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import matplotlib.pyplot as plt
from pyodesys.symbolic import SymbolicSys
%matplotlib inline


    

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def decay(t, y, p):
    return [-p['lmb']*y[0]]


    

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odesys = SymbolicSys.from_callback(decay, 1, 1, par_by_name=True, param_names=['lmb'])


    

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res = odesys.integrate(3, [1], {'lmb': 7, 'irrelevant_key': 'irrelevant_value'}, integrator='odeint')
res.plot()


    

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results = odesys.integrate(3, [1], {'lmb': [1, 5, 25]}, integrator='odeint')
fig, axes = plt.subplots(1, len(results), figsize=(14, 4))
for res, ax in zip(results, axes):
    res.plot(ax=ax)


    

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def decay2(t, y, p):
    return [-p['foo']*y[0], p['foo']*y[0] - p['bar']*y[1]]


    

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odesys2 = SymbolicSys.from_callback(decay2, 2, 2, par_by_name=True, param_names=['foo', 'bar'])
res2 = odesys2.integrate(3, [2, 1], {'foo': 2, 'bar': 1}, integrator='cvode')
res2.plot()


    

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results2 = odesys2.integrate(3, [2, 1], {'foo': 2, 'bar': [1, 2, 3]}, integrator='cvode')
fig, axes = plt.subplots(1, len(results2), figsize=(14, 4))
for r, ax in zip(results2, axes):
    r.plot(ax=ax)