Fix issue with the solver status method

Fixes #24 and #25

docs/examples/fastcore.md

@@ -14,7 +14,7 @@ import miom
 import numpy as np
 
 # Use the flux-consistent subnetwork (fcm) of the Human1 GEM model 
-m = miom.mio.load_gem('https://github.com/pablormier/miom-gems/raw/main/gems/homo_sapiens_human1_fcm.miom')
+m = miom.load_gem('@SysBioChalmers/Human-GEM/v1.9.0/consistent')
 # Select reactions from the cholesterol metabolism as the core reactions to keep
 core_rxn = m.find_reactions_from_pathway("Cholesterol metabolism")
 print(sum(core_rxn))
@@ -25,8 +25,8 @@ weights[core_rxn == 1] = 1
 
 # Exact-Fastcore
 fmc = (miom
-        .load(m, solver=miom.Solvers.GUROBI_PYMIP)
-        .setup(opt_tol=0.01)
+        .load(m, solver=miom.Solvers.CPLEX)
+        .setup(opt_tol=0.02)
         .steady_state()
         .subset_selection(weights)
         .keep(core_rxn == 1)

docs/examples/fba.md

@@ -4,7 +4,7 @@ A simple Flux Balance Analysis can be easily defined and solved with any of the
 
 ```python
 import miom
-network = miom.mio.load_gem("https://github.com/pablormier/miom-gems/raw/main/gems/mus_musculus_iMM1865.miom")
+network = miom.mio.load_gem("@iMM1865")
 target = "BIOMASS_reaction"
 flux = (miom
         .load(network)

docs/examples/imat.md

@@ -9,7 +9,7 @@ Example implementation of iMAT using MIOM. Note that this implementation support
 import miom
 
 # Use the iHuman-GEM model
-m = miom.mio.load_gem('https://github.com/pablormier/miom-gems/raw/main/gems/homo_sapiens_human1.miom')
+m = miom.load_gem('@SysBioChalmers/Human-GEM/v1.9.0')
 
 # Add all the reactions from the Cholesterol pathway to the highly expressed set
 RH = m.find_reactions_from_pathway("Cholesterol metabolism")

docs/examples/sparse_fba.md

@@ -12,7 +12,7 @@ import miom
 # Load a genome-scale metabolic network. You can load SMBL or Matlab metabolic networks
 # as well using the same method, but it requires to have the cobratoolbox python library
 # installed.
-network = miom.mio.load_gem("https://github.com/pablormier/miom-gems/raw/main/gems/mus_musculus_iMM1865.miom")
+network = miom.load_gem("@iMM1865")
 
 # Create the sparse FBA problem to get a solution that maximizes
 # the optimal flux through the BIOMASS_reaction minimizing the

miom/__main__.py

@@ -57,7 +57,7 @@ def convert_gem(args):
     input = args.input
     output = args.output
     if isinstance(input, str):
-        if os.path.isfile(input):
+        if os.path.isfile(input) and input.endswith('.txt'):
             # Open file and get all the lines into a list
             print(f"Reading list of files from {input}...")
             with open(input, "r") as f:
@@ -70,17 +70,12 @@ def convert_gem(args):
                         out_files.append(out_path.strip())
                 input = in_files
                 output = out_files
-        elif miom.mio._is_url(input):
-            print("Imporing file from URL")
-            input = [input]
-        else:
-            # Assume it's a folder
-            input_folder = os.path.abspath(input)
-            print("Input folder", input_folder)
-            # Check if folder is valid and exists:
-            if not os.path.isdir(input_folder):
-                raise FileNotFoundError(f"{input_folder} is not a valid folder, a file or an URL")
+        elif os.path.isdir(os.path.abspath(input)):
+            #in_folder = os.path.abspath(input)
             input = [os.path.join(input, f) for f in os.listdir(input)]
+        else:
+            input = [input]
+            output = [output]
     convert_list_gems(input, output, consistent=args.consistent, solver=args.solver)
 
 

miom/miom.py

@@ -422,6 +422,11 @@ def initialize_problem(self):
     def get_solver_status(self):
         pass
 
+    @property
+    def status(self):
+        return self.get_solver_status()
+
+
     @_composable
     def setup(self, **kwargs):
         """Provide the options for the solver.
@@ -956,8 +961,13 @@ def _copy(self, **kwargs):
         return m
 
     def get_solver_status(self):
+        # Check if attribute solutions exist
+        if not hasattr(self, "solutions"):
+            status = "empty"
+        else:
+            status = self.solutions.claimedStatus
         return {
-            "status": self.solutions.claimedStatus,
+            "status": status,
             "objective_value": self.problem.value,
             "elapsed_seconds": self.last_solver_time
         }