue
if isinstance(s,(InEquality, OnEvent)):
continue
symbol_units[s] = s.get_dimension()
# Event Handling:
assert False, 'Deprecated, needs rewrite'
zero_arg_events = [ev for ev in eqnset.onevents if len(ev.parameters) == 0]
if len(zero_arg_events) == 0:
event_function = None
elif len(zero_arg_events) == 1:
event_function= zero_arg_events[0]
else:
raise ValueError('Multiple Zero-Param Events')
return MODLBuildParameters(mechanismtype=mech_type, currents=currents, supplied_values=supplied_values, suffix="nmmodl"+eqnset.name, symbol_units=symbol_units, event_function=event_function )
def InferFromEqnset(cls, eqnset):
currents = {}
supplied_values = {}
for io_info in [
io_info for io_info in eqnset.io_data
if io_info.iotype in (IOType.Output, IOType.Input)
]:
if not io_info.metadata or not 'mf' in io_info.metadata:
continue
role = io_info.metadata['mf'].get('role', None)
if role:
if not eqnset.has_terminal_obj(io_info.symbol):
continue
obj = eqnset.get_terminal_obj(io_info.symbol)
# Outputs:
if role == "TRANSMEMBRANECURRENT":
assert io_info.iotype == IOType.Output
currents[obj] = NeuronMembraneCurrent(obj=obj,
symbol=obj.symbol)
# Inputs (Supplied Values):
elif role == "MEMBRANEVOLTAGE":
assert io_info.iotype == IOType.Input
supplied_values[obj] = NeuronSuppliedValues.MembraneVoltage
elif role == "TIME":
assert io_info.iotype == IOType.Input
supplied_values[obj] = NeuronSuppliedValues.Time
elif role == "TEMPERATURE":
assert io_info.iotype == IOType.Input
supplied_values[obj] = NeuronSuppliedValues.Temperature
else:
assert False
if not currents:
raise ValueError('Mechanism does not expose any currents! %s' %
eqnset.name)
# PointProcess or Distributed Process:
mech_type = currents.values()[0].getCurrentType()
for c in currents.values():
assert mech_type == c.getCurrentType(
), 'Mixed Current types [Distributed/Point]'
# Work out the units of all the terminal symbols:
symbol_units = {}
objs = eqnset.terminal_symbols
n = EqnsetVisitorNodeCollector()
n.visit(eqnset)
objs = n.all()
for s in objs:
if s in currents:
symbol_units[s] = NEURONMappings.current_units[mech_type]
elif s in supplied_values:
t = supplied_values[s]
if t in NeuronSuppliedValues.All:
symbol_units[s] = NEURONMappings.supplied_value_units[
t] #NeuroUnitParser.Unit("mV")
else:
print 'Unknown supplied value:', t
assert False
else:
if isinstance(s, (EqnTimeDerivativeByRegime,
EqnAssignmentByRegime, EqnSet, ConstValue)):
continue
if isinstance(s, (InEquality, OnEvent)):
continue
symbol_units[s] = s.get_dimension()
# Event Handling:
assert False, 'Deprecated, needs rewrite'
zero_arg_events = [
ev for ev in eqnset.onevents if len(ev.parameters) == 0
]
if len(zero_arg_events) == 0:
event_function = None
elif len(zero_arg_events) == 1:
event_function = zero_arg_events[0]
else:
raise ValueError('Multiple Zero-Param Events')
return MODLBuildParameters(mechanismtype=mech_type,
currents=currents,
supplied_values=supplied_values,
suffix="nmmodl" + eqnset.name,
symbol_units=symbol_units,
event_function=event_function)
def _cache_nodes(self):
t = EqnsetVisitorNodeCollector()
t.visit(self)
self._parameters = t.nodes[Parameter]
self._supplied_values = t.nodes[SuppliedValue]
def all_ast_nodes(self):
from neurounits.visitors.common.terminal_node_collector import EqnsetVisitorNodeCollector
c = EqnsetVisitorNodeCollector()
c.visit(self)
return itertools.chain(*c.nodes.values())
def all_ast_nodes(self):
from neurounits.visitors.common.terminal_node_collector import EqnsetVisitorNodeCollector
c = EqnsetVisitorNodeCollector()
c.visit(self)
return itertools.chain( *c.nodes.values() )
