xdem.fit
Functions to perform normal, weighted and robust fitting.
Functions
huber_loss (z)
|
Huber loss cost (reduces the weight of outliers) :type z: ndarray [Any , dtype [floating [Any ]]] :param z: Residuals between predicted and true values :rtype: float :return: Huber cost |
polynomial_1d (xx, *params)
|
N-order 1D polynomial. |
polynomial_2d (xx, *params)
|
N-order 2D polynomial. |
rmse (z)
|
Return root mean square error :type z: ndarray [Any , dtype [floating [Any ]]] :param z: Residuals between predicted and true value :rtype: float :return: Root Mean Square Error |
robust_nfreq_sumsin_fit (xdata, ydata[, ...])
|
Given 1D vectors x and y, compute a robust sum of sinusoid fit to the data. |
robust_norder_polynomial_fit (xdata, ydata[, ...])
|
Given 1D vectors x and y, compute a robust polynomial fit to the data. |
soft_loss (z[, scale])
|
Soft loss cost (reduces the weight of outliers) :type z: ndarray [Any , dtype [floating [Any ]]] :param z: Residuals between predicted and true values :type scale: float :param scale: Scale factor :rtype: float :return: Soft loss cost |
sumsin_1d (xx, *params)
|
Sum of N sinusoids in 1D. |