fit

Module Contents

Classes

Functions

class _Device(fitFunction, nbArgs)

class _Objective(x_data, y_data, fitCriterion)

Bases: optimeed.optimize.InterfaceObjCons

Interface class for objectives and constraints. The objective is to MINIMIZE and the constraint has to respect VALUE <= 0

compute(theDevice)

Get the value of the objective or the constraint. The objective is to MINIMIZE and the constraint has to respect VALUE <= 0

Parameters:theDevice – Input device that has already been evaluated Returns:float.

leastSquare(function, functionArgs, x_data, y_data)

Least square calculation (sum (y-ŷ)^2)

Parameters:

• function – Function to fit
• functionArgs – Arguments of the function
• x_data – x-axis coordinates of data to fit
• y_data – y-axis coordinates of data to fit

Returns:

least squares

r_squared(function, functionArgs, x_data, y_data)

R squared calculation

Parameters:

• function – Function to fit
• functionArgs – Arguments of the function
• x_data – x-axis coordinates of data to fit
• y_data – y-axis coordinates of data to fit

Returns:

R squared

do_fit(fitFunction, x_data, y_data, *args, fitCriterion=leastSquare)

Main method to fit a function

Parameters:

• fitFunction – the function to fit (link to it)
• x_data – x-axis coordinates of data to fit
• y_data – y-axis coordinates of data to fit
• args – for each parameter: [min, max] admissible value
• fitCriterion – fit criterion to minimize. Default: least square

Returns:

[arg_i_optimal, …], y estimated, error.