def decode_complex_pattern(self, cp):
cp_obj = ComplexPattern(
[self.decode_monomer_pattern(mp) for mp in cp['monomer_patterns']],
self._modelget(cp['compartment']),
cp['match_once']
)
cp_obj._tag = self._modelget(cp['tag'])
return cp_obj
def _parse_initials(self):
for i in self._x.iterfind(_ns('{0}ListOfSpecies/{0}Species')):
value_param = i.get('concentration')
try:
value = float(value_param)
# Need to create a new parameter for the initial conc. literal
name = re.sub('[^\w]+', '_',
i.get('name').replace(')', '').replace(
'(', '')) + '_0'
try:
value_param = self.parameter(name, value)
except ValueError as ve:
raise BnglImportError(str(ve))
except ValueError:
# Retrieve existing parameter or (constant) expression
try:
value_param = self.model.parameters[i.get('concentration')]
except KeyError:
value_param = self.model.expressions[i.get(
'concentration')]
mon_pats = self._parse_species(i)
species_cpt = self.model.compartments.get(i.get('compartment'))
cp = ComplexPattern(mon_pats, species_cpt)
fixed = i.get('Fixed') == "1"
self.initial(cp, value_param, fixed)
def _parse_initials(self):
for i in self._x.iterfind(_ns('{0}ListOfSpecies/{0}Species')):
if i.get('Fixed') is not None and i.get('Fixed') == "1":
self._warn_or_except('Species %s is fixed, but will be '
'treated as an ordinary species in '
'PySB.' % i.get('name'))
value_param = i.get('concentration')
try:
value = float(value_param)
# Need to create a new parameter for the initial conc. literal
name = re.sub('[^\w]+', '_',
i.get('name').replace(')', '').replace(
'(', '')) + '_0'
try:
value_param = self.parameter(name, value)
except ValueError as ve:
raise BnglImportError(str(ve))
except ValueError:
# Retrieve existing parameter or (constant) expression
try:
value_param = self.model.parameters[i.get('concentration')]
except KeyError:
value_param = self.model.expressions[i.get(
'concentration')]
mon_pats = self._parse_species(i)
species_cpt = self.model.compartments.get(i.get('compartment'))
self.initial(ComplexPattern(mon_pats, species_cpt), value_param)
def _parse_observables(self):
for o in self._x.iterfind(_ns('{0}ListOfObservables/{0}Observable')):
o_name = o.get('name')
cplx_pats = []
for mp in o.iterfind(_ns('{0}ListOfPatterns/{0}Pattern')):
match_once = mp.get('matchOnce')
match_once = True if match_once == "1" else False
cplx_pats.append(
ComplexPattern(self._parse_species(mp),
compartment=None,
match_once=match_once))
self.observable(o_name,
ReactionPattern(cplx_pats),
match=o.get('type').lower())
def _parse_observables(self):
for o in self._x.iterfind(_ns('{0}ListOfObservables/{0}Observable')):
o_name = o.get('name')
match_mode = o.get('type').lower()
# Some BNG observables have same name as a monomer, but in PySB
# these must be unique
if o_name in self.model.monomers.keys():
o_name = 'Obs_{}'.format(o_name)
cplx_pats = []
for mp in o.iterfind(_ns('{0}ListOfPatterns/{0}Pattern')):
cpt = self.model.compartments.get(mp.get('compartment'))
match_once = mp.get('matchOnce')
match_once = True if match_once == "1" and \
match_mode != 'species' else False
cplx_pats.append(
ComplexPattern(self._parse_species(mp),
compartment=cpt,
match_once=match_once))
self.observable(o_name,
ReactionPattern(cplx_pats),
match=match_mode)
def _parse_rules(self):
# Store reversible rates for post-processing (we don't know if we'll
# encounter fwd or rev rule first)
rev_rates = {}
for r in self._x.iterfind(
_ns('{0}ListOfReactionRules/'
'{0}ReactionRule')):
r_name = r.get('name')
r_rate_xml = r.find(_ns('{}RateLaw'))
if r_rate_xml is None:
raise BnglImportError('Rate law missing for rule %s' % r_name)
r_rate = self._parse_rate_law(r_rate_xml)
# Store reverse rates for post-processing
if r_name.startswith('_reverse_'):
r_name = r_name[9:]
rev_rates[r_name] = r_rate
continue
# Compile reactant and product patterns
reactant_pats = []
for rp in r.iterfind(
_ns('{0}ListOfReactantPatterns/'
'{0}ReactantPattern')):
cpt = self.model.compartments.get(rp.get('compartment'))
reactant_pats.append(
ComplexPattern(self._parse_species(rp), cpt))
if 'label' in rp.attrib:
reactant_pats[-1]._tag = self.model.tags[rp.get('label')]
product_pats = []
for pp in r.iterfind(
_ns('{0}ListOfProductPatterns/'
'{0}ProductPattern')):
cpt = self.model.compartments.get(pp.get('compartment'))
product_pats.append(
ComplexPattern(self._parse_species(pp), cpt))
if 'label' in pp.attrib:
product_pats[-1]._tag = self.model.tags[pp.get('label')]
rule_exp = RuleExpression(ReactionPattern(reactant_pats),
ReactionPattern(product_pats),
is_reversible=False)
# Process any DeleteMolecules declaration
delete_molecules = False
for del_operations in r.iterfind(
_ns('{0}ListOfOperations/'
'{0}Delete')):
if del_operations.get('DeleteMolecules') == "1":
delete_molecules = True
break
# Process any MoveConnected declaration
move_connected = False
for change_cpt_ops in r.iterfind(
_ns('{0}ListOfOperations/'
'{0}ChangeCompartment')):
if change_cpt_ops.get('moveConnected') == "1":
move_connected = True
break
# Give warning/error if ListOfExcludeReactants or
# ListOfExcludeProducts is present
if r.find(_ns('{}ListOfExcludeReactants')) is not None or \
r.find(_ns('{}ListOfExcludeProducts')) is not None:
self._warn_or_except(
'ListOfExcludeReactants and/or '
'ListOfExcludeProducts declarations '
'are deprecated in BNG, and not supported '
'in PySB.')
# Give warning/error if ListOfIncludeReactants or
# ListOfIncludeProducts is present
if r.find(_ns('{}ListOfIncludeReactants')) is not None or \
r.find(_ns('{}ListOfIncludeProducts')) is not None:
self._warn_or_except(
'ListOfIncludeReactants and/or '
'ListOfIncludeProducts declarations '
'are deprecated in BNG, and not supported '
'in PySB.')
self.rule(r_name,
rule_exp,
r_rate,
delete_molecules=delete_molecules,
move_connected=move_connected)
# Set the reverse rates
for r_name, rev_rate in rev_rates.items():
rule = self.model.rules[r_name]
rule.rule_expression.is_reversible = True
rule.is_reversible = True
rule.rate_reverse = rev_rate
def _parse_rules(self):
# Store reversible rates for post-processing (we don't know if we'll
# encounter fwd or rev rule first)
rev_rates = {}
for r in self._x.iterfind(
_ns('{0}ListOfReactionRules/'
'{0}ReactionRule')):
r_name = r.get('name')
r_rate_xml = r.find(_ns('{}RateLaw'))
if r_rate_xml is None:
raise BnglImportError('Rate law missing for rule %s' % r_name)
r_rate = self._parse_rate_law(r_rate_xml)
# Store reverse rates for post-processing
if r_name.startswith('_reverse_'):
r_name = r_name[9:]
rev_rates[r_name] = r_rate
continue
# Compile reactant and product patterns
reactant_pats = []
for rp in r.iterfind(
_ns('{0}ListOfReactantPatterns/'
'{0}ReactantPattern')):
cpt = self.model.compartments.get(rp.get('compartment'))
reactant_pats.append(
ComplexPattern(self._parse_species(rp), cpt))
product_pats = []
for pp in r.iterfind(
_ns('{0}ListOfProductPatterns/'
'{0}ProductPattern')):
cpt = self.model.compartments.get(pp.get('compartment'))
product_pats.append(
ComplexPattern(self._parse_species(pp), cpt))
rule_exp = RuleExpression(ReactionPattern(reactant_pats),
ReactionPattern(product_pats),
is_reversible=False)
# Process any DeleteMolecules declaration
delete_molecules = False
for del_operations in r.iterfind(
_ns('{0}ListOfOperations/'
'{0}Delete')):
if del_operations.get('DeleteMolecules') == "1":
delete_molecules = True
break
# Give warning/error if ListOfExcludeReactants or
# ListOfExcludeProducts is present
if r.find(_ns('{}ListOfExcludeReactants')) is not None or \
r.find(_ns('{}ListOfExcludeProducts')) is not None:
self._warn_or_except('ListOfExcludeReactants and/or '
'ListOfExcludeProducts declarations will '
'be ignored. This may lead to long '
'network generation times.')
# Give warning/error if ListOfIncludeReactants or
# ListOfIncludeProducts is present
if r.find(_ns('{}ListOfIncludeReactants')) is not None or \
r.find(_ns('{}ListOfIncludeProducts')) is not None:
self._warn_or_except('ListOfIncludeReactants and/or '
'ListOfIncludeProducts declarations will '
'be ignored. This may lead to long '
'network generation times.')
self.rule(r_name,
rule_exp,
r_rate,
delete_molecules=delete_molecules)
# Set the reverse rates
for r_name, rev_rate in rev_rates.items():
rule = self.model.rules[r_name]
rule.rule_expression.is_reversible = True
rule.is_reversible = True
rule.rate_reverse = rev_rate
