diff --git a/applications/lofar2/model/pfb_os/README.txt b/applications/lofar2/model/pfb_os/README.txt new file mode 100644 index 0000000000000000000000000000000000000000..011e8e527f7a9c931c0aa558bcd8e995450ccd87 --- /dev/null +++ b/applications/lofar2/model/pfb_os/README.txt @@ -0,0 +1,34 @@ +Author: Eric Kooistra, nov 2023 + +* Practise DSP [1]. + +* Try to reproduce LOFAR subband filter FIR coefficients using scipy instead + of MATLAB. + The pfs_coeff_final.m from the Filter Task Force (FTF) in 2005 use fircls1 + with r_pass and r_stop to define the ripple. In addition it post applies a + Kaiser window with beta = 1 to make the filter attenuation a bit more deep + near the transition. The pfir_coeff.m from Apertif also uses fircls1. + Both use fircls1 with N = 1024 FIR coefficients and then Fourier + interpolation to achieve Ncoefs = 1024 * 16 FIR coefficients. Both scripts + can not exactly reproduce the actual LOFAR1 coefficients, therefore these + are loaded from a file Coeffs16384Kaiser-quant.dat + +* Try low pass filter design methods using windowed sync, firls, remez [3] + The windowed sync method, firls leased squares method and remez method all + yield comparable results, but firls and remez perform slightly better near + the transition band. The firls and remez functions from scipy.signal use + transition bandwidth and weights between pass and stop band to influence + the transition region and ripple. For remez the ripple is constant in the + pass band and stop band, for firls the ripple is largest near the band + transition. + +* It is possible to design a good FIR filter using Python scipy. Possibly with + some extra help of a filter design and analysis (FDA) tool like pyfda [2]. + +[1] dsp_study_erko.txt, summary of DSP books +[2] pyfda, dsp, at https://github.com/chipmuenk +[3] Try FIR filter design methods + * dsp.py import for Python jupyter notebooks + * filter_design_firls.ipynb + * filter_design_remez.ipynb + * filter_design_windowed_sync.ipynb diff --git a/applications/lofar2/model/pfb_os/dsp.py b/applications/lofar2/model/pfb_os/dsp.py new file mode 100644 index 0000000000000000000000000000000000000000..c30de5e7f01d30f7cb67ac560d3e5c274d1e9ab8 --- /dev/null +++ b/applications/lofar2/model/pfb_os/dsp.py @@ -0,0 +1,354 @@ +#! /usr/bin/env python3 +############################################################################### +# +# Copyright 2022 +# ASTRON (Netherlands Institute for Radio Astronomy) <http://www.astron.nl/> +# P.O.Box 2, 7990 AA Dwingeloo, The Netherlands +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +############################################################################### + +# Author: Eric Kooistra +# Purpose: Utilities and functions for DSP +# Description: + + +import numpy as np +import matplotlib.pyplot as plt + + +c_interpolate = 10 +c_atol = 1e-15 +c_rtol = 1e-8 # 1/2**32 = 2.3e-10 + + +############################################################################### +# Utilities +############################################################################### + +def ceil_div(num, den): + """ Return integer ceil value of num / den """ + return int(np.ceil(num / den)) + + +def ceil_log2(num): + """ Return integer ceil value of log2(num) """ + return int(np.ceil(np.log2(num))) + + +def ceil_pow2(num): + """ Return power of 2 value that is equal or greater than num """ + return 2**ceil_log2(num) + + +def pow_db(volts): + """Voltage to power in dB""" + return 20 * np.log10(np.abs(volts) + c_atol) + + +def is_even(n): + """Return True if n is even, else False when odd.""" + return n % 2 == 0 + + +def is_symmetrical(x, anti=False): + """Return True when x[n] = +-x[N-1 - n], within tolerances, else False.""" + rtol = c_rtol + atol = np.min(np.abs(x[np.nonzero(x)])) * rtol + n = len(x) + h = n // 2 + if is_even(n): + if anti: + return np.allclose(x[0:h], np.flip(-x[h:]), rtol=rtol, atol=atol) + else: + return np.allclose(x[0:h], np.flip(x[h:]), rtol=rtol, atol=atol) + else: + if anti: + return np.allclose(x[0:h], np.flip(-x[h + 1:]), rtol=rtol, atol=atol) and np.abs(x[h]) < atol + else: + return np.allclose(x[0:h], np.flip(x[h + 1:]), rtol=rtol, atol=atol) + + +def read_coefficients_file(filepathname): + coefs = [] + with open(filepathname, 'r') as fp: + for line in fp: + if line.strip(): # skip empty line + s = int(line) # one coef per line + coefs.append(s) + return coefs + + +############################################################################### +# Filter design +############################################################################### + +def ideal_low_pass_filter(Npoints, Npass, bandEdgeGain=1.0): + """Derive FIR coefficients for prototype low pass filter using ifft of + magnitude frequency response. + + Input: + - Npoints: Number of points of the DFT in the filterbank + - Npass: Number of points with gain > 0 in pass band + - bandEdgeGain : Gain at band edge + Return: + - h: FIR coefficients from impulse response + . f: normalized frequency axis for HF, fs = 1 + - HF: frequency transfer function of h + """ + # Magnitude frequency reponse + HF = np.zeros([Npoints]) + HF[0] = bandEdgeGain + HF[1 : Npass - 1] = 1 + HF[Npass - 1] = bandEdgeGain + # Zero center HF to make it even + HF = np.roll(HF, -(Npass // 2)) + f = np.arange(0, 1, 1 / Npoints) + # Filter impulse response + h = np.fft.ifft(HF).real # imag is 0 for even HF + h = np.roll(h, Npoints // 2) + return h, f, HF + + +def fourier_interpolate(HFfilter, Ncoefs): + """Use Fourier interpolation to create final FIR filter coefs. + + HF contains filter transfer function for N points, in order 0 to fs. The + interpolation inserts Ncoefs - N zeros and then performs IFFT to get the + interpolated impulse response. + + Use phase correction depenent on interpolation factor Q to have fractional + time shift of hInterpolated, to make it symmetrical. Similar as done in + pfs_coeff_final.m and pfir_coeff.m. Use upper = conj(lower), because that + is easier than using upper from HFfilter. + """ + N = len(HFfilter) + K = N // 2 + + # Interpolation factor Q can be fractional, for example: + # - Ncoefs = 1024 * 16 + # . firls: N = 1024 + 1 --> Q = 15.98439 + # . remez: N = 1024 --> Q = 16 + Q = Ncoefs / N + + # Apply phase correction (= time shift) to make the impulse response + # exactly symmetric + f = np.arange(N) / Ncoefs + p = np.exp(-1j * np.pi * (Q - 1) * f) + HF = HFfilter * p + + HFextended = np.zeros(Ncoefs, dtype=np.complex_) + if is_even(N): + # Copy DC and K - 1 positive frequencies in lower part (K values) + HFextended[0:K] = HF[0:K] # starts with DC at [0] + # Create the upper part of the spectrum from the K - 1 positive + # frequencies and fs/2 in lower part (K values) + HFflip = np.conjugate(np.flip(HF[0:K + 1])) # contains DC at [0] + HFextended[-K:] = HFflip[0:K] # omit DC at [K] + # K + K = N values, because N is even and K = N // 2 + else: + # Copy DC and K positive frequencies in lower part (K + 1 values) + HFextended[0:K + 1] = HF[0:K + 1] # starts with DC at [0] + # Create the upper part of the spectrum from the K positive + # frequencies in the lower part (K values) + HFflip = np.conjugate(np.flip(HF[0:K + 1])) # contains DC at [0] + HFextended[-K:] = HFflip[0:K] # omit DC at [K] + # K + 1 + K = N values, because N is odd and K = N // 2 + hInterpolated = np.fft.ifft(HFextended) + if np.allclose(hInterpolated.imag, np.zeros(Ncoefs), rtol=c_rtol, atol=c_atol): + print('hInterpolated.imag ~= 0') + else: + print('WARNING: hInterpolated.imag != 0 (max(abs) = %f)' % np.max(np.abs(hInterpolated.imag))) + return hInterpolated.real + + +############################################################################### +# DFT +############################################################################### + +def dtft(coefs, Ndtft=None, zeroCenter=True, fftShift=True): + """Calculate DTFT of filter impulse response or window. + + Use DFT with Ndtft points, to have frequency resolution of 2 pi / Ndtft. + Define h by extending coefs with Ndtft - M zeros, where M = len(coefs). + This DFT approaches the DTFT using bandlimited interpolation, similar to + INTERP() which interpolates by factor L = Ndtft / M [JOS1]. + + Input: + . coefs: filter impulse response or window coefficients + . Ndtft: number of points in DFT to calculate DTFT + . zeroCenter: when True zero center h to have even function that aligns + with cos() in DTFT, for zero-phase argument (+-1 --> 0, +-pi). Else + apply h as causal function. + . fftShift: when True fft shift to have -0.5 to +0.5 frequency axis, + else use 0 to 1.0. + Return: + . h: zero padded coefs + . f: normalized frequency axis for HF, fs = 1 + . HF: dtft(h), the frequency transfer function of h + """ + M = len(coefs) + if Ndtft is None: + Ndtft = ceil_pow2(M * c_interpolate) + # Time series, causal with coefs at left in h + h = np.concatenate((coefs, np.zeros([Ndtft - M]))) + if zeroCenter: + # Zero center h to try to make it even + h = np.roll(h, -(M // 2)) + # DFT + HF = np.fft.fft(h) + # Normalized frequency axis, fs = 1, ws = 2 pi + f = np.arange(0, 1, 1 / Ndtft) # f = 0,pos, neg + if fftShift: + # FFT shift to center HF, f = neg, 0,pos + f = f - 0.5 + HF = np.roll(HF, Ndtft // 2) + return h, f, HF + + +############################################################################### +# Plotting +############################################################################### + +def plot_time_response(h, markers=False): + """Plot time response (= impulse response, window, FIR filter coefficients). + + Input: + . h: time response + . markers: when True plot time sample markers in curve + """ + if markers: + plt.plot(h, '-', h, 'o') + else: + plt.plot(h, '-') + plt.title('Time response') + plt.ylabel('Voltage') + plt.xlabel('Sample') + plt.grid(True) + + +def plot_spectra(f, HF, fs=1.0, fLim=None, dbLim=None): + """Plot spectra for power, magnitude, phase, real, imag + + Input: + . f: normalized frequency axis for HF (fs = 1) + . HF: spectrum, e.g. frequency transfer function HF = DTFT(h) + . fs: sample frequency in Hz, scale f by fs, fs >= 1 + """ + Hmag = np.abs(HF) + Hphs = np.angle(HF) + Hpow_dB = pow_db(HF) # power response + fn = f * fs + if fs > 1: + flabel = 'Frequency [fs / %d]' % fs + else: + flabel = 'Frequency [fs]' + + plt.figure(1) + plt.plot(fn, Hpow_dB) + plt.title('Power spectrum') + plt.ylabel('Power [dB]') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + if dbLim: + plt.ylim(dbLim) + plt.grid(True) + + plt.figure(2) + plt.plot(fn, HF.real, 'r') + plt.plot(fn, HF.imag, 'g') + plt.title('Complex voltage spectrum') + plt.ylabel('Voltage') + plt.xlabel(flabel) + plt.legend(['real', 'imag']) + if fLim: + plt.xlim(fLim) + plt.grid(True) + + plt.figure(3) + plt.plot(fn, Hmag) + plt.title('Magnitude spectrum') # = amplitude + plt.ylabel('Voltage') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + plt.grid(True) + + plt.figure(4) + plt.plot(fn, Hphs) + plt.title('Phase spectrum (note -1: pi = -pi)') + plt.ylabel('Phase [rad]') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + plt.grid(True) + + +def plot_power_spectrum(f, HF, fmt='r', fs=1.0, fLim=None, dbLim=None, showRoll=False): + """Plot power spectrum + + Input: + . f: normalized frequency axis for HF (fs = 1) + . HF: spectrum, e.g. frequency transfer function HF = DTFT(h) + . fmt: curve format string + . fs: sample frequency in Hz, scale f by fs, fs >= 1 + """ + if fs > 1: + flabel = 'Frequency [fs / %d]' % fs + else: + flabel = 'Frequency [fs]' + + plt.plot(f * fs, pow_db(HF), fmt) + plt.title('Power spectrum') + plt.ylabel('Power [dB]') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + if dbLim: + plt.ylim(dbLim) + plt.grid(True) + + +def plot_two_power_spectra(f1, HF1, name1, f2, HF2, name2, fs=1.0, fLim=None, dbLim=None, showRoll=False): + """Plot two power spectra in same plot for comparison + + Input: + . f1,f2: normalized frequency axis for HF1, HF2 (fs = 1) + . HF1, HF2: spectrum, e.g. frequency transfer function HF = DTFT(h) + . fs: sample frequency in Hz, scale f by fs, fs >= 1 + """ + if fs > 1: + flabel = 'Frequency [fs / %d]' % fs + else: + flabel = 'Frequency [fs]' + + if showRoll: + plt.plot(f1 * fs, pow_db(HF1), 'r', + f1 * fs, np.roll(pow_db(HF1), len(f1) // 2), 'r--', + f2 * fs, pow_db(HF2), 'b', + f2 * fs, np.roll(pow_db(HF2), len(f2) // 2), 'b--') + plt.legend([name1, '', name2, '']) + else: + plt.plot(f1 * fs, pow_db(HF1), 'r', + f2 * fs, pow_db(HF2), 'b') + plt.legend([name1, name2]) + plt.title('Power spectrum') + plt.ylabel('Power [dB]') + plt.xlabel(flabel) + if fLim: + plt.xlim(fLim) + if dbLim: + plt.ylim(dbLim) + plt.grid(True) diff --git a/applications/lofar2/model/pfb_os/dsp_study_erko.txt b/applications/lofar2/model/pfb_os/dsp_study_erko.txt new file mode 100644 index 0000000000000000000000000000000000000000..8964b652a7eb89cdff9ce8090a012ed22072bcd2 --- /dev/null +++ b/applications/lofar2/model/pfb_os/dsp_study_erko.txt @@ -0,0 +1,374 @@ +############################################################################### +# Copyright 2023 +# ASTRON (Netherlands Institute for Radio Astronomy) <http://www.astron.nl/> +# P.O.Box 2, 7990 AA Dwingeloo, The Netherlands +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +############################################################################### +# +# Author: Eric Kooistra +# Purpose: DSP theory summary +# +# References: +# +# * [LYONS] Understanding Digital Signal Processing, 3rd edition +# * [PROAKIS] Digital Signal Processing, 3rd edition +# * [HARRIS] Multirate Signal Processing for Communication Systems +# * [CROCHIERE] Multirate Signal Processing +# * [JOS1] Mathematics of the Discrete Fourier Transform +# * [JOS2] Introduction to Digital Filters +# * [JOS3] Physical Audio Signal Processing +# * [JOS4] Spectral Audio Signal Processing +# + +1) Linear Time Invariant (LTI) system [LYONS 1.6] + +- Time shift in input causes equal time shift in output. +- Order of sequential LTI operations can be rearranged with no change in final + output +- LTI output is linear combination (weighted sum) of delayed copies of the + input signal [JOS1 4.3.11] +- Transforms use discrete or continuous range of complex phasors [JOS1 4.3.12] + * For causal signals x(n) = 0 for n < 0, yields unilateral (one sided) + transforms. Used to solve difference equations with initial conditions + [PROAKIS 3.5]. Only unique for causal signals, because these are 0 for + n < 0. + * DFT: Every signal x(n) can be expressed as a linear combination of complex + sinusoids W_N^kn = exp(j w_k t_n). The coefficients of projecting x(n) on + W_N^kn for n = 0,1,...,N-1 yield the DFT of x is X(k) for k = 0,1,...,N-1. + * DTFT: For N --> inf, linear combination of exp(j w t_n) = exp(j w T)^n + * z-transform: linear combination of z^n. Generalization (analytic + continuation) of the DTFT on the unit circle in the complex plane, to the + entire complex z-plane. + * FT: integral 0 --> inf, linear combination of exp(j w t) + * Laplace transform: integral 0 --> inf, linear combination of exp(s t), + s = o + jw, so analytic continuation of FT (on jw axis) to the s-plane. +- Analogue (Laplace) and digital (z) complex planes [JOS1 4.3.13] + . Transform of growing functions, important for transient behaviour and + stability analysis + . Poles and zeros, frequency reponse z = exp(jw) [PROAKIS 4.4.6] + . Laplace: Every point in s-plane corresponds to a complex sinusoid + A exp(s t), t >= 0. Frequency axis s = j w + . Z: Every point in z-plane corresponds to sampled z = exp(s T), z^n + +- FT, DTFT, DFT [MATLAB sinusoids-and-fft-frequency-bins.m] + . Fourier transform (FT): continuous time <-> continuous frequency + . Discrete-time Fourier transform (DTFT): discrete time <-> continuous + frequency. If there is no aliasing, then the DTFT is the same as the + Fourier transform up to half the sampling frequency. + . Discrete Fourier transform (DFT): discrete time <-> discrete frequency. + For a signal that is nonzero only in the interval 0 <= n < N, an Ndtft + point DFT exactly samples the DTFT when N_dtft >= N. + +- Transforms are used because the time-domain mathematical models of systems + are generally complex differential equations. Transforming these complex + differential equations into simpler algebraic expressions makes them much + easier to solve. Once the solution to the algebraic expression is found, + the inverse transform will give you the time-domain repsponse. + . Fourier is a subset of Laplace. Laplace is a more generalized transform. + Fourier is used primarily for steady state signal analysis, while Laplace + is used for transient signal analysis. Laplace is good at looking for the + response to pulses, step functions, delta functions, while Fourier is + good for continuous signals. + Many of the explanations just mention that the relationship between the + Laplace and Fourier transforms is that s = o + jw, so the Fourier + transform becomes a special case of the laplace transform. Better + explanations deals that Laplace is used for stability studies and Fourier + is used for sinusoidal responses of systems. Systems are stable if the + real part of s is negative, that is to say there is a transient that will + vanish in time, in those cases, it is enough to use Fourier. Of course + you will lose the insight of the transient part. Laplace should be able to + determine the full response of a system, be it stable or unstable, + including transient parts. + +2) Windows [JOS4 3] +- Tabel [PROAKIS 8.2.2] +- Rectangular window with length M [LYONS 3.13] + . Dirichlet kernel or aliased sinc: + HF(m) = c sin(pi * m * M / Ndtft) / sin(pi * m / Ndtft) + . Ndtft = M yields all-ones form that defines the DFT frequency response + to an input sinusoidal and it is also the of a single DFT bin: + HF(m) = sin(pi * m) / sin(pi * m / M) + ~= Ndtft * sinc(pi * m) for Ndtft = M >~ 10 +- Properties of rectangular window with M points from [JOS4 3.1.2]: + . Zero crossings at integer multiples of 2 pi / M = Ndtft / M [LYONS Eq. + 3.45] + . Main lobe width is 4 pi / M + . As M increases, the main lobe narrows (better frequency resolution). + . M has no effect on the height of the side lobes (same as the Gibbs + phenomenon for truncated Fourier series expansions. + . First side lobe only 13 dB down from the main-lobe peak. + . Side lobes roll off at approximately 6dB per octave. + . A phase term arises when we shift the window to make it causal, while + the window transform is real in the zero-phase case (i.e., centered + about time 0). + +3) Low pass filter (LPF) +- Design parameters [JOS4 4.2] + . Pass band edge frequency: w_pass + . Pass band ripple (allowed gain deviation): + r_pass = 10**(r_pass_dB / 20) - 1 + . Stop band edge frequency: w_stop + . Stop band ripple (allowed leakage level): + r_stop = 10**(r_stop_dB / 20) +- Ideal LPF [JOS4 4.1] + . w_cutoff = w_pass = w_stop, r_pass = r_stop = 0 + . sinc(t) = sin(pi t) / (pi t) [JOS4 3.1, numpy) + . h_ideal(n) = 2 f_c sinc(2 f_c n), n in Z + - f_c is normalized cutoff frequency with fs = 1 +- LPF FIR filter design [LYONS 5.3] + . Methods based on desired response characteristics [MNE]: + - Frequency-domain design (construct filter in Fourier domain and use an + IFFT to invert it, MATLAB fir2) + - Windowed FIR design (scipy.signal.firwin(), firwin2(), and MATLAB fir1 + with default Hamming) + - Least squares designs (scipy.signal.firls(), MATLAB firls, fircls1) + . firls = least squares + . fircls, fircls1 = constrained ls with pass, stop ripple + - The Remez or Parks-McClellan algorithm (scipy.signal.remez(), MATLAB + firpm) + . MATLAB filters yield n + 1 coefs + . LS and Remez can do bandpass (= flat), differentiator, hilbert + . Linear phase filter types (filter order is Ntaps - 1, fNyquist = f2/2): + Type Ntaps Symmetry H(0) H(fs/2) + I Odd Even any any --> LPF, HPF + II Even Even any 0 --> LPF + III Odd Odd 0 0 --> differentiator, hilbert + IV Even Odd 0 any --> differentiator, hilbert + +2) Finite Impulse Response (FIR) filters +- FIR filters perform time domain Convolution by summing products of shifted + input samples and a sequence of filter coefficients [LYONS 5.2]. +- Convolution equation [LYONS Eq. 5.6]: + + N-1 + y(n) = sum h(k)(x(n-k) = h(k) * x(n) + k=0 + +- Impulse response h(k) are the FIR filter coefficients: + + x(n) --> x(n-1) --> ... --> x(N-1) --\ + | | | + h(0) h(1) h(N-1) + \----------\-- ... ------------\--> + --> y(n) + +- Convolution in time domain is equivalent to multiplication in frequency + domain + y(n) = h(k) * x(n) ==> DFT ==> Y(m) = H(m) X(m) + +- Number of FIR coefficients (Ntaps) + . Trade window main-lobe width for window side-lobe levels and in turn filter + transition bandwidth and side-lobe levels + . Transition bandwidth: df = fstop - fpass + . Window based design [HARRIS 3.2, LYONS 5.10.5]: + - Ntaps ~= fs / df * (Atten(dB) - 8) / 14 + . Remez = Parks-McClellan [HARRIS 3.3, LYONS 5.6]: + - yield a Chebychev-type filter + - Steeper transition than window based, but constant stopband peak levels + - Ntaps = f(fs, fpass, fstop, passband ripple +-d1, stopband ripple +-d2) + ~= fs / df * Atten(dB) / 22 + +- Linear phase FIR filter + . Even or odd symmetrical h(n) = +-h(M - 1 - n), n = 0,1,...,N-1 + [PROAKIS 8.2.1]. Reason for using FIR [LYONS 5.10.3] + . Group delay (= envelope delay[LYONS 5.8]) of symmetrical FIR filter is: + G = (N_taps - 1) / 2 [Ts] [LYONS 5.10.3] + . Design using windowed sinc, because windows are symmetrical [PROAKIS 8.2.2, + LYONS 5.3.2, DSPGUIDE 16] + +- Half band FIR filter [LYONS 5.7] + . Symmetrical frequency response about fs / 2, so fpass + fstop = fs / 2 + . When Ntaps is odd, then half of the coefs are 0. + + +3) Discrete Fourier Transform (DFT) +- The N roots of unity [JOS1 3.12, 5.1, PROAKIS 5.1.3, LYONS 4.3]. Note JOS + uses +j in W_N because inproduct is with conj(W_N), others use -j because + then W_N can be used directly in equation and matrix: + + W_N = exp(-j 2pi / N) is primitive Nth root of unity + W_N^k = exp(-j 2pi k / N) + W_N^kn = exp(-j 2pi k / N * n) = exp(-j w_k * t_n) + . w_k = k 2pi fs / N + . t_n = n Ts + . fs / N is the frequency sampling interval in Hz + . Ts = 1 / fs is time sampling interval in seconds + . ws = 2pi fs is the frequency sampling interval in rad/s + +- Normalized frequency axis [LYONS 3.5, 3.13.4]: + . fs = 1, ws = 2pi fs = 2pi + . -fs/2, 0, fs/2 [Hz] + -pi, 0, pi [rad] + -0.5, 0, 0.5 [fs] + . N even, e.g. N = 4: + + <------ N = 4 -------> + 0 fs/2 ( fs ) + | | ( | ) + n = 0 1 2 3 ( | ) + 0/4 1/4 2/4 3/4 ( 4/4 ) + DC positive | negative + | + \--> fftshift([0, 1, 2, 3]) = [2, 3, 0, 1] + + . N odd, e.g. N = 5: + <------- N = 5 --------> + 0 fs/2 ( fs ) + | | ( | ) + n = 0 1 2 | 3 4 ( | ) + 0/5 1/5 2/5 | 3/5 4/5 ( 5/5 ) + DC positive | negative + | + \-->fftshift([0, 1, 2, 3, 5]) = [3, 4, 0, 1, 2] + + . With K = N // 2: + . N even : DC, K - 1 positive, fs/2, K - 1 negative frequencies + . N odd : DC, K positive, K negative frequencies + +- The DFT project a length N signal x on a set of N sampled complex sinusoids + that are generated by the Nth roots of unity [JOS4 6.1]. These sinusoids form + an orthogonal basis and are the only frequencies that have a whole number of + periods in N samples [JOS1 6.2]. + +- Discrete Fourier Transform of x(n), n, k = 0,1,...,N-1 [JOS1 5.1, 6.6, 7.1], + [PROAKIS 5.1.2, 5.1.3]: + + N-1 + X(w_k) = X(k) = sum x(n) W_N^kn + n=0 exp(-j w_k t_n) + exp(-j 2pi k n / N) + Inverse DFT: + + N-1 + x(n) = 1/N sum X(k) exp(+j w_k t_n) + k=0 s_k(n) + with: + . s_k(n) = exp(+j w_k t_n) + +- Matrix formulation, DFT as linear transformation [JOS1, PROAKIS 5.1.3]: + + DFT: + XN = WN xN + + |X(0) | |1 1 1 ... 1 | |x(0) | + |X(1) | |1 W_N W_N^2 ... W_N^(N-1) | |x(1) | + |X(2) | = |1 W_N^2 W_N^4 ... W_N^2(N-1) | |x(2) | + |... | |... ... | |... | + |X(N-1)| |1 W_N^(N-1) W_N^2(N-1) ... W_N^(N-1)(N-1)| |x(N-1)| + + IDFT: + xN = WN^-1 XN = 1/N conj(WN) XN, so + + WN conj(WN) = N IN, where IN i N x N identity matrix + +- Real input: X(k) = conj(X(N - k)) + +- Spectral leakage or cross-talk occurs for frequencies other then w_k, because + this cause truncation distortian in the periodic extension of x(n) = + x(n + mN) [JOS1 7.1.2]. + +- DTFT Ndtft >= N [LYONS 3.11, JOS1 7.2.9] + . Zero padding N to Ndtft increases the interpolation density, but does not + increase the frequency resolution in the ability to resolve, to distinguish + between closely space features in the spectrum. The frequency resolution + can only be increased by increasing N +- N point DFT of rectangular function yields aliased sinc (= Dirchlet kernel): + + x(n) = 1 for K samples + X(m) = c sin(pi * m * K / N) / sin(pi * m / N) + + . c = 1 for symmetric rect -(K-1)/2 to + (K-1)/2 + . m = 0: X(0) = K + . m first zero crossing = N / K --> main lobe width is 2N / K + . K = N yields all-ones form that defines the DFT frequency response + to an input sinusoidal and it is also the of a single DFT bin: + X(m) = sin(pi * m) / sin(pi * m / K) + ~= K * sinc(pi * m) for K = N >~ 10 + +4) Multirate processing: +- Linear Time Variant (LTV) process, because it depends on when the + downsampling and upsampling start. +- Polyphase filtering ensures that only the values that remain are calculated, + so there are D or U phases [LYONS 10.7]. The LPF with all phases is called + the protype filter. +- For large D or U use two stage D = D1 * D2 or U = U1 * U2, where D1 > D2 and + U1 < U2 [LYONS 10.8.2] + +LPF + downsampling = decimation: +- Do not calculate samples that will be thrown away. +- Discarding samples folds the spectrum, first the LPF has to remove all + folds. + +Upsampling + LPF = interpolation: +- Do not calculate samples that will be inserted as zeros. +- Inserting zeros replicates the spectrum, the LPF remove all replicas and by + that it interpolates to fill in the zeros. +- Using zero order hold would be a naive approach, because then all samples + need to be calculated and the LPF then needs to compensate for the non-flat + pass band of sin(x)/x [LYONS 10.5.1] + + +5) Signal operators [JOS1 7.2] + +- Operator(x) is element of C^N for all x element of C^N + . assume modulo N indexing for n in x(n), so x(n) = x(n + mN) or periodic + extension +- FLIP_n(x) = x(-n) reversal + . x(0) = x(-0) + . x(-n) = x(N - n) for modulo N +- SHIFT_L,n(x) = x(n - L) + +- ZEROPAD_M,m(x) = x(n) for |m| < N / 2 + = 0 else + . zero centered, zero-phase, periodic + . ZEROPAD_10([1,2,3,4]) = [1,2,0,0,0,0,0,0,3,4] + . ZEROPAD_10([1,2,3,4,5]) = [1,2,3,0,0,0,0,0,4,5] +- CAUSALZEROPAD_M,m(x) = x(n) for m < N + = 0 for N < m < M + . CAUSALZEROPAD_10([1,2,3,4]) = [1,2,3,4,0,0,0,0,0,0] +- INTERP_L,k'(X) = X(w_k'), for X(w_k) with k = 0,1,...,N-1, where: + w_k' = 2pi k' / M, k' = 0,1,...,M-1 + M = L * N + . Interpolates a signal by factor L using bandlimited interpolation + +- STRETCH_L,m(x) = x(n) for n = m / L is an integer + = 0 else + . Upsampling by inserting L-1 zeros after every x sample +- REPEAT_L,m(x) = x(m), where: + m = 0,1,...,M-1 and M = L * N and n = m modulo N + . REPEAT_2([1,2,3,4]) = [1,2,3,4,1,2,3,4] +- DOWNSAMPLE_L,m = x(mL), where N = L * M and m = 0,1,...,M-1 + . DOWNSAMPLE_L(STRETCH_L(x) = x + . DOWNSAMPLE_2([1,2,3,4,5,6]) = [1,3,5] + L-1 +- ALIAS_L,m(x) = sum x(m + lM), with m = 0,1,...,M-1 and N = L*M + l=0 + . ALIAS_3([1,2,3,4,5,6] = [1,2] + [3,4] + [5,6] = [9,12] + +- DFT_N,k(x) = X(k) with N points +- DFT relations: + . STRETCH_L <==> REPEAT_L + . DOWNSAMPLE_L(x) <==> 1/L * ALIAS_L(X) [JOS1 7.4.11] + . ZEROPAD_LN(x) <==> INTERP_L(X) [JOS1 7.4.12] + . conj(x) <==> FLIP(conj(X)) + . FLIP(conj(x)) <==> conj(X) + . FLIP(x) <==> FLIP(X) + . x even <==> X even + . SHIFT_L(x) <==> exp(-j w_k L) X(k) + + + +https://learning.anaconda.cloud/ +https://realpython.com/python-scipy-fft/ + +https://mne.tools/0.24/auto_tutorials/preprocessing/25_background_filtering.html diff --git a/applications/lofar2/model/pfb_os/filter_design_firls.ipynb b/applications/lofar2/model/pfb_os/filter_design_firls.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..c53b1d3555a5becb4e5abc719e2492100b08ba64 --- /dev/null +++ b/applications/lofar2/model/pfb_os/filter_design_firls.ipynb @@ -0,0 +1,385 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6e0a005d", + "metadata": {}, + "source": [ + "# Try firls FIR filter design method\n", + "\n", + "Author: Eric Kooistra, nov 2023\n", + "Purpose:\n", + "* Practise DSP [1].\n", + "* Try firls least squares FIR filter design method for LPF.\n", + "* Try to reproduce LOFAR subband filter FIR coefficients using scipy instead of MATLAB.\n", + "\n", + "MATLAB:\n", + "* The pfs_coeff_final.m from the Filter Task Force (FTF) in 2005 use fircls1 with r_pass and r_stop to define the ripple. In addition it post applies a Kaiser window with beta = 1 to make the filter attenuation a bit more deep near the transition.\n", + "* The pfir_coeff.m from Apertif also uses fircls1. \n", + "* Both use fircls1 with N = 1024 FIR coefficients and then Fourier interpolation to achieve Ncoefs = 1024 * 16 FIR coefficients. Both scripts can not exactly reproduce the actual LOFAR1 coefficients, therefore these are loaded from a file Coeffs16384Kaiser-quant.dat\n", + "\n", + "Python (scipy.signal):\n", + "* The windowed sync method, firls leased squares method and remez method all yield comparable results, but firls and remez perform slightly better near the transition band. The firls and remez functions from scipy.signal use transition bandwidth and weights between pass and stop band to influence the transition region and ripple. For remez the ripple is constant in the pass band and stop band, for firls the ripple is largest near the band transition.\n", + "\n", + "Conclusion:\n", + "* It is possible to design a good FIR filter using Python scipy. Possibly with some extra help of a filter design and analysis (FDA) tool like pyfda [2].\n", + "\n", + "References:\n", + "\n", + "1. dsp_study_erko, summary of DSP books\n", + "2. pyfda, dsp, at https://github.com/chipmuenk" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "id": "3563bc63", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy import signal" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "id": "f820b0ac", + "metadata": {}, + "outputs": [], + "source": [ + "import dsp" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "id": "a131b5b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<module 'dsp' from '/dop466_0/kooistra/git/hdl/applications/lofar2/model/pfb_os/dsp.py'>" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import importlib\n", + "importlib.reload(dsp)" + ] + }, + { + "cell_type": "markdown", + "id": "2a467746", + "metadata": {}, + "source": [ + "# 1 Least squares method" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "id": "da2a98e9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "r_pass = 0.059254\n", + "r_stop = 0.000035\n", + "r_pass / r_stop = 1669.996877\n" + ] + } + ], + "source": [ + "# passband ripple (in dB);\n", + "r_pass_dB = 0.5;\n", + "r_pass = 10**(r_pass_dB / 20) - 1;\n", + "# stopband ripple (in dB);\n", + "r_stop_dB = -89;\n", + "r_stop = 10**(r_stop_dB / 20);\n", + "print('r_pass = %f' % r_pass)\n", + "print('r_stop = %f' % r_stop)\n", + "print('r_pass / r_stop = %f' % (r_pass / r_stop))" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "id": "4b23f0c1", + "metadata": {}, + "outputs": [], + "source": [ + "# LPF specification for LOFAR subband filter\n", + "Npoints = 1024 # = number of bins in fs, = DFT size\n", + "BWbin = 1 / Npoints # bandwidth of one bin\n", + "# . Use half power bandwidth factor to tune half power cutoff frequency of LPF, default 1.0\n", + "hp_factor = 0.9\n", + "BWpass = hp_factor * BWbin\n", + "fpass = BWpass / 2 # bin at DC: -fpass to +fpass\n", + "\n", + "# Actual FIR filter length\n", + "Ntaps = 16\n", + "Ncoefs = Npoints * Ntaps" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "id": "a81f3239", + "metadata": {}, + "outputs": [], + "source": [ + "# Initial FIR filter length\n", + "# . Use interpolation of factor Q shorter filter to ensure the FIR filter design converges\n", + "# and to speed up calculation. N >> 1000 is not feasible.\n", + "# . The passband ripple and stopband attenuation depend on the transition bandwidth w_tb\n", + "# and the weight. Choose 0 ~< w_tb ~< 1.0 fpass, to ensure the FIR filter design converges\n", + "# and improve the passband ripple and stopband attenuation. A to large transition band \n", + "# also gives the design too much freedom and causes artifacts in the transition.\n", + "Q = Ntaps\n", + "N = Ncoefs // Q + 1 # + 1, because firls only supports odd number of FIR coefficients\n", + "f_pb = fpass * Q # pass band cut off frequency\n", + "w_tb = 0.4 * fpass * Q # transition bandwidth\n", + "f_sb = f_pb + w_tb # stop band frequency\n", + "weight = [1, 1000000] # weight pass band ripple versus stop band ripple\n", + "hFirls = signal.firls(N, [0, f_pb, f_sb, 0.5], [1, 1, 0, 0], weight, fs=1.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "id": "1d05396d", + "metadata": {}, + "outputs": [], + "source": [ + "# Apply Kaiser window with beta = 1 like in pfs_coeff_final.m, this improves the\n", + "# stopband attenuation near the transition band somewhat\n", + "# . beta: 0 rect, 5 hamming, 6 hanning\n", + "win = signal.windows.kaiser(N, beta=1)\n", + "hFirls *= win" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "id": "dbd8577f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ". f_pb = 0.007031\n", + ". w_tb = 0.002813\n", + ". f_sb = 0.009844\n", + ". Q = 16\n", + ". N = 1025\n", + ". DC sum = 0.995106\n", + ". Symmetrical coefs = True\n" + ] + } + ], + "source": [ + "# Symmetrical FIR coeffients: coefs[0] = 0, coefs[1] = coefs[-1]\n", + "print('. f_pb = %f' % f_pb)\n", + "print('. w_tb = %f' % w_tb)\n", + "print('. f_sb = %f' % f_sb)\n", + "print('. Q = %d' % Q)\n", + "print('. N = %d' % len(hFirls))\n", + "print('. DC sum = %f' % np.sum(hFirls))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hFirls))" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "id": "cdf06c69", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "hInterpolated.imag ~= 0\n", + ". Ncoefs = 16384\n", + ". DC sum = 0.995106\n", + ". Symmetrical coefs = True\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Use Fourier interpolation to create final FIR filter coefs\n", + "HFfirls = np.fft.fft(hFirls)\n", + "hInterpolated = dsp.fourier_interpolate(HFfirls, Ncoefs)\n", + "print('. Ncoefs = %d' % len(hInterpolated))\n", + "print('. DC sum = %f' % np.sum(hInterpolated))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hInterpolated))\n", + "\n", + "plt.plot(hInterpolated, 'r', hInterpolated - np.flip(hInterpolated), 'r--')\n", + "plt.grid(True)" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "id": "3ed56c18", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fLim = (-2, 2)\n", + "#fLim = None\n", + "dbLim = (-150, 5)\n", + "#dbLim = None\n", + "h, f, HF = dsp.dtft(hInterpolated)\n", + "dsp.plot_spectra(f, HF, Npoints, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "e8acbe8f", + "metadata": {}, + "source": [ + "# 2 Compare firls filter and LOFAR subband filter" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "id": "732899c1", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fLim = (-2, 2)\n", + "dbLim = (-140, 5)\n", + "\n", + "#plt.figure(0)\n", + "fs = Npoints / Q\n", + "h, f, HF = dsp.dtft(hFirls)\n", + "dsp.plot_power_spectrum(f, HF, 'b', fs, fLim, dbLim)\n", + "\n", + "#plt.figure(1)\n", + "fs = Npoints\n", + "h, f, HF = dsp.dtft(hInterpolated)\n", + "dsp.plot_power_spectrum(f, HF, 'r', fs, fLim, dbLim)\n", + "\n", + "#plt.figure(2)\n", + "lofarCoefs = dsp.read_coefficients_file('../data/Coeffs16384Kaiser-quant.dat')\n", + "lofarCoefs /= np.sum(lofarCoefs)\n", + "fs = Npoints\n", + "h, f, HF = dsp.dtft(lofarCoefs)\n", + "dsp.plot_power_spectrum(f, HF, 'g', fs, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5f307eee", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/applications/lofar2/model/pfb_os/filter_design_remez.ipynb b/applications/lofar2/model/pfb_os/filter_design_remez.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..5a444a446d2e2fc27f748bc87a1c29d9988ce5e4 --- /dev/null +++ b/applications/lofar2/model/pfb_os/filter_design_remez.ipynb @@ -0,0 +1,356 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6e0a005d", + "metadata": {}, + "source": [ + "# Try remez FIR filter design method\n", + "\n", + "Author: Eric Kooistra, nov 2023\n", + "Purpose:\n", + "* Practise DSP [1].\n", + "* Try remez FIR filter design method for LPF.\n", + "* Try to reproduce LOFAR subband filter FIR coefficients using scipy instead of MATLAB.\n", + "\n", + "MATLAB:\n", + "* The pfs_coeff_final.m from the Filter Task Force (FTF) in 2005 use fircls1 with r_pass and r_stop to define the ripple. In addition it post applies a Kaiser window with beta = 1 to make the filter attenuation a bit more deep near the transition.\n", + "* The pfir_coeff.m from Apertif also uses fircls1. \n", + "* Both use fircls1 with N = 1024 FIR coefficients and then Fourier interpolation to achieve Ncoefs = 1024 * 16 FIR coefficients. Both scripts can not exactly reproduce the actual LOFAR1 coefficients, therefore these are loaded from a file Coeffs16384Kaiser-quant.dat\n", + "\n", + "Python (scipy.signal):\n", + "* The windowed sync method, firls leased squares method and remez method all yield comparable results, but firls and remez perform slightly better near the transition band. The firls and remez functions from scipy.signal use transition bandwidth and weights between pass and stop band to influence the transition region and ripple. For remez the ripple is constant in the pass band and stop band, for firls the ripple is largest near the band transition.\n", + "\n", + "Conclusion:\n", + "* It is possible to design a good FIR filter using Python scipy. Possibly with some extra help of a filter design and analysis (FDA) tool like pyfda [2].\n", + "\n", + "References:\n", + "\n", + "1. dsp_study_erko, summary of DSP books\n", + "2. pyfda, dsp, at https://github.com/chipmuenk" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "3563bc63", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy import signal" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f820b0ac", + "metadata": {}, + "outputs": [], + "source": [ + "import dsp" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a131b5b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<module 'dsp' from '/dop466_0/kooistra/git/hdl/applications/lofar2/model/pfb_os/dsp.py'>" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import importlib\n", + "importlib.reload(dsp)" + ] + }, + { + "cell_type": "markdown", + "id": "6ca908a5", + "metadata": {}, + "source": [ + "# 1 Remez method" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "efe5479c", + "metadata": {}, + "outputs": [], + "source": [ + "# LPF specification for subband prototype filter\n", + "Npoints = 1024 # = number of bins in fs, = DFT size\n", + "BWbin = 1 / Npoints # bandwidth of one bin\n", + "# . Use half power bandwidth factor to tune half power cutoff frequency of LPF, default 1.0\n", + "hp_factor = 0.85\n", + "BWpass = hp_factor * BWbin\n", + "fpass = BWpass / 2 # bin at DC -fpass to +fpass\n", + "\n", + "# Actual FIR filter length\n", + "Ntaps = 16\n", + "Ncoefs = Npoints * Ntaps" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "dfc5651a", + "metadata": {}, + "outputs": [], + "source": [ + "# Initial FIR filter length\n", + "# . Use interpolation of factor Q shorter filter\n", + "# . The passband ripple and stopband attenuation depend on the transition bandwidth w_tb\n", + "# and the weight. Choose 0.4 ~< w_tb ~< 1.0 fpass, to ensure the FIR filter design converges\n", + "# and improve the passband ripple and stopband attenuation. A large transition band does not\n", + "# cause artefacts.\n", + "Q = Ntaps\n", + "N = Ncoefs // Q\n", + "f_pb = fpass * Q # pass band cut off frequency\n", + "w_tb = 0.5 * fpass * Q # transition bandwidth\n", + "f_sb = f_pb + w_tb # stop band frequency\n", + "weight = [1, 1000] # weight pass band ripple versus stop band ripple\n", + "hRemez = signal.remez(N, [0, f_pb, f_sb, 0.5], [1, 0], weight, fs=1.0)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "0d4569d1", + "metadata": {}, + "outputs": [], + "source": [ + "# Apply Kaiser window with beta = 1 like in pfs_coeff_final.m, this improves the\n", + "# stopband attenuation near the transition band somewhat\n", + "# . beta: 0 rect, 5 hamming, 6 hanning\n", + "win = signal.windows.kaiser(N, beta=1)\n", + "hRemez *= win" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4b8d732e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + ". f_pb = 0.006641\n", + ". w_tb = 0.003320\n", + ". f_sb = 0.009961\n", + ". Q = 16\n", + ". N = 1024\n", + ". DC sum = 0.978544\n", + ". Symmetrical coefs = True\n" + ] + } + ], + "source": [ + "# Symmetrical FIR coeffients: coefs[0] = 0, coefs[1] = coefs[-1]\n", + "print('. f_pb = %f' % f_pb)\n", + "print('. w_tb = %f' % w_tb)\n", + "print('. f_sb = %f' % f_sb)\n", + "print('. Q = %d' % Q)\n", + "print('. N = %d' % len(hRemez))\n", + "print('. DC sum = %f' % np.sum(hRemez))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hRemez))" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "9314f402", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "hInterpolated.imag ~= 0\n", + ". Ncoefs = 16384\n", + ". DC sum = 0.978544\n", + ". Symmetrical coefs = True\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Use Fourier interpolation to create final FIR filter coefs\n", + "HFremez = np.fft.fft(hRemez)\n", + "hInterpolated = dsp.fourier_interpolate(HFremez, Ncoefs)\n", + "print('. Ncoefs = %d' % len(hInterpolated))\n", + "print('. DC sum = %f' % np.sum(hInterpolated))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(hInterpolated))\n", + "\n", + "plt.plot(hInterpolated, 'r', hInterpolated - np.flip(hInterpolated), 'r--')\n", + "plt.grid(True)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "580e0fd5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fLim = (-2, 2)\n", + "#fLim = None\n", + "dbLim = (-150, 5)\n", + "#dbLim = None\n", + "h, f, HF = dsp.dtft(hInterpolated)\n", + "dsp.plot_spectra(f, HF, Npoints, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "00759606", + "metadata": {}, + "source": [ + "# 2 Compare remez filter and LOFAR subband filter" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "73baa95f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fLim = (-2, 2)\n", + "dbLim = (-140, 5)\n", + "\n", + "#plt.figure(0)\n", + "fs = Npoints / Q\n", + "h, f, HF = dsp.dtft(hRemez)\n", + "dsp.plot_power_spectrum(f, HF, 'b', fs, fLim, dbLim)\n", + "\n", + "#plt.figure(1)\n", + "fs = Npoints\n", + "h, f, HF = dsp.dtft(hInterpolated)\n", + "dsp.plot_power_spectrum(f, HF, 'r', fs, fLim, dbLim)\n", + "\n", + "#plt.figure(2)\n", + "lofarCoefs = dsp.read_coefficients_file('../data/Coeffs16384Kaiser-quant.dat')\n", + "lofarCoefs /= np.sum(lofarCoefs)\n", + "fs = Npoints\n", + "h, f, HF = dsp.dtft(lofarCoefs)\n", + "dsp.plot_power_spectrum(f, HF, 'g', fs, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e5f840ab", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/applications/lofar2/model/pfb_os/filter_design_windowed_sync.ipynb b/applications/lofar2/model/pfb_os/filter_design_windowed_sync.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..fc6969db46c3383c704a57828ba870b8c35c9863 --- /dev/null +++ b/applications/lofar2/model/pfb_os/filter_design_windowed_sync.ipynb @@ -0,0 +1,356 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6e0a005d", + "metadata": {}, + "source": [ + "# Try windowed sync FIR filter design method\n", + "\n", + "Author: Eric Kooistra, nov 2023\n", + "Purpose:\n", + "\n", + "Practise DSP [1]:\n", + "- Use windowed sync method for FIR filter design in time domain\n", + "- Compare LOFAR subband filter with windowed sync LPF for Kaiser window with beta\n", + "\n", + "References:\n", + "\n", + "[1] dsp_study_erko, summary of DSP books" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "3563bc63", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy import signal" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f820b0ac", + "metadata": {}, + "outputs": [], + "source": [ + "import dsp" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a131b5b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<module 'dsp' from '/dop466_0/kooistra/git/hdl/applications/lofar2/model/pfb_os/dsp.py'>" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import importlib\n", + "importlib.reload(dsp)" + ] + }, + { + "cell_type": "markdown", + "id": "672a425f", + "metadata": {}, + "source": [ + "# 1 Windowed sinc method" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "4e185794", + "metadata": {}, + "outputs": [], + "source": [ + "# LPF specifications\n", + "Npoints = 1024\n", + "Ntaps = 16\n", + "Ncoefs = Npoints * Ntaps\n", + "hp_factor = 0.97\n", + "fpass = hp_factor / Npoints" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "ccbe2065", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Window method: firwin, kaiser with beta = 8.000000\n", + ". Ncoefs = 16384\n", + ". Coefs sum = 1.000000\n", + ". Symmetrical coefs = True\n" + ] + } + ], + "source": [ + "# Select windowed sinc method\n", + "# . method\n", + "method = 'manual'\n", + "method = 'firwin'\n", + "# Window type\n", + "window = 'hann'\n", + "window = 'kaiser'\n", + "if window == 'kaiser':\n", + " beta = 8 # beta: 0 rect, 5 hamming, 6 hanning\n", + " print('Window method: %s, %s with beta = %f' % (method, window, beta))\n", + "else:\n", + " print('Window method: %s, %s' % (method, window))\n", + "\n", + "# FIR coefficients\n", + "if method == 'manual':\n", + " # sinc, sinc(t) = sin(pi t)/(pi t)\n", + " nlo = -Ncoefs//2\n", + " n = np.arange(nlo, nlo + Ncoefs)\n", + " sinc = np.sinc(fpass * (n + 0.5))\n", + " print('. Symmetrical sinc = %s' % dsp.is_symmetrical(sinc))\n", + " # window\n", + " if window == 'hann':\n", + " win = signal.windows.hann(Ncoefs)\n", + " elif window == 'kaiser':\n", + " win = signal.windows.kaiser(Ncoefs, beta) \n", + " print('. Symmetrical win = %s' % dsp.is_symmetrical(win))\n", + " # FIR coefs\n", + " coefs = win * sinc\n", + " # Normalize DC gain\n", + " coefs /= np.sum(coefs)\n", + "elif method == 'firwin':\n", + " if window == 'hann':\n", + " coefs = signal.firwin(Ncoefs, fpass, window='hann')\n", + " elif window == 'kaiser':\n", + " coefs = signal.firwin(Ncoefs, fpass, window=('kaiser', beta))\n", + "# Plot\n", + "h, f, HF = dsp.dtft(coefs)\n", + "# Symmetrical FIR coeffients: coefs[0] = 0, coefs[1] = coefs[-1]\n", + "print('. Ncoefs = %d' % len(coefs))\n", + "print('. Coefs sum = %f' % np.sum(coefs))\n", + "print('. Symmetrical coefs = %s' % dsp.is_symmetrical(coefs))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "0eddef92", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "dsp.plot_time_response(coefs)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "cecb34c7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fLim = (-2, 2)\n", + "dbLim = (-120, 5)\n", + "dsp.plot_spectra(f, HF, Npoints, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "a49c1d87", + "metadata": {}, + "outputs": [], + "source": [ + "# Compare coefs using different methods\n", + "# . first run manual window, then run using scipy.signal window to compare the coefs,\n", + "# the difference is zero after ensuring that sinc and win are symmetrical and with correct fc.\n", + "try:\n", + " plt.plot(coefs - prefCoefs)\n", + " prefCoefs = coefs\n", + "except:\n", + " prefCoefs = coefs" + ] + }, + { + "cell_type": "markdown", + "id": "b03374df", + "metadata": {}, + "source": [ + "# 2 Compare LOFAR subband filter with Kaiser window LPF" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a1c86a38", + "metadata": {}, + "outputs": [], + "source": [ + "# LOFAR coefs\n", + "Npoints = 1024\n", + "Ntaps = 16\n", + "lofarCoefs = dsp.read_coefficients_file('../data/Coeffs16384Kaiser-quant.dat')\n", + "lofarCoefs /= np.sum(lofarCoefs)\n", + "hLofar, fLofar, HFlofar = dsp.dtft(lofarCoefs)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "29baa88c", + "metadata": {}, + "outputs": [], + "source": [ + "# Windowed sync type LPF\n", + "fpass = 1 / Npoints\n", + "window = 'hann'\n", + "window = 'kaiser'\n", + "\n", + "windowLegend = window\n", + "if window == 'hann':\n", + " coefs = signal.firwin(Ncoefs, fpass, window='hann')\n", + "elif window == 'kaiser':\n", + " beta = 8 # beta: 0 rect, 5 hamming, 6 hanning\n", + " coefs = signal.firwin(Ncoefs, fpass, window=('kaiser', beta))\n", + " windowLegend = window + ', beta = %.1f' % beta\n", + "hWin, fWin, HFwin = dsp.dtft(coefs)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "697c358d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Compare frequency response\n", + "fs = Npoints\n", + "fLim = (-2, 2)\n", + "#fLim = None\n", + "dbLim = (-120, 5)\n", + "dsp.plot_two_power_spectra(fWin, HFwin, windowLegend,\n", + " fLofar, HFlofar, 'LOFAR',\n", + " fs, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "73baa95f", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/applications/lofar2/model/pfb_os/rectangular_window_and_ideal_lpf.ipynb b/applications/lofar2/model/pfb_os/rectangular_window_and_ideal_lpf.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..6d8919d29c34a13c8ba7ede9a383896ad793536b --- /dev/null +++ b/applications/lofar2/model/pfb_os/rectangular_window_and_ideal_lpf.ipynb @@ -0,0 +1,585 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "6e0a005d", + "metadata": {}, + "source": [ + "# Try rectangular time window and frequency response\n", + "\n", + "Author: Eric Kooistra, nov 2023\n", + "Purpose:\n", + "\n", + "Practise DSP [1]:\n", + "- DTFT of rectangular time window\n", + "- Impulse response of rectangular frequency reponse (= ideal LPF)\n", + "- Half band ideal LPF\n", + "- Compare LOFAR subband filter with ideal LPF\n", + "- Compare LOFAR subband filter with rectangular time window (= FFT bin response)\n", + "\n", + "References:\n", + "\n", + "[1] dsp_study_erko, summary of DSP books" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "3563bc63", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from scipy import signal" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f820b0ac", + "metadata": {}, + "outputs": [], + "source": [ + "import dsp" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a131b5b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "<module 'dsp' from '/dop466_0/kooistra/git/hdl/applications/lofar2/model/pfb_os/dsp.py'>" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import importlib\n", + "importlib.reload(dsp)" + ] + }, + { + "cell_type": "markdown", + "id": "76144f4f", + "metadata": {}, + "source": [ + "# 1 DTFT of rectangular time window" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "861313c3", + "metadata": {}, + "outputs": [], + "source": [ + "# Select rectangular time window with Nrect time samples:\n", + "# . Nrect = 16 : [LYONS Fig 5.24]\n", + "# . Nrect = 31 : [LYONS Fig 5.25] use 31 odd, instead of 32, for zero phase.\n", + "# . Nrect = 99 : [HARRIS Fig 3.4] use 99 odd, instead of 100, for zero phase, first sidelobe\n", + "# level is -22 relative to main lobe of +100, and 20log10(100/22) = -13.2 dB.\n", + "# . Nrect = 1024 : implicit rectangular window of FFT in LOFAR PFB without prefilter.\n", + "Nrect = 16\n", + "Nrect = 31\n", + "Nrect = 99\n", + "Nrect = 1024\n", + "rect = np.ones([Nrect]) / Nrect" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "29ed15d4", + "metadata": {}, + "outputs": [], + "source": [ + "# Calculate frequency response using DTFT\n", + "Ninterpolate = 20\n", + "Ndtft = Nrect * Ninterpolate\n", + "hRect, fRect, HFrect = dsp.dtft(rect, Ndtft)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "0c79a5b9", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot time window\n", + "dsp.plot_time_response(hRect)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c2a7daba", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot frequency response\n", + "fs = 1\n", + "fLim = (-0.5, 0.5); dbLim = (-70, 5)\n", + "if Nrect == 1024:\n", + " fs = Nrect # to have frequency in units of fsub = fs / Nrect\n", + " fLim = (-5, 5); dbLim = (-70, 5)\n", + "dsp.plot_spectra(fRect, HFrect, fs, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "98200c25", + "metadata": {}, + "source": [ + "# 2 Impulse response of rectangular frequency reponse (ideal LPF)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "5c1de1c5", + "metadata": {}, + "outputs": [], + "source": [ + "# Try ideal subband prototype filter [HARRIS Fig 3.6]\n", + "# . Npass = Npoints / 5\n", + "Npoints = 100\n", + "Npass = Npoints // 5 + 1 # Ideal LPF number of points in pass band\n", + "bandEdgeGain = 1" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "90d0823a", + "metadata": {}, + "outputs": [], + "source": [ + "# Try half band FIR filter\n", + "# . fpass = fs / 4 --> Npass = Npoints / 2 for half band\n", + "Npoints = 64\n", + "Npass = Npoints // 2\n", + "bandEdgeGain = 0.5 # Band edge gain 0.5 for half band\n", + "#bandEdgeGain = 1.0\n", + "if bandEdgeGain == 0.5:\n", + " Npass += 1 # make odd for fc = 0.5" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "d47b1dd4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DC response: sum(hIdeal) = 1.000000\n" + ] + }, + { + "data": { + "text/plain": [ + "[<matplotlib.lines.Line2D at 0x7fa3ad57e5e0>,\n", + " <matplotlib.lines.Line2D at 0x7fa3ad57e730>]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Use ifft of sampled frequency response to obtain impulse response = FIR filter coefs\n", + "hIdeal, fIdeal, HFideal = dsp.ideal_low_pass_filter(Npoints, Npass, bandEdgeGain)\n", + "print('DC response: sum(hIdeal) = %f' % np.sum(hIdeal))\n", + "\n", + "# Plot coefs, for half band all even coef except [0] are zero\n", + "plt.plot(hIdeal, '-', hIdeal, 'o')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "82875d5f", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Compare frequency response between ideal and Npoints realisation\n", + "fs = 1\n", + "fLim = (-0.5, 0.5)\n", + "dbLim = (-40, 5)\n", + "\n", + "# Calculate frequency response using DTFT\n", + "_, f, HF = dsp.dtft(hIdeal)\n", + "dsp.plot_two_power_spectra(fIdeal - 0.5, np.roll(HFideal, Npoints // 2), 'ideal',\n", + " f, HF, 'realisation',\n", + " fs, fLim, dbLim, showRoll=True)" + ] + }, + { + "cell_type": "markdown", + "id": "ee728eb1", + "metadata": {}, + "source": [ + "# 3 LOFAR filter impulse response (= coefs) and spectrum" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "2b398ab5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ncoefs = 16384\n", + "Symmetrical = True\n" + ] + } + ], + "source": [ + "# LOFAR filter\n", + "Npoints = 1024\n", + "Ntaps = 16\n", + "Ncoefs = Npoints * Ntaps # = len(lofarCoefs)\n", + "lofarCoefs = dsp.read_coefficients_file('../data/Coeffs16384Kaiser-quant.dat')\n", + "lofarCoefs /= np.sum(lofarCoefs)\n", + "if Ncoefs == len(lofarCoefs):\n", + " print('Ncoefs = %d' % Ncoefs)\n", + " print('Symmetrical = %s' % dsp.is_symmetrical(lofarCoefs))\n", + "hLofar, fLofar, HFlofar = dsp.dtft(lofarCoefs)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "66ba1f2b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fs = Npoints\n", + "fLim = (-2, 2)\n", + "dbLim = (-120, 5)\n", + "dsp.plot_spectra(fLofar, HFlofar, fs, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "f5328ae3", + "metadata": {}, + "source": [ + "# 4 Compare LOFAR subband filter with ideal LPF" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "741d2424", + "metadata": {}, + "outputs": [], + "source": [ + "# Ideal LPF\n", + "Nideal = Npoints * Ntaps\n", + "hIdeal, fIdeal, HFideal = dsp.ideal_low_pass_filter(Nideal, Ntaps)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "d2595f67", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DC response: sum(h) = 1.000000\n" + ] + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Compare coefs\n", + "plt.plot(hIdeal,'-r', lofarCoefs, '-g')\n", + "plt.title('Impulse response comparison')\n", + "plt.ylabel('Amplitude')\n", + "plt.xlabel('Sample index')\n", + "plt.legend(['Ideal (aliased sinc)', 'LOFAR'])\n", + "plt.grid(True)\n", + "print('DC response: sum(h) = %f' % np.sum(hIdeal))" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "abdfe51a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Compare frequency response LOFAR filter and ideal LPF\n", + "fs = Npoints\n", + "fLim = (-2, 2)\n", + "dbLim = (-120, 5)\n", + "dsp.plot_two_power_spectra(fIdeal - 0.5, np.roll(HFideal, Nideal // 2), 'ideal',\n", + " fLofar, HFlofar, 'LOFAR',\n", + " fs, fLim, dbLim)" + ] + }, + { + "cell_type": "markdown", + "id": "8bf65780", + "metadata": {}, + "source": [ + "# 5 Compare LOFAR filter and rectangular time window" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "209ae412", + "metadata": {}, + "outputs": [], + "source": [ + "# Rectangular time window yields response of FFT bin, so PFB = FFT without pre filter.\n", + "Nrect = 1024\n", + "rect = np.ones([Nrect]) / Nrect\n", + "\n", + "# Calculate frequency response using DTFT\n", + "Ninterpolate = 40\n", + "Ndtft = Nrect * Ninterpolate\n", + "hRect, fRect, HFrect = dsp.dtft(rect, Ndtft)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "5fa3a246", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fs = Npoints\n", + "fLim = (-2, 2)\n", + "dbLim = (-120, 5)\n", + "dsp.plot_two_power_spectra(fRect, HFrect, 'rect',\n", + " fLofar, HFlofar, 'LOFAR',\n", + " fs, fLim, dbLim)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1c33fc6b", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.10" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}