linvpy.py 文件源码

def estimate(self, a, y, initial_x=None):
        """
        :param a: MxN matrix A in the y=Ax equation
        :type a: numpy.ndarray
        :param y: M vector y in the y=Ax equation
        :type y: numpy.ndarray
        :param initial_x: N vector of an initial solution
        :type initial_x: numpy.ndarray
        :return: best estimation of the N vector x in the y=Ax equation
        :rtype: numpy.ndarray

        :Example:

        >>> import numpy as np
        >>> import linvpy as lp

        >>> a = np.matrix([[1, 2], [3, 4], [5, 6]])
        >>> y = np.array([1, 2, 3])

        >>> m = lp.MEstimator()
        >>> m.estimate(a,y)
        array([ -2.95552481e-16,   5.00000000e-01])

        >>> m_ = lp.MEstimator(loss_function=lp.Bisquare, clipping=2.23, \
        regularization=lp.Lasso(), lamb=3)
        >>> initial_solution = np.array([1, 2])
        >>> m_.estimate(a, y, initial_x=initial_solution)
        array([ 0.,  0.])
        """
        return self.irls(a, y, initial_x)