phy-4660/lag/data/clag_analysis-origbins-noLFerrors.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/dist-packages/IPython/core/magics/pylab.py:161: UserWarning: pylab import has clobbered these variables: ['norm']\n",
      "`%matplotlib` prevents importing * from pylab and numpy\n",
      "  \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Container object of 3 artists>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tvhMr3fCZ8Lp89zzkk4IHhw3vbrVPgqN3hXp1RoCTIhcg+4IZ3239oquHGZIZ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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f676e282ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from scipy.stats import norm\n",
    "from scipy.stats import lognorm\n",
    "import sys\n",
    "import getopt\n",
    "sys.path.insert(1,\"/usr/local/science/clag/\")\n",
    "import clag\n",
    "%pylab inline\n",
    "\n",
    "ref_file=\"lc/1367A.lc\"\n",
    "echo_file=\"lc/2246A.lc\"\n",
    "\n",
    "\n",
    "dt = 0.01\n",
    "t1, l1, l1e = np.loadtxt(ref_file).T\n",
    "errorbar(t1, l1, yerr=l1e, fmt='o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.005     ,  0.01861938,  0.04473305,  0.06933623,  0.10747115,\n",
       "        0.16658029,  0.25819945,  0.40020915,  0.62032418])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "\n",
    "fqL = np.array([0.0049999999, 0.018619375, 0.044733049, 0.069336227, 0.10747115, 0.16658029, \n",
    "                0.25819945, 0.40020915, 0.62032418])\n",
    "# fqL = np.logspace(np.log10(0.0006),np.log10(1.2),11)\n",
    "nfq = len(fqL) - 1\n",
    "fqd = 10**(np.log10( (fqL[:-1]*fqL[1:]) )/2.)\n",
    "\n",
    "\n",
    "fqL\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   1 4.342e-01 5.077e+01 inf -- -5.530e+02 -- 1 1 1 1 1 1 1 1\n",
      "   2 7.674e-01 5.065e+01 8.300e+01 -- -4.700e+02 -- 0.653018 0.587019 0.568277 0.567457 0.566281 0.566085 0.565773 0.566163\n",
      "   3 3.298e+00 5.043e+01 8.075e+01 -- -3.893e+02 -- 0.414806 0.209135 0.141159 0.13784 0.133393 0.132728 0.131612 0.132761\n",
      "   4 1.572e+00 5.010e+01 7.754e+01 -- -3.117e+02 -- 0.322539 -0.0834456 -0.273066 -0.284295 -0.297612 -0.299435 -0.302479 -0.300412\n",
      "   5 5.908e-01 4.964e+01 7.386e+01 -- -2.379e+02 -- 0.302357 -0.214604 -0.654658 -0.688754 -0.723838 -0.729279 -0.736418 -0.733888\n",
      "   6 3.713e-01 4.877e+01 6.953e+01 -- -1.683e+02 -- 0.284419 -0.200357 -0.96379 -1.05472 -1.13798 -1.15477 -1.17031 -1.16748\n",
      "   7 2.709e-01 4.671e+01 6.269e+01 -- -1.056e+02 -- 0.277768 -0.185001 -1.13047 -1.34026 -1.52128 -1.56845 -1.6043 -1.60101\n",
      "   8 2.135e-01 4.361e+01 5.281e+01 -- -5.282e+01 -- 0.277012 -0.185189 -1.16375 -1.49463 -1.83211 -1.9477 -2.03737 -2.03476\n",
      "   9 1.764e-01 3.767e+01 4.019e+01 -- -1.264e+01 -- 0.282161 -0.184207 -1.17891 -1.53049 -2.01851 -2.24569 -2.46562 -2.46922\n",
      "  10 1.508e-01 2.738e+01 2.645e+01 -- 1.382e+01 -- 0.289545 -0.182463 -1.18795 -1.52893 -2.08812 -2.41103 -2.87498 -2.90486\n",
      "  11 1.349e-01 1.468e+01 1.390e+01 -- 2.772e+01 -- 0.293547 -0.180898 -1.1897 -1.52803 -2.10944 -2.46526 -3.22702 -3.34288\n",
      "  12 1.358e-01 5.365e+00 5.378e+00 -- 3.309e+01 -- 0.295456 -0.179941 -1.19052 -1.52801 -2.11928 -2.48294 -3.46233 -3.79368\n",
      "  13 1.868e-01 1.338e+00 1.633e+00 -- 3.473e+01 -- 0.297315 -0.17923 -1.19104 -1.52666 -2.12491 -2.48975 -3.55567 -4.30889\n",
      "  14 6.248e-01 2.604e-01 4.517e-01 -- 3.518e+01 -- 0.299091 -0.178645 -1.191 -1.52463 -2.12805 -2.4915 -3.5672 -5.11363\n",
      "  15 2.744e+02 2.611e-01 7.022e-02 -- 3.525e+01 -- 0.300248 -0.178286 -1.19075 -1.52307 -2.12961 -2.49161 -3.56337 -8\n",
      "  16 2.745e+02 2.782e-01 4.368e-04 -- 3.525e+01 -- 0.300566 -0.178158 -1.19062 -1.52252 -2.13009 -2.49151 -3.5617 -8\n",
      "  17 2.745e+02 2.805e-01 6.410e-05 -- 3.525e+01 -- 0.300599 -0.178134 -1.19059 -1.52242 -2.13017 -2.49148 -3.56148 -8\n",
      "********************\n",
      "0.300599 -0.178134 -1.19059 -1.52242 -2.13017 -2.49148 -3.56148 -8\n",
      "0.238931 0.202434 0.232634 0.177249 0.153039 0.132988 0.297259 3285.23\n",
      "-0.000915535 -0.00131061 -0.00195128 -0.00497899 -0.0226059 -0.0776175 -0.280541 -0.000206646\n",
      "********************\n"
     ]
    }
   ],
   "source": [
    "P1 = clag.clag('psd10r', [t1], [l1], [l1e], dt, fqL)\n",
    "p1 = np.ones(nfq)\n",
    "p1, p1e = clag.optimize(P1, p1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t### errors for param 0 ###\n",
      "+++ 3.525e+01 3.480e+01 3.006e-01 5.395e-01 0.891 +++\n",
      "+++ 3.525e+01 3.431e+01 3.006e-01 6.590e-01 1.87 +++\n",
      "+++ 3.525e+01 3.458e+01 3.006e-01 5.993e-01 1.34 +++\n",
      "+++ 3.525e+01 3.469e+01 3.006e-01 5.694e-01 1.11 +++\n",
      "+++ 3.525e+01 3.475e+01 3.006e-01 5.545e-01 0.997 +++\n",
      "\t### errors for param 1 ###\n",
      "+++ 3.525e+01 3.476e+01 -1.781e-01 2.430e-02 0.973 +++\n",
      "+++ 3.525e+01 3.421e+01 -1.781e-01 1.255e-01 2.07 +++\n",
      "+++ 3.525e+01 3.451e+01 -1.781e-01 7.491e-02 1.48 +++\n",
      "+++ 3.525e+01 3.464e+01 -1.781e-01 4.961e-02 1.21 +++\n",
      "+++ 3.525e+01 3.470e+01 -1.781e-01 3.696e-02 1.09 +++\n",
      "+++ 3.525e+01 3.473e+01 -1.781e-01 3.063e-02 1.03 +++\n",
      "+++ 3.525e+01 3.475e+01 -1.781e-01 2.747e-02   1 +++\n",
      "\t### errors for param 2 ###\n",
      "+++ 3.525e+01 3.511e+01 -1.191e+00 -1.074e+00 0.276 +++\n",
      "+++ 3.525e+01 3.495e+01 -1.191e+00 -1.016e+00 0.598 +++\n",
      "+++ 3.525e+01 3.485e+01 -1.191e+00 -9.870e-01 0.8 +++\n",
      "+++ 3.525e+01 3.479e+01 -1.191e+00 -9.725e-01 0.91 +++\n",
      "+++ 3.525e+01 3.476e+01 -1.191e+00 -9.652e-01 0.968 +++\n",
      "+++ 3.525e+01 3.475e+01 -1.191e+00 -9.616e-01 0.997 +++\n",
      "\t### errors for param 3 ###\n",
      "+++ 3.525e+01 3.482e+01 -1.522e+00 -1.345e+00 0.865 +++\n",
      "+++ 3.525e+01 3.432e+01 -1.522e+00 -1.257e+00 1.86 +++\n",
      "+++ 3.525e+01 3.459e+01 -1.522e+00 -1.301e+00 1.32 +++\n",
      "+++ 3.525e+01 3.471e+01 -1.522e+00 -1.323e+00 1.08 +++\n",
      "+++ 3.525e+01 3.476e+01 -1.522e+00 -1.334e+00 0.97 +++\n",
      "+++ 3.525e+01 3.473e+01 -1.522e+00 -1.329e+00 1.03 +++\n",
      "+++ 3.525e+01 3.475e+01 -1.522e+00 -1.331e+00 0.998 +++\n",
      "\t### errors for param 4 ###\n",
      "+++ 3.525e+01 3.481e+01 -2.130e+00 -1.977e+00 0.874 +++\n",
      "+++ 3.525e+01 3.429e+01 -2.130e+00 -1.901e+00 1.91 +++\n",
      "+++ 3.525e+01 3.457e+01 -2.130e+00 -1.939e+00 1.35 +++\n",
      "+++ 3.525e+01 3.470e+01 -2.130e+00 -1.958e+00 1.1 +++\n",
      "+++ 3.525e+01 3.476e+01 -2.130e+00 -1.968e+00 0.983 +++\n",
      "+++ 3.525e+01 3.473e+01 -2.130e+00 -1.963e+00 1.04 +++\n",
      "+++ 3.525e+01 3.474e+01 -2.130e+00 -1.965e+00 1.01 +++\n",
      "+++ 3.525e+01 3.475e+01 -2.130e+00 -1.966e+00 0.997 +++\n",
      "\t### errors for param 5 ###\n",
      "+++ 3.525e+01 3.474e+01 -2.491e+00 -2.358e+00 1.01 +++\n",
      "+++ 3.525e+01 3.512e+01 -2.491e+00 -2.425e+00 0.263 +++\n",
      "+++ 3.525e+01 3.496e+01 -2.491e+00 -2.392e+00 0.579 +++\n",
      "+++ 3.525e+01 3.486e+01 -2.491e+00 -2.375e+00 0.781 +++\n",
      "+++ 3.525e+01 3.480e+01 -2.491e+00 -2.367e+00 0.893 +++\n",
      "+++ 3.525e+01 3.477e+01 -2.491e+00 -2.363e+00 0.952 +++\n",
      "+++ 3.525e+01 3.476e+01 -2.491e+00 -2.361e+00 0.982 +++\n",
      "+++ 3.525e+01 3.475e+01 -2.491e+00 -2.360e+00 0.997 +++\n",
      "\t### errors for param 6 ###\n",
      "+++ 3.525e+01 3.507e+01 -3.561e+00 -3.413e+00 0.363 +++\n",
      "+++ 3.525e+01 3.484e+01 -3.561e+00 -3.339e+00 0.814 +++\n",
      "+++ 3.525e+01 3.468e+01 -3.561e+00 -3.301e+00 1.13 +++\n",
      "+++ 3.525e+01 3.477e+01 -3.561e+00 -3.320e+00 0.962 +++\n",
      "+++ 3.525e+01 3.473e+01 -3.561e+00 -3.311e+00 1.04 +++\n",
      "+++ 3.525e+01 3.475e+01 -3.561e+00 -3.315e+00   1 +++\n",
      "\t### errors for param 7 ###\n",
      "+++ 3.525e+01 3.524e+01 -8.000e+00 -6.000e+00 0.0178 +++\n",
      "+++ 3.525e+01 3.515e+01 -8.000e+00 -5.000e+00 0.187 +++\n",
      "+++ 3.525e+01 3.494e+01 -8.000e+00 -4.500e+00 0.618 +++\n",
      "+++ 3.525e+01 3.466e+01 -8.000e+00 -4.250e+00 1.18 +++\n",
      "+++ 3.525e+01 3.482e+01 -8.000e+00 -4.375e+00 0.851 +++\n",
      "+++ 3.525e+01 3.475e+01 -8.000e+00 -4.312e+00   1 +++\n",
      "********************\n",
      "0.300605 -0.178131 -1.19059 -1.52241 -2.13019 -2.49148 -3.56144 -8\n",
      "0.253864 0.205597 0.228999 0.191096 0.1638 0.131949 0.246154 3.6875\n",
      "********************\n"
     ]
    }
   ],
   "source": [
    "p1, p1e = clag.errors(P1, p1, p1e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 3 artists>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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OIZVKcf36darVKrlcjhs3bpDNZrtdlhQp9yRIkqQg9yRI0gnivkW11CsMCZJ0AkOAhpWH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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f67900fa210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xscale('log'); ylim(-4,2)\n",
    "errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color=\"black\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 3 artists>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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V8jlWyU7BQwrwXFE5GN35bxDSO9Mp+u/hVcIbz1cEZgDlWuX1pf32iBOYzRUF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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f676c054a10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t2, l2, l2e = np.loadtxt(echo_file).T\n",
    "errorbar(t1, l1, yerr=l1e, fmt='o', color=\"green\")\n",
    "errorbar(t2, l2, yerr=l2e, fmt='o', color=\"black\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   1 4.379e-01 6.748e+01 inf -- -3.302e+02 -- 1 1 1 1 1 1 1 1\n",
      "   2 7.796e-01 6.679e+01 7.758e+01 -- -2.526e+02 -- 0.618991 0.579498 0.564066 0.564121 0.56476 0.563682 0.563867 0.56205\n",
      "   3 3.540e+00 6.595e+01 7.576e+01 -- -1.769e+02 -- 0.314779 0.183356 0.127531 0.127909 0.129377 0.127333 0.127748 0.123875\n",
      "   4 1.452e+00 6.481e+01 7.321e+01 -- -1.036e+02 -- 0.145822 -0.154058 -0.309225 -0.308235 -0.306082 -0.309022 -0.308575 -0.314603\n",
      "   5 5.873e-01 6.313e+01 7.037e+01 -- -3.327e+01 -- 0.101594 -0.377738 -0.742409 -0.742747 -0.740971 -0.745083 -0.745333 -0.753741\n",
      "   6 3.716e-01 6.044e+01 6.710e+01 -- 3.383e+01 -- 0.0846307 -0.469976 -1.15278 -1.17038 -1.1732 -1.18022 -1.18308 -1.19385\n",
      "   7 3.359e-01 5.601e+01 6.209e+01 -- 9.591e+01 -- 0.0659456 -0.50867 -1.48798 -1.574 -1.5971 -1.61323 -1.62275 -1.63479\n",
      "   8 5.149e-01 4.857e+01 5.399e+01 -- 1.499e+02 -- 0.0437973 -0.538092 -1.68322 -1.90776 -2.00001 -2.04069 -2.06646 -2.07709\n",
      "   9 7.563e-01 3.652e+01 4.228e+01 -- 1.922e+02 -- 0.0212475 -0.55813 -1.75872 -2.09423 -2.35209 -2.45331 -2.51958 -2.52359\n",
      "  10 1.974e+00 2.058e+01 2.756e+01 -- 2.197e+02 -- 0.00517809 -0.569653 -1.80128 -2.12815 -2.59485 -2.83321 -2.9937 -2.97691\n",
      "  11 1.071e+00 7.198e+00 1.293e+01 -- 2.327e+02 -- -0.00504406 -0.575918 -1.82651 -2.12905 -2.68784 -3.15505 -3.51079 -3.42807\n",
      "  12 2.091e-01 1.531e+00 3.715e+00 -- 2.364e+02 -- -0.0104477 -0.580461 -1.83547 -2.13193 -2.69807 -3.39738 -4.11475 -3.83333\n",
      "  13 5.653e-01 3.932e-01 6.297e-01 -- 2.370e+02 -- -0.0124146 -0.583395 -1.83764 -2.13329 -2.69789 -3.54657 -4.97511 -4.11701\n",
      "  14 1.852e+02 1.372e-01 6.354e-02 -- 2.371e+02 -- -0.0129899 -0.584709 -1.83799 -2.13471 -2.69697 -3.6137 -7.78741 -4.23122\n",
      "  15 2.921e+02 7.159e-02 2.904e-03 -- 2.371e+02 -- -0.0130755 -0.585195 -1.83773 -2.13556 -2.696 -3.63655 -8 -4.24469\n",
      "  16 2.917e+02 5.374e-02 4.141e-04 -- 2.371e+02 -- -0.0130579 -0.585335 -1.83758 -2.13596 -2.69543 -3.64347 -8 -4.24419\n",
      "  17 2.916e+02 4.858e-02 9.106e-05 -- 2.371e+02 -- -0.0130506 -0.585376 -1.83754 -2.13607 -2.69524 -3.64553 -8 -4.24379\n",
      "********************\n",
      "-0.0130506 -0.585376 -1.83754 -2.13607 -2.69524 -3.64553 -8 -4.24379\n",
      "0.269171 0.232445 0.302922 0.233996 0.234912 0.539942 6377.59 0.989373\n",
      "-0.000636424 -0.00149059 -0.00259185 -0.00860622 -0.0213922 -0.0485818 -5.7966e-05 -0.0291693\n",
      "********************\n"
     ]
    }
   ],
   "source": [
    "P2 = clag.clag('psd10r', [t2], [l2], [l2e], dt, fqL)\n",
    "p2 = np.ones(nfq)\n",
    "p2, p2e = clag.optimize(P2, p2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\t### errors for param 0 ###\n",
      "+++ 2.371e+02 2.366e+02 -1.305e-02 2.561e-01 0.96 +++\n",
      "+++ 2.371e+02 2.361e+02 -1.305e-02 3.907e-01   2 +++\n",
      "+++ 2.371e+02 2.364e+02 -1.305e-02 3.234e-01 1.44 +++\n",
      "+++ 2.371e+02 2.365e+02 -1.305e-02 2.898e-01 1.19 +++\n",
      "+++ 2.371e+02 2.365e+02 -1.305e-02 2.729e-01 1.07 +++\n",
      "+++ 2.371e+02 2.366e+02 -1.305e-02 2.645e-01 1.02 +++\n",
      "+++ 2.371e+02 2.366e+02 -1.305e-02 2.603e-01 0.987 +++\n",
      "+++ 2.371e+02 2.366e+02 -1.305e-02 2.624e-01   1 +++\n",
      "\t### errors for param 1 ###\n",
      "+++ 2.371e+02 2.366e+02 -5.854e-01 -3.529e-01 0.949 +++\n",
      "+++ 2.371e+02 2.361e+02 -5.854e-01 -2.367e-01 1.99 +++\n",
      "+++ 2.371e+02 2.364e+02 -5.854e-01 -2.948e-01 1.43 +++\n",
      "+++ 2.371e+02 2.365e+02 -5.854e-01 -3.239e-01 1.18 +++\n",
      "+++ 2.371e+02 2.365e+02 -5.854e-01 -3.384e-01 1.06 +++\n",
      "+++ 2.371e+02 2.366e+02 -5.854e-01 -3.457e-01   1 +++\n",
      "\t### errors for param 2 ###\n",
      "+++ 2.371e+02 2.369e+02 -1.838e+00 -1.686e+00 0.273 +++\n",
      "+++ 2.371e+02 2.368e+02 -1.838e+00 -1.610e+00 0.6 +++\n",
      "+++ 2.371e+02 2.367e+02 -1.838e+00 -1.572e+00 0.806 +++\n",
      "+++ 2.371e+02 2.366e+02 -1.838e+00 -1.554e+00 0.92 +++\n",
      "+++ 2.371e+02 2.366e+02 -1.838e+00 -1.544e+00 0.979 +++\n",
      "+++ 2.371e+02 2.366e+02 -1.838e+00 -1.539e+00 1.01 +++\n",
      "\t### errors for param 3 ###\n",
      "+++ 2.371e+02 2.369e+02 -2.136e+00 -2.019e+00 0.267 +++\n",
      "+++ 2.371e+02 2.368e+02 -2.136e+00 -1.961e+00 0.589 +++\n",
      "+++ 2.371e+02 2.367e+02 -2.136e+00 -1.931e+00 0.793 +++\n",
      "+++ 2.371e+02 2.366e+02 -2.136e+00 -1.917e+00 0.905 +++\n",
      "+++ 2.371e+02 2.366e+02 -2.136e+00 -1.909e+00 0.964 +++\n",
      "+++ 2.371e+02 2.366e+02 -2.136e+00 -1.906e+00 0.994 +++\n",
      "\t### errors for param 4 ###\n",
      "+++ 2.371e+02 2.370e+02 -2.695e+00 -2.578e+00 0.256 +++\n",
      "+++ 2.371e+02 2.368e+02 -2.695e+00 -2.519e+00 0.577 +++\n",
      "+++ 2.371e+02 2.367e+02 -2.695e+00 -2.490e+00 0.787 +++\n",
      "+++ 2.371e+02 2.366e+02 -2.695e+00 -2.475e+00 0.904 +++\n",
      "+++ 2.371e+02 2.366e+02 -2.695e+00 -2.468e+00 0.965 +++\n",
      "+++ 2.371e+02 2.366e+02 -2.695e+00 -2.464e+00 0.997 +++\n",
      "\t### errors for param 5 ###\n",
      "+++ 2.371e+02 2.369e+02 -3.646e+00 -3.376e+00 0.301 +++\n",
      "+++ 2.371e+02 2.367e+02 -3.646e+00 -3.241e+00 0.783 +++\n",
      "+++ 2.371e+02 2.365e+02 -3.646e+00 -3.173e+00 1.15 +++\n",
      "+++ 2.371e+02 2.366e+02 -3.646e+00 -3.207e+00 0.953 +++\n",
      "+++ 2.371e+02 2.366e+02 -3.646e+00 -3.190e+00 1.05 +++\n",
      "+++ 2.371e+02 2.366e+02 -3.646e+00 -3.199e+00   1 +++\n",
      "\t### errors for param 6 ###\n",
      "+++ 2.371e+02 2.371e+02 -8.000e+00 -5.000e+00 0.0545 +++\n",
      "+++ 2.371e+02 2.353e+02 -8.000e+00 -3.500e+00 3.58 +++\n",
      "+++ 2.371e+02 2.369e+02 -8.000e+00 -4.250e+00 0.39 +++\n",
      "+++ 2.371e+02 2.365e+02 -8.000e+00 -3.875e+00 1.18 +++\n",
      "+++ 2.371e+02 2.367e+02 -8.000e+00 -4.062e+00 0.674 +++\n",
      "+++ 2.371e+02 2.366e+02 -8.000e+00 -3.969e+00 0.891 +++\n",
      "+++ 2.371e+02 2.366e+02 -8.000e+00 -3.922e+00 1.03 +++\n",
      "+++ 2.371e+02 2.366e+02 -8.000e+00 -3.945e+00 0.956 +++\n",
      "+++ 2.371e+02 2.366e+02 -8.000e+00 -3.934e+00 0.99 +++\n",
      "\t### errors for param 7 ###\n",
      "+++ 2.371e+02 2.367e+02 -4.244e+00 -3.749e+00 0.707 +++\n",
      "+++ 2.371e+02 2.359e+02 -4.244e+00 -3.502e+00 2.45 +++\n",
      "+++ 2.371e+02 2.364e+02 -4.244e+00 -3.625e+00 1.37 +++\n",
      "+++ 2.371e+02 2.366e+02 -4.244e+00 -3.687e+00 0.998 +++\n",
      "********************\n",
      "-0.0130485 -0.585388 -1.83753 -2.1361 -2.69519 -3.64613 -8 -4.24367\n",
      "0.275479 0.239709 0.298186 0.230343 0.23123 0.447579 2 0.556379\n",
      "********************\n"
     ]
    }
   ],
   "source": [
    "p2, p2e = clag.errors(P2, p2, p2e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 3 artists>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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0Y2mGHxyuy7yk9c6QIKnpJRIJRh8epfub3SQ/n4QngYuVDy8CT0Ly80m6v9nN8aPH2bp1\npTsvrUz+iTxv+tCbePWbX82Ld72YF7zuBbx414t59ZtfzZs+9CbyT+SXP4jUgqKq3SBJNZVIJBh5\naISZmRkG7hvgkc8FVSDTW9Ls69hH/yejqQJZLpc5/NuHLxWWujV4f555vn/m+8wPz3P4C4f5mQd+\nxnoRWncMCZJaSiqVYvAjg0yenaTjcAdH7jpC+w3RVI+1sJTizpAgqWXkn8iTPxFc2p/74Rw7XrGD\nA391gE3XbgIg9/ocuV25mo23msJSIw+N1Gx8qdEMCZJaRm5XbUPA1TxfWCrsCkKYrVD4alBYyicr\ntF64cFGSQlhYSjIkSFIoC0tJhgRJCmVhKck1CZJaSD6fJ5+vLFycm+P06dNs376dTZsqCxdzOXK5\n2qxZsLCUZEiQ1EIWh4DJyUk6OjrI5/O0t9f+EcjOmzo5ceZEdbccLCyldcbbDZIUwsJSkiFBkkJZ\nWEoyJEjSkiwspbgzJEhqKTMzM/T19dHT0wNAT08PfX19zMzM1HysRheWkhrNhYuSWkK5XCabzVIo\nFCiVLm1yVCwWKRaLHD16lEwmw9DQUE3rJzSqsJTUDAwJkppeuVxm7969TE1NLdmmVCpRKpXo6upi\ndLS2hZaerxnRBa/5qdew8ZmNbH/Zdp6+9ml+a+y3yH2vfttFS/VkSJDU9LLZ7FUDwmLFYpFsNsvI\nSO0KLdWzZoTUTFyTIKmpTU9PUygUqupTKBQiWaMgxY0hQVJTO3To0GVrEFaiVCoxMGChJWmtDAmS\nmtr4+OoKJq22n6RLogoJKeBBYAr4J+D/AvcCbmouqSrz86srmLTafpIuiWrh4muBDcBdBAFhF/An\nwIuAeyIaU9I61Na2ut8tVttP0iVRhYTPVV4LZoD7gPdiSJBUhc7OTk6cOFF1v927a1doqZ7VJ6Vm\nsqGOY/034OeAsP9z24GJiYmJSKq5SWpdMzMz7Nmzp6rFi8lkkrGxsUg2OVqoPunPKzWLhXMS6AAm\na3nsei1cTAO/CXysTuNJWidSqRSZTKaqPplM7Qst1XM76MvGvLuPXbftIrM3w67bdtF3d7RjSotV\neyXhXqB/mTZv4PIkcyPwN8AIwRqFMF5JkLSkcrlMV1cXxWJx2bbpdJrjx2tXR2Gp7aAXJJPJmm8H\nXS6XuT17O1PfneLZ9mdh26IPz8B1k9fxmpe+hpGhkZruLKnWFOWVhGpDwisqr6s5DTxb+f5GgnAw\nBrzrKn3agYnbbruNzZs3X/aB9/okwcr/sR4eHq5pQFhuO+gF6XS6JttBl8tl9t6xl6lbp+Bqf41K\n5cnRh2u7BbWa2+L1MQvOnz/Po48+Ck0QEqrxSoKAMA68k0u108J4JUHSiszMzDAwMMAjjzxCsVgk\nnU6zb98++vtrX2jp9ttv59ixYytu393dvebtoG//pds59upjVw8IC2ah+5vdjDxUuy2o1XpacU3C\nK4FjBFcV7gESQLLykqRVS6VSDA4OcuTIEQCOHDnC4OBgzQNCI7aDnp6epnCusLKAALAVCufcglrR\niSok/CzBYsWfAc4AT1Ve34poPEmqqUZsB33ovkOUXlflmDtLDNznFtSKRlQh4U8rx95Y+XrNoj9L\nUtNrxHbQ44+PX75IcSW2wfjX3IJa0bBUtKSWceWmRjt27ODAgQORbGrUiO2g559bRd8NMH/BLagV\nDUOCpJZRz6edGrEddNvGVfS9CG3XuAW1omEVSEkK0dnZuap+a9kOuvOmzmAVVzXOwO6ba7cFtbSY\nIUGSQvT395NMVvdAVjKZ5ODBg6sf855+kierHPNUkoPvW/2Y0tUYEiQpRCO2g06lUmS2ZGB2hR1m\nIbOl9ltQSwsMCZK0hKGhIdLp9IraptNphoeH1z7mA0OkH0svHxQqOy4OP7j2MaWlGBIkaQmJRILR\n0VG6u7uXvPWQTCbp7u6uWb2IRCLB6MOj7Dy5k+s+ex08yaX9ai8CT8J1n72OnSd3cvxo7WpUSGF8\nukGSriKRSDAyMlLX7aATiQQnR04GY943wPgXx5m/ME/bNW103txJ/1/UfszFZmZmGPjAAOOPjzP/\n3DxtG9vovKmT/nuiHVfNJ8raDdWwdoOklrCwT/56/HlVLpfJ3pmlcK4Q7Px4RfXJ5MkkmS0Zhh6o\nXcVLrV2UtRu8kiBJy6jnJk6Ncln1yTeENNgGpW0lSrMluu7osvpkTHglQZJk9ckW1opVICVJLcLq\nk1qKIUGSYs7qk1qKaxIkqQlduQ7i9OnTbN++PZJ1EOOPj8Obquy0Dca/aPXJ9c6QIElNaHEIWLjn\nnM/nI1m3ZfVJLcXbDZLUpGZmZujr66OnpweAnp4e+vr6ar4WwOqTWopXEiSpyZTLZbLZLIVCgVLp\n0lqBYrFIsVjk6NGjZDIZhoZqs19B502dnDhz4vJ9EZZj9clY8EqCJDWRcrnM3r17OXbs2GUBYbFS\nqcSxY8fo6uqiXC6veUyrT2ophgRJaiLZbJapqakVtS0Wi2Sz2TWPafVJLcWQIElNYnp6mkKhUFWf\nQqE2+xVYfVJhDAmS1CQOHTq05C2GpZRKJQYG1r5fwUL1ye5vdpP8fDK0+mTy80m6v9lt9ckYceGi\nJDWJ8fHV7Tuw2n5XSiQSjDw0snT1yU9aBTJuDAmS1CTm51e378Bq+y0llUox+JHBmh5TrcnbDZLU\nJNraVrfvwGr7ScsxJEhSk+js7FxVv9273a9A0TAkSFKT6O/vJ5mscr+CZJKDB92vQNEwJEhSk0il\nUmQymar6ZDLuV6DoGBIkqYkMDQ2RTqdX1DadTjM87H4Fik5UIeGzwGngB8BTwJ8DN0Q0liStG4lE\ngtHRUbq7u5e89ZBMJunu7ub4cfcrULSiCgl/DfwysAN4B5AG/jKisSRpXUkkEoyMjDA2NkZvb+/z\nVxbS6TS9vb2MjY0xMjJiQFDkoton4f5F3z8J/B7waWAj8FxEY0rSupJKpRgcHGRycpKOjg6OHDlC\ne3t7o6elGKnHZkpbgF8DRjAgSNKK5PN58vk8AHNzc+zYsYMDBw6wadMmAHK5HLlcrpFTVAxEGRJ+\nD7gbeCHwZeDNEY4lSeuKIUDNoJo1CfcCF5Z5Lb4O9vvALcDPAc8CnwE2rHnGkiSpLqr5R/sVldfV\nnCYIBFd6JcHahDcCx0M+bwcmbrvtNjZv3nzZB6ZpSZICi29DLTh//jyPPvooQAcwWcvx6vWb/asI\nAsRPA4+GfN4OTExMTLgoR5KkKiwsbCWCkBDFmoTdldffAt8BXgMMAN8AxiIYT5IkRSCKfRL+CfhX\nwF8BBeBB4HGCqwg/jGA8SZIUgSiuJJwA/mUEx5UkSXVk7QZJkhTKkCBJkkLVY8dFSVKLuHKnx9On\nT7N9+3Z3eowpQ4Ik6XmLQ8DCo3X5fN7H02PK2w2SJCmUIUGSJIUyJEiSpFCuSZAkNVT+iTz5E5XF\nkj+c4/Qzp9n+su1surayWPL1OXK7XCzZCIYESVJD5XZdCgGTZyfpONxB/h152m9wsWSjebtBktRw\nMzMz9N3dR8/be+BT0PP2Hvru7mNmZqbRU4s1ryRIkhqmXC6TvTNL4VyB0utK8PPB+0WKFM8UOfpr\nR8lsyTD0wBCJRKKxk40hQ4IkqSHK5TJ779jL1K1T8IaQBtugtK1EabZE1x1djD48alCoM283SJIa\nIntnNggIW5dpuBWKtxbJ3pmty7x0iSFBknSZmZkZ+vr66OnpAaCnp4e+vtquD5ienqZwrrB8QFiw\nFQrnCq5RqDNDgiQJCC7/33777ezZs4ePf/zjFItFAIrFIh//+MfZs2cPt99+O+Vyec1jHbrvULAG\noQqlnSUG7htY89haOdckSJKC9QF79zI1NbVkm1KpRKlUoquri9HRta0PGH98HN5UZadtMP7F8VWP\nqep5JUGSRDabvWpAWKxYLJLNrm19wPxz89V32gDzF1bRT6tmSJCkmJuenqZQKFTVp1BY2/qAto1t\n1Xe6CG3XrKKfVs2QIEkxd+jQIUqlKtcHlEoMDKx+fUDnTZ1wpspOZ2D3zbtXPaaqZ0iQpJgbH1/d\nff7V9gPov6ef5MlkVX2Sp5IcfN/BVY+p6hkSJCnm5udXd59/tf0AUqkUmS0ZmF1hh1nIbMmQSqVW\nPaaq59MNkhRzbW2ru8+/2n4Lhh4YouuOLoq3Fq++X8IspB9LM3x0eE3jXSmfz5PPV6pPzs1x+vRp\ntm/fzqZNleqTuRy5XLyrTxoSJCnmOjs7OXHiRNX9du9e2/qARCLB6MOjQe2GrxYo7SzBNmADcBE4\nE9xiyGzJMHx0mK1bV7rz0sosDgGTk5N0dHSQz+dpb7f65AJvN0hSzPX395NMVrk+IJnk4MG1rw9I\nJBKMPDTC2CfH6N3US/pzafgUpD+XpndTL2OfHGPkoZGaBwStjFcSJCnmUqkUmUymqiccMpnarg9I\npVIMfmSQybOTdBzu4MhdR2i/wd/oG80rCZIkhoaGSKfTK2qbTqcZHq7t+gA1J68kSJKC9QGjo2Sz\nWQqFQuhVhWQySSaTYXi4tusD8k/kyZ+oLCD84Rw7XrGDA391gE3XVhYQvj5Hble8FxA2iiFBkgRU\n1geMjDAzM8PAwACPPPIIxWKRdDrNvn376O/vj+QRxNwuQ0CzijokXAd8CbgJuAV4POLxJElrlEql\nGBwcfH7F/5EjR1zxH1NRr0n4feBbEY8hSZIiEGVIeDNBIdD3RTiGJEmKSFS3GxLAYeCtwA8iGkOS\nJEUoiisJG4A/Bf4YmIzg+JIkqQ6quZJwL9C/TJtOoAt4MfD+Kz7bsNwA+/fvZ/PmzZe9597ZkiQF\nFtebWHD+/PnIxqsmJHwY+NQybU4D/wXYAzx7xWdfBj4B9C7V+f7773cFrSRJSwj7xXnhKZQoVBMS\nvl15Lee3gN9Z9OdXAp8Deggeh5QkSS0gijUJTwInF72+UXm/CDwVwXiSJK3KzMwMfX199PT0ANDT\n00NfXx8zMzONnViTqNeOixfrNI4kaQ0W3/Oem5tjx44dHDhwgE2bKlskr5N1YuVyOXQL6mKxSLFY\n5OjRo2QyGYaGhkgkEg2caWPVIyTMABvrMI4kaY3WSwi4mnK5zN69e5mamlqyTalUolQq0dXVxejo\naGyDglUgJUmxks1mrxoQFisWi2Sz2Yhn1LwMCZKk2JienqZQKFTVp1AoxHaNgiFBkhQbhw4dCi2D\nfTWlUomBgYGIZtTcDAmSpNgYHx+va79WZ0iQJMXG/Px8Xfu1OkOCJCk22tra6tqv1RkSJEmx0dnZ\nuap+u3fvrvFMWoMhQZIUG/39/SSTyar6JJNJDh48GNGMmpshQZIUG6lUikwmU1WfTCZDKpWKZkJN\nzpAgSYqVoaEh0un0itqm02mGh4cjnlHzMiRIkmIlkUgwOjpKd3f3krcekskk3d3dHD9+nK1bt9Z5\nhs3DkCBJip1EIsHIyAhjY2P09vayLbUNgG2pbfT29jI2NsbIyEisAwIYEiRJMZZKpRgcHOT9H3s/\nAO//2PsZHByM7RqEKxkSJElSKEOCJEkKZUiQJEmhDAmSJCmUIUGSJIUyJEiSpFCGBEmSFMqQIEmS\nQhkSJElSKEOCJEkKZUiQJEmhDAmSJCnUtY2egCRJjZDP58nn8wDMPjMLr4AP/+6HGf6jYQByuRy5\nXK6RU2w4Q4IkKZYWh4DJs5N0HO7go3d9lPYb2hs8s+YR1e2GGeDCFa/fjWgsSZIUgaiuJFwEDgJ/\nsui970c0liRJikCUtxv+EZiN8PiSJClCUT7d8J+Ap4GvAL8NtEU4liRJqrGoriT8ITABfAf4KeC/\nAz8O/NuIxpMkSTVWzZWEe/nRxYhXvhaWhN4PPAqcAB4Efh14N/DyWkxakiRFr5orCR8GPrVMm9NL\nvP+lytefAMaX6rx//342b9582Xs+pypJUmDx3g4Lzp8/H9l41YSEb1deq/EvKl/PXq3R/fffT3u7\nz6dKkhQm7BfnyclJOjo6IhkvijUJtwJ7gBHgGaAT+APgfwFnIhhPkiRFIIqQ8CzQA/QD1xHcgjgM\n/H4EY0mSpIhEERK+QnAlQZIktTCrQEqSpFCGBEmSFMqQIEmSQhkSJElSKEOCJEkKZUiQJEmhDAmS\nJCmUIUGy/M51AAAE9ElEQVSSJIUyJEiSpFCGBEmSFMqQIEmSQhkSJElSKEOCJEkKZUiQJEmhDAmS\nJCmUIUGSJIUyJEiSpFCGBEmSFMqQIEmSQhkSJElSKEOCJEkKZUiQJEmhDAmSJCmUIUGSJIUyJEiS\npFCGBEmSFMqQIEmSQhkSJElSqChDwi8AXwL+CfgH4C8iHEtasXw+3+gpKCY819TqogoJ7wD+HHgQ\nuAnYC3wyorGkqviDW/XiuaZWd21Ex/xD4H3Axxe9/40IxpIkSRGJ4kpCO3AjcBH4CvAU8DDwkxGM\n1XD1/k2hluOt5VjV9q2m/UraLtdmPf4G57lW+/aea+Hieq7xRHRjteq5FkVIeE3l673AAPCLwHeA\nY8DLIxivoeL6P5M/uOvPc6327T3XwsX1XDMk/KhqbjfcC/Qv06aTS8HjvwGfrnzfC5wBfhk4vFTn\nU6dOVTGd5nD+/HkmJydbcry1HKvavtW0X0nb5dpc7fN6/zerFc+12rf3XAsXx3Pt1D+cgjk49fgp\nOFv7saI816L8t3NDFW1fUXldzWmCRYpfBN4IHF/02WPAF4CDIf1uAMaBV1YxH0mSFPgWwS/qK4w4\nK1PNlYRvV17LmQCeBTJcCgltQIogRIQ5S/CXu6GK+UiSpMBZahwQovRB4EngZ4HXAg8QTP5ljZyU\nJElqvGuBDwAl4Bngc8DOhs5IkiRJkiRJkiRJkiTpR70E+D8EOzieAH6zsdPROvYqgo2//g74GvCv\nGzobrXefBs4B/7PRE9G69YtAAfh74N0NnktkrgE2Vb7/MWAK+GeNm47WsSRBUTIIzrEnCc45KQo/\nTfBD3JCgKFwLfJ1ge4EXEwSFLdUcIMpS0bV0AZirfP9CYH7Rn6VaKgGPV77/B4Lf8qr6n0qqwt8A\n/9joSWjd2k1wVfQswXn2MPBz1RygVUICBHssfA34JkGVye81djqKgTcQ7Er6rUZPRJJW4UYu//l1\nhip3Nm6lkPAMcDPw48DdwE80djpa514B/BlwV6MnIkmrdHGtB4gqJOwDHiJIMBeAt4a0+Q1gGvgB\n8GWCWg8L/h3BIsVJgi2dF5slWFh2S01nrFYVxbl2HfCXwO8S1ByRILqfa2v+Qa51a63n3FNcfuXg\nVTTJldGfJygT/TaCv9hbrvj8VwjqO/QRbNv8QYLbB69a4nhbgZdWvn8pwT3j19Z2ympRtT7XNgB5\n4L9GMVm1tFqfawu6ceGiwq31nLuWYLHijQRPCf498PLIZ12lsL/Yl4A/uuK9kwS/uYVpJ0jgX628\nems5Qa0btTjX3gg8R/Db3lcqr5+s4Ry1PtTiXINgy/pZ4PsET9J01GqCWndWe879EsETDt8A7oxs\ndmtw5V/sBQRPJ1x52eR+gtsI0mp5rqlePNdUbw055xqxcPF6YCNQvuL9WYJn1KVa8VxTvXiuqd7q\ncs610tMNkiSpjhoREp4muOebuOL9BMGGD1KteK6pXjzXVG91OecaERL+HzDBj+769LPA8fpPR+uY\n55rqxXNN9dbS59yLCPYxuIVgscX+yvcLj2X0EDy20QvsJHhs47ss/6iQdCXPNdWL55rqbd2ec90E\nf6ELBJdDFr4fXNTmvQQbQMwB41y+AYS0Ut14rqk+uvFcU3114zknSZIkSZIkSZIkSZIkSZIkSZIk\nSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZLUAv4/ZzQeXoShUskAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f676b9aaa90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "xscale('log'); ylim(-6,2)\n",
    "errorbar(fqd, p1, yerr=p1e, fmt='o', ms=10, color=\"green\")\n",
    "errorbar(fqd, p2, yerr=p2e, fmt='o', ms=10, color=\"black\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   1 5.670e+03 9.675e+00 inf -- 2.919e+02 -- -0.156222 -0.68176 -1.81406 -2.12926 -2.71269 -3.36881 -6.08072 -6.42184 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1\n",
      "   3 1.047e+03 1.151e+01 2.879e+00 -- 2.948e+02 -- -0.118762 -0.639838 -1.76688 -2.08895 -2.66889 -3.26353 -5.78072 -6.12184 0.0424515 0.105123 0.138683 0.0948799 0.140121 0.0393153 2.81332 0.248074\n",
      "   5 4.807e+02 1.352e+01 2.643e+00 -- 2.974e+02 -- -0.0866187 -0.605762 -1.72887 -2.05583 -2.63238 -3.19092 -6.08072 -5.82184 0.000648562 0.108523 0.164491 0.0915061 0.170413 0.00913963 2.85855 1.07978\n",
      "   7 1.906e+02 1.570e+01 2.338e+00 -- 2.998e+02 -- -0.0590998 -0.577513 -1.69772 -2.02818 -2.60158 -3.1372 -6.38072 -5.52184 -0.0305296 0.110846 0.182461 0.0892265 0.194212 -0.00858619 2.71513 -3.11054\n",
      "   9 5.891e+01 1.810e+01 2.317e+00 -- 3.021e+02 -- -0.0354896 -0.55376 -1.67186 -2.0048 -2.57534 -3.09575 -6.30939 -5.82184 -0.0543126 0.112411 0.195339 0.0877287 0.21341 -0.0199574 1.23313 2.11694\n",
      "  11 5.912e+01 2.072e+01 2.113e+00 -- 3.042e+02 -- -0.0151439 -0.533554 -1.65012 -1.98485 -2.55283 -3.06281 -6.00939 -5.52184 -0.0727701 0.113507 0.204816 0.0866854 0.229407 -0.0274598 -2.84324 2.21189\n",
      "  13 5.318e+02 2.358e+01 2.081e+00 -- 3.063e+02 -- 0.00246155 -0.516217 -1.63169 -1.96771 -2.5334 -3.03613 -6.30939 -5.22184 -0.0873173 0.114241 0.211893 0.0859833 0.242956 -0.0325361 -0.803414 1.81103\n",
      "  15 6.000e+01 2.669e+01 1.754e+00 -- 3.080e+02 -- 0.0177641 -0.501232 -1.61594 -1.95288 -2.51654 -3.01421 -6.60939 -4.92184 -0.0989192 0.114745 0.21724 0.085486 0.254699 -0.0358684 -2.05745 -0.439047\n",
      "  17 2.760e+02 3.007e+01 2.029e+00 -- 3.101e+02 -- 0.0311238 -0.488205 -1.60242 -1.93999 -2.50187 -2.99581 -6.90939 -4.99492 -0.108184 0.115134 0.221508 0.0852356 0.26512 -0.0377338 1.31525 1.49865\n",
      "  19 3.455e+02 3.375e+01 1.932e+00 -- 3.120e+02 -- 0.0428159 -0.476826 -1.59071 -1.92874 -2.48903 -2.98053 -6.60939 -4.69492 -0.115759 0.115347 0.224648 0.0849875 0.274357 -0.0388865 2.71661 0.824234\n",
      "  21 5.627e+02 3.773e+01 2.106e+00 -- 3.141e+02 -- 0.0530961 -0.466839 -1.58055 -1.91888 -2.47782 -2.96759 -6.90939 -4.39492 -0.121894 0.115561 0.227171 0.0847372 0.282893 -0.0391746 3.09606 1.24474\n",
      "  23 1.412e+03 4.204e+01 2.098e+00 -- 3.162e+02 -- 0.0621536 -0.458045 -1.57168 -1.9102 -2.468 -2.95676 -7.20939 -4.18138 -0.126953 0.115732 0.229039 0.084359 0.29081 -0.0390341 -1.48027 1.23885\n",
      "  25 4.162e+04 4.667e+01 1.855e+00 -- 3.181e+02 -- 0.0701599 -0.450276 -1.56393 -1.90253 -2.45941 -2.94767 -7.50939 -4.06761 -0.131108 0.115932 0.230463 0.0838354 0.298357 -0.0385057 0.151626 1.24726\n",
      "  27 1.368e+03 5.163e+01 1.694e+00 -- 3.197e+02 -- 0.0772509 -0.443397 -1.55713 -1.89576 -2.45187 -2.94001 -7.20939 -3.99039 -0.134522 0.11614 0.231552 0.0832518 0.30556 -0.0376963 2.85355 1.25729\n",
      "  29 3.278e+03 5.692e+01 1.564e+00 -- 3.213e+02 -- 0.0835427 -0.437294 -1.55116 -1.88977 -2.44524 -2.93357 -7.50939 -3.9332 -0.137326 0.116351 0.232387 0.0826471 0.312468 -0.0366776 2.17754 1.26747\n",
      "  31 7.767e+02 6.255e+01 1.446e+00 -- 3.228e+02 -- 0.0891349 -0.43187 -1.54591 -1.88447 -2.4394 -2.92816 -7.20939 -3.88882 -0.139623 0.116565 0.233032 0.0820438 0.319124 -0.0354977 -1.72243 1.27737\n",
      "  33 6.146e+04 6.851e+01 1.343e+00 -- 3.241e+02 -- 0.0941131 -0.427041 -1.5413 -1.87977 -2.43426 -2.92364 -7.50939 -3.85335 -0.141498 0.116784 0.233532 0.0814561 0.325567 -0.0341934 0.110556 1.28681\n",
      "  35 5.141e+02 7.481e+01 1.246e+00 -- 3.253e+02 -- 0.0985508 -0.422736 -1.53723 -1.87561 -2.42973 -2.91988 -7.20939 -3.82441 -0.143017 0.117008 0.233923 0.0808916 0.331826 -0.0327907 0.968192 1.29571\n",
      "  37 2.561e+03 8.143e+01 1.157e+00 -- 3.265e+02 -- 0.102512 -0.418892 -1.53365 -1.87193 -2.42573 -2.9168 -6.90939 -3.80046 -0.144236 0.11724 0.234234 0.0803546 0.337926 -0.0313104 0.474092 1.30403\n",
      "  39 4.175e+02 8.835e+01 1.071e+00 -- 3.276e+02 -- 0.106051 -0.415457 -1.53049 -1.86867 -2.4222 -2.91429 -6.60939 -3.78043 -0.145202 0.117482 0.234484 0.0798467 0.343885 -0.0297682 2.50013 1.31174\n",
      "  41 2.484e+02 9.557e+01 9.861e-01 -- 3.286e+02 -- 0.109218 -0.412381 -1.52772 -1.86578 -2.41908 -2.91229 -6.30939 -3.76351 -0.14595 0.117736 0.234692 0.079367 0.349713 -0.0281813 -1.35794 1.31885\n",
      "  43 1.664e+02 1.030e+02 9.286e-01 -- 3.295e+02 -- 0.112053 -0.409626 -1.52527 -1.86322 -2.41632 -2.91073 -6.60939 -3.74914 -0.146514 0.118004 0.234875 0.0789157 0.355418 -0.0265569 0.955065 1.32532\n",
      "  45 3.715e+01 1.108e+02 8.360e-01 -- 3.303e+02 -- 0.114595 -0.407155 -1.52313 -1.86096 -2.41388 -2.90956 -6.30939 -3.73686 -0.146919 0.118288 0.235035 0.0784863 0.361005 -0.024906 -2.00648 1.33124\n",
      "  47 1.757e+03 1.187e+02 7.899e-01 -- 3.311e+02 -- 0.116875 -0.404936 -1.52125 -1.85897 -2.41171 -2.90871 -6.60939 -3.7263 -0.147187 0.118587 0.235191 0.0780786 0.366467 -0.0232463 -0.606714 1.3366\n",
      "  49 2.419e+03 1.268e+02 7.198e-01 -- 3.318e+02 -- 0.118922 -0.402941 -1.5196 -1.85722 -2.40977 -2.90815 -6.90939 -3.71719 -0.147336 0.118903 0.235343 0.0776863 0.371808 -0.0215787 -0.828333 1.34144\n",
      "  50 3.758e+03 1.322e+04 4.674e+00 -- 3.272e+02 -- 0.137314 -0.384994 -1.50519 -1.84182 -2.39252 -2.9049 -8 -3.63812 -0.147803 0.122227 0.236936 0.0738852 0.423919 -0.00499483 -1.20255 1.3852\n",
      "  52 2.909e+04 6.385e+02 1.073e+01 -- 3.379e+02 -- 0.136943 -0.384318 -1.50651 -1.84446 -2.39241 -2.90988 -8 -3.64036 -0.1468 0.121814 0.239523 0.0607648 0.447789 0.00582078 -0.683535 1.38625\n",
      "  53 8.944e+04 2.504e+02 4.851e-01 -- 3.384e+02 -- 0.137108 -0.382857 -1.511 -1.85395 -2.38877 -2.93977 -8 -3.6534 -0.132666 0.131148 0.26174 0.0372861 0.519783 0.0387377 0.222008 1.38794\n",
      "  55 1.907e+04 2.097e+02 2.143e-01 -- 3.386e+02 -- 0.137241 -0.382905 -1.51059 -1.85324 -2.38834 -2.93581 -7.7 -3.65133 -0.133058 0.131502 0.26506 0.0380769 0.517294 0.0298916 0.427458 1.38872\n",
      "  57 2.701e+03 1.743e+02 1.707e-01 -- 3.388e+02 -- 0.137362 -0.382947 -1.51023 -1.85264 -2.38795 -2.93261 -7.4 -3.64964 -0.133373 0.131817 0.267849 0.0388293 0.515228 0.0226558 -1.3799 1.38928\n",
      "  58 1.901e+04 6.807e+03 9.857e+00 -- 3.289e+02 -- 0.138463 -0.383316 -1.50699 -1.84755 -2.38449 -2.90718 -8 -3.63586 -0.135895 0.13461 0.291172 0.0458143 0.498444 -0.0363648 -0.545357 1.39317\n",
      "  60 5.237e+04 4.383e+02 8.985e+00 -- 3.379e+02 -- 0.138201 -0.382988 -1.50809 -1.84815 -2.38423 -2.91079 -8 -3.63639 -0.138737 0.135181 0.288716 0.034039 0.510877 -0.0254366 -0.396913 1.39809\n",
      "  61 8.766e+03 4.097e+02 8.172e-01 -- 3.387e+02 -- 0.137968 -0.382536 -1.51047 -1.85072 -2.38194 -2.93875 -8 -3.64468 -0.141543 0.135484 0.281935 0.0183923 0.556885 0.045315 1.79478 1.42693\n",
      "  63 1.814e+04 3.493e+02 1.618e-01 -- 3.389e+02 -- 0.13803 -0.382587 -1.51013 -1.85062 -2.38179 -2.93566 -7.7 -3.64395 -0.140901 0.135271 0.284223 0.0205977 0.55377 0.0372067 -0.67593 1.42469\n",
      "  64 4.667e+03 9.194e+03 7.138e+00 -- 3.317e+02 -- 0.138594 -0.383049 -1.50705 -1.84979 -2.38045 -2.91127 -8 -3.63796 -0.135166 0.133564 0.302461 0.0405415 0.526549 -0.0285933 1.72877 1.40601\n",
      "  66 2.229e+03 8.468e+02 6.334e+00 -- 3.381e+02 -- 0.138375 -0.382821 -1.50788 -1.8493 -2.38027 -2.91526 -7.7 -3.63713 -0.138411 0.134331 0.300768 0.0296213 0.534063 -0.0172368 -2.02693 1.41805\n",
      "  67 6.383e+03 4.433e+02 6.946e-01 -- 3.388e+02 -- 0.138019 -0.382446 -1.51012 -1.84832 -2.37854 -2.94579 -8 -3.63552 -0.145232 0.136059 0.290585 0.00900103 0.566205 0.0595408 -1.58605 1.49345\n",
      "  69 2.791e+04 3.818e+02 1.832e-01 -- 3.389e+02 -- 0.13807 -0.382495 -1.50981 -1.84878 -2.37843 -2.94234 -8 -3.63605 -0.14425 0.135725 0.292234 0.0124456 0.563364 0.0504802 -0.811369 1.48719\n",
      "  71 7.592e+03 3.289e+02 1.419e-01 -- 3.391e+02 -- 0.138118 -0.382539 -1.50952 -1.84915 -2.37833 -2.93967 -8 -3.63644 -0.143394 0.135448 0.293502 0.0154512 0.560893 0.0432337 1.73025 1.48211\n",
      "  72 9.792e+00 1.238e+04 4.549e+00 -- 3.345e+02 -- 0.138556 -0.382946 -1.50702 -1.85213 -2.37736 -2.91947 -5 -3.63926 -0.135949 0.133151 0.302987 0.0415893 0.539598 -0.0143255 -2.01979 1.44199\n",
      "  73 1.790e+03 2.036e+04 5.362e+00 -- 3.292e+02 -- 0.13686 -0.381484 -1.51285 -1.83573 -2.37645 -2.96346 -8 -3.61694 -0.169822 0.139603 0.306242 -0.0616507 0.578831 0.105014 -2.94898 1.60824\n",
      "  75 2.000e+04 3.767e+03 7.143e+00 -- 3.363e+02 -- 0.136937 -0.381554 -1.51207 -1.84035 -2.37648 -2.95217 -8 -3.62182 -0.164447 0.137434 0.31164 -0.0445826 0.577957 0.0688955 -1.04621 1.58574\n",
      "  77 1.670e+04 2.864e+03 1.308e+00 -- 3.376e+02 -- 0.137027 -0.381619 -1.51152 -1.84295 -2.37643 -2.94676 -8 -3.62459 -0.16153 0.135849 0.316596 -0.035261 0.576777 0.0522889 -1.10409 1.57318\n",
      "  79 3.940e+03 2.269e+03 6.679e-01 -- 3.383e+02 -- 0.137114 -0.381682 -1.51105 -1.8448 -2.37637 -2.94335 -8 -3.62651 -0.159205 0.134652 0.320529 -0.028154 0.575644 0.041706 1.23968 1.56483\n",
      "  81 3.136e+03 1.843e+03 4.148e-01 -- 3.387e+02 -- 0.137197 -0.381742 -1.51062 -1.84618 -2.3763 -2.9411 -7.7 -3.62789 -0.157267 0.133753 0.323527 -0.0224013 0.574634 0.0345912 2.94827 1.55921\n",
      "  83 7.332e+03 1.524e+03 2.814e-01 -- 3.390e+02 -- 0.137277 -0.381798 -1.51025 -1.84723 -2.37623 -2.9396 -8 -3.6289 -0.155627 0.133083 0.325719 -0.0176294 0.573764 0.0297776 1.97421 1.55551\n",
      "  84 4.352e+01 2.419e+05 8.521e+00 -- 3.305e+02 -- 0.13802 -0.382337 -1.50692 -1.85513 -2.37556 -2.92991 -5 -3.63632 -0.141645 0.128163 0.340891 0.0224931 0.566412 -0.00221606 2.81464 1.53266\n",
      "  86 2.646e+01 1.360e+05 5.846e+00 -- 3.363e+02 -- 0.137542 -0.382135 -1.50734 -1.85175 -2.3755 -2.93273 -4.7 -3.63458 -0.154265 0.130343 0.343497 0.00406723 0.567925 0.0074277 1.76444 1.5434\n",
      "  88 3.599e+00 1.247e+03 4.005e+00 -- 3.403e+02 -- 0.137281 -0.382038 -1.50761 -1.84969 -2.37546 -2.93454 -4.44346 -3.63355 -0.162752 0.1317 0.344853 -0.00669382 0.568721 0.0140179 2.19787 1.55056\n",
      "  90 1.187e+00 3.038e+03 3.904e-01 -- 3.407e+02 -- 0.13727 -0.382043 -1.50767 -1.84906 -2.37542 -2.93544 -4.35974 -3.63317 -0.162904 0.131742 0.343848 -0.00910299 0.569009 0.0171214 2.09178 1.55417\n",
      "  92 7.462e-01 5.052e+03 2.290e-01 -- 3.409e+02 -- 0.13728 -0.382056 -1.50771 -1.84873 -2.3754 -2.93603 -4.30688 -3.63296 -0.16231 0.131703 0.342609 -0.0100924 0.569167 0.0191537 2.00906 1.55662\n",
      "  94 5.215e-01 6.434e+03 1.735e-01 -- 3.411e+02 -- 0.137299 -0.382072 -1.50773 -1.84856 -2.37538 -2.93645 -4.26782 -3.63284 -0.161418 0.131643 0.341287 -0.0103928 0.569258 0.0205828 1.9431 1.5584\n",
      "  96 3.952e-01 7.618e+03 1.468e-01 -- 3.413e+02 -- 0.137323 -0.38209 -1.50774 -1.84848 -2.37536 -2.93676 -4.23675 -3.63278 -0.16042 0.131584 0.339946 -0.0103403 0.569314 0.0216563 1.89017 1.55979\n",
      "  98 3.181e-01 8.762e+03 1.305e-01 -- 3.414e+02 -- 0.137349 -0.382109 -1.50775 -1.84843 -2.37535 -2.93701 -4.21105 -3.63274 -0.159411 0.131539 0.338623 -0.0101102 0.56935 0.0225121 1.84758 1.56093\n",
      " 100 3.494e-01 9.944e+03 1.188e-01 -- 3.415e+02 -- 0.137376 -0.382128 -1.50775 -1.84841 -2.37533 -2.93721 -4.18933 -3.63272 -0.158443 0.131511 0.337339 -0.00979793 0.569375 0.0232282 1.81316 1.56189\n",
      " 102 3.644e-01 1.121e+04 1.096e-01 -- 3.416e+02 -- 0.137403 -0.382146 -1.50776 -1.8484 -2.37532 -2.93738 -4.17073 -3.63271 -0.157537 0.131501 0.336106 -0.0094556 0.569394 0.023849 1.78523 1.56274\n",
      " 104 3.648e-01 1.258e+04 1.021e-01 -- 3.417e+02 -- 0.13743 -0.382164 -1.50776 -1.84839 -2.37531 -2.93754 -4.15467 -3.6327 -0.156705 0.131508 0.33493 -0.00911106 0.569409 0.0244002 1.7624 1.56349\n",
      " 106 3.569e-01 1.408e+04 9.589e-02 -- 3.418e+02 -- 0.137456 -0.382182 -1.50777 -1.84838 -2.3753 -2.93768 -4.14072 -3.6327 -0.155947 0.13153 0.333816 -0.00877869 0.569422 0.0248968 1.74363 1.56416\n",
      " 108 3.443e-01 1.574e+04 9.062e-02 -- 3.419e+02 -- 0.137481 -0.382199 -1.50777 -1.84838 -2.3753 -2.9378 -4.12855 -3.63269 -0.155261 0.131565 0.332764 -0.00846538 0.569432 0.0253482 1.72809 1.56477\n",
      " 110 3.290e-01 1.757e+04 8.614e-02 -- 3.420e+02 -- 0.137504 -0.382216 -1.50778 -1.84837 -2.37529 -2.93791 -4.11789 -3.63269 -0.154643 0.131611 0.331773 -0.00817392 0.569442 0.0257602 1.71513 1.56532\n",
      " 112 3.124e-01 1.961e+04 8.229e-02 -- 3.421e+02 -- 0.137527 -0.382232 -1.50779 -1.84837 -2.37528 -2.93801 -4.10852 -3.63269 -0.154086 0.131666 0.330844 -0.00790497 0.569451 0.0261371 1.70424 1.56582\n",
      " 114 2.950e-01 2.186e+04 7.896e-02 -- 3.422e+02 -- 0.137548 -0.382247 -1.50779 -1.84836 -2.37527 -2.9381 -4.10026 -3.63269 -0.153586 0.131728 0.329975 -0.00765804 0.569459 0.0264824 1.69505 1.56628\n",
      " 116 2.774e-01 2.436e+04 7.607e-02 -- 3.422e+02 -- 0.137569 -0.382262 -1.5078 -1.84835 -2.37527 -2.93819 -4.09297 -3.63269 -0.153136 0.131795 0.329162 -0.00743212 0.569466 0.0267986 1.68724 1.5667\n",
      " 118 2.597e-01 2.714e+04 7.354e-02 -- 3.423e+02 -- 0.137588 -0.382276 -1.50781 -1.84835 -2.37526 -2.93826 -4.08651 -3.63268 -0.152733 0.131866 0.328406 -0.00722598 0.569472 0.0270881 1.68057 1.56707\n",
      " 120 2.423e-01 3.022e+04 7.133e-02 -- 3.424e+02 -- 0.137606 -0.38229 -1.50781 -1.84834 -2.37526 -2.93833 -4.08078 -3.63268 -0.15237 0.13194 0.327701 -0.0070383 0.569478 0.0273531 1.67485 1.56742\n",
      " 122 2.253e-01 3.365e+04 6.937e-02 -- 3.424e+02 -- 0.137623 -0.382303 -1.50782 -1.84833 -2.37525 -2.93839 -4.07569 -3.63268 -0.152044 0.132015 0.327048 -0.00686775 0.569484 0.0275954 1.66993 1.56773\n",
      " 124 2.087e-01 3.745e+04 6.764e-02 -- 3.425e+02 -- 0.137638 -0.382316 -1.50783 -1.84833 -2.37525 -2.93845 -4.07116 -3.63268 -0.151752 0.132092 0.326442 -0.00671305 0.569489 0.027817 1.66568 1.56802\n",
      " 126 1.926e-01 4.168e+04 6.611e-02 -- 3.426e+02 -- 0.137653 -0.382328 -1.50783 -1.84832 -2.37525 -2.9385 -4.06713 -3.63268 -0.15149 0.132168 0.325881 -0.00657297 0.569493 0.0280195 1.66199 1.56827\n",
      " 128 1.773e-01 4.637e+04 6.474e-02 -- 3.426e+02 -- 0.137667 -0.38234 -1.50784 -1.84831 -2.37524 -2.93855 -4.06353 -3.63268 -0.151255 0.132244 0.325363 -0.00644634 0.569497 0.0282044 1.65879 1.56851\n",
      " 130 1.626e-01 5.158e+04 6.353e-02 -- 3.427e+02 -- 0.13768 -0.382351 -1.50784 -1.84831 -2.37524 -2.93859 -4.06031 -3.63268 -0.151045 0.132319 0.324886 -0.00633207 0.569501 0.0283732 1.656 1.56872\n",
      " 132 1.487e-01 5.737e+04 6.244e-02 -- 3.428e+02 -- 0.137692 -0.382362 -1.50785 -1.8483 -2.37524 -2.93863 -4.05743 -3.63268 -0.150856 0.132392 0.324446 -0.00622911 0.569505 0.0285272 1.65356 1.56892\n",
      " 134 1.356e-01 6.381e+04 6.147e-02 -- 3.428e+02 -- 0.137703 -0.382372 -1.50785 -1.84829 -2.37524 -2.93866 -4.05486 -3.63268 -0.150688 0.132464 0.324041 -0.00613648 0.569508 0.0286677 1.65143 1.56909\n",
      " 136 1.233e-01 7.096e+04 6.059e-02 -- 3.429e+02 -- 0.137714 -0.382381 -1.50786 -1.84829 -2.37523 -2.9387 -4.05256 -3.63268 -0.150538 0.132535 0.32367 -0.00605327 0.569511 0.0287957 1.64957 1.56925\n",
      " 138 1.118e-01 7.890e+04 5.981e-02 -- 3.429e+02 -- 0.137723 -0.382391 -1.50786 -1.84828 -2.37523 -2.93873 -4.05049 -3.63268 -0.150404 0.132603 0.32333 -0.00597864 0.569514 0.0289123 1.64794 1.5694\n",
      " 140 1.012e-01 8.773e+04 5.910e-02 -- 3.430e+02 -- 0.137732 -0.382399 -1.50787 -1.84828 -2.37523 -2.93875 -4.04864 -3.63267 -0.150285 0.132669 0.323018 -0.00591178 0.569516 0.0290186 1.6465 1.56953\n",
      " 142 9.132e-02 9.753e+04 5.847e-02 -- 3.431e+02 -- 0.137741 -0.382407 -1.50787 -1.84827 -2.37523 -2.93878 -4.04698 -3.63267 -0.150179 0.132732 0.322732 -0.00585198 0.569518 0.0291153 1.64524 1.56965\n",
      " 144 8.225e-02 1.084e+05 5.790e-02 -- 3.431e+02 -- 0.137748 -0.382415 -1.50788 -1.84827 -2.37523 -2.9388 -4.04549 -3.63267 -0.150085 0.132794 0.322472 -0.00579854 0.56952 0.0292034 1.64413 1.56976\n",
      " 146 7.394e-02 1.205e+05 5.739e-02 -- 3.432e+02 -- 0.137755 -0.382422 -1.50788 -1.84826 -2.37523 -2.93882 -4.04416 -3.63267 -0.150003 0.132852 0.322234 -0.00575085 0.569522 0.0292835 1.64315 1.56985\n",
      " 148 6.635e-02 1.340e+05 5.692e-02 -- 3.432e+02 -- 0.137762 -0.382429 -1.50788 -1.84826 -2.37523 -2.93883 -4.04295 -3.63267 -0.14993 0.132909 0.322017 -0.00570833 0.569524 0.0293563 1.64229 1.56994\n",
      " 150 5.944e-02 1.489e+05 5.650e-02 -- 3.433e+02 -- 0.137767 -0.382436 -1.50788 -1.84825 -2.37522 -2.93885 -4.04187 -3.63267 -0.149865 0.132963 0.321819 -0.00567045 0.569526 0.0294226 1.64153 1.57002\n",
      " 152 5.317e-02 1.655e+05 5.613e-02 -- 3.434e+02 -- 0.137773 -0.382442 -1.50789 -1.84825 -2.37522 -2.93887 -4.0409 -3.63267 -0.149809 0.133014 0.32164 -0.00563675 0.569527 0.0294828 1.64086 1.5701\n",
      " 154 4.750e-02 1.840e+05 5.579e-02 -- 3.434e+02 -- 0.137778 -0.382448 -1.50789 -1.84825 -2.37522 -2.93888 -4.04003 -3.63267 -0.14976 0.133063 0.321476 -0.00560678 0.569529 0.0295374 1.64027 1.57016\n",
      " 156 4.239e-02 2.045e+05 5.548e-02 -- 3.435e+02 -- 0.137782 -0.382453 -1.50789 -1.84824 -2.37522 -2.93889 -4.03925 -3.63267 -0.149717 0.13311 0.321328 -0.00558015 0.56953 0.0295871 1.63974 1.57022\n",
      " 158 3.778e-02 2.273e+05 5.521e-02 -- 3.435e+02 -- 0.137786 -0.382458 -1.50789 -1.84824 -2.37522 -2.9389 -4.03854 -3.63267 -0.149679 0.133154 0.321193 -0.00555649 0.569531 0.0296321 1.63928 1.57028\n",
      " 160 3.366e-02 2.526e+05 5.496e-02 -- 3.436e+02 -- 0.13779 -0.382462 -1.5079 -1.84824 -2.37522 -2.93891 -4.03791 -3.63267 -0.149647 0.133196 0.321071 -0.0055355 0.569532 0.029673 1.63887 1.57033\n",
      " 162 2.995e-02 2.807e+05 5.473e-02 -- 3.436e+02 -- 0.137794 -0.382467 -1.5079 -1.84823 -2.37522 -2.93892 -4.03734 -3.63267 -0.149619 0.133236 0.32096 -0.00551686 0.569533 0.0297101 1.63851 1.57037\n",
      " 164 2.663e-02 3.119e+05 5.453e-02 -- 3.437e+02 -- 0.137797 -0.382471 -1.5079 -1.84823 -2.37522 -2.93893 -4.03683 -3.63267 -0.149594 0.133273 0.32086 -0.00550034 0.569534 0.0297438 1.63819 1.57041\n",
      " 166 2.370e-02 3.467e+05 5.435e-02 -- 3.437e+02 -- 0.137799 -0.382475 -1.5079 -1.84823 -2.37522 -2.93894 -4.03636 -3.63266 -0.149574 0.133308 0.320769 -0.0054857 0.569535 0.0297742 1.6379 1.57045\n",
      " 168 2.105e-02 3.852e+05 5.418e-02 -- 3.438e+02 -- 0.137802 -0.382478 -1.5079 -1.84823 -2.37522 -2.93894 -4.03595 -3.63266 -0.149556 0.133341 0.320686 -0.00547269 0.569536 0.0298019 1.63765 1.57048\n",
      " 170 1.872e-02 4.281e+05 5.403e-02 -- 3.438e+02 -- 0.137804 -0.382481 -1.5079 -1.84823 -2.37522 -2.93895 -4.03557 -3.63266 -0.14954 0.133373 0.320612 -0.00546117 0.569536 0.0298269 1.63743 1.57051\n",
      " 172 1.661e-02 4.757e+05 5.390e-02 -- 3.439e+02 -- 0.137806 -0.382484 -1.5079 -1.84822 -2.37522 -2.93895 -4.03524 -3.63266 -0.149527 0.133402 0.320545 -0.00545095 0.569537 0.0298495 1.63723 1.57054\n",
      " 174 1.477e-02 5.286e+05 5.378e-02 -- 3.440e+02 -- 0.137808 -0.382487 -1.5079 -1.84822 -2.37522 -2.93896 -4.03493 -3.63266 -0.149516 0.133429 0.320484 -0.00544189 0.569537 0.02987 1.63705 1.57056\n",
      " 176 1.314e-02 5.874e+05 5.367e-02 -- 3.440e+02 -- 0.13781 -0.382489 -1.50791 -1.84822 -2.37522 -2.93896 -4.03466 -3.63266 -0.149506 0.133454 0.320429 -0.00543385 0.569538 0.0298886 1.63689 1.57058\n",
      " 178 1.169e-02 6.528e+05 5.357e-02 -- 3.441e+02 -- 0.137812 -0.382492 -1.50791 -1.84822 -2.37522 -2.93897 -4.03442 -3.63266 -0.149498 0.133478 0.320379 -0.00542671 0.569538 0.0299054 1.63675 1.5706\n",
      " 180 1.036e-02 7.254e+05 5.348e-02 -- 3.441e+02 -- 0.137813 -0.382494 -1.50791 -1.84822 -2.37522 -2.93897 -4.0342 -3.63266 -0.149491 0.1335 0.320335 -0.00542037 0.569539 0.0299206 1.63663 1.57062\n",
      " 182 9.239e-03 8.060e+05 5.340e-02 -- 3.442e+02 -- 0.137814 -0.382496 -1.50791 -1.84822 -2.37522 -2.93897 -4.034 -3.63266 -0.149485 0.133521 0.320294 -0.00541475 0.569539 0.0299343 1.63652 1.57064\n",
      " 184 8.217e-03 8.957e+05 5.333e-02 -- 3.442e+02 -- 0.137815 -0.382498 -1.50791 -1.84822 -2.37522 -2.93898 -4.03382 -3.63266 -0.149481 0.13354 0.320258 -0.00540975 0.56954 0.0299467 1.63642 1.57065\n",
      " 186 7.314e-03 9.952e+05 5.327e-02 -- 3.443e+02 -- 0.137816 -0.382499 -1.50791 -1.84821 -2.37522 -2.93898 -4.03366 -3.63266 -0.149476 0.133557 0.320225 -0.00540531 0.56954 0.0299579 1.63633 1.57066\n",
      " 188 6.496e-03 1.106e+06 5.321e-02 -- 3.443e+02 -- 0.137817 -0.382501 -1.50791 -1.84821 -2.37522 -2.93898 -4.03351 -3.63266 -0.149472 0.133573 0.320195 -0.00540135 0.56954 0.029968 1.63625 1.57068\n",
      " 190 5.793e-03 1.229e+06 5.315e-02 -- 3.444e+02 -- 0.137818 -0.382502 -1.50791 -1.84821 -2.37522 -2.93899 -4.03338 -3.63266 -0.14947 0.133589 0.320169 -0.00539784 0.56954 0.0299772 1.63618 1.57069\n",
      " 192 5.217e-03 1.365e+06 5.311e-02 -- 3.444e+02 -- 0.137819 -0.382503 -1.50791 -1.84821 -2.37522 -2.93899 -4.03326 -3.63266 -0.149468 0.133603 0.320144 -0.00539472 0.569541 0.0299854 1.63612 1.5707\n",
      " 194 4.529e-03 1.517e+06 5.306e-02 -- 3.445e+02 -- 0.13782 -0.382504 -1.50791 -1.84821 -2.37522 -2.93899 -4.03316 -3.63266 -0.149465 0.133615 0.320123 -0.0053919 0.569541 0.0299928 1.63606 1.57071\n",
      " 196 4.139e-03 1.686e+06 5.303e-02 -- 3.445e+02 -- 0.13782 -0.382505 -1.50791 -1.84821 -2.37522 -2.93899 -4.03306 -3.63266 -0.149464 0.133627 0.320103 -0.00538946 0.569541 0.0299996 1.63601 1.57071\n",
      " 198 3.573e-03 1.873e+06 5.299e-02 -- 3.446e+02 -- 0.137821 -0.382506 -1.50791 -1.84821 -2.37522 -2.93899 -4.03298 -3.63266 -0.149462 0.133636 0.320085 -0.00538723 0.569541 0.0300056 1.63597 1.57072\n",
      " 200 3.302e-03 2.081e+06 5.296e-02 -- 3.446e+02 -- 0.137821 -0.382507 -1.50791 -1.84821 -2.37522 -2.93899 -4.0329 -3.63266 -0.14946 0.133646 0.32007 -0.00538531 0.569541 0.0300111 1.63593 1.57073\n",
      " 202 2.976e-03 2.313e+06 5.293e-02 -- 3.447e+02 -- 0.137822 -0.382508 -1.50791 -1.84821 -2.37521 -2.93899 -4.03283 -3.63266 -0.149459 0.133656 0.320055 -0.00538353 0.569542 0.0300161 1.63589 1.57073\n",
      " 204 2.400e-03 2.570e+06 5.291e-02 -- 3.448e+02 -- 0.137822 -0.382509 -1.50791 -1.84821 -2.37521 -2.939 -4.03277 -3.63266 -0.149457 0.133663 0.320042 -0.00538193 0.569542 0.0300205 1.63586 1.57074\n",
      " 206 2.292e-03 2.855e+06 5.288e-02 -- 3.448e+02 -- 0.137823 -0.382509 -1.50791 -1.84821 -2.37521 -2.939 -4.03271 -3.63266 -0.149457 0.13367 0.320031 -0.00538063 0.569542 0.0300245 1.63583 1.57074\n",
      " 208 2.150e-03 3.173e+06 5.287e-02 -- 3.449e+02 -- 0.137823 -0.38251 -1.50791 -1.84821 -2.37521 -2.939 -4.03266 -3.63266 -0.149456 0.13368 0.32002 -0.0053794 0.569542 0.0300281 1.6358 1.57075\n",
      " 210 1.886e-03 3.525e+06 5.285e-02 -- 3.449e+02 -- 0.137823 -0.38251 -1.50791 -1.84821 -2.37521 -2.939 -4.03262 -3.63266 -0.149456 0.133687 0.320011 -0.00537824 0.569542 0.0300314 1.63578 1.57075\n",
      " 212 1.670e-03 3.917e+06 5.283e-02 -- 3.450e+02 -- 0.137823 -0.382511 -1.50791 -1.84821 -2.37521 -2.939 -4.03258 -3.63266 -0.149454 0.133693 0.320002 -0.00537723 0.569542 0.0300343 1.63576 1.57075\n",
      " 214 1.507e-03 4.352e+06 5.281e-02 -- 3.450e+02 -- 0.137824 -0.382511 -1.50791 -1.84821 -2.37521 -2.939 -4.03254 -3.63266 -0.149455 0.133696 0.319995 -0.00537633 0.569542 0.030037 1.63574 1.57076\n",
      " 216 1.104e-03 4.836e+06 5.280e-02 -- 3.451e+02 -- 0.137824 -0.382512 -1.50791 -1.84821 -2.37521 -2.939 -4.03251 -3.63266 -0.149453 0.133698 0.319988 -0.00537552 0.569542 0.0300394 1.63572 1.57076\n",
      " 218 1.248e-03 5.374e+06 5.279e-02 -- 3.451e+02 -- 0.137824 -0.382512 -1.50791 -1.84821 -2.37521 -2.939 -4.03247 -3.63266 -0.14945 0.133705 0.319982 -0.00537493 0.569542 0.0300416 1.63571 1.57076\n",
      " 220 9.861e-04 5.971e+06 5.278e-02 -- 3.452e+02 -- 0.137824 -0.382512 -1.50791 -1.84821 -2.37521 -2.939 -4.03245 -3.63266 -0.14945 0.13371 0.319976 -0.00537426 0.569542 0.0300435 1.6357 1.57077\n",
      " 222 1.025e-03 6.634e+06 5.277e-02 -- 3.452e+02 -- 0.137824 -0.382513 -1.50791 -1.84821 -2.37521 -2.939 -4.03242 -3.63266 -0.149451 0.133714 0.319971 -0.00537373 0.569542 0.0300453 1.63568 1.57077\n",
      " 224 7.583e-04 7.371e+06 5.276e-02 -- 3.453e+02 -- 0.137825 -0.382513 -1.50791 -1.84821 -2.37521 -2.939 -4.0324 -3.63266 -0.14945 0.133716 0.319966 -0.00537318 0.569542 0.0300468 1.63567 1.57077\n",
      " 226 6.529e-04 8.190e+06 5.275e-02 -- 3.453e+02 -- 0.137825 -0.382513 -1.50791 -1.84821 -2.37521 -2.939 -4.03238 -3.63266 -0.149445 0.133722 0.319962 -0.00537277 0.569542 0.0300482 1.63566 1.57077\n",
      " 228 8.712e-04 9.101e+06 5.274e-02 -- 3.454e+02 -- 0.137825 -0.382513 -1.50791 -1.84821 -2.37521 -2.939 -4.03236 -3.63266 -0.14945 0.133724 0.319959 -0.00537242 0.569543 0.0300495 1.63566 1.57077\n",
      " 230 7.297e-04 1.011e+07 5.274e-02 -- 3.454e+02 -- 0.137825 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.03235 -3.63266 -0.149455 0.133729 0.319955 -0.00537195 0.569543 0.0300506 1.63565 1.57077\n",
      " 232 7.713e-04 1.124e+07 5.273e-02 -- 3.455e+02 -- 0.137825 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.03233 -3.63266 -0.149461 0.133726 0.319952 -0.00537156 0.569543 0.0300516 1.63564 1.57077\n",
      " 234 1.232e-03 1.248e+07 5.273e-02 -- 3.455e+02 -- 0.137825 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.03232 -3.63266 -0.14946 0.133736 0.319949 -0.00537133 0.569543 0.0300525 1.63563 1.57078\n",
      " 236 8.332e-04 1.387e+07 5.272e-02 -- 3.456e+02 -- 0.137825 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.03231 -3.63266 -0.149466 0.133721 0.319947 -0.00537067 0.569543 0.0300532 1.63562 1.57078\n",
      " 238 1.904e-03 1.541e+07 5.271e-02 -- 3.456e+02 -- 0.137825 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.0323 -3.63266 -0.149478 0.133724 0.319945 -0.00537055 0.569543 0.0300541 1.63562 1.57078\n",
      " 240 1.685e-03 1.712e+07 5.271e-02 -- 3.457e+02 -- 0.137825 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.03229 -3.63266 -0.149472 0.13372 0.319943 -0.00536953 0.569543 0.0300545 1.63561 1.57078\n",
      " 242 2.904e-03 1.903e+07 5.268e-02 -- 3.458e+02 -- 0.137825 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.03228 -3.63266 -0.149485 0.133743 0.319941 -0.00537003 0.569543 0.0300553 1.63561 1.57078\n",
      " 244 2.822e-03 2.113e+07 5.268e-02 -- 3.458e+02 -- 0.137826 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03227 -3.63266 -0.149462 0.133738 0.319939 -0.00536847 0.569543 0.0300552 1.63559 1.57078\n",
      " 246 3.296e-03 2.349e+07 5.271e-02 -- 3.459e+02 -- 0.137826 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.03227 -3.63266 -0.149478 0.133747 0.319938 -0.00536999 0.569543 0.0300566 1.63561 1.57078\n",
      " 248 8.922e-04 2.610e+07 5.276e-02 -- 3.459e+02 -- 0.137826 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03226 -3.63266 -0.149469 0.133756 0.319936 -0.00536822 0.569543 0.0300563 1.63559 1.57078\n",
      " 250 1.022e-03 2.900e+07 5.270e-02 -- 3.460e+02 -- 0.137826 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03226 -3.63266 -0.149478 0.133751 0.319935 -0.0053687 0.569543 0.0300571 1.63559 1.57078\n",
      " 252 1.275e-03 3.223e+07 5.272e-02 -- 3.460e+02 -- 0.137826 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03225 -3.63266 -0.149493 0.133745 0.319934 -0.00536846 0.569543 0.0300572 1.63559 1.57078\n",
      " 254 2.477e-03 3.581e+07 5.270e-02 -- 3.461e+02 -- 0.137826 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03225 -3.63266 -0.149483 0.133762 0.319933 -0.00536868 0.569543 0.0300576 1.63558 1.57078\n",
      " 256 2.786e-03 3.976e+07 5.253e-02 -- 3.461e+02 -- 0.137826 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03224 -3.63266 -0.149446 0.133745 0.319932 -0.00536896 0.569543 0.0300578 1.63558 1.57078\n",
      " 258 2.532e-03 4.421e+07 5.284e-02 -- 3.462e+02 -- 0.137827 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.03224 -3.63266 -0.149451 0.133732 0.319933 -0.00537046 0.569543 0.0300589 1.6356 1.57078\n",
      " 260 5.032e-03 4.907e+07 5.240e-02 -- 3.462e+02 -- 0.137827 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03223 -3.63266 -0.149413 0.133704 0.319932 -0.00536945 0.569543 0.0300589 1.63559 1.57078\n",
      " 262 3.782e-03 5.456e+07 5.281e-02 -- 3.463e+02 -- 0.137827 -0.382514 -1.50791 -1.84821 -2.37521 -2.939 -4.03223 -3.63266 -0.149414 0.133736 0.319934 -0.00537215 0.569543 0.0300602 1.63561 1.57078\n",
      " 264 4.099e-03 6.056e+07 5.240e-02 -- 3.463e+02 -- 0.137827 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03223 -3.63266 -0.149357 0.133751 0.319931 -0.00537099 0.569543 0.0300595 1.63559 1.57078\n",
      " 266 3.335e-03 6.736e+07 5.298e-02 -- 3.464e+02 -- 0.137827 -0.382514 -1.50791 -1.8482 -2.37521 -2.939 -4.03222 -3.63266 -0.14935 0.133787 0.319931 -0.00537319 0.569543 0.030061 1.63561 1.57079\n",
      " 268 2.128e-03 7.485e+07 5.274e-02 -- 3.464e+02 -- 0.137827 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03222 -3.63266 -0.149373 0.133832 0.319929 -0.00537226 0.569543 0.0300605 1.6356 1.57079\n",
      " 270 4.362e-03 8.314e+07 5.273e-02 -- 3.465e+02 -- 0.137827 -0.382516 -1.50791 -1.84821 -2.37521 -2.939 -4.03222 -3.63266 -0.149357 0.133842 0.319928 -0.00537111 0.569543 0.0300599 1.63558 1.57078\n",
      " 272 7.401e-03 9.241e+07 5.281e-02 -- 3.465e+02 -- 0.137827 -0.382515 -1.50791 -1.84821 -2.37521 -2.939 -4.03222 -3.63266 -0.149297 0.133867 0.319929 -0.00537346 0.569543 0.0300607 1.6356 1.57079\n",
      " 273 2.449e-01 9.778e+11 3.957e+01 -- 3.070e+02 -- 0.137829 -0.382514 -1.50792 -1.8482 -2.37521 -2.93901 -4.03219 -3.63266 -0.149811 0.134858 0.319919 -0.00539408 0.569543 0.0300672 1.63566 1.57079\n",
      " 275 2.085e-01 1.216e+12 5.713e+01 -- 2.498e+02 -- 0.137838 -0.382547 -1.50791 -1.84822 -2.37521 -2.93901 -4.03229 -3.63267 -0.146142 0.136356 0.319715 -0.00536682 0.569539 0.0300298 1.63519 1.57077\n",
      " 278 1.768e-01 1.553e+11 6.527e+01 -- 3.151e+02 -- 0.13783 -0.382542 -1.50791 -1.84822 -2.37521 -2.93901 -4.03228 -3.63266 -0.146083 0.136071 0.319727 -0.00537179 0.56954 0.0300328 1.63531 1.57077\n",
      " 280 1.401e-01 2.293e+10 2.877e+01 -- 3.439e+02 -- 0.13781 -0.382487 -1.50792 -1.8482 -2.37521 -2.93902 -4.03218 -3.63266 -0.147503 0.133665 0.319814 -0.00542418 0.569545 0.0300764 1.63632 1.57081\n",
      " 282 3.005e-01 1.584e+12 6.015e+01 -- 2.837e+02 -- 0.137818 -0.38251 -1.50792 -1.84821 -2.37521 -2.93902 -4.03219 -3.63266 -0.149569 0.134696 0.319799 -0.00539672 0.56954 0.0300658 1.63602 1.5708\n",
      " 285 6.887e-01 3.338e+12 5.965e+01 -- 2.241e+02 -- 0.137808 -0.382511 -1.50792 -1.84821 -2.37521 -2.93901 -4.03218 -3.63266 -0.149948 0.13503 0.319788 -0.0053805 0.569539 0.0300609 1.63597 1.5708\n",
      " 286 2.694e+01 1.474e+08 6.253e+01 -- 2.866e+02 -- 0.13812 -0.382806 -1.50771 -1.84841 -2.37523 -2.93893 -4.03632 -3.63262 -0.0891567 0.0420396 0.319568 -0.00184545 0.56953 0.029434 1.62857 1.57017\n",
      " 289 1.835e+01 2.710e+07 3.352e+01 -- 3.201e+02 -- 0.137998 -0.382649 -1.50775 -1.84833 -2.37522 -2.93901 -4.03602 -3.63259 -0.0918629 0.0445307 0.319829 -0.00234263 0.56956 0.0297005 1.63399 1.57042\n",
      " 291 1.677e+00 4.770e+04 1.799e+01 -- 3.381e+02 -- 0.13705 -0.381771 -1.50801 -1.84766 -2.3752 -2.93967 -4.03323 -3.63229 -0.113651 0.0634674 0.321859 -0.00664201 0.569811 0.0320009 1.68021 1.57254\n",
      " 293 8.980e-01 2.894e+05 2.261e+00 -- 3.404e+02 -- 0.137302 -0.381985 -1.50798 -1.84785 -2.37521 -2.93948 -4.03313 -3.63237 -0.110751 0.0693232 0.32106 -0.00552825 0.569729 0.0313773 1.66678 1.57201\n",
      " 295 7.368e-01 3.177e+05 9.101e-01 -- 3.413e+02 -- 0.137338 -0.382099 -1.50797 -1.84786 -2.37521 -2.93948 -4.03253 -3.63238 -0.112228 0.0755485 0.320805 -0.00556173 0.569719 0.0313963 1.66607 1.57205\n",
      " 297 5.900e-01 3.573e+05 6.175e-01 -- 3.419e+02 -- 0.137345 -0.382178 -1.50797 -1.84784 -2.37521 -2.93949 -4.03194 -3.63237 -0.114034 0.0811151 0.320645 -0.00570323 0.56972 0.0314796 1.66672 1.57213\n",
      " 299 4.790e-01 3.999e+05 4.486e-01 -- 3.424e+02 -- 0.137357 -0.382242 -1.50797 -1.84783 -2.37521 -2.9395 -4.03146 -3.63237 -0.11548 0.0859006 0.320493 -0.00578771 0.569719 0.0315348 1.66691 1.57219\n",
      " 301 3.950e-01 4.458e+05 3.396e-01 -- 3.427e+02 -- 0.137372 -0.382298 -1.50797 -1.84783 -2.37521 -2.93951 -4.03105 -3.63237 -0.116614 0.0900153 0.320346 -0.00582755 0.569717 0.0315672 1.66675 1.57223\n",
      " 303 3.299e-01 4.961e+05 2.661e-01 -- 3.430e+02 -- 0.137388 -0.382345 -1.50797 -1.84783 -2.37521 -2.93951 -4.03071 -3.63237 -0.117524 0.0935712 0.320206 -0.00584073 0.569714 0.0315858 1.6664 1.57225\n",
      " 305 2.783e-01 5.518e+05 2.149e-01 -- 3.432e+02 -- 0.137405 -0.382386 -1.50797 -1.84783 -2.37521 -2.93951 -4.03042 -3.63237 -0.118268 0.0966579 0.320075 -0.00583822 0.569712 0.0315961 1.66596 1.57227\n",
      " 307 2.366e-01 6.135e+05 1.782e-01 -- 3.434e+02 -- 0.137421 -0.382421 -1.50797 -1.84783 -2.37521 -2.93951 -4.03017 -3.63237 -0.118886 0.0993476 0.319954 -0.00582657 0.569709 0.0316013 1.66548 1.57227\n",
      " 309 2.026e-01 6.820e+05 1.512e-01 -- 3.435e+02 -- 0.137436 -0.382452 -1.50797 -1.84784 -2.37521 -2.93951 -4.02995 -3.63238 -0.119407 0.101698 0.319843 -0.00580983 0.569707 0.0316033 1.665 1.57228\n",
      " 311 1.745e-01 7.581e+05 1.310e-01 -- 3.436e+02 -- 0.137449 -0.382478 -1.50797 -1.84784 -2.37521 -2.9395 -4.02976 -3.63238 -0.11985 0.103759 0.319742 -0.00579053 0.569705 0.0316034 1.66454 1.57228\n",
      " 313 1.511e-01 8.426e+05 1.157e-01 -- 3.438e+02 -- 0.137462 -0.382502 -1.50797 -1.84784 -2.37521 -2.9395 -4.02959 -3.63238 -0.120231 0.10557 0.319649 -0.00577023 0.569703 0.0316024 1.6641 1.57228\n",
      " 315 1.314e-01 9.364e+05 1.039e-01 -- 3.439e+02 -- 0.137474 -0.382522 -1.50797 -1.84785 -2.37521 -2.9395 -4.02944 -3.63238 -0.120561 0.107165 0.319566 -0.00574994 0.569701 0.0316007 1.66369 1.57228\n",
      " 317 1.146e-01 1.041e+06 9.470e-02 -- 3.440e+02 -- 0.137484 -0.38254 -1.50797 -1.84785 -2.37521 -2.9395 -4.0293 -3.63238 -0.120849 0.108572 0.31949 -0.00573024 0.569699 0.0315987 1.66331 1.57228\n",
      " 319 1.002e-01 1.157e+06 8.741e-02 -- 3.440e+02 -- 0.137494 -0.382556 -1.50797 -1.84785 -2.37521 -2.9395 -4.02918 -3.63238 -0.121102 0.109816 0.319421 -0.00571149 0.569698 0.0315965 1.66296 1.57228\n",
      " 321 8.813e-02 1.285e+06 8.158e-02 -- 3.441e+02 -- 0.137503 -0.382571 -1.50797 -1.84786 -2.37521 -2.9395 -4.02907 -3.63239 -0.121323 0.110917 0.319359 -0.0056939 0.569696 0.0315944 1.66265 1.57228\n",
      " 323 7.747e-02 1.428e+06 7.694e-02 -- 3.442e+02 -- 0.13751 -0.382583 -1.50797 -1.84786 -2.37521 -2.9395 -4.02898 -3.63239 -0.12152 0.111894 0.319303 -0.00567758 0.569695 0.0315923 1.66236 1.57228\n",
      " 325 6.841e-02 1.587e+06 7.313e-02 -- 3.443e+02 -- 0.137518 -0.382594 -1.50797 -1.84786 -2.37521 -2.93949 -4.02889 -3.63239 -0.121694 0.112761 0.319252 -0.00566248 0.569694 0.0315904 1.6621 1.57228\n",
      " 327 6.037e-02 1.764e+06 7.004e-02 -- 3.443e+02 -- 0.137524 -0.382604 -1.50797 -1.84786 -2.37521 -2.93949 -4.02881 -3.63239 -0.121849 0.113533 0.319207 -0.00564862 0.569693 0.0315885 1.66187 1.57228\n",
      " 329 5.354e-02 1.960e+06 6.747e-02 -- 3.444e+02 -- 0.13753 -0.382613 -1.50797 -1.84786 -2.37521 -2.93949 -4.02875 -3.63239 -0.121987 0.114218 0.319166 -0.00563591 0.569692 0.0315868 1.66165 1.57228\n",
      " 331 4.752e-02 2.178e+06 6.536e-02 -- 3.445e+02 -- 0.137535 -0.382621 -1.50797 -1.84787 -2.37521 -2.93949 -4.02868 -3.63239 -0.12211 0.114829 0.319129 -0.00562439 0.569691 0.0315853 1.66146 1.57228\n",
      " 333 4.222e-02 2.420e+06 6.360e-02 -- 3.445e+02 -- 0.13754 -0.382628 -1.50797 -1.84787 -2.37521 -2.93949 -4.02863 -3.63239 -0.122219 0.115375 0.319095 -0.00561382 0.56969 0.0315839 1.66129 1.57228\n",
      " 335 3.769e-02 2.689e+06 6.211e-02 -- 3.446e+02 -- 0.137544 -0.382634 -1.50797 -1.84787 -2.37521 -2.93949 -4.02858 -3.63239 -0.122317 0.115862 0.319065 -0.00560428 0.56969 0.0315826 1.66113 1.57228\n",
      " 337 3.311e-02 2.989e+06 6.088e-02 -- 3.447e+02 -- 0.137547 -0.38264 -1.50797 -1.84787 -2.37521 -2.93949 -4.02853 -3.63239 -0.122404 0.116299 0.319038 -0.00559562 0.569689 0.0315815 1.66099 1.57228\n",
      " 339 2.982e-02 3.321e+06 5.975e-02 -- 3.447e+02 -- 0.137551 -0.382645 -1.50797 -1.84787 -2.37521 -2.93949 -4.02849 -3.63239 -0.122484 0.116684 0.319014 -0.00558779 0.569689 0.0315804 1.66087 1.57228\n",
      " 341 2.639e-02 3.690e+06 5.889e-02 -- 3.448e+02 -- 0.137554 -0.382649 -1.50797 -1.84787 -2.37521 -2.93949 -4.02845 -3.63239 -0.122555 0.117032 0.318992 -0.00558071 0.569688 0.0315795 1.66076 1.57228\n",
      " 343 2.409e-02 4.100e+06 5.809e-02 -- 3.448e+02 -- 0.137557 -0.382653 -1.50797 -1.84787 -2.37521 -2.93949 -4.02842 -3.63239 -0.122619 0.117341 0.318972 -0.00557437 0.569688 0.0315786 1.66065 1.57228\n",
      " 345 2.129e-02 4.556e+06 5.751e-02 -- 3.449e+02 -- 0.137559 -0.382657 -1.50797 -1.84787 -2.37521 -2.93949 -4.02839 -3.63239 -0.122676 0.117624 0.318955 -0.00556861 0.569687 0.0315779 1.66056 1.57227\n",
      " 347 1.889e-02 5.062e+06 5.690e-02 -- 3.450e+02 -- 0.137561 -0.38266 -1.50797 -1.84787 -2.37521 -2.93949 -4.02837 -3.6324 -0.12273 0.117874 0.318939 -0.0055633 0.569687 0.0315772 1.66048 1.57227\n",
      " 349 1.666e-02 5.625e+06 5.637e-02 -- 3.450e+02 -- 0.137563 -0.382663 -1.50797 -1.84788 -2.37521 -2.93949 -4.02834 -3.6324 -0.122775 0.118097 0.318924 -0.00555856 0.569687 0.0315765 1.6604 1.57227\n",
      " 351 1.548e-02 6.250e+06 5.589e-02 -- 3.451e+02 -- 0.137565 -0.382666 -1.50797 -1.84788 -2.37521 -2.93949 -4.02832 -3.6324 -0.122815 0.118293 0.318911 -0.00555438 0.569686 0.031576 1.66034 1.57227\n",
      " 353 1.367e-02 6.945e+06 5.559e-02 -- 3.451e+02 -- 0.137567 -0.382668 -1.50797 -1.84788 -2.37521 -2.93949 -4.0283 -3.6324 -0.122851 0.118477 0.3189 -0.00555074 0.569686 0.0315756 1.66028 1.57227\n",
      " 355 1.218e-02 7.717e+06 5.527e-02 -- 3.452e+02 -- 0.137568 -0.38267 -1.50797 -1.84788 -2.37521 -2.93949 -4.02828 -3.6324 -0.122888 0.118639 0.318889 -0.00554714 0.569686 0.0315751 1.66022 1.57227\n",
      " 357 1.125e-02 8.574e+06 5.496e-02 -- 3.452e+02 -- 0.13757 -0.382672 -1.50797 -1.84788 -2.37521 -2.93949 -4.02827 -3.6324 -0.122919 0.118783 0.31888 -0.00554391 0.569686 0.0315747 1.66017 1.57227\n",
      " 359 9.239e-03 9.527e+06 5.475e-02 -- 3.453e+02 -- 0.137571 -0.382674 -1.50797 -1.84788 -2.37521 -2.93949 -4.02825 -3.6324 -0.122951 0.118917 0.318871 -0.00554137 0.569686 0.0315743 1.66013 1.57227\n",
      " 361 8.671e-03 1.059e+07 5.442e-02 -- 3.453e+02 -- 0.137572 -0.382675 -1.50797 -1.84788 -2.37521 -2.93949 -4.02824 -3.6324 -0.122974 0.119027 0.318864 -0.00553843 0.569685 0.0315738 1.66009 1.57227\n",
      " 363 7.118e-03 1.176e+07 5.421e-02 -- 3.454e+02 -- 0.137573 -0.382677 -1.50797 -1.84788 -2.37521 -2.93949 -4.02823 -3.6324 -0.122989 0.11913 0.318857 -0.00553662 0.569685 0.0315737 1.66005 1.57227\n",
      " 365 6.502e-03 1.307e+07 5.400e-02 -- 3.454e+02 -- 0.137574 -0.382678 -1.50797 -1.84788 -2.37521 -2.93948 -4.02822 -3.6324 -0.123017 0.119215 0.318851 -0.0055347 0.569685 0.0315735 1.66002 1.57227\n",
      " 367 5.241e-03 1.452e+07 5.386e-02 -- 3.455e+02 -- 0.137574 -0.382679 -1.50797 -1.84788 -2.37521 -2.93948 -4.02821 -3.6324 -0.123025 0.119292 0.318845 -0.00553265 0.569685 0.0315732 1.65999 1.57227\n",
      " 369 4.797e-03 1.614e+07 5.362e-02 -- 3.456e+02 -- 0.137575 -0.382679 -1.50797 -1.84788 -2.37521 -2.93948 -4.0282 -3.6324 -0.123045 0.119355 0.318841 -0.00553154 0.569685 0.0315732 1.65997 1.57227\n",
      " 371 4.242e-03 1.793e+07 5.357e-02 -- 3.456e+02 -- 0.137575 -0.38268 -1.50797 -1.84788 -2.37521 -2.93948 -4.0282 -3.6324 -0.123059 0.119412 0.318836 -0.00553001 0.569685 0.031573 1.65995 1.57227\n",
      " 373 5.841e-03 1.992e+07 5.347e-02 -- 3.457e+02 -- 0.137576 -0.382681 -1.50797 -1.84788 -2.37521 -2.93948 -4.02819 -3.6324 -0.123078 0.119463 0.318832 -0.00552879 0.569685 0.0315729 1.65993 1.57227\n",
      " 375 3.219e-03 2.213e+07 5.366e-02 -- 3.457e+02 -- 0.137577 -0.382682 -1.50797 -1.84788 -2.37521 -2.93948 -4.02818 -3.6324 -0.123089 0.119532 0.318828 -0.00552759 0.569685 0.0315728 1.65991 1.57227\n",
      " 377 2.633e-03 2.459e+07 5.334e-02 -- 3.458e+02 -- 0.137577 -0.382683 -1.50797 -1.84788 -2.37521 -2.93948 -4.02818 -3.6324 -0.123107 0.119571 0.318825 -0.00552604 0.569685 0.0315725 1.65989 1.57227\n",
      " 379 4.116e-03 2.733e+07 5.319e-02 -- 3.458e+02 -- 0.137578 -0.382683 -1.50797 -1.84788 -2.37521 -2.93948 -4.02817 -3.6324 -0.12312 0.119602 0.318822 -0.00552505 0.569685 0.0315725 1.65988 1.57227\n",
      " 380 5.533e+01 8.512e+13 3.580e+01 -- 3.100e+02 -- 0.13758 -0.382687 -1.50797 -1.84788 -2.37521 -2.93948 -4.02813 -3.6324 -0.123171 0.120095 0.318799 -0.0055189 0.569684 0.0315729 1.65977 1.57227\n",
      " 382 7.194e+00 3.296e+06 1.119e+02 -- 1.981e+02 -- 0.136564 -0.384498 -1.50899 -1.84727 -2.37514 -2.93869 -4.00752 -3.63339 -0.76763 0.784575 0.315418 -0.0211879 0.568207 0.0342865 1.65043 1.57386\n",
      " 385 6.393e+00 7.364e+05 4.355e+01 -- 2.417e+02 -- 0.134399 -0.385404 -1.5086 -1.84755 -2.37516 -2.93833 -4.01279 -3.63358 -0.756411 0.778329 0.313579 -0.0196636 0.5681 0.0330514 1.62964 1.57277\n",
      " 387 6.586e+00 2.759e+05 6.486e+01 -- 3.066e+02 -- 0.116998 -0.394901 -1.50618 -1.84965 -2.37527 -2.93545 -4.04221 -3.6351 -0.661407 0.711541 0.301895 -0.00709193 0.567185 0.023737 1.46306 1.56458\n",
      " 389 8.793e-01 6.706e+03 1.268e+01 -- 3.192e+02 -- 0.115989 -0.400915 -1.50697 -1.8488 -2.37519 -2.93697 -4.03138 -3.63433 -0.618922 0.64982 0.305913 -0.0117627 0.567838 0.0280683 1.55938 1.56838\n",
      " 391 8.721e-01 1.576e+04 4.935e+00 -- 3.242e+02 -- 0.112264 -0.405631 -1.5073 -1.84862 -2.37517 -2.93742 -4.02343 -3.63415 -0.565235 0.59268 0.305403 -0.0120062 0.568 0.0294253 1.57977 1.56959\n",
      " 393 8.609e-01 2.268e+04 2.879e+00 -- 3.271e+02 -- 0.110008 -0.408683 -1.50757 -1.84848 -2.37515 -2.93776 -4.01681 -3.63402 -0.51694 0.540991 0.304308 -0.0120189 0.568108 0.0304757 1.59266 1.57052\n",
      " 395 8.448e-01 2.811e+04 1.940e+00 -- 3.290e+02 -- 0.108886 -0.410427 -1.50779 -1.8484 -2.37513 -2.938 -4.01122 -3.63393 -0.473875 0.494416 0.302852 -0.011813 0.568178 0.0312724 1.60029 1.57123\n",
      " 397 8.241e-01 3.293e+04 1.442e+00 -- 3.304e+02 -- 0.108628 -0.411163 -1.50798 -1.84834 -2.37512 -2.93818 -4.00644 -3.63387 -0.435812 0.452647 0.30122 -0.0114726 0.568224 0.0318892 1.60467 1.57177\n",
      " 399 7.993e-01 3.764e+04 1.149e+00 -- 3.316e+02 -- 0.108995 -0.411144 -1.50813 -1.84831 -2.37512 -2.93832 -4.00231 -3.63383 -0.402379 0.415346 0.299533 -0.0110612 0.568256 0.0323797 1.60708 1.5722\n",
      " 401 7.711e-01 4.253e+04 9.635e-01 -- 3.325e+02 -- 0.109791 -0.410578 -1.50827 -1.84829 -2.37511 -2.93843 -3.99871 -3.6338 -0.37314 0.382148 0.297866 -0.01062 0.568277 0.0327796 1.60828 1.57255\n",
      " 403 7.403e-01 4.778e+04 8.370e-01 -- 3.334e+02 -- 0.110862 -0.409634 -1.50838 -1.84828 -2.3751 -2.93852 -3.99556 -3.63378 -0.347639 0.35268 0.296263 -0.0101744 0.568292 0.0331127 1.60875 1.57284\n",
      " 405 7.072e-01 5.351e+04 7.456e-01 -- 3.341e+02 -- 0.11209 -0.408441 -1.50848 -1.84827 -2.3751 -2.93859 -3.9928 -3.63377 -0.325436 0.326572 0.29475 -0.00973915 0.568303 0.0333948 1.60877 1.57308\n",
      " 407 6.726e-01 5.984e+04 6.759e-01 -- 3.348e+02 -- 0.11339 -0.407097 -1.50857 -1.84826 -2.3751 -2.93866 -3.99036 -3.63375 -0.306122 0.303476 0.29334 -0.00932269 0.568311 0.0336367 1.60852 1.57328\n",
      " 409 6.368e-01 6.686e+04 6.201e-01 -- 3.354e+02 -- 0.114702 -0.405678 -1.50865 -1.84826 -2.37509 -2.93871 -3.98821 -3.63374 -0.289327 0.283064 0.292038 -0.00892928 0.568317 0.033846 1.60811 1.57346\n",
      " 411 6.003e-01 7.469e+04 5.735e-01 -- 3.360e+02 -- 0.115982 -0.404238 -1.50873 -1.84826 -2.37509 -2.93876 -3.98632 -3.63374 -0.274719 0.265039 0.290845 -0.00856069 0.568322 0.0340282 1.60761 1.57361\n",
      " 413 5.635e-01 8.343e+04 5.332e-01 -- 3.365e+02 -- 0.117205 -0.402814 -1.50879 -1.84826 -2.37509 -2.9388 -3.98465 -3.63373 -0.262009 0.249128 0.289757 -0.0082171 0.568325 0.0341871 1.60706 1.57375\n",
      " 415 5.268e-01 9.320e+04 4.976e-01 -- 3.370e+02 -- 0.118353 -0.401435 -1.50885 -1.84826 -2.37509 -2.93884 -3.98317 -3.63373 -0.25094 0.235089 0.288769 -0.00789773 0.568328 0.034326 1.60648 1.57386\n",
      " 417 4.906e-01 1.041e+05 4.652e-01 -- 3.375e+02 -- 0.119416 -0.400117 -1.5089 -1.84826 -2.37508 -2.93887 -3.98187 -3.63372 -0.241292 0.222703 0.287874 -0.00760125 0.56833 0.0344471 1.60589 1.57396\n",
      " 419 4.551e-01 1.164e+05 4.356e-01 -- 3.379e+02 -- 0.120392 -0.398872 -1.50895 -1.84826 -2.37508 -2.93889 -3.98073 -3.63372 -0.23287 0.211778 0.287065 -0.00732599 0.568331 0.0345524 1.6053 1.57405\n",
      " 421 4.207e-01 1.301e+05 4.080e-01 -- 3.383e+02 -- 0.12128 -0.397707 -1.50899 -1.84826 -2.37508 -2.93892 -3.97972 -3.63372 -0.225507 0.202139 0.286336 -0.00707017 0.568332 0.0346434 1.6047 1.57413\n",
      " 423 3.877e-01 1.454e+05 3.822e-01 -- 3.387e+02 -- 0.122083 -0.396622 -1.50902 -1.84826 -2.37508 -2.93894 -3.97883 -3.63372 -0.219056 0.193634 0.285679 -0.00683198 0.568332 0.0347216 1.6041 1.57419\n",
      " 425 3.562e-01 1.626e+05 3.580e-01 -- 3.391e+02 -- 0.122806 -0.39562 -1.50906 -1.84827 -2.37508 -2.93895 -3.97805 -3.63372 -0.213392 0.186128 0.285086 -0.0066097 0.568332 0.034788 1.60349 1.57425\n",
      " 427 3.264e-01 1.818e+05 3.352e-01 -- 3.394e+02 -- 0.123454 -0.394697 -1.50909 -1.84827 -2.37508 -2.93897 -3.97737 -3.63372 -0.208405 0.179498 0.284553 -0.00640172 0.568331 0.0348437 1.60289 1.57429\n",
      " 429 2.984e-01 2.032e+05 3.137e-01 -- 3.397e+02 -- 0.124033 -0.39385 -1.50911 -1.84827 -2.37508 -2.93898 -3.97677 -3.63372 -0.204002 0.173639 0.284072 -0.0062066 0.56833 0.0348898 1.60227 1.57433\n",
      " 431 2.872e-01 2.272e+05 2.934e-01 -- 3.400e+02 -- 0.124549 -0.393077 -1.50913 -1.84828 -2.37508 -2.93899 -3.97624 -3.63372 -0.200103 0.168457 0.283638 -0.00602309 0.568329 0.034927 1.60166 1.57436\n",
      " 433 2.792e-01 2.540e+05 2.744e-01 -- 3.403e+02 -- 0.125009 -0.392371 -1.50915 -1.84828 -2.37508 -2.939 -3.97578 -3.63372 -0.196637 0.163868 0.283246 -0.00585012 0.568328 0.0349564 1.60104 1.57439\n",
      " 435 2.715e-01 2.839e+05 2.565e-01 -- 3.406e+02 -- 0.125417 -0.39173 -1.50917 -1.84828 -2.37508 -2.939 -3.97538 -3.63372 -0.193545 0.159801 0.282892 -0.00568681 0.568326 0.0349787 1.60041 1.57441\n",
      " 437 2.639e-01 3.173e+05 2.396e-01 -- 3.408e+02 -- 0.12578 -0.391148 -1.50919 -1.84829 -2.37508 -2.939 -3.97503 -3.63373 -0.190778 0.156191 0.282571 -0.00553244 0.568324 0.0349948 1.59979 1.57442\n",
      " 439 2.564e-01 3.545e+05 2.239e-01 -- 3.410e+02 -- 0.126102 -0.390621 -1.5092 -1.84829 -2.37508 -2.93901 -3.97472 -3.63373 -0.188292 0.152983 0.282281 -0.00538642 0.568322 0.0350054 1.59916 1.57443\n",
      " 441 2.488e-01 3.960e+05 2.092e-01 -- 3.412e+02 -- 0.126388 -0.390144 -1.50921 -1.8483 -2.37508 -2.93901 -3.97446 -3.63373 -0.186054 0.150128 0.282017 -0.00524832 0.56832 0.0350114 1.59854 1.57443\n",
      " 443 2.409e-01 4.422e+05 1.954e-01 -- 3.414e+02 -- 0.126643 -0.389713 -1.50922 -1.84831 -2.37508 -2.93901 -3.97422 -3.63373 -0.18403 0.147582 0.281778 -0.00511776 0.568317 0.0350133 1.59793 1.57443\n",
      " 445 2.327e-01 4.937e+05 1.827e-01 -- 3.416e+02 -- 0.126869 -0.389324 -1.50923 -1.84831 -2.37508 -2.93901 -3.97402 -3.63374 -0.182195 0.14531 0.281562 -0.00499447 0.568315 0.0350119 1.59733 1.57443\n",
      " 447 2.243e-01 5.511e+05 1.709e-01 -- 3.418e+02 -- 0.12707 -0.388974 -1.50923 -1.84832 -2.37508 -2.93901 -3.97384 -3.63374 -0.18053 0.143277 0.281365 -0.00487824 0.568313 0.0350078 1.59674 1.57443\n",
      " 449 2.155e-01 6.150e+05 1.600e-01 -- 3.419e+02 -- 0.127249 -0.388658 -1.50924 -1.84833 -2.37508 -2.939 -3.97369 -3.63374 -0.179014 0.141458 0.281186 -0.00476884 0.56831 0.0350015 1.59617 1.57442\n",
      " 451 2.064e-01 6.861e+05 1.499e-01 -- 3.421e+02 -- 0.127409 -0.388373 -1.50924 -1.84833 -2.37508 -2.939 -3.97356 -3.63375 -0.177636 0.139827 0.281023 -0.00466608 0.568308 0.0349935 1.59562 1.57441\n",
      " 453 1.969e-01 7.653e+05 1.407e-01 -- 3.422e+02 -- 0.127551 -0.388118 -1.50925 -1.84834 -2.37508 -2.939 -3.97344 -3.63375 -0.176375 0.138362 0.280875 -0.00456977 0.568305 0.0349843 1.59509 1.5744\n",
      " 455 1.874e-01 8.534e+05 1.322e-01 -- 3.424e+02 -- 0.127678 -0.387888 -1.50925 -1.84835 -2.37508 -2.939 -3.97334 -3.63375 -0.175226 0.137048 0.280741 -0.00447979 0.568303 0.0349741 1.59459 1.57439\n",
      " 457 1.775e-01 9.514e+05 1.245e-01 -- 3.425e+02 -- 0.127792 -0.387681 -1.50925 -1.84835 -2.37508 -2.93899 -3.97325 -3.63376 -0.174176 0.135866 0.28062 -0.00439585 0.568301 0.0349634 1.59411 1.57438\n",
      " 459 1.678e-01 1.060e+06 1.174e-01 -- 3.426e+02 -- 0.127894 -0.387495 -1.50926 -1.84836 -2.37508 -2.93899 -3.97317 -3.63376 -0.17322 0.134805 0.280509 -0.0043178 0.568299 0.0349524 1.59365 1.57437\n",
      " 461 1.581e-01 1.182e+06 1.110e-01 -- 3.427e+02 -- 0.127985 -0.387328 -1.50926 -1.84836 -2.37508 -2.93899 -3.9731 -3.63376 -0.172347 0.13385 0.280409 -0.00424533 0.568297 0.0349413 1.59322 1.57436\n",
      " 463 1.484e-01 1.317e+06 1.052e-01 -- 3.428e+02 -- 0.128066 -0.387178 -1.50926 -1.84837 -2.37508 -2.93898 -3.97304 -3.63376 -0.171549 0.132987 0.280318 -0.0041782 0.568295 0.0349303 1.59282 1.57435\n",
      " 465 1.387e-01 1.467e+06 9.997e-02 -- 3.429e+02 -- 0.128139 -0.387043 -1.50926 -1.84837 -2.37508 -2.93898 -3.97299 -3.63377 -0.170819 0.132211 0.280236 -0.00411621 0.568293 0.0349196 1.59244 1.57434\n",
      " 467 1.295e-01 1.634e+06 9.520e-02 -- 3.430e+02 -- 0.128204 -0.386922 -1.50926 -1.84838 -2.37508 -2.93898 -3.97295 -3.63377 -0.170155 0.131513 0.280162 -0.0040591 0.568292 0.0349092 1.59209 1.57433\n",
      " 469 1.206e-01 1.820e+06 9.088e-02 -- 3.431e+02 -- 0.128263 -0.386813 -1.50926 -1.84838 -2.37508 -2.93898 -3.97291 -3.63377 -0.169555 0.130886 0.280094 -0.00400655 0.56829 0.0348992 1.59177 1.57432\n",
      " 471 1.118e-01 2.026e+06 8.702e-02 -- 3.432e+02 -- 0.128316 -0.386716 -1.50926 -1.84839 -2.37508 -2.93897 -3.97287 -3.63377 -0.169004 0.130321 0.280033 -0.00395823 0.568289 0.0348897 1.59147 1.57431\n",
      " 473 1.033e-01 2.256e+06 8.358e-02 -- 3.433e+02 -- 0.128363 -0.386628 -1.50926 -1.84839 -2.37508 -2.93897 -3.97284 -3.63377 -0.168497 0.129809 0.279978 -0.00391395 0.568287 0.0348807 1.59119 1.57431\n",
      " 475 9.579e-02 2.511e+06 8.038e-02 -- 3.433e+02 -- 0.128405 -0.386549 -1.50926 -1.84839 -2.37508 -2.93897 -3.97282 -3.63378 -0.168047 0.129353 0.279928 -0.00387351 0.568286 0.0348723 1.59093 1.5743\n",
      " 477 8.818e-02 2.794e+06 7.758e-02 -- 3.434e+02 -- 0.128443 -0.386478 -1.50926 -1.8484 -2.37508 -2.93897 -3.97279 -3.63378 -0.167639 0.128938 0.279883 -0.00383641 0.568285 0.0348643 1.59069 1.57429\n",
      " 479 8.091e-02 3.109e+06 7.509e-02 -- 3.435e+02 -- 0.128478 -0.386415 -1.50926 -1.8484 -2.37508 -2.93896 -3.97277 -3.63378 -0.167267 0.128559 0.279842 -0.00380258 0.568284 0.0348569 1.59048 1.57428\n",
      " 481 7.424e-02 3.460e+06 7.280e-02 -- 3.436e+02 -- 0.128509 -0.386357 -1.50926 -1.8484 -2.37508 -2.93896 -3.97275 -3.63378 -0.166936 0.128218 0.279805 -0.00377181 0.568283 0.0348501 1.59028 1.57428\n",
      " 483 6.806e-02 3.849e+06 7.073e-02 -- 3.436e+02 -- 0.128537 -0.386306 -1.50926 -1.84841 -2.37508 -2.93896 -3.97274 -3.63378 -0.166628 0.127921 0.279772 -0.00374381 0.568282 0.0348438 1.5901 1.57427\n",
      " 485 6.227e-02 4.282e+06 6.891e-02 -- 3.437e+02 -- 0.128562 -0.38626 -1.50926 -1.84841 -2.37508 -2.93896 -3.97272 -3.63378 -0.166346 0.127652 0.279742 -0.00371833 0.568281 0.034838 1.58993 1.57426\n",
      " 487 5.690e-02 4.762e+06 6.723e-02 -- 3.438e+02 -- 0.128585 -0.386219 -1.50926 -1.84841 -2.37508 -2.93896 -3.97271 -3.63378 -0.166098 0.127408 0.279715 -0.00369517 0.56828 0.0348326 1.58978 1.57426\n",
      " 489 5.246e-02 5.297e+06 6.572e-02 -- 3.438e+02 -- 0.128605 -0.386181 -1.50926 -1.84841 -2.37508 -2.93896 -3.9727 -3.63378 -0.165881 0.127186 0.27969 -0.00367415 0.56828 0.0348277 1.58964 1.57426\n",
      " 491 4.668e-02 5.891e+06 6.451e-02 -- 3.439e+02 -- 0.128623 -0.386148 -1.50926 -1.84841 -2.37508 -2.93895 -3.97269 -3.63378 -0.165662 0.126983 0.279668 -0.00365488 0.568279 0.0348231 1.58952 1.57425\n",
      " 493 4.336e-02 6.551e+06 6.330e-02 -- 3.440e+02 -- 0.12864 -0.386118 -1.50927 -1.84842 -2.37508 -2.93895 -3.97268 -3.63379 -0.165486 0.126802 0.279649 -0.00363782 0.568279 0.0348191 1.58941 1.57425\n",
      " 495 3.896e-02 7.284e+06 6.215e-02 -- 3.440e+02 -- 0.128655 -0.386091 -1.50927 -1.84842 -2.37508 -2.93895 -3.97267 -3.63379 -0.165321 0.12665 0.279631 -0.00362204 0.568278 0.0348153 1.5893 1.57424\n",
      " 497 3.577e-02 8.098e+06 6.116e-02 -- 3.441e+02 -- 0.128668 -0.386067 -1.50927 -1.84842 -2.37508 -2.93895 -3.97266 -3.63379 -0.165157 0.126529 0.279614 -0.00360793 0.568278 0.0348118 1.58921 1.57424\n",
      " 499 3.106e-02 9.005e+06 6.042e-02 -- 3.442e+02 -- 0.12868 -0.386045 -1.50927 -1.84842 -2.37508 -2.93895 -3.97266 -3.63379 -0.164994 0.126396 0.2796 -0.00359503 0.568277 0.0348086 1.58912 1.57424\n",
      "********************\n",
      "0.128691 -0.386025 -1.50927 -1.84842 -2.37508 -2.93895 -3.97265 -3.63379 -0.164908 0.12629 0.279587 -0.00358386 0.568277 0.034806 1.58905 1.57423\n",
      "0.00126105 0.000998709 0.00018594 0.000356512 2.30678e-05 0.000253636 0.00869718 0.000210956 0.0200512 0.0186844 0.00479074 0.00354031 0.000510855 0.00183101 0.0188838 0.0015161\n",
      "-10903 199.23 -2.70075 -1.73798 -1.01372 0.00748608 0.0139392 -0.0830399 -358.669 233.027 -1.33222 -0.312077 -0.267079 -0.122273 0.0137976 -0.0193582\n",
      "********************\n"
     ]
    }
   ],
   "source": [
    "Cx = clag.clag('cxd10r', [[t1,t2]], [[l1,l2]], [[l1e,l2e]], dt, fqL, p1, p2)\n",
    "p  = np.concatenate( ((p1+p2)*0.5-0.3,p1*0+0.1) ) # a  good starting point generally\n",
    "p, pe = clag.optimize(Cx, p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "phi, phie = p[nfq:], pe[nfq:]\n",
    "lag, lage = phi/(2*np.pi*fqd), phie/(2*np.pi*fqd)    \n",
    "cx, cxe   = p[:nfq], pe[:nfq]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 3 artists>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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OXDVtZmYmMzMzheUCQP+Yn5/P/Pz8VdMuX77c0de8qc3re/XW43r+Pclndpn+2iTPpjo6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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f676b953610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "xscale('log'); ylim(-10,10)\n",
    "errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color=\"black\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.095117985155199827, 1.1056585227168947)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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85aiKnQhsBH4K/B/g7WWtRtXua8D/A75a7kJUtS4ABoCfAe8tcy2xmQHMGXl/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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f676881b110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s, loc, scale = lognorm.fit(lag,loc=.01)\n",
    "xscale('log'); ylim(-4,1.5)\n",
    "errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color=\"black\")\n",
    "#plot(fqd,norm.pdf(fqd,mu,sigma))\n",
    "plot(fqd,lognorm.pdf(fqd,s,loc,scale))\n",
    "mu,sigma\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python2.7/dist-packages/numpy/core/numeric.py:460: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return array(a, dtype, copy=False, order=order)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f676847e7d0>]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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/v6WsG/bv35+UlJR9zmVkZJCRkRGFMqIvOdk6RE6YAOPG2U6YIiIiXsnJySEnJ2efc/n5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\nRERERERERERERERi5/8B5ExnbdanXmMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f6768614950>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(ifft(lag))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}