{"worksheets": [{"metadata": {}, "cells": [{"cell_type": "markdown", "source": ["# Arithmetic on Squiggles"], "metadata": {}}, {"metadata": {}, "language": "python", "cell_type": "code", "outputs": [], "prompt_number": 3, "collapsed": false, "input": ["import numpy as np\n", "import matplotlib.pyplot as pt"]}, {"metadata": {}, "language": "python", "cell_type": "code", "outputs": [], "prompt_number": 4, "collapsed": false, "input": ["squiggle_1 = \"141.03 291.04 141.28 291.50 141.92 291.50 142.67 291.04 143.94 290.13 145.58 288.32 147.22 285.25 149.62 281.27 152.40 276.15 155.31 270.24 158.21 264.10 161.37 258.19 164.02 252.96 166.67 248.41 168.69 244.89 170.72 241.82 172.48 239.55 174.25 237.84 175.52 236.59 176.27 236.13 176.65 236.48 176.65 237.50 177.03 240.00 177.41 244.21 177.79 250.12 178.04 257.39 178.04 265.12 178.42 273.08 178.67 280.93 179.05 288.43 179.56 295.71 179.94 302.64 180.69 309.01 181.71 314.35 182.72 318.10 183.85 320.03 184.86 321.06 186.00 320.72 187.52 319.35 189.28 316.40 191.31 311.39 193.33 304.35 195.60 295.93 198.00 286.84 200.65 277.86 203.56 269.67 206.21 262.62 208.61 257.17 210.51 253.07 212.02 250.23 213.03 248.64 213.79 247.84 214.17 247.73 214.17 248.53 214.17 250.35 214.04 253.53 213.92 258.19 213.66 263.99 213.54 270.13 213.41 276.38 213.41 282.18 213.92 287.41 214.80 291.84 216.32 295.48 218.21 298.09 220.11 299.80 222.13 300.59 224.27 300.71 226.55 300.03 228.95 298.43 231.22 295.71 233.24 292.07 235.26 287.07 237.16 280.81 239.31 273.76 241.83 265.81 244.86 257.39 248.15 249.21 251.68 241.14 255.09 233.63 258.00 227.27 260.40 222.49 261.92 219.54 262.80 218.63 263.18 218.63 263.18 219.88 263.05 222.49 262.55 226.93 261.92 233.75 261.03 242.16 260.40 251.82 260.27 262.40 260.53 273.08 260.91 284.11 261.79 294.91 262.80 304.35 264.44 312.30 266.72 317.99 269.12 321.63 271.64 323.56 274.17 324.69 276.95 324.47 279.98 322.42 283.26 318.56 286.42 311.96 289.83 303.21 293.24 292.98 296.78 282.18 300.32 272.17 303.60 263.42 306.38 256.60 308.65 251.82 310.04 248.75 310.93 247.50 311.18 247.96 311.05 248.98 310.93 250.91 310.80 253.98 310.55 258.76 310.42 265.12 310.17 272.74 310.55 280.81 311.31 289.00 312.57 296.50 314.46 302.64 316.86 307.41 319.77 310.37 322.80 311.73 325.96 312.08 328.86 311.17 331.64 309.01 334.29 304.91 336.82 299.00 339.47 291.73 342.38 283.43 345.54 275.13 348.95 267.51 352.36 260.69 355.14 255.57 357.03 252.16 358.17 250.46 358.55 250.23 358.55 250.69 358.80 251.94 359.43 254.32 360.06 258.19 360.69 264.33 361.20 271.95 361.71 280.59 362.59 289.23 363.98 296.84 366.00 303.44 368.53 308.44 371.56 311.73 375.22 313.33 379.26 312.64 383.81 310.26 388.74 306.62 394.29 301.50 \"\n", "squiggle_2 = \"243.60 219.20 243.60 218.06 242.84 216.92 242.21 215.67 241.07 214.19 239.56 212.60 237.66 211.01 235.26 209.65 232.23 208.62 228.82 207.60 225.03 206.92 220.86 206.46 216.57 206.12 212.27 206.80 207.60 208.05 202.80 210.33 198.13 213.74 193.20 217.72 188.78 222.15 184.74 226.59 181.45 231.13 178.93 235.91 177.28 241.02 176.27 246.59 175.89 252.62 176.27 258.99 177.28 265.81 178.93 272.85 181.33 279.79 184.74 286.38 188.91 292.64 193.83 298.32 199.52 303.78 205.71 308.67 212.40 312.99 219.60 316.62 226.80 319.69 234.00 322.19 241.20 323.90 248.27 324.81 255.60 325.26 262.93 324.81 270.25 323.90 277.96 322.53 285.54 320.60 293.12 318.56 300.32 316.17 306.63 313.33 312.44 310.14 317.75 306.39 322.80 301.96 327.60 296.73 332.15 290.82 336.44 284.11 340.48 276.83 344.15 269.22 347.05 261.60 349.07 253.98 350.34 246.59 350.59 239.20 349.83 231.59 348.19 223.63 345.41 215.67 341.75 208.17 337.07 201.35 331.77 195.66 326.21 191.12 320.65 187.48 315.09 184.75 309.16 182.93 302.84 182.02 296.02 181.91 288.82 182.36 281.87 183.27 274.93 184.52 268.11 185.89 261.54 187.25 255.35 188.61 249.66 190.21 244.86 191.68 240.82 193.28 237.03 194.87 233.87 196.57 230.97 198.28 228.44 199.98 226.42 201.69 224.65 203.51 223.52 205.55 222.51 207.94 221.75 210.78 221.24 213.97 220.74 217.72 220.48 221.24 220.23 224.43 219.85 227.04 219.22 229.20 218.72 230.91 218.21 232.04 217.83 232.72 217.71 233.07 217.33 233.07 216.95 232.50 216.06 231.13 215.43 228.86 215.05 225.56 \""]}, {"metadata": {}, "language": "python", "cell_type": "code", "outputs": [], "prompt_number": 5, "collapsed": false, "input": ["def parse_squiggle(s):\n", " numbers = [float(num) for num in s.split()]\n", " a = np.array(numbers)\n", " return a.reshape(-1, 2).T"]}, {"metadata": {}, "language": "python", "cell_type": "code", "outputs": [], "prompt_number": 6, "collapsed": false, "input": ["s1 = parse_squiggle(squiggle_1)\n", "s2 = parse_squiggle(squiggle_2)"]}, {"cell_type": "markdown", "source": ["Let's plot both squiggles."], "metadata": {}}, {"metadata": {}, "language": "python", "cell_type": "code", "outputs": [{"text": ["[]"], "metadata": {}, "output_type": "pyout", "prompt_number": 11}, {"metadata": {}, "output_type": "display_data", "png": 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"text": [""]}], "prompt_number": 11, "collapsed": false, "input": ["pt.plot(s1[0], s1[1])"]}, {"cell_type": "markdown", "source": ["What are we going to get here?"], "metadata": {}}, {"metadata": {}, "language": "python", "cell_type": "code", "outputs": [{"text": ["[]"], "metadata": {}, "output_type": "pyout", "prompt_number": 14}, {"metadata": {}, "output_type": "display_data", "png": 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h06bi5JSUONOeafNS0aJi7xBB8OzB3b1Zly41U+w7dZIN6o8f988G26s3bdTT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\nomKvKGGMGiViH0tRtHfegcs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"text": [""]}], "prompt_number": 14, "collapsed": false, "input": ["pt.plot(s1[1])"]}, {"metadata": {}, "language": "python", "cell_type": "code", "outputs": [{"text": ["[]"], "metadata": {}, "output_type": "pyout", "prompt_number": 12}, {"metadata": {}, "output_type": "display_data", "png": 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"text": [""]}], "prompt_number": 9, "collapsed": false, "input": ["pt.plot(s2[0], s2[1])"]}, {"cell_type": "markdown", "source": ["Interpolate to same length."], "metadata": {}}, {"metadata": {}, "language": "python", "cell_type": "code", "outputs": [], "prompt_number": 24, "collapsed": false, "input": ["from scipy.interpolate import interp1d\n", "\n", "_, ns1 = s1.shape\n", "_, ns2 = s2.shape\n", "\n", "s1x_interp = interp1d(np.linspace(0, 1, ns1), s1[0])\n", "s1y_interp = interp1d(np.linspace(0, 1, ns1), s1[1])\n", "\n", "s1_new = np.array([\n", " s1x_interp(np.linspace(0, 1, ns2)),\n", " s1y_interp(np.linspace(0, 1, ns2))])"]}, {"cell_type": "markdown", "source": ["And do arithmetic..."], "metadata": {}}, {"metadata": {}, "language": "python", "cell_type": "code", "outputs": [{"text": ["[]"], "metadata": {}, "output_type": "pyout", "prompt_number": 33}, {"metadata": {}, "output_type": "display_data", "png": 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OxhOrApPk3Zwvf8IJULZs/LzzS/CceCL88gvs3Bn9sW680T45f/JJ+D/jxjz5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\nRK5CYII=\n", "text": [""]}], "prompt_number": 33, "collapsed": false, "input": ["\n", "s3 = s1_new + s2\n", "pt.plot(s3[0], s3[1])"]}]}], "metadata": {"name": "", "signature": "sha256:126af7701dca8b25b3662f6c0a9a14f43e34a3d2f429983bfd7824b0cb6bccae"}, "nbformat": 3, "nbformat_minor": 0}