{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from lasp import SeriesBiquad\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2022-08-16 15:02:57+0200 \n", "2022-08-16 15:02:57+0200 Enter SeriesBiquad (lasp_biquadbank.cpp: 12)\n", "2022-08-16 15:02:57+0200 Leave SeriesBiquad (lasp_biquadbank.cpp)\n" ] } ], "source": [ "coefs = np.array([1.,0,0,1.,-.9,0])\n", "bq = SeriesBiquad(coefs)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2022-08-16 15:02:57+0200 \n", "2022-08-16 15:02:57+0200 Enter filter (lasp_biquadbank.cpp: 41)\n", "2022-08-16 15:02:57+0200 Leave filter (lasp_biquadbank.cpp)\n" ] } ], "source": [ "x = np.zeros(10, dtype=float)\n", "x[0] = 1\n", "\n", "x2 = bq.filter(x)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1. ],\n", " [0.9 ],\n", " [0.81 ],\n", " [0.729 ],\n", " [0.6561 ],\n", " [0.59049 ],\n", " [0.531441 ],\n", " [0.4782969 ],\n", " [0.43046721],\n", " [0.38742049]])" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "x2" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 4 }