{
 "metadata": {
  "name": "",
  "signature": "sha256:d2d00dd83c902684bef4ac4d44e7f3c3db439664e53d6122dc2c7f1175b18f8f"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas\n",
      "import numpy as np\n",
      "import isochrones.isochrones as iso\n",
      "from isochrones import dartmouth\n",
      "from isochrones.isochrones import "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dar = dartmouth.Dartmouth_Isochrone()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ev = dar.evtrack(1.5,dage=0.02)\n",
      "plot((ev['Teff']),ev['logL'],'.')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "[<matplotlib.lines.Line2D at 0x10e2a4e50>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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PJUnT1HwOPg/gkmT5IsJ8wMLk8XeAN5N2LwJjTKNJYEmSJEmSJDVyD/AG4VDRl4B1qXXn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\nu/8HpimZRFDLTVgAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x105d5ffd0>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import isochrones.starmodel as sm\n",
      "reload(iso)\n",
      "reload(dartmouth)\n",
      "dar = dartmouth.Dartmouth_Isochrone()\n",
      "mod = sm.StarModel(dar,Teff=(5783,64),logg=(4.36,0.07),feh=(-0.06,0.1))#,\n",
      "                    #H=(9.92,0.04),J=(10.23,0.04),K=(9.85,0.04))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mod.fit_mcmc()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mod.plot_samples('radius')\n",
      "mod.plot_samples('mass')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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kxCX2eIJVtLg+z1UTSILi4ur/oM45x5lYRKrTpAl8+GHFmusbb5gEUZVVq8Dn\ngwsvTHqIkkRKAjVUVgaffAI7dgTLfvghuN66NUyYEP6aQBurSKo480yzhHr+eVNjjRzmpLgY9u41\n66FJQ9KT081BLYFpwHnAdmA08FrI/rRrDvr97+Fvf6t6f5cu5huTSKYYMgTefdesT50K559v1pcv\nh1mzKo5hBJCXB3ffrc6QyZBuzUEvAPuBXKAX8AHwHZDyt0w3bIBbb634gV5UFP11nTsnLyYRt1V2\nE7kq27bBjBnJi0Xi42QSyAEuA7oDe4EFwDvAdZgaQUqbPBn+8Y/ox5x7rulwE5CbC3/4Q3Db5/Ph\n9XqTEl8q0PWlN7vXd9RR8b3//Pkwfnx42a9/bWoSoU8ZeTxQJwmfTJn+/xcvJ5NAZ6AMWBdS9h3g\nTfaJi4pg0iTYssX+a9auhbPOgmbNzPann0Y//uqr4dVXox+T6b+Eur70Zvf67rkH/vUvWL++4r7d\nu839rhtvNNtr1sCYMWb93/+GRx6xF0utWubGdKCl4733YOHC4N9jqOOOM/fdOnQIlpWWmvOF+vvf\nfeTleenYUX0eQjmZBBoDkfMc7QGaJPvEI0fCm2/G/rp//rPy8qeegiuuCG7Xr29uAItkg+7dzVNB\nduzcCU88Afv2xXaOI0fg8svtHbtokf2/78mTzc+BA4OJ4IMPoFs385SU3dgWLYKLLgrWYP75T/M5\n8KtfVTw+N9ckwt697b2/05zMh72ALzHNQgH3AmcBg/3b6XNHWEQktcT1ee5kf781mJpHx5CynsD3\nIduqpImIxO5utwOw6zXgf4BGwBnAL0BXVyMSERHHtADeBkqAjcCVrkYjIiIiIiIiIiIOaEl4k9BV\nUY59BCjC3DuYD3RLdnAJYPf66gN/AoqBnzG9qVN9LKc7gCWYXt9RBssAzI2qH4FdmKFC0mG+KrvX\ndyLwMbANOOJAXIli9/qG+Y/bhfn7+y+gdtKjqxm713YlsApzbduBt4C2SY+u5mL52wv4FPP7GfUB\nIDdGAw8dOuIa4C9U/uE+GBgOnIn5YF0IzHQoxpqwe30PAL0xPag7+9cfdijGeBUD44Dp1Rx3PjAK\n6A/kA8cDY5MbWkLYvb6DwGzgxqRHlFh2r68h8EfgKOBUYADmce5UZvfaFmAeS2+G+d3cCzyb3NAS\nwu71BVyD+VKZco/d5wAHCH9M9BXg8UqOHQ28HrLdHYixy4njYrm+xUBod5irgM3JCy2hxhH928j/\nAKEDBJzvYewKAAAEoUlEQVSDqRWki+quL6Aj6VUTCLB7fQF3A+8mKZZEi+XaGmP+Pv+UvHASzs71\nNQNWYxJ4ytUEqho6onslx34K/AboBNTFVFE/SnaANRTL9UF4v4hawLE40IM6Aarrz9ENc90By4HW\nmKfD0kGm91eJ9frOJrw/Tyqzc22Bx9N3A8dhaq3pws71TQQmA1vtvKHTSSCWoSMWYbL0akyV7bfA\nyKRGV3OxXN9cTJX7aKAN8AdM1a1RMgNMkOqqmI0xba4BgX+TdEhwkIJV6ASL5fp+j2mqfDpJsSSa\nnWv7EmiO+dJ1CHgqqRElVnXX1xfz5XmS3Td0OgmUAE0jypphPigj3YFpizwWcxP1MWAepr0yVcVy\nfROAb4FlmF/KtzG1CFvZ22XVfRuJ/HcIDPsVZZ6qlKKagHEJ5lvlhZiHF9JBLP93P2AePhmapFiS\nIdr11cLUAO4ivJky6r+J00nAztARARdgehj/gLmgVzDNCancwziW69sP3IlJch0xf2RLkh1gglT3\nbaQQOClkuycmue1MWkSJpZqA+fubAgzC/H+mi1j/7+piWhrSRbTrawr0wdxL/RHTmgLwb6BfVS9y\nOgmUYh7Jeozg0BEXU/lTP8uBKzBP2dTCzDtQh/D29lQTy/W19S8e4DTMk0FjnAkzbrWBBpj/h9qY\nGlpljw7OwDw50xWTuB8hthuRbrF7ffiPCzz2Wt+/pDq719cfeBUz/0e6fDGxe21XA4GxPvMxNfI5\nTgRYQ3au7xfgGMyXrp7ARf7y3gQTQkqoauiI4zDNBYEJ6BoBLwFbMO3LS4D/cDLQONm9vjOBDZjE\nsZLo/SVSRQGmVha6PErFawPzREng/24a5htXqivA3vW1C9l/2P/zX86GGpcC7F3fPMxjsHtClg8c\njjVWBdi7tvGYvg8lmL+/JzAfrqmuAPt/ewHtML+fbnQFEBERERERERERERERERERERERERERERER\nEUk57QgfjvdDTO91ERHJAu2wMSa7SLrSL7Zkm1SfwlPEUUoCkg02AvdjBiUsAR7CDES4GzNC5iUh\nx9bCjJ2/DVgPDIx4Lx/BaSULCB8csB3htYbr/e+xGzO20NU1vRCRRNO3IskWV2LGxd+BGR75DMwA\nd1cAs4AOmOGub8F88J+EGWL4LcKH77VCtqMN65sD/BkzycdazMxqRyXmUkQSRzUByQYW8N+Yybr3\nA29iEgDAG5gP6VP821dg5pwtxsx/MJGqJ+WobgKTI0APzERIW4EV8YUvkjxKApItikLWh2Jmddvp\nX07ETPMJZjz20GM3x3m+UuB3wHDMxEjvA13ifC+RpFESkGwRaLrJx8yYdTvQEjP/w/cEv9X/iBmj\nPSB0PVIJ4XNCt4nY/7+YOTDaAKuAqfEELpJMSgKSbXIwCWE75vf/BkxNIOAN4A9AHiZBPBDlvZYB\nZ2FmqmoGjA7ZlwsM8Z/vEKZmcDghVyCSQEoCkm1WAM8ACzH3BU4EvgzZPxX4GPgOM5vdHKq+AfwJ\nZj7X5cBi4L2QY2thZlcrxtyMPhMYkcDrEBERERERERERERERERERERERERERERERERERERERkaz3\nf2sj9hNXtJbKAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x109d00bd0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x109d00d90>"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from keputils import koiutils as ku"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ku.KICmags(69)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "{'H': 8.4459999999999997,\n",
        " 'J': 8.7710000000000008,\n",
        " 'K': 8.3699999999999992,\n",
        " 'Kepler': 9.9310000000000009,\n",
        " 'Ks': 8.3699999999999992,\n",
        " 'g': 10.329207800000001,\n",
        " 'h': 8.4459999999999997,\n",
        " 'i': 9.6892607999999996,\n",
        " 'j': 8.7710000000000008,\n",
        " 'k': 8.3699999999999992,\n",
        " 'kep': 9.9310000000000009,\n",
        " 'r': 9.8304404000000005,\n",
        " 'z': 9.6506958000000012}"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}