149 lines
3.6 KiB
Plaintext
149 lines
3.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "bcd07c1e-6722-44c7-b162-267f1341c2fe",
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"metadata": {},
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"source": [
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"# Compare Butterworth bandpass implementation with Scipy's implementation"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f0c4d6ef-69b2-4b5c-92fd-d987a11f3cbd",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Prerequisites, uncomment below in case of errors. Also for ipympl, restart Jupyter Lab if it was not installed\n",
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"\n",
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"#!cd .. && maturin develop -F python-bindings\n",
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"#!pip install ipympl scipy matplotlib"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "23b45cf6-85bc-4eaa-8f27-77c5b354e772",
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"metadata": {},
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"outputs": [],
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"source": [
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"# If this does not work, install ipympl and reboot Jupyter Lab\n",
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"%matplotlib widget"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "96090ac9-2033-411d-8e45-0c6b375a268b",
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from lasprs.filter import Biquad, SeriesBiquad, BiquadBank, FilterSpec, ZPKModel"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8c137d60-51f3-4a14-892c-925aad662dc5",
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"metadata": {},
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"outputs": [],
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"source": [
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"#!pip install matplotlib\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"from numpy import log10, sqrt, exp, pi\n",
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"from scipy.signal import butter, freqs_zpk\n",
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"# Cut-\n",
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"fc = 100\n",
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"fl = fc/1.1\n",
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"fu = fc*1.5\n",
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"order = 4\n",
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"fs = 32e3"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "25d36d28-80e9-40cc-9364-f708d21f9b49",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Create Scipy filter\n",
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"but = butter(order, [2*pi*fl, 2*pi*fu],'bandpass', analog=True, output ='zpk')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1f877979-55a8-4eee-b1f3-fc8500414664",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"# fspec = FilterSpec.Lowpass(fc, order)\n",
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"# fspec = FilterSpec.Highpass(fc, order)\n",
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"fspec = FilterSpec.Bandpass(fl, fu, order)\n",
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"m = ZPKModel.butter(fspec)\n",
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"freq = np.logspace(log10(fc)-1, log10(fc)+1, 100)\n",
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"def level(a):\n",
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" return 20*np.log10(np.abs(a))\n",
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"#m"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "3ae5384d-2b5e-4688-b20d-148120e66147",
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"metadata": {},
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"outputs": [],
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"source": [
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"w, hbut = freqs_zpk(*but, worN=2*np.pi*freq)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ad12c873-a47f-4ed5-a5ad-bb4d45bc5c3a",
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"metadata": {},
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"outputs": [],
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"source": [
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"plt.figure()\n",
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"plt.subplot(211)\n",
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"plt.title('Magnitude [dB]')\n",
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"plt.semilogx(freq, level(hbut), lw=3)\n",
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"plt.semilogx(freq, level(m.tf(1e-16, freq)), '--')\n",
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"plt.ylim(-10, 1)\n",
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"plt.legend(['Scipy', 'Lasprs'])\n",
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"plt.subplot(212)\n",
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"plt.title('Phase [deg]')\n",
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"plt.semilogx(freq, np.angle(m.tf(1e-16, freq), deg=True))\n",
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"plt.semilogx(freq, np.angle(hbut, deg=True))\n",
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"plt.xlabel('Freq. [Hz]')"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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