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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## ThinkDSP\n",
+ "\n",
+ "This notebook contains code examples from Chapter 1: Sounds and Signals\n",
+ "\n",
+ "Copyright 2015 Allen Downey\n",
+ "\n",
+ "License: [Creative Commons Attribution 4.0 International](http://creativecommons.org/licenses/by/4.0/)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import thinkdsp\n",
+ "import matplotlib.pyplot as plt"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Read a wave\n",
+ "\n",
+ "`read_wave` reads WAV files. The WAV examples in the book are from freesound.org. In the contributors section of the book, I list and thank the people who uploaded the sounds I use."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "wave = thinkdsp.read_wave('92002__jcveliz__violin-origional.wav')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "wave.make_audio()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "I pulled out a segment of this recording where the pitch is constant. When we plot the segment, we can't see the waveform clearly, but we can see the \"envelope\", which tracks the change in amplitude during the segment."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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VZrbOzO6t5PlEM3vN9/ynZpYTiH5FRKR+/A5/M4sFngFGAt2Bq8ys+ynNbgT2Oec6A+OBP/jbr4iI1F8gRv4DgHXOuQ3OuSJgEjDqlDajgJd8tycDwyzYE1oiIlKlQIR/FrC5wv0tvscqbeOcKwEOAM1P3ZCZjTOzPDPL27VrVwBKExGRygQi/Csbwbt6tME597xzLtc5l5uRkRGA0kREpDKBCP8tQLsK99sC26pqY2ZxQCqwNwB9i4hIPQQi/D8DuphZBzNLAK4ETl1acypwre/2GOAD59xpI38REQmNOH834JwrMbNbgfeAWOAF59xyM/stkOecmwr8DfiHma2jfMR/pb/9iohEsmCPj/0OfwDn3HRg+imPPVjh9jHg+4HoS0RE/KczfEVEopDCX0QkCin8RUSikMJfRCQKKfxFRKKQwl9EJAop/EVEopDCX0QkCin8RUSikMJfRCQKKfxFRKJQxIX/FSNyvS5BRMRvwV73OOLC/7JhfbwuQUQk7EVc+CcmxPO9ofoDICJSnYgLf4CrvnO21yWIiIS1iAz/hPg47hs30usyRETCVkSGP0D/7tmc1b2912WIiISliA1/M+PWqy/0ugwRkbAUseEPwT9USkSkoYro8BcRkcop/EVEolBEh3+Z5n1ERCoV0eHvFP4iIpWK6PBPaZzkdQkiImEposM/Pj6W+39yCeee1ZnY2IjeVRGROonzuoBg6989m/7ds7nm0kNMnrmYWfNXel2SiEiNenXNCur2o2Y43CKtCTf/4AJuueoCr0sREalRi7QmQd1+1IT/cUMHnKFVP0Uk6kVd+MfExHDtZYP41U+/43UpIiKe8Sv8zSzdzGaZ2Vrf77RK2vQ1swVmttzMvjKzH/jTZ6C0b9Pc6xJERDzj78j/XmC2c64LMNt3/1RHgLHOuR7ACOApM2vmZ79+S2vamB+M1CUfRSQ6+Rv+o4CXfLdfAi47tYFzbo1zbq3v9jYgH8jws9+AuGJELued1cXrMkREQs7f8G/lnNsO4PvdsrrGZjYASADW+9lvwNx29VCvSxARCbkaw9/M3jezZZX8jKpLR2aWCfwDuN45V1ZFm3Fmlmdmebt27arL5ustNjaGn111YUj6EhEJFzWGv3NuuHOuZyU//wJ2+kL9eLjnV7YNM2sKTAMecM4trKav551zuc653IyM0M0MfWvgmSHrS0QkHPg77TMVuNZ3+1rgX6c2MLME4G3gZefcG372FzT/ff1FXpcgIhIy/ob/o8BFZrYWuMh3HzPLNbMJvjZXAOcD15nZEt9PXz/7DbjBfTt5XYKISMj4tbaPc24PMKySx/OAm3y3XwFe8aefUGnapBEHDx31ugwRkaCLujN8q/OLsaf9HRMRiUgK/wp6d83S3L+IRAWFfwVmxuC+nfjluJFelyIiElQK/0q0TE/xugQRkaBS+FciOzOdS87v6XUZIiJBo/Cvwo2Xn+t1CSIiQaPwFxGJQgr/amS19HzlaRGRoFD4V+MBXe1LRCKUwr8aLdNTSE1p5HUZIiIBp/Cvwa9/dinn53bRRV9EJKL4tbZPNMjOTOf2a4bhnOPsXjk8+eIsr0sSEfGbRv61ZGYM6deJR+8c7XUpIiJ+U/jXUZf2rbjzuosYPqib16WIiNSbpn3qYUi/Tgzp14lR3+rDrPkrKS0rY9rcpUHrb2DvDmRmpLJo6UZ27z8MQGFRcb23l5PVgo1bd5PcKJHB/Toye+FqzGDc989j+KBu5O8t4Ke/eTVQ5YtIGDLnnNc1VCo3N9fl5eV5XUatOOf4ya9fYY8vmP3x2H9fTqfsDI6/L2Z2Wl9mxoGCo+zcc5DH/vYe+w4eqfX2f3/HaLrmtDrt8ePbPa6ouIRnJ83lo7y19dwTEfHHm3+6uV6vM7PFzrncGtsp/ANj38Ej3PybVykpKa3X6+PiYnn8rsvJzkyv82v37D/E+Jdms3LDdjIzUrnhv4Ywa/4KFi3deKJNTEwM4+/9Pm1bpdVp2/l7C1i1YTsDenVg5YYdPPLctDrXJyJ1p/BvQIqKS8jfW8D0uct4b97yGtt375TJ6OH96NaxNQCNkhICWo9zjn0Hj7D/4BE6tssIyDaPFRaTmBDHlp372XfgMKkpjfls2UayM9OZ+sGXrNywPSD9iES7YIe/5vwDKCE+jrat0hh3xXnVhv9940bSv3v2aVM6gWZmpKcmk56aHLBtJiXGA9CudRrtWpd/imjfpvzTyoBeOWzfdYBfPPp6vT8BiUhoKPyD5KFbvstv/vzvkx7r0r4ld11/MS3SmnhUVfBlZqTy19/8iGNFJTRLacTGrXvonJ3BpOl5vDnrc6/LE2kQBvbuEPQ+NO0TRMcKi1mwZAMd2jYnJ6uF1+V47ptte7jnj29RrE8FItX62yNjaZbSuF6vre20j47zD6KkxHiGnnOGgt+nfZvmTPrjj7nnphEkN0r0uhyRsNSvW7t6B39daNpHQm5ArxxefvR6AGbNX8Fzr33kcUUi4WNw304h6UfhL566aHB3hg/qxqEjhcycv4J//nuR1yWJeCYxoXy2IBQ05y9hR2cYS7R69bEbTxxRV1+a85cGq2V6Cs8+dDX9urXzuhSRkPnd7Zf5Hfx1oWkfCUst01N44ObyK6mt+yafe558y+OKRIKrc3ZgTsSsLY38Jex1bt+Sm8ac63UZIkHz6J2jiYuLDWmfGvlLg3DRoG4cPlrEzHnLA7KAnki4+N/7rySrZbOQ96uRvzQIcXGxjLm4P889dDWtWzT1uhyRgDijQ2tPgh/8DH8zSzezWWa21ve7yiUjzaypmW01s6f96VOiW0xMDE/cPYbf3vY9r0sR8dsdY4d51re/I/97gdnOuS7AbN/9qjwMzPWzPxEaJSXQo3Mbnrh7DAP7dKRX1yyvSxKps1f+cAMZ6Sme9e/vnP8o4ELf7ZeAD4F7Tm1kZmcBrYAZQI3Hn4rURoe2Lbj7hosB2Jq/nw8WrmLK7CUeVyVSs1uuuiDgS7jXlb8j/1bOue0Avt8tT21gZjHAH4G7/exLpEpZLZvxo0vPYUj/zl6XIlKtgb07MHRAaM7irU6NI38zex9oXclT99eyj1uA6c65zTWtX29m44BxANnZ2bXcvEg5M+POa4dzx9hh7C84yk2/erlWr2vSOJFDRwoBaJORSlarNA4ePsbqr3cEs1yJQtePHsx3L+ztdRmAn8s7mNlq4ELn3HYzywQ+dM6dcUqbV4HzgDKgCZAA/Nk5V933A1reQfyWv7eAR56dxtb8/SceGz2sL0MHnsnufYd4a9bn9OySxfe/fValr//rGx8z45Oar8gmUpPUlEY88JNLAnZFveqE5DKOZvY4sMc596iZ3QukO+f+p5r21wG5zrlba9q2wl8C5UDBURIT4up86vzho4W8+PYCPvh0VZAqk0jXo3Mb7r1pBI0bhW5+P1Th3xx4HcgGNgHfd87tNbNc4Gbn3E2ntL8Ohb80UEeOFjF74SoWfLlBU0JSo7tvuJhzencI+uVaT6ULuIsE0YGCo7zyzqekNW3MyPN78sTfZ7Jqg/4gRLNvD+lB/x7ZZKSlkJ2ZFvLQP07hL+KBTxavY/zL73tdhoTAZcP6kp2ZzqC+HSkrcyFdkbM6tQ1/re0jEkDnntWZIf07sWP3QW59ZKLX5UiANU5KYPigbnTNacXAPqGf0gkkhb9IgJkZmRmpvP7kON6YuZg3Ziz2uiQJgNf++OOQr7wZTFrYTSRIYmNjuHLk2fz8R9/yuhTx0+UX9Y+o4AeN/EWC7oKzu9KudRp3P/Gm16VILXXObskN/zWY9NRkvtm+l35nRt5V5RT+IiHQsV0G940byaR38yguKSV/TwGFRcVelyUVtG2Vxnm5XehzRhZd2rc68biXi68Fk8JfJETO6tGes3q0P3H/2UlzeX/BSg8rkuPGjhrEt845g5TkJK9LCRnN+Yt45MbLh5CemgxAt46ZJDdK9Lii6HTfuJGM+lafqAp+0MhfxDMJ8XE886ur2HfwCK2al1+d7EDBUW544CWPK4t8SYnx3HHtcBLj4+jZpY3X5XhC4S/ioYT4uBPBD+ULgP3f/Vdy2+8meVhV5EpPTebKS3LpmtOadq2rvPBgVNC0j0iYadOyGY/8fJTXZUSchPg4/vTLHzBsYLeoD37QyF8kLHXrlMn/3Phttu86wEWDuxEfF8tVd03wuqwGbcLD14R0dc1wp5G/SJg6p3cHLhvWl+RGiSTEx/HonaNp3aJpzS+U09x29VB9oX4KjfxFGogu7VvxzK9+yOGjhdz/p3+xefter0sKez+98gJSkpM4u2f7mhtHGYW/SAOT3CiR8fd8n9LSMm7//Wvs2H3Q65LCTlxcLL/7+Sg6tz/tsuLio/AXaYDMjLi4WB7++SiWrtnKuk35TP9omddlhYV2mek8de8VXpcR9hT+Ig1YemoyF5zdlfNzuzCgVwfaZabRKDGeuZ+tZdrcpWzZuc/rEkPu/nEjvS6hQdDFXEQiXMHhYxw8fIynX53Dmo07vS4naNq2SuP+my+hZYSuxVNbupiLiACQkpxESnISv79jNCUlpfx50lzmfrbG67ICJierBb8YO0zH7teRRv4iUe6dOV/x4pT5pCQn8ZdfX01Rcfmqox3btWDe5+vD9rKUiQnx/OXXV0fdmjw10TV8RaTWvtm2h4y0lEpPgnLOsWL9dt79eDkLlqw/8XibjFRiYmJO+l6hebNk9uw/HPR6H7j5O/Q9s22DvoxisGjaR0RqrX2b5lU+Z2b06NyGHp3bsGVnLnv2H6Z316wTwVtYVExRcSnxcbEkJsRx2+8msX3XgfLXAunNkomNiSF/bwEd2rageWoyecu/qVed3xvah7GjBir0A0AjfxEJqAMFR1mxfjv9u7ejtNTRKCkeKP8EERNTvqjA5bc/V6ttDezdgbtuuJiyMsfho4U0bdIoaHVHCo38RcQTqSmNGNS342mPVxytDxt4JrMXrgKgXes0ysocRcWlXDCgK1u27+WSC3rRvVPmidfExpqCP8AU/iIScj8ecx65PXPo0r4laU0bA+WfDDSdEzoKfxEJufj4WAb0yjnpMQV/aGlVTxGRKKTwFxGJQgp/EZEopPAXEYlCCn8RkSik8BcRiUIKfxGRKBS2yzuY2S6gfguAlGsB7A5QOV6KlP0A7Uu4ipR9iZT9AP/2pb1zLqOmRmEb/v4ys7zarG8R7iJlP0D7Eq4iZV8iZT8gNPuiaR8RkSik8BcRiUKRHP7Pe11AgETKfoD2JVxFyr5Eyn5ACPYlYuf8RUSkapE88hcRkSo06PA3sxfMLN/MllXx/NVm9pXvZ76Z9Ql1jbVVi30Z5duPJWaWZ2bnhrrG2qhpPyq0O9vMSs1sTKhqq6tavCcXmtkB33uyxMweDHWNtVWb98W3P0vMbLmZzQ1lfbVVi/fk7grvxzLfv7H0UNdZG7XYl1Qze8fMvvS9J9cHtADnXIP9Ac4H+gPLqnh+MJDmuz0S+NTrmv3Ylyb8Z5quN7DK65rrsx++NrHAB8B0YIzXNfvxnlwI/NvrOgO0L82AFUC2735Lr2uuz36c0vZS4AOva/bjPbkP+IPvdgawF0gIVP8NeuTvnPuI8v8gVT0/3zm3z3d3IdA2JIXVQy325ZDz/SsAkoGw/LKmpv3wuQ14E8gPfkX1V8t9aRBqsS8/BN5yzm3ytQ/L96aO78lVwMQgluOXWuyLA1Ks/Co3TXxtSwLVf4MO/zq6EXjX6yL8YWajzWwVMA24wet66sPMsoDRQO2u4B3+Bvk+lr9rZj28LsYPXYE0M/vQzBab2VivC/KHmTUGRlA+yGionga6AduApcDtzrmyQG08Ki7jaGZDKQ//sJwnry3n3NvA22Z2PvAwMNzjkurjKeAe51xpBFy273PKT6U/ZGaXAFOALh7XVF9xwFnAMKARsMDMFjrn1nhbVr1dCsxzzjXkT27fBpYA3wI6AbPM7GPn3MFAbDziR/5m1huYAIxyzu3xup5A8H1c7GRmLbyupR5ygUlmthEYA/zZzC7ztqT6cc4ddM4d8t2eDsQ30PcEYAswwzl32Dm3G/gICNsDJGrhSsJ4yqeWrqd8Ks4559YBXwNnBmrjER3+ZpYNvAVc04BHMACYWWfvjPYXAAAC5UlEQVTf3B9m1h9IABrcHzPnXAfnXI5zLgeYDNzinJvicVn1YmatK7wnAyj//6nBvSc+/wLOM7M435TJOcBKj2uqFzNLBS6gfJ8ask2UfxLDzFoBZwAbArXxBj3tY2YTKT/iooWZbQEeAuIBnHPPAQ8CzSkfXQKUuDBd+KkW+3I5MNbMioGjwA8qfAEcNmqxHw1GLfZlDPBTMyuh/D25MhzfE6h5X5xzK81sBvAVUAZMcM5Ve7iuF2r572s0MNM5d9iTImupFvvyMPCimS0FjPLp0oCtWqozfEVEolBET/uIiEjlFP4iIlFI4S8iEoUU/iIiUUjhLyIShRT+IiJRSOEvEc/MmldY5neHmW2tcH9+kPrsZ2YTqnk+w3dcvYgnGvRJXiK14VvWoy+Amf0aOOSceyLI3d4HPFJNTbvMbLuZDXHOzQtyLSKn0chfopqZHfL9vtDM5prZ62a2xswe9V0MaJGZLTWzTr52GWb2ppl95vsZUsk2U4DezrkvffcvqPBJ4wvf81C+ENzVIdpVkZMo/EX+ow9wO9ALuAbo6pwbQPnCgLf52vwJGO+cO5vyJTcqm9rJBSoujXAX8DPnXF/gPMqXggDI890XCTlN+4j8x2fOue0AZrYemOl7fCkw1Hd7ONC9wnLUTc0sxTlXUGE7mcCuCvfnAU+a2auUr9K4xfd4PtAm8LshUjOFv8h/FFa4XVbhfhn/+X8lBhjknDtK1Y4CScfvOOceNbNpwCXAQjMb7pxb5WtT3XZEgkbTPiJ1MxO49fgdM+tbSZuVQOcKbTo555Y65/5A+VTP8TXZu3Ly9JBIyCj8Rerm50CumX1lZiuAm09t4BvVp1b4YvcXZrbMzL6kfKR//HKiQym/JKdIyGlJZ5EgMLM7gALnXHXH+n9E+RXm9oWuMpFyGvmLBMeznPwdwknMLAN4UsEvXtHIX0QkCmnkLyIShRT+IiJRSOEvIhKFFP4iIlFI4S8iEoX+P6x9JyHJfKfeAAAAAElFTkSuQmCC\n",
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