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