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Fitting several datasets at once

Several datasets can be fitted simultaneously, either using the BornAgain fit facilities, or using external minimizers.

With the BornAgain fit facilities

Add different data and different fit models to an instance of class FitObjective:

    fit_objective = ba.FitObjective()
    fit_objective.addSimulationAndData(simulation1, data1[, stdv1][, wgt1])
    fit_objective.addSimulationAndData(simulation2, data2[, stdv2][, wgt2])

The optional stdv arguments hold error estimates. The optional weights wgt are by default set to 1.

For a full example, see Examples > Fitting > Simultaneous fit.

With external minimizer

See the honeycomb fit example, where differential evolution is called with an objective function that has contributions from several reflectometry datasets and models:

    def objective_function(*args):
        ...
        return <sum of squared relative differences>

    result = scipy.optimize.differential_evolution(
        objective_function,
        ...)