Interactive kinetic modelling

In this notebook we will look at how we can explore a simple kinetic system using only a handful of lines of Python code and the ChemPy library. First we import the functions & classes that we will be using:



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from collections import defaultdict
from ipywidgets import interact, FloatSlider
from chempy import ReactionSystem, Substance
from chempy.kinetics.ode import get_odesys
from chempy.kinetics._native import get_native
from chempy.units import SI_base_registry, default_units as u
import matplotlib.pyplot as plt
%matplotlib inline

Next we define our what reactions are taking place:



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rsys = ReactionSystem.from_string("""
A -> B; 'k1'
B + C -> P; 'k2'
""", substance_factory=Substance)
rsys

From this reactionsystem we generate a system of ordinary differential equations:



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odesys, extra = get_odesys(rsys, include_params=False, unit_registry=SI_base_registry,
                           output_conc_unit=u.micromolar, output_time_unit=u.minute)

Not that it is strictly needed for this simple system, but since we are using pyodesys, we can generate C++ code which is compiled to a native extension module:



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native = get_native(rsys, odesys, 'cvode')

We will use ipywidgets for our interactive controls:



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def integrate_and_plot(
    tend_minutes=FloatSlider(5, min=1, max=60, step=1),
    lgA0molar=FloatSlider(-6, min=-7, max=-5, step=.1),
    lgC0molar=FloatSlider(-6, min=-7, max=-5, step=.1),
    k1_per_min=FloatSlider(5.8, min=1.0, max=20.0, step=0.1),
    k2_per_M_per_s=FloatSlider(4000, min=500, max=16000, step=500)
):
    result = native.integrate(tend_minutes*u.minute, defaultdict(lambda: 0*u.M, {'A': 10**lgA0molar*u.M, 'C': 10**lgC0molar*u.M}),
                              {'k1': k1_per_min/u.minute, 'k2': k2_per_M_per_s/u.M/u.s}, integrator='cvode')
    result.plot(title_info=2)

Try exploring the system by adjusting the parameter sliders below:



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interact(integrate_and_plot)