addressing review comments

README.md

@@ -319,6 +319,23 @@ model.fba()[-1]
 # 0.21166294973531055
 ```
 
+### Who-is-who
+
+Models may use ids for metabolites and reactions hard to interpret. 
+You may use the `reactions_map` and the `metabolites_map` that return the reactions/metabolites ids along with their corresponding names. 
+For example: 
+
+```python
+>>> model.reactions_map
+                                         reaction_name
+PFK                                Phosphofructokinase
+PFL                             Pyruvate formate lyase
+PGI                      Glucose-6-phosphate isomerase
+PGK                            Phosphoglycerate kinase
+PGL                          6-phosphogluconolactonase
+```
+
+
 
 
 

dingo/MetabolicNetwork.py

@@ -111,7 +111,7 @@ def from_cobra_model(cls, arg):
 
         return cls(parse_cobra_model(arg))
 
-    def fva(self):
+    def _fva(self):
         """A member function to apply the FVA method on the metabolic network."""
 
         if self._parameters["fast_computations"]:
@@ -136,7 +136,7 @@ def fva(self):
         self._opt_value = max_biomass_objective
         return min_fluxes, max_fluxes, max_biomass_flux_vector, max_biomass_objective
 
-    def fba(self):
+    def _fba(self):
         """A member function to apply the FBA method on the metabolic network."""
 
         if self._parameters["fast_computations"]:
@@ -147,15 +147,15 @@ def fba(self):
         self._opt_value = opt_value
         return opt_vector, opt_value
 
-    def fba_to_df(self):
+    def fba(self):
         if not hasattr(self, '_opt_vector'):
-            self.fba()
+            self._fba()
         fba_df = pd.DataFrame({'fluxes': self._opt_vector}, index=self._reactions)
         return fba_df
 
-    def fva_to_df(self):
+    def fva(self):
         if not hasattr(self, '_min_fluxes'):
-            self.fva()
+            self._fva()
         fva_df = pd.DataFrame({'minimum': self._min_fluxes, 'maximum': self._max_fluxes}, index=self._reactions)
         return fva_df
 
@@ -209,20 +209,20 @@ def metabolites_map(self):
         return self._metabolites_map
 
     @property
-    def opt_value(self, value):
-        self._opt_value = value
+    def opt_value(self):
+        return self._opt_value
 
     @property
-    def opt_vector(self, value):
-        self._opt_vector = value
+    def opt_vector(self):
+        return self._opt_vector
 
     @property
-    def min_fluxes(self, value):
-        self._min_fluxes = value
+    def min_fluxes(self):
+        return self._min_fluxes
 
     @property
-    def max_fluxes(self, value):
-        self._max_fluxes = value
+    def max_fluxes(self):
+        return self._max_fluxes
 
     @property
     def get_as_tuple(self):

dingo/PolytopeSampler.py

@@ -81,7 +81,7 @@ def get_polytope(self):
             (
                 max_biomass_flux_vector,
                 max_biomass_objective,
-            ) = self._metabolic_network.fba()
+            ) = self._metabolic_network._fba()
 
             if (
                 self._parameters["fast_computations"]
@@ -108,7 +108,7 @@ def get_polytope(self):
                     max_fluxes,
                     max_biomass_flux_vector,
                     max_biomass_objective,
-                ) = self._metabolic_network.fva()
+                ) = self._metabolic_network._fva()
 
                 A, b, Aeq, beq = get_matrices_of_low_dim_polytope(
                     self._metabolic_network.S,
@@ -318,7 +318,7 @@ def sample_from_fva_output(
         num_threads -- the number of threads to use for parallel mmcs
         """
 
-        min_fluxes, max_fluxes, opt_vector, opt_value = model.fva()
+        min_fluxes, max_fluxes, opt_vector, opt_value = model._fva()
 
         A, b, Aeq, beq = get_matrices_of_low_dim_polytope(
             model.S, min_fluxes, max_fluxes, opt_percentage, model._parameters["tol"]

dingo/__init__.py

@@ -169,7 +169,7 @@ def dingo_main():
         else:
             raise Exception("An unknown format file given.")
 
-        result_obj = model.fba()
+        result_obj = model._fba()
 
         with open("dingo_fba_" + name + ".pckl", "wb") as dingo_fba_file:
             pickle.dump(result_obj, dingo_fba_file)

dingo/loading_models.py

@@ -57,7 +57,7 @@ def read_mat_file(input_file):
     return (parse_cobra_model( model ))
 
 def read_sbml_file(input_file):
-    """A Python function, based on the cobra.io.read_sbml_model() function of cabrapy
+    """A Python function, based on the cobra.io.read_sbml_model() function of cobrapy
     and the extract_polytope() function of PolyRound
     (https://gitlab.com/csb.ethz/PolyRound/-/blob/master/PolyRound/static_classes/parse_sbml_stoichiometry.py)
     to read an SBML file (.xml) and return:
@@ -144,6 +144,5 @@ def parse_cobra_model(cobra_model):
     metabolites_map = pd.DataFrame( [x.name for x in cobra_model.metabolites], [x.id for x in cobra_model.metabolites])
     metabolites_map.columns = ["metabolite_name"]
 
-    return lb, ub, S, metabolites, reactions, \
-        biomass_index, biomass_function, medium, inter_medium, exchanges, \
-            reactions_map, metabolites_map
+    return lb, ub, S, metabolites, reactions, biomass_index, biomass_function, \
+        medium, inter_medium, exchanges, reactions_map, metabolites_map

tests/fast_implementation_test.py

@@ -12,6 +12,7 @@
 from dingo.gurobi_based_implementations import fast_inner_ball
 
 class TestFastMethods(unittest.TestCase):
+
     def test_fast_max_bal_computation(self):
 
         m = 2
@@ -26,6 +27,7 @@ def test_fast_max_bal_computation(self):
 
         self.assertTrue(abs(max_ball[1] - 1) < 1e-08)
 
+
     def test_fast_fva(self):
 
         current_directory = os.getcwd()
@@ -34,12 +36,18 @@ def test_fast_fva(self):
         model = MetabolicNetwork.from_json(input_file_json)
         model.set_fast_mode()
 
-        res = model.fva()
+        res = model._fva()
 
         self.assertTrue(abs(res[3] - 0.8739215069684305) < 1e-08)
         self.assertEqual(res[0].size, 95)
         self.assertEqual(res[1].size, 95)
 
+        fva_df = model.fva()
+        biomass_function = model.reactions[model.biomass_index]
+        self.assertTrue(fva_df.loc[biomass_function]["maximum"] - fva_df.loc[biomass_function]["minimum"] <= 1e-03)
+        self.assertEqual(fva_df.shape, (95,2))
+
+
     def test_ecoli_to_full_dimensional_polytope(self):
 
         current_directory = os.getcwd()
@@ -55,21 +63,23 @@ def test_ecoli_to_full_dimensional_polytope(self):
 
         self.assertEqual(sampler.A.shape[0], 26)
         self.assertEqual(sampler.A.shape[1], 24)
-
         self.assertEqual(steady_states.shape[0], 95)
 
+
     def test_fast_fba(self):
 
         current_directory = os.getcwd()
         input_file_json = current_directory + "/ext_data/e_coli_core.json"
 
         model = MetabolicNetwork.from_json(input_file_json)
         model.set_fast_mode()
-
-        res = model.fba()
-
+        res = model._fba()
         self.assertTrue(abs(res[1] - 0.8739215069684305) < 1e-08)
 
+        fba_df = model.fba()
+        biomass_function = model.reactions[model.biomass_index]
+        self.assertTrue(abs(fba_df.loc[biomass_function]["fluxes"] - 0.8739215069684305) < 1e-08)
+
 
 if __name__ == "__main__":
     unittest.main()

tests/fba.py

@@ -16,30 +16,37 @@ def test_fba_json(self):
         input_file_json = os.getcwd() + "/ext_data/e_coli_core.json"
         model = MetabolicNetwork.from_json(input_file_json)
         model.set_slow_mode()
-        res = model.fba()
-
+        res = model._fba()
         self.assertTrue(abs(res[1] - 0.8739215067486387) < 1e-03)
 
+        biomass_function = model.reactions[model.biomass_index]
+        fba_df = model.fba()
+        self.assertTrue(abs(fba_df.loc[biomass_function]["fluxes"] - 0.8739215067486387) < 1e-03)
+
     def test_fba_mat(self):
 
         input_file_mat = os.getcwd() + "/ext_data/e_coli_core.mat"
         model = MetabolicNetwork.from_mat(input_file_mat)
         model.set_slow_mode()
-
-        res = model.fba()
-
+        res = model._fba()
         self.assertTrue(abs(res[1] - 0.8739215067486387) < 1e-03)
 
+        biomass_function = model.reactions[model.biomass_index]
+        fba_df = model.fba()
+        self.assertTrue(abs(fba_df.loc[biomass_function]["fluxes"] - 0.8739215067486387) < 1e-03)
+
     def test_fba_sbml(self):
 
         input_file_sbml = os.getcwd() + "/ext_data/e_coli_core.xml"
         model = MetabolicNetwork.from_sbml(input_file_sbml)
         model.set_slow_mode()
-
-        res = model.fba()
-
+        res = model._fba()
         self.assertTrue(abs(res[1] - 0.8739215067486387) < 1e-03)
 
+        biomass_function = model.reactions[model.biomass_index]
+        fba_df = model.fba()
+        self.assertTrue(abs(fba_df.loc[biomass_function]["fluxes"] - 0.8739215067486387) < 1e-03)
+
     def test_modify_medium(self):
 
         input_file_sbml = os.getcwd() + "/ext_data/e_coli_core.xml"
@@ -50,7 +57,8 @@ def test_modify_medium(self):
             model.set_slow_mode()
 
         initial_medium = model.medium
-        initial_fba = model.fba()[-1]
+        initial_fba = model._fba()[-1]
+        initial_fba_df = model.fba()
 
         # Original indices of the exchange reactions
         e_coli_core_medium_compound_indices = {
@@ -82,7 +90,16 @@ def test_modify_medium(self):
         self.assertTrue(model.lb[glc_index] == -35 and model.lb[o2_index] == -0.5)
 
         # Check if optimal value is affected
-        self.assertTrue( abs((model.fba()[-1] - initial_fba) - 0.1172) <= 1e-03)
+        self.assertTrue(
+            abs((model._fba()[-1] - initial_fba) - 0.1172) <= 1e-03
+        )
+
+
+        biomass_function = model.reactions[model.biomass_index]
+        fba_df = model.fba()
+        self.assertTrue(
+            abs((fba_df.loc[biomass_function]["fluxes"] - initial_fba_df.loc[biomass_function]["fluxes"]) - 0.1172) <= 1e-03
+        )
 
 
 if __name__ == "__main__":