def test_pysb_preassembler_replace_activities2():
a_act = Agent('a', activity=ActivityCondition('activity', True))
st = Activation(a_act, Agent('b'))
st2 = Activation(Agent('c'), Agent('a'))
ppa = PysbPreassembler([st, st2])
ppa.replace_activities()
assert(len(ppa.statements) == 2)
def test_pysb_preassembler_replace_activities1():
st1 = ActiveForm(Agent('a', location='nucleus'), 'activity', True)
st2 = Phosphorylation(
Agent('a', activity=ActivityCondition('activity', True)), Agent('b'))
ppa = PysbPreassembler([st1, st2])
ppa.replace_activities()
assert (len(ppa.statements) == 2)
assert (ppa.statements[1].enz.location == 'nucleus')
def test_pysb_preassembler_replace_activities3():
p = Agent('PPP2CA')
bc = BoundCondition(p, False)
erk = Agent('ERK')
mek1 = Agent('MEK', mods=[ModCondition('phosphorylation',
None, None, True)])
mek2 = Agent('MEK', activity=ActivityCondition('activity', True),
bound_conditions=[bc])
st2 = ActiveForm(mek1, 'activity', True)
st1 = Phosphorylation(mek2, erk)
ppa = PysbPreassembler([st1, st2])
ppa.replace_activities()
assert(len(ppa.statements) == 2)
assert(ppa.statements[0].enz.mods)
assert(ppa.statements[0].enz.bound_conditions)
def make_model(self):
"""Assemble the SBGN model from the collected INDRA Statements.
This method assembles an SBGN model from the set of INDRA Statements.
The assembled model is set as the assembler's sbgn attribute (it is
represented as an XML ElementTree internally). The model is returned
as a serialized XML string.
Returns
-------
sbgn_str : str
The XML serialized SBGN model.
"""
ppa = PysbPreassembler(self.statements)
ppa.replace_activities()
self.statements = ppa.statements
self.sbgn = emaker.sbgn()
self._map = emaker.map()
self.sbgn.append(self._map)
for stmt in self.statements:
if isinstance(stmt, Modification):
self._assemble_modification(stmt)
elif isinstance(stmt, RegulateActivity):
self._assemble_regulateactivity(stmt)
elif isinstance(stmt, RegulateAmount):
self._assemble_regulateamount(stmt)
elif isinstance(stmt, Complex):
self._assemble_complex(stmt)
elif isinstance(stmt, ActiveForm):
#self._assemble_activeform(stmt)
pass
else:
logger.warning("Unhandled Statement type %s" % type(stmt))
continue
sbgn_str = self.print_model()
return sbgn_str
def make_model(self,
policies=None,
initial_conditions=True,
reverse_effects=False):
"""Assemble the Kami model from the collected INDRA Statements.
This method assembles a Kami model from the set of INDRA Statements.
The assembled model is both returned and set as the assembler's
model argument.
Parameters
----------
policies : Optional[Union[str, dict]]
A string or dictionary of policies, as defined in
:py:class:`indra.assemblers.KamiAssembler`. This set of policies
locally supersedes the default setting in the assembler. This
is useful when this function is called multiple times with
different policies.
initial_conditions : Optional[bool]
If True, default initial conditions are generated for the
agents in the model.
Returns
-------
model : dict
The assembled Kami model.
"""
ppa = PysbPreassembler(self.statements)
ppa.replace_activities()
if reverse_effects:
ppa.add_reverse_effects()
self.statements = ppa.statements
# Set local policies for this make_model call that overwrite
# the global policies of the Kami assembler
if policies is not None:
global_policies = self.policies
if isinstance(policies, basestring):
local_policies = {'other': policies}
else:
local_policies = {'other': 'default'}
local_policies.update(policies)
self.policies = local_policies
self.model = {}
graphs = []
self.model['graphs'] = graphs
self.model['typing'] = []
# Action graph generated here
action_graph = {
'id': 'action_graph',
'attrs': {
'name': 'action_graph'
}
}
action_graph['graph'] = {'nodes': [], 'edges': []}
graphs.append(action_graph)
# Iterate over the statements to generate rules
self._assemble()
# Add initial conditions
#if initial_conditions:
# self.add_default_initial_conditions()
# If local policies were applied, revert to the global one
if policies is not None:
self.policies = global_policies
return self.model