Gammatone(freq, ftype)Ĭompute the group delay of a digital filter. Return a digital IIR filter from an analog one using a bilinear transform.įind array of frequencies for computing the response of an analog filter.įirls(numtaps, bands, desired)įIR filter design using least-squares error minimization.įirwin(numtaps, cutoff)įIR filter design using the window method.įirwin2(numtaps, freq, gain)Ĭompute frequency response of analog filter.įreqz(b)Ĭompute the frequency response of a digital filter.Ĭompute the frequency response of a digital filter in ZPK form.Ĭompute the frequency response of a digital filter in SOS format. Resample x along the given axis using polyphase filtering. Resample x to num samples using Fourier method along the given axis. Remove linear trend along axis from data. Sosfiltfilt(sos, x)Ī forward-backward digital filter using cascaded second-order sections.Ĭompute the analytic signal, using the Hilbert transform.ĭecimate(x, q)ĭownsample the signal after applying an anti-aliasing filter.ĭetrend(data) Savgol_filter(x, window_length, polyorder)Īpply a Savitzky-Golay filter to an array.ĭeconvolves divisor out of signal using inverse filtering.įilter data along one dimension using cascaded second-order sections.Ĭonstruct initial conditions for sosfilt for step response steady-state. This implements the following transfer function.įilter data along one-dimension with an IIR or FIR filter.Ĭonstruct initial conditions for lfilter given input and output vectors.Ĭonstruct initial conditions for lfilter for step response steady-state.įiltfilt(b, a, x)Īpply a digital filter forward and backward to a signal. The second section uses a reversed sequence. Implement a smoothing IIR filter with mirror-symmetric boundary conditions using a cascade of second-order sections. This implements a system with the following transfer function and mirror-symmetric boundary conditions. Implement a smoothing IIR filter with mirror-symmetric boundary conditions using a cascade of first-order sections. Perform a Wiener filter on an N-dimensional array.

Perform a median filter on an N-dimensional array. Smoothing spline (cubic) filtering of a rank-2 array. Gaussian approximation to B-spline basis function of order n.Ĭompute cubic spline coefficients for rank-1 array.Ĭompute quadratic spline coefficients for rank-1 array.Ĭoefficients for 2-D cubic (3rd order) B-spline.Ĭoefficients for 2-D quadratic (2nd order) B-spline:Įvaluate a cubic spline at the new set of points.Įvaluate a quadratic spline at the new set of points. Signal processing ( scipy.signal) # Convolution #Ĭross-correlate two N-dimensional arrays.Ĭonvolve two N-dimensional arrays using FFT.Ĭonvolve two N-dimensional arrays using the overlap-add method.Ĭonvolve2d(in1, in2)Ĭorrelate2d(in1, in2)Ĭross-correlate two 2-dimensional arrays.Ĭonvolve with a 2-D separable FIR filter.Ĭhoose_conv_method(in1, in2)įind the fastest convolution/correlation method.Ĭorrelation_lags(in1_len, in2_len)Ĭalculates the lag / displacement indices array for 1D cross-correlation.

Statistical functions for masked arrays (

K-means clustering and vector quantization (

Matlab line style sweep