scipy.signal.deconvolve#

scipy.signal.deconvolve(signal, divisor)[source]#

Deconvolves divisor out of signal using inverse filtering.

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

Parameters

signalarray_like: Signal data, typically a recorded signal
divisorarray_like: Divisor data, typically an impulse response or filter that was applied to the original signal

Returns

quotientndarray: Quotient, typically the recovered original signal
remainderndarray: 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.])

scipy.signal.savgol_filter

scipy.signal.sosfilt