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Syto VS scipy.signal
Sashko edited this page Aug 31, 2019
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| Scipy functions | Description | Syto's analog |
|---|---|---|
| order_filter(a, domain, rank) | Perform an order filter on an N-dimensional array | To be developed |
| medfilt(volume[, kernel_size]) | Perform a median filter on an N-dimensional array | To be developed |
| medfilt2d(input[, kernel_size]) | Median filter a 2-dimensional array | To be developed |
| wiener(im[, mysize, noise]) | Perform a Wiener filter on an N-dimensional array | To be developed |
| symiirorder1(input, c0, z1 {, precision}) | Implement a smoothing IIR filter with mirror-symmetric boundary conditions using a cascade of first-order sections | To be developed |
| symiirorder2(input, r, omega {, precision}) | Implement a smoothing IIR filter with mirror-symmetric boundary conditions using a cascade of second-order sections | To be developed |
| lfilter(b, a, x[, axis, zi]) | Filter data along one-dimension with an IIR or FIR filter | YES |
| lfiltic(b, a, y[, x]) | Construct initial conditions for lfilter given input and output vectors | Implemented, to be public later |
| lfilter_zi(b, a) | Construct initial conditions for lfilter for step response steady-state | Implemented, to be public later |
| filtfilt(b, a, x[, axis, padtype, padlen, …]) | Apply a digital filter forward and backward to a signal | YES |
| savgol_filter(x, window_length, polyorder[, …]) | Apply a Savitzky-Golay filter to an array | To be developed |
| deconvolve(signal, divisor) | Deconvolves divisor out of signal using inverse filtering | To be developed |
| sosfilt(sos, x[, axis, zi]) | Filter data along one dimension using cascaded second-order sections | To be developed |
| sosfilt_zi(sos) | Construct initial conditions for sosfilt for step response steady-state | To be developed |
| sosfiltfilt(sos, x[, axis, padtype, padlen]) | A forward-backward digital filter using cascaded second-order sections | To be developed |
| hilbert(x[, N, axis]) | Compute the analytic signal, using the Hilbert transform | To be developed |
| hilbert2(x[, N]) | Compute the ‘2-D’ analytic signal of x | To be developed |
| decimate(x, q[, n, ftype, axis, zero_phase]) | Downsample the signal after applying an anti-aliasing filter | To be developed |
| detrend(data[, axis, type, bp, overwrite_data]) | Remove linear trend along axis from data | To be developed |
| resample(x, num[, t, axis, window]) | Resample x to num samples using Fourier method along the given axis | To be developed |
| resample_poly(x, up, down[, axis, window]) | Resample x along the given axis using polyphase filtering | To be developed |
| upfirdn(h, x[, up, down, axis]) | Upsample, FIR filter, and downsample | To be developed |
| Scipy functions | Description | Syto's analog |
|---|---|---|
| bilinear(b, a[, fs]) | Return a digital IIR filter from an analog one using a bilinear transform | Implemented, to be public later |
| bilinear_zpk(z, p, k, fs) | Return a digital IIR filter from an analog one using a bilinear transform | To be developed |
| findfreqs(num, den, N[, kind]) | Find array of frequencies for computing the response of an analog filter | To be developed |
| firls(numtaps, bands, desired[, weight, nyq, fs]) | FIR filter design using least-squares error minimization | To be developed |
| firwin(numtaps, cutoff[, width, window, …]) | FIR filter design using the window method | To be developed |
| firwin2(numtaps, freq, gain[, nfreqs, …]) | FIR filter design using the window method | To be developed |
| freqs(b, a[, worN, plot]) | Compute frequency response of analog filter | To be developed |
| freqs_zpk(z, p, k[, worN]) | Compute frequency response of analog filter | To be developed |
| freqz(b[, a, worN, whole, plot, fs]) | Compute the frequency response of a digital filter | To be developed |
| freqz_zpk(z, p, k[, worN, whole, fs]) | Compute the frequency response of a digital filter in ZPK form | To be developed |
| sosfreqz(sos[, worN, whole, fs]) | Compute the frequency response of a digital filter in SOS format | To be developed |
| group_delay(system[, w, whole, fs]) | Compute the group delay of a digital filter | To be developed |
| iirdesign(wp, ws, gpass, gstop[, analog, …]) | Complete IIR digital and analog filter design | To be developed |
| iirfilter(N, Wn[, rp, rs, btype, analog, …]) | IIR digital and analog filter design given order and critical points | YES |
| kaiser_atten(numtaps, width) | Compute the attenuation of a Kaiser FIR filter | To be developed |
| kaiser_beta(a) | Compute the Kaiser parameter beta, given the attenuation a | To be developed |
| kaiserord(ripple, width) | Determine the filter window parameters for the Kaiser window method | To be developed |
| minimum_phase(h[, method, n_fft]) | Convert a linear-phase FIR filter to minimum phase | To be developed |
| savgol_coeffs(window_length, polyorder[, …]) | Compute the coefficients for a 1-d Savitzky-Golay FIR filter | To be developed |
| remez(numtaps, bands, desired[, weight, Hz, …]) | Calculate the minimax optimal filter using the Remez exchange algorithm | To be developed |
| unique_roots(p[, tol, rtype]) | Determine unique roots and their multiplicities from a list of roots | To be developed |
| residue(b, a[, tol, rtype]) | Compute partial-fraction expansion of b(s) / a(s) | To be developed |
| residuez(b, a[, tol, rtype]) | Compute partial-fraction expansion of b(z) / a(z) | To be developed |
| invres(r, p, k[, tol, rtype]) | Compute b(s) and a(s) from partial fraction expansion | To be developed |
| invresz(r, p, k[, tol, rtype]) | Compute b(z) and a(z) from partial fraction expansion | To be developed |
| BadCoefficients | Warning about badly conditioned filter coefficients | To be developed |
| Lower-level filter design functions: | ||
| abcd_normalize([A, B, C, D]) | Check state-space matrices and ensure they are two-dimensional | To be developed |
| band_stop_obj(wp, ind, passb, stopb, gpass, …) | Band Stop Objective Function for order minimization | To be developed |
| besselap(N[, norm]) | Return (z,p,k) for analog prototype of an Nth-order Bessel filter | YES |
| buttap(N) | Return (z,p,k) for analog prototype of Nth-order Butterworth filter | YES |
| cheb1ap(N, rp) | Return (z,p,k) for Nth-order Chebyshev type I analog lowpass filter | YES |
| cheb2ap(N, rs) | Return (z,p,k) for Nth-order Chebyshev type I analog lowpass filter | YES |
| cmplx_sort(p) | Sort roots based on magnitude | To be developed |
| ellipap(N, rp, rs) | Return (z,p,k) of Nth-order elliptic analog lowpass filter | YES |
| lp2bp(b, a[, wo, bw]) | Transform a lowpass filter prototype to a bandpass filter | YES |
| lp2bp_zpk(z, p, k[, wo, bw]) | Transform a lowpass filter prototype to a bandpass filter | To be developed |
| lp2bs(b, a[, wo, bw]) | Transform a lowpass filter prototype to a bandstop filter | YES |
| lp2bs_zpk(z, p, k[, wo, bw]) | Transform a lowpass filter prototype to a bandstop filter | To be developed |
| lp2hp(b, a[, wo]) | Transform a lowpass filter prototype to a highpass filter | YES |
| lp2hp_zpk(z, p, k[, wo]) | Transform a lowpass filter prototype to a highpass filter | To be developed |
| lp2lp(b, a[, wo]) | Transform a lowpass filter prototype to a different frequency | YES |
| lp2lp_zpk(z, p, k[, wo]) | Transform a lowpass filter prototype to a different frequency | To be developed |
| normalize(b, a) | Normalize numerator/denominator of a continuous-time transfer function | Implemented, to be public later |