scipy.signal.deconvolve

scipy.signal.deconvolve(signal, divisor)

Deconvolves divisor out of signal using inverse filtering.

Returns the quotient and remainder such that signal = convolve(divisor, quotient) + remainder

Parameters:

signal : array_like

Signal data, typically a recorded signal

divisor : array_like

Divisor data, typically an impulse response or filter that was applied to the original signal

Returns:

quotient : ndarray

Quotient, typically the recovered original signal

remainder : ndarray

Remainder

See also

numpy.polydiv

performs polynomial division (same operation, but also accepts poly1d objects)

Examples

Deconvolve a signal that’s been filtered:

>>> from scipy import signal
>>> original = [0, 1, 0, 0, 1, 1, 0, 0]
>>> impulse_response = [2, 1]
>>> recorded = signal.convolve(impulse_response, original)
>>> recorded
array([0, 2, 1, 0, 2, 3, 1, 0, 0])
>>> recovered, remainder = signal.deconvolve(recorded, impulse_response)
>>> recovered
array([ 0.,  1.,  0.,  0.,  1.,  1.,  0.,  0.])