fixed plotting and updated deps for latest release

bio_compose/__init__.py

@@ -5,7 +5,8 @@
     get_output,
     get_compatible_verification_simulators,
     verify,
-    run_simulation
+    run_simulation,
+    visualize_observables
 )
 
 
@@ -21,5 +22,6 @@
     'get_output',
     'get_compatible_verification_simulators',
     'verify',
-    'run_simulation'
+    'run_simulation',
+    'visualize_observables'
 ]

bio_compose/api.py

@@ -75,7 +75,7 @@ def verify(*args) -> VerificationResult:
     buffer_time = 5
     poll_time = 5
     submission_generator = verifier.verify_sbml if run_sbml else verifier.verify_omex
-    print("Submitting verification...")
+    print("Submitting verification...", end='\r')
     time.sleep(buffer_time)
 
     # fetch params
@@ -168,4 +168,20 @@ def run_simulation(*args, **kwargs) -> SimulationResult:
                     break
             else:
                 i += 1
-    return SimulationResult(data=output)
+    return SimulationResult(data=output)
+
+
+def visualize_observables(job_id: str, save_dest: str = None, hspace: float = 0.25, use_grid: bool = False):
+    """
+    Visualize simulation output (observables) data, not comparison data, with subplots for each species.
+
+    :param job_id: (`str`) job id for the simulation observable output you wish to visualize.
+    :param save_dest: (`str`) path to save the figure. If this value is passed, the figure will be saved in pdf format to this location.
+    :param hspace: (`float`) horizontal spacing between subplots. Defaults to 0.25.
+    :param use_grid: (`bool`) whether to use a grid for each subplot. Defaults to False.
+    
+    :rtype: `Tuple[matplotlib.Figure, Dict]` 
+    :return: matplotlib Figure and simulation observables indexed by simulator
+    """
+    return API_VERIFIER.visualize_observables(job_id=job_id, save_dest=save_dest, hspace=hspace, use_grid=use_grid)
+

bio_compose/verifier.py

@@ -287,6 +287,14 @@ def visualize_observables(self, job_id: str, hspace: float = 0.25, use_grid: boo
         observables = [key for key in species_data_content.keys() if key not in excluded_observables]
         first_observable = species_data_content[observables[0]]
         simulators = list(first_observable['output_data'].keys())
+
+        # post-process to handle any strings (errors)
+        for sim in simulators:
+            data = first_observable['output_data'][sim]
+            if isinstance(data, str):
+                simulators.remove(sim)
+
+        # count post processed sims
         n_simulators = len(simulators)
 
         # create subplots
@@ -302,6 +310,8 @@ def visualize_observables(self, job_id: str, hspace: float = 0.25, use_grid: boo
             ax = axes[idx]
             for observable in observables:
                 value_data = species_data_content[observable]['output_data'][simulator]
+                if isinstance(value_data, str):
+                    continue 
                 obs[observable][simulator] = value_data
                 sns.lineplot(data=value_data, ax=ax, label=observable)