experiment results.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "%pylab\n",
        "%matplotlib inline\n",
        "%config InlineBackend.figure_format = 'svg'\n",
        "import seaborn as sns\n",
        "sns.set()"
      ],
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Using matplotlib backend: MacOSX\n",
            "Populating the interactive namespace from numpy and matplotlib\n"
          ]
        }
      ],
      "execution_count": 2,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "import glob, re, itertools\n",
        "import statsmodels.api as sm"
      ],
      "outputs": [],
      "execution_count": 3,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "results = []\n",
        "for f in glob.glob('./experiment_regs_*.npy'):\n",
        "    i = tuple(map(int,re.match('./experiment_regs_([0-9]+)_([0-9]+)_([0-9]+).npy',f).groups()))\n",
        "    if i[-1]<=4:\n",
        "        results.append((i,np.load(f)))\n",
        "    "
      ],
      "outputs": [],
      "execution_count": 4,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "results.sort()\n",
        "results_mean = {k:\n",
        "    np.mean([np.cumsum(np.real(x[1])) for x in g],0)\n",
        "    for k,g in itertools.groupby(results,key=lambda x: x[0][:2])\n",
        "}\n",
        "results_len = {k:\n",
        "    len(list(g))\n",
        "    for k,g in itertools.groupby(results,key=lambda x: x[0][:2])\n",
        "}"
      ],
      "outputs": [],
      "execution_count": 5,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "results_len"
      ],
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 6,
          "data": {
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          },
          "metadata": {}
        }
      ],
      "execution_count": 6,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "probparams = [\n",
        "    dict(beta=1.5, sigma=0.05),\n",
        "    dict(beta=2.5, sigma=0.05),\n",
        "    dict(beta=3.5, sigma=0.05),\n",
        "    dict(beta=4.5, sigma=0.05),\n",
        "    dict(beta=5.5, sigma=0.05),\n",
        "    dict(beta=6.5, sigma=0.05)\n",
        "]\n",
        "\n",
        "algparams = [\n",
        "    dict(beta=0.5,  c1=.5, c2=1.),\n",
        "    dict(beta=1.5,  c1=.5, c2=1.),\n",
        "    dict(beta=2.5,  c1=.5, c2=1.),\n",
        "    dict(beta=3.5,  c1=.5, c2=1.),\n",
        "    dict(beta=4.5,  c1=.5, c2=1.),\n",
        "    dict(beta=5.5,  c1=.5, c2=1.),\n",
        "    dict(beta=6.5,  c1=.5, c2=1.),\n",
        "    dict(beta=7.5,  c1=.5, c2=1.),\n",
        "    dict(beta=8.5,  c1=.5, c2=1.),\n",
        "    dict(beta=9.5,  c1=.5, c2=1.),\n",
        "    dict(beta=10.5, c1=.5, c2=1.),\n",
        "]\n",
        "\n",
        "T = 20000\n",
        "d = 2"
      ],
      "outputs": [],
      "execution_count": 7,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "T0=int(T/2.)\n",
        "coeffs = {k: \n",
        "          sm.OLS(np.log(results_mean[k][T0:]),sm.add_constant(np.log(np.arange(T)[T0:]))).fit().params[1] \n",
        "          for k in results_mean}\n"
      ],
      "outputs": [],
      "execution_count": 8,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "coeffs2 = {k: \n",
        "          sm.OLS(np.log(results_mean[k][int(T/4):int(T/2)]),sm.add_constant(np.log(np.arange(T)[int(T/4):int(T/2)]))).fit().params[1] \n",
        "          for k in results_mean}\n",
        "coeffs3 = {k: \n",
        "          sm.OLS(np.log(results_mean[k][int(T/8):int(T/4)]),sm.add_constant(np.log(np.arange(T)[int(T/8):int(T/4)]))).fit().params[1] \n",
        "          for k in results_mean}\n",
        "coeffs4 = {k: \n",
        "          sm.OLS(np.log(results_mean[k][int(T/16):int(T/8)]),sm.add_constant(np.log(np.arange(T)[int(T/16):int(T/8)]))).fit().params[1] \n",
        "          for k in results_mean}\n"
      ],
      "outputs": [],
      "execution_count": 104,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "style.use('seaborn')\n",
        "rc('text', usetex=True)\n",
        "rc('font', size=22)"
      ],
      "outputs": [],
      "execution_count": 55,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "def adjustFigAspect(fig,aspect=1):\n",
        "    '''\n",
        "    Adjust the subplot parameters so that the figure has the correct\n",
        "    aspect ratio.\n",
        "    '''\n",
        "    xsize,ysize = fig.get_size_inches()\n",
        "    minsize = min(xsize,ysize)\n",
        "    xlim = .4*minsize/xsize\n",
        "    ylim = .4*minsize/ysize\n",
        "    if aspect < 1:\n",
        "        xlim *= aspect\n",
        "    else:\n",
        "        ylim /= aspect\n",
        "    fig.subplots_adjust(left=.5-xlim,\n",
        "                        right=.5+xlim,\n",
        "                        bottom=.5-ylim,\n",
        "                        top=.5+ylim)\n"
      ],
      "outputs": [],
      "execution_count": 85,
      "metadata": {}
    },
    {
      "cell_type": "code",
      "source": [
        "for prob in [0,4]:#range(len(probparams)):\n",
        "    fig=figure()\n",
        "    xscale('log')\n",
        "    yscale('log')\n",
        "    beta0 = probparams[prob]['beta']\n",
        "    marker = itertools.cycle(('.', '*','^', 'o', 'P','v','s','X','<','D','>')) \n",
        "    for j in range(len(algparams)):\n",
        "        beta = algparams[j]['beta']\n",
        "        plot(np.arange(100+1,T+1),results_mean[prob,j][100:],marker = next(marker),markevery=.1,\n",
        "             label=\n",
        "             r'$\\beta={:.1f},\\,\\hat s={:.2f},\\,s^*={:.2f}$'\n",
        "            .format(beta,coeffs[prob,j],d/(2*beta+d)))\n",
        "    #     title(r'$\\beta_0={:.1f}$'%beta0)\n",
        "    #     plot(np.arange(100+1,T+1),0.5*np.arange(100+1,T+1),'k--')\n",
        "    legend(loc='center left', bbox_to_anchor=(1, 0.5))\n",
        "    xlabel(r'$T$')\n",
        "    ylabel(r'$R_T(\\pi)$')\n",
        "    #     plt.show()\n",
        "    adjustFigAspect(fig)\n",
        "    savefig('regret_{:.1f}.pdf'.format(beta0),bbox_inches = 'tight',pad_inches = 0)\n",
        "\n"
      ],
      "outputs": [
        {
          "output_type": "display_data",
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236.028326 \nL 141.576379 235.7533 \nL 141.806165 235.590257 \nL 142.149036 235.400247 \nL 142.489762 235.362401 \nL 143.164884 235.020016 \nL 143.388077 234.981259 \nL 143.61036 234.620454 \nL 144.271815 234.444971 \nL 144.490527 234.079786 \nL 145.141441 233.84255 \nL 145.356695 233.644036 \nL 145.891136 233.562197 \nL 146.103453 233.162694 \nL 146.525619 232.977569 \nL 146.944538 232.885768 \nL 147.256625 232.563906 \nL 147.463695 232.563906 \nL 147.875486 232.176525 \nL 148.08022 232.081426 \nL 148.385885 232.00163 \nL 149.492203 231.465297 \nL 149.690959 231.144465 \nL 149.888993 230.894696 \nL 150.184699 230.773447 \nL 150.478809 230.524811 \nL 150.868501 230.487135 \nL 151.15895 230.29554 \nL 152.588406 229.964515 \nL 152.86985 229.492496 \nL 153.242859 229.455185 \nL 153.705556 229.392422 \nL 153.88954 229.244149 \nL 154.619322 228.976103 \nL 154.80025 228.930875 \nL 154.980578 228.855663 \nL 155.070519 228.854053 \nL 155.249956 228.588438 \nL 155.518008 228.438925 \nL 155.873371 228.36378 \nL 156.22643 228.22817 \nL 156.48973 228.029721 \nL 156.577215 228.029721 \nL 156.751764 227.753343 \nL 157.444417 227.657872 \nL 157.701908 227.451027 \nL 158.043346 227.257716 \nL 158.467154 227.152474 \nL 158.803843 226.972118 \nL 159.221797 226.732889 \nL 159.719144 226.642336 \nL 159.966125 226.542669 \nL 160.862257 226.088132 \nL 161.023617 225.980379 \nL 161.104119 225.980379 \nL 161.344911 225.746995 \nL 161.823326 225.655026 \nL 162.68965 225.33381 \nL 163.001291 225.256009 \nL 163.233857 225.110382 \nL 163.542409 225.074323 \nL 163.77268 224.89365 \nL 163.849222 224.88025 \nL 164.078202 224.625865 \nL 164.230323 224.577387 \nL 164.38202 224.29796 \nL 164.608776 224.207115 \nL 164.834592 224.100777 \nL 165.283433 224.064806 \nL 165.654663 223.777048 \nL 166.170169 223.683418 \nL 166.462568 223.521579 \nL 166.680841 223.447222 \nL 167.473775 223.143253 \nL 167.901467 223.038341 \nL 170.737441 222.189908 \nL 170.939267 222.097895 \nL 171.140347 221.995362 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213.58097 \nL 191.083923 213.497138 \nL 191.222909 213.428466 \nL 191.49982 213.358439 \nL 191.63775 213.227804 \nL 191.912565 213.137445 \nL 192.186001 212.92746 \nL 192.322206 212.800227 \nL 194.977118 211.552144 \nL 195.149593 211.340784 \nL 195.450117 211.147518 \nL 195.621104 211.063266 \nL 195.791555 211.019016 \nL 196.088567 210.875037 \nL 196.257564 210.784398 \nL 196.51008 210.690441 \nL 196.76143 210.629638 \nL 197.053214 210.540035 \nL 197.260677 210.417997 \nL 197.426081 210.349429 \nL 197.590984 210.264958 \nL 198.892535 209.965382 \nL 199.13315 209.855414 \nL 199.372707 209.745756 \nL 199.571535 209.57981 \nL 199.730077 209.45615 \nL 200.045784 209.326131 \nL 204.210778 207.951196 \nL 204.718728 207.859612 \nL 204.934979 207.800932 \nL 205.078671 207.703828 \nL 205.329223 207.504614 \nL 205.400598 207.504614 \nL 205.543068 207.336819 \nL 206.495114 207.078307 \nL 206.634753 206.8757 \nL 206.912961 206.85218 \nL 207.051534 206.679064 \nL 207.533782 206.610446 \nL 207.670786 206.457093 \nL 207.909717 206.359749 \nL 208.586657 206.130691 \nL 208.754586 206.029081 \nL 208.921998 205.937116 \nL 209.685534 205.550152 \nL 210.014196 205.44233 \nL 210.243085 205.35033 \nL 210.859549 205.250316 \nL 211.787217 204.704315 \nL 212.040369 204.474094 \nL 212.543169 204.37069 \nL 212.917246 204.243956 \nL 213.319617 204.095733 \nL 213.473587 203.955347 \nL 213.627123 203.916317 \nL 214.236974 203.811806 \nL 214.418606 203.713682 \nL 214.900016 203.611486 \nL 215.19875 203.560752 \nL 215.555082 203.48082 \nL 215.702868 203.34792 \nL 216.260826 203.259803 \nL 216.58126 202.989878 \nL 217.331239 202.863966 \nL 218.014479 202.477422 \nL 218.2685 202.369654 \nL 218.437191 202.272209 \nL 218.689252 202.173252 \nL 218.995751 202.120357 \nL 219.438511 202.025398 \nL 219.713419 201.90209 \nL 220.123197 201.799522 \nL 220.502893 201.585869 \nL 220.906795 201.475652 \nL 221.837743 201.017066 \nL 222.07458 200.939722 \nL 223.525528 200.623645 \nL 223.729686 200.529813 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194.874037 \nL 238.517129 194.760898 \nL 238.710934 194.663834 \nL 239.134893 194.556953 \nL 239.669747 194.334144 \nL 239.802644 194.15604 \nL 240.161737 194.108803 \nL 240.29344 193.933701 \nL 240.649322 193.837949 \nL 240.872898 193.770578 \nL 241.261959 193.650938 \nL 241.409445 193.549869 \nL 241.721533 193.388853 \nL 242.068234 193.299411 \nL 242.430813 193.207663 \nL 242.593189 193.166455 \nL 243.113132 193.057896 \nL 243.80463 192.689305 \nL 244.06827 192.597971 \nL 244.348086 192.388315 \nL 245.024176 192.2389 \nL 245.230526 192.183916 \nL 245.521523 192.075037 \nL 246.737029 191.622928 \nL 247.020107 191.501253 \nL 247.152813 191.45863 \nL 247.433744 191.348503 \nL 247.680426 191.196811 \nL 247.893318 191.136168 \nL 248.510885 191.008436 \nL 248.640012 190.963801 \nL 248.961496 190.860615 \nL 249.121529 190.763756 \nL 249.3607 190.686667 \nL 249.5037 190.626818 \nL 249.883208 190.426761 \nL 250.307016 190.283838 \nL 250.463149 190.190122 \nL 250.665455 190.090278 \nL 250.867013 189.995381 \nL 251.052406 189.910571 \nL 251.34466 189.802287 \nL 256.437462 187.8256 \nL 256.646626 187.745918 \nL 256.965791 187.654744 \nL 257.269339 187.558362 \nL 257.4342 187.483626 \nL 258.007316 187.20653 \nL 258.22407 187.139866 \nL 258.372588 187.037296 \nL 258.628171 186.929663 \nL 258.788976 186.830065 \nL 258.949307 186.739638 \nL 259.281822 186.635587 \nL 259.638673 186.496761 \nL 259.849041 186.396661 \nL 260.15003 186.247948 \nL 261.363151 185.657707 \nL 261.605107 185.607091 \nL 261.984968 185.498575 \nL 262.224184 185.376515 \nL 262.349666 185.181304 \nL 262.61224 185.084 \nL 262.761717 185.016995 \nL 262.947987 184.907393 \nL 263.158326 184.810495 \nL 263.711215 184.705551 \nL 263.882087 184.637315 \nL 264.040275 184.555172 \nL 264.185887 184.462438 \nL 264.451837 184.243295 \nL 264.608381 184.109902 \nL 264.83637 184.002761 \nL 265.146815 183.876455 \nL 265.372565 183.780784 \nL 265.53831 183.730145 \nL 265.679978 183.632081 \nL 265.821277 183.559711 \nL 266.114479 183.449015 \nL 267.431824 182.870089 \nL 267.72786 182.766505 \nL 267.863951 182.682858 \nL 268.044879 182.577549 \nL 268.460986 182.450672 \nL 268.718054 182.343113 \nL 269.250666 182.135473 \nL 269.646734 182.025284 \nL 269.865534 181.968807 \nL 270.126938 181.832402 \nL 270.376279 181.698732 \nL 270.667534 181.59777 \nL 270.871561 181.529553 \nL 271.202816 181.418539 \nL 271.584987 181.240899 \nL 271.690671 181.137292 \nL 271.880388 181.071037 \nL 272.07993 180.967538 \nL 272.539239 180.678769 \nL 272.850198 180.575084 \nL 273.035925 180.517697 \nL 273.670845 180.26907 \nL 273.894372 180.164202 \nL 274.137178 180.042833 \nL 274.268247 179.93897 \nL 274.539463 179.844232 \nL 274.90895 179.738166 \nL 275.206704 179.642239 \nL 275.807164 179.448455 \nL 276.294454 179.174179 \nL 276.488155 179.079122 \nL 276.623338 179.013864 \nL 276.738942 178.906331 \nL 276.863903 178.81681 \nL 277.160736 178.733889 \nL 277.303787 178.586043 \nL 277.721246 178.481118 \nL 277.872259 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288.506784 173.244252 \nL 288.66163 173.221595 \nL 288.83916 173.110785 \nL 289.06218 173.065102 \nL 289.436944 172.955524 \nL 289.566364 172.904823 \nL 289.884795 172.799531 \nL 290.035777 172.749396 \nL 290.261468 172.666178 \nL 290.388946 172.595107 \nL 290.613181 172.488196 \nL 290.76216 172.425681 \nL 291.051501 172.331853 \nL 291.184527 172.129313 \nL 291.552346 171.91534 \nL 291.822942 171.809646 \nL 291.983202 171.736637 \nL 292.200981 171.626564 \nL 292.913534 171.244187 \nL 293.099134 171.149957 \nL 293.89851 170.761676 \nL 294.045782 170.590885 \nL 294.325203 170.517764 \nL 294.450477 170.35803 \nL 294.810768 170.256422 \nL 294.955597 170.177833 \nL 295.148105 170.089264 \nL 295.285196 169.997403 \nL 295.612812 169.89595 \nL 295.74195 169.847533 \nL 295.972279 169.754993 \nL 296.114056 169.672681 \nL 296.336105 169.57021 \nL 296.490333 169.523713 \nL 296.690846 169.421903 \nL 296.864028 169.352961 \nL 297.162471 169.243093 \nL 297.439551 169.116976 \nL 298.106646 168.744674 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163.393294 \nL 308.881736 163.291723 \nL 309.020227 163.209506 \nL 309.094654 163.128203 \nL 309.216706 162.971571 \nL 310.146936 162.461106 \nL 310.297843 162.339962 \nL 310.562221 162.234973 \nL 310.701668 162.197811 \nL 310.881903 162.086593 \nL 311.490277 161.695612 \nL 311.617227 161.569307 \nL 311.860145 161.458373 \nL 312.262617 161.29971 \nL 312.387782 161.242749 \nL 312.696954 161.132164 \nL 312.880628 161.089868 \nL 313.236281 160.980429 \nL 313.609189 160.684485 \nL 314.294341 160.337466 \nL 314.410109 160.239512 \nL 314.68887 160.138067 \nL 314.832499 160.056255 \nL 315.17567 159.95018 \nL 315.370125 159.890268 \nL 315.620469 159.780317 \nL 315.977456 159.627307 \nL 316.206384 159.528896 \nL 316.33677 159.434486 \nL 317.359637 158.92096 \nL 317.646444 158.813038 \nL 317.76437 158.717108 \nL 318.139127 158.61295 \nL 318.260482 158.550971 \nL 318.506853 158.444729 \nL 318.712057 158.319699 \nL 318.854352 158.210793 \nL 319.186408 158.051353 \nL 319.384673 157.940785 \nL 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115.12164 244.606284 \nL 115.494649 244.433108 \nL 115.6802 244.19166 \nL 116.049416 244.175033 \nL 116.23309 243.962402 \nL 116.416146 243.532956 \nL 116.598589 243.479935 \nL 116.780423 243.276728 \nL 117.142279 242.489519 \nL 117.322309 242.336924 \nL 117.680594 241.51055 \nL 118.036538 241.078372 \nL 118.213641 241.020384 \nL 118.566129 240.696222 \nL 119.090619 240.355703 \nL 119.437494 240.053773 \nL 119.610106 239.989446 \nL 120.295136 239.14525 \nL 120.634446 238.156937 \nL 121.30679 237.287709 \nL 121.473587 237.244363 \nL 121.970934 236.468641 \nL 122.952207 235.068719 \nL 123.114047 235.019424 \nL 124.39174 233.589167 \nL 126.558015 231.409088 \nL 126.860566 231.326335 \nL 127.460673 230.50257 \nL 127.758265 229.6583 \nL 128.201625 229.454346 \nL 129.077663 228.559429 \nL 129.222309 228.489971 \nL 129.939831 227.644487 \nL 130.788562 227.164345 \nL 131.208019 226.455642 \nL 131.347123 226.339939 \nL 131.624269 225.783824 \nL 131.762315 225.758769 \nL 132.037362 225.175639 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207.093706 \nL 151.15895 206.876386 \nL 151.543822 206.683573 \nL 151.735243 206.542051 \nL 152.682382 205.847609 \nL 152.963342 205.498706 \nL 153.42841 205.38009 \nL 153.88954 204.958003 \nL 154.164356 204.876572 \nL 154.709861 204.460478 \nL 154.80025 204.456362 \nL 154.980578 204.309697 \nL 155.160311 204.201891 \nL 155.339454 204.003896 \nL 155.518008 203.907661 \nL 156.050187 203.63012 \nL 156.314338 203.481109 \nL 157.444417 202.483375 \nL 157.958187 202.307888 \nL 158.298026 202.016327 \nL 158.635759 201.626804 \nL 160.130159 200.647014 \nL 160.375286 200.477079 \nL 160.456751 200.453928 \nL 160.862257 199.938514 \nL 161.264765 199.712485 \nL 161.50485 199.579488 \nL 162.13995 199.190964 \nL 162.376215 199.045856 \nL 162.454743 199.037339 \nL 162.61146 198.739413 \nL 163.001291 198.642307 \nL 163.542409 198.305471 \nL 163.696031 198.275722 \nL 163.925656 198.081952 \nL 164.154316 198.051098 \nL 164.608776 197.553539 \nL 164.984617 197.249019 \nL 165.059475 197.249019 \nL 165.208883 197.128997 \nL 165.432229 197.072171 \nL 165.654663 196.808081 \nL 165.949835 196.721306 \nL 166.680841 196.467553 \nL 166.898244 196.205511 \nL 169.785572 194.814323 \nL 169.990949 194.725268 \nL 170.331533 194.592889 \nL 171.273989 194.107678 \nL 171.47384 194.007766 \nL 171.805302 193.720788 \nL 172.527496 193.435414 \nL 172.787755 193.229181 \nL 173.304572 193.10785 \nL 173.943771 192.709747 \nL 174.260579 192.644202 \nL 174.512705 192.457696 \nL 175.013483 192.344719 \nL 175.817551 192.079503 \nL 176.001431 191.830855 \nL 176.549376 191.599181 \nL 177.390925 191.087895 \nL 177.569577 191.006572 \nL 177.925133 190.836538 \nL 178.160887 190.742888 \nL 178.337036 190.634277 \nL 178.745846 190.538233 \nL 179.382126 190.2863 \nL 180.011058 190.078024 \nL 180.237971 189.930716 \nL 180.52029 189.849886 \nL 180.913093 189.692478 \nL 181.303084 189.454076 \nL 181.800431 189.279115 \nL 182.074785 189.035488 \nL 182.72765 188.872908 \nL 183.051171 188.71744 \nL 183.532877 188.622579 \nL 183.957511 188.289153 \nL 184.063155 188.26374 \nL 184.221237 188.151746 \nL 184.431301 188.048846 \nL 185.056676 187.661279 \nL 185.263549 187.414495 \nL 185.623696 187.324674 \nL 185.879493 187.162454 \nL 186.235603 187.111149 \nL 186.488549 186.731775 \nL 186.890834 186.582451 \nL 187.140762 186.365038 \nL 189.721786 185.207759 \nL 189.864287 185.159511 \nL 190.100964 184.96734 \nL 190.336616 184.852095 \nL 190.477519 184.757501 \nL 190.711551 184.715579 \nL 190.898056 184.621411 \nL 191.17662 184.56887 \nL 191.453766 184.252518 \nL 191.775331 184.208546 \nL 192.049455 183.97773 \nL 193.399751 183.330067 \nL 194.062548 183.229689 \nL 194.23794 183.000577 \nL 194.717375 182.893529 \nL 195.149593 182.821126 \nL 195.450117 182.763258 \nL 195.621104 182.608858 \nL 195.791555 182.541296 \nL 196.046236 182.438336 \nL 196.257564 182.327769 \nL 197.177787 182.098074 \nL 197.343442 181.962768 \nL 197.9193 181.822569 \nL 198.204961 181.71538 \nL 199.611214 181.054054 \nL 199.848682 180.931039 \nL 201.788315 180.247625 \nL 202.092345 180.152924 \nL 202.243726 180.028561 \nL 202.432362 179.945914 \nL 202.770269 179.790055 \nL 203.217574 179.741683 \nL 203.365863 179.61974 \nL 203.661236 179.497932 \nL 203.955015 179.420308 \nL 204.429051 179.366038 \nL 204.574082 179.27669 \nL 204.75483 179.177705 \nL 204.898997 179.072583 \nL 205.221985 178.904368 \nL 205.507486 178.692159 \nL 205.968256 178.538468 \nL 206.249881 178.296241 \nL 206.495114 178.255689 \nL 206.774035 177.903044 \nL 207.120689 177.686287 \nL 207.533782 177.605073 \nL 207.670786 177.42606 \nL 208.181504 177.325837 \nL 210.177787 176.284844 \nL 210.308306 176.113251 \nL 210.5035 176.01726 \nL 210.924036 175.808233 \nL 212.88617 175.111385 \nL 213.504329 175.005769 \nL 213.657778 174.903038 \nL 213.902401 174.793527 \nL 214.267288 174.566698 \nL 215.614244 173.990639 \nL 215.76187 173.90778 \nL 216.114548 173.707503 \nL 216.552208 173.419584 \nL 218.884497 172.331308 \nL 219.106779 172.312743 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165.905959 \nL 231.258989 165.730888 \nL 231.436164 165.645606 \nL 232.008034 165.40349 \nL 232.160979 165.343742 \nL 232.573962 165.157719 \nL 233.005324 165.046033 \nL 233.283888 164.920762 \nL 233.411977 164.85684 \nL 233.752082 164.748715 \nL 233.900212 164.620633 \nL 234.405052 164.454234 \nL 234.572297 164.395133 \nL 234.822205 164.200608 \nL 234.967458 164.03928 \nL 235.174291 163.884564 \nL 236.479741 163.18295 \nL 236.620645 162.980891 \nL 236.821305 162.887831 \nL 236.981303 162.662997 \nL 237.180641 162.537525 \nL 237.438695 162.459225 \nL 237.616634 162.306922 \nL 238.127438 162.015687 \nL 238.264147 161.945991 \nL 238.575343 161.846906 \nL 238.826887 161.58685 \nL 239.134893 161.479699 \nL 239.36476 161.313518 \nL 241.739836 160.020797 \nL 242.08642 159.914554 \nL 242.304184 159.675294 \nL 242.629207 159.588467 \nL 242.755082 159.516611 \nL 243.113132 159.408419 \nL 243.362373 159.252375 \nL 243.504287 159.142788 \nL 243.962967 158.981701 \nL 244.365527 158.75941 \nL 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150.661744 \nL 256.535172 150.552019 \nL 256.674454 150.52002 \nL 256.938112 150.410839 \nL 257.090174 150.290002 \nL 257.172939 150.197579 \nL 257.406758 150.032044 \nL 257.639578 149.928777 \nL 257.789697 149.807133 \nL 258.020889 149.674045 \nL 258.156427 149.634073 \nL 258.64159 149.525987 \nL 261.28652 147.908137 \nL 261.541539 147.77166 \nL 262.236745 147.348323 \nL 262.33713 147.26979 \nL 262.474859 147.171413 \nL 262.662111 147.06291 \nL 262.86114 146.946645 \nL 263.009936 146.822737 \nL 263.183018 146.717911 \nL 263.293996 146.62975 \nL 263.478457 146.471586 \nL 263.76009 146.344814 \nL 263.967322 146.180924 \nL 264.11313 146.061166 \nL 264.282747 145.95146 \nL 264.500053 145.78069 \nL 264.644443 145.672158 \nL 264.824394 145.536704 \nL 264.991813 145.435481 \nL 265.561947 144.987927 \nL 265.809516 144.865101 \nL 266.371197 144.521475 \nL 266.64988 144.204516 \nL 266.80024 144.100785 \nL 267.088232 143.858446 \nL 267.317534 143.757559 \nL 267.568656 143.589722 \nL 267.693784 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136.383381 \nL 277.692884 136.23364 \nL 277.919365 136.08378 \nL 278.369521 135.671159 \nL 278.583909 135.561955 \nL 278.890042 135.37377 \nL 279.037853 135.21919 \nL 279.176063 135.120605 \nL 279.313923 135.078412 \nL 279.524632 134.982236 \nL 279.670733 134.887772 \nL 279.925471 134.780367 \nL 280.079553 134.652248 \nL 280.296343 134.549916 \nL 280.610954 134.152379 \nL 280.763113 134.052179 \nL 280.914847 133.897824 \nL 281.092818 133.799082 \nL 281.234777 133.680727 \nL 281.499958 133.528606 \nL 281.7463 133.371253 \nL 281.895323 133.265467 \nL 282.096296 133.031799 \nL 282.287839 132.894823 \nL 282.504687 132.785355 \nL 282.668916 132.61106 \nL 283.081618 132.349248 \nL 283.235578 132.136681 \nL 283.440184 132.027299 \nL 283.923064 131.747567 \nL 284.099893 131.632653 \nL 284.376613 131.452848 \nL 284.518618 131.281502 \nL 284.635287 131.175196 \nL 284.901023 131.023894 \nL 284.9838 130.928986 \nL 285.157224 130.749819 \nL 285.346533 130.639286 \nL 285.486035 130.519946 \nL 285.666038 130.432239 \nL 285.821018 130.291362 \nL 285.98368 130.180459 \nL 286.323697 129.840048 \nL 286.492912 129.737712 \nL 286.653583 129.543486 \nL 286.861748 129.438906 \nL 287.1884 129.185203 \nL 287.347035 129.031529 \nL 287.481512 128.895739 \nL 287.607775 128.81275 \nL 287.835885 128.711822 \nL 288.055226 128.331233 \nL 288.203563 128.231668 \nL 288.452484 127.975968 \nL 288.731167 127.880086 \nL 288.946939 127.690635 \nL 289.09287 127.608065 \nL 289.238411 127.451212 \nL 289.421698 127.368223 \nL 289.55876 127.257944 \nL 289.884795 127.147399 \nL 290.171304 126.933412 \nL 290.246451 126.829658 \nL 290.403924 126.762886 \nL 290.463793 126.689641 \nL 290.598261 126.526164 \nL 290.955225 126.35322 \nL 291.859406 125.622175 \nL 292.244432 125.425927 \nL 292.439536 125.293597 \nL 292.583608 125.185644 \nL 292.734474 125.070095 \nL 292.870613 124.962194 \nL 293.36217 124.559546 \nL 293.461367 124.447486 \nL 293.638057 124.269015 \nL 294.644776 123.577648 \nL 294.783138 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160.284228 \nL 198.041909 160.185766 \nL 198.610467 159.549765 \nL 198.771827 159.45715 \nL 199.012975 159.311825 \nL 199.173149 159.189899 \nL 199.650864 158.742165 \nL 199.809176 158.484571 \nL 199.888159 158.481558 \nL 200.045784 158.306427 \nL 200.242175 158.238041 \nL 200.827133 157.561913 \nL 200.943375 157.470171 \nL 201.097979 157.225764 \nL 201.864482 156.69208 \nL 202.281505 156.322005 \nL 202.620346 156.110389 \nL 202.770269 155.91933 \nL 202.88244 155.89307 \nL 203.06888 155.606507 \nL 203.476816 155.264063 \nL 203.734829 155.126598 \nL 203.918379 154.973967 \nL 204.028213 154.949366 \nL 204.174314 154.620654 \nL 204.356391 154.521665 \nL 204.501615 154.363715 \nL 205.006873 153.850195 \nL 205.078671 153.754794 \nL 205.329223 153.134911 \nL 206.10925 152.170597 \nL 206.355116 152.045796 \nL 206.530057 151.964213 \nL 206.982292 151.854026 \nL 207.155233 151.682704 \nL 207.36204 151.395583 \nL 207.943765 150.814722 \nL 208.181504 150.568073 \nL 208.350684 150.389944 \nL 208.519341 150.300815 \nL 208.721042 150.082955 \nL 208.855095 149.94278 \nL 209.487381 149.408159 \nL 209.652559 149.263113 \nL 209.784341 149.140399 \nL 210.177787 148.678609 \nL 210.471016 148.58156 \nL 210.827277 148.013646 \nL 211.149141 147.789667 \nL 211.437201 147.240823 \nL 211.532883 147.186281 \nL 211.723745 146.995159 \nL 212.008789 146.883174 \nL 212.229463 146.665271 \nL 212.292349 146.587244 \nL 212.543169 146.384526 \nL 212.605694 146.346978 \nL 212.792839 146.173702 \nL 212.855078 146.077953 \nL 213.134276 145.744331 \nL 213.412051 145.597866 \nL 213.688416 145.348082 \nL 214.024302 144.655723 \nL 214.297585 144.486235 \nL 214.810075 144.101583 \nL 214.959894 144.034009 \nL 215.109302 143.962436 \nL 215.16895 143.898973 \nL 215.347505 143.76704 \nL 215.525476 143.695631 \nL 215.702868 143.510126 \nL 215.909097 143.399871 \nL 216.114548 143.200204 \nL 216.899821 142.311101 \nL 217.044007 142.09822 \nL 217.187813 141.970383 \nL 217.44571 141.667607 \nL 217.58846 141.521009 \nL 217.759268 141.367567 \nL 217.957868 141.261248 \nL 218.155748 141.170977 \nL 218.324788 141.057571 \nL 218.577369 140.60138 \nL 218.828784 140.50464 \nL 219.02353 140.349422 \nL 219.245247 140.242725 \nL 219.548641 139.725786 \nL 219.713419 139.529514 \nL 219.795622 139.476658 \nL 220.095974 139.064064 \nL 221.227773 138.076252 \nL 221.467272 137.986168 \nL 221.652823 137.826211 \nL 221.86411 137.701831 \nL 222.179511 137.291944 \nL 222.908421 136.291707 \nL 223.423161 135.928355 \nL 223.627703 135.777068 \nL 223.704208 135.704859 \nL 223.907699 135.480113 \nL 224.789138 134.763205 \nL 224.888972 134.70888 \nL 225.013507 134.573932 \nL 225.187379 134.457517 \nL 225.360698 134.289887 \nL 225.828372 133.916264 \nL 225.999666 133.832105 \nL 226.219112 133.607481 \nL 226.267758 133.560635 \nL 226.413436 133.452537 \nL 226.461909 133.428495 \nL 226.607069 133.164089 \nL 226.751843 133.063433 \nL 227.136036 132.746387 \nL 227.350959 132.647455 \nL 229.888733 130.25213 \nL 229.956935 130.220917 \nL 230.093083 130.061027 \nL 230.20628 129.95932 \nL 230.409444 129.744127 \nL 230.723978 129.373942 \nL 231.014428 129.313153 \nL 231.192399 129.130153 \nL 231.942355 128.388223 \nL 232.378728 128.058753 \nL 232.682123 127.568682 \nL 232.876273 127.482339 \nL 233.069734 127.379827 \nL 233.411977 127.137319 \nL 233.475908 127.04819 \nL 233.667254 126.780531 \nL 233.752082 126.68748 \nL 233.879076 126.587663 \nL 234.216285 126.237422 \nL 234.530534 125.781697 \nL 234.697395 125.714814 \nL 234.84298 125.559282 \nL 234.925997 125.457224 \nL 235.380342 125.035504 \nL 235.483076 124.924686 \nL 235.687963 124.639724 \nL 235.790119 124.544871 \nL 235.953171 124.389696 \nL 236.439416 124.158888 \nL 236.600538 123.961277 \nL 236.801272 123.658035 \nL 236.921359 123.550179 \nL 237.596892 122.632172 \nL 237.911913 122.397121 \nL 238.517129 121.953825 \nL 238.672228 121.728089 \nL 238.923326 121.62112 \nL 239.096487 121.457442 \nL 239.249948 121.361695 \nL 239.441167 121.107272 \nL 239.745728 120.846151 \nL 239.935217 120.735423 \nL 240.199399 120.523836 \nL 240.368556 120.426551 \nL 241.758132 119.268133 \nL 241.97721 119.193786 \nL 242.177261 118.943336 \nL 242.340394 118.833196 \nL 243.059574 118.378472 \nL 243.220089 118.149022 \nL 243.380133 117.977155 \nL 243.698815 117.604569 \nL 244.120845 117.203694 \nL 244.260798 117.06221 \nL 244.382963 116.99253 \nL 244.730501 116.373215 \nL 244.851618 116.276123 \nL 245.401889 115.799049 \nL 245.640895 115.694946 \nL 245.929713 115.438159 \nL 246.098894 115.340152 \nL 247.6476 113.918799 \nL 247.909659 113.700468 \nL 248.10538 113.607172 \nL 248.430026 113.037056 \nL 248.575487 112.960128 \nL 248.720561 112.789795 \nL 248.83313 112.713815 \nL 249.041571 112.492733 \nL 249.18541 112.381926 \nL 249.344788 112.252712 \nL 249.5037 112.131905 \nL 249.772791 111.961657 \nL 249.977673 111.686879 \nL 250.244438 111.491204 \nL 250.416356 111.304455 \nL 250.541048 111.2128 \nL 250.712035 111.088729 \nL 250.867013 110.950078 \nL 251.574284 110.046574 \nL 251.78773 109.936064 \nL 252.000343 109.797749 \nL 252.332781 109.39037 \nL 252.513258 109.281665 \nL 252.723063 109.014675 \nL 253.006511 108.919803 \nL 253.140262 108.693729 \nL 253.258877 108.634896 \nL 253.406784 108.463036 \nL 253.51008 108.405887 \nL 253.642602 108.266911 \nL 254.806614 107.415992 \nL 255.007783 107.153171 \nL 255.208211 106.988789 \nL 255.350924 106.8396 \nL 255.450601 106.744351 \nL 255.606868 106.703806 \nL 255.903958 106.60684 \nL 256.10112 106.399838 \nL 256.213465 106.276177 \nL 256.353571 105.970233 \nL 256.549116 105.876967 \nL 257.172939 105.145035 \nL 257.324348 105.039416 \nL 257.925811 104.465216 \nL 258.0887 104.226781 \nL 258.332123 103.995994 \nL 258.507255 103.632445 \nL 258.601324 103.527198 \nL 258.762208 103.399068 \nL 259.095864 103.251471 \nL 259.665013 102.761779 \nL 259.757105 102.658342 \nL 259.9932 102.551017 \nL 260.110865 102.450184 \nL 260.332429 102.109038 \nL 260.436384 101.944889 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76.582066 \nL 289.467424 76.483184 \nL 289.725812 76.213546 \nL 289.952789 76.109265 \nL 290.088522 76.020584 \nL 290.23143 75.886353 \nL 290.411411 75.695421 \nL 290.523598 75.591398 \nL 290.784471 75.258083 \nL 290.962637 75.152576 \nL 291.405517 74.676821 \nL 291.530347 74.588196 \nL 291.684156 74.484698 \nL 291.822942 74.394398 \nL 292.128485 74.037134 \nL 292.266145 73.933313 \nL 292.468381 73.717985 \nL 292.605186 73.612026 \nL 292.741648 73.479934 \nL 292.934982 73.333221 \nL 293.077751 73.167731 \nL 293.191697 73.073988 \nL 293.333795 72.994499 \nL 293.574515 72.887603 \nL 293.905532 72.456539 \nL 294.206624 72.233001 \nL 294.387876 72.131573 \nL 294.533833 71.974579 \nL 294.672476 71.871192 \nL 294.879782 71.712036 \nL 295.038184 71.566057 \nL 295.333096 71.302446 \nL 295.456075 71.210567 \nL 295.544721 71.123812 \nL 295.714789 70.906714 \nL 295.809795 70.796557 \nL 295.985798 70.664611 \nL 296.167969 70.587587 \nL 296.309238 70.39207 \nL 296.577313 70.224089 \nL 296.724193 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121.30679 224.253591 \nL 121.473587 224.18267 \nL 121.970934 223.186844 \nL 122.135713 223.12563 \nL 122.463781 222.554333 \nL 122.789884 221.662957 \nL 123.916111 219.794996 \nL 124.233658 218.933227 \nL 124.863251 218.296056 \nL 125.640142 217.306661 \nL 125.947822 216.797558 \nL 126.101012 216.706073 \nL 126.7095 215.876356 \nL 127.011214 215.664468 \nL 127.460673 214.841989 \nL 127.758265 213.829465 \nL 128.054239 213.302995 \nL 128.348614 213.196691 \nL 128.932632 211.971042 \nL 129.077663 211.92371 \nL 129.653956 210.979869 \nL 129.797081 210.878605 \nL 130.507119 209.586601 \nL 130.788562 209.315967 \nL 130.92874 208.721357 \nL 131.068559 208.720523 \nL 131.624269 207.810911 \nL 131.762315 207.788956 \nL 132.174366 207.096852 \nL 133.525779 205.067091 \nL 133.659094 205.067091 \nL 133.792084 204.921919 \nL 134.057092 204.372555 \nL 134.452203 203.827983 \nL 136.385867 201.033336 \nL 136.512369 200.924049 \nL 137.14051 199.833668 \nL 137.265273 199.824366 \nL 137.389751 199.686393 \nL 137.637857 199.240049 \nL 138.375464 198.568227 \nL 138.497433 198.287575 \nL 138.61913 198.287575 \nL 138.86171 197.897457 \nL 138.982596 197.851808 \nL 139.343652 197.438068 \nL 139.821367 197.110607 \nL 140.176923 196.655088 \nL 140.412678 196.071853 \nL 140.647416 195.805072 \nL 140.881146 195.539894 \nL 141.113878 195.469961 \nL 141.34562 195.255568 \nL 141.691393 194.638321 \nL 142.034985 194.076808 \nL 142.149036 194.076808 \nL 142.489762 193.520655 \nL 142.828369 192.989053 \nL 143.276595 192.038347 \nL 143.721162 191.458043 \nL 144.162129 191.001814 \nL 144.271815 190.921633 \nL 144.490527 190.29623 \nL 144.599554 190.266465 \nL 144.925333 189.593413 \nL 145.249174 189.277533 \nL 145.356695 189.249446 \nL 146.84011 186.929557 \nL 147.048766 186.832286 \nL 147.256625 186.458289 \nL 147.77283 186.126729 \nL 148.891545 184.275825 \nL 149.392552 184.002394 \nL 149.690959 183.602226 \nL 149.790066 183.587152 \nL 150.282913 182.864392 \nL 150.478809 182.790306 \nL 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202.20592 131.129787 \nL 202.657866 131.02353 \nL 202.957093 130.877325 \nL 203.180439 130.602583 \nL 203.698045 130.468155 \nL 203.991626 130.213292 \nL 204.283633 130.044051 \nL 204.429051 129.936316 \nL 204.718728 129.836142 \nL 204.862991 129.709845 \nL 205.006873 129.634666 \nL 205.221985 129.520461 \nL 205.47188 129.126766 \nL 205.649677 129.050722 \nL 206.074036 128.754155 \nL 206.214757 128.717345 \nL 206.355116 128.549172 \nL 206.495114 128.482478 \nL 206.634753 128.410122 \nL 207.773313 127.763066 \nL 207.977791 127.584171 \nL 208.113684 127.495868 \nL 208.283075 127.379829 \nL 208.451941 127.284909 \nL 208.821612 126.977984 \nL 208.955419 126.874359 \nL 209.388033 126.644688 \nL 209.553512 126.589307 \nL 209.784341 126.321215 \nL 210.046954 126.212259 \nL 210.405991 126.078527 \nL 210.665629 125.934009 \nL 211.020624 125.856551 \nL 211.277356 125.662285 \nL 211.373319 125.59701 \nL 211.532883 125.43001 \nL 211.75549 125.325495 \nL 212.040369 125.167015 \nL 212.417903 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            "text/plain": "<Figure size 576x396 with 1 Axes>"
          },
          "metadata": {}
        }
      ],
      "execution_count": 100,
      "metadata": {
        "scrolled": false
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for prob in [0,4]:\n",
        "# prob=4\n",
        "    fig=figure()\n",
        "    plot()\n",
        "    beta0 = probparams[prob]['beta']\n",
        "    plot( [algparams[j]['beta'] for j in range(len(algparams))], [coeffs[prob,j] for j in range(len(algparams))] , 'ro-', label=r'$\\hat s$ ($T=20000$)')\n",
        "    plot( [algparams[j]['beta'] for j in range(len(algparams))], [coeffs2[prob,j] for j in range(len(algparams))] , 'rv--', alpha=0.5, label=r'$\\hat s$ ($T=10000$)')\n",
        "    plot( [algparams[j]['beta'] for j in range(len(algparams))], [coeffs3[prob,j] for j in range(len(algparams))] , 'r^--', alpha=0.5, label=r'$\\hat s$ ($T=5000$)')\n",
        "    plot( [algparams[j]['beta'] for j in range(len(algparams))], [coeffs4[prob,j] for j in range(len(algparams))] , 'r>--', alpha=0.5, label=r'$\\hat s$ ($T=2500$)')\n",
        "    plot( [algparams[j]['beta'] for j in range(len(algparams))], [d/(2*algparams[j]['beta']+d) for j in range(len(algparams))] , 'bo-.', label=r'$s^*$')\n",
        "    axvline(beta0, color='k', linestyle=':', label=r'$\\beta_0$')\n",
        "    xlabel(r'$\\beta$')\n",
        "    ylabel(r'slope')\n",
        "    legend(bbox_to_anchor=(0.5, 1), loc='upper right')\n",
        "    adjustFigAspect(fig)\n",
        "    savefig('slope_{:.1f}.pdf'.format(beta0),bbox_inches = 'tight',pad_inches = 0)\n",
        "# forceAspect(plt.gca())\n",
        "# axes.set_aspect(10)\n",
        "#     plt.axes().set_aspect(aspect=10)\n",
        "#     xlim(0,11)\n"
      ],
      "outputs": [
        {
          "output_type": "display_data",
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            "text/plain": "<Figure size 576x396 with 1 Axes>"
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