scipy.signal.detrend(data, axis=-1, type='linear', bp=0)[source]

Remove linear trend along axis from data.

Parameters :

data : array_like

The input data.

axis : int, optional

The axis along which to detrend the data. By default this is the last axis (-1).

type : {‘linear’, ‘constant’}, optional

The type of detrending. If type == 'linear' (default), the result of a linear least-squares fit to data is subtracted from data. If type == 'constant', only the mean of data is subtracted.

bp : array_like of ints, optional

A sequence of break points. If given, an individual linear fit is performed for each part of data between two break points. Break points are specified as indices into data.

Returns :

ret : ndarray

The detrended input data.


>>> from scipy import signal
>>> randgen = np.random.RandomState(9)
>>> npoints = 1e3
>>> noise = randgen.randn(npoints)
>>> x = 3 + 2*np.linspace(0, 1, npoints) + noise
>>> (signal.detrend(x) - noise).max() < 0.01

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