updating for wc_lang.ChemicalStructure

KarrLab · Apr 2, 2019 · 9c7dbdc · 9c7dbdc
1 parent 6b1a9f3
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diff --git a/.circleci/requirements.txt b/.circleci/requirements.txt
@@ -2,6 +2,7 @@
 git+https://github.com/KarrLab/log.git#egg=log
 
 # Karr Lab
+git+https://github.com/KarrLab/bpforms.git#egg=bpforms
 git+https://github.com/KarrLab/wc_onto.git#egg=wc_onto
 git+https://github.com/KarrLab/wc_utils.git#egg=wc_utils
 git+https://github.com/KarrLab/obj_model.git#egg=obj_model

diff --git a/examples/transcription_translation_hybrid_model/model.xlsx b/examples/transcription_translation_hybrid_model/model.xlsx
diff --git a/examples/translation_metabolism_hybrid_model/model.xlsx b/examples/translation_metabolism_hybrid_model/model.xlsx
diff --git a/tests/log/test_checkpoint.py b/tests/log/test_checkpoint.py
@@ -167,8 +167,9 @@ def build_mock_model():
     compartment_c = model.compartments.create(id='c', init_volume=init_volume)
     compartment_e = model.compartments.create(id='e', init_volume=init_volume)
 
-    species_type_L = model.species_types.create(id='L', molecular_weight=10)
-    species_type_R = model.species_types.create(id='R', molecular_weight=10)
+    structure = wc_lang.ChemicalStructure(molecular_weight=10.)
+    species_type_L = model.species_types.create(id='L', structure=structure)
+    species_type_R = model.species_types.create(id='R', structure=structure)
 
     species_L = wc_lang.Species(id='L[c]', species_type=species_type_L, compartment=compartment_c)
     species_R = wc_lang.Species(id='R[c]', species_type=species_type_R, compartment=compartment_c)

diff --git a/tests/multialgorithm/fixtures/2_species_1_reaction.xlsx b/tests/multialgorithm/fixtures/2_species_1_reaction.xlsx
diff --git a/...multialgorithm/fixtures/2_species_1_reaction_with_rates_given_by_reactant_population.xlsx b/...multialgorithm/fixtures/2_species_1_reaction_with_rates_given_by_reactant_population.xlsx
diff --git a/...ixtures/2_species_a_pair_of_symmetrical_reactions_rates_given_by_reactant_population.xlsx b/...ixtures/2_species_a_pair_of_symmetrical_reactions_rates_given_by_reactant_population.xlsx
diff --git a/tests/multialgorithm/fixtures/MetabolismAndGeneExpression.xlsx b/tests/multialgorithm/fixtures/MetabolismAndGeneExpression.xlsx
diff --git a/tests/multialgorithm/fixtures/test_dry_model.xlsx b/tests/multialgorithm/fixtures/test_dry_model.xlsx
diff --git a/tests/multialgorithm/fixtures/test_dry_model_with_mass_computation.xlsx b/tests/multialgorithm/fixtures/test_dry_model_with_mass_computation.xlsx
diff --git a/tests/multialgorithm/fixtures/test_model.xlsx b/tests/multialgorithm/fixtures/test_model.xlsx
diff --git a/tests/multialgorithm/fixtures/test_model_for_access_species_populations.xlsx b/tests/multialgorithm/fixtures/test_model_for_access_species_populations.xlsx
diff --git a/tests/multialgorithm/fixtures/test_model_for_access_species_populations_steady_state.xlsx b/tests/multialgorithm/fixtures/test_model_for_access_species_populations_steady_state.xlsx
diff --git a/tests/multialgorithm/fixtures/test_model_with_mass_computation.xlsx b/tests/multialgorithm/fixtures/test_model_with_mass_computation.xlsx
diff --git a/tests/multialgorithm/fixtures/test_new_features_model.xlsx b/tests/multialgorithm/fixtures/test_new_features_model.xlsx
diff --git a/tests/multialgorithm/submodels/fixtures/test_submodel.xlsx b/tests/multialgorithm/submodels/fixtures/test_submodel.xlsx
diff --git a/tests/multialgorithm/submodels/fixtures/test_submodel_no_shared_species.xlsx b/tests/multialgorithm/submodels/fixtures/test_submodel_no_shared_species.xlsx
diff --git a/tests/multialgorithm/test_dynamic_mass.py b/tests/multialgorithm/test_dynamic_mass.py
@@ -49,8 +49,8 @@ def gen_model(self):
         model = model = wc_lang.Model(id='model', version='0.0.1', wc_lang_version='0.0.1')
 
         # compartments and species
-        st_constant = model.species_types.create(id='st_constant', charge=0., molecular_weight=1.)
-        st_dynamic = model.species_types.create(id='st_dynamic', charge=0., molecular_weight=0.)
+        st_constant = model.species_types.create(id='st_constant', structure=wc_lang.ChemicalStructure(charge=0., molecular_weight=1.))
+        st_dynamic = model.species_types.create(id='st_dynamic', structure=wc_lang.ChemicalStructure(charge=0., molecular_weight=0.))
         comp = model.compartments.create(id='comp', init_volume=wc_lang.InitVolume(std=0.))
         spec_constant = model.species.create(species_type=st_constant, compartment=comp)
         spec_dynamic = model.species.create(species_type=st_dynamic, compartment=comp)
@@ -178,12 +178,12 @@ def test_exponentially_increase_to_steady_state_count_with_constant_mass(self):
 
         # set quantitative values
         comp.init_volume.mean = 100e-15
-        st_constant.molecular_weight = 1.
-        st_dynamic.molecular_weight = 0.
+        st_constant.structure.molecular_weight = 1.
+        st_dynamic.structure.molecular_weight = 0.
         spec_constant.distribution_init_concentration.mean = 1e6
         spec_dynamic.distribution_init_concentration.mean = 10.
-        init_mass = (spec_constant.distribution_init_concentration.mean * st_constant.molecular_weight +
-                     spec_dynamic.distribution_init_concentration.mean * st_dynamic.molecular_weight
+        init_mass = (spec_constant.distribution_init_concentration.mean * st_constant.structure.molecular_weight +
+                     spec_dynamic.distribution_init_concentration.mean * st_dynamic.structure.molecular_weight
                      ) / scipy.constants.Avogadro
         init_density = density.value = init_mass / comp.init_volume.mean
         model.parameters.get_one(id='k_syn_dynamic').value = 1.
@@ -195,7 +195,7 @@ def test_exponentially_increase_to_steady_state_count_with_constant_mass(self):
         # verify results
         numpy.testing.assert_equal(pop_constant, numpy.full((201,), spec_constant.distribution_init_concentration.mean))
         numpy.testing.assert_equal(comp_mass, numpy.full((201,), spec_constant.distribution_init_concentration.mean
-                                                         * st_constant.molecular_weight
+                                                         * st_constant.structure.molecular_weight
                                                          / scipy.constants.Avogadro))
         self.assertEqual(density.value, init_density)
 
@@ -215,12 +215,12 @@ def test_exponentially_increase_to_steady_state_count_and_mass(self):
 
         # set quantitative values
         comp.init_volume.mean = 100e-15
-        st_constant.molecular_weight = 0.
-        st_dynamic.molecular_weight = 1.
+        st_constant.structure.molecular_weight = 0.
+        st_dynamic.structure.molecular_weight = 1.
         spec_constant.distribution_init_concentration.mean = 0.
         spec_dynamic.distribution_init_concentration.mean = 10.
-        init_mass = (spec_constant.distribution_init_concentration.mean * st_constant.molecular_weight +
-                     spec_dynamic.distribution_init_concentration.mean * st_dynamic.molecular_weight
+        init_mass = (spec_constant.distribution_init_concentration.mean * st_constant.structure.molecular_weight +
+                     spec_dynamic.distribution_init_concentration.mean * st_dynamic.structure.molecular_weight
                      ) / scipy.constants.Avogadro
         init_density = density.value = init_mass / comp.init_volume.mean
         model.parameters.get_one(id='k_syn_dynamic').value = 5.
@@ -239,8 +239,8 @@ def test_exponentially_increase_to_steady_state_count_and_mass(self):
         self.assertGreater(numpy.mean(pop_dynamic[101:]), spec_dynamic_ss - 3 * std_spec_dynamic_ss)
         self.assertLess(numpy.mean(pop_dynamic[101:]), spec_dynamic_ss + 3 * std_spec_dynamic_ss)
 
-        mass_ss = spec_dynamic_ss * st_dynamic.molecular_weight / scipy.constants.Avogadro
-        std_mass_ss = std_spec_dynamic_ss * st_dynamic.molecular_weight / scipy.constants.Avogadro
+        mass_ss = spec_dynamic_ss * st_dynamic.structure.molecular_weight / scipy.constants.Avogadro
+        std_mass_ss = std_spec_dynamic_ss * st_dynamic.structure.molecular_weight / scipy.constants.Avogadro
         self.assertGreater(numpy.mean(comp_mass[101:]), mass_ss - 3 * std_mass_ss)
         self.assertLess(numpy.mean(comp_mass[101:]), mass_ss + 3 * std_mass_ss)
 
@@ -255,12 +255,12 @@ def test_exponentially_descend_to_steady_state_count_and_mass(self):
 
         # set quantitative values
         comp.init_volume.mean = 100e-15
-        st_constant.molecular_weight = 0.
-        st_dynamic.molecular_weight = 1.
+        st_constant.structure.molecular_weight = 0.
+        st_dynamic.structure.molecular_weight = 1.
         spec_constant.distribution_init_concentration.mean = 0.
         spec_dynamic.distribution_init_concentration.mean = 100.
-        init_mass = (spec_constant.distribution_init_concentration.mean * st_constant.molecular_weight +
-                     spec_dynamic.distribution_init_concentration.mean * st_dynamic.molecular_weight
+        init_mass = (spec_constant.distribution_init_concentration.mean * st_constant.structure.molecular_weight +
+                     spec_dynamic.distribution_init_concentration.mean * st_dynamic.structure.molecular_weight
                      ) / scipy.constants.Avogadro
         init_density = density.value = init_mass / comp.init_volume.mean
         model.parameters.get_one(id='k_syn_dynamic').value = 1.
@@ -279,8 +279,8 @@ def test_exponentially_descend_to_steady_state_count_and_mass(self):
         self.assertGreater(numpy.mean(pop_dynamic[101:]), spec_dynamic_ss - 3 * std_spec_dynamic_ss)
         self.assertLess(numpy.mean(pop_dynamic[101:]), spec_dynamic_ss + 3 * std_spec_dynamic_ss)
 
-        mass_ss = spec_dynamic_ss * st_dynamic.molecular_weight / scipy.constants.Avogadro
-        std_mass_ss = std_spec_dynamic_ss * st_dynamic.molecular_weight / scipy.constants.Avogadro
+        mass_ss = spec_dynamic_ss * st_dynamic.structure.molecular_weight / scipy.constants.Avogadro
+        std_mass_ss = std_spec_dynamic_ss * st_dynamic.structure.molecular_weight / scipy.constants.Avogadro
         self.assertGreater(numpy.mean(comp_mass[101:]), mass_ss - 3 * std_mass_ss)
         self.assertLess(numpy.mean(comp_mass[101:]), mass_ss + 3 * std_mass_ss)
 
@@ -314,21 +314,21 @@ def test_exponentially_increase_to_steady_state_mass_and_descend_to_concentratio
 
         # set quantitative values
         comp.init_volume.mean = 100e-15
-        st_constant.molecular_weight = 1.
-        st_dynamic.molecular_weight = 0.
+        st_constant.structure.molecular_weight = 1.
+        st_dynamic.structure.molecular_weight = 0.
         spec_constant.distribution_init_concentration.mean = 10.
         spec_dynamic.distribution_init_concentration.mean = 100.
-        init_mass = (spec_constant.distribution_init_concentration.mean * st_constant.molecular_weight +
-                     spec_dynamic.distribution_init_concentration.mean * st_dynamic.molecular_weight
+        init_mass = (spec_constant.distribution_init_concentration.mean * st_constant.structure.molecular_weight +
+                     spec_dynamic.distribution_init_concentration.mean * st_dynamic.structure.molecular_weight
                      ) / scipy.constants.Avogadro
         init_density = density.value = init_mass / comp.init_volume.mean
         model.parameters.get_one(id='k_syn_constant').value = 1.
         model.parameters.get_one(id='k_deg_constant').value = 2e-2
 
         spec_constant_ss = model.parameters.get_one(id='k_syn_constant').value / model.parameters.get_one(id='k_deg_constant').value
         std_spec_constant_ss = numpy.sqrt(spec_constant_ss)
-        mass_ss = spec_constant_ss * st_constant.molecular_weight / scipy.constants.Avogadro
-        std_mass_ss = spec_constant_ss * st_constant.molecular_weight / scipy.constants.Avogadro
+        mass_ss = spec_constant_ss * st_constant.structure.molecular_weight / scipy.constants.Avogadro
+        std_mass_ss = spec_constant_ss * st_constant.structure.molecular_weight / scipy.constants.Avogadro
         vol_ss = mass_ss / density.value
         std_vol_ss = std_mass_ss / density.value
 

diff --git a/tests/multialgorithm/test_model_utilities.py b/tests/multialgorithm/test_model_utilities.py
@@ -78,15 +78,17 @@ def test_concentration_to_molecules(self):
 
         compartment_c = model.compartments.create(id='c', init_volume=wc_lang.InitVolume(mean=1.))
 
+        structure = wc_lang.ChemicalStructure(molecular_weight=10.)
+
         species_types = {}
         cus_species_types = {}
         for cu in wc_lang.DistributionInitConcentration.units.choices:
             id = str(cu).replace(' ', '_')
-            species_types[id] = model.species_types.create(id=id, molecular_weight=10)
+            species_types[id] = model.species_types.create(id=id, structure=structure)
             cus_species_types[id] = cu
 
         for other in ['no_units', 'no_concentration', 'no_such_concentration_unit']:
-            species_types[other] = model.species_types.create(id=other, molecular_weight=10)
+            species_types[other] = model.species_types.create(id=other, structure=structure)
 
         species = {}
         for key, species_type in species_types.items():

diff --git a/tests/multialgorithm/test_multialgorithm_simulation.py b/tests/multialgorithm/test_multialgorithm_simulation.py
@@ -373,7 +373,8 @@ def setUp(self):
 
     @unittest.skip('Disable temporarily, while A finishes "incomplete-updates" branch')
     def test_nan_propensities(self):
-        self.model.species_types.get_one(id='spec_type_0').molecular_weight = float('NaN')
+        st_0 = self.model.species_types.get_one(id='spec_type_0')
+        st_0.structure.molecular_weight = float('NaN')
         multialgorithm_simulation = MultialgorithmSimulation(self.model, {})
         simulation_engine, _ = multialgorithm_simulation.build_simulation()
         with self.assertRaisesRegex(AssertionError, "total propensities is 'NaN'"):

diff --git a/tests/multialgorithm/test_species_populations.py b/tests/multialgorithm/test_species_populations.py
@@ -778,7 +778,7 @@ def setUp(self):
         self.simulator = SimulationEngine()
         self.species_ids = 's1 s2 s3'.split()
         self.initial_population = dict(zip(self.species_ids, range(3)))
-        self.molecular_weight = dict(zip(self.species_ids, [10]*3))
+        self.molecular_weight = dict(zip(self.species_ids, [10.]*3))
         self.test_species_pop_sim_obj = SpeciesPopSimObject('test_name', self.initial_population,
                                                             self.molecular_weight, 
                                                             random_state=RandomStateManager.instance())

diff --git a/wc_sim/multialgorithm/make_models.py b/wc_sim/multialgorithm/make_models.py
@@ -14,7 +14,7 @@
                      Observable, Function, FunctionExpression,
                      Reaction, RateLawDirection, RateLawExpression, Parameter,
                      DistributionInitConcentration,
-                     Validator, InitVolume)
+                     Validator, InitVolume, ChemicalStructure)
 from wc_lang.transform import PrepForWcSimTransform
 from wc_utils.util.enumerate import CaseInsensitiveEnum
 from wc_onto import onto
@@ -67,7 +67,7 @@ def convert_pop_conc(species_copy_number, vol):
 
     @classmethod
     def add_test_submodel(cls, model, model_type, submodel_num, init_vol, species_types,
-                          default_species_copy_number, default_species_std, 
+                          default_species_copy_number, default_species_std,
                           species_copy_numbers, species_stds, expressions):
         """ Create a test submodel
 
@@ -121,8 +121,8 @@ def add_test_submodel(cls, model, model_type, submodel_num, init_vol, species_ty
                                          init_volume=init_volume)
         objects[Compartment][comp.id] = comp
 
-        density = comp.init_density = model.parameters.create(id='density_compt_{}'.format(submodel_num), 
-            value=1100, units=unit_registry.parse_units('g l^-1'))
+        density = comp.init_density = model.parameters.create(id='density_compt_{}'.format(submodel_num),
+                                                              value=1100, units=unit_registry.parse_units('g l^-1'))
         objects[Parameter][density.id] = density
 
         volume = model.functions.create(id='volume_compt_{}'.format(submodel_num), units=unit_registry.parse_units('l'))
@@ -245,7 +245,7 @@ def add_test_submodel(cls, model, model_type, submodel_num, init_vol, species_ty
     @classmethod
     def make_test_model(cls, model_type,
                         init_vols=None,
-                        molecular_weight=10,
+                        molecular_weight=10.,
                         charge=0,
                         num_submodels=1,
                         default_species_copy_number=1000000,
@@ -294,14 +294,15 @@ def make_test_model(cls, model_type,
         model = Model(id='test_model', name='{} with {} submodels'.format(model_type, num_submodels),
                       version='0.0.0', wc_lang_version='0.0.1')
 
+        structure = ChemicalStructure(molecular_weight=molecular_weight, charge=charge)
+
         # SpeciesTypes
         species_types = []
         for i in range(num_species):
             spec_type = model.species_types.create(
                 id='spec_type_{}'.format(i),
-                type=onto['WC:protein'], # protein
-                molecular_weight=molecular_weight,
-                charge=charge)
+                type=onto['WC:protein'],  # protein
+                structure=structure)
             species_types.append(spec_type)
 
         # make submodels
@@ -311,7 +312,7 @@ def make_test_model(cls, model_type,
             cls.add_test_submodel(model, model_type, submodel_num, init_vols[i],
                                   species_types, default_species_copy_number=default_species_copy_number,
                                   default_species_std=default_species_std,
-                                  species_copy_numbers=species_copy_numbers, species_stds=species_stds, 
+                                  species_copy_numbers=species_copy_numbers, species_stds=species_stds,
                                   expressions=expressions)
 
         if transform_prep_and_check:

diff --git a/wc_sim/multialgorithm/multialgorithm_simulation.py b/wc_sim/multialgorithm/multialgorithm_simulation.py
@@ -185,8 +185,12 @@ def molecular_weights_for_species(self, species):
         """
         species_weights = {}
         for species_id in species:
-            (species_type_id, _) = ModelUtilities.parse_species_id(species_id)
-            species_weights[species_id] = self.model.species_types.get_one(id=species_type_id).molecular_weight
+            species_type_id, _ = ModelUtilities.parse_species_id(species_id)
+            species_type = self.model.species_types.get_one(id=species_type_id)
+            if species_type.structure:
+                species_weights[species_id] = species_type.structure.molecular_weight
+            else:
+                species_weights[species_id] = float('nan')
         return species_weights
 
     def create_shared_species_pop_objs(self):
@@ -310,7 +314,11 @@ def make_local_species_pop(model, random_state, retain_history=True):
         for specie in model.get_species():
             (species_type_id, _) = ModelUtilities.parse_species_id(specie.id)
             # TODO(Arthur): make get_one more robust, or do linear search
-            molecular_weights[specie.id] = model.species_types.get_one(id=species_type_id).molecular_weight
+            species_type = model.species_types.get_one(id=species_type_id)
+            if species_type.structure:
+                molecular_weights[specie.id] = species_type.structure.molecular_weight
+            else:
+                molecular_weights[specie.id] = float('nan')
 
         # Species used by continuous time submodels (like DFBA and ODE) need initial fluxes
         # which indicate that the species is modeled by a continuous time submodel.