# scipy.signal.detrend

scipy.signal.detrend(data, axis=- 1, type='linear', bp=0, overwrite_data=False)

  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. This parameter only has an effect when `type == 'linear'`.

    overwrite_data bool, optional

      If True, perform in place detrending and avoid a copy. Default is False

  Returns
    ret ndarray

      The detrended input data.

  Examples

      >>> from scipy import signal
      >>> from numpy.random import default_rng
      >>> rng = default_rng()
      >>> npoints = 1000
      >>> noise = rng.standard_normal(npoints)
      >>> x = 3 + 2*np.linspace(0, 1, npoints) + noise
      >>> (signal.detrend(x) - noise).max()
      0.06  # random

scipy.signal.decimate scipy.signal.resample