def _check_regulate_activity(self, stmt):
"""Check a RegulateActivity statement."""
logger.info('Checking stmt: %s' % stmt)
# FIXME Currently this will match rules with the corresponding monomer
# pattern from the Activation/Inhibition statement, which will nearly
# always have no state conditions on it. In future, this statement foo
# should also match rules in which 1) the agent is in its active form,
# or 2) the agent is tagged as the enzyme in a rule of the appropriate
# activity (e.g., a phosphorylation rule) FIXME
subj_mp = pa.get_monomer_pattern(self.model, stmt.subj)
target_polarity = 1 if stmt.is_activation else -1
# This may fail, since there may be no rule in the model activating the
# object, and the object may not have an "active" site of the
# appropriate type
obj_obs_name = pa.get_agent_rule_str(stmt.obj) + '_obs'
try:
obj_site_pattern = pa.get_site_pattern(stmt.obj)
obj_site_pattern.update({stmt.obj_activity: 'active'})
obj_monomer = self.model.monomers[stmt.obj.name]
obj_mp = obj_monomer(**obj_site_pattern)
except Exception as e:
logger.info("Could not create obj monomer pattern: %s" % e)
return False
obj_obs = Observable(obj_obs_name, obj_mp, _export=False)
return self._find_im_paths(subj_mp, obj_obs, target_polarity)
def _check_regulate_activity(self, stmt):
"""Check a RegulateActivity statement."""
logger.info('Checking stmt: %s' % stmt)
# FIXME Currently this will match rules with the corresponding monomer
# pattern from the Activation/Inhibition statement, which will nearly
# always have no state conditions on it. In future, this statement foo
# should also match rules in which 1) the agent is in its active form,
# or 2) the agent is tagged as the enzyme in a rule of the appropriate
# activity (e.g., a phosphorylation rule) FIXME
subj_mp = pa.get_monomer_pattern(self.model, stmt.subj)
target_polarity = 1 if stmt.is_activation else -1
# This may fail, since there may be no rule in the model activating the
# object, and the object may not have an "active" site of the
# appropriate type
obj_obs_name = pa.get_agent_rule_str(stmt.obj) + '_obs'
try:
obj_site_pattern = pa.get_site_pattern(stmt.obj)
obj_site_pattern.update({stmt.obj_activity: 'active'})
obj_monomer = self.model.monomers[stmt.obj.name]
obj_mp = obj_monomer(**obj_site_pattern)
except Exception as e:
logger.info("Could not create obj monomer pattern: %s" % e)
return False
obj_obs = Observable(obj_obs_name, obj_mp, _export=False)
return self._find_im_paths(subj_mp, obj_obs, target_polarity)
def _check_regulate_amount(self, stmt, max_paths, max_path_length):
"""Check a RegulateAmount statement."""
logger.info('Checking stmt: %s' % stmt)
subj_mp = pa.get_monomer_pattern(self.model, stmt.subj)
target_polarity = 1 if isinstance(stmt, IncreaseAmount) else -1
obs_names = self.stmt_to_obs[stmt]
for obs_name in obs_names:
return self._find_im_paths(subj_mp, obs_name, target_polarity,
max_paths, max_path_length)
def _check_regulate_activity(self, stmt, max_paths, max_path_length):
"""Check a RegulateActivity statement."""
logger.info('Checking stmt: %s' % stmt)
# FIXME Currently this will match rules with the corresponding monomer
# pattern from the Activation/Inhibition statement, which will nearly
# always have no state conditions on it. In future, this statement foo
# should also match rules in which 1) the agent is in its active form,
# or 2) the agent is tagged as the enzyme in a rule of the appropriate
# activity (e.g., a phosphorylation rule) FIXME
subj_mp = pa.get_monomer_pattern(self.model, stmt.subj)
target_polarity = 1 if stmt.is_activation else -1
# This may fail, since there may be no rule in the model activating the
# object, and the object may not have an "active" site of the
# appropriate type
obs_names = self.stmt_to_obs[stmt]
for obs_name in obs_names:
return self._find_im_paths(subj_mp, obs_name, target_polarity,
max_paths, max_path_length)
