resample(x, num, t=None, axis=0, window=None, domain='time')

The resampled signal starts at the same value as x but is sampled with a spacing of len(x) / num * (spacing of x) . Because a Fourier method is used, the signal is assumed to be periodic.

Notes

The argument :None:None:`window` controls a Fourier-domain window that tapers the Fourier spectrum before zero-padding to alleviate ringing in the resampled values for sampled signals you didn't intend to be interpreted as band-limited.

If :None:None:`window` is a function, then it is called with a vector of inputs indicating the frequency bins (i.e. fftfreq(x.shape[axis]) ).

If :None:None:`window` is an array of the same length as :None:None:`x.shape[axis]` it is assumed to be the window to be applied directly in the Fourier domain (with dc and low-frequency first).

For any other type of :None:None:`window`, the function scipy.signal.get_window is called to generate the window.

The first sample of the returned vector is the same as the first sample of the input vector. The spacing between samples is changed from dx to dx * len(x) / num .

If t is not None, then it is used solely to calculate the resampled positions :None:None:`resampled_t`

As noted, resample uses FFT transformations, which can be very slow if the number of input or output samples is large and prime; see scipy.fft.fft .

Parameters

x : array_like

The data to be resampled.

num : int

The number of samples in the resampled signal.

t : array_like, optional

If t is given, it is assumed to be the equally spaced sample positions associated with the signal data in x.

axis : int, optional

The axis of x that is resampled. Default is 0.

window : array_like, callable, string, float, or tuple, optional

Specifies the window applied to the signal in the Fourier domain. See below for details.

domain : string, optional

A string indicating the domain of the input x: time Consider the input x as time-domain (Default), freq Consider the input x as frequency-domain.

Returns

resampled_x or (resampled_x, resampled_t)

Either the resampled array, or, if t was given, a tuple containing the resampled array and the corresponding resampled positions.

Resample x to :None:None:`num` samples using Fourier method along the given axis.

See Also

decimate

Downsample the signal after applying an FIR or IIR filter.

resample_poly

Resample using polyphase filtering and an FIR filter.

Examples

Note that the end of the resampled data rises to meet the first sample of the next cycle:

>>> from scipy import signal

>>> x = np.linspace(0, 10, 20, endpoint=False)
... y = np.cos(-x**2/6.0)
... f = signal.resample(y, 100)
... xnew = np.linspace(0, 10, 100, endpoint=False)

>>> import matplotlib.pyplot as plt
... plt.plot(x, y, 'go-', xnew, f, '.-', 10, y[0], 'ro')
... plt.legend(['data', 'resampled'], loc='best')
... plt.show()

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.signal._signaltools.decimate scipy.signal._signaltools.resample scipy.signal._signaltools.resample_poly

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