updates to content

biosimulator_processes/__init__.py

@@ -19,7 +19,7 @@
     ('amici', 'amici_process.AmiciProcess')]
 
 STEPS_TO_REGISTER = [
-    ('get_sbml_step', 'get_sbml.GetSbmlStep'),
+    # ('get_sbml_step', 'get_sbml.GetSbmlStep'),
     ('plotter', 'viz.CompositionPlotter'),
     ('plotter2d', 'viz.Plotter2d')]
 

biosimulator_processes/data_model/sed_data_model.py

@@ -3,11 +3,11 @@
 from types import NoneType
 import requests
 from abc import abstractmethod, ABC
+
 from pydantic import Field, create_model
-from biosimulator_processes.data_model import _BaseClass
 
+from biosimulator_processes.data_model import _BaseClass
 
-__all__ = ['SedDataModel']
 
 @dataclass
 class SimulationModelParameter(_BaseClass):

biosimulator_processes/data_model/verify_data_model.py

@@ -1,9 +1,32 @@
 from dataclasses import dataclass
 
+from process_bigraph.experiments.parameter_scan import RunProcess
+
+from biosimulator_processes import CORE
+
 
 @dataclass
 class OutputAspectVerification:
     aspect_type: str  # one of: 'names', 'values'. TODO: Add more
     is_verified: bool
     expected_data: any
     process_data: any
+
+
+class ODEProcess(RunProcess):
+    def __init__(self, config=None, core=CORE, **kwargs):
+        """ODE-based wrapper of RunProcess from process_bigraph.
+
+            kwargs:
+                'process_address': 'string',
+                'process_config': 'tree[any]',
+                'observables': 'list[path]',
+                'timestep': 'float',
+                'runtime': 'float'
+        """
+        configuration = config or kwargs
+        configuration['observables'] = kwargs.get('observables') or self.set_observables()
+        super().__init__(configuration, core)
+
+    def set_observables(self):
+        return [(k, v) for k, v in self.process.inputs().items()]

biosimulator_processes/instance.py

@@ -0,0 +1,59 @@
+import matplotlib.pyplot as plt
+from process_bigraph.experiments.parameter_scan import RunProcess
+
+from biosimulator_processes import CORE
+from biosimulator_processes.steps.ode_simulation import ODEProcess
+
+
+def get_observables(proc: RunProcess):
+    observables = []
+    for port_name, port_dict in proc.process.inputs().items():
+        if port_name.lower() == 'floating_species_concentrations':
+            if isinstance(port_dict, dict):
+                for name, typeVal in port_dict.items():
+                    obs = [port_name, name]
+                    observables.append(obs)
+            else:
+                obs = [port_name]
+                observables.append(obs)
+    return observables
+
+
+def generate_ode_instance(process_address: str, model_fp: str, step_size: float, duration: float) -> ODEProcess:
+    ode_process_config = {'model': {'model_source': model_fp}}
+    proc = RunProcess(
+        config={
+            'process_address': process_address,
+            'process_config': ode_process_config,
+            'timestep': step_size,
+            'runtime': duration},
+        core=CORE)
+    obs = get_observables(proc)
+
+    return ODEProcess(
+        address=process_address,
+        model_fp=model_fp,
+        observables=obs,
+        step_size=step_size,
+        duration=duration)
+
+
+def plot_ode_output_data(data: dict):
+    time = data['results']['time']
+    spec_outputs = []
+    for name, output in data['results']['floating_species_concentrations'].items():
+        spec_outputs.append({name: output})
+
+    # Plotting the data
+    plt.figure(figsize=(10, 8))
+    for output in spec_outputs:
+        for name, out in output.items():
+            plt.plot(time, out, label=name)
+
+    plt.xlabel('Time')
+    plt.ylabel('Concentration')
+    plt.title('Species Concentrations Over Time')
+    plt.legend()
+    plt.grid(True)
+    plt.show()
+

biosimulator_processes/steps/ode_simulation.py

@@ -1,5 +1,9 @@
 import abc
+
 from process_bigraph import Step
+from process_bigraph.experiments.parameter_scan import RunProcess
+
+from biosimulator_processes import CORE
 
 
 class OdeSimulation(Step, abc.ABC):
@@ -37,3 +41,35 @@ def set_global_parameters(self):
     @abc.abstractmethod
     def set_reactions(self):
         pass
+
+
+class ODEProcess(RunProcess):
+    def __init__(self,
+                 address: str,
+                 model_fp: str,
+                 observables: list[list[str]],
+                 step_size: float,
+                 duration: float,
+                 config=None,
+                 core=CORE,
+                 **kwargs):
+        """
+            Kwargs:
+                'process_address': 'string',
+                'process_config': 'tree[any]',
+                'observables': 'list[path]',
+                'timestep': 'float',
+                'runtime': 'float'
+        """
+        configuration = config or {}
+        if not config:
+            configuration['process_address'] = address
+            configuration['timestep'] = step_size
+            configuration['runtime'] = duration
+            configuration['process_config'] = {'model': {'model_source': model_fp}}
+            configuration['observables'] = observables
+        super().__init__(config=configuration, core=core)
+
+    def run(self, inputs=None):
+        input_state = inputs or {}
+        return self.update(input_state)