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ODEModel with constraints gives error #282
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Constraints should not always be of the same type as their parent model apparently. As a workaround, could you try to create a constraint like this? cons = Model.as_constraint(sf.Eq(a+b, 0.055), ode_model)
constraints = [cons] I'm unable to try it myself at the moment, unfortunately. As an aside, this is not the best way of solving this: you're better of expressing |
Hm, that gives a key error: import numpy as np
import symfit as sf
tdata = np.array([10, 26, 44, 70, 120])
adata = 10e-4 * np.array([44, 34, 27, 20, 14])
a, b, t = sf.variables('a, b, t')
k = sf.Parameter('k', 0.1)
a0 = 54 * 10e-4
model_dict = {
sf.D(a, t): - k * a**2,
sf.D(b, t): k * a**2,
}
ode_model = sf.ODEModel(model_dict, initial={t: 0.0, a: a0, b: 0.0})
cons = sf.Model.as_constraint(sf.Eq(a, 0.055-b), ode_model)
constraints = [cons]
fit = sf.Fit(ode_model, t=tdata, a=adata, b=None, constraints=constraints)
fit_result = fit.execute()
print(fit_result)
(And yes, this is a toy problem. The real problem is related to this: #284 |
…Add initial parameters to connectivity_mapping Fixes tBuLi#282
…Add initial parameters to connectivity_mapping Fixes tBuLi#282
Adding constraints to the fitting of an ODEModel raises an error,
__init__() missing 1 required positional argument: 'initial'
Taking the simple coupled ODE model from the docs and adding an equality constraint to the variables (one that will necessarily be true anyways) gives the following output:
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