Merge pull request #314 from gyorilab/scenario5

Scenario5

mira/metamodel/templates.py

@@ -30,12 +30,15 @@
  "has_subject",
  "has_outcome",
  "has_controller",
- "num_controllers"
+ "num_controllers",
+ "get_binding_templates",
+ "conversion_to_deg_prod",
 ]
 
 import logging
 import sys
 from collections import ChainMap
+from copy import deepcopy
 from itertools import product
 from typing import (
  Callable,
@@ -1824,3 +1827,54 @@ def num_controllers(template):
  return len(template.controllers)
  else:
  return 0
+
+
+def get_binding_templates(a, b, c, kf, kr):
+ """Return a list of templates emulating a reversible binding process."""
+ af = lambda: Concept(name=a)
+ bf = lambda: Concept(name=b)
+ cf = lambda: Concept(name=c)
+ templates = [
+ GroupedControlledProduction(controllers=[af(), bf()],
+ outcome=cf()).with_mass_action_rate_law(kf),
+ ControlledDegradation(controller=af(),
+ subject=bf()).with_mass_action_rate_law(kf),
+ ControlledDegradation(controller=bf(),
+ subject=af()).with_mass_action_rate_law(kf),
+ NaturalDegradation(subject=cf()).with_mass_action_rate_law(kr),
+ ControlledProduction(controller=cf(),
+ outcome=af()).with_mass_action_rate_law(kr),
+ ControlledProduction(controller=cf(),
+ outcome=bf()).with_mass_action_rate_law(kr)
+ ]
+ return templates
+
+
+def conversion_to_deg_prod(conv_template):
+ """Given a conversion template, compile into degradation/production templates."""
+ if not is_conversion(conv_template):
+ return [conv_template]
+ nc = num_controllers(conv_template)
+ if nc == 0:
+ tdeg = NaturalDegradation(subject=conv_template.subject,
+ rate_law=conv_template.rate_law)
+ tprod = ControlledProduction(outcome=conv_template.outcome,
+ controller=conv_template.subject,
+ rate_law=conv_template.rate_law)
+ elif nc == 1:
+ tdeg = ControlledDegradation(subject=conv_template.subject,
+ controller=conv_template.controller,
+ rate_law=conv_template.rate_law)
+ tprod = GroupedControlledProduction(outcome=conv_template.outcome,
+ controllers=[conv_template.controller,
+ conv_template.subject],
+ rate_law=conv_template.rate_law)
+ else:
+ tdeg = GroupedControlledDegradation(subject=conv_template.subject,
+ controllers=conv_template.controllers,
+ rate_law=conv_template.rate_law)
+ tprod = GroupedControlledProduction(outcome=conv_template.outcome,
+ controllers=conv_template.controllers +
+ [conv_template.subject],
+ rate_law=conv_template.rate_law)
+ return deepcopy([tdeg, tprod])

mira/modeling/__init__.py

@@ -252,9 +252,10 @@ def make_model(self):
  ModelParameter(key, display_name=display_name, description=description,
  distribution=distribution,
  value=value,
+ concept=self.template_model.parameters[key],
  placeholder=False))
 
- for template in self.template_model.templates:
+ for idx, template in enumerate(self.template_model.templates):
  if isinstance(template, StaticConcept):
  self.assemble_variable(template.subject,
  self.template_model.initials)
@@ -308,7 +309,7 @@ def make_model(self):
  produced, produced_key = tuple(), None
 
  tkey_elements = tuple(
- element for element in [consumed_key, produced_key, control_key]
+ element for element in [consumed_key, produced_key, control_key, str(idx)]
  if element is not None
  )
  tkey = get_transition_key(tkey_elements, template.type)
@@ -334,6 +335,7 @@ def make_model(self):
  ModelParameter(key, display_name=display_name, description=description,
  distribution=distribution,
  value=value,
+ concept=self.template_model.parameters[key],
  placeholder=False))
 
  def get_create_parameter(self, parameter: ModelParameter) -> ModelParameter:

mira/modeling/amr/regnet.py

@@ -9,6 +9,7 @@
 import json
 import logging
 from copy import deepcopy
+from collections import defaultdict
 from typing import Dict, List, Optional, Union
 
 import sympy
@@ -84,6 +85,9 @@ def __init__(self, model: Model):
  self._states_by_id[name] = state_data
 
  idx = 0
+ # It's possible that something is naturally degraded/replicated
+ # by multiple transitions so we need to collect and aggregate rates
+ intrinsic_by_var = defaultdict(list)
  for transition in model.transitions.values():
  # Regnets cannot represent conversions (only
  # production/degradation) so we skip these
@@ -122,11 +126,7 @@ def __init__(self, model: Model):
 
  if transition.template.rate_law:
  rate_law = transition.template.rate_law.args[0]
- self.rates.append({
- 'target': var,
- 'expression': str(rate_law),
- 'expression_mathml': expression_to_mathml(rate_law)
- })
+ intrinsic_by_var[var].append(rate_law)
  # Beyond these, we can assume that the transition is a
  # form of replication or degradation corresponding to
  # a regular transition in the regnet framework
@@ -174,6 +174,14 @@ def __init__(self, model: Model):
  self.transitions.append(transition_dict)
  idx += 1
 
+ for var, rates in intrinsic_by_var.items():
+ rate_law = sum(rates)
+ self.rates.append({
+ 'target': var,
+ 'expression': str(rate_law),
+ 'expression_mathml': expression_to_mathml(rate_law)
+ })
+
  for key, param in model.parameters.items():
  if param.placeholder:
  continue