Added ability to extract new parameters from transition rate laws thr…

…ough explicit argument definition or implicitly and modified unit tests

mira/modeling/askenet/ops.py

@@ -3,7 +3,7 @@
 from sympy import sstr
 from mira.metamodel import SympyExprStr, Unit
 import mira.metamodel.ops as tmops
-from mira.sources.askenet.petrinet import template_model_from_askenet_json, state_to_concept, get_sympy
+from mira.sources.askenet.petrinet import template_model_from_askenet_json
 from .petrinet import template_model_to_petrinet_json
 from mira.metamodel.io import mathml_to_expression
 from mira.metamodel.template_model import Parameter, Distribution, Observable, \
@@ -149,6 +149,32 @@ def add_parameter(tm, parameter_id: str,
  return tm
 
 
+def add_parameter_no_wrapper(tm, parameter_id: str,
+ name: str = None,
+ value: float = None,
+ distribution=None,
+ units_mathml: str = None):
+ distribution = Distribution(**distribution) if distribution else None
+ if units_mathml:
+ units = {
+ 'expression': mathml_to_expression(units_mathml),
+ 'expression_mathml': units_mathml
+ }
+ else:
+ units = None
+
+ data = {
+ 'name': parameter_id,
+ 'display_name': name if name else parameter_id,
+ 'value': value,
+ 'distribution': distribution,
+ 'units': units
+ }
+
+ parameter = Parameter(**data)
+ tm.parameters[parameter_id] = parameter
+
+
 @amr_to_mira
 def replace_initial_id(tm, old_id, new_id):
  """Replace the ID of an initial."""
@@ -193,14 +219,14 @@ def add_state(tm, state_id: str, value: float, name: str = None, units_mathml: s
  else:
  units = None
 
- new_concept_new = Concept(name=state_id,
-  display_name=name,
-  identifiers=grounding,
-  units=units,
-  context=context)
- new_state = Initial(concept=new_concept_new, value=value)
+ new_concept = Concept(name=state_id,
+ display_name=name,
+ identifiers=grounding,
+ units=units,
+ context=context)
+ new_state = Initial(concept=new_concept, value=value)
  tm.initials[state_id] = new_state
- static_template = StaticConcept(subject=new_concept_new)
+ static_template = StaticConcept(subject=new_concept)
  tm.templates.append(static_template)
  return tm
 
@@ -214,20 +240,12 @@ def remove_transition(tm, transition_id):
 
 @amr_to_mira
 def add_transition(tm, new_transition_id, src_id=None, tgt_id=None,
- rate_law_mathml=None):
- # TODO: handle parameters added in the rate law as follows
- # option 1 take in optional parameters dict if rate law contains parameters
- # that aren't already present
- # option 2, reverse engineer rate law and find parameters and states within
- # the rate law and add to model
-
- # each transition has inputs such as subjects and controllers and those appear in rate laws as states
- # look at sympy expression and get free symbols, take out ones that represent the inputs and controllers (states)
- # whatever remains are parameters for models
+ rate_law_mathml=None, params_dict: dict = None):
  if src_id is None and tgt_id is None:
  ValueError("You must pass in at least one of source and target id")
  rate_law_sympy = SympyExprStr(mathml_to_expression(rate_law_mathml)) \
  if rate_law_mathml else None
+
  if src_id is None and tgt_id:
  template = NaturalProduction(name=new_transition_id, outcome=tgt_id,
  rate_law=rate_law_sympy)
@@ -237,6 +255,59 @@ def add_transition(tm, new_transition_id, src_id=None, tgt_id=None,
  else:
  template = NaturalConversion(name=new_transition_id, subject=src_id,
  outcome=tgt_id, rate_law=rate_law_sympy)
+ if params_dict:
+ # add parameters to template model
+ for free_symbol_sympy in template.rate_law.free_symbols:
+ free_symbol_str = sstr(free_symbol_sympy)
+ if free_symbol_str in params_dict:
+ # free_symbol_str = sstr(free_symbol_sympy)
+ # distribution = Distribution(**params_dict[free_symbol_str]['distribution']) if \
+ # 'distribution' in params_dict[free_symbol_str] else None
+ #
+ # if 'units' in params_dict[free_symbol_str]:
+ # units = {
+ # 'expression': mathml_to_expression(params_dict[free_symbol_str]['units']),
+ # 'expression_mathml': params_dict[free_symbol_str]['units']
+ # }
+ # else:
+ # units = None
+ #
+ # data = {
+ # 'name': free_symbol_str,
+ # 'display_name': params_dict[free_symbol_str]['display_name'] if 'display_name' in params_dict[
+ # free_symbol_str] else free_symbol_str,
+ # 'value': params_dict[free_symbol_str]['value'] if 'value' in params_dict[free_symbol_str] else None,
+ # 'distribution': distribution,
+ # 'units': units
+ # }
+ #
+ # parameter = Parameter(**data)
+ # tm.parameters[free_symbol_str] = parameter
+ name = params_dict[free_symbol_str]['display_name'] if 'display_name' in params_dict[
+ free_symbol_str] else None
+ value = params_dict[free_symbol_str]['value'] if 'value' in params_dict[free_symbol_str] else None
+ units = params_dict[free_symbol_str]['units'] if 'units' in params_dict[free_symbol_str] else None
+ distribution = params_dict[free_symbol_str]['distribution'] if 'distribution' in params_dict[
+ free_symbol_str] else None
+ add_parameter_no_wrapper(tm, free_symbol_str, name=name,
+ value=value,
+ units_mathml=units,
+ distribution=distribution)
+ # If there are no explicitly defined parameters
+ # Extract new parameters from rate laws without any other information about that parameter
+ else:
+ free_symbol_str = {sstr(symbol) for symbol in template.rate_law.free_symbols}
+
+ if not isinstance(template, NaturalProduction):
+ if template.subject.name in free_symbol_str:
+ free_symbol_str.remove(template.subject.name)
+
+ for param in tm.parameters.keys():
+ if param in free_symbol_str:
+ free_symbol_str.remove(param)
+
+ for new_param in free_symbol_str:
+ add_parameter_no_wrapper(tm, new_param)
  tm.templates.append(template)
  return tm