Insert Parameters

Parameters can be inserted automatically into a Copasi model from python code using PyCoTools

Build a demonistration model

While antimony or the COPASI user interface are the preferred ways to build a model, PyCoTools does have a mechanism for constructing COPASI models. For variation and demonstration, this method is used here.

import os
import site
site.addsitedir('D:\pycotools3')
from pycotools3 import model, tasks, viz
## Choose a working directory for model
working_directory = os.path.abspath('')
copasi_file = os.path.join(working_directory, 'MichaelisMenten.cps')

if os.path.isfile(copasi_file):
    os.remove(copasi_file)


kf = 0.01
kb = 0.1
kcat = 0.05
with model.Build(copasi_file) as m:
    m.name = 'Michaelis-Menten'
    m.add('compartment', name='Cell')

    m.add('metabolite', name='P', concentration=0)
    m.add('metabolite', name='S', concentration=30)
    m.add('metabolite', name='E', concentration=10)
    m.add('metabolite', name='ES', concentration=0)

    m.add('reaction', name='S bind E', expression='S + E -> ES', rate_law='kf*S*E',
          parameter_values={'kf': kf})

    m.add('reaction', name='S unbind E', expression='ES -> S + E', rate_law='kb*ES',
         parameter_values={'kb': kb})

    m.add('reaction', name='ES produce P', expression='ES -> P + E', rate_law='kcat*ES',
          parameter_values={'kcat': kcat})

mm = model.Model(copasi_file)
mm

Model(name=Michaelis-Menten, time_unit=s, volume_unit=ml, quantity_unit=mmol)

Insert Parameters from Python Dictionary

params = {'E': 100,
          'P': 150}

## Insert into model
I = model.InsertParameters(mm, parameter_dict=params)
##format the parameters for displaying nicely
I.parameters.index = ['Parameter Value']
I.parameters.transpose()

	Parameter Value
E	100
P	150

Alternatively use inplace=True argument (analogous to the pandas library) to modify the object inplace, rather than needing to assign

model.InsertParameters(mm, parameter_dict=params, inplace=True)

<pycotools3.model.InsertParameters at 0x1b41f67a9e8>

Insert Parameters from Pandas DataFrame

import pandas
params = {'(S bind E).kf': 50,
          '(S unbind E).kb': 96}
df = pandas.DataFrame(params, index=[0])
df

	(S bind E).kf	(S unbind E).kb
0	50	96

model.InsertParameters(mm, df=df, inplace=True)

<pycotools3.model.InsertParameters at 0x1b41f67a048>

Insert Parameters from Parameter Estimation Output

First we’ll get some parameter estimation data by fitting a model to simulated data.

fname = os.path.join(os.path.abspath(''), 'timecourse.txt')
data = mm.simulate(0, 50, 1, report_name=fname)
assert os.path.isfile(fname)

with  tasks.ParameterEstimation.Context(copasi_file, fname, context='s', parameters='a') as context:
    context.randomize_start_values = True
    context.lower_bound = 0.01
    context.upper_bound = 100
    context.run_mode = True
    config = context.get_config()
PE = tasks.ParameterEstimation(config)

mm

Model(name=Michaelis-Menten, time_unit=s, volume_unit=ml, quantity_unit=mmol)

Now we can insert the estimated parameters using:

##index=0 for best parameter set (i.e. lowest RSS)
model.InsertParameters(mm, parameter_path=PE.results_directory, index=0, inplace=True)

---------------------------------------------------------------------------
InputError                                Traceback (most recent call last)
<ipython-input-24-d908d0566dc2> in <module>()
      1 ##index=0 for best parameter set (i.e. lowest RSS)
----> 2 model.InsertParameters(mm, parameter_path=PE.results_directory, index=0, inplace=True)

D:\pycotools3\pycotools3\model.py in __init__(self, model, parameter_dict, df, parameter_path, index, quantity_type, inplace)
   4674         self._do_checks()
   4675
-> 4676         self.model = self.insert()
   4677         if self.inplace:
   4678             self.model.save()

D:\pycotools3\pycotools3\model.py in insert(self)
   4867
   4868         """
-> 4869         self.model = self.insert_locals()
   4870         self.model = self.insert_compartments()
   4871         self.model = self.insert_global_quantities()

D:\pycotools3\pycotools3\model.py in insert_locals(self)
   4774         # print self.parameters
   4775
-> 4776         locals = [j for i in self.model.reactions for j in i.parameters if
   4777                   j.global_name in list(self.parameters.keys())]
   4778         if locals == []:

D:\pycotools3\pycotools3\model.py in <listcomp>(.0)
   4775
   4776         locals = [j for i in self.model.reactions for j in i.parameters if
-> 4777                   j.global_name in list(self.parameters.keys())]
   4778         if locals == []:
   4779             return self.model

D:\pycotools3\pycotools3\cached_property.py in __get__(self, obj, cls)
     38         if obj is None:
     39             return self
---> 40         value = obj.__dict__[self.func.__name__] = self.func(obj)
     41         return value
     42

D:\pycotools3\pycotools3\model.py in parameters(self)
   4760
   4761         if self.parameter_path != None:
-> 4762             P = viz.Parse(self.parameter_path, copasi_file=self.model.copasi_file)
   4763             if isinstance(self.index, int):
   4764                 return pandas.DataFrame(P.data.iloc[self.index]).transpose()

D:\pycotools3\pycotools3\viz.py in __init__(self, cls_instance, log10, copasi_file, alpha, rss_value, num_data_points)
    519             raise errors.InputError('{} not in {}'.format(
    520                 self.cls_instance,
--> 521                 accepted_types)
    522             )
    523

InputError: {'MichaelisMenten': 'D:\\pycotools3\\docs\\source\\Tutorials\\Problem1\\Fit1\\MichaelisMenten\\ParameterEstimationData'} not in [<class 'pycotools3.tasks.TimeCourse'>, <class 'pycotools3.tasks.Scan'>, <class 'pycotools3.tasks.ParameterEstimation'>, <class 'str'>, <class 'pycotools3.viz.Parse'>, <class 'pycotools3.tasks.ProfileLikelihood'>, <class 'pandas.core.frame.DataFrame'>, <class 'pycotools3.tasks.ChaserParameterEstimations'>]

Insert Parameters using the model.Model().insert_parameters method

The same means of inserting parameters can be used from the model object itself

mm.insert_parameters(parameter_dict=params, inplace=True)

Change parameters using model.Model().set

Individual parameters can also be changed using the set method. For example, we could set the metabolite with name S concentration or particle numbers to 55

mm.set('metabolite', 'S', 55, 'name', 'concentration')

## or

mm.set('metabolite', 'S', 55, 'name', 'particle_numbers')