fit
¶
Module Contents¶
Classes¶
Functions¶
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class
_Objective
(x_data, y_data, fitCriterion)[source]¶ Bases:
optimeed.optimize.InterfaceObjCons
Interface class for objectives and constraints. The objective is to MINIMIZE and the constraint has to respect VALUE <= 0
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leastSquare
(function, functionArgs, x_data, y_data)[source]¶ 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
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r_squared
(function, functionArgs, x_data, y_data)[source]¶ 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
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do_fit
(fitFunction, x_data, y_data, *args, fitCriterion=leastSquare)[source]¶ 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.