source: sasview/src/sas/sasgui/plottools/fittings.py @ b2669f5

"""
"""
from scipy import optimize


class Parameter(object):
    """
    Class to handle model parameters
    """
    def __init__(self, model, name, value=None):
        self.model = model
        self.name = name
        if not value == None:
            self.model.setParam(self.name, value)

    def set(self, value):
        """
            Set the value of the parameter
        """
        self.model.setParam(self.name, value)

    def __call__(self):
        """
            Return the current value of the parameter
        """
        return self.model.getParam(self.name)


def sasfit(model, pars, x, y, err_y, qmin=None, qmax=None):
    """
    Fit function

    :param model: sas model object
    :param pars: list of parameters
    :param x: vector of x data
    :param y: vector of y data
    :param err_y: vector of y errors
    """
    def f(params):
        """
        Calculates the vector of residuals for each point
        in y for a given set of input parameters.

        :param params: list of parameter values
        :return: vector of residuals
        """
        i = 0
        for p in pars:
            p.set(params[i])
            i += 1

        residuals = []
        for j in range(len(x)):
            if x[j] >= qmin and x[j] <= qmax:
                residuals.append((y[j] - model.runXY(x[j])) / err_y[j])
        return residuals

    def chi2(params):
        """
        Calculates chi^2

        :param params: list of parameter values

        :return: chi^2

        """
        sum = 0
        res = f(params)
        for item in res:
            sum += item * item
        return sum

    p = [param() for param in pars]
    out, cov_x, info, mesg, success = optimize.leastsq(f, p, full_output=1)
    # Calculate chi squared
    if len(pars) > 1:
        chisqr = chi2(out)
    elif len(pars) == 1:
        chisqr = chi2([out])

    return chisqr, out, cov_x


def calcCommandline(event):
    # Testing implementation
    # Fit a Line model
    from LineModel import LineModel
    line = LineModel()
    cstA = Parameter(line, 'A', event.cstA)
    cstB = Parameter(line, 'B', event.cstB)
    y = line.run()
    chisqr, out, cov = sasfit(line, [cstA, cstB], event.x, y, 0)
    # print "Output parameters:", out
    print "The right answer is [70.0, 1.0]"
    print chisqr, out, cov