phy-4660/lag/data/clag_analysis-origbins-noLFerrors-1928A.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Container object of 3 artists>"
      ]
     },
     "execution_count": 17,
     "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 0x7f9bcc1230d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import sys\n",
    "import getopt\n",
    "sys.path.insert(1,\"/usr/local/science/clag/\")\n",
    "import clag\n",
    "%pylab inline\n",
    "\n",
    "from scipy.stats import norm\n",
    "from scipy.stats import lognorm\n",
    "\n",
    "ref_file=\"lc/1367A.lc\"\n",
    "echo_file=\"lc/1928A.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 0x7f9be77ed850>"
      ]
     },
     "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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AHXkdWZ9jlekUPGQB7xmVg7Gd/4Yhry+P6r+NrhLeeD4jMAMo10qfH+0DAQcw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\nyQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9bcfa46f50>"
      ]
     },
     "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 4.344e-01 7.393e+01 inf -- -3.944e+02 -- 1 1 1 1 1 1 1 1\n",
      "   2 7.685e-01 7.351e+01 8.622e+01 -- -3.082e+02 -- 0.624092 0.584331 0.567607 0.567004 0.567011 0.567373 0.565602 0.572165\n",
      "   3 3.322e+00 7.320e+01 8.468e+01 -- -2.235e+02 -- 0.335696 0.192847 0.135867 0.134225 0.133328 0.135054 0.130916 0.142995\n",
      "   4 1.578e+00 7.233e+01 8.258e+01 -- -1.409e+02 -- 0.188517 -0.142584 -0.293749 -0.297289 -0.300771 -0.296754 -0.30398 -0.289444\n",
      "   5 6.020e-01 7.051e+01 7.959e+01 -- -6.131e+01 -- 0.148668 -0.367563 -0.714785 -0.72349 -0.733746 -0.726833 -0.738389 -0.724505\n",
      "   6 3.768e-01 6.774e+01 7.540e+01 -- 1.409e+01 -- 0.144731 -0.462001 -1.10711 -1.13381 -1.16285 -1.15289 -1.1711 -1.16069\n",
      "   7 2.756e-01 6.360e+01 6.924e+01 -- 8.333e+01 -- 0.174356 -0.494567 -1.42737 -1.5044 -1.58181 -1.57067 -1.60086 -1.59803\n",
      "   8 2.179e-01 5.635e+01 5.976e+01 -- 1.431e+02 -- 0.217323 -0.511297 -1.61338 -1.7878 -1.97301 -1.97114 -2.02736 -2.03849\n",
      "   9 1.801e-01 4.421e+01 4.621e+01 -- 1.893e+02 -- 0.246071 -0.522108 -1.67034 -1.93112 -2.29163 -2.33219 -2.45077 -2.48259\n",
      "  10 1.570e-01 2.842e+01 3.021e+01 -- 2.195e+02 -- 0.26181 -0.527692 -1.69937 -1.95215 -2.46868 -2.6103 -2.87208 -2.92966\n",
      "  11 1.534e-01 1.394e+01 1.638e+01 -- 2.359e+02 -- 0.270025 -0.532175 -1.71636 -1.93588 -2.49871 -2.76037 -3.29811 -3.38966\n",
      "  12 1.967e-01 4.790e+00 7.494e+00 -- 2.434e+02 -- 0.270795 -0.536861 -1.72096 -1.92459 -2.47931 -2.79803 -3.75141 -3.90973\n",
      "  13 5.458e-01 9.532e-01 2.865e+00 -- 2.462e+02 -- 0.26859 -0.539948 -1.7231 -1.91925 -2.46297 -2.79554 -4.30331 -4.67867\n",
      "  14 1.056e+02 2.730e-01 7.004e-01 -- 2.469e+02 -- 0.26685 -0.541445 -1.72405 -1.91702 -2.45339 -2.78988 -5.27857 -7.23243\n",
      "  15 5.573e+02 3.423e-01 3.921e-02 -- 2.470e+02 -- 0.266108 -0.541837 -1.72399 -1.91704 -2.44871 -2.78749 -8 -8\n",
      "  16 5.573e+02 3.538e-01 2.319e-04 -- 2.470e+02 -- 0.265884 -0.541836 -1.72403 -1.91735 -2.44747 -2.78719 -8 -8\n",
      "  17 5.573e+02 3.544e-01 3.124e-05 -- 2.470e+02 -- 0.265818 -0.541848 -1.72407 -1.91742 -2.44724 -2.78718 -8 -8\n",
      "********************\n",
      "0.265818 -0.541848 -1.72407 -1.91742 -2.44724 -2.78718 -8 -8\n",
      "0.236518 0.210143 0.256686 0.193866 0.180651 0.167701 4558.58 3532.49\n",
      "-0.003073 -0.00781145 -0.023497 -0.0612628 -0.14201 -0.354433 -0.000171646 -0.000375339\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",
      "+++ 2.470e+02 2.466e+02 2.658e-01 5.023e-01 0.855 +++\n",
      "+++ 2.470e+02 2.461e+02 2.658e-01 6.206e-01 1.8 +++\n",
      "+++ 2.470e+02 2.463e+02 2.658e-01 5.615e-01 1.29 +++\n",
      "+++ 2.470e+02 2.465e+02 2.658e-01 5.319e-01 1.06 +++\n",
      "+++ 2.470e+02 2.465e+02 2.658e-01 5.171e-01 0.957 +++\n",
      "+++ 2.470e+02 2.465e+02 2.658e-01 5.245e-01 1.01 +++\n",
      "+++ 2.470e+02 2.465e+02 2.658e-01 5.208e-01 0.983 +++\n",
      "+++ 2.470e+02 2.465e+02 2.658e-01 5.226e-01 0.997 +++\n",
      "\t### errors for param 1 ###\n",
      "+++ 2.470e+02 2.465e+02 -5.419e-01 -3.317e-01 0.963 +++\n",
      "+++ 2.470e+02 2.460e+02 -5.419e-01 -2.266e-01 2.03 +++\n",
      "+++ 2.470e+02 2.463e+02 -5.419e-01 -2.792e-01 1.46 +++\n",
      "+++ 2.470e+02 2.464e+02 -5.419e-01 -3.054e-01 1.2 +++\n",
      "+++ 2.470e+02 2.464e+02 -5.419e-01 -3.186e-01 1.08 +++\n",
      "+++ 2.470e+02 2.465e+02 -5.419e-01 -3.251e-01 1.02 +++\n",
      "+++ 2.470e+02 2.465e+02 -5.419e-01 -3.284e-01 0.991 +++\n",
      "\t### errors for param 2 ###\n",
      "+++ 2.470e+02 2.468e+02 -1.724e+00 -1.596e+00 0.302 +++\n",
      "+++ 2.470e+02 2.467e+02 -1.724e+00 -1.532e+00 0.653 +++\n",
      "+++ 2.470e+02 2.466e+02 -1.724e+00 -1.499e+00 0.873 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.724e+00 -1.483e+00 0.993 +++\n",
      "\t### errors for param 3 ###\n",
      "+++ 2.470e+02 2.465e+02 -1.917e+00 -1.724e+00 0.929 +++\n",
      "+++ 2.470e+02 2.460e+02 -1.917e+00 -1.627e+00 1.98 +++\n",
      "+++ 2.470e+02 2.463e+02 -1.917e+00 -1.675e+00 1.41 +++\n",
      "+++ 2.470e+02 2.464e+02 -1.917e+00 -1.699e+00 1.16 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.917e+00 -1.711e+00 1.04 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.917e+00 -1.718e+00 0.984 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.917e+00 -1.714e+00 1.01 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.917e+00 -1.716e+00 0.998 +++\n",
      "\t### errors for param 4 ###\n",
      "+++ 2.470e+02 2.466e+02 -2.447e+00 -2.267e+00 0.864 +++\n",
      "+++ 2.470e+02 2.460e+02 -2.447e+00 -2.176e+00 1.9 +++\n",
      "+++ 2.470e+02 2.463e+02 -2.447e+00 -2.221e+00 1.33 +++\n",
      "+++ 2.470e+02 2.464e+02 -2.447e+00 -2.244e+00 1.09 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.447e+00 -2.255e+00 0.972 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.447e+00 -2.250e+00 1.03 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.447e+00 -2.252e+00   1 +++\n",
      "\t### errors for param 5 ###\n",
      "+++ 2.470e+02 2.468e+02 -2.787e+00 -2.703e+00 0.292 +++\n",
      "+++ 2.470e+02 2.467e+02 -2.787e+00 -2.661e+00 0.614 +++\n",
      "+++ 2.470e+02 2.466e+02 -2.787e+00 -2.640e+00 0.82 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.787e+00 -2.630e+00 0.934 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.787e+00 -2.625e+00 0.993 +++\n",
      "\t### errors for param 6 ###\n",
      "+++ 2.470e+02 2.470e+02 -8.000e+00 -6.000e+00 0.0115 +++\n",
      "+++ 2.470e+02 2.469e+02 -8.000e+00 -5.000e+00 0.147 +++\n",
      "+++ 2.470e+02 2.467e+02 -8.000e+00 -4.500e+00 0.484 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.250e+00 0.884 +++\n",
      "+++ 2.470e+02 2.464e+02 -8.000e+00 -4.125e+00 1.2 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.188e+00 1.03 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.219e+00 0.954 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.203e+00 0.991 +++\n",
      "\t### errors for param 7 ###\n",
      "+++ 2.470e+02 2.470e+02 -8.000e+00 -6.000e+00 0.0294 +++\n",
      "+++ 2.470e+02 2.468e+02 -8.000e+00 -5.000e+00 0.323 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.500e+00 1.03 +++\n",
      "+++ 2.470e+02 2.467e+02 -8.000e+00 -4.750e+00 0.579 +++\n",
      "+++ 2.470e+02 2.466e+02 -8.000e+00 -4.625e+00 0.774 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.562e+00 0.894 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.531e+00 0.962 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.516e+00 0.997 +++\n",
      "********************\n",
      "0.265804 -0.541852 -1.72407 -1.91743 -2.44719 -2.78718 -8 -8\n",
      "0.256844 0.213426 0.240643 0.20144 0.19476 0.162461 2 3.48438\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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g1P7A8QHmXjWXddvWMWXyFABSN6RILUjlbbyxFJZqfaY1b+NLxWZIkFQ2UgvyGwIu5CeF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\nSZIkSZIkSZIkSZIklYH/DxLfa082qjO6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9bd0153d50>"
      ]
     },
     "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 2.077e+05 1.197e+01 inf -- 3.072e+02 -- -0.0167957 -0.659991 -1.75733 -2.01992 -2.58869 -2.93933 -6.08072 -8.3 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1\n",
      "   3 3.271e+03 1.431e+01 2.187e+00 -- 3.094e+02 -- 0.0139188 -0.616992 -1.71242 -1.98591 -2.55782 -2.91741 -5.78072 -8 0.0404571 0.0959238 0.114705 0.117637 0.0759046 0.11315 2.83682 -2.97794\n",
      "   5 3.402e+03 1.686e+01 2.074e+00 -- 3.115e+02 -- 0.0411101 -0.582169 -1.67612 -1.95765 -2.53188 -2.89876 -6.08072 -8 -0.00584518 0.0932078 0.124735 0.131247 0.0572905 0.124022 1.45283 -3.03469\n",
      "   7 3.420e+03 1.966e+01 1.889e+00 -- 3.134e+02 -- 0.0650135 -0.553404 -1.64618 -1.93385 -2.50984 -2.88274 -5.78072 -8 -0.0424699 0.0913679 0.131869 0.14207 0.0426621 0.133189 -0.940465 1.19045\n",
      "   9 2.868e+03 2.272e+01 1.819e+00 -- 3.152e+02 -- 0.0859844 -0.529292 -1.62113 -1.91359 -2.49094 -2.8689 -6.08072 -7.7 -0.0718915 0.0901134 0.137101 0.15086 0.0309294 0.141054 0.754261 2.5184\n",
      "  11 5.181e+03 2.608e+01 1.679e+00 -- 3.169e+02 -- 0.104393 -0.508851 -1.59992 -1.8962 -2.4746 -2.85689 -5.78072 -8 -0.0958425 0.0892713 0.140997 0.158143 0.021406 0.147907 -0.44842 2.70944\n",
      "  13 4.148e+04 2.974e+01 1.637e+00 -- 3.185e+02 -- 0.120579 -0.491366 -1.5818 -1.88115 -2.46039 -2.84641 -5.48072 -8 -0.115571 0.088729 0.14396 0.164245 0.0136007 0.153954 1.68591 0.219106\n",
      "  15 1.364e+03 3.373e+01 1.423e+00 -- 3.199e+02 -- 0.134842 -0.476304 -1.56621 -1.86807 -2.44792 -2.83724 -5.18072 -7.7 -0.131975 0.0884089 0.146209 0.169436 0.00715737 0.159354 2.77837 -1.88001\n",
      "  17 3.384e+03 3.807e+01 1.457e+00 -- 3.214e+02 -- 0.147438 -0.463252 -1.55271 -1.85663 -2.43694 -2.82923 -5.48072 -8 -0.145729 0.088245 0.147942 0.173866 0.00170694 0.164237 -0.858069 -3.03191\n",
      "  19 5.448e+03 4.279e+01 1.401e+00 -- 3.228e+02 -- 0.15859 -0.451883 -1.54097 -1.84658 -2.42726 -2.82213 -5.78072 -8 -0.157362 0.0882266 0.149341 0.177654 -0.00272343 0.168668 0.243127 1.49491\n",
      "  21 5.570e+02 4.789e+01 1.208e+00 -- 3.240e+02 -- 0.168487 -0.441941 -1.53072 -1.83772 -2.41866 -2.81587 -5.48072 -7.7 -0.167244 0.0883118 0.150432 0.180941 -0.00638645 0.172731 -2.75775 -2.43488\n",
      "  23 5.770e+04 5.341e+01 1.297e+00 -- 3.253e+02 -- 0.177287 -0.433218 -1.52174 -1.82988 -2.411 -2.81036 -5.78072 -8 -0.175683 0.0884674 0.151298 0.18378 -0.00950607 0.176491 -0.399562 0.166824\n",
      "  25 2.578e+03 5.934e+01 1.208e+00 -- 3.265e+02 -- 0.185129 -0.42554 -1.51385 -1.82293 -2.40415 -2.80545 -5.48072 -7.7 -0.182926 0.0886974 0.152004 0.18625 -0.0120039 0.179977 1.74647 1.42211\n",
      "  27 4.862e+03 6.571e+01 1.069e+00 -- 3.276e+02 -- 0.192131 -0.418765 -1.5069 -1.81673 -2.39801 -2.8011 -5.18072 -7.4 -0.189156 0.0889782 0.152558 0.188415 -0.0140412 0.18323 2.48031 -0.745704\n",
      "  29 9.405e+02 7.253e+01 9.711e-01 -- 3.285e+02 -- 0.198393 -0.412774 -1.50077 -1.81121 -2.39247 -2.79726 -5.17938 -7.7 -0.19453 0.0892935 0.153002 0.190299 -0.0157421 0.186287 -1.33712 -2.59349\n",
      "  31 6.968e+03 7.979e+01 1.152e+00 -- 3.297e+02 -- 0.204002 -0.407466 -1.49534 -1.80628 -2.38752 -2.79383 -5.47938 -8 -0.199199 0.0896459 0.15344 0.191883 -0.0170844 0.18917 1.57648 -1.46962\n",
      "  33 5.064e+03 8.750e+01 8.071e-01 -- 3.305e+02 -- 0.209036 -0.402755 -1.49055 -1.80185 -2.38303 -2.79076 -5.17938 -8 -0.203237 0.0900308 0.153771 0.193301 -0.0180605 0.19188 -2.99641 -1.64369\n",
      "  35 4.661e+03 9.564e+01 1.077e+00 -- 3.316e+02 -- 0.213558 -0.398567 -1.48629 -1.79787 -2.37897 -2.78807 -5.47938 -8 -0.206743 0.0904245 0.154068 0.194501 -0.0188992 0.194463 0.599717 1.32447\n",
      "  37 2.185e+04 1.042e+02 7.254e-01 -- 3.323e+02 -- 0.217628 -0.394841 -1.48253 -1.7943 -2.3753 -2.7856 -5.17938 -7.7 -0.209797 0.0908529 0.154345 0.195543 -0.0193431 0.196896 3.07347 -0.309744\n",
      "  39 5.370e+02 1.132e+02 9.309e-01 -- 3.332e+02 -- 0.221294 -0.391521 -1.47918 -1.79107 -2.37197 -2.78346 -5.47938 -7.4 -0.212449 0.0912809 0.154587 0.196421 -0.0197202 0.199223 -0.122741 -2.19799\n",
      "  41 4.124e+02 1.225e+02 8.464e-01 -- 3.341e+02 -- 0.224602 -0.38856 -1.47621 -1.78815 -2.36895 -2.78149 -5.17938 -7.7 -0.214768 0.0917346 0.154842 0.197156 -0.0197791 0.201426 0.185379 0.875823\n",
      "  43 1.140e+04 1.321e+02 5.576e-01 -- 3.346e+02 -- 0.227588 -0.385917 -1.47357 -1.78551 -2.36621 -2.7797 -4.87938 -7.4 -0.216789 0.0922022 0.155086 0.197771 -0.0196213 0.203517 2.76502 -0.295434\n",
      "  44 1.202e+03 9.319e+03 6.921e+00 -- 3.415e+02 -- 0.25457 -0.362307 -1.45009 -1.76155 -2.34098 -2.76463 -7.3588 -4.4 -0.234221 0.0967125 0.156919 0.202935 -0.0187407 0.223585 -3.03547 0.658572\n",
      "  46 3.348e+03 2.383e+03 2.056e+00 -- 3.436e+02 -- 0.2541 -0.362138 -1.45037 -1.76118 -2.3417 -2.76372 -7.6588 -4.27727 -0.236662 0.0951999 0.162918 0.195741 -0.00804371 0.221694 2.83744 0.887952\n",
      "  48 8.279e+03 1.188e+03 7.339e-01 -- 3.443e+02 -- 0.253984 -0.362098 -1.45055 -1.76083 -2.34195 -2.763 -7.9588 -4.18142 -0.238339 0.0952591 0.166595 0.190819 -0.00170333 0.220894 1.62132 0.948638\n",
      "  50 5.831e+02 7.367e+02 4.678e-01 -- 3.448e+02 -- 0.25397 -0.362096 -1.45068 -1.76047 -2.34209 -2.76245 -7.6588 -4.11058 -0.239676 0.0957548 0.169216 0.186723 0.00306954 0.220363 -2.34059 0.972914\n",
      "  52 1.225e+04 5.114e+02 3.593e-01 -- 3.452e+02 -- 0.254002 -0.36211 -1.45078 -1.76013 -2.34219 -2.76201 -7.9588 -4.05557 -0.240772 0.0964213 0.171173 0.183133 0.00691799 0.219951 -1.3379 0.984989\n",
      "  54 2.908e+03 3.804e+02 2.971e-01 -- 3.455e+02 -- 0.254058 -0.362133 -1.45087 -1.75979 -2.34228 -2.76167 -8 -4.01135 -0.241679 0.0971513 0.172659 0.179917 0.0101243 0.219607 -2.58716 0.991938\n",
      "  56 2.520e+04 2.966e+02 2.554e-01 -- 3.457e+02 -- 0.254126 -0.362159 -1.45094 -1.75946 -2.34236 -2.76142 -8 -3.975 -0.242428 0.0978921 0.17379 0.177 0.012847 0.219308 -0.893281 0.996473\n",
      "  58 1.393e+04 2.392e+02 2.239e-01 -- 3.459e+02 -- 0.2542 -0.362187 -1.451 -1.75914 -2.34244 -2.76123 -8 -3.94463 -0.243046 0.098616 0.174644 0.174336 0.0151899 0.219038 0.548158 0.999814\n",
      "  60 8.788e+02 1.978e+02 1.977e-01 -- 3.461e+02 -- 0.254275 -0.362215 -1.45106 -1.75884 -2.34252 -2.7611 -7.7 -3.919 -0.243552 0.0993077 0.175277 0.171891 0.0172264 0.218788 -2.44331 1.00258\n",
      "  62 8.149e+03 1.668e+02 1.772e-01 -- 3.463e+02 -- 0.25435 -0.362242 -1.45111 -1.75855 -2.34259 -2.76101 -8 -3.89719 -0.243965 0.0999593 0.175731 0.169641 0.019011 0.218552 2.73951 1.0051\n",
      "  64 3.097e+03 1.429e+02 1.584e-01 -- 3.465e+02 -- 0.254423 -0.362268 -1.45115 -1.75828 -2.34266 -2.76097 -8 -3.87855 -0.244298 0.100567 0.176038 0.167566 0.0205874 0.218325 0.780197 1.00758\n",
      "  66 1.637e+03 1.238e+02 1.410e-01 -- 3.466e+02 -- 0.254493 -0.362292 -1.45119 -1.75803 -2.34273 -2.76096 -7.7 -3.86256 -0.244565 0.10113 0.176223 0.165649 0.02199 0.218102 -2.63332 1.01014\n",
      "  68 1.780e+05 1.083e+02 1.272e-01 -- 3.467e+02 -- 0.254559 -0.362315 -1.45123 -1.75779 -2.34279 -2.76097 -8 -3.84883 -0.244776 0.101648 0.176309 0.163876 0.0232461 0.217881 -0.110744 1.01285\n",
      "  70 2.894e+03 9.543e+01 1.126e-01 -- 3.469e+02 -- 0.254622 -0.362337 -1.45126 -1.75757 -2.34285 -2.761 -7.7 -3.83704 -0.244941 0.102124 0.176311 0.162237 0.0243797 0.217658 -1.79891 1.01576\n",
      "  72 3.221e+03 8.461e+01 1.009e-01 -- 3.470e+02 -- 0.254681 -0.362357 -1.45129 -1.75736 -2.3429 -2.76105 -8 -3.8269 -0.245067 0.102559 0.176245 0.16072 0.025409 0.217434 -2.61948 1.01891\n",
      "  73 3.986e+04 8.840e+04 3.099e+01 -- 3.160e+02 -- 0.255228 -0.362541 -1.45157 -1.75543 -2.3433 -2.76164 -8 -3.73993 -0.246022 0.106522 0.175014 0.146688 0.0348206 0.215163 -1.11659 1.05295\n",
      "  75 8.896e+03 2.717e+02 3.098e+01 -- 3.469e+02 -- 0.254563 -0.362134 -1.45184 -1.757 -2.34298 -2.7592 -8 -3.74513 -0.25066 0.107475 0.155394 0.124168 0.0867597 0.167292 1.40399 1.0852\n",
      "  76 1.040e+01 7.468e+01 5.524e-01 -- 3.475e+02 -- 0.254408 -0.362427 -1.45159 -1.7568 -2.33986 -2.76088 -5 -3.7742 -0.252304 0.108109 0.154003 0.131005 0.0778512 0.176436 2.13841 1.28287\n",
      "  78 1.148e+02 6.144e+01 2.449e-01 -- 3.477e+02 -- 0.254428 -0.362448 -1.45159 -1.75668 -2.33984 -2.7612 -4.7 -3.77154 -0.252011 0.107845 0.155672 0.132885 0.0741505 0.180529 -0.0860208 1.27425\n",
      "  80 5.736e-01 5.603e+01 5.946e-01 -- 3.483e+02 -- 0.254453 -0.362466 -1.4516 -1.75658 -2.33986 -2.76138 -4.45762 -3.76935 -0.251748 0.107647 0.157187 0.134499 0.0710198 0.184185 0.901147 1.267\n",
      "  82 3.050e-01 5.070e+01 6.261e-01 -- 3.490e+02 -- 0.25448 -0.362483 -1.4516 -1.75645 -2.33989 -2.76144 -4.20194 -3.76751 -0.251481 0.107471 0.158475 0.136032 0.0683814 0.187492 0.910107 1.26066\n",
      "  84 2.525e-01 4.649e+01 4.542e-01 -- 3.494e+02 -- 0.254511 -0.362499 -1.45161 -1.75631 -2.33995 -2.76134 -4.07732 -3.76602 -0.251239 0.107333 0.159592 0.137475 0.0662961 0.190508 0.913997 1.25501\n",
      "  86 2.077e-01 4.317e+01 3.787e-01 -- 3.498e+02 -- 0.254544 -0.362513 -1.45163 -1.75617 -2.34003 -2.76113 -3.99339 -3.7648 -0.251017 0.107226 0.160556 0.138816 0.0646219 0.193263 0.917195 1.25003\n",
      "  88 1.690e-01 4.054e+01 3.278e-01 -- 3.501e+02 -- 0.254579 -0.362526 -1.45164 -1.75602 -2.34015 -2.76083 -3.93087 -3.76381 -0.250811 0.107146 0.161384 0.140062 0.0632798 0.195783 0.92011 1.24565\n",
      "  90 1.357e-01 3.844e+01 2.899e-01 -- 3.504e+02 -- 0.254615 -0.362538 -1.45165 -1.75588 -2.34028 -2.76046 -3.88172 -3.76302 -0.25062 0.107088 0.162091 0.141219 0.0622103 0.198094 0.922868 1.24181\n",
      "  92 1.073e-01 3.979e+01 2.602e-01 -- 3.507e+02 -- 0.254653 -0.36255 -1.45167 -1.75573 -2.34044 -2.76004 -3.84172 -3.76239 -0.250443 0.107051 0.16269 0.142294 0.0613659 0.200217 0.925524 1.23844\n",
      "  94 8.910e-02 4.379e+01 2.364e-01 -- 3.509e+02 -- 0.25469 -0.362561 -1.45169 -1.75559 -2.34061 -2.75957 -3.80836 -3.7619 -0.250278 0.10703 0.163195 0.143295 0.0607075 0.202171 0.928104 1.23549\n",
      "  96 8.159e-02 4.824e+01 2.169e-01 -- 3.511e+02 -- 0.254729 -0.362572 -1.4517 -1.75545 -2.34079 -2.75908 -3.78005 -3.76152 -0.250125 0.107023 0.163616 0.144231 0.0602022 0.203972 0.930626 1.23291\n",
      "  98 7.491e-02 5.321e+01 2.009e-01 -- 3.513e+02 -- 0.254767 -0.362582 -1.45172 -1.75531 -2.34099 -2.75856 -3.75567 -3.76124 -0.249983 0.107028 0.163963 0.145106 0.0598227 0.205636 0.933099 1.23064\n",
      " 100 6.896e-02 5.877e+01 1.874e-01 -- 3.515e+02 -- 0.254805 -0.362593 -1.45174 -1.75518 -2.34119 -2.75803 -3.73444 -3.76104 -0.249849 0.107042 0.164245 0.145927 0.0595455 0.207177 0.935528 1.22866\n",
      " 102 6.363e-02 6.501e+01 1.761e-01 -- 3.517e+02 -- 0.254843 -0.362603 -1.45176 -1.75505 -2.3414 -2.75749 -3.71578 -3.76092 -0.249724 0.107065 0.16447 0.1467 0.0593509 0.208605 0.937919 1.22691\n",
      " 104 5.885e-02 7.201e+01 1.664e-01 -- 3.519e+02 -- 0.25488 -0.362613 -1.45178 -1.75493 -2.34162 -2.75695 -3.69927 -3.76085 -0.249607 0.107094 0.164646 0.14743 0.0592217 0.209933 0.940273 1.22537\n",
      " 106 5.455e-02 7.989e+01 1.581e-01 -- 3.520e+02 -- 0.254916 -0.362622 -1.4518 -1.75482 -2.34183 -2.7564 -3.68456 -3.76083 -0.249496 0.107129 0.164779 0.148121 0.0591435 0.211168 0.942591 1.22401\n",
      " 108 5.065e-02 8.875e+01 1.509e-01 -- 3.522e+02 -- 0.254952 -0.362632 -1.45182 -1.75471 -2.34205 -2.75586 -3.67139 -3.76085 -0.24939 0.107168 0.164876 0.148776 0.0591036 0.21232 0.944874 1.22279\n",
      " 110 4.711e-02 9.874e+01 1.446e-01 -- 3.523e+02 -- 0.254988 -0.362641 -1.45184 -1.7546 -2.34226 -2.75533 -3.65956 -3.76091 -0.24929 0.10721 0.16494 0.149401 0.0590914 0.213396 0.947122 1.22169\n",
      " 112 4.386e-02 1.100e+02 1.390e-01 -- 3.524e+02 -- 0.255022 -0.362651 -1.45186 -1.7545 -2.34248 -2.7548 -3.64889 -3.761 -0.249193 0.107255 0.164978 0.149997 0.0590972 0.214401 0.949333 1.22069\n",
      " 114 4.086e-02 1.226e+02 1.340e-01 -- 3.526e+02 -- 0.255056 -0.36266 -1.45188 -1.75441 -2.34269 -2.75428 -3.63925 -3.76111 -0.249101 0.107302 0.164994 0.150567 0.0591131 0.215341 0.951506 1.21977\n",
      " 116 3.807e-02 1.369e+02 1.295e-01 -- 3.527e+02 -- 0.255089 -0.362669 -1.4519 -1.75432 -2.3429 -2.75377 -3.63051 -3.76124 -0.24901 0.10735 0.164992 0.151115 0.0591318 0.216221 0.953639 1.21891\n",
      " 118 3.543e-02 1.529e+02 1.253e-01 -- 3.528e+02 -- 0.255121 -0.362678 -1.45192 -1.75423 -2.3431 -2.75328 -3.62259 -3.76138 -0.248923 0.107399 0.164974 0.151642 0.0591471 0.217044 0.95573 1.21809\n",
      " 120 3.292e-02 1.710e+02 1.213e-01 -- 3.530e+02 -- 0.255152 -0.362687 -1.45193 -1.75415 -2.3433 -2.7528 -3.61541 -3.76153 -0.248837 0.107449 0.164945 0.152149 0.0591535 0.217814 0.957773 1.2173\n",
      " 122 3.110e-02 1.912e+02 1.176e-01 -- 3.531e+02 -- 0.255182 -0.362696 -1.45195 -1.75407 -2.34349 -2.75234 -3.60889 -3.76169 -0.248752 0.1075 0.164908 0.15264 0.0591462 0.218531 0.959768 1.21653\n",
      " 124 3.007e-02 2.139e+02 1.139e-01 -- 3.532e+02 -- 0.255212 -0.362704 -1.45197 -1.754 -2.34368 -2.7519 -3.60297 -3.76186 -0.248668 0.107551 0.164864 0.153114 0.0591207 0.219197 0.961708 1.21577\n",
      " 126 2.912e-02 2.393e+02 1.104e-01 -- 3.533e+02 -- 0.255241 -0.362713 -1.45199 -1.75393 -2.34386 -2.75147 -3.5976 -3.76202 -0.248584 0.107603 0.164817 0.153575 0.0590734 0.219814 0.963589 1.215\n",
      " 128 2.825e-02 2.677e+02 1.069e-01 -- 3.534e+02 -- 0.255269 -0.362721 -1.45201 -1.75387 -2.34404 -2.75106 -3.59275 -3.76219 -0.2485 0.107655 0.164769 0.154022 0.0590009 0.220381 0.965407 1.21423\n",
      " 130 2.746e-02 2.993e+02 1.034e-01 -- 3.535e+02 -- 0.255297 -0.362729 -1.45203 -1.75381 -2.34421 -2.75067 -3.58835 -3.76235 -0.248416 0.107708 0.164721 0.154457 0.0589 0.220898 0.967157 1.21345\n",
      " 132 2.805e-02 3.345e+02 9.997e-02 -- 3.536e+02 -- 0.255324 -0.362737 -1.45205 -1.75375 -2.34437 -2.7503 -3.58439 -3.76251 -0.248331 0.107761 0.164676 0.154881 0.0587683 0.221364 0.968833 1.21265\n",
      " 134 3.410e-02 3.735e+02 9.652e-02 -- 3.537e+02 -- 0.25535 -0.362745 -1.45207 -1.7537 -2.34453 -2.74995 -3.58082 -3.76266 -0.248245 0.107815 0.164635 0.155295 0.0586035 0.221779 0.970432 1.21184\n",
      " 136 4.046e-02 4.168e+02 9.310e-02 -- 3.538e+02 -- 0.255376 -0.362753 -1.45208 -1.75365 -2.34469 -2.74962 -3.57761 -3.7628 -0.248158 0.10787 0.164599 0.1557 0.0584036 0.222141 0.97195 1.211\n",
      " 138 4.708e-02 4.645e+02 8.971e-02 -- 3.539e+02 -- 0.255401 -0.36276 -1.4521 -1.7536 -2.34484 -2.74931 -3.57474 -3.76293 -0.248069 0.107925 0.164571 0.156096 0.0581673 0.222449 0.973382 1.21015\n",
      " 140 5.391e-02 5.172e+02 8.638e-02 -- 3.540e+02 -- 0.255426 -0.362767 -1.45212 -1.75356 -2.34499 -2.74902 -3.57218 -3.76306 -0.247979 0.107983 0.16455 0.156484 0.0578935 0.222701 0.974726 1.20929\n",
      " 142 6.088e-02 5.752e+02 8.313e-02 -- 3.541e+02 -- 0.25545 -0.362775 -1.45214 -1.75352 -2.34513 -2.74875 -3.56989 -3.76317 -0.247887 0.108041 0.164537 0.156864 0.0575814 0.222897 0.97598 1.2084\n",
      " 144 6.792e-02 6.389e+02 7.999e-02 -- 3.541e+02 -- 0.255474 -0.362781 -1.45215 -1.75348 -2.34526 -2.74851 -3.56787 -3.76327 -0.247793 0.108101 0.164534 0.157238 0.0572308 0.223035 0.977144 1.20751\n",
      " 146 7.496e-02 7.089e+02 7.699e-02 -- 3.542e+02 -- 0.255498 -0.362788 -1.45217 -1.75345 -2.3454 -2.74829 -3.56608 -3.76337 -0.247697 0.108163 0.164541 0.157606 0.0568421 0.223116 0.978218 1.20662\n",
      " 148 8.194e-02 7.858e+02 7.415e-02 -- 3.543e+02 -- 0.255521 -0.362795 -1.45218 -1.75341 -2.34553 -2.74809 -3.56451 -3.76345 -0.247599 0.108227 0.164558 0.157967 0.0564161 0.22314 0.979203 1.20571\n",
      " 150 8.877e-02 8.701e+02 7.150e-02 -- 3.544e+02 -- 0.255544 -0.362801 -1.4522 -1.75338 -2.34566 -2.74791 -3.56313 -3.76352 -0.247499 0.108292 0.164584 0.158323 0.0559538 0.223106 0.980101 1.20482\n",
      " 152 9.539e-02 9.628e+02 6.905e-02 -- 3.544e+02 -- 0.255566 -0.362807 -1.45222 -1.75336 -2.34579 -2.74775 -3.56192 -3.76359 -0.247398 0.108359 0.16462 0.158673 0.0554571 0.223018 0.980916 1.20392\n",
      " 154 1.017e-01 1.065e+03 6.682e-02 -- 3.545e+02 -- 0.255589 -0.362813 -1.45223 -1.75333 -2.34591 -2.74761 -3.56087 -3.76365 -0.247295 0.108428 0.164666 0.159017 0.0549281 0.222877 0.981651 1.20304\n",
      " 156 1.077e-01 1.177e+03 6.480e-02 -- 3.546e+02 -- 0.255611 -0.362819 -1.45225 -1.75331 -2.34603 -2.74749 -3.55996 -3.76369 -0.247191 0.108499 0.164721 0.159357 0.0543694 0.222685 0.982311 1.20217\n",
      " 158 1.132e-01 1.300e+03 6.299e-02 -- 3.546e+02 -- 0.255633 -0.362825 -1.45226 -1.75329 -2.34615 -2.74739 -3.55918 -3.76373 -0.247085 0.108571 0.164785 0.159691 0.0537841 0.222446 0.982901 1.20132\n",
      " 160 1.182e-01 1.436e+03 6.139e-02 -- 3.547e+02 -- 0.255654 -0.36283 -1.45227 -1.75327 -2.34627 -2.74731 -3.55851 -3.76377 -0.246978 0.108645 0.164856 0.160019 0.0531753 0.222164 0.983425 1.20049\n",
      " 162 1.227e-01 1.586e+03 6.000e-02 -- 3.547e+02 -- 0.255676 -0.362835 -1.45229 -1.75326 -2.34638 -2.74724 -3.55794 -3.76379 -0.246871 0.108719 0.164934 0.160342 0.0525467 0.221843 0.98389 1.19969\n",
      " 164 1.266e-01 1.752e+03 5.878e-02 -- 3.548e+02 -- 0.255697 -0.36284 -1.4523 -1.75324 -2.34649 -2.74719 -3.55745 -3.76382 -0.246763 0.108795 0.165018 0.160659 0.0519018 0.221488 0.9843 1.19892\n",
      " 166 1.299e-01 1.936e+03 5.774e-02 -- 3.549e+02 -- 0.255717 -0.362845 -1.45231 -1.75323 -2.3466 -2.74715 -3.55703 -3.76383 -0.246655 0.10887 0.165107 0.16097 0.0512446 0.221103 0.98466 1.19817\n",
      " 167 8.335e-01 5.253e+05 1.229e+00 -- 3.561e+02 -- 0.255921 -0.362892 -1.45244 -1.75313 -2.34767 -2.74689 -3.55355 -3.76396 -0.245575 0.109632 0.166041 0.164016 0.0445881 0.217007 0.987818 1.19106\n",
      " 169 4.967e-01 6.931e+04 9.078e-01 -- 3.570e+02 -- 0.256778 -0.363023 -1.45248 -1.75314 -2.34788 -2.74729 -3.55391 -3.76392 -0.240168 0.115356 0.168594 0.167645 0.0408715 0.213369 0.987598 1.19065\n",
      " 171 3.048e-01 2.023e+05 2.339e-01 -- 3.572e+02 -- 0.257135 -0.363073 -1.4525 -1.75314 -2.348 -2.7475 -3.5541 -3.76389 -0.237882 0.117852 0.16997 0.169576 0.0388412 0.2114 0.98748 1.19042\n",
      " 173 1.911e-01 2.661e+05 1.067e-01 -- 3.573e+02 -- 0.257299 -0.363094 -1.45251 -1.75314 -2.34807 -2.74763 -3.55422 -3.76388 -0.236811 0.118996 0.170757 0.170684 0.0376575 0.210262 0.987412 1.19029\n",
      " 175 1.242e-01 3.120e+05 7.122e-02 -- 3.574e+02 -- 0.257367 -0.363102 -1.45252 -1.75313 -2.34811 -2.7477 -3.55428 -3.76387 -0.236362 0.119438 0.171223 0.171343 0.036938 0.209578 0.987372 1.19021\n",
      " 177 8.518e-02 3.537e+05 6.017e-02 -- 3.575e+02 -- 0.257377 -0.363102 -1.45252 -1.75313 -2.34814 -2.74775 -3.55433 -3.76386 -0.236301 0.119504 0.171509 0.171751 0.0364794 0.209147 0.987347 1.19015\n",
      " 178 8.968e+00 4.801e+09 1.203e+01 -- 3.454e+02 -- 0.25718 -0.363074 -1.45256 -1.7531 -2.34833 -2.74807 -3.55461 -3.76383 -0.236925 0.118229 0.173367 0.174411 0.0333719 0.206265 0.987183 1.18976\n",
      " 181 2.164e+01 5.609e+09 1.234e+00 -- 3.467e+02 -- 0.254646 -0.363062 -1.45256 -1.7531 -2.34833 -2.74806 -3.55461 -3.76383 -0.215677 0.117722 0.173339 0.174333 0.0334359 0.206333 0.987186 1.18977\n",
      " 184 5.483e+01 2.331e+10 1.652e+01 -- 3.302e+02 -- 0.252058 -0.363045 -1.45256 -1.7531 -2.34833 -2.74806 -3.5546 -3.76383 -0.169015 0.117128 0.173323 0.174259 0.0334941 0.206388 0.987189 1.18977\n",
      " 188 6.183e+01 1.828e+10 5.801e+00 -- 3.360e+02 -- 0.252061 -0.363046 -1.45256 -1.7531 -2.34833 -2.74806 -3.5546 -3.76383 -0.178282 0.117142 0.173318 0.174255 0.0334983 0.206394 0.987189 1.18977\n",
      " 192 5.885e+01 2.436e+10 3.844e+00 -- 3.321e+02 -- 0.253244 -0.363049 -1.45256 -1.7531 -2.34833 -2.74806 -3.5546 -3.76383 -0.189305 0.117135 0.173312 0.174248 0.0335015 0.206395 0.987189 1.18977\n",
      " 196 2.129e+01 1.929e+10 7.309e+00 -- 3.394e+02 -- 0.252685 -0.363051 -1.45256 -1.7531 -2.34833 -2.74806 -3.5546 -3.76383 -0.200446 0.117182 0.173307 0.174242 0.0335052 0.206401 0.987189 1.18978\n",
      " 200 2.206e+01 2.181e+10 2.023e+00 -- 3.374e+02 -- 0.253371 -0.363052 -1.45256 -1.7531 -2.34833 -2.74806 -3.5546 -3.76383 -0.204712 0.117211 0.173302 0.174232 0.0335083 0.206402 0.987189 1.18978\n",
      " 204 8.299e+01 5.939e+10 2.238e+01 -- 3.150e+02 -- 0.254665 -0.363051 -1.45256 -1.7531 -2.34833 -2.74806 -3.5546 -3.76383 -0.200196 0.117131 0.173299 0.174226 0.0335125 0.206401 0.98719 1.18978\n",
      " 208 9.303e+01 8.504e+10 5.484e+00 -- 3.095e+02 -- 0.255535 -0.363057 -1.45256 -1.7531 -2.34833 -2.74806 -3.5546 -3.76383 -0.216811 0.117221 0.173291 0.174227 0.0335159 0.206403 0.98719 1.18978\n",
      " 212 6.491e+01 2.077e+11 3.885e+01 -- 2.707e+02 -- 0.254951 -0.36305 -1.45256 -1.7531 -2.34833 -2.74806 -3.5546 -3.76383 -0.196641 0.117099 0.173292 0.174214 0.0335247 0.206409 0.987191 1.18978\n",
      " 217 1.111e+02 2.167e+11 3.081e+00 -- 2.676e+02 -- 0.25519 -0.363051 -1.45256 -1.7531 -2.34832 -2.74806 -3.5546 -3.76383 -0.197918 0.117105 0.173291 0.174215 0.0335252 0.206409 0.987191 1.18978\n",
      " 221 2.876e+02 9.255e+11 1.181e+02 -- 1.495e+02 -- 0.254392 -0.363043 -1.45256 -1.7531 -2.34832 -2.74805 -3.5546 -3.76383 -0.175939 0.116879 0.173293 0.174201 0.0335327 0.206419 0.987192 1.18978\n",
      " 225 1.234e+00 2.500e+08 2.070e+02 -- 3.565e+02 -- 0.257392 -0.363058 -1.45256 -1.7531 -2.34832 -2.74805 -3.5546 -3.76383 -0.226547 0.117399 0.173269 0.174192 0.0335295 0.206406 0.987194 1.18978\n",
      " 226 5.528e+01 1.532e+11 3.627e+02 -- -6.266e+00 -- 0.253834 -0.36252 -1.45253 -1.75307 -2.34805 -2.74748 -3.5541 -3.76389 0.0531025 0.0821288 0.169868 0.16878 0.0388404 0.211605 0.987527 1.19032\n",
      " 229 7.686e+00 1.730e+09 3.323e+02 -- 3.261e+02 -- 0.255597 -0.362547 -1.45253 -1.75307 -2.34807 -2.7475 -3.55413 -3.76389 0.08246 0.0832204 0.170036 0.169033 0.0385988 0.211368 0.987512 1.19029\n",
      " 232 3.732e+00 4.680e+08 1.751e+01 -- 3.436e+02 -- 0.257357 -0.362572 -1.45254 -1.75307 -2.34808 -2.74752 -3.55415 -3.76389 0.0887979 0.0841294 0.170166 0.169243 0.0384008 0.211174 0.987501 1.19027\n",
      " 235 3.446e+00 2.036e+08 5.719e+00 -- 3.493e+02 -- 0.258519 -0.362592 -1.45254 -1.75307 -2.34808 -2.74754 -3.55416 -3.76388 0.0921117 0.0848699 0.17027 0.169411 0.03824 0.211016 0.987491 1.19026\n",
      " 237 2.034e+00 1.556e+08 4.483e-02 -- 3.492e+02 -- 0.26605 -0.36276 -1.45254 -1.75309 -2.34815 -2.74769 -3.55429 -3.76387 0.123855 0.0911334 0.171129 0.170821 0.0369156 0.209732 0.987409 1.19012\n",
      " 239 1.466e+00 1.245e+08 2.780e+00 -- 3.520e+02 -- 0.259943 -0.362627 -1.45254 -1.75308 -2.34809 -2.74756 -3.55417 -3.76388 0.0986618 0.085177 0.170356 0.169568 0.0381123 0.210889 0.987481 1.19024\n",
      " 241 1.862e+00 2.649e+08 3.442e+00 -- 3.486e+02 -- 0.266437 -0.362754 -1.45254 -1.75309 -2.34814 -2.74767 -3.55427 -3.76387 0.113128 0.0899647 0.170998 0.17062 0.0371147 0.209918 0.987421 1.19014\n",
      " 243 1.266e+01 1.952e+09 9.726e+00 -- 3.388e+02 -- 0.259641 -0.362639 -1.45253 -1.75308 -2.34809 -2.74755 -3.55417 -3.76388 0.0920617 0.0850623 0.170303 0.169498 0.038182 0.210959 0.987481 1.19025\n",
      " 246 3.739e+00 6.376e+08 9.943e+00 -- 3.488e+02 -- 0.260555 -0.362649 -1.45254 -1.75308 -2.3481 -2.74756 -3.55418 -3.76388 0.103714 0.0855166 0.170377 0.169607 0.0380736 0.210855 0.987475 1.19024\n",
      " 249 7.179e+00 2.798e+08 3.620e+00 -- 3.524e+02 -- 0.261275 -0.362658 -1.45254 -1.75308 -2.3481 -2.74757 -3.55419 -3.76388 0.107592 0.0858678 0.170432 0.169696 0.0379917 0.210774 0.987471 1.19023\n",
      " 251 6.516e-01 1.445e+07 2.805e+00 -- 3.552e+02 -- 0.260815 -0.362722 -1.45254 -1.75308 -2.34813 -2.74765 -3.55425 -3.76387 0.184829 0.0886738 0.170854 0.170348 0.0373649 0.210209 0.987427 1.19017\n",
      " 253 3.810e+00 2.052e+08 1.727e+00 -- 3.535e+02 -- 0.257283 -0.362714 -1.45254 -1.75308 -2.34812 -2.74764 -3.55423 -3.76387 0.172785 0.088281 0.17073 0.170156 0.0375437 0.210382 0.987434 1.19018\n",
      " 255 3.064e+00 8.311e+06 1.177e+00 -- 3.547e+02 -- 0.258177 -0.36276 -1.45254 -1.75308 -2.34815 -2.74769 -3.55428 -3.76387 0.238623 0.0899565 0.171066 0.170674 0.0370633 0.209939 0.987402 1.19013\n",
      " 257 7.394e+00 3.133e+09 1.172e+01 -- 3.429e+02 -- 0.254324 -0.362757 -1.45254 -1.75308 -2.34814 -2.74767 -3.55426 -3.76387 0.165501 0.0891934 0.170888 0.170414 0.0372912 0.210148 0.987412 1.19016\n",
      " 259 4.577e+00 8.174e+09 2.129e+01 -- 3.217e+02 -- 0.25069 -0.36289 -1.45254 -1.7531 -2.34818 -2.74774 -3.55433 -3.76386 0.0431235 0.0911987 0.171302 0.171131 0.0366077 0.209486 0.987358 1.19009\n",
      " 261 2.816e+00 1.095e+09 2.508e+01 -- 3.467e+02 -- 0.259954 -0.363017 -1.45255 -1.75311 -2.34824 -2.74786 -3.55443 -3.76385 0.0628627 0.0987668 0.171982 0.172358 0.0355272 0.20841 0.987296 1.18998\n",
      " 263 8.570e+00 1.645e+09 2.114e+00 -- 3.489e+02 -- 0.252615 -0.362928 -1.45254 -1.7531 -2.3482 -2.74777 -3.55435 -3.76386 0.0451626 0.0945636 0.171419 0.171452 0.0363838 0.209263 0.987344 1.19006\n",
      " 266 6.015e+00 7.015e+08 4.892e+00 -- 3.537e+02 -- 0.254279 -0.362935 -1.45254 -1.7531 -2.3482 -2.74777 -3.55435 -3.76386 0.041292 0.0948982 0.171457 0.171509 0.0363216 0.209197 0.987341 1.19006\n",
      " 269 2.525e+01 1.168e+08 3.655e+00 -- 3.574e+02 -- 0.256735 -0.362939 -1.45254 -1.7531 -2.3482 -2.74777 -3.55436 -3.76386 0.0388082 0.0951206 0.171485 0.171557 0.0362756 0.209144 0.98734 1.19005\n",
      " 271 1.208e+01 6.119e+09 1.521e+01 -- 3.422e+02 -- 0.257086 -0.362929 -1.45255 -1.7531 -2.34821 -2.7478 -3.55437 -3.76386 0.136783 0.0964349 0.171623 0.17166 0.0360846 0.209008 0.987331 1.19003\n",
      " 273 6.524e+01 2.429e+09 1.264e+01 -- 3.548e+02 -- 0.249456 -0.36281 -1.45255 -1.75308 -2.34818 -2.74774 -3.55432 -3.76386 0.302002 0.0935984 0.171321 0.171267 0.0365623 0.209564 0.98736 1.19009\n",
      " 277 8.104e+01 1.297e+10 5.058e+00 -- 3.498e+02 -- 0.248213 -0.362807 -1.45255 -1.75308 -2.34818 -2.74775 -3.55432 -3.76386 0.321703 0.0935769 0.171325 0.171264 0.0365626 0.209571 0.987359 1.19009\n",
      " 282 2.328e+01 1.055e+10 1.358e+00 -- 3.511e+02 -- 0.248486 -0.362807 -1.45255 -1.75308 -2.34818 -2.74775 -3.55432 -3.76386 0.319096 0.0935799 0.171325 0.171264 0.0365624 0.20957 0.987359 1.19009\n",
      " 286 6.803e+00 3.491e+09 3.884e+00 -- 3.550e+02 -- 0.249067 -0.362804 -1.45255 -1.75308 -2.34818 -2.74775 -3.55432 -3.76386 0.326525 0.0936242 0.171326 0.171261 0.0365618 0.209572 0.98736 1.19009\n",
      " 291 6.563e+01 1.909e+09 6.548e-01 -- 3.557e+02 -- 0.249237 -0.362804 -1.45255 -1.75308 -2.34818 -2.74775 -3.55432 -3.76386 0.326513 0.0936243 0.171326 0.171261 0.0365619 0.209571 0.98736 1.19009\n",
      " 295 2.097e+01 5.540e+08 7.801e-01 -- 3.565e+02 -- 0.249081 -0.362799 -1.45255 -1.75307 -2.34818 -2.74775 -3.55432 -3.76386 0.347942 0.093616 0.171332 0.171258 0.0365647 0.209579 0.98736 1.19009\n",
      " 299 5.078e+01 2.673e+09 1.016e+00 -- 3.554e+02 -- 0.248981 -0.362802 -1.45255 -1.75307 -2.34818 -2.74775 -3.55432 -3.76386 0.340645 0.0934478 0.171333 0.171274 0.0365637 0.209578 0.98736 1.19009\n",
      " 304 1.217e+02 6.839e+08 7.133e-01 -- 3.562e+02 -- 0.249232 -0.362802 -1.45255 -1.75307 -2.34818 -2.74775 -3.55432 -3.76386 0.338915 0.0934395 0.171333 0.171274 0.0365637 0.209577 0.98736 1.19009\n",
      " 308 8.032e-01 2.458e+07 1.069e+00 -- 3.551e+02 -- 0.252232 -0.362801 -1.45255 -1.75308 -2.34818 -2.74774 -3.55432 -3.76386 0.297682 0.0932028 0.17133 0.171276 0.0365613 0.209559 0.987364 1.19009\n",
      " 310 2.176e+00 1.190e+08 1.235e+00 -- 3.539e+02 -- 0.24778 -0.362787 -1.45255 -1.75307 -2.34817 -2.74773 -3.55431 -3.76386 0.321591 0.0922355 0.17126 0.171144 0.0366787 0.209695 0.987368 1.1901\n",
      " 313 7.459e+00 1.929e+07 9.609e-01 -- 3.548e+02 -- 0.249155 -0.36279 -1.45255 -1.75307 -2.34817 -2.74774 -3.55432 -3.76386 0.314594 0.0923622 0.171282 0.171188 0.0366438 0.209658 0.987366 1.1901\n",
      " 315 5.281e+00 2.205e+08 1.301e+00 -- 3.561e+02 -- 0.255257 -0.362875 -1.45254 -1.75309 -2.34819 -2.74775 -3.55434 -3.76386 0.0799459 0.0941447 0.171371 0.171431 0.0364087 0.209347 0.987352 1.19007\n",
      " 318 4.407e+00 4.106e+07 1.134e+00 -- 3.572e+02 -- 0.256315 -0.362879 -1.45254 -1.75309 -2.3482 -2.74775 -3.55434 -3.76386 0.0757242 0.0943132 0.171389 0.17146 0.0363794 0.209314 0.987352 1.19007\n",
      " 321 7.132e+00 7.906e+07 6.987e-01 -- 3.579e+02 -- 0.25764 -0.362879 -1.45254 -1.75309 -2.3482 -2.74775 -3.55434 -3.76386 0.0723873 0.0944535 0.171398 0.171474 0.0363617 0.209289 0.987352 1.19007\n",
      " 324 7.614e+00 3.913e+07 3.547e-01 -- 3.576e+02 -- 0.258611 -0.362877 -1.45254 -1.75309 -2.3482 -2.74775 -3.55434 -3.76386 0.0775498 0.0944425 0.171402 0.17148 0.0363586 0.209281 0.987353 1.19007\n",
      " 327 1.263e+00 4.729e+07 5.561e-01 -- 3.570e+02 -- 0.258918 -0.362873 -1.45254 -1.75309 -2.3482 -2.74775 -3.55434 -3.76386 0.0834542 0.0943921 0.171395 0.171469 0.0363714 0.20929 0.987354 1.19007\n",
      " 330 1.910e+01 8.393e+07 7.689e-01 -- 3.578e+02 -- 0.258007 -0.362872 -1.45254 -1.75309 -2.34819 -2.74775 -3.55434 -3.76386 0.0845079 0.0943617 0.171384 0.171449 0.036389 0.20931 0.987354 1.19007\n",
      " 333 2.525e+01 1.008e+08 2.575e-01 -- 3.581e+02 -- 0.258286 -0.362878 -1.45254 -1.75309 -2.3482 -2.74774 -3.55434 -3.76386 0.0683659 0.0944189 0.171376 0.171441 0.0363934 0.209307 0.987354 1.19007\n",
      " 336 5.562e+00 5.143e+07 4.538e-01 -- 3.576e+02 -- 0.25833 -0.362872 -1.45254 -1.75309 -2.34819 -2.74775 -3.55434 -3.76386 0.0856295 0.0943039 0.171382 0.171444 0.036396 0.209312 0.987355 1.19007\n",
      " 339 1.157e+01 9.557e+07 2.073e-01 -- 3.578e+02 -- 0.257744 -0.36287 -1.45254 -1.75309 -2.34819 -2.74775 -3.55434 -3.76386 0.0903926 0.0942372 0.171377 0.171435 0.0364077 0.209327 0.987355 1.19007\n",
      " 342 1.068e+01 9.556e+08 3.223e+00 -- 3.546e+02 -- 0.260013 -0.36287 -1.45254 -1.75309 -2.34819 -2.74774 -3.55434 -3.76386 0.0799386 0.0943017 0.171369 0.171427 0.0364092 0.20932 0.987357 1.19007\n",
      " 345 4.170e+01 1.886e+08 2.403e+00 -- 3.570e+02 -- 0.258928 -0.362866 -1.45254 -1.75309 -2.34819 -2.74774 -3.55433 -3.76386 0.0884755 0.0939485 0.171358 0.171408 0.0364383 0.209351 0.987358 1.19008\n",
      " 348 2.879e+01 9.511e+07 1.296e+00 -- 3.583e+02 -- 0.258843 -0.362878 -1.45254 -1.75309 -2.34819 -2.74774 -3.55433 -3.76386 0.0515822 0.0941797 0.171336 0.171408 0.0364491 0.209351 0.987357 1.19008\n",
      " 351 4.880e+01 1.238e+08 3.808e-01 -- 3.579e+02 -- 0.259089 -0.362884 -1.45254 -1.75309 -2.34819 -2.74774 -3.55434 -3.76386 0.0367321 0.0942631 0.171336 0.171434 0.0364398 0.209343 0.987356 1.19008\n",
      " 354 1.177e+02 4.510e+08 6.040e-01 -- 3.573e+02 -- 0.259363 -0.362893 -1.45254 -1.7531 -2.34819 -2.74774 -3.55434 -3.76386 0.0188061 0.094653 0.171334 0.171438 0.0364246 0.209325 0.987355 1.19007\n",
      " 357 1.797e+01 2.155e+08 1.342e+00 -- 3.586e+02 -- 0.259777 -0.362885 -1.45254 -1.7531 -2.34819 -2.74774 -3.55434 -3.76386 0.0409415 0.0945432 0.171355 0.171458 0.0364111 0.209306 0.987355 1.19007\n",
      " 359 2.641e+04 1.751e+14 2.177e+03 -- -1.818e+03 -- 0.258935 -0.362902 -1.45254 -1.7531 -2.3482 -2.74773 -3.55433 -3.76386 -0.0326452 0.0965976 0.171306 0.171256 0.0364091 0.20932 0.987355 1.19007\n",
      " 368 1.789e+04 2.368e+14 3.546e+02 -- -2.173e+03 -- 0.258935 -0.362902 -1.45254 -1.7531 -2.3482 -2.74773 -3.55433 -3.76386 -0.0326366 0.0965975 0.171306 0.171256 0.0364091 0.20932 0.987355 1.19007\n",
      " 372 6.690e-01 1.850e+06 2.525e+03 -- 3.517e+02 -- 0.261935 -0.363089 -1.45251 -1.75324 -2.3482 -2.74767 -3.55432 -3.76386 -0.616453 0.0981103 0.170229 0.17144 0.0374651 0.209113 0.987434 1.19006\n",
      " 374 6.163e-01 2.129e+05 2.479e+00 -- 3.542e+02 -- 0.258997 -0.363262 -1.45252 -1.75326 -2.34833 -2.7479 -3.55454 -3.76384 -0.578257 0.104674 0.17185 0.173716 0.0352143 0.206809 0.987308 1.18982\n",
      " 376 5.913e-01 6.432e+05 1.228e+00 -- 3.554e+02 -- 0.256225 -0.363323 -1.45253 -1.75326 -2.3484 -2.74802 -3.55465 -3.76382 -0.542617 0.108165 0.172695 0.174865 0.0340199 0.205587 0.987244 1.18969\n",
      " 378 5.514e-01 8.533e+05 7.479e-01 -- 3.561e+02 -- 0.254051 -0.363342 -1.45253 -1.75326 -2.34844 -2.74809 -3.55472 -3.76382 -0.510533 0.110241 0.173163 0.175487 0.0333382 0.204888 0.987208 1.18961\n",
      " 380 5.180e-01 1.004e+06 4.971e-01 -- 3.566e+02 -- 0.25242 -0.363341 -1.45254 -1.75326 -2.34846 -2.74813 -3.55476 -3.76381 -0.482381 0.111475 0.17342 0.175814 0.0329481 0.204485 0.987189 1.18957\n",
      " 382 4.902e-01 1.139e+06 3.585e-01 -- 3.570e+02 -- 0.25124 -0.36333 -1.45254 -1.75326 -2.34847 -2.74815 -3.55478 -3.76381 -0.457393 0.112191 0.173555 0.175975 0.0327287 0.204255 0.987179 1.18954\n",
      " 384 4.537e-01 1.276e+06 2.752e-01 -- 3.573e+02 -- 0.250444 -0.363315 -1.45254 -1.75326 -2.34848 -2.74816 -3.55479 -3.76381 -0.434971 0.112595 0.173618 0.176038 0.0326106 0.204128 0.987175 1.18953\n",
      " 386 4.177e-01 1.422e+06 2.177e-01 -- 3.575e+02 -- 0.249927 -0.363298 -1.45254 -1.75326 -2.34849 -2.74816 -3.55479 -3.76381 -0.415237 0.112771 0.173639 0.176044 0.0325551 0.204065 0.987174 1.18952\n",
      " 388 3.997e-01 1.582e+06 1.784e-01 -- 3.577e+02 -- 0.249603 -0.36328 -1.45254 -1.75325 -2.34849 -2.74816 -3.55479 -3.76381 -0.397894 0.112831 0.173635 0.176017 0.0325368 0.20404 0.987175 1.18952\n",
      " 390 3.521e-01 1.759e+06 1.541e-01 -- 3.578e+02 -- 0.24945 -0.363264 -1.45254 -1.75325 -2.34849 -2.74816 -3.55479 -3.76381 -0.381991 0.11281 0.173617 0.175973 0.0325408 0.204038 0.987177 1.18952\n",
      " 392 2.781e-01 1.955e+06 1.294e-01 -- 3.580e+02 -- 0.249369 -0.363247 -1.45254 -1.75325 -2.34849 -2.74815 -3.55479 -3.76381 -0.368541 0.112703 0.17359 0.175916 0.0325603 0.204053 0.98718 1.18952\n",
      " 394 3.503e-01 2.172e+06 1.069e-01 -- 3.581e+02 -- 0.249517 -0.363233 -1.45254 -1.75325 -2.34849 -2.74815 -3.55479 -3.76381 -0.35829 0.112607 0.173559 0.17586 0.0325849 0.204074 0.987183 1.18952\n",
      " 396 2.380e-01 2.413e+06 1.111e-01 -- 3.582e+02 -- 0.249439 -0.363219 -1.45254 -1.75325 -2.34849 -2.74814 -3.55478 -3.76381 -0.345741 0.112463 0.173528 0.175799 0.0326152 0.204099 0.987186 1.18952\n",
      " 398 2.527e-01 2.681e+06 9.063e-02 -- 3.583e+02 -- 0.249818 -0.363207 -1.45254 -1.75325 -2.34849 -2.74814 -3.55478 -3.76381 -0.337514 0.112322 0.173495 0.175737 0.0326474 0.204127 0.987189 1.18952\n",
      " 400 1.574e-01 2.980e+06 8.735e-02 -- 3.583e+02 -- 0.24992 -0.363195 -1.45254 -1.75324 -2.34849 -2.74813 -3.55478 -3.76381 -0.328983 0.112124 0.17346 0.175677 0.0326852 0.204162 0.987193 1.18953\n",
      " 402 4.787e-02 3.312e+06 7.415e-02 -- 3.584e+02 -- 0.250149 -0.363185 -1.45254 -1.75324 -2.34848 -2.74813 -3.55477 -3.76381 -0.323806 0.111956 0.173429 0.175624 0.0327188 0.204194 0.987196 1.18953\n",
      " 404 1.565e-01 3.682e+06 6.319e-02 -- 3.585e+02 -- 0.250644 -0.363177 -1.45254 -1.75324 -2.34848 -2.74812 -3.55477 -3.76381 -0.322256 0.111821 0.173403 0.175576 0.0327469 0.204218 0.987198 1.18953\n",
      " 406 1.014e-01 4.089e+06 7.156e-02 -- 3.586e+02 -- 0.250855 -0.363169 -1.45254 -1.75324 -2.34848 -2.74812 -3.55477 -3.76381 -0.317211 0.111743 0.17338 0.175533 0.0327711 0.20424 0.9872 1.18953\n",
      " 408 6.026e-02 4.546e+06 6.444e-02 -- 3.586e+02 -- 0.250942 -0.363162 -1.45254 -1.75324 -2.34848 -2.74812 -3.55476 -3.76381 -0.313996 0.111664 0.173354 0.175484 0.032799 0.204265 0.987203 1.18954\n",
      " 410 5.353e-02 5.051e+06 6.122e-02 -- 3.587e+02 -- 0.251214 -0.363156 -1.45254 -1.75324 -2.34848 -2.74811 -3.55476 -3.76381 -0.312103 0.111601 0.173334 0.175452 0.0328209 0.204283 0.987205 1.18954\n",
      " 412 3.313e-01 5.616e+06 5.936e-02 -- 3.587e+02 -- 0.25132 -0.36315 -1.45254 -1.75324 -2.34848 -2.74811 -3.55476 -3.76381 -0.310433 0.111483 0.173315 0.175418 0.0328405 0.204302 0.987206 1.18954\n",
      " 414 2.458e-01 6.221e+06 8.104e-02 -- 3.588e+02 -- 0.25152 -0.363144 -1.45254 -1.75324 -2.34848 -2.74811 -3.55476 -3.76381 -0.300149 0.111342 0.173305 0.175396 0.0328536 0.204313 0.987208 1.18954\n",
      " 416 3.303e-01 6.940e+06 4.243e-02 -- 3.589e+02 -- 0.252529 -0.363141 -1.45254 -1.75324 -2.34848 -2.7481 -3.55475 -3.76381 -0.307525 0.111245 0.173274 0.175347 0.0328886 0.204345 0.987211 1.18954\n",
      " 418 2.732e-01 7.749e+06 7.538e-02 -- 3.589e+02 -- 0.251523 -0.363133 -1.45254 -1.75324 -2.34848 -2.7481 -3.55475 -3.76381 -0.297369 0.111097 0.173256 0.175306 0.0329145 0.204372 0.987212 1.18955\n",
      " 420 2.171e-01 8.619e+06 6.585e-02 -- 3.590e+02 -- 0.250986 -0.363128 -1.45254 -1.75324 -2.34848 -2.7481 -3.55475 -3.76381 -0.289245 0.110957 0.173254 0.175304 0.0329193 0.204375 0.987213 1.18955\n",
      " 422 1.367e-01 9.558e+06 6.498e-02 -- 3.591e+02 -- 0.25117 -0.363126 -1.45254 -1.75324 -2.34848 -2.7481 -3.55475 -3.76381 -0.282965 0.110892 0.173251 0.175291 0.0329228 0.204377 0.987213 1.18955\n",
      " 424 1.078e-01 1.065e+07 5.047e-02 -- 3.591e+02 -- 0.250283 -0.363121 -1.45254 -1.75324 -2.34848 -2.7481 -3.55475 -3.76381 -0.279096 0.110663 0.173235 0.175263 0.0329452 0.204402 0.987215 1.18955\n",
      " 426 6.572e-01 1.172e+07 3.144e-02 -- 3.592e+02 -- 0.249336 -0.363121 -1.45254 -1.75324 -2.34848 -2.7481 -3.55475 -3.76381 -0.282104 0.11081 0.173244 0.175268 0.03293 0.204387 0.987213 1.18955\n",
      " 428 5.054e-01 1.316e+07 7.386e-02 -- 3.592e+02 -- 0.249036 -0.36312 -1.45254 -1.75324 -2.34848 -2.74811 -3.55475 -3.76381 -0.263564 0.110889 0.173276 0.175312 0.0328876 0.204345 0.987211 1.18954\n",
      " 430 1.710e+00 1.428e+07 5.282e-02 -- 3.593e+02 -- 0.249406 -0.363114 -1.45254 -1.75324 -2.34848 -2.7481 -3.55475 -3.76381 -0.250243 0.110635 0.173257 0.175261 0.0329177 0.204379 0.987214 1.18955\n",
      " 432 7.772e-01 1.655e+07 5.093e-02 -- 3.593e+02 -- 0.251439 -0.363115 -1.45254 -1.75324 -2.34847 -2.74809 -3.55474 -3.76381 -0.293033 0.1105 0.173206 0.175194 0.0329741 0.20443 0.987218 1.18955\n",
      " 434 1.590e+00 1.724e+07 4.105e-02 -- 3.593e+02 -- 0.251114 -0.363123 -1.45254 -1.75324 -2.34848 -2.7481 -3.55475 -3.76381 -0.315808 0.11098 0.173234 0.175245 0.0329205 0.20438 0.987214 1.18955\n",
      " 436 2.078e+00 1.442e+07 6.228e-02 -- 3.594e+02 -- 0.252467 -0.36312 -1.45254 -1.75324 -2.34848 -2.74811 -3.55476 -3.76381 -0.265603 0.111067 0.173304 0.17534 0.0328373 0.204281 0.987211 1.18954\n",
      " 438 2.622e+00 2.092e+07 1.046e-01 -- 3.595e+02 -- 0.249064 -0.363089 -1.45254 -1.75323 -2.34847 -2.74809 -3.55474 -3.76381 -0.210422 0.109904 0.173201 0.175158 0.0330073 0.204453 0.987222 1.18955\n",
      " 440 2.370e-01 2.398e+07 1.058e-01 -- 3.596e+02 -- 0.250133 -0.363091 -1.45254 -1.75324 -2.34847 -2.74808 -3.55473 -3.76381 -0.265588 0.109484 0.173108 0.175038 0.033125 0.204566 0.987227 1.18957\n",
      " 442 6.561e-01 2.389e+07 2.821e-02 -- 3.595e+02 -- 0.247097 -0.363105 -1.45254 -1.75324 -2.34847 -2.74809 -3.55474 -3.76381 -0.271884 0.110528 0.173184 0.175113 0.033014 0.204456 0.987219 1.18955\n",
      " 444 5.072e+00 5.109e+08 1.835e+00 -- 3.577e+02 -- 0.236997 -0.363105 -1.45255 -1.75323 -2.34848 -2.74811 -3.55476 -3.76381 -0.254045 0.11072 0.173288 0.175291 0.0328836 0.204367 0.987207 1.18954\n",
      " 447 1.057e+01 4.593e+08 1.662e-01 -- 3.579e+02 -- 0.237886 -0.363111 -1.45255 -1.75323 -2.34848 -2.74812 -3.55476 -3.76381 -0.266931 0.110974 0.173303 0.175328 0.0328554 0.204341 0.987206 1.18954\n",
      " 450 7.338e+01 1.668e+10 1.284e+01 -- 3.450e+02 -- 0.229947 -0.363104 -1.45255 -1.75323 -2.34848 -2.74812 -3.55476 -3.76381 -0.238724 0.11079 0.17333 0.175359 0.032836 0.204334 0.987203 1.18954\n",
      " 454 1.669e+01 4.660e+07 1.379e+01 -- 3.588e+02 -- 0.232947 -0.363102 -1.45255 -1.75323 -2.34848 -2.74812 -3.55476 -3.76381 -0.221206 0.110782 0.173331 0.175354 0.0328338 0.204323 0.987204 1.18953\n",
      " 457 6.736e+00 7.637e+07 8.954e-03 -- 3.588e+02 -- 0.236984 -0.363112 -1.45255 -1.75323 -2.34848 -2.74812 -3.55476 -3.76381 -0.258136 0.110966 0.173339 0.17538 0.0328089 0.204294 0.987203 1.18953\n",
      " 460 6.471e+00 9.704e+06 4.604e-01 -- 3.593e+02 -- 0.236655 -0.363111 -1.45255 -1.75323 -2.34849 -2.74813 -3.55477 -3.76381 -0.240747 0.111111 0.173355 0.1754 0.0327882 0.204273 0.987202 1.18953\n",
      " 463 8.613e+00 4.704e+07 4.115e-01 -- 3.597e+02 -- 0.237547 -0.36311 -1.45255 -1.75323 -2.34849 -2.74813 -3.55477 -3.76381 -0.225168 0.111183 0.173367 0.17542 0.032773 0.204255 0.987202 1.18953\n",
      " 466 3.362e+00 7.507e+07 1.913e-01 -- 3.599e+02 -- 0.238404 -0.363107 -1.45255 -1.75323 -2.34849 -2.74813 -3.55477 -3.76381 -0.205775 0.111127 0.173375 0.175432 0.0327636 0.204245 0.987202 1.18953\n",
      " 468 3.391e+01 6.069e+07 2.465e-01 -- 3.596e+02 -- 0.233164 -0.363093 -1.45255 -1.75323 -2.34849 -2.74813 -3.55477 -3.76381 -0.136596 0.111009 0.173402 0.175399 0.0327685 0.204241 0.987201 1.18953\n",
      " 471 1.410e+02 2.370e+07 3.883e-01 -- 3.592e+02 -- 0.228233 -0.363082 -1.45255 -1.75323 -2.34849 -2.74813 -3.55477 -3.76381 -0.0902722 0.110874 0.173404 0.175393 0.0327806 0.204258 0.987201 1.18953\n",
      " 472 4.001e+00 6.877e+07 5.523e+01 -- 3.040e+02 -- 0.144854 -0.360368 -1.4527 -1.75287 -2.34832 -2.74795 -3.55454 -3.76384 0.073615 0.0439555 0.174963 0.172283 0.0343795 0.20623 0.987592 1.18965\n",
      " 474 4.449e+00 9.477e+04 4.908e+01 -- 3.531e+02 -- 0.178975 -0.361472 -1.45258 -1.7526 -2.34944 -2.74907 -3.55594 -3.76368 0.0676088 0.0602605 0.184173 0.186509 0.0206225 0.191289 0.986849 1.18821\n",
      " 476 7.496e+00 1.443e+05 8.590e-01 -- 3.539e+02 -- 0.184083 -0.361709 -1.45256 -1.75266 -2.34954 -2.74923 -3.5561 -3.76366 0.0375291 0.0666604 0.184752 0.186797 0.01903 0.189498 0.986749 1.188\n",
      " 478 2.779e+01 1.616e+05 4.958e-01 -- 3.544e+02 -- 0.188654 -0.361864 -1.45255 -1.75273 -2.34955 -2.74927 -3.55613 -3.76365 0.00939594 0.0715689 0.184457 0.186024 0.018875 0.189182 0.986725 1.18796\n",
      " 480 1.441e+01 1.748e+05 3.655e-01 -- 3.548e+02 -- 0.192925 -0.361971 -1.45254 -1.7528 -2.34952 -2.74926 -3.55609 -3.76366 -0.0167118 0.075451 0.183801 0.184833 0.0193558 0.189523 0.986735 1.18799\n",
      " 482 5.419e+00 1.903e+05 3.047e-01 -- 3.551e+02 -- 0.196991 -0.36205 -1.45252 -1.75286 -2.34949 -2.74921 -3.55603 -3.76366 -0.0407928 0.0786126 0.183025 0.183518 0.020092 0.190136 0.986762 1.18805\n",
      " 484 3.210e+00 2.094e+05 2.684e-01 -- 3.554e+02 -- 0.20088 -0.36211 -1.45251 -1.75292 -2.34944 -2.74916 -3.55596 -3.76367 -0.0629001 0.081257 0.18224 0.182224 0.0208981 0.190834 0.986794 1.18811\n",
      " 486 2.214e+00 2.319e+05 2.427e-01 -- 3.556e+02 -- 0.204623 -0.362158 -1.4525 -1.75296 -2.3494 -2.74911 -3.55589 -3.76368 -0.0830936 0.0835154 0.181498 0.181014 0.0216866 0.191527 0.986828 1.18818\n",
      " 488 1.641e+00 2.576e+05 2.220e-01 -- 3.558e+02 -- 0.2082 -0.362199 -1.45249 -1.753 -2.34936 -2.74906 -3.55583 -3.76369 -0.101492 0.0854718 0.18082 0.179912 0.0224199 0.192178 0.986859 1.18824\n",
      " 490 1.279e+00 2.867e+05 2.041e-01 -- 3.560e+02 -- 0.21159 -0.362234 -1.45249 -1.75303 -2.34933 -2.74901 -3.55577 -3.76369 -0.118149 0.0871837 0.18021 0.178923 0.0230854 0.192771 0.986888 1.1883\n",
      " 492 1.019e+00 3.190e+05 1.889e-01 -- 3.562e+02 -- 0.214798 -0.362264 -1.45248 -1.75306 -2.3493 -2.74897 -3.55572 -3.7637 -0.133264 0.0886906 0.179665 0.178041 0.0236819 0.193305 0.986915 1.18835\n",
      " 494 8.350e-01 3.550e+05 1.755e-01 -- 3.564e+02 -- 0.217839 -0.362291 -1.45247 -1.75309 -2.34927 -2.74893 -3.55567 -3.76371 -0.146847 0.0900198 0.179181 0.177257 0.024214 0.193782 0.986939 1.1884\n",
      " 496 6.864e-01 3.949e+05 1.631e-01 -- 3.566e+02 -- 0.220677 -0.362314 -1.45247 -1.75311 -2.34924 -2.74889 -3.55563 -3.76371 -0.159109 0.0911918 0.178751 0.17656 0.0246885 0.19421 0.98696 1.18844\n",
      " 498 5.835e-01 4.392e+05 1.520e-01 -- 3.567e+02 -- 0.223333 -0.362335 -1.45246 -1.75313 -2.34922 -2.74886 -3.55559 -3.76371 -0.17003 0.0922269 0.178367 0.175939 0.0251115 0.194591 0.986979 1.18847\n",
      " 500 4.877e-01 4.884e+05 1.422e-01 -- 3.569e+02 -- 0.225803 -0.362354 -1.45246 -1.75314 -2.3492 -2.74883 -3.55556 -3.76372 -0.179951 0.0931396 0.178026 0.175387 0.0254897 0.194933 0.986996 1.18851\n",
      "********************\n",
      "0.248545 -0.362521 -1.45242 -1.75328 -2.34903 -2.74857 -3.55526 -3.76375 -0.267712 0.101175 0.174975 0.17046 0.0288768 0.198006 0.987152 1.18879\n",
      "0.0326854 0.00121998 0.000396181 0.00485342 0.00441057 0.00846026 0.00173706 0.000198443 0.208668 0.0333017 0.0139548 0.0472137 0.0310511 0.0388547 0.00686236 0.00229119\n",
      "21.6768 960.747 11500.2 1088.5 2531.9 1489.42 54226.9 488371 -1.74721 7.48018 -88.3148 -31.5201 -35.9069 149.822 -1498.85 -399.194\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": 14,
   "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": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Container object of 3 artists>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9bcffaae50>"
      ]
     },
     "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": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f9bcb7e8b50>]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JkhQRV0D4JjAX+A/wekxtSF2WSqWSLkFFwr6mfBdXQOgF3A38JKbzS9vEb9rK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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9bcb90f9d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "s, loc, scale = lognorm.fit(lag,loc=.01)\n",
    "\n",
    "xscale('log'); ylim(-1,5)\n",
    "errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color=\"black\")\n",
    "plot(fqd,lognorm.pdf(fqd,s,loc,scale))"
   ]
  },
  {
   "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
}