SciPy

This is documentation for an old release of SciPy (version 0.19.0). Read this page in the documentation of the latest stable release (version 1.14.1).

scipy.signal.decimate

scipy.signal.decimate(x, q, n=None, ftype='iir', axis=-1, zero_phase=None)[source]

Downsample the signal after applying an anti-aliasing filter.

By default, an order 8 Chebyshev type I filter is used. A 30 point FIR filter with Hamming window is used if ftype is ‘fir’.

Parameters:

x : ndarray

The signal to be downsampled, as an N-dimensional array.

q : int

The downsampling factor. For downsampling factors higher than 13, it is recommended to call decimate multiple times.

n : int, optional

The order of the filter (1 less than the length for ‘fir’). Defaults to 8 for ‘iir’ and 30 for ‘fir’.

ftype : str {‘iir’, ‘fir’} or dlti instance, optional

If ‘iir’ or ‘fir’, specifies the type of lowpass filter. If an instance of an dlti object, uses that object to filter before downsampling.

axis : int, optional

The axis along which to decimate.

zero_phase : bool, optional

Prevent phase shift by filtering with filtfilt instead of lfilter when using an IIR filter, and shifting the outputs back by the filter’s group delay when using an FIR filter. A value of True is recommended, since a phase shift is generally not desired. Using None defaults to False for backwards compatibility. This default will change to True in a future release, so it is best to set this argument explicitly.

New in version 0.18.0.

Returns:

y : ndarray

The down-sampled signal.

See also

resample
Resample up or down using the FFT method.
resample_poly
Resample using polyphase filtering and an FIR filter.

Notes

The zero_phase keyword was added in 0.18.0. The possibility to use instances of dlti as ftype was added in 0.18.0.

Previous topic

scipy.signal.hilbert2

Next topic

scipy.signal.detrend