phy-4660/lag/data/clag_analysis-origbins.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"
     ]
    },
    {
     "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 0x7f59e7a8bc10>"
      ]
     },
     "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/6175A.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": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.00964867,  0.02886003,  0.0556922 ,  0.08632291,  0.13380051,\n",
       "        0.20739079,  0.32145572,  0.49825637])"
      ]
     },
     "execution_count": 3,
     "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",
    "fqd\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   1 4.337e-01 6.112e+01 inf -- -4.041e+02 -- 1 1 1 1 1 1 1\n",
      "   2 7.647e-01 6.015e+01 6.901e+01 -- -3.351e+02 -- 0.65784 0.58285 0.5699 0.567505 0.56704 0.566344 0.573791\n",
      "   3 3.242e+00 5.939e+01 6.602e+01 -- -2.691e+02 -- 0.42512 0.198095 0.146253 0.137492 0.135449 0.133237 0.150987\n",
      "   4 1.563e+00 5.894e+01 6.233e+01 -- -2.067e+02 -- 0.328446 -0.100568 -0.261985 -0.286046 -0.293214 -0.298752 -0.270142\n",
      "   5 6.151e-01 5.858e+01 5.845e+01 -- -1.483e+02 -- 0.300114 -0.231637 -0.637422 -0.692493 -0.715789 -0.728243 -0.692465\n",
      "   6 3.834e-01 5.758e+01 5.397e+01 -- -9.432e+01 -- 0.288119 -0.218711 -0.948517 -1.05695 -1.12601 -1.152 -1.11841\n",
      "   7 2.764e-01 5.488e+01 4.687e+01 -- -4.745e+01 -- 0.288807 -0.20359 -1.129 -1.33421 -1.50858 -1.56203 -1.54725\n",
      "   8 2.123e-01 4.884e+01 3.703e+01 -- -1.042e+01 -- 0.290741 -0.199424 -1.16697 -1.47951 -1.82761 -1.93862 -1.97495\n",
      "   9 1.660e-01 3.761e+01 2.500e+01 -- 1.458e+01 -- 0.297078 -0.192793 -1.17471 -1.51254 -2.03046 -2.24008 -2.39415\n",
      "  10 1.251e-01 2.218e+01 1.352e+01 -- 2.810e+01 -- 0.304071 -0.185609 -1.18142 -1.51049 -2.10848 -2.41366 -2.79148\n",
      "  11 8.256e-02 9.018e+00 5.492e+00 -- 3.359e+01 -- 0.305677 -0.180534 -1.18507 -1.51162 -2.12584 -2.46833 -3.14066\n",
      "  12 4.067e-02 2.560e+00 1.439e+00 -- 3.503e+01 -- 0.30378 -0.178308 -1.18784 -1.51647 -2.12974 -2.48272 -3.39994\n",
      "  13 1.216e-02 5.340e-01 2.063e-01 -- 3.524e+01 -- 0.301773 -0.177939 -1.18966 -1.52028 -2.13067 -2.48953 -3.5382\n",
      "  14 2.104e-03 8.200e-02 1.337e-02 -- 3.525e+01 -- 0.30075 -0.178052 -1.19052 -1.52208 -2.13075 -2.49214 -3.58123\n",
      "  15 2.833e-04 1.082e-02 3.730e-04 -- 3.525e+01 -- 0.300445 -0.178142 -1.19077 -1.52264 -2.13068 -2.4928 -3.58876\n",
      "  16 3.684e-05 1.402e-03 6.992e-06 -- 3.525e+01 -- 0.300387 -0.178169 -1.19082 -1.52276 -2.13064 -2.4929 -3.58978\n",
      "********************\n",
      "0.300387 -0.178169 -1.19082 -1.52276 -2.13064 -2.4929 -3.58978\n",
      "0.23893 0.202426 0.232625 0.177239 0.153017 0.132987 0.308424\n",
      "-0.000180614 -0.000143998 -0.000174906 -0.000705814 0.000447101 -0.000873593 -0.00140183\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 3.481e+01 3.004e-01 5.393e-01 0.89 +++\n",
      "+++ 3.525e+01 3.432e+01 3.004e-01 6.588e-01 1.87 +++\n",
      "+++ 3.525e+01 3.458e+01 3.004e-01 5.990e-01 1.34 +++\n",
      "+++ 3.525e+01 3.470e+01 3.004e-01 5.692e-01 1.11 +++\n",
      "+++ 3.525e+01 3.475e+01 3.004e-01 5.543e-01 0.996 +++\n",
      "\t### errors for param 1 ###\n",
      "+++ 3.525e+01 3.476e+01 -1.782e-01 2.426e-02 0.974 +++\n",
      "+++ 3.525e+01 3.422e+01 -1.782e-01 1.255e-01 2.07 +++\n",
      "+++ 3.525e+01 3.451e+01 -1.782e-01 7.486e-02 1.48 +++\n",
      "+++ 3.525e+01 3.464e+01 -1.782e-01 4.956e-02 1.21 +++\n",
      "+++ 3.525e+01 3.471e+01 -1.782e-01 3.691e-02 1.09 +++\n",
      "+++ 3.525e+01 3.474e+01 -1.782e-01 3.058e-02 1.03 +++\n",
      "+++ 3.525e+01 3.475e+01 -1.782e-01 2.742e-02   1 +++\n",
      "\t### errors for param 2 ###\n",
      "+++ 3.525e+01 3.511e+01 -1.191e+00 -1.075e+00 0.275 +++\n",
      "+++ 3.525e+01 3.495e+01 -1.191e+00 -1.016e+00 0.597 +++\n",
      "+++ 3.525e+01 3.485e+01 -1.191e+00 -9.873e-01 0.798 +++\n",
      "+++ 3.525e+01 3.480e+01 -1.191e+00 -9.727e-01 0.909 +++\n",
      "+++ 3.525e+01 3.477e+01 -1.191e+00 -9.655e-01 0.966 +++\n",
      "+++ 3.525e+01 3.475e+01 -1.191e+00 -9.618e-01 0.995 +++\n",
      "\t### errors for param 3 ###\n",
      "+++ 3.525e+01 3.482e+01 -1.523e+00 -1.346e+00 0.861 +++\n",
      "+++ 3.525e+01 3.433e+01 -1.523e+00 -1.257e+00 1.85 +++\n",
      "+++ 3.525e+01 3.459e+01 -1.523e+00 -1.301e+00 1.32 +++\n",
      "+++ 3.525e+01 3.471e+01 -1.523e+00 -1.323e+00 1.08 +++\n",
      "+++ 3.525e+01 3.477e+01 -1.523e+00 -1.334e+00 0.967 +++\n",
      "+++ 3.525e+01 3.474e+01 -1.523e+00 -1.329e+00 1.02 +++\n",
      "+++ 3.525e+01 3.475e+01 -1.523e+00 -1.332e+00 0.994 +++\n",
      "\t### errors for param 4 ###\n",
      "+++ 3.525e+01 3.482e+01 -2.131e+00 -1.978e+00 0.868 +++\n",
      "+++ 3.525e+01 3.430e+01 -2.131e+00 -1.901e+00 1.9 +++\n",
      "+++ 3.525e+01 3.458e+01 -2.131e+00 -1.939e+00 1.34 +++\n",
      "+++ 3.525e+01 3.471e+01 -2.131e+00 -1.958e+00 1.09 +++\n",
      "+++ 3.525e+01 3.476e+01 -2.131e+00 -1.968e+00 0.977 +++\n",
      "+++ 3.525e+01 3.473e+01 -2.131e+00 -1.963e+00 1.03 +++\n",
      "+++ 3.525e+01 3.475e+01 -2.131e+00 -1.966e+00 1.01 +++\n",
      "\t### errors for param 5 ###\n",
      "+++ 3.525e+01 3.476e+01 -2.493e+00 -2.360e+00 0.992 +++\n",
      "\t### errors for param 6 ###\n",
      "+++ 3.525e+01 3.511e+01 -3.590e+00 -3.436e+00 0.274 +++\n",
      "+++ 3.525e+01 3.491e+01 -3.590e+00 -3.358e+00 0.68 +++\n",
      "+++ 3.525e+01 3.477e+01 -3.590e+00 -3.320e+00 0.971 +++\n",
      "+++ 3.525e+01 3.468e+01 -3.590e+00 -3.301e+00 1.14 +++\n",
      "+++ 3.525e+01 3.472e+01 -3.590e+00 -3.310e+00 1.05 +++\n",
      "+++ 3.525e+01 3.475e+01 -3.590e+00 -3.315e+00 1.01 +++\n",
      "+++ 3.525e+01 3.476e+01 -3.590e+00 -3.317e+00 0.991 +++\n",
      "********************\n",
      "0.300387 -0.178169 -1.19082 -1.52276 -2.13064 -2.4929 -3.58978\n",
      "0.253863 0.205589 0.22899 0.191086 0.164971 0.132987 0.27228\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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dQiqV4vr161SrVXK5HDdu3CCbzXa7LClS7kmQJElB7kmQpBPEfYtqqVcYEiTpBIYADSsP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\nn1ehj9IuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa601861750>"
      ]
     },
     "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 0x7fa6011ddf50>"
      ]
     },
     "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 4.366e-01 5.289e+01 inf -- -1.581e+02 -- 1 1 1 1 1 1 1\n",
      "   2 7.741e-01 5.224e+01 6.092e+01 -- -9.716e+01 -- 0.64151 0.582988 0.567078 0.568391 0.566833 0.565789 0.56338\n",
      "   3 3.418e+00 5.136e+01 5.853e+01 -- -3.863e+01 -- 0.388803 0.191096 0.136557 0.140188 0.135589 0.132301 0.127287\n",
      "   4 1.555e+00 5.020e+01 5.546e+01 -- 1.684e+01 -- 0.278504 -0.141428 -0.288802 -0.28161 -0.292287 -0.300033 -0.307779\n",
      "   5 5.853e-01 4.862e+01 5.209e+01 -- 6.893e+01 -- 0.251696 -0.361387 -0.704482 -0.692633 -0.715864 -0.730643 -0.741316\n",
      "   6 3.638e-01 4.653e+01 4.847e+01 -- 1.174e+02 -- 0.242093 -0.451675 -1.10227 -1.08525 -1.13485 -1.15797 -1.17191\n",
      "   7 2.636e-01 4.340e+01 4.346e+01 -- 1.609e+02 -- 0.240629 -0.481083 -1.4522 -1.44125 -1.54556 -1.57775 -1.59823\n",
      "   8 2.061e-01 3.824e+01 3.545e+01 -- 1.963e+02 -- 0.243061 -0.504278 -1.67538 -1.722 -1.93248 -1.97969 -2.01957\n",
      "   9 1.693e-01 3.015e+01 2.492e+01 -- 2.212e+02 -- 0.246578 -0.524331 -1.72708 -1.87967 -2.25718 -2.33983 -2.4357\n",
      "  10 1.458e-01 1.978e+01 1.425e+01 -- 2.355e+02 -- 0.254622 -0.533743 -1.72985 -1.91821 -2.45669 -2.6121 -2.84811\n",
      "  11 1.353e-01 1.021e+01 6.810e+00 -- 2.423e+02 -- 0.264297 -0.537479 -1.7301 -1.91543 -2.50815 -2.75364 -3.26334\n",
      "  12 1.464e-01 3.997e+00 3.032e+00 -- 2.453e+02 -- 0.268248 -0.539862 -1.72642 -1.91378 -2.49097 -2.79169 -3.705\n",
      "  13 2.296e-01 1.073e+00 1.223e+00 -- 2.465e+02 -- 0.268013 -0.541085 -1.72532 -1.91534 -2.4707 -2.79511 -4.24757\n",
      "  14 1.191e+00 1.664e-01 4.032e-01 -- 2.469e+02 -- 0.266953 -0.541769 -1.72481 -1.91721 -2.45806 -2.793 -5.22266\n",
      "  15 4.403e+02 2.073e-01 4.480e-02 -- 2.470e+02 -- 0.266181 -0.542036 -1.72478 -1.91832 -2.45194 -2.79147 -8\n",
      "  16 4.405e+02 2.177e-01 9.908e-05 -- 2.470e+02 -- 0.265853 -0.542082 -1.72492 -1.91871 -2.45034 -2.79121 -8\n",
      "********************\n",
      "0.265853 -0.542082 -1.72492 -1.91871 -2.45034 -2.79121 -8\n",
      "0.236507 0.210135 0.2567 0.193885 0.180857 0.168104 4543.34\n",
      "-0.00248404 -0.00270298 -0.00703597 -0.020554 -0.0555367 -0.217652 -0.000171146\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 0.854 +++\n",
      "+++ 2.470e+02 2.461e+02 2.658e-01 6.205e-01 1.8 +++\n",
      "+++ 2.470e+02 2.463e+02 2.658e-01 5.614e-01 1.29 +++\n",
      "+++ 2.470e+02 2.465e+02 2.658e-01 5.318e-01 1.06 +++\n",
      "+++ 2.470e+02 2.465e+02 2.658e-01 5.171e-01 0.956 +++\n",
      "+++ 2.470e+02 2.465e+02 2.658e-01 5.244e-01 1.01 +++\n",
      "\t### errors for param 1 ###\n",
      "+++ 2.470e+02 2.465e+02 -5.421e-01 -3.320e-01 0.961 +++\n",
      "+++ 2.470e+02 2.460e+02 -5.421e-01 -2.269e-01 2.03 +++\n",
      "+++ 2.470e+02 2.463e+02 -5.421e-01 -2.794e-01 1.45 +++\n",
      "+++ 2.470e+02 2.464e+02 -5.421e-01 -3.057e-01 1.2 +++\n",
      "+++ 2.470e+02 2.465e+02 -5.421e-01 -3.188e-01 1.08 +++\n",
      "+++ 2.470e+02 2.465e+02 -5.421e-01 -3.254e-01 1.02 +++\n",
      "+++ 2.470e+02 2.465e+02 -5.421e-01 -3.287e-01 0.989 +++\n",
      "+++ 2.470e+02 2.465e+02 -5.421e-01 -3.270e-01   1 +++\n",
      "\t### errors for param 2 ###\n",
      "+++ 2.470e+02 2.468e+02 -1.725e+00 -1.597e+00 0.298 +++\n",
      "+++ 2.470e+02 2.467e+02 -1.725e+00 -1.532e+00 0.648 +++\n",
      "+++ 2.470e+02 2.466e+02 -1.725e+00 -1.500e+00 0.867 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.725e+00 -1.484e+00 0.986 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.725e+00 -1.476e+00 1.05 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.725e+00 -1.480e+00 1.02 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.725e+00 -1.482e+00   1 +++\n",
      "\t### errors for param 3 ###\n",
      "+++ 2.470e+02 2.465e+02 -1.919e+00 -1.725e+00 0.916 +++\n",
      "+++ 2.470e+02 2.460e+02 -1.919e+00 -1.628e+00 1.97 +++\n",
      "+++ 2.470e+02 2.463e+02 -1.919e+00 -1.676e+00 1.4 +++\n",
      "+++ 2.470e+02 2.464e+02 -1.919e+00 -1.701e+00 1.15 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.919e+00 -1.713e+00 1.03 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.919e+00 -1.719e+00 0.971 +++\n",
      "+++ 2.470e+02 2.465e+02 -1.919e+00 -1.716e+00 0.999 +++\n",
      "\t### errors for param 4 ###\n",
      "+++ 2.470e+02 2.466e+02 -2.450e+00 -2.269e+00 0.84 +++\n",
      "+++ 2.470e+02 2.461e+02 -2.450e+00 -2.179e+00 1.87 +++\n",
      "+++ 2.470e+02 2.463e+02 -2.450e+00 -2.224e+00 1.3 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.450e+00 -2.247e+00 1.06 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.450e+00 -2.258e+00 0.947 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.450e+00 -2.252e+00   1 +++\n",
      "\t### errors for param 5 ###\n",
      "+++ 2.470e+02 2.465e+02 -2.791e+00 -2.623e+00 1.01 +++\n",
      "+++ 2.470e+02 2.469e+02 -2.791e+00 -2.707e+00 0.27 +++\n",
      "+++ 2.470e+02 2.467e+02 -2.791e+00 -2.665e+00 0.583 +++\n",
      "+++ 2.470e+02 2.466e+02 -2.791e+00 -2.644e+00 0.784 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.791e+00 -2.634e+00 0.895 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.791e+00 -2.628e+00 0.954 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.791e+00 -2.626e+00 0.984 +++\n",
      "+++ 2.470e+02 2.465e+02 -2.791e+00 -2.624e+00 0.999 +++\n",
      "\t### errors for param 6 ###\n",
      "+++ 2.470e+02 2.470e+02 -8.000e+00 -6.000e+00 0.0147 +++\n",
      "+++ 2.470e+02 2.469e+02 -8.000e+00 -5.000e+00 0.151 +++\n",
      "+++ 2.470e+02 2.467e+02 -8.000e+00 -4.500e+00 0.489 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.250e+00 0.891 +++\n",
      "+++ 2.470e+02 2.464e+02 -8.000e+00 -4.125e+00 1.21 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.188e+00 1.04 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.219e+00 0.961 +++\n",
      "+++ 2.470e+02 2.465e+02 -8.000e+00 -4.203e+00 0.998 +++\n",
      "********************\n",
      "0.265765 -0.5421 -1.72494 -1.9188 -2.45004 -2.79121 -8\n",
      "0.258682 0.215059 0.242662 0.202981 0.197785 0.166791 3.79688\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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UGc8NDAxENl4uIeGl4cdE/NvhjwfP1eiee+6hrq7uXE0kSapYYb84p9Np6uvr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\nP/5eAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa601598990>"
      ]
     },
     "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 2.269e+03 1.198e+01 inf -- 3.072e+02 -- -0.016924 -0.660135 -1.75788 -2.02078 -2.59034 -2.94206 -6.09489 0.1 0.1 0.1 0.1 0.1 0.1 0.1\n",
      "   3 1.973e+01 1.431e+01 2.169e+00 -- 3.094e+02 -- 0.013775 -0.617135 -1.71294 -1.98677 -2.55944 -2.92003 -5.79489 0.0404501 0.0959497 0.114729 0.117623 0.0757218 0.113097 -2.34566\n",
      "   5 1.376e+02 1.686e+01 2.089e+00 -- 3.115e+02 -- 0.040954 -0.582314 -1.67663 -1.9585 -2.5335 -2.90131 -6.09489 -0.00586333 0.0932507 0.124785 0.131208 0.0569706 0.123911 1.99582\n",
      "   7 4.464e+02 1.966e+01 1.915e+00 -- 3.134e+02 -- 0.064849 -0.55355 -1.64669 -1.9347 -2.51145 -2.88524 -5.79489 -0.0424971 0.0914217 0.131924 0.142018 0.0422318 0.133023 -0.334542\n",
      "   9 3.480e+01 2.272e+01 1.812e+00 -- 3.152e+02 -- 0.0858141 -0.529439 -1.62163 -1.91445 -2.49256 -2.87136 -5.49489 -0.0719278 0.0901783 0.137158 0.150801 0.0304433 0.140833 2.03211\n",
      "  11 1.002e+01 2.607e+01 1.783e+00 -- 3.170e+02 -- 0.104218 -0.509001 -1.60042 -1.89706 -2.47621 -2.85932 -5.19489 -0.0958829 0.089339 0.141038 0.158083 0.0208371 0.147639 1.24275\n",
      "  13 7.968e+03 2.974e+01 1.627e+00 -- 3.186e+02 -- 0.120402 -0.491519 -1.58231 -1.88202 -2.46198 -2.8488 -4.89489 -0.115613 0.088809 0.143973 0.164209 0.0130572 0.153636 -0.00200163\n",
      "  15 7.700e+00 3.372e+01 1.748e+00 -- 3.204e+02 -- 0.134664 -0.476455 -1.56672 -1.86894 -2.44956 -2.83954 -4.59489 -0.132041 0.088517 0.146286 0.169375 0.00677842 0.158969 1.59295\n",
      "  17 2.375e+01 3.806e+01 2.026e+00 -- 3.224e+02 -- 0.147265 -0.463405 -1.55325 -1.85749 -2.43853 -2.83144 -4.29489 -0.145779 0.0883846 0.147915 0.173914 0.00155918 0.163793 0.96984\n",
      "  19 1.222e+01 4.277e+01 1.856e+00 -- 3.243e+02 -- 0.158428 -0.452038 -1.54155 -1.84743 -2.4288 -2.82406 -4.10712 -0.157385 0.0884563 0.149176 0.177908 -0.0021446 0.168153 0.95096\n",
      "  21 3.757e+00 4.786e+01 1.686e+00 -- 3.260e+02 -- 0.168341 -0.442099 -1.53136 -1.83856 -2.42015 -2.81739 -3.99633 -0.167232 0.0886703 0.150095 0.181462 -0.00476573 0.172153 0.946458\n",
      "  23 1.719e+00 5.335e+01 1.565e+00 -- 3.275e+02 -- 0.17716 -0.433379 -1.52245 -1.8307 -2.41246 -2.81134 -3.9178 -0.175626 0.0889884 0.150755 0.184625 -0.00655603 0.175857 0.945111\n",
      "  25 7.670e-01 5.926e+01 1.462e+00 -- 3.290e+02 -- 0.185022 -0.425705 -1.51464 -1.82371 -2.40559 -2.80587 -3.85771 -0.18281 0.0893847 0.151217 0.187442 -0.00768333 0.179309 0.944998\n",
      "  27 3.271e-01 6.558e+01 1.371e+00 -- 3.304e+02 -- 0.192044 -0.418936 -1.50777 -1.81749 -2.39945 -2.80089 -3.80967 -0.188981 0.0898403 0.151526 0.189953 -0.00827265 0.182546 0.945473\n",
      "  29 2.839e-01 7.234e+01 1.288e+00 -- 3.316e+02 -- 0.198326 -0.412951 -1.50172 -1.81194 -2.39395 -2.79637 -3.77014 -0.194296 0.0903402 0.151717 0.192191 -0.0084207 0.185594 0.946256\n",
      "  31 6.344e-01 7.952e+01 1.212e+00 -- 3.328e+02 -- 0.203957 -0.407649 -1.49638 -1.80697 -2.38902 -2.79224 -3.73694 -0.198885 0.0908733 0.151818 0.194187 -0.00820387 0.188473 0.9472\n",
      "  33 1.008e+00 8.711e+01 1.140e+00 -- 3.340e+02 -- 0.20901 -0.402946 -1.49167 -1.80251 -2.38459 -2.78847 -3.70862 -0.202854 0.0914304 0.151849 0.195966 -0.00768338 0.1912 0.948221\n",
      "  35 1.430e+00 9.512e+01 1.074e+00 -- 3.351e+02 -- 0.213553 -0.398767 -1.4875 -1.79849 -2.3806 -2.78502 -3.68416 -0.206293 0.0920046 0.151828 0.197549 -0.00690885 0.193787 0.949267\n",
      "  37 1.972e+00 1.035e+02 1.010e+00 -- 3.361e+02 -- 0.217642 -0.395048 -1.48381 -1.79488 -2.37701 -2.78186 -3.66283 -0.209276 0.0925904 0.151767 0.198956 -0.00592089 0.196245 0.950302\n",
      "  38 1.386e+01 2.586e+03 1.075e+01 -- 3.468e+02 -- 0.254492 -0.361933 -1.45115 -1.76223 -2.34466 -2.75279 -3.47522 -0.235177 0.0985198 0.150868 0.211428 0.00575786 0.2196 0.960307\n",
      "  40 4.847e+00 1.291e+03 4.830e-01 -- 3.473e+02 -- 0.254339 -0.36196 -1.45129 -1.7616 -2.34565 -2.75065 -3.47325 -0.238184 0.0984132 0.154637 0.207337 0.0137373 0.221423 0.959887\n",
      "  42 2.820e+00 7.911e+02 2.689e-01 -- 3.476e+02 -- 0.254314 -0.362014 -1.45138 -1.76102 -2.34642 -2.7488 -3.47177 -0.240479 0.0987825 0.157405 0.204131 0.0203959 0.222522 0.958597\n",
      "  44 1.927e+00 5.366e+02 1.843e-01 -- 3.478e+02 -- 0.254352 -0.362079 -1.45146 -1.76045 -2.34705 -2.74718 -3.47058 -0.24227 0.0993579 0.159522 0.201533 0.0261467 0.223117 0.956931\n",
      "  45 6.846e-01 2.491e+03 7.144e-01 -- 3.470e+02 -- 0.255087 -0.362762 -1.45206 -1.75508 -2.35235 -2.73284 -3.4608 -0.256273 0.106036 0.17597 0.180236 0.0765365 0.225273 0.938514\n",
      "  47 3.859e-01 7.440e+02 1.045e+00 -- 3.481e+02 -- 0.255642 -0.362946 -1.45188 -1.75441 -2.35202 -2.735 -3.46127 -0.253243 0.107817 0.170909 0.185077 0.0713684 0.20985 0.938462\n",
      "  49 2.428e-01 4.740e+02 3.238e-01 -- 3.484e+02 -- 0.255958 -0.36305 -1.45177 -1.75394 -2.35178 -2.73606 -3.46158 -0.25133 0.108819 0.167827 0.187945 0.0689457 0.201752 0.937949\n",
      "  50 1.845e+00 3.237e+04 3.382e+00 -- 3.450e+02 -- 0.258014 -0.363678 -1.45096 -1.74999 -2.35001 -2.74182 -3.46363 -0.23749 0.114761 0.147522 0.2072 0.0566519 0.152758 0.930353\n",
      "  52 5.341e-01 2.738e+03 3.310e+00 -- 3.483e+02 -- 0.256859 -0.363253 -1.45121 -1.74947 -2.35141 -2.73938 -3.46259 -0.241519 0.110174 0.1534 0.199686 0.0671039 0.167388 0.929964\n",
      "  54 2.673e-01 4.258e+02 4.126e-01 -- 3.488e+02 -- 0.256513 -0.363117 -1.45131 -1.74933 -2.35166 -2.73828 -3.46219 -0.242924 0.108757 0.155979 0.197112 0.0706881 0.173906 0.929109\n",
      "  56 1.484e-01 7.070e+02 1.233e-01 -- 3.489e+02 -- 0.256358 -0.363054 -1.45135 -1.74924 -2.35169 -2.73765 -3.46198 -0.243691 0.108123 0.157394 0.195813 0.0725777 0.177563 0.928277\n",
      "  57 2.633e+00 1.761e+05 5.893e+00 -- 3.430e+02 -- 0.255689 -0.362752 -1.45153 -1.74846 -2.35114 -2.73373 -3.46071 -0.248243 0.105285 0.165654 0.188899 0.0833473 0.19847 0.920537\n",
      "  59 5.986e-01 4.834e+03 6.298e+00 -- 3.493e+02 -- 0.25881 -0.363072 -1.45138 -1.74823 -2.34996 -2.73665 -3.46097 -0.236008 0.109215 0.161791 0.19747 0.0614059 0.167187 0.920664\n",
      "  61 1.056e-01 1.057e+04 3.624e-01 -- 3.497e+02 -- 0.259231 -0.363167 -1.45134 -1.74818 -2.34961 -2.73738 -3.46105 -0.234491 0.110247 0.160667 0.199701 0.0577301 0.160365 0.920596\n",
      "  63 9.832e-02 1.198e+04 8.624e-02 -- 3.497e+02 -- 0.259256 -0.363199 -1.45132 -1.74815 -2.34952 -2.73761 -3.46108 -0.234434 0.110544 0.160282 0.200426 0.0572685 0.158672 0.920487\n",
      "  65 1.477e-01 1.320e+04 5.481e-02 -- 3.498e+02 -- 0.259155 -0.363209 -1.45131 -1.74812 -2.34952 -2.73767 -3.46109 -0.234836 0.110592 0.160145 0.20064 0.0578316 0.158622 0.920373\n",
      "  66 5.254e-01 1.244e+05 1.134e+00 -- 3.509e+02 -- 0.257792 -0.363238 -1.45127 -1.74783 -2.34977 -2.73779 -3.46112 -0.240158 0.110293 0.159591 0.201062 0.0663719 0.163096 0.919291\n",
      "  68 2.702e-02 4.790e+05 6.404e-01 -- 3.516e+02 -- 0.256458 -0.363212 -1.45128 -1.74783 -2.34996 -2.7376 -3.4611 -0.248024 0.109945 0.159825 0.200359 0.0698593 0.166007 0.919278\n",
      "  70 7.753e-03 5.328e+05 5.502e-02 -- 3.516e+02 -- 0.256548 -0.363213 -1.45128 -1.74783 -2.34995 -2.73761 -3.4611 -0.247354 0.109964 0.159811 0.200397 0.0696895 0.165854 0.919275\n",
      "  71 4.990e-02 5.349e+08 2.391e+00 -- 3.540e+02 -- 0.256515 -0.363211 -1.45128 -1.74782 -2.34996 -2.73759 -3.4611 -0.246413 0.109926 0.159825 0.200321 0.0702298 0.166204 0.919243\n",
      "  73 1.883e-01 1.908e+08 7.849e-01 -- 3.548e+02 -- 0.256638 -0.363212 -1.45128 -1.74782 -2.34995 -2.7376 -3.4611 -0.245184 0.109938 0.159816 0.200349 0.0700951 0.166094 0.919244\n",
      "  75 3.505e-01 1.280e+10 5.592e+00 -- 3.492e+02 -- 0.256429 -0.363212 -1.45128 -1.74782 -2.34996 -2.73759 -3.4611 -0.2498 0.109944 0.15982 0.200324 0.0701695 0.16617 0.919243\n",
      "  76 7.399e-01 4.729e+08 1.154e+01 -- 3.377e+02 -- 0.255205 -0.363227 -1.45127 -1.74784 -2.34981 -2.73775 -3.46111 -0.162247 0.110105 0.15966 0.201149 0.0677482 0.164465 0.919251\n",
      "  78 1.590e-01 5.754e+06 1.469e+01 -- 3.524e+02 -- 0.253232 -0.363205 -1.45128 -1.74785 -2.34999 -2.73758 -3.46109 -0.174252 0.109807 0.15986 0.200551 0.0708851 0.16699 0.919246\n",
      "  80 5.807e-02 1.303e+07 7.214e-01 -- 3.531e+02 -- 0.253726 -0.36321 -1.45127 -1.74785 -2.34994 -2.73762 -3.4611 -0.171481 0.109878 0.159812 0.200693 0.0701441 0.166393 0.919247\n",
      "  82 6.557e-03 1.579e+07 9.480e-02 -- 3.532e+02 -- 0.253613 -0.363209 -1.45127 -1.74785 -2.34995 -2.73761 -3.4611 -0.172477 0.109861 0.159824 0.200658 0.0703205 0.166534 0.919247\n",
      "  84 6.675e-03 1.765e+07 5.646e-02 -- 3.532e+02 -- 0.253648 -0.363209 -1.45127 -1.74785 -2.34995 -2.73761 -3.4611 -0.172493 0.109866 0.15982 0.200667 0.0702744 0.166497 0.919247\n",
      "  86 1.405e-02 1.962e+07 5.316e-02 -- 3.533e+02 -- 0.253645 -0.363209 -1.45127 -1.74785 -2.34995 -2.73761 -3.4611 -0.172608 0.109865 0.159821 0.200664 0.070284 0.166504 0.919247\n",
      "  87 2.371e+00 3.577e+10 6.090e-01 -- 3.539e+02 -- 0.25362 -0.36321 -1.45127 -1.74785 -2.34995 -2.73762 -3.4611 -0.175034 0.10987 0.159819 0.200659 0.0702718 0.166492 0.919246\n",
      "  91 6.875e-01 6.345e+10 1.055e+00 -- 3.528e+02 -- 0.253591 -0.36321 -1.45127 -1.74785 -2.34995 -2.73762 -3.4611 -0.174619 0.109871 0.159819 0.200661 0.0702715 0.166492 0.919246\n",
      "  94 8.161e+00 6.043e+11 1.715e+01 -- 3.357e+02 -- 0.253529 -0.36321 -1.45127 -1.74785 -2.34995 -2.73762 -3.4611 -0.175819 0.109861 0.159819 0.200658 0.0702745 0.16649 0.919246\n",
      "  96 2.611e-01 3.717e+08 9.546e+00 -- 3.452e+02 -- 0.257412 -0.363213 -1.45128 -1.74782 -2.34996 -2.73763 -3.4611 -0.319306 0.109793 0.159798 0.200183 0.0701731 0.16621 0.919236\n",
      "  98 3.737e-02 1.435e+07 7.911e+00 -- 3.531e+02 -- 0.258178 -0.363226 -1.45127 -1.74781 -2.34985 -2.73772 -3.46111 -0.312069 0.109964 0.159681 0.20055 0.0683407 0.164732 0.919241\n",
      " 100 4.006e-03 2.110e+07 1.702e-01 -- 3.533e+02 -- 0.25807 -0.363224 -1.45127 -1.74782 -2.34987 -2.73771 -3.46111 -0.312793 0.10994 0.159697 0.200499 0.0685961 0.164939 0.919241\n",
      " 102 5.577e-03 2.351e+07 5.453e-02 -- 3.534e+02 -- 0.258084 -0.363224 -1.45127 -1.74782 -2.34987 -2.73771 -3.46111 -0.312702 0.109943 0.159695 0.200505 0.0685686 0.164916 0.919241\n",
      " 104 6.916e-03 2.613e+07 5.344e-02 -- 3.534e+02 -- 0.258079 -0.363224 -1.45127 -1.74782 -2.34987 -2.73771 -3.46111 -0.312527 0.109942 0.159696 0.200505 0.0685733 0.16492 0.919241\n",
      " 105 6.197e+00 8.850e+11 1.956e+01 -- 3.339e+02 -- 0.258065 -0.363224 -1.45127 -1.74782 -2.34987 -2.73771 -3.46111 -0.314689 0.109936 0.159698 0.200489 0.0686299 0.164957 0.91924\n",
      " 106 2.457e+00 5.060e+05 4.423e+01 -- 2.896e+02 -- 0.25217 -0.363236 -1.45128 -1.74787 -2.35122 -2.73772 -3.46109 -2.26495 0.107765 0.159324 0.193074 0.0661005 0.165589 0.919229\n",
      " 108 9.160e-01 1.076e+06 4.129e+01 -- 3.309e+02 -- 0.190213 -0.363421 -1.45121 -1.74789 -2.34962 -2.73898 -3.46119 -2.20299 0.109386 0.15792 0.199777 0.0502385 0.149847 0.919513\n",
      " 110 7.545e-01 1.842e+06 3.241e+00 -- 3.342e+02 -- 0.172789 -0.363413 -1.45121 -1.7479 -2.34968 -2.73894 -3.46119 -2.16833 0.109263 0.157968 0.199848 0.0508925 0.150441 0.919501\n",
      " 112 6.604e-01 2.413e+06 1.815e+00 -- 3.360e+02 -- 0.159752 -0.363413 -1.45121 -1.74791 -2.34967 -2.73895 -3.46119 -2.14156 0.109248 0.157963 0.200007 0.0508058 0.150387 0.9195\n",
      " 114 5.952e-01 3.001e+06 1.236e+00 -- 3.372e+02 -- 0.149202 -0.363414 -1.45121 -1.74791 -2.34966 -2.73896 -3.46119 -2.11865 0.10925 0.157953 0.20014 0.0506565 0.150272 0.9195\n",
      " 116 5.401e-01 3.623e+06 9.191e-01 -- 3.381e+02 -- 0.140322 -0.363414 -1.4512 -1.74792 -2.34964 -2.73897 -3.46119 -2.09844 0.109254 0.157944 0.200248 0.0505214 0.150164 0.9195\n",
      " 118 4.946e-01 4.287e+06 7.180e-01 -- 3.389e+02 -- 0.132742 -0.363415 -1.4512 -1.74792 -2.34963 -2.73898 -3.46119 -2.08012 0.10926 0.157935 0.200335 0.0504064 0.150071 0.919501\n",
      " 120 4.554e-01 5.002e+06 5.840e-01 -- 3.394e+02 -- 0.126177 -0.363416 -1.4512 -1.74792 -2.34962 -2.73898 -3.46119 -2.06319 0.109265 0.157928 0.200408 0.0503087 0.14999 0.919501\n",
      " 122 4.163e-01 5.781e+06 4.883e-01 -- 3.399e+02 -- 0.120431 -0.363416 -1.4512 -1.74792 -2.34961 -2.73899 -3.46119 -2.04749 0.10927 0.157922 0.200469 0.0502247 0.14992 0.919501\n",
      " 124 3.856e-01 6.633e+06 4.091e-01 -- 3.403e+02 -- 0.115418 -0.363417 -1.4512 -1.74793 -2.34961 -2.739 -3.46119 -2.03366 0.109275 0.157917 0.200521 0.0501519 0.149858 0.919501\n",
      " 126 3.459e-01 7.569e+06 3.539e-01 -- 3.407e+02 -- 0.110968 -0.363417 -1.4512 -1.74793 -2.3496 -2.739 -3.46119 -2.02099 0.109279 0.157912 0.200566 0.0500901 0.149806 0.919501\n",
      " 128 3.257e-01 8.604e+06 2.868e-01 -- 3.410e+02 -- 0.10713 -0.363417 -1.4512 -1.74793 -2.34959 -2.739 -3.4612 -2.01203 0.109283 0.157908 0.200604 0.0500359 0.14976 0.919502\n",
      " 130 2.677e-01 9.741e+06 2.645e-01 -- 3.412e+02 -- 0.10364 -0.363418 -1.4512 -1.74793 -2.34959 -2.73901 -3.4612 -2.00265 0.109286 0.157905 0.200636 0.0499941 0.149724 0.919502\n",
      " 132 2.564e-01 1.094e+07 2.420e-01 -- 3.415e+02 -- 0.100866 -0.363418 -1.4512 -1.74793 -2.34959 -2.73901 -3.4612 -1.991 0.109289 0.157902 0.200663 0.0499572 0.14969 0.919502\n",
      " 134 2.658e-01 1.231e+07 2.111e-01 -- 3.417e+02 -- 0.0982797 -0.363418 -1.4512 -1.74793 -2.34958 -2.73901 -3.4612 -1.98223 0.109291 0.157899 0.200689 0.0499203 0.149658 0.919502\n",
      " 136 2.061e-01 1.381e+07 2.284e-01 -- 3.419e+02 -- 0.095667 -0.363418 -1.4512 -1.74793 -2.34958 -2.73901 -3.4612 -1.97018 0.109293 0.157897 0.200713 0.0498902 0.149631 0.919502\n",
      " 138 2.448e-01 1.549e+07 1.683e-01 -- 3.421e+02 -- 0.0936952 -0.363418 -1.4512 -1.74793 -2.34958 -2.73902 -3.4612 -1.96336 0.109297 0.157894 0.200734 0.0498553 0.1496 0.919502\n",
      " 140 1.932e-01 1.745e+07 1.492e-01 -- 3.422e+02 -- 0.0914011 -0.363419 -1.4512 -1.74793 -2.34957 -2.73902 -3.4612 -1.96101 0.109298 0.157892 0.200752 0.0498304 0.14958 0.919502\n",
      " 142 1.543e-01 1.951e+07 1.616e-01 -- 3.424e+02 -- 0.0896351 -0.363419 -1.4512 -1.74793 -2.34957 -2.73902 -3.4612 -1.95324 0.109299 0.157891 0.200767 0.0498145 0.149565 0.919502\n",
      " 144 1.977e-01 2.183e+07 1.088e-01 -- 3.425e+02 -- 0.0882519 -0.363419 -1.4512 -1.74793 -2.34957 -2.73902 -3.4612 -1.95169 0.109301 0.157889 0.200779 0.0497925 0.149546 0.919502\n",
      " 146 2.223e-01 2.449e+07 1.198e-01 -- 3.426e+02 -- 0.0865074 -0.363419 -1.4512 -1.74793 -2.34957 -2.73902 -3.4612 -1.95019 0.109302 0.157888 0.200791 0.0497808 0.149537 0.919502\n",
      " 148 1.483e-01 2.753e+07 1.474e-01 -- 3.428e+02 -- 0.084584 -0.363419 -1.4512 -1.74793 -2.34956 -2.73902 -3.4612 -1.94508 0.109302 0.157888 0.200805 0.0497691 0.149528 0.919502\n",
      " 150 1.690e-01 3.082e+07 8.624e-02 -- 3.429e+02 -- 0.0833299 -0.363419 -1.4512 -1.74793 -2.34956 -2.73902 -3.4612 -1.9461 0.109303 0.157886 0.200815 0.0497502 0.149512 0.919502\n",
      " 152 1.762e-01 3.449e+07 1.188e-01 -- 3.430e+02 -- 0.0819216 -0.363419 -1.4512 -1.74793 -2.34956 -2.73902 -3.4612 -1.94249 0.109303 0.157886 0.200824 0.049743 0.149507 0.919502\n",
      " 154 1.238e-01 3.866e+07 1.240e-01 -- 3.431e+02 -- 0.0804781 -0.363419 -1.4512 -1.74793 -2.34956 -2.73902 -3.4612 -1.93818 0.109303 0.157885 0.200835 0.0497304 0.149497 0.919502\n",
      " 156 1.139e-01 4.323e+07 8.517e-02 -- 3.432e+02 -- 0.079482 -0.363419 -1.4512 -1.74793 -2.34956 -2.73902 -3.4612 -1.93786 0.109305 0.157884 0.200843 0.049715 0.149485 0.919503\n",
      " 157 4.942e-02 2.466e+07 9.311e-01 -- 3.441e+02 -- 0.0704267 -0.363418 -1.4512 -1.74794 -2.34957 -2.73903 -3.4612 -1.77759 0.1093 0.15788 0.200952 0.0496793 0.149428 0.919498\n",
      " 159 8.388e-02 3.418e+07 1.894e-01 -- 3.443e+02 -- 0.0700786 -0.36342 -1.4512 -1.74794 -2.34955 -2.73904 -3.4612 -1.77245 0.109321 0.157867 0.200998 0.0494922 0.149273 0.9195\n",
      " 160 4.666e-01 2.671e+08 9.403e-01 -- 3.453e+02 -- 0.0642006 -0.363422 -1.4512 -1.74794 -2.34953 -2.73906 -3.4612 -1.69928 0.109349 0.157846 0.201123 0.0492057 0.149018 0.9195\n",
      " 161 6.172e+00 9.031e+05 6.135e+00 -- 3.391e+02 -- 0.0572531 -0.363415 -1.4512 -1.74794 -2.34959 -2.73898 -3.46119 -2.49218 0.1092 0.157938 0.20046 0.0506396 0.150192 0.919509\n",
      " 163 1.463e+01 1.084e+06 1.303e+00 -- 3.404e+02 -- 0.0219138 -0.363415 -1.4512 -1.74794 -2.34957 -2.739 -3.46119 -2.43778 0.109224 0.15792 0.200646 0.0504673 0.149985 0.919507\n",
      " 165 2.912e+01 1.297e+06 9.553e-01 -- 3.414e+02 -- -0.0101463 -0.363418 -1.4512 -1.74794 -2.34954 -2.73902 -3.4612 -2.38182 0.109267 0.157892 0.200829 0.0501465 0.149663 0.919507\n",
      " 167 6.809e+00 1.524e+06 7.449e-01 -- 3.421e+02 -- -0.0396938 -0.36342 -1.4512 -1.74795 -2.34952 -2.73904 -3.4612 -2.32367 0.109303 0.15787 0.200977 0.0498882 0.1494 0.919507\n",
      " 169 3.698e+00 1.765e+06 5.996e-01 -- 3.427e+02 -- -0.0667198 -0.363421 -1.4512 -1.74795 -2.3495 -2.73905 -3.4612 -2.26425 0.109332 0.157852 0.201095 0.0496903 0.149192 0.919507\n",
      " 171 2.425e+00 2.021e+06 4.993e-01 -- 3.432e+02 -- -0.0913899 -0.363422 -1.4512 -1.74795 -2.34949 -2.73907 -3.4612 -2.20346 0.109355 0.157838 0.201191 0.0495391 0.149027 0.919507\n",
      " 173 1.738e+00 2.292e+06 4.250e-01 -- 3.436e+02 -- -0.113555 -0.363423 -1.4512 -1.74795 -2.34948 -2.73908 -3.4612 -2.14116 0.109374 0.157827 0.20127 0.0494225 0.148895 0.919506\n",
      " 175 1.307e+00 2.583e+06 3.649e-01 -- 3.440e+02 -- -0.133292 -0.363424 -1.4512 -1.74795 -2.34947 -2.73908 -3.4612 -2.0796 0.10939 0.157817 0.201335 0.049332 0.148788 0.919506\n",
      " 177 1.047e+00 2.895e+06 3.223e-01 -- 3.443e+02 -- -0.150718 -0.363424 -1.4512 -1.74795 -2.34946 -2.73909 -3.4612 -2.01741 0.109403 0.15781 0.201391 0.0492627 0.148701 0.919505\n",
      " 179 8.090e-01 3.236e+06 2.859e-01 -- 3.446e+02 -- -0.166497 -0.363425 -1.4512 -1.74795 -2.34945 -2.73909 -3.4612 -1.95757 0.109414 0.157804 0.201439 0.0492083 0.14863 0.919505\n",
      " 181 6.080e-01 3.601e+06 2.585e-01 -- 3.449e+02 -- -0.179967 -0.363425 -1.4512 -1.74795 -2.34945 -2.7391 -3.4612 -1.89744 0.109423 0.157799 0.20148 0.0491661 0.148572 0.919504\n",
      " 182 2.539e-01 3.660e+07 2.576e+00 -- 3.475e+02 -- -0.289393 -0.363427 -1.45119 -1.74796 -2.34941 -2.73913 -3.46121 -1.30909 0.109498 0.157756 0.201827 0.0488447 0.148088 0.919499\n",
      " 184 4.016e-01 5.855e+07 2.221e-01 -- 3.477e+02 -- -0.282045 -0.363425 -1.45119 -1.74796 -2.34943 -2.73912 -3.46121 -1.30097 0.10948 0.157768 0.201786 0.0490279 0.148229 0.919497\n",
      " 186 3.091e-01 6.932e+07 2.593e-03 -- 3.477e+02 -- -0.27144 -0.363425 -1.45119 -1.74796 -2.34943 -2.73912 -3.46121 -1.35322 0.10948 0.15777 0.201757 0.0490685 0.148251 0.919497\n",
      " 187 2.851e-01 7.479e+06 1.835e+00 -- 3.458e+02 -- -0.321756 -0.363424 -1.4512 -1.74796 -2.34944 -2.73911 -3.46121 -1.77155 0.109467 0.157782 0.201631 0.0492586 0.148401 0.919498\n",
      " 188 2.336e-01 2.433e+07 2.960e-01 -- 3.455e+02 -- -0.374916 -0.363436 -1.45119 -1.74795 -2.34932 -2.73919 -3.46121 -1.26642 0.109638 0.157681 0.202071 0.0478576 0.147162 0.919505\n",
      " 190 1.438e-01 1.271e+07 1.388e+00 -- 3.469e+02 -- -0.381149 -0.363427 -1.45119 -1.74796 -2.3494 -2.73914 -3.46121 -1.23684 0.109523 0.157749 0.201855 0.0489144 0.148006 0.919497\n",
      " 192 1.187e-01 1.489e+07 1.009e-01 -- 3.470e+02 -- -0.380686 -0.363426 -1.45119 -1.74796 -2.34942 -2.73913 -3.46121 -1.21905 0.109507 0.157758 0.201826 0.049072 0.148126 0.919496\n",
      " 193 2.616e+00 1.803e+07 9.241e-01 -- 3.480e+02 -- -0.385652 -0.363423 -1.45119 -1.74796 -2.34943 -2.73912 -3.46121 -1.07438 0.109491 0.157771 0.201807 0.0493538 0.148299 0.919493\n",
      " 194 5.869e-01 1.719e+09 1.149e+01 -- 3.365e+02 -- -0.106959 -0.363434 -1.45119 -1.74797 -2.34929 -2.73922 -3.46122 1.73606 0.109587 0.15766 0.202786 0.047551 0.147005 0.919497\n",
      " 196 1.130e-01 9.258e+07 9.800e+00 -- 3.463e+02 -- -0.113236 -0.363424 -1.45119 -1.74797 -2.34939 -2.73916 -3.46121 1.65362 0.109461 0.157728 0.202605 0.0485995 0.147848 0.919488\n",
      " 198 2.772e+00 1.481e+08 2.691e-01 -- 3.465e+02 -- -0.11407 -0.363423 -1.45119 -1.74797 -2.3494 -2.73915 -3.46121 1.63494 0.109445 0.157735 0.20259 0.0487043 0.147935 0.919487\n",
      " 199 2.169e+00 1.764e+06 2.451e+00 -- 3.441e+02 -- -0.430263 -0.363426 -1.45119 -1.74795 -2.34941 -2.73915 -3.46121 -3.05269 0.109524 0.157742 0.201897 0.0488874 0.147882 0.919492\n",
      " 201 1.913e+00 2.072e+06 3.862e-01 -- 3.445e+02 -- -0.523586 -0.363424 -1.45119 -1.74795 -2.34943 -2.73914 -3.46121 -3.00172 0.109506 0.157754 0.201892 0.049131 0.148027 0.919488\n",
      " 203 1.779e+00 2.384e+06 3.220e-01 -- 3.448e+02 -- -0.623769 -0.363423 -1.45119 -1.74795 -2.34943 -2.73914 -3.46121 -2.9345 0.109515 0.15775 0.20193 0.0491329 0.147982 0.919486\n",
      " 205 1.694e+00 2.724e+06 2.804e-01 -- 3.451e+02 -- -0.734739 -0.363423 -1.45119 -1.74795 -2.34943 -2.73915 -3.46121 -2.8405 0.109525 0.157746 0.201967 0.0491169 0.147929 0.919485\n",
      " 207 1.635e+00 3.084e+06 2.445e-01 -- 3.453e+02 -- -0.85919 -0.363423 -1.45119 -1.74795 -2.34943 -2.73915 -3.46121 -2.70669 0.109533 0.157742 0.201998 0.0491085 0.147887 0.919483\n",
      " 209 1.600e+00 3.438e+06 2.122e-01 -- 3.455e+02 -- -0.999683 -0.363423 -1.45119 -1.74795 -2.34943 -2.73915 -3.46121 -2.50076 0.109539 0.157739 0.202024 0.0491084 0.147855 0.919482\n",
      " 211 2.671e+00 3.755e+06 1.835e-01 -- 3.457e+02 -- -1.15968 -0.363423 -1.45119 -1.74795 -2.34943 -2.73915 -3.46121 -2.16708 0.109544 0.157737 0.202047 0.0491139 0.147832 0.919481\n",
      " 213 5.748e+00 3.882e+06 1.403e-01 -- 3.459e+02 -- -1.29788 -0.363423 -1.45119 -1.74795 -2.34944 -2.73915 -3.46121 -1.58825 0.109548 0.157736 0.202067 0.0491226 0.147813 0.91948\n",
      " 215 6.833e+00 3.560e+06 8.682e-02 -- 3.459e+02 -- -1.27817 -0.363423 -1.45119 -1.74795 -2.34944 -2.73916 -3.46121 -0.6754 0.109551 0.157734 0.202086 0.0491335 0.147798 0.919479\n",
      " 217 2.427e+00 3.223e+06 1.398e-01 -- 3.461e+02 -- -0.980173 -0.363423 -1.45119 -1.74795 -2.34944 -2.73916 -3.46121 -0.213922 0.109556 0.157733 0.202103 0.0491447 0.14778 0.919478\n",
      " 219 1.487e+00 3.453e+06 2.184e-01 -- 3.463e+02 -- -0.786827 -0.363422 -1.45119 -1.74795 -2.34944 -2.73916 -3.46121 -0.162012 0.109559 0.157732 0.202119 0.0491691 0.147769 0.919477\n",
      " 221 1.150e+00 3.793e+06 2.018e-01 -- 3.465e+02 -- -0.669794 -0.363422 -1.45119 -1.74795 -2.34944 -2.73916 -3.46121 -0.139676 0.109561 0.157732 0.202129 0.0492111 0.147775 0.919475\n",
      " 223 1.019e+00 4.201e+06 1.765e-01 -- 3.467e+02 -- -0.592793 -0.363422 -1.45119 -1.74795 -2.34945 -2.73916 -3.46121 -0.12627 0.109561 0.157733 0.202135 0.0492592 0.147788 0.919474\n",
      " 225 8.538e-01 4.676e+06 1.677e-01 -- 3.468e+02 -- -0.532414 -0.363421 -1.45119 -1.74795 -2.34945 -2.73915 -3.46121 -0.119629 0.10956 0.157734 0.202139 0.0493085 0.147804 0.919473\n",
      " 227 8.801e-01 5.212e+06 1.505e-01 -- 3.470e+02 -- -0.486958 -0.363421 -1.45119 -1.74795 -2.34945 -2.73915 -3.46121 -0.114455 0.10956 0.157736 0.202142 0.0493586 0.147824 0.919472\n",
      " 229 6.974e-01 5.828e+06 1.558e-01 -- 3.472e+02 -- -0.444102 -0.36342 -1.45119 -1.74795 -2.34946 -2.73915 -3.46121 -0.111906 0.109558 0.157737 0.202144 0.0494072 0.147843 0.919471\n",
      " 231 7.119e-01 6.497e+06 1.325e-01 -- 3.473e+02 -- -0.41313 -0.36342 -1.45119 -1.74795 -2.34946 -2.73915 -3.46121 -0.105843 0.109556 0.157739 0.202144 0.0494579 0.147868 0.91947\n",
      " 233 5.442e-01 7.244e+06 1.335e-01 -- 3.474e+02 -- -0.383719 -0.36342 -1.45119 -1.74795 -2.34946 -2.73915 -3.46121 -0.0984818 0.109554 0.157741 0.202145 0.0495033 0.147889 0.919469\n",
      " 235 1.131e+00 8.076e+06 1.137e-01 -- 3.475e+02 -- -0.362839 -0.363419 -1.45119 -1.74795 -2.34947 -2.73915 -3.46121 -0.0938439 0.109552 0.157743 0.202143 0.0495491 0.147913 0.919469\n",
      " 237 3.653e-01 8.999e+06 1.361e-01 -- 3.477e+02 -- -0.335364 -0.363419 -1.45119 -1.74795 -2.34947 -2.73915 -3.46121 -0.0832267 0.10955 0.157744 0.202146 0.0495886 0.147933 0.919468\n",
      " 239 3.363e-01 1.004e+07 9.350e-02 -- 3.478e+02 -- -0.323113 -0.363418 -1.45119 -1.74795 -2.34947 -2.73914 -3.46121 -0.0832685 0.109547 0.157747 0.202141 0.0496366 0.147961 0.919467\n",
      " 241 1.247e+00 1.121e+07 8.989e-02 -- 3.478e+02 -- -0.312392 -0.363418 -1.45119 -1.74795 -2.34947 -2.73914 -3.46121 -0.0860685 0.109546 0.157748 0.202138 0.0496699 0.147977 0.919467\n",
      " 243 4.749e-01 1.245e+07 1.061e-01 -- 3.480e+02 -- -0.295953 -0.363418 -1.45119 -1.74795 -2.34948 -2.73914 -3.46121 -0.0753345 0.109544 0.157749 0.202141 0.049698 0.147993 0.919466\n",
      " 245 6.925e-01 1.386e+07 8.248e-02 -- 3.480e+02 -- -0.287411 -0.363418 -1.45119 -1.74795 -2.34948 -2.73914 -3.46121 -0.0717567 0.109542 0.157751 0.202138 0.0497334 0.148014 0.919466\n",
      " 247 2.983e+00 1.541e+07 5.421e-02 -- 3.481e+02 -- -0.28685 -0.363417 -1.45119 -1.74795 -2.34948 -2.73914 -3.46121 -0.0667875 0.109541 0.157752 0.202135 0.0497581 0.148028 0.919466\n",
      " 248 1.312e+00 2.319e+07 5.164e-01 -- 3.486e+02 -- -0.185228 -0.363417 -1.45119 -1.74795 -2.34947 -2.73914 -3.46121 0.132449 0.109541 0.157752 0.202202 0.0498364 0.148059 0.919464\n",
      " 250 1.351e+00 2.829e+07 1.424e-01 -- 3.488e+02 -- -0.170989 -0.363415 -1.45119 -1.74795 -2.34949 -2.73913 -3.46121 0.149822 0.109523 0.157762 0.202181 0.0499928 0.148185 0.919463\n",
      " 251 4.563e+00 1.588e+08 1.471e+00 -- 3.473e+02 -- -0.220484 -0.36341 -1.4512 -1.74795 -2.34955 -2.7391 -3.46121 -0.0525833 0.109471 0.157803 0.201972 0.0506843 0.148669 0.919457\n",
      " 253 4.464e+00 5.169e+07 1.638e+00 -- 3.489e+02 -- -0.228996 -0.363414 -1.45119 -1.74795 -2.34951 -2.73913 -3.46121 -0.0765774 0.109532 0.157768 0.202077 0.050136 0.148227 0.91946\n",
      " 254 1.174e+00 1.462e+08 2.584e+00 -- 3.463e+02 -- -0.165269 -0.363424 -1.45119 -1.74795 -2.3494 -2.73918 -3.46121 0.26524 0.109648 0.157698 0.202403 0.0490414 0.147404 0.919469\n",
      " 256 3.140e-01 3.210e+07 2.338e+00 -- 3.487e+02 -- -0.184679 -0.363416 -1.45119 -1.74795 -2.34947 -2.73913 -3.46121 0.254255 0.109557 0.157753 0.202214 0.0499032 0.148084 0.919464\n",
      " 258 1.020e+00 3.780e+07 5.449e-02 -- 3.487e+02 -- -0.189584 -0.363416 -1.45119 -1.74795 -2.34948 -2.73913 -3.46121 0.262239 0.109548 0.157759 0.202195 0.049992 0.148154 0.919463\n",
      " 259 9.690e-01 1.442e+07 3.727e-01 -- 3.484e+02 -- -0.0646749 -0.363416 -1.45119 -1.74796 -2.34945 -2.73913 -3.46121 0.529609 0.109531 0.157755 0.202322 0.0499443 0.148158 0.919466\n",
      " 261 5.802e-01 2.148e+07 2.027e-01 -- 3.486e+02 -- -0.0584081 -0.363414 -1.45119 -1.74796 -2.34947 -2.73911 -3.46121 0.526988 0.109501 0.157773 0.202272 0.0502225 0.148376 0.919464\n",
      " 263 2.171e+00 2.442e+07 8.307e-02 -- 3.486e+02 -- -0.0550193 -0.363413 -1.45119 -1.74796 -2.34948 -2.73911 -3.46121 0.523608 0.109493 0.157777 0.202259 0.0503048 0.148438 0.919463\n",
      " 265 1.244e+00 2.695e+07 7.115e-02 -- 3.487e+02 -- -0.0430724 -0.363413 -1.45119 -1.74796 -2.34948 -2.73911 -3.46121 0.533686 0.109488 0.157779 0.202264 0.0503385 0.148465 0.919463\n",
      " 267 5.411e-01 3.028e+07 6.665e-02 -- 3.488e+02 -- -0.037713 -0.363412 -1.45119 -1.74796 -2.34948 -2.7391 -3.46121 0.538519 0.109482 0.157783 0.202258 0.0503975 0.148511 0.919463\n",
      " 269 5.807e-01 3.469e+07 1.242e-01 -- 3.489e+02 -- -0.0397535 -0.363412 -1.45119 -1.74796 -2.34949 -2.7391 -3.46121 0.509938 0.109479 0.157785 0.202246 0.0504397 0.148535 0.919462\n",
      " 271 9.263e-01 3.892e+07 8.342e-02 -- 3.490e+02 -- -0.0420622 -0.363411 -1.45119 -1.74796 -2.34949 -2.7391 -3.46121 0.49377 0.109477 0.157787 0.202237 0.0504718 0.148554 0.919461\n",
      " 273 1.045e+00 4.354e+07 8.479e-02 -- 3.491e+02 -- -0.0381661 -0.363411 -1.45119 -1.74796 -2.3495 -2.7391 -3.46121 0.48762 0.109476 0.157788 0.202238 0.0504836 0.14856 0.919461\n",
      " 275 6.628e-01 4.858e+07 4.584e-02 -- 3.491e+02 -- -0.0341795 -0.363411 -1.45119 -1.74796 -2.3495 -2.7391 -3.46121 0.498943 0.109473 0.15779 0.202236 0.0505139 0.148586 0.919461\n",
      " 277 3.138e+00 5.585e+07 1.196e-01 -- 3.492e+02 -- -0.031914 -0.363411 -1.45119 -1.74796 -2.3495 -2.7391 -3.46121 0.48038 0.10947 0.157791 0.202233 0.0505361 0.148596 0.91946\n",
      " 278 1.106e+00 3.818e+07 1.331e+00 -- 3.479e+02 -- -0.132049 -0.363407 -1.4512 -1.74796 -2.34957 -2.73908 -3.46121 0.209795 0.109439 0.157817 0.202029 0.0510012 0.148874 0.919453\n",
      " 280 3.299e-01 3.189e+07 1.021e+00 -- 3.489e+02 -- -0.138042 -0.363412 -1.45119 -1.74795 -2.34952 -2.73911 -3.46121 0.186601 0.109503 0.15778 0.202137 0.0504273 0.148408 0.919456\n",
      " 282 1.357e+00 3.797e+07 6.512e-02 -- 3.490e+02 -- -0.142597 -0.363412 -1.45119 -1.74795 -2.34951 -2.73912 -3.46121 0.187456 0.109515 0.157773 0.202156 0.0503221 0.148322 0.919457\n",
      " 284 3.374e-01 4.168e+07 2.378e-02 -- 3.490e+02 -- -0.16194 -0.363413 -1.45119 -1.74795 -2.34951 -2.73912 -3.46121 0.171472 0.109522 0.157771 0.202147 0.0502934 0.148293 0.919457\n",
      " 286 1.284e+00 4.784e+07 8.469e-02 -- 3.491e+02 -- -0.157165 -0.363413 -1.45119 -1.74795 -2.34951 -2.73912 -3.46121 0.177257 0.109529 0.157766 0.202164 0.0502281 0.14824 0.919457\n",
      " 287 5.863e+00 2.746e+07 7.569e-01 -- 3.483e+02 -- -0.0125226 -0.363413 -1.45119 -1.74795 -2.34949 -2.73912 -3.46121 0.404916 0.109511 0.157767 0.202299 0.0502314 0.148274 0.919458\n",
      " 289 1.630e+00 3.365e+07 9.013e-01 -- 3.492e+02 -- -0.0198645 -0.363408 -1.4512 -1.74796 -2.34953 -2.73909 -3.46121 0.404159 0.109451 0.157802 0.202181 0.0507898 0.148716 0.919454\n",
      " 291 6.748e+00 3.775e+07 7.961e-02 -- 3.493e+02 -- -0.0166256 -0.363408 -1.4512 -1.74796 -2.34954 -2.73909 -3.46121 0.400832 0.109447 0.157805 0.202176 0.0508312 0.148746 0.919454\n",
      " 293 2.863e+00 4.073e+07 4.445e-02 -- 3.493e+02 -- -0.00540687 -0.363408 -1.4512 -1.74796 -2.34953 -2.73909 -3.46121 0.422946 0.109441 0.157807 0.202184 0.050862 0.148775 0.919454\n",
      " 295 1.589e+01 4.688e+07 9.607e-02 -- 3.494e+02 -- -0.00385862 -0.363407 -1.4512 -1.74796 -2.34954 -2.73908 -3.46121 0.414394 0.109434 0.157811 0.202171 0.0509315 0.148827 0.919453\n",
      " 297 9.102e+01 5.176e+07 5.621e-02 -- 3.495e+02 -- 0.00227262 -0.363407 -1.4512 -1.74796 -2.34954 -2.73908 -3.46121 0.424492 0.109429 0.157813 0.202172 0.0509648 0.148855 0.919453\n",
      " 298 1.218e+00 1.223e+06 2.212e+00 -- 3.473e+02 -- -0.204579 -0.363401 -1.4512 -1.74795 -2.34966 -2.73907 -3.4612 -0.153771 0.109419 0.157847 0.201763 0.0516137 0.149147 0.91944\n",
      " 300 7.366e-01 5.541e+06 7.566e-01 -- 3.480e+02 -- -0.179665 -0.363411 -1.4512 -1.74794 -2.34957 -2.73913 -3.46121 -0.141308 0.109542 0.157774 0.202006 0.0505035 0.148242 0.919447\n",
      " 302 6.563e-01 6.257e+06 1.223e-01 -- 3.481e+02 -- -0.166432 -0.363412 -1.4512 -1.74794 -2.34956 -2.73913 -3.46121 -0.136129 0.109556 0.157767 0.202034 0.0504092 0.14815 0.919447\n",
      " 304 6.204e-01 6.962e+06 1.049e-01 -- 3.482e+02 -- -0.155509 -0.363411 -1.4512 -1.74794 -2.34956 -2.73913 -3.46121 -0.128246 0.109555 0.157768 0.202033 0.0504491 0.148168 0.919446\n",
      " 306 6.510e-01 7.764e+06 1.013e-01 -- 3.483e+02 -- -0.14586 -0.363411 -1.4512 -1.74794 -2.34956 -2.73913 -3.46121 -0.123823 0.109552 0.157771 0.202028 0.050505 0.1482 0.919446\n",
      " 308 3.481e-01 8.654e+06 1.011e-01 -- 3.484e+02 -- -0.136364 -0.36341 -1.4512 -1.74794 -2.34957 -2.73913 -3.46121 -0.117368 0.109549 0.157773 0.202024 0.0505599 0.148233 0.919445\n",
      " 310 4.054e-01 9.652e+06 7.879e-02 -- 3.485e+02 -- -0.131618 -0.36341 -1.4512 -1.74794 -2.34957 -2.73912 -3.46121 -0.117155 0.109545 0.157776 0.202015 0.0506154 0.148266 0.919444\n",
      " 312 5.584e-01 1.075e+07 8.122e-02 -- 3.486e+02 -- -0.126283 -0.36341 -1.4512 -1.74794 -2.34957 -2.73912 -3.46121 -0.115499 0.109544 0.157777 0.202011 0.0506528 0.148287 0.919444\n",
      " 314 4.952e-01 1.200e+07 9.239e-02 -- 3.487e+02 -- -0.119231 -0.363409 -1.4512 -1.74794 -2.34958 -2.73912 -3.46121 -0.115658 0.109542 0.157779 0.202007 0.0506895 0.148307 0.919443\n",
      " 316 5.287e-01 1.338e+07 8.527e-02 -- 3.488e+02 -- -0.113326 -0.363409 -1.4512 -1.74794 -2.34958 -2.73912 -3.46121 -0.111769 0.109538 0.157781 0.202002 0.0507334 0.148335 0.919443\n",
      " 318 8.017e-01 1.491e+07 8.643e-02 -- 3.489e+02 -- -0.107335 -0.363409 -1.4512 -1.74794 -2.34958 -2.73912 -3.46121 -0.108356 0.109536 0.157783 0.201998 0.0507734 0.14836 0.919442\n",
      " 319 2.149e+01 1.344e+08 1.285e+00 -- 3.502e+02 -- -0.0771257 -0.363406 -1.4512 -1.74794 -2.3496 -2.7391 -3.46121 -0.0214826 0.109506 0.157804 0.20197 0.0511631 0.148633 0.91944\n",
      " 322 5.016e+01 1.083e+08 7.733e-02 -- 3.501e+02 -- -0.0812549 -0.363406 -1.4512 -1.74794 -2.3496 -2.7391 -3.46121 -0.0261001 0.109507 0.157803 0.201968 0.0511544 0.148625 0.91944\n",
      " 325 1.441e+01 1.887e+08 2.246e-01 -- 3.503e+02 -- -0.0735921 -0.363406 -1.4512 -1.74794 -2.3496 -2.7391 -3.46121 -0.0130075 0.109508 0.157802 0.201979 0.0511409 0.148617 0.91944\n",
      " 328 7.901e+01 1.536e+08 9.576e-02 -- 3.502e+02 -- -0.0797361 -0.363406 -1.4512 -1.74794 -2.3496 -2.7391 -3.46121 -0.0148821 0.109509 0.157802 0.201976 0.0511349 0.148612 0.91944\n",
      " 331 1.082e+01 1.784e+08 6.179e-02 -- 3.503e+02 -- -0.0795032 -0.363406 -1.4512 -1.74794 -2.3496 -2.7391 -3.46121 -0.0266401 0.10951 0.157801 0.201974 0.0511287 0.148603 0.91944\n",
      " 333 4.675e+01 2.786e+08 1.995e-01 -- 3.505e+02 -- -0.0809661 -0.363407 -1.4512 -1.74794 -2.3496 -2.7391 -3.46121 -0.0554529 0.109514 0.157797 0.201978 0.0510476 0.148535 0.91944\n",
      " 334 5.032e+00 2.430e+05 6.301e+00 -- 3.442e+02 -- -0.985862 -0.363409 -1.4512 -1.74792 -2.3498 -2.73912 -3.4612 -2.64765 0.109732 0.157802 0.200524 0.0514617 0.148271 0.919427\n",
      " 336 1.413e+01 2.950e+05 3.625e-01 -- 3.445e+02 -- -1.28586 -0.363418 -1.4512 -1.74791 -2.3497 -2.73918 -3.46121 -1.84183 0.109927 0.157714 0.2008 0.0506701 0.147252 0.919428\n",
      " 338 4.005e+01 3.176e+05 1.360e-01 -- 3.447e+02 -- -1.46152 -0.363418 -1.4512 -1.74791 -2.34969 -2.73919 -3.46121 0.760727 0.109999 0.157695 0.200857 0.0507901 0.147055 0.919422\n",
      " 340 6.766e+00 4.153e+05 6.549e-02 -- 3.446e+02 -- -1.16152 -0.363417 -1.4512 -1.74791 -2.34969 -2.7392 -3.46121 -2.28614 0.110051 0.157686 0.200882 0.0510196 0.146972 0.919414\n",
      " 342 2.742e+01 4.570e+05 2.707e-01 -- 3.449e+02 -- -1.46152 -0.363415 -1.4512 -1.7479 -2.3497 -2.73919 -3.46121 -0.739337 0.110077 0.157687 0.200893 0.0513039 0.146999 0.919408\n",
      " 344 1.369e+01 4.823e+05 3.346e-02 -- 3.448e+02 -- -1.16152 -0.363414 -1.4512 -1.7479 -2.3497 -2.73919 -3.46121 1.28787 0.110109 0.157683 0.200916 0.0514964 0.146967 0.919402\n",
      " 346 9.597e+00 6.439e+05 3.666e-01 -- 3.452e+02 -- -1.08009 -0.363413 -1.45119 -1.7479 -2.3497 -2.73919 -3.46121 -0.475334 0.110141 0.157677 0.200944 0.051654 0.146914 0.919397\n",
      " 348 3.843e+01 6.683e+05 2.895e-01 -- 3.455e+02 -- -0.780091 -0.363412 -1.45119 -1.7479 -2.34971 -2.73919 -3.46121 -0.0191557 0.110155 0.157679 0.200954 0.051853 0.146942 0.919392\n",
      " 350 2.431e+00 7.534e+05 4.815e-01 -- 3.460e+02 -- -0.516668 -0.363411 -1.45119 -1.7479 -2.34971 -2.73919 -3.46121 -0.0927694 0.110174 0.157677 0.20097 0.0519999 0.146932 0.919388\n",
      " 352 2.128e+00 8.462e+05 3.602e-01 -- 3.463e+02 -- -0.391053 -0.363409 -1.4512 -1.7479 -2.34972 -2.73919 -3.46121 -0.102471 0.110182 0.15768 0.200966 0.0522036 0.146984 0.919383\n",
      " 354 1.958e+00 9.507e+05 3.104e-01 -- 3.466e+02 -- -0.307832 -0.363408 -1.4512 -1.7479 -2.34973 -2.73918 -3.46121 -0.105727 0.110186 0.157686 0.200953 0.0524185 0.147058 0.919379\n",
      " 356 1.882e+00 1.068e+06 2.733e-01 -- 3.469e+02 -- -0.247561 -0.363406 -1.4512 -1.7479 -2.34974 -2.73917 -3.46121 -0.106268 0.110186 0.157693 0.200935 0.0526364 0.147146 0.919376\n",
      " 358 1.839e+00 1.199e+06 2.470e-01 -- 3.472e+02 -- -0.200962 -0.363405 -1.4512 -1.7479 -2.34976 -2.73916 -3.46121 -0.105856 0.110183 0.1577 0.200914 0.0528519 0.147243 0.919372\n",
      " 360 1.795e+00 1.346e+06 2.241e-01 -- 3.474e+02 -- -0.164003 -0.363403 -1.4512 -1.7479 -2.34977 -2.73916 -3.46121 -0.105114 0.110179 0.157708 0.20089 0.053063 0.147344 0.919369\n",
      " 362 1.817e+00 1.511e+06 2.017e-01 -- 3.476e+02 -- -0.134568 -0.363402 -1.4512 -1.7479 -2.34978 -2.73915 -3.46121 -0.103975 0.110173 0.157716 0.200865 0.053267 0.147448 0.919366\n",
      " 364 1.856e+00 1.694e+06 1.860e-01 -- 3.478e+02 -- -0.110116 -0.3634 -1.4512 -1.7479 -2.34979 -2.73914 -3.46121 -0.103075 0.110167 0.157724 0.200841 0.0534605 0.14755 0.919364\n",
      " 366 1.880e+00 1.899e+06 1.714e-01 -- 3.479e+02 -- -0.089674 -0.363399 -1.4512 -1.7479 -2.3498 -2.73913 -3.46121 -0.101649 0.110159 0.157732 0.200816 0.0536444 0.14765 0.919361\n",
      " 368 1.968e+00 2.128e+06 1.562e-01 -- 3.481e+02 -- -0.0728171 -0.363398 -1.4512 -1.74789 -2.34981 -2.73912 -3.46121 -0.100506 0.110152 0.157739 0.200792 0.053818 0.147747 0.919359\n",
      " 370 2.101e+00 2.382e+06 1.448e-01 -- 3.483e+02 -- -0.0584857 -0.363396 -1.4512 -1.74789 -2.34982 -2.73912 -3.46121 -0.099281 0.110145 0.157747 0.200769 0.0539785 0.147839 0.919357\n",
      " 372 2.314e+00 2.665e+06 1.350e-01 -- 3.484e+02 -- -0.0461955 -0.363395 -1.4512 -1.74789 -2.34983 -2.73911 -3.46121 -0.0980682 0.110138 0.157753 0.200747 0.0541276 0.147925 0.919355\n",
      " 374 2.560e+00 2.981e+06 1.272e-01 -- 3.485e+02 -- -0.0355074 -0.363394 -1.4512 -1.74789 -2.34984 -2.7391 -3.46121 -0.0975489 0.110131 0.15776 0.200727 0.0542661 0.148006 0.919354\n",
      " 376 2.984e+00 3.332e+06 1.180e-01 -- 3.486e+02 -- -0.0264176 -0.363393 -1.4512 -1.74789 -2.34985 -2.7391 -3.46121 -0.0966277 0.110124 0.157766 0.200707 0.0543948 0.148083 0.919352\n",
      " 378 3.745e+00 3.724e+06 1.111e-01 -- 3.487e+02 -- -0.0185355 -0.363392 -1.4512 -1.74789 -2.34985 -2.73909 -3.46121 -0.0961985 0.110118 0.157771 0.200689 0.0545125 0.148154 0.919351\n",
      " 380 5.245e+00 4.158e+06 1.050e-01 -- 3.488e+02 -- -0.0115937 -0.363392 -1.4512 -1.74789 -2.34986 -2.73909 -3.46121 -0.0949656 0.110112 0.157777 0.200673 0.0546199 0.148219 0.919349\n",
      " 382 9.697e+00 4.642e+06 9.994e-02 -- 3.489e+02 -- -0.00551311 -0.363391 -1.4512 -1.74789 -2.34987 -2.73908 -3.46121 -0.0945279 0.110106 0.157781 0.200657 0.0547192 0.148279 0.919348\n",
      " 384 2.565e+02 5.180e+06 9.454e-02 -- 3.490e+02 -- -0.000167303 -0.36339 -1.4512 -1.74789 -2.34987 -2.73908 -3.46121 -0.0931954 0.110101 0.157786 0.200644 0.0548099 0.148335 0.919347\n",
      " 386 9.880e+00 5.780e+06 8.805e-02 -- 3.491e+02 -- 0.00412335 -0.36339 -1.4512 -1.74789 -2.34988 -2.73907 -3.46121 -0.093928 0.110096 0.15779 0.20063 0.0548933 0.148386 0.919346\n",
      " 388 4.224e+00 6.439e+06 8.467e-02 -- 3.492e+02 -- 0.00819704 -0.363389 -1.4512 -1.74789 -2.34988 -2.73907 -3.46121 -0.0916356 0.110092 0.157793 0.20062 0.054964 0.14843 0.919346\n",
      " 390 2.907e+00 7.178e+06 8.143e-02 -- 3.493e+02 -- 0.0116595 -0.363389 -1.4512 -1.74789 -2.34988 -2.73907 -3.46121 -0.0913694 0.110088 0.157797 0.200609 0.0550314 0.148472 0.919345\n",
      " 392 1.516e+00 7.995e+06 8.031e-02 -- 3.494e+02 -- 0.0150489 -0.363388 -1.4512 -1.74789 -2.34989 -2.73907 -3.46121 -0.0900351 0.110084 0.1578 0.2006 0.0550912 0.148509 0.919344\n",
      " 394 2.049e+00 8.907e+06 7.170e-02 -- 3.494e+02 -- 0.0173306 -0.363388 -1.4512 -1.74789 -2.34989 -2.73906 -3.46121 -0.0887767 0.11008 0.157802 0.200591 0.0551488 0.148546 0.919344\n",
      " 396 8.714e-01 9.911e+06 8.151e-02 -- 3.495e+02 -- 0.020882 -0.363387 -1.4512 -1.74789 -2.34989 -2.73906 -3.46121 -0.0870916 0.110078 0.157805 0.200585 0.0551934 0.148573 0.919343\n",
      " 398 9.679e-01 1.107e+07 7.197e-02 -- 3.496e+02 -- 0.0227018 -0.363387 -1.4512 -1.74789 -2.3499 -2.73906 -3.46121 -0.0909551 0.110074 0.157808 0.200573 0.0552522 0.14861 0.919343\n",
      " 400 1.270e+00 1.232e+07 7.128e-02 -- 3.497e+02 -- 0.024899 -0.363387 -1.4512 -1.74789 -2.3499 -2.73906 -3.46121 -0.0902504 0.110072 0.15781 0.200567 0.0552904 0.148634 0.919342\n",
      " 402 6.361e-01 1.367e+07 7.507e-02 -- 3.497e+02 -- 0.0280603 -0.363386 -1.4512 -1.74789 -2.3499 -2.73905 -3.46121 -0.0837997 0.110068 0.157811 0.200565 0.0553281 0.14866 0.919342\n",
      " 404 8.794e-01 1.528e+07 6.816e-02 -- 3.498e+02 -- 0.0292014 -0.363386 -1.4512 -1.74789 -2.34991 -2.73905 -3.46121 -0.0891302 0.110065 0.157814 0.200552 0.0553829 0.148695 0.919341\n",
      " 406 3.784e-01 1.697e+07 7.227e-02 -- 3.499e+02 -- 0.0317693 -0.363386 -1.4512 -1.74789 -2.34991 -2.73905 -3.46121 -0.0855337 0.110063 0.157816 0.200551 0.0554098 0.148713 0.919341\n",
      " 408 8.584e-01 1.892e+07 6.373e-02 -- 3.500e+02 -- 0.0329715 -0.363385 -1.4512 -1.74789 -2.34991 -2.73905 -3.46121 -0.0840924 0.110059 0.157818 0.200544 0.0554524 0.148743 0.919341\n",
      " 410 2.281e-01 2.102e+07 7.585e-02 -- 3.500e+02 -- 0.0358016 -0.363385 -1.4512 -1.74789 -2.34991 -2.73905 -3.46121 -0.0818116 0.110057 0.15782 0.200541 0.0554798 0.148761 0.91934\n",
      " 412 2.994e-01 2.352e+07 5.761e-02 -- 3.501e+02 -- 0.0358705 -0.363385 -1.4512 -1.74789 -2.34991 -2.73904 -3.46121 -0.0836779 0.110053 0.157822 0.200531 0.0555267 0.148795 0.91934\n",
      " 414 7.158e-01 2.615e+07 5.648e-02 -- 3.501e+02 -- 0.0361137 -0.363385 -1.4512 -1.74789 -2.34991 -2.73904 -3.46121 -0.086183 0.110053 0.157823 0.200528 0.0555391 0.148801 0.91934\n",
      " 415 4.481e+00 7.672e+07 5.225e-01 -- 3.507e+02 -- 0.027996 -0.363384 -1.4512 -1.74789 -2.34993 -2.73904 -3.46121 -0.147877 0.110054 0.157826 0.200473 0.0556367 0.148828 0.919338\n",
      " 418 2.687e+00 9.990e+07 3.995e-02 -- 3.506e+02 -- 0.0267416 -0.363384 -1.4512 -1.74789 -2.34993 -2.73904 -3.46121 -0.148469 0.110055 0.157825 0.200475 0.0556202 0.148816 0.919338\n",
      " 421 9.609e+00 8.090e+07 3.507e-02 -- 3.507e+02 -- 0.026023 -0.363384 -1.4512 -1.74789 -2.34992 -2.73904 -3.46121 -0.144961 0.110057 0.157824 0.200481 0.0556034 0.148804 0.919338\n",
      " 423 8.329e+00 2.967e+08 1.085e+00 -- 3.496e+02 -- 0.0510295 -0.363386 -1.4512 -1.74789 -2.3499 -2.73905 -3.46121 -0.0496008 0.110067 0.157813 0.200579 0.0554229 0.148684 0.91934\n",
      " 425 9.815e-01 4.106e+07 1.153e+00 -- 3.507e+02 -- 0.0367336 -0.363383 -1.4512 -1.74789 -2.34993 -2.73903 -3.4612 -0.0909145 0.110038 0.157835 0.200479 0.055778 0.148952 0.919338\n",
      " 427 1.774e+00 2.140e+08 4.961e-01 -- 3.512e+02 -- 0.03879 -0.363384 -1.4512 -1.74789 -2.34992 -2.73904 -3.46121 -0.0998381 0.110055 0.157825 0.200503 0.0556283 0.14883 0.919338\n",
      " 428 1.829e+01 3.065e+08 7.322e-02 -- 3.513e+02 -- 0.0449577 -0.363384 -1.4512 -1.74789 -2.3499 -2.73904 -3.46121 0.0772391 0.11003 0.157827 0.200623 0.0555725 0.148873 0.919341\n",
      " 430 2.067e+00 2.772e+09 7.286e+00 -- 3.440e+02 -- 0.0871111 -0.363384 -1.4512 -1.74789 -2.34988 -2.73904 -3.46121 0.218532 0.110015 0.157828 0.200722 0.0555747 0.148913 0.919342\n",
      " 433 9.668e-01 1.632e+09 2.268e+00 -- 3.463e+02 -- 0.0853101 -0.363384 -1.4512 -1.74789 -2.34989 -2.73903 -3.46121 0.215536 0.110009 0.157832 0.200707 0.0556372 0.148962 0.919342\n",
      " 435 2.233e+00 5.145e+08 3.823e+00 -- 3.501e+02 -- 0.0895547 -0.363379 -1.4512 -1.74789 -2.34993 -2.739 -3.4612 0.194698 0.109954 0.157866 0.200601 0.0561718 0.149374 0.919338\n",
      " 437 8.471e-01 1.114e+08 8.833e-01 -- 3.510e+02 -- 0.0957779 -0.363377 -1.4512 -1.74789 -2.34994 -2.73899 -3.4612 0.238181 0.109929 0.15788 0.200589 0.0563701 0.149554 0.919338\n",
      " 440 2.255e+00 1.662e+08 1.147e-01 -- 3.511e+02 -- 0.0949666 -0.363377 -1.4512 -1.7479 -2.34994 -2.73899 -3.4612 0.239067 0.109928 0.15788 0.200586 0.0563808 0.149563 0.919338\n",
      " 443 2.186e+00 2.435e+08 1.498e-01 -- 3.512e+02 -- 0.0928252 -0.363377 -1.4512 -1.7479 -2.34994 -2.73899 -3.4612 0.239188 0.109928 0.157881 0.200582 0.0563891 0.14957 0.919338\n",
      " 445 3.207e+00 4.072e+07 7.106e-01 -- 3.505e+02 -- 0.104422 -0.363377 -1.4512 -1.7479 -2.34993 -2.73899 -3.4612 0.291471 0.109923 0.157882 0.200614 0.0563947 0.149592 0.919339\n",
      " 446 3.453e+00 3.733e+06 4.698e+00 -- 3.458e+02 -- -0.0763908 -0.363361 -1.45121 -1.74788 -2.35021 -2.73891 -3.46119 -0.643341 0.10981 0.158001 0.199689 0.0585065 0.150869 0.919317\n",
      " 448 2.985e+00 1.422e+06 1.924e+00 -- 3.478e+02 -- -0.0500124 -0.36339 -1.4512 -1.74786 -2.34993 -2.7391 -3.46121 -0.583889 0.110183 0.157776 0.200426 0.0551411 0.148099 0.919337\n",
      " 450 3.389e+00 1.653e+06 2.223e-01 -- 3.480e+02 -- -0.0350817 -0.363393 -1.4512 -1.74786 -2.34989 -2.73912 -3.46121 -0.545114 0.110235 0.157748 0.200523 0.0547811 0.147759 0.919338\n",
      " 452 4.450e+00 1.833e+06 1.695e-01 -- 3.482e+02 -- -0.0231916 -0.363393 -1.4512 -1.74786 -2.34989 -2.73912 -3.46121 -0.515006 0.110238 0.15775 0.200522 0.0548683 0.147787 0.919337\n",
      " 454 7.001e+00 2.038e+06 1.566e-01 -- 3.483e+02 -- -0.0128712 -0.363392 -1.4512 -1.74786 -2.3499 -2.73911 -3.46121 -0.489289 0.110232 0.157756 0.200508 0.0550141 0.147866 0.919335\n",
      " 456 2.133e+01 2.270e+06 1.442e-01 -- 3.485e+02 -- -0.00386017 -0.36339 -1.4512 -1.74786 -2.34991 -2.7391 -3.46121 -0.467919 0.110226 0.157762 0.200491 0.0551616 0.14795 0.919333\n",
      " 458 1.676e+01 2.528e+06 1.371e-01 -- 3.486e+02 -- 0.00437402 -0.363389 -1.4512 -1.74786 -2.34991 -2.7391 -3.46121 -0.449042 0.11022 0.157769 0.200474 0.0553006 0.148032 0.919331\n",
      " 460 5.489e+00 2.814e+06 1.297e-01 -- 3.487e+02 -- 0.0117036 -0.363388 -1.4512 -1.74786 -2.34992 -2.73909 -3.46121 -0.431565 0.110213 0.157775 0.200459 0.0554329 0.148111 0.91933\n",
      " 462 3.102e+00 3.136e+06 1.197e-01 -- 3.488e+02 -- 0.018128 -0.363387 -1.4512 -1.74786 -2.34993 -2.73908 -3.46121 -0.41801 0.110206 0.157781 0.200442 0.0555588 0.148188 0.919329\n",
      " 464 2.085e+00 3.494e+06 1.125e-01 -- 3.490e+02 -- 0.0237512 -0.363387 -1.4512 -1.74786 -2.34993 -2.73908 -3.46121 -0.405779 0.1102 0.157786 0.200427 0.0556737 0.148258 0.919327\n",
      " 466 1.578e+00 3.891e+06 1.061e-01 -- 3.491e+02 -- 0.0287038 -0.363386 -1.4512 -1.74786 -2.34994 -2.73907 -3.46121 -0.394935 0.110194 0.157791 0.200413 0.0557793 0.148323 0.919326\n",
      " 468 1.215e+00 4.333e+06 1.019e-01 -- 3.492e+02 -- 0.0332333 -0.363385 -1.4512 -1.74786 -2.34994 -2.73907 -3.46121 -0.385103 0.110188 0.157796 0.2004 0.0558765 0.148384 0.919325\n",
      " 470 8.728e-01 4.825e+06 9.728e-02 -- 3.493e+02 -- 0.0372705 -0.363384 -1.4512 -1.74786 -2.34995 -2.73906 -3.46121 -0.376014 0.110183 0.1578 0.200388 0.0559674 0.148442 0.919324\n",
      " 472 7.791e-01 5.374e+06 8.909e-02 -- 3.494e+02 -- 0.0405235 -0.363384 -1.4512 -1.74786 -2.34995 -2.73906 -3.46121 -0.368803 0.110178 0.157805 0.200376 0.0560518 0.148496 0.919323\n",
      " 474 6.891e-01 5.981e+06 8.746e-02 -- 3.494e+02 -- 0.0436808 -0.363383 -1.4512 -1.74786 -2.34996 -2.73906 -3.46121 -0.362446 0.110173 0.157808 0.200366 0.0561246 0.148541 0.919323\n",
      " 476 5.921e-01 6.661e+06 8.541e-02 -- 3.495e+02 -- 0.0466909 -0.363383 -1.4512 -1.74786 -2.34996 -2.73905 -3.46121 -0.357513 0.110169 0.157812 0.200356 0.0561939 0.148585 0.919322\n",
      " 478 3.144e-01 7.415e+06 8.354e-02 -- 3.496e+02 -- 0.0494557 -0.363382 -1.4512 -1.74786 -2.34996 -2.73905 -3.46121 -0.352194 0.110165 0.157815 0.200346 0.0562588 0.148627 0.919321\n",
      " 480 4.451e-01 8.264e+06 7.056e-02 -- 3.497e+02 -- 0.0510106 -0.363382 -1.4512 -1.74786 -2.34997 -2.73905 -3.46121 -0.349714 0.110161 0.157818 0.200336 0.0563208 0.148667 0.919321\n",
      " 482 2.834e-01 9.191e+06 7.707e-02 -- 3.498e+02 -- 0.0532813 -0.363381 -1.4512 -1.74786 -2.34997 -2.73905 -3.46121 -0.346633 0.110159 0.15782 0.20033 0.0563633 0.148692 0.91932\n",
      " 484 3.966e-01 1.023e+07 7.072e-02 -- 3.498e+02 -- 0.0547914 -0.363381 -1.4512 -1.74786 -2.34997 -2.73904 -3.46121 -0.342721 0.110156 0.157823 0.200323 0.0564112 0.148724 0.91932\n",
      " 486 2.514e-01 1.136e+07 7.734e-02 -- 3.499e+02 -- 0.0569644 -0.363381 -1.4512 -1.74786 -2.34997 -2.73904 -3.46121 -0.337696 0.110153 0.157824 0.200319 0.056451 0.148749 0.919319\n",
      " 488 2.119e-01 1.266e+07 6.951e-02 -- 3.500e+02 -- 0.0583964 -0.36338 -1.4512 -1.74786 -2.34998 -2.73904 -3.46121 -0.335476 0.11015 0.157827 0.20031 0.0565002 0.148783 0.919319\n",
      " 490 1.907e-01 1.409e+07 6.640e-02 -- 3.500e+02 -- 0.0596337 -0.36338 -1.4512 -1.74786 -2.34998 -2.73904 -3.46121 -0.33443 0.110147 0.157829 0.200304 0.0565377 0.148807 0.919318\n",
      " 492 2.838e-01 1.566e+07 6.668e-02 -- 3.501e+02 -- 0.060771 -0.36338 -1.4512 -1.74786 -2.34998 -2.73904 -3.46121 -0.330323 0.110145 0.157831 0.200301 0.0565667 0.148826 0.919318\n",
      " 494 2.169e-01 1.737e+07 7.289e-02 -- 3.502e+02 -- 0.062496 -0.36338 -1.4512 -1.74786 -2.34998 -2.73903 -3.46121 -0.324585 0.110142 0.157832 0.200299 0.056597 0.148846 0.919318\n",
      " 496 1.775e-01 1.940e+07 6.791e-02 -- 3.502e+02 -- 0.0638514 -0.363379 -1.4512 -1.74786 -2.34998 -2.73903 -3.46121 -0.32577 0.11014 0.157835 0.200289 0.0566408 0.148875 0.919317\n",
      " 497 4.848e-01 6.026e+09 5.483e+00 -- 3.448e+02 -- 0.0541459 -0.363377 -1.4512 -1.74786 -2.35001 -2.73902 -3.4612 -0.383591 0.110125 0.157851 0.200189 0.056956 0.149081 0.919315\n",
      " 499 3.946e+00 2.201e+08 6.636e+00 -- 3.514e+02 -- 0.0518619 -0.36338 -1.4512 -1.74786 -2.34998 -2.73904 -3.46121 -0.364994 0.110159 0.157825 0.200285 0.0565514 0.14877 0.919318\n",
      "********************\n",
      "0.071793 -0.363381 -1.4512 -1.74785 -2.35 -2.73904 -3.46121 -0.509038 0.110198 0.157822 0.200171 0.0565592 0.148673 0.919314\n",
      "0.00680549 6.76709e-06 1.61276e-06 5.24533e-05 0.000285416 0.000268179 6.23129e-06 0.028847 0.000202035 7.49946e-05 0.000565924 0.00181438 0.00135023 0.000137249\n",
      "-78607.4 133.971 0.348338 -0.642816 -0.163519 -0.0095348 0.0102973 -2654.2 38.5323 -4.2263 0.532549 -0.374281 -0.0618559 0.00134632\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": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:root:Line magic function `%autoreload` not found.\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'clag' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-1-b2ff5ab5f6f9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmagic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mu'autoreload'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpe\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mclag\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mCx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'clag' is not defined"
     ]
    }
   ],
   "source": [
    "%autoreload\n",
    "p, pe = clag.errors(Cx, p, pe)"
   ]
  },
  {
   "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": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'fqd' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m----------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m    Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-2-d86f08ecda84>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0mxscale\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'log'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m;\u001b[0m \u001b[0mylim\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0merrorbar\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfqd\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlag\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlage\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfmt\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'o'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mms\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"black\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mlag\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mNameError\u001b[0m: name 'fqd' is not defined"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f59ff7ed810>"
      ]
     },
     "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",
    "lag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mu,sigma = norm.fit(lag,loc=12e-2)\n",
    "xscale('log'); ylim(-10,10)\n",
    "errorbar(fqd, lag, yerr=lage, fmt='o', ms=10,color=\"black\")\n",
    "plot(fqd,norm.pdf(fqd,mu,sigma))\n",
    "mu,sigma\n",
    "\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
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