pmdarima.utils.diff¶
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pmdarima.utils.diff(x, lag=1, differences=1)[source][source]¶
- Difference an array. - A python implementation of the R - difffunction [1]. This computes lag differences from an array given a- lagand- differencingterm.- If - xis a vector of length \(n\),- lag=1and- differences=1, then the computed result is equal to the successive differences- x[lag:n] - x[:n-lag].- Parameters: - x : array-like, shape=(n_samples, [n_features]) - The array to difference. - lag : int, optional (default=1) - An integer > 0 indicating which lag to use. - differences : int, optional (default=1) - An integer > 0 indicating the order of the difference. - Returns: - res : np.ndarray, shape=(n_samples, [n_features]) - The result of the differenced arrays. - References - [R93] - https://stat.ethz.ch/R-manual/R-devel/library/base/html/diff.html - Examples - Where - lag=1and- differences=1:- >>> x = c(10, 4, 2, 9, 34) >>> diff(x, 1, 1) array([ -6., -2., 7., 25.], dtype=float32) - Where - lag=1and- differences=2:- >>> x = c(10, 4, 2, 9, 34) >>> diff(x, 1, 2) array([ 4., 9., 18.], dtype=float32) - Where - lag=3and- differences=1:- >>> x = c(10, 4, 2, 9, 34) >>> diff(x, 3, 1) array([ -1., 30.], dtype=float32) - Where - lag=6(larger than the array is) and- differences=1:- >>> x = c(10, 4, 2, 9, 34) >>> diff(x, 6, 1) array([], dtype=float32) - For a 2d array with - lag=1and- differences=1:- >>> import numpy as np >>> >>> x = np.arange(1, 10).reshape((3, 3)).T >>> diff(x, 1, 1) array([[ 1., 1., 1.], [ 1., 1., 1.]], dtype=float32) 
