Analyzing saved diamonds.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook shows the analysis of the 29 diamonds whose results are in the thesis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/juan/anaconda/envs/python2/lib/python2.7/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 1\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "#import qutip as qt\n",
    "import os,sys,inspect\n",
    "import sklearn as sk\n",
    "currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))\n",
    "parentdir = os.path.dirname(currentdir)\n",
    "sys.path.insert(0,parentdir) \n",
    "%aimport analysis\n",
    "%aimport learning\n",
    "%aimport NV_generator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fig_dir='/Users/juan/Google Drive/Brown/2017S/Machine Learning Applied to Scientific Data  - ENGN2912Z/NV-Tomography/';"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "diamonds = []\n",
    "num_diamonds = 100 - 4\n",
    "for diamond_num in range(num_diamonds):\n",
    "    diamond = learning.load_obj_2(\"diamonds/diamond_\" + str(diamond_num))\n",
    "    diamonds.append(diamond)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "B_field = 0.0403555 # Teslas\n",
    "gam_c = 67.262 * 10 ** 6 # Gyromagnetic ratio for a single c13 nucleus in rad s-1 T-1\n",
    "ms = 1\n",
    "omega_larmor = -1 * ms * gam_c * B_field"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A : 467\n",
      "tau : 5100\n",
      "B : 467\n",
      "successful_fits : 1114\n",
      "windows : 1114\n",
      "data : 5100\n",
      "N_data : 128\n",
      "error_tol : val: 0.0015625\n",
      "N : val: 64\n",
      "N_vals : 128\n",
      "num_subsets : val: 4\n",
      "xs_list : 1114\n",
      "costheta : 467\n",
      "scaled_errors : 1114\n",
      "phis_list : 1114\n",
      "r : 467\n",
      "dip_inds : 1114\n",
      "sintheta : 467\n",
      "good_fits : 1114\n"
     ]
    }
   ],
   "source": [
    "for llave in diamonds[0].keys():\n",
    "    print llave,\":\",\n",
    "    try:\n",
    "        print len(diamonds[0][llave])\n",
    "    except:\n",
    "        print \"val:\",diamonds[0][llave]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3795, 3810],\n",
       "       [4840, 4855],\n",
       "       [2107, 2121],\n",
       "       ..., \n",
       "       [3888, 3890],\n",
       "       [1753, 1755],\n",
       "       [2361, 2363]])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diamonds[0]['windows']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "the_times = 10**6*diamonds[0]['tau']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/juan/anaconda/envs/python2/lib/python2.7/site-packages/ipykernel/__main__.py:7: VisibleDeprecationWarning: boolean index did not match indexed array along dimension 0; dimension is 5100 but corresponding boolean dimension is 1114\n"
     ]
    },
    {
     "data": {
      "image/png": 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OX5oBduzYiJw/WFo8HJZ8VwIv539IhBC8u/kEAGBHyXk4Fy4WY39syR6JYUWFquP8b/0R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\n2knD/VwDKWQ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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ccf93d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,4))\n",
    "the_times = 10**6*diamonds[0]['tau']\n",
    "the_data = diamonds[0]['data']\n",
    "good_ones = np.array(diamonds[0]['good_fits'])\n",
    "plt.plot(the_times,the_data,label='M')\n",
    "plt.plot(the_times[diamonds[0]['dip_inds']],the_data[diamonds[0]['dip_inds']],'ro',label='dips')\n",
    "plt.plot(the_times[good_ones],the_data[good_ones],'ko',label='goodfits')\n",
    "plt.legend()\n",
    "#for ventana in diamonds[0]['windows']:\n",
    "#    plt.plot(the_times[ventana[0]:ventana[1]],(-0.1)+the_data[ventana[0]:ventana[1]],'r--')\n",
    "#plt.xlim(15,17.5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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zw3R3d8feGuPz+RgioqSkpMDc3BzT1dUVt5k1DAaD12KxxHo8HmZ+fp6xWCxx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+nuqnSqfmZuBLy8kX5mnbQZ+598dfocQQYWfHW6aUzXv7yH80LyRf7lPfy+1/15V4MjBw4hVVbg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\nbO8YOXAUV7XSsPEahaF2dzJ2nWs0BPm/7jRi/t6YydmzG6PiAHL27MJM6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4/HYrFw6tQp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\n8i9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rqaysxGazeWyXk5ODzWajsbGR3t5eKioq3Pu8vLyw2+1kZWWRnJxMYWEhjY2NbN++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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11700add0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "\n",
    "#plt.subplot(6,5,i+1)\n",
    "for i in range(50):\n",
    "    plt.plot(10.**(-3)/2./np.pi*diamonds[i]['A'],10.**(-3)/2./np.pi*diamonds[i]['B'],\n",
    "             'o',label='diamond '+str(i),ms=1)\n",
    "plt.xlabel('A/Hz')\n",
    "plt.ylabel('B/Hz')\n",
    "plt.legend()\n",
    "plt.xlim(-50,50)\n",
    "plt.ylim(-50,50)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1494850616.021179"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time.time()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "diamond_ind:  0\n",
      "dips measured:  388\n",
      "num_removed:  0\n",
      "correct:  12 incorrect:  4\n",
      "diamond_ind:  1\n",
      "dips measured:  404\n",
      "num_removed:  2\n",
      "correct:  16 incorrect:  4\n",
      "diamond_ind:  2\n",
      "dips measured:  370\n",
      "num_removed:  0\n",
      "correct:  15 incorrect:  4\n",
      "diamond_ind:  3\n",
      "dips measured:  382\n",
      "num_removed:  1\n",
      "correct:  15 incorrect:  1\n",
      "diamond_ind:  4\n",
      "dips measured:  408\n",
      "num_removed:  2\n",
      "correct:  9 incorrect:  5\n",
      "diamond_ind:  5\n",
      "dips measured:  408\n",
      "num_removed:  0\n",
      "correct:  4 incorrect:  10\n",
      "diamond_ind:  6\n",
      "dips measured:  420\n",
      "num_removed:  1\n",
      "correct:  13 incorrect:  5\n",
      "diamond_ind:  7\n",
      "dips measured:  365\n",
      "num_removed:  0\n",
      "correct:  12 incorrect:  2\n",
      "diamond_ind:  8\n",
      "dips measured:  379\n",
      "num_removed:  0\n",
      "correct:  12 incorrect:  5\n",
      "diamond_ind:  9\n",
      "dips measured:  373\n",
      "num_removed:  0\n",
      "correct:  7 incorrect:  5\n",
      "diamond_ind:  10\n",
      "dips measured:  352\n",
      "num_removed:  3\n",
      "correct:  17 incorrect:  2\n",
      "diamond_ind:  11\n",
      "dips measured:  376\n",
      "num_removed:  2\n",
      "correct:  17 incorrect:  3\n",
      "diamond_ind:  12\n",
      "dips measured:  455\n",
      "num_removed:  1\n",
      "correct:  17 incorrect:  11\n",
      "diamond_ind:  13\n",
      "dips measured:  408\n",
      "num_removed:  0\n",
      "correct:  13 incorrect:  6\n",
      "diamond_ind:  14\n",
      "dips measured:  349\n",
      "num_removed:  0\n",
      "correct:  14 incorrect:  3\n",
      "diamond_ind:  15\n",
      "dips measured:  388\n",
      "num_removed:  0\n",
      "correct:  11 incorrect:  4\n",
      "diamond_ind:  16\n",
      "dips measured:  389\n",
      "num_removed:  4\n",
      "correct:  19 incorrect:  4\n",
      "diamond_ind:  17\n",
      "dips measured:  382\n",
      "num_removed:  2\n",
      "correct:  14 incorrect:  1\n",
      "diamond_ind:  18\n",
      "dips measured:  425\n",
      "num_removed:  1\n",
      "correct:  17 incorrect:  4\n",
      "diamond_ind:  19\n",
      "dips measured:  433\n",
      "num_removed:  4\n",
      "correct:  17 incorrect:  5\n",
      "diamond_ind:  20\n",
      "dips measured:  429\n",
      "num_removed:  0\n",
      "correct:  19 incorrect:  6\n",
      "diamond_ind:  21\n",
      "dips measured:  382\n",
      "num_removed:  2\n",
      "correct:  15 incorrect:  5\n",
      "diamond_ind:  22\n",
      "dips measured:  405\n",
      "num_removed:  0\n",
      "correct:  11 incorrect:  1\n",
      "diamond_ind:  23\n",
      "dips measured:  383\n",
      "num_removed:  1\n",
      "correct:  9 incorrect:  3\n",
      "diamond_ind:  24\n",
      "dips measured:  354\n",
      "num_removed:  0\n",
      "correct:  13 incorrect:  4\n",
      "diamond_ind:  25\n",
      "dips measured:  372\n",
      "num_removed:  0\n",
      "correct:  21 incorrect:  3\n",
      "diamond_ind:  26\n",
      "dips measured:  420\n",
      "num_removed:  4\n",
      "correct:  16 incorrect:  5\n",
      "diamond_ind:  27\n",
      "dips measured:  407\n",
      "num_removed:  0\n",
      "correct:  13 incorrect:  9\n",
      "diamond_ind:  28\n",
      "dips measured:  415\n",
      "num_removed:  1\n",
      "correct:  13 incorrect:  5\n",
      "diamond_ind:  29\n",
      "dips measured:  390\n",
      "num_removed:  2\n",
      "correct:  13 incorrect:  6\n",
      "diamond_ind:  30\n",
      "dips measured:  383\n",
      "num_removed:  0\n",
      "correct:  17 incorrect:  7\n",
      "diamond_ind:  31\n",
      "dips measured:  413\n",
      "num_removed:  2\n",
      "correct:  20 incorrect:  6\n",
      "diamond_ind:  32\n",
      "dips measured:  387\n",
      "num_removed:  1\n",
      "correct:  16 incorrect:  5\n",
      "diamond_ind:  33\n",
      "dips measured:  365\n",
      "num_removed:  4\n",
      "correct:  11 incorrect:  7\n",
      "diamond_ind:  34\n",
      "dips measured:  377\n",
      "num_removed:  0\n",
      "correct:  14 incorrect:  2\n",
      "diamond_ind:  35\n",
      "dips measured:  355\n",
      "num_removed:  1\n",
      "correct:  9 incorrect:  4\n",
      "diamond_ind:  36\n",
      "dips measured:  390\n",
      "num_removed:  1\n",
      "correct:  12 incorrect:  3\n",
      "diamond_ind:  37\n",
      "dips measured:  438\n",
      "num_removed:  2\n",
      "correct:  19 incorrect:  6\n",
      "diamond_ind:  38\n",
      "dips measured:  407\n",
      "num_removed:  2\n",
      "correct:  13 incorrect:  4\n",
      "diamond_ind:  39\n",
      "dips measured:  400\n",
      "num_removed:  1\n",
      "correct:  12 incorrect:  3\n",
      "diamond_ind:  40\n",
      "dips measured:  423\n",
      "num_removed:  0\n",
      "correct:  4 incorrect:  3\n",
      "diamond_ind:  41\n",
      "dips measured:  424\n",
      "num_removed:  0\n",
      "correct:  14 incorrect:  10\n",
      "diamond_ind:  42\n",
      "dips measured:  360\n",
      "num_removed:  3\n",
      "correct:  16 incorrect:  3\n",
      "diamond_ind:  43\n",
      "dips measured:  401\n",
      "num_removed:  1\n",
      "correct:  13 incorrect:  5\n",
      "diamond_ind:  44\n",
      "dips measured:  397\n",
      "num_removed:  0\n",
      "correct:  8 incorrect:  2\n",
      "diamond_ind:  45\n",
      "dips measured:  372\n",
      "num_removed:  1\n",
      "correct:  8 incorrect:  0\n",
      "diamond_ind:  46\n",
      "dips measured:  426\n",
      "num_removed:  3\n",
      "correct:  15 incorrect:  5\n",
      "diamond_ind:  47\n",
      "dips measured:  356\n",
      "num_removed:  1\n",
      "correct:  14 incorrect:  1\n",
      "diamond_ind:  48\n",
      "dips measured:  400\n",
      "num_removed:  0\n",
      "correct:  9 incorrect:  1\n",
      "diamond_ind:  49\n",
      "dips measured:  419\n",
      "num_removed:  0\n",
      "correct:  10 incorrect:  5\n",
      "diamond_ind:  50\n",
      "dips measured:  450\n",
      "num_removed:  2\n",
      "correct:  20 incorrect:  10\n",
      "diamond_ind:  51\n",
      "dips measured:  396\n",
      "num_removed:  3\n",
      "correct:  15 incorrect:  3\n",
      "diamond_ind:  52\n",
      "dips measured:  372\n",
      "num_removed:  3\n",
      "correct:  12 incorrect:  6\n",
      "diamond_ind:  53\n",
      "dips measured:  417\n",
      "num_removed:  1\n",
      "correct:  10 incorrect:  5\n",
      "diamond_ind:  54\n",
      "dips measured:  398\n",
      "num_removed:  2\n",
      "correct:  18 incorrect:  5\n",
      "diamond_ind:  55\n",
      "dips measured:  375\n",
      "num_removed:  3\n",
      "correct:  12 incorrect:  4\n",
      "diamond_ind:  56\n",
      "dips measured:  366\n",
      "num_removed:  0\n",
      "correct:  17 incorrect:  9\n",
      "diamond_ind:  57\n",
      "dips measured:  389\n",
      "num_removed:  1\n",
      "correct:  9 incorrect:  5\n",
      "diamond_ind:  58\n",
      "dips measured:  409\n",
      "num_removed:  3\n",
      "correct:  20 incorrect:  8\n",
      "diamond_ind:  59\n",
      "dips measured:  416\n",
      "num_removed:  2\n",
      "correct:  21 incorrect:  2\n",
      "diamond_ind:  60\n",
      "dips measured:  380\n",
      "num_removed:  1\n",
      "correct:  14 incorrect:  4\n",
      "diamond_ind:  61\n",
      "dips measured:  368\n",
      "num_removed:  2\n",
      "correct:  11 incorrect:  7\n",
      "diamond_ind:  62\n",
      "dips measured:  414\n",
      "num_removed:  0\n",
      "correct:  8 incorrect:  4\n",
      "diamond_ind:  63\n",
      "dips measured:  350\n",
      "num_removed:  0\n",
      "correct:  13 incorrect:  3\n",
      "diamond_ind:  64\n",
      "dips measured:  389\n",
      "num_removed:  1\n",
      "correct:  9 incorrect:  3\n",
      "diamond_ind:  65\n",
      "dips measured:  382\n",
      "num_removed:  2\n",
      "correct:  13 incorrect:  2\n",
      "diamond_ind:  66\n",
      "dips measured:  373\n",
      "num_removed:  2\n",
      "correct:  9 incorrect:  2\n",
      "diamond_ind:  67\n",
      "dips measured:  385\n",
      "num_removed:  0\n",
      "correct:  17 incorrect:  2\n",
      "diamond_ind:  68\n",
      "dips measured:  423\n",
      "num_removed:  0\n",
      "correct:  9 incorrect:  6\n",
      "diamond_ind:  69\n",
      "dips measured:  374\n",
      "num_removed:  1\n",
      "correct:  10 incorrect:  4\n",
      "diamond_ind:  70\n",
      "dips measured:  385\n",
      "num_removed:  2\n",
      "correct:  11 incorrect:  6\n",
      "diamond_ind:  71\n",
      "dips measured:  389\n",
      "num_removed:  0\n",
      "correct:  7 incorrect:  2\n",
      "diamond_ind:  72\n",
      "dips measured:  410\n",
      "num_removed:  0\n",
      "correct:  21 incorrect:  1\n",
      "diamond_ind:  73\n",
      "dips measured:  394\n",
      "num_removed:  0\n",
      "correct:  13 incorrect:  3\n",
      "diamond_ind:  74\n",
      "dips measured:  379\n",
      "num_removed:  3\n",
      "correct:  6 incorrect:  4\n",
      "diamond_ind:  75\n",
      "dips measured:  377\n",
      "num_removed:  0\n",
      "correct:  16 incorrect:  3\n",
      "diamond_ind:  76\n",
      "dips measured:  389\n",
      "num_removed:  2\n",
      "correct:  12 incorrect:  2\n",
      "diamond_ind:  77\n",
      "dips measured:  342\n",
      "num_removed:  3\n",
      "correct:  20 incorrect:  1\n",
      "diamond_ind:  78\n",
      "dips measured:  435\n",
      "num_removed:  2\n",
      "correct:  13 incorrect:  5\n",
      "diamond_ind:  79\n",
      "dips measured:  369\n",
      "num_removed:  2\n",
      "correct:  13 incorrect:  10\n",
      "diamond_ind:  80\n",
      "dips measured:  386\n",
      "num_removed:  3\n",
      "correct:  14 incorrect:  3\n",
      "diamond_ind:  81\n",
      "dips measured:  392\n",
      "num_removed:  0\n",
      "correct:  8 incorrect:  2\n",
      "diamond_ind:  82\n",
      "dips measured:  416\n",
      "num_removed:  4\n",
      "correct:  26 incorrect:  9\n",
      "diamond_ind:  83\n",
      "dips measured:  419\n",
      "num_removed:  0\n",
      "correct:  11 incorrect:  9\n",
      "diamond_ind:  84\n",
      "dips measured:  406\n",
      "num_removed:  1\n",
      "correct:  13 incorrect:  6\n",
      "diamond_ind:  85\n",
      "dips measured:  385\n",
      "num_removed:  0\n",
      "correct:  9 incorrect:  2\n",
      "diamond_ind:  86\n",
      "dips measured:  414\n",
      "num_removed:  1\n",
      "correct:  13 incorrect:  3\n",
      "diamond_ind:  87\n",
      "dips measured:  415\n",
      "num_removed:  3\n",
      "correct:  13 incorrect:  11\n",
      "diamond_ind:  88\n",
      "dips measured:  396\n",
      "num_removed:  0\n",
      "correct:  12 incorrect:  6\n",
      "diamond_ind:  89\n",
      "dips measured:  370\n",
      "num_removed:  0\n",
      "correct:  12 incorrect:  5\n",
      "diamond_ind:  90\n",
      "dips measured:  380\n",
      "num_removed:  0\n",
      "correct:  4 incorrect:  4\n",
      "diamond_ind:  91\n",
      "dips measured:  402\n",
      "num_removed:  2\n",
      "correct:  15 incorrect:  2\n",
      "diamond_ind:  92\n",
      "dips measured:  419\n",
      "num_removed:  0\n",
      "correct:  13 incorrect:  3\n",
      "diamond_ind:  93\n",
      "dips measured:  404\n",
      "num_removed:  0\n",
      "correct:  12 incorrect:  8\n",
      "diamond_ind:  94\n",
      "dips measured:  432\n",
      "num_removed:  6\n",
      "correct:  22 incorrect:  10\n",
      "diamond_ind:  95\n",
      "dips measured:  345\n",
      "num_removed:  2\n",
      "correct:  15 incorrect:  7\n",
      "23.2502515316\n"
     ]
    }
   ],
   "source": [
    "begin_time=time.time()\n",
    "# What is Michael doing here?\n",
    "# First he imports two sklearn objects: a scaler and a classifier.\n",
    "guess_scaler = learning.load_obj(\"classifiers/scaler_svm_rbf_di3220_29diamonds_cxABe\")#(\"classifiers/scaler_svm_rbfguess_limited_3220_C1_29diamonds\")scaler_svm_linear_di3220_29diamond\n",
    "guess_clf = learning.load_obj(\"classifiers/clf_svm_rbf_di3220_29diamonds_cxABe\")#(\"classifiers/clf_svm_rbfguess_limited_3220_C1_29diamonds\")\n",
    "num_correct_list, num_incorrect_list = [], []\n",
    "As_list, Bs_list = [], []\n",
    "guess_As_list, guess_Bs_list = [], []\n",
    "dips_measured = []\n",
    "# He then iterates through all of the 29 diamonds.\n",
    "for diamond_ind in range(len(diamonds)):\n",
    "    print \"diamond_ind: \", diamond_ind\n",
    "    diamond = diamonds[diamond_ind]\n",
    "    tau = diamond[\"tau\"] # This is an array with all the free evolution times.\n",
    "    data = diamond[\"data\"] # These are the corresping M(tau) values for N = 64\n",
    "    N = diamond[\"N\"]\n",
    "    dip_inds = diamond[\"dip_inds\"] # indices for the dips in data\n",
    "    windows = diamond[\"windows\"] # these indices determine the window around each dip\n",
    "    min_dip_ind = 3220\n",
    "    measure_dii = filter(lambda dii: dip_inds[dii] >= min_dip_ind, range(len(dip_inds))) # only times after 15 micros are taken\n",
    "    print \"dips measured: \", len(measure_dii)\n",
    "    dips_measured.append(len(measure_dii))\n",
    "    spin_dict = {}\n",
    "    for dii in measure_dii: # this loop iterates over all dips\n",
    "        if diamond[\"good_fits\"][dii]: # If this happens to be a good fit then\n",
    "            dip_ind = dip_inds[dii] \n",
    "            res_tau = tau[dip_ind]\n",
    "            for phi, x in zip(diamond[\"phis_list\"][dii], diamond[\"xs_list\"][dii]):\n",
    "                for omega_tilde, cosphi in analysis.calc_omega_tilde(phi, x, res_tau, omega_larmor):\n",
    "                    A, B = analysis.calc_A_B(cosphi, res_tau, omega_larmor, omega_tilde)\n",
    "                    if analysis.valid_A_B(A, B):\n",
    "                        if (dip_ind, phi, x) in spin_dict:\n",
    "                            spin_dict[(dip_ind, phi, x)] += [(A, B, cosphi)]\n",
    "                        else:\n",
    "                            spin_dict[(dip_ind, phi, x)] = [(A, B, cosphi)]\n",
    "    def guess_classifier(features): # this defines a pipeline with scaler and classifier.\n",
    "        #flip a coin\n",
    "        the_coin = np.random.rand()\n",
    "        if the_coin < 0.:\n",
    "            return np.array([0.])\n",
    "        else:\n",
    "            return np.array([1.])\n",
    "#         return guess_clf.predict(guess_scaler.transform([features]))\n",
    "    guess_As, guess_Bs, dataerrs, _, _, _, _ = analysis.choose_spin_guesses(spin_dict, N, omega_larmor, tau, data,\n",
    "                                                                guess_classifier, x_min = 1, error_fun = analysis.squared_error)\n",
    "    cluster_As, cluster_Bs, cluster_dataerrs = analysis.cluster_spin_guesses(guess_As, guess_Bs, dataerrs, eps = .075, min_samples = 1)\n",
    "    As, Bs, num_remove = cluster_As, cluster_Bs, 1\n",
    "    while num_remove <= 2:\n",
    "        As, Bs, num_remove = analysis.remove_spins(As, Bs, N, omega_larmor, tau, data, num_remove = num_remove, error_fun = analysis.squared_error)\n",
    "    As_list.append(As)\n",
    "    Bs_list.append(Bs)\n",
    "    guess_As_list.append(guess_As)\n",
    "    guess_Bs_list.append(guess_Bs)\n",
    "    \n",
    "    print \"num_removed: \", len(cluster_As) - len(As)\n",
    "    num_correct = 0\n",
    "    spins = set(zip(diamond[\"A\"], np.abs(diamond[\"B\"])))\n",
    "    for A, B in zip(As, np.abs(Bs)):\n",
    "        for spin in spins:\n",
    "            if learning.is_fit(A, B, spin, A_acc = .5, B_acc = 2):\n",
    "                num_correct = num_correct + 1\n",
    "                spins.remove(spin)\n",
    "                break\n",
    "    num_incorrect = len(As) - num_correct\n",
    "    num_correct_list.append(num_correct)\n",
    "    num_incorrect_list.append(num_incorrect)\n",
    "    print \"correct: \", num_correct, \"incorrect: \", len(As) - num_correct\n",
    "finish_time = time.time()\n",
    "print((finish_time-begin_time)/60.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\\# defective diamond log and replacements\n",
    "\n",
    "+ 20 was defective, replaced by 99.\n",
    "+ 21 is defective too, replaced by 98.\n",
    "+ 74 is defective too, replaced by 97.\n",
    "+ 82 is defective too, replaced by 96."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'num_correct_list' 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-23-406399ec650b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnum_correct_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnum_incorrect_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'num_correct_list' is not defined"
     ]
    }
   ],
   "source": [
    "np.mean(num_correct_list), np.mean(num_incorrect_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#results_dict = {\"As_list\" : As_list, \"Bs_list\" : Bs_list,\n",
    "#                \"num_correct_list\" : num_correct_list, \"num_incorrect_list\" : num_incorrect_list, \"dips_measured\" : dips_measured}\n",
    "#learning.store_obj(results_dict, \"results/results_di3220_29diamonds_cxABe_x1\")\n",
    "results_dict = learning.load_obj(\"results/results_di3220_29diamonds_cxABe_x1\")\n",
    "As_list = results_dict[\"As_list\"]\n",
    "Bs_list = results_dict[\"Bs_list\"]\n",
    "num_correct_list = results_dict[\"num_correct_list\"]\n",
    "num_incorrect_list = results_dict[\"num_incorrect_list\"]\n",
    "dips_measured = results_dict[\"dips_measured\"]\n",
    "#print np.mean(results_dict[\"num_correct_list\"])#, num_correct_list\n",
    "#print results_dict[\"num_incorrect_list\"]#, num_incorrect_list\n",
    "#As_list = results_dict[\"As_list\"]\n",
    "#Bs_list = results_dict[\"Bs_list\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "55298.068965517239"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(np.array(dips_measured) * 128 + 5100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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k71prnzxIWUfK2PaUHwAAAID9V1VprdV+HbOXgumQ1tqOx7jgY35mLCmYAAAA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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10eff0850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "diamond_ind = 21\n",
    "plt.figure(figsize=(20,10))\n",
    "plt.title(\"Fitted As and Bs\")\n",
    "plt.xlabel(\"A/(2 * pi * 1e3)\")\n",
    "plt.ylabel(\"B/(2 * pi * 1e3)\")\n",
    "plt.scatter(diamonds[diamond_ind][\"A\"]/analysis.mag, np.abs(diamonds[diamond_ind][\"B\"])/analysis.mag, c='b', marker = 'o', s = 50, label = 'true')\n",
    "plt.scatter(As_list[diamond_ind]/analysis.mag, np.abs(Bs_list[diamond_ind])/analysis.mag, c='r', marker = 'x', s = 50, label = 'fit')\n",
    "plt.legend(loc=2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## New Diamonds' Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# new diamonds \n",
    "diamonds=[learning.load_obj(\"new_diamonds/diamond_1\"),\n",
    "          learning.load_obj(\"new_diamonds/diamond_2\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1194d4050>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.scatter(full_lattice[:,0]/analysis.mag,full_lattice[:,1]/analysis.mag)\n",
    "plt.xlim(-150,150)\n",
    "plt.ylim(0,150)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "diamond_ind:  0\n",
      "dips measured:  388\n",
      "num_removed:  0\n",
      "correct:  13 incorrect:  2\n",
      "diamond_ind:  1\n",
      "dips measured:  404\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-70-44a25013311d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     55\u001b[0m \u001b[0;31m#             return np.array([0.])\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     56\u001b[0m     guess_As, guess_Bs, dataerrs, _, _, _, _ = analysis.choose_spin_guesses(spin_dict, N, omega_larmor, tau, data,\n\u001b[0;32m---> 57\u001b[0;31m                                                                 guess_classifier, x_min = 1, error_fun = analysis.squared_error)\n\u001b[0m\u001b[1;32m     58\u001b[0m     \u001b[0mcluster_As\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcluster_Bs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcluster_dataerrs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0manalysis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcluster_spin_guesses\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mguess_As\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mguess_Bs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdataerrs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0meps\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m.075\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmin_samples\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     59\u001b[0m     \u001b[0mAs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mBs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnum_remove\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcluster_As\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcluster_Bs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/juan/Gits/NV-spin-tomography/analysis.pyc\u001b[0m in \u001b[0;36mchoose_spin_guesses\u001b[0;34m(spin_dict, N, omega_larmor, tau, data, classifier, x_min, error_fun)\u001b[0m\n\u001b[1;32m    351\u001b[0m                         \u001b[0mall_guess_As\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mA\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    352\u001b[0m                         \u001b[0mall_guess_Bs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mB\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 353\u001b[0;31m                         \u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merror_fun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcalc_M_single\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mA\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mB\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mN\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0momega_larmor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtau\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    354\u001b[0m                 \u001b[0mmin_err_ind\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    355\u001b[0m                 \u001b[0mbest_A\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbest_B\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbest_cosphi\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mspin_dict\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmin_err_ind\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/juan/Gits/NV-spin-tomography/analysis.pyc\u001b[0m in \u001b[0;36msquared_error\u001b[0;34m(l1, l2)\u001b[0m\n\u001b[1;32m    146\u001b[0m \u001b[0;31m# for two arrays l1 and l2 returns the squared error between them\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    147\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0msquared_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ml1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ml2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 148\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msum\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ml1\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0ml2\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m**\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    149\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    150\u001b[0m \u001b[0;31m# Use scipy.optimize.curve_fit to fit N_data to several spins using fit_fun. Requires a guess of the spin\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# What is Michael doing here?\n",
    "# First he imports two sklearn objects: a scaler and a classifier.\n",
    "guess_scaler = learning.load_obj(\"classifiers/scaler_svm_rbf_di3220_29diamonds_cxABe\")#(\"classifiers/scaler_svm_rbfguess_limited_3220_C1_29diamonds\")scaler_svm_linear_di3220_29diamond\n",
    "guess_clf = learning.load_obj(\"classifiers/clf_svm_rbf_di3220_29diamonds_cxABe\")#(\"classifiers/clf_svm_rbfguess_limited_3220_C1_29diamonds\")\n",
    "num_correct_list, num_incorrect_list = [], []\n",
    "As_list, Bs_list = [], []\n",
    "guess_As_list, guess_Bs_list = [], []\n",
    "dips_measured = []\n",
    "####\n",
    "full_lattice = np.genfromtxt('complete_lattice.csv',delimiter=',');\n",
    "full_lattice[:,1]=np.abs(full_lattice[:,1])\n",
    "full_lattice = analysis.mag*full_lattice\n",
    "dA = 0.5 * analysis.mag\n",
    "dB = 0.1 * analysis.mag\n",
    "###\n",
    "\n",
    "# He then iterates through all of the 29 diamonds.\n",
    "for diamond_ind in range(len(diamonds)):\n",
    "    print \"diamond_ind: \", diamond_ind\n",
    "    diamond = diamonds[diamond_ind]\n",
    "    tau = diamond[\"tau\"] # This is an array with all the free evolution times.\n",
    "    data = diamond[\"data\"] # These are the corresping M(tau) values for N = 64\n",
    "    N = diamond[\"N\"]\n",
    "    dip_inds = diamond[\"dip_inds\"] # indices for the dips in data\n",
    "    windows = diamond[\"windows\"] # these indices determine the window around each dip\n",
    "    min_dip_ind = 3220\n",
    "    measure_dii = filter(lambda dii: dip_inds[dii] >= min_dip_ind, range(len(dip_inds))) # only times after 15 micros are taken\n",
    "    print \"dips measured: \", len(measure_dii)\n",
    "    dips_measured.append(len(measure_dii))\n",
    "    spin_dict = {}\n",
    "    for dii in measure_dii: # this loop iterates over all dips\n",
    "        if diamond[\"good_fits\"][dii]: # If this happens to be a good fit then\n",
    "            dip_ind = dip_inds[dii] \n",
    "            res_tau = tau[dip_ind]\n",
    "            for phi, x in zip(diamond[\"phis_list\"][dii], diamond[\"xs_list\"][dii]):\n",
    "                for omega_tilde, cosphi in analysis.calc_omega_tilde(phi, x, res_tau, omega_larmor):\n",
    "                    A, B = analysis.calc_A_B(cosphi, res_tau, omega_larmor, omega_tilde)\n",
    "                    if analysis.valid_A_B(A, B):\n",
    "                        if (dip_ind, phi, x) in spin_dict:\n",
    "                            spin_dict[(dip_ind, phi, x)] += [(A, B, cosphi)]\n",
    "                        else:\n",
    "                            spin_dict[(dip_ind, phi, x)] = [(A, B, cosphi)]\n",
    "    def guess_classifier(features): # this defines a pipeline with scaler and classifier.\n",
    "        return guess_clf.predict(guess_scaler.transform([features]))\n",
    "#     def guess_classifier(features):\n",
    "#         # to make it compliant to the feature vector defined\n",
    "#         # by Scheer, I assume that it has five components and only\n",
    "#         # take the two corresponding to indices 2 and 3\n",
    "#         # note that dA and dB must be converted to rad / s\n",
    "#         simple_features = np.array([features[2],features[3]])\n",
    "#         differences = np.abs(simple_features - full_lattice)\n",
    "#         if np.any((differences[:,0] < dA) & (differences[:,1] < dB)):\n",
    "#             return np.array([1.])\n",
    "#         else:\n",
    "#             return np.array([0.])\n",
    "    guess_As, guess_Bs, dataerrs, _, _, _, _ = analysis.choose_spin_guesses(spin_dict, N, omega_larmor, tau, data,\n",
    "                                                                guess_classifier, x_min = 1, error_fun = analysis.squared_error)\n",
    "    cluster_As, cluster_Bs, cluster_dataerrs = analysis.cluster_spin_guesses(guess_As, guess_Bs, dataerrs, eps = .075, min_samples = 1)\n",
    "    As, Bs, num_remove = cluster_As, cluster_Bs, 1\n",
    "    while num_remove <= 2:\n",
    "        As, Bs, num_remove = analysis.remove_spins(As, Bs, N, omega_larmor, tau, data, num_remove = num_remove, error_fun = analysis.squared_error)\n",
    "    As_list.append(As)\n",
    "    Bs_list.append(Bs)\n",
    "    guess_As_list.append(guess_As)\n",
    "    guess_Bs_list.append(guess_Bs)\n",
    "    \n",
    "    print \"num_removed: \", len(cluster_As) - len(As)\n",
    "    num_correct = 0\n",
    "    spins = set(zip(diamond[\"A\"], np.abs(diamond[\"B\"])))\n",
    "    for A, B in zip(As, np.abs(Bs)):\n",
    "        for spin in spins:\n",
    "            if learning.is_fit(A, B, spin, A_acc = .5, B_acc = 2):\n",
    "                num_correct = num_correct + 1\n",
    "                spins.remove(spin)\n",
    "                break\n",
    "    num_incorrect = len(As) - num_correct\n",
    "    num_correct_list.append(num_correct)\n",
    "    num_incorrect_list.append(num_incorrect)\n",
    "    print \"correct: \", num_correct, \"incorrect: \", len(As) - num_correct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3, 3]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_incorrect_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "suffix = \"_di3220_29diamonds_cxABe\"\n",
    "guess_set = learning.load_obj(\"datasets/guess_dataset\" + suffix)\n",
    "xtrain=np.array(guess_set[\"train_X\"])\n",
    "ytrain=np.array(guess_set[\"train_Y\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "full_lattice = np.genfromtxt('complete_lattice.csv',delimiter=',');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(33532, 2)"
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.shape(full_lattice)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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47LHHAAA//elPcejQIVeXIggYvxoRdQdaV0f/t2vVsFM2M+uH3nG8skrYPU5Y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4U4O1TNLZE59FAAsw5Ovgkf+pBgtO8/rjMw7AEbQgGdCVcLo5UJNtfGePhrrfT1N2EWaJQ3\n3ijj1zVZQXSXn6htw0gCEpXi2LNZqcANhSQNf/asgJfpadGIK8zfsTGILeoMTfmpatLQshm0RZPn\nj1cyYPmW2vHoOuy/f5ze9hTjI3maXNNEdnrQZzbLlzQ2CkCpr3d8IYjfq64WX1KsQ+VyrZQmUMJe\nxX6mrc3xt6paRO3+Sz9faqXAQulSKYkClSMuLq7R9ZVK64ruUBztAec8i5s7FwOr1VJuVwJANvqZ\nqw1u3mNK4Fds73JQefWr+WZnHeJ28e6jTHsJwNkNFU/Y+npnQm/e7OSbiqNXo6POxFtjp9FalSDs\nsWn3z0jn+BkTtDBNTSUPMplkYCxI32seOmsm0bMZrJo6+ka66H35DaJ1/bI4dHfL99fXi1Mr3m2V\nThqlol6uZU5LC81tBuEGPx35FEMjOl4PhII2/+zOPP/+3ySJNi2KsnlDHfs/Pk7viTOM5+toanOx\n+Ro/j37VoO/ZBuxMhoqQTdC7SNNsO+nju9i7F77whTKAJBikeXMOXC6mMmEJ6uULQauAjTkbwlUT\np6s6BEhGYTYT5PpojONnvMQzHnJ5nfaWPFu7vXz6gzE5z3INYUusGDQUA5o/eqB77XYcb7OpCNlX\nXx5cBvKkD5x22WT1cmm6aGNoKTJ1pVbc3Pmk9yQzVUPUeDv4QEv3UmWcKjZTa7FlSWZ6cRHe/34B\nVrHxHAvzFg+9P40rK2NzGXjVK4jU5tFNUwBFICALX0WF/EskGHtzjnC4js5OeP01D/FFi3wefB4X\nh17xE/1QBfrevc4Cu2mTnETRvNRTSXru1HntDV0aJBOHhRgDI14+fNMFPrq7n77DDZD2ozf7IJPB\nGBsh7K6ls83Hgw8aPP20vqQ+4vXC6KhOqrqFh7/XyiNPhQkFbLDTtLfZ9J/xcv68TrSrTtDouXNL\nquNUVkrEZds2udkzMwKkMhnxWV1dS90WmpshnTCxkxk0Oy0pVcODv9bHuFUpYKoACvTTbxKtDROt\n0yBjQz4r39XY6GwQ1c78wgWWtCZUukxVESq5FtOUksw33xSA1N29+uKs2r1cDhdoLV2qQEBKcqur\nnYij4pEVK63HYlLBrcSVixXM1fNXm+XGxuXZidVSblcCQMp9phxYu9rg5r1KKr9ce5eDyqsLppJJ\nmXjdJYvRWjdRVaUUT9hMZmW6qKVFyBtTU/I9KkTf3r4m4o3scNPTep6+s42yEzU1em7qJ7LpOmB5\nlcrYiWkwG9ErKyDvR6+uhOk04xMa0Vs2izM+dUp4UBvpQ6Waba7SMkc1FD70nBfDlSGdsPjIA3m+\n8JkYrnzRLg/Qb9hFtGWCaDIJAT80NrL/kxP0Np5jfNZDg/4mhMNMBrpouqWmfGSnkNKIBGfouSnE\n3/0oTM4ysGyNkM/CABYfu5ObboIvflE+MjYGmq6zqQvOjRnUeG0yGZObr00zNR1Gb2pEj258UigQ\nZdk2NgJEPrGze0UvulKBx8u11aJPxem5YhW09dJ6a0WqygGt9VJ7GzGldj7WepIZcxA0mK0eYna2\nG5V59npXCnxGIjLdVNeQ2mofF06nmLyUY/vWIFZ943LwatfTc62H/bfNQGs7A9Zmxg6N0rwpT+QW\nIYg3hxNoWh3t7XD2rEZ1jUE2C3f+ksELr2S4a2+Y6BZzJb+nZF62tgpOaG8HnQCWPUtjIMfNm2fR\nqytpTl8AdorCuqaJBELOpEGf5pWpxqWAkqaJm2ho0Jm263j+LQgGs6I7pRsMj4DbnWZ8PEA0NC3p\ntZ4eR6A3HJaITnE6Sm3WgkEn2jIwQCQQYO8Wk0dO1aDhBcukvSVDRX2VtLdRn08kxI+dOSMRHbWp\nTKcdKQF1fMWvVNF0dU6Kc6YkXi5dcrhQ09MCrHbvLr84X8mivdoGUFUEVlU5x1fq6aVK62ozXE7B\nXD1/xZUp6afK66/L96sm1QWKxhVdS7nPFI/BYrD2C3Bz9e1dDiqvLpgyDInYKCXb0vJcJTZUbOVa\nLRSq8VbY0FB5VfI1wJreUMf+W39Er/cw41YDTVsrpIpkqkSgrrGR5qphiMWwtEV0n1d6dJkumq5r\nAJcpO0WVwtyILS5K7mV6Ws5blcQGg2Ca6BMT7O9N0rutQiJOrQVR0fNTKyNtaiAWNYjWvV5JX8zP\nQ00zBINsD7scOky5Pk+BAHqdzf6es9zRqPGbX9nDa6c8mJbGfAzqGhx1ieeec2gXsYwHr9umKgzz\n8zaV1ToxcwPNc0tMgRCQKNDHbu1YtRfdRr+7HHAqFy1Sr2nIQl0MftZL64HDg6r0u5ZSglsagmtW\n/f0scgnqvpy1hgT52eAe7iDuc+gxLS0COourIS1L+vQttaNBx/YFSdUGee4spE+IgGdXlwKvOn0n\nq9l7XRvPHw/T94oHUh74UZaec372PzBNZEeQnh547DGh9Kiit/p6SEwbjA9niW4uiTyXIThHNpn0\n9BgFIKdDopaerSeJeIdhKEvkmiA9MxfpO98OXh+4DPbsyXHoBzGefDVIbM4LhotAQOPWW51+xT4f\naJaNpRmk0xrxlM70lEVDbZm+b+XK8Eub6k5NLRGv9GSCL+w9Btpenn89hN9jUeFO09tbtfQ1S30I\nxytpnpslYk+jK3CiUm0KMG3dupxfWVEkDTA8XAgHzzpVwkqcrabGoUIUn6vXK79furR0n5cAyXq2\n2gbQ65WUoWUJIi9uQwPLN7CzswKeXC4nPVjKmVJRq9J+qnNz4sfb2go7N00aML9d9gvy9y/sbbKr\n307mjTdkMpTTQSlHPFcps/r65Zoo65lpYk3PMvD0YKFxZqPTOLPIrMlpBnzdXHKNks3YXDoTB62S\nyOEj6Nu2isMqOIpI9Qw90Rx9w10QS0EgQM+deSIVE2DVONyGjWpnqdY6LS0S1ZqZEYdkWbLyBQLo\nFRVEm2JEg+by8PpqueXisHgyKatna+tK4mfpe4v7PIXD6E1N7Axd5Ce/NMLv/vcmvvdjL9mc3LxT\np0S7aOtW56tiWR/xlImNSWeHTVVzgNiI02Nvo1YcxVniF/UXnlWZXnQbsXLAp1y0qNyxN3KeyhT/\naSGVX/HaV18e5PCFmRURqdUq9dYCWepv92/rALrZqndw1hqieraDhVe6mb9O7pHS7SqthlR/6+uD\ns+GTjAaGaA538LWvdaNpMvSUyjw44PVYf4W0Ceo00fNgZbSCLluY6B117N8ve5e/+AvhatXVFaoI\nfX6a2j2QWlwZeVaR5Joaad0yNcH+/S0O+LNjRGbG0AelNZQe9LP/wUV6z5xg3N1O045qrJNv8l++\n08lcPEE67iJjwvycjm1qfObjC9xUH+MpVx1tzRpHj3uIJzXyJmC7+Jv/keRf93qJtiTQBwclarRt\nW/my7OL5ogBYgePjqvDz+x84ycBuP+PnkzRtDhC5x0Q/n8HyBTjwnWr6XnaDy4DF6+jZtcD+3qCI\ndZZr6aLmZCn36MIFBzCpApdz52QyFlMoirmm/f1yj9VgGBwsHwVYTxKguOFwIiEI1TDk/FWXiQsX\nHFBqmgKUFYF/0ybx4cUK5uX8veoVqEBOW9vyAfl22rucp/MLe+fY1Y9MpVLOJFFWThSumEekAI3a\n5qkqIBV29/nkPdms8BwsC2t2ngMv7aDvYh3kTXCl6flnwWU8G8uCA39rcOjYTs6e3srkpE5jOEnk\nrQy90Qn2e4fQXfpS13M9Ns/+BzV6L74lFU2140Q+fiv6mzOOIyssCni9soO8cGEld0pZMCjfnU7L\nSpdIOIJ7KsqmCJnFO6ZVIm2WBQOncowtVNHcaBHpCqBnyigQKyvdlRW/lkxCayue2Vk+s2eKwXM7\nqGwLYyJNghMJoZVUV4u//H/+X51nn9U5e9YtIpwj5UU417NyZOu1etFtxFSloGXbfPG7J5cdQ6X1\n1O+mbfN/i+QZVLQJ4BO3dS595mO3dnDuS/cvHeOL3z259P9Kv2sZoFLWPxFfOn7xuZVLH6roXLnK\nRvX3J88M8Xs93fT1ddNMN/0VJ7EefJLq9g6+cE/3qiT9Yu2uex+RcTYWHOKeGhH9DIXgRz+SgGl9\nvQNe7XAltivN3EyOxUyAijovlpHmyCs2Y5NzNO+sZt8+gyNH5FmNjqqKOZ3InkbQy5S3z8zIIEoV\nSO8u13LwN5CATbsh6Jc55vGgb+4iem2QqGHAhQs8eyHFickGBqcCuDBx6xqaSyNIgr1N52AaGtw6\nh4camY3p5POi7jA6afCVv/Nw7vRm3r9rhP23jqIHCs3QiwUuFbAoni8qCqSq6XbtQj9zhqj7AtE7\nm8BjwvAgbNrEwKksfUcq6eyy0M0MVouPvoEgvc+fIdqRFh9XCt7UHC/lHg0MSPS7oUH83pYt4mvm\n5+U+VlVJJcLwsNz8UEjeNz4u91hp3ZWLwKwnCVDccHhmZrmG1cWLTtVfgXqwVAnY3i7+bHjY8YWl\ntloErKZGIlKbNjlrxsDAxjlf69m7nKfzT87ewW1nri6YMk2HA1Ccqisuz1UTehUeEeC8Z2FBdmXx\nuOQW6uuXxHMGMu30nW+ls8NC18DKZpzGmYUd+sAA9L0eosKfJUmQ1to5FpIeKpim73wLvW9NEr2z\n2el6Hgiguw2it1YTVVGo2WmH76DKkpVGhhL3WU2rpLiZcjLpVLuUOmvFoyhyIlZTixCEz0JzXKLo\njz4KfT9W4NGg5/o4+z8ZoCxHu7ghaU2NOFyPZ7l8ROEcJ8LtVFYbbGpMcnGmYsmnxeMSnVc9qItF\nON/Oti4gpfc+nxzrxhuXq5+vZsXRHUPTVk3rffXlwWUARnG1YHm1nXqt+HtKwQ/AA7tal0jspVaq\no7Va+lClGrc0BFdUAhYDsP0POCm8T/1wCNu2eW5kiAPRtSNrCrB8/NYOvnZ4iKZEB7pf/lZXJ2ug\nmlog4HX3zQb/86+DS6kz60SWRNzFYrySSn8O20hDIIhtO0VeqmJu2bNSDvHECZnfk5MyBuNxRxhL\nmar0qq52IjLBIFZTC/3nDI6+pHP8Yh2jc348uoXfbWIbGrGcC5+Z4NEfNjKx4GN+KsfIiIZlgsct\np5DPQ1bX0XI5+k5U0XvbVqKduszLUnCges4psKHaUxVXw+XzwgfVNNlIAWgaY7FC2r5ShG91gLEE\n43YD0S7d4T8VL+zFAK6Ye+TxiF95802ZfLt3SyStVGPK65WI1PbtTqpwbs6J+ihgVrwgqeOupvtX\n0OdjelreV1xRrZ5VabpMvVbMlduIqXvR0aHE0ATAKdHnfGGzcqUcm9JFuRzF5Bf2zrN3cNuZqwum\nXC76k22MXfLRHE4QiXaKk43HnSq86enlpHFFviyt8FOVJEo4Lhz+/9s7s9i4rvOO/84dcsgZLhLX\n4SKRojWiDUm25USIlSaSgySO7TRF3KAt4jhCUCNNUNRFU/TFqVEkqWE4femCoH0IUmdpmwQB0iYG\nsscILDqBnTi2JS+yJUqyJK4iNaKGHM5wyLmnD98c3ss7MyTF4e7zAwRx1nvmnnvO/Z/vfItMAPm7\n7HC4G1wRUszOSpLLyYV+NsPDQCRCKqPAzc1P+NNuBK5fZ+Rcit6Os7L6m56W+nuJRKEVqtiE659M\nSu3FB1dFXV2etW1sTM7HuXMyCe7cKcdMpXAHhnjye7X5moIhqI6wr9fhzBnYc3MEJ53CnZmh7+Va\njn3MC81egL8gaSIhx+rulknX+GDlz3OsxSWZruDC+TlyNV6qr9rahVtupZJrluMX5I9YM6TTy/OV\nKuYE7hcn/uSbfjGk8ASLn72tNdzZ0zT/ff7EnHmXJUAEU2VIMZvT8/8H21XqPAS3Gvd+/scFIjAo\nwMw5fzBx40lBH7v/IMf3H+Txx8FtkD7UWnaNHnxQ7uNGGJvt1pkZuZe5MzCVrqAjlqa1CcZGZ/np\nr+Hee2XIuK4E/50/H+gv/4Ipk5EF0BtviKnzwAGxMPv9Kicn5Qba2wvV1bijY3ztG2G+/oMdXBlv\nYnpqJ5PpEDoHs5WaymqHmiqXTK6SMwOV3LZ7gsmxqvm1jaM0WkHOdZhzQVWHYS7FSCJMb/NOOd7o\nqIxBpbwcEmYO2r1bxqPZ5zYWJFOEMJPxso93ddFen4WK6MJt6uwcbdXX4a3rskowA8mfKuDSJZnj\nTFSh44iojETk+Mmk/J13hDc1R4lGZfya33DkiCxijR9Sdd765i/Q3NHhzV3BvH/GSmcWiJ2dco4m\nJuR3dnV5CT2D22Ur3UIzlqqODnELGRryIgd9VswVs5E35U1sXdn0bGIft3UVU+NTER7/Sn2+wFuz\nF94+MuQlghsbk0nEDE5j9vBHkSST3sokk/GqqhpyOdqbZyGTw03M4DTswI3IQPb72bS3A8qhpiUK\nThbXqYSKCqJqmilCtO2phgjeNmMs5pWnAW9l5+/Ynh4ZKMZ8Y1ZupZLiBYs5nzzplZ6ZmpLz0tS0\nwErXf2KEvt/skOi2XAa3wuXZZ+uIVLs46VRePFZCJMLImENvb5HBOzEh53liQiZmrUVI+X9LNIo7\nmeLEc82MjipOJSLzV0xLi8zxyaRYLb71+qt85+vFBdNKy6iYU1wqku/hH3kO31OZXMGxg8IkKE7O\nPfFhHrv/ID2P/GheCB0/0j3/HU+dHCzwfzp3JTXvVO4XYPtitZwdnZr/ntmc5q0v/yHA/DENe1tr\nuP1LP+N6eo4dkQpOfuGeBYLTv31YTASWOocrza8V3EbVWnRLOLzQwmgc3pWSfzntgKuZTiuYnSU1\nK6YtM7+VDBQw12E0Ktf/W2/J/8kkPP20iKtDh+S6nJ4WcbV/v3T+a6/R//I0P3l6D6kp6GzLcWkw\nxOw1h5CjmXHDhN0sVSrHzbdWMpvMyFZ3KEqoQuHkpNyNqx201lSFXdraFKlsjLbbayCbtwJrLeMv\nnZZIi+Zmqa1jqhqYceuPBpubE+V4/bqcvLzPUHx/nKN3R+j7tXcKjt46QTw6BFWNIlxMIl9/qoAX\nX/QKJr75pozbpiYZDC0t0k5T+bury0vQmUhIuzo7PbHQ2uqlexgbk9x3wRuSWdwF8/4ZK53Zrjt1\nysvEPjPj1RAstv5aAEMAABH2SURBVF12o1topYSG8atLp0UMJhKFVswbYSNvypvYurLp2cQ+busq\npqZS0L1H4ewIhLc7vgu7sxNeekmS4UQiMujNQPVPWmZwgVebz+zlt7URb5ji6Pub6ftNBKZDEHEK\n/GzMTeTECYhWzTE4FiW2c4ZJZwfH7hgh/v4uaI8VmqfNgDcrta6uhY6VK8mDYr7ThAi3tnorMP9K\n9epVhs9HIOTghDQ4lThzs1I5YmIGN5PFqarEzWQh7Ui+rGKD9/JlL1GgKdJmJpiJCTn/QP9AlF//\nppkP3DXHxGyVJAy9Dp/9rPwsc7Pd92hpwVROweDFIvmCDt/BYxcTF3tbazgzOsXeVhmE//CDV/Hb\njfzfUczvyV/Tz1ijFIXJN3dEKhZYwPzbfueupObFlb/txc5fMRG4WkWSDX4fqqEhePZZsUKdPSuv\nm0VPNis7cqbQwNRUiDffcMlmchAOU9MkTshmB78gUCCbldD9M5KTzW1qof90juHL7bSHrxLvyODs\n6/Ru1g0N3pdNTs5XaB6efAfT0xqlc2TSIdKzlUSjOdwcNNTMkHMd/uiOi3zmL+r4p6824EYzdDSm\nqY/OMTcbwsElpxSugt2tGYYSVew7UIXbWI1bncMx0YWuK20GL9tpU5OMnxdflLE6NeUJk7o6Gae7\ndolFbXAQhoZw4nEe+nPNsfflt8BbcsRHL+JcS8FgWkRBTY18pr9fvvett+S7u7u9iL9oVETU1avy\n+OJF+TuVEgHa1eXl2FNK9v5bWuQ3jI7KfNrYKJ148qREARa7IZk9Wn8Wav92XSbj+TAZoRMUVGbb\n8kZFQimhYeZ98Gq3lePfZHY0DMVqCK4VaynktrvVaxP7uK17BnRT727BqjXuU5uDg/JiZz5By8DA\nwhu9P1T44EGZnE+flgmpp0cmlWwWpzbKQw+kOXYkxMjlWdoO1xT48Cy4iZyaZiYxRdXEKB0Tp4n3\n5HB23iWT27Vr3v69P5Hc7t0yIF96SSY8vyNpMatTMMoPvAsjmZTn/ZmEDc3NIqQyGdi9m/buHPSl\ncHMRnNwsbkVYaoz1pDg7EMnf5cVnKh6vgfMlBq9JQtjWJhOnCc8eGJDHzc0Mv6IhlyO0s4EmoKlF\nfnJNjZw3k9zxfbu7+NXlSzxQRDCVk5HcLD6LRfKZxJd+y9RSnLsizrHGGTy4lWe27779/KWSjuRB\ndOBxb6x2XjD913MXOX6ke95nyxzDWL12RCrmn1tMcJYjSJeD2aIFEVFeWgRv0RMOi8a/fl3ep7Wi\npTXE1Zl6fp59laH6S7Tf18Vk8iBTky6k03INRnOQi8lYHR+Hm27CPXuOJ78/R9/AbflF0DhHD2d4\naPcYzq5dMjHceqsXkfrcc5JzqL6e9ropoqFZ9GwlMxVila6uglpnmkN7k2ituP/dY9xSneDoPbvo\n+ylod4qupimaq3LU1YfQFRW8Y3+GcE2Y89fqGB2DJ76Y4uihEA99qAFnbEwEXGurjNHxcS9gJJGQ\n8V1MmJiotkTCK2qeTOKMjNBbXy9zXS4HVx0v8i6blTktl5O5xuSdSqVEVLXn/Ta7u0W4jY7CD38o\nHdTTI/PFa69Je+Jx+WcWlzMznm+XUcF798ogDmY/989rfofx4BZeY2PxLb3VsLiUEhqmjRUVXqmw\nrSoS1tK6st2tXps4F9W6p0ZwcXAIrFr9atM4X5sVqYk8KXYBmqKa3d2eGIjFZAKaljIXvW1JevfW\nLCg1FmiS+JzsbYCTl+BqEnbsl1XhiRMyicVi4uBuQor9A762ViZD41h/I8UzoTDUurVVJtWzZ+V7\nzCqxpUUmuYoK4k1zHH0lSd+ZCFRWQ3VEaox9KMv5N6YYmayhrS4lpSocip87k+9r1y65IVy75mVR\ndl2xGlyOcHm6muvX3HmN6O+3hf5MBznKQfaMe8KnXIyoOXRzFxff9MSYsTCuJPFlsAZg0Gr0/IWr\nRVMcFCMoogwms7k/LYLh+JFunr9wlevpOXpjtdzZ0zRvwfJv7wUpt0TOclnMEtjZKW5Cxq0uWu2S\nvJLmkx+Z4C/flN94pe4i33zPDCPJKG1dYeIHq3HS0wutro5Df/VB+i5E6D68UyoPvHWdvlNhjv3B\nHL3tFbIoMjf7wUEZf7fdBleuEK8Y5L6bz/H11G0MXAsxPQ076hUHOlIcaL/GpclGOm6qxnFmZbG0\na5SRy7O0Jvthbo4rU1HaDrXhTiR54qeHuPXWvHAcz/sZvrdDEoxOTHilYyYnPatTfb2059QpsZZc\nuybvqauT7cmBAXkuEpH3B7N7Dw+L6Boels8r5Y3HhgYZ57mcHGd8XOaXfftk8WhuJg0Nom6rquT1\nZHKhMMrlvILwXV3yPnP+jf9ZMBzWP68Zh3GTC8wfmNLd7fm0+Y+5GhaXUkJjtW+iMzOedU1rbxdg\nPVhL68om9ina7qyrmKqt9QJEwBfe7vgGSjQqqypzEZiLotgFeOGCTBJmsopE5L1dXZ7oWe7FGiy0\nODwsM6wxjWQy8gOCwi6YubfUxVvqIi8WvZfNyiTc0+P9hnzZDkIhnNkZHvrrGo5N13uRcz05nJEc\nvTWD9NYg56A9/7uLnbvmZrEUJBKeg/vOnTA+jjue4Mmfd9F3JoaemWF0MsKVp6WvlPL6bTF/ppVm\nJvdjtr5enrzETx49WFaUoN8n6fiRbr79/CVqq0MFUXfLqZW3HEp9z2P3H2TPIz+af08xwfXfz11E\nU5iKYT3E1GKWQJOR3/hWTY2nuesdU9z9QXgwU8m3L2b5RFeY3l3T9A6cgdZeCLUvtGiMj0NjI8MX\nMhBpxMnNQmUlTnsbTM0yMjlD7zvrRDgYX8jXX/ci21pbcYaG+PTDEY5FovzuRYdnnoHxcYf6UB2X\nUoqjNw8TV+cgHMfROXpbJ+h1xiHnwNA4t+yqhnp4JtENkYgnHCtDMDnFyCtj9B7Kwn33iZDzJ/TM\nZr1KB3V1sujascPLFZWTLc/5m3QsJv5O/jnCCK3OTlk0RSIyt4yNyWumQe3t8J73FBcRe/fKADQL\nukOHFr5v9275Z4jFvPHe3FxYhQKKC5lidU3D4eJtWg2Ly3pt42yk781aWlc2sU/RdmddxVRzMzz6\n6BKh86Zekn9VZUy6xRLbnT8vgqq62rNi7du3uAl4OcUzjbDJZOSOkkjIpBUUdsHMvTdaPLNYqLVS\nXlG1oGN7/rNOLEZvyCdahopMeotVYA+FJKwa4Je/FCGVz6Lcf7GKvrMxuhuSODURut8V5dXTcM89\nspsRdEheaWbypfBvbRWLErwRgpF9Oa2LWp6Wu7W3Uj70L88ssFoF2wiexcvv5O6vE7iWLJbTy78t\nPjICbTPjxG+pwAkpHjtQzWO6H9o7IOXKDdefh8lEq+Zv6O1726E1hluRxpmbxa2KQHszbR/ppCD8\n1GynRaNiITp0COeO27klFOKWAxJ12N8PI4MR2iYuEo+O4zT3emLAbM+lUiJglIIDB2jfFYNnnULh\n2Jj3kypWNLimRsbm4KBntTblU8xngj6TwTmioUG+J5MRIdXQIG0yPk9mIJm5DwrnLGOlSiRkNVNM\nHPkJh73xXopSC9blWjpWQwit1zbOJva9KYvt+ru2AOu7zUfx0PkFhEKFq6pSmMFeUeE5amazS++l\nL6d4ZlOTZ/U6f14uzO7uQmEXzNxb6uJdKtrFlJHwizq/dW2pSaYc867PYkAiwTB7oKkZp0d8OkJ4\n9dL8fbeYFWM1WM2tLX9UXKkcULD01l65nBmdIuRPWAsF5WuMZeoTd3bN/60KvmltKBBMgUXPgvQX\nQ5ULFx/gLTyqqmQM+f1yfAI+7sLRq9DXVzd/7KPHSiRiNb6RiYRs9Rkh4WuztCkE/VUQ2e9Zhqan\nC/O51dRARwfxtoBwTCqOfiBM/FgHqPzWT2ARMz9ue3u9PHL+pLeGxeYI48RtfBXB82+Kx5fnJgBL\niyPDcp2SSy1Yl2vp2MT+LAVspbbeCNv1d20ByhJTSql7gX9D7rdf01p/eVVatVxKrRyXopTwKDYB\nVlV5BU+XOwGVamux9xV7biWri3LMu/6bVXMz7R174NmlRVK5mcnXA//2XtA/aqPwp0kA+KQvHQNQ\nNLXEWjmeF6NUvrAC/NdpY6M8vnJFrC1NTeIsXWJhs5RoW8ByrCqGYuOgxHgqaINKS11OFV18EVPK\nel6KYsEopj0miizoDB6knMWSX4glk/JjTWWFpRy5raXDYlkWSutSbrRLfFCpEHAGuBsYAH4HPKC1\nfr3UZw4fPqxfeOGFFR2vJCsJBS1SrX7Lq/lVDIktlihzPidYsLahu3ZZz1cDk1LAWIOMkDl+pHve\n6rMZMPmtyklwuqFsljFVzjjYzGHl5Zzf/n4vi/rwsCya9u/fPnOfxbKGKKV+r7U+vOT7yhBT7wa+\nqLW+J//48wBa6ydKfWZNxNRK2MyT5iZhs4skw1Liw/+6idRbDb+o3lgtP//buxbU7lsMc0wTwRdM\n+hlSinNPfHiB+Fssum/TsZpjyo7PQoLnpLnZi6hb6hz5hZiJ2G1v96LY1suUbPvVsgVZrpgqZ5uv\nE7jsezwA3FnG960fdl95SZa91bMG3Ih1JpjsMvjZYB0+KPSL8peCWQojogz+vxcTVlOZ3HxGdCgs\nomy28dY6n9SasZpjarvnylkJpQoBL+ccrSRgZi2w/WrZxpRjmfoT4F6t9afzj48Dd2qtHw687zPA\nZ/IPbwbeXHlztxTNwPhGN2IrEo7F32kUTna0//eLvTe0I9YVqq5ryWUmx3LXRy8V++z8c0XIpfOf\na4u/c6l2ZUfm27Jo31a23nS7cpwFCxVznKWOYYFqqHLBNY8dcDIws06H3xLjtpxzFIZKBxwX3CzM\nrl0rF2L71bJGrHXfdmutW5Z6UzmWqUHAH3K3K//cArTWXwW+WsZxtiRKqReWYxq0bD1s325fbN9u\nT2y/bl82S9+W4wXzO2CfUqpHKRUGPg48tTrNslgsFovFYtkarNgypbWeU0o9DPwMSY3wpNb6tVVr\nmcVisVgsFssWoKw8U1rrHwM/XqW2bDfedlubbyNs325fbN9uT2y/bl82Rd+u2AHdYrFYLBaLxVKe\nz5TFYrFYLBbL2x4rplYZpdSfKqVeU0q5SqnDgdc+r5TqV0q9qZS6Z6PaaFkZSql7833Xr5R6ZKPb\nYykPpdSTSqkrSqlXfc81KqV+oZQ6m/+/YSPbaLlxlFK7lVK/Ukq9np+L/yb/vO3bLY5Sqlop9Vul\n1Ml8334p//yG960VU6vPq8DHgBP+J5VS+5GIxwPAvcB/5EvyWLYA+b76d+A+YD/wQL5PLVuXbyBj\n0c8jwNNa633A0/nHlq3FHPB3Wuv9wBHgr/Jj1fbt1mcGeL/W+nbgEHCvUuoIm6BvrZhaZbTWp7XW\nxRKTfhT4rtZ6Rmt9AegH3rW+rbOUwbuAfq31ea11Fvgu0qeWLYrW+gSQCDz9UeCb+b+/Cdy/ro2y\nlI3Welhr/WL+70ngNFKxw/btFkcLpsxEZf6fZhP0rRVT60ex8judG9QWy41j++/tQUxrPZz/ewSI\nbWRjLOWhlNoD3AE8j+3bbYFSKqSUehm4AvxCa70p+ras1AhvV5RSvwTairz0qNb6h+vdHovFsvpo\nrbVSyoY7b1GUUrXA94HPaa2TSnk1pWzfbl201jngkFJqJ/B/SqmDgdc3pG+tmFoBWusPruBjyyq/\nY9m02P57ezCqlGrXWg8rpdqR1a9li6GUqkSE1P9orf83/7Tt222E1npCKfUrxO9xw/vWbvOtH08B\nH1dKVSmleoB9wG83uE2W5WPLJ709eAr4VP7vTwHW0rzFUGKC+k/gtNb6n30v2b7d4iilWvIWKZRS\nEeBu4A02Qd/apJ2rjFLqj4GvAC3ABPCy1vqe/GuPAg8h0Saf01r/ZMMaarlhlFIfBv4Vr3zS4xvc\nJEsZKKW+A7wPqTo/CnwB+AHwPaALuAj8mdY66KRu2cQopd4L9AGvAG7+6b9H/KZs325hlFK3IQ7m\nIcQY9D2t9T8qpZrY4L61YspisVgsFoulDOw2n8VisVgsFksZWDFlsVgsFovFUgZWTFksFovFYrGU\ngRVTFovFYrFYLGVgxZTFYrFYLBZLGVgxZbFYLBaLxVIGVkxZLBaLxWKxlIEVUxaLxWKxWCxl8P+Q\nmkyOSED7xAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e772cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.plot(xtrain[:,2][ytrain==0]/analysis.mag,xtrain[:,3][ytrain==0]/analysis.mag,'ro',label='(train) false spin',ms=4,alpha=0.1)\n",
    "plt.plot(xtrain[:,2][ytrain==1]/analysis.mag,xtrain[:,3][ytrain==1]/analysis.mag,'bo',label='(train) true spin',ms=5,alpha=0.5)\n",
    "plt.plot(diamonds[1]['A']/analysis.mag,np.abs(diamonds[1]['B'])/analysis.mag,'o',label='true',ms=2)\n",
    "plt.plot(As/analysis.mag,Bs/analysis.mag,'kx',ms=20,label='fit')\n",
    "#plt.plot(lots_of_A/analysis.mag,lots_of_B/analysis.mag,'o',ms=5,label='all_C13',alpha=0.5)\n",
    "#plt.plot(full_lattice[:,0],np.abs(full_lattice[:,1]),'o',ms=5,label='all_C13',alpha=0.1)\n",
    "plt.legend()\n",
    "plt.xlim(-15,32)\n",
    "plt.ylim(0,85)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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WD55mQ/l1wVo7dWh1X68sWX69FwLnES7ijMCtmAKsCSohpASuNSLqDnRwkJZI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\nGEkyc/QotLWVYLMVkZ5ejKqKqq7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9tbeLiWIy+fai8+mUL4IAn43EFA7nKz4JLOM/gU0r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mUOVfxPTc3SRabys8+3+hyLxcSxwSC8+674m1JpIZ8HonohGAS3GzmXpTsQo3tdPQzMlzlI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\ng0wBAAwyBQAwBJ94eGmFKmCzAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10efc3710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "plt.plot(xtrain[:,2][ytrain==0]/analysis.mag,xtrain[:,3][ytrain==0]/analysis.mag,'ro',label='(train) false spin',ms=4,alpha=0.1)\n",
    "plt.plot(xtrain[:,2][ytrain==1]/analysis.mag,xtrain[:,3][ytrain==1]/analysis.mag,'bo',label='(train) true spin',ms=5,alpha=0.5)\n",
    "plt.plot(diamonds[1]['A']/analysis.mag,np.abs(diamonds[1]['B'])/analysis.mag,'o',label='true',ms=2)\n",
    "plt.plot(As/analysis.mag,Bs/analysis.mag,'kx',ms=20,label='fit')\n",
    "#plt.plot(lots_of_A/analysis.mag,lots_of_B/analysis.mag,'o',ms=5,label='all_C13',alpha=0.5)\n",
    "plt.plot(full_lattice[:,0],np.abs(full_lattice[:,1]),'o',ms=5,label='all_C13',alpha=0.1)\n",
    "plt.legend()\n",
    "plt.xlim(-15,32)\n",
    "plt.ylim(0,85)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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8gZ+1ozPatKUrFtTKlpnWfh5rXmljSldzusqPHPFPvOx29pqVJTfJONpnrNXH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9igo7kxMPP9loq//uJ3Mnasa/OoigqiZ58lmjnTcfvQUH7PTz3F69tu4/W330qKQf+wN+i2fp+b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\niIiISJD/H1d7AtlBryowAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110513890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fitted_M = analysis.calc_M(As,Bs,64,omega_larmor,diamonds[1]['tau'])\n",
    "clean_M = analysis.calc_M(diamonds[1]['A'],diamonds[1]['B'],64,omega_larmor,diamonds[1]['tau'])\n",
    "plt.figure(figsize=(13,5))\n",
    "plt.plot(10**6*diamonds[1]['tau'],clean_M,'go',ms=1,label='clean signal')\n",
    "plt.plot(10**6*diamonds[1]['tau'],diamonds[1]['data'],'ko',ms=1,label='noisy signal')\n",
    "plt.plot(10**6*diamonds[1]['tau'],fitted_M,'ro',ms=1,label='fit')\n",
    "plt.plot(10**6*diamonds[1]['tau'],fitted_M - clean_M,'bo-',ms=1,label='fit - signal')\n",
    "plt.legend()\n",
    "plt.xlim(10,15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$\\frac{\\vec{a}\\cdot\\vec{b}}{\\left|\\vec{a}\\right| \\left|\\vec{b}\\right|}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.96875946523919365"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(fitted_M*diamonds[1]['data'])/np.sqrt(np.sum(fitted_M**2))/np.sqrt(np.sum(diamonds[1]['data']**2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
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      "99\n"
     ]
    }
   ],
   "source": [
    "many_many=[[],[]]\n",
    "for i in range(100):\n",
    "    print(i)\n",
    "    A,B,_,_,_=NV_generator.generate_spins(450);\n",
    "    many_many[0].append(A)\n",
    "    many_many[1].append(B)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#pickle.dump(many_many,open('many_spins.pickle','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "lots_of_A = []\n",
    "lots_of_B = []\n",
    "for thisset in many_many[0]:\n",
    "    for thing in thisset:\n",
    "        lots_of_A.append(thing);\n",
    "for thisset in many_many[1]:\n",
    "    for thing in thisset:\n",
    "        lots_of_B.append(thing);\n",
    "lots_of_AB = zip(lots_of_A,lots_of_B)\n",
    "lots_of_AB = list(set(lots_of_AB))\n",
    "lots_of_A = np.array(zip(*lots_of_AB)[0])\n",
    "lots_of_B = np.array(zip(*lots_of_AB)[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Yet another test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# new diamonds \n",
    "diamonds=[learning.load_obj(\"new_diamonds/diamond_1\"),\n",
    "          learning.load_obj(\"new_diamonds/diamond_2\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "diamond_ind:  0\n",
      "dips measured:  370\n",
      "num_removed:  0\n",
      "correct:  16 incorrect:  4\n",
      "diamond_ind:  1\n",
      "dips measured:  372\n",
      "num_removed:  1\n",
      "correct:  16 incorrect:  3\n"
     ]
    }
   ],
   "source": [
    "# What is Michael doing here?\n",
    "# First he imports two sklearn objects: a scaler and a classifier.\n",
    "guess_scaler = learning.load_obj(\"classifiers/scaler_svm_rbf_di3220_29diamonds_cxABe\")#(\"classifiers/scaler_svm_rbfguess_limited_3220_C1_29diamonds\")scaler_svm_linear_di3220_29diamond\n",
    "guess_clf = learning.load_obj(\"classifiers/clf_svm_rbf_di3220_29diamonds_cxABe\")#(\"classifiers/clf_svm_rbfguess_limited_3220_C1_29diamonds\")\n",
    "num_correct_list, num_incorrect_list = [], []\n",
    "As_list, Bs_list = [], []\n",
    "guess_As_list, guess_Bs_list = [], []\n",
    "dips_measured = []\n",
    "# He then iterates through all of the 29 diamonds.\n",
    "for diamond_ind in range(len(diamonds)):\n",
    "    print \"diamond_ind: \", diamond_ind\n",
    "    diamond = diamonds[diamond_ind]\n",
    "    tau = diamond[\"tau\"] # This is an array with all the free evolution times.\n",
    "    data = diamond[\"data\"] # These are the corresping M(tau) values for N = 64\n",
    "    N = diamond[\"N\"]\n",
    "    dip_inds = diamond[\"dip_inds\"] # indices for the dips in data\n",
    "    windows = diamond[\"windows\"] # these indices determine the window around each dip\n",
    "    min_dip_ind = 3220\n",
    "    measure_dii = filter(lambda dii: dip_inds[dii] >= min_dip_ind, range(len(dip_inds))) # only times after 15 micros are taken\n",
    "    print \"dips measured: \", len(measure_dii)\n",
    "    dips_measured.append(len(measure_dii))\n",
    "    spin_dict = {}\n",
    "    for dii in measure_dii: # this loop iterates over all dips\n",
    "        if diamond[\"good_fits\"][dii]: # If this happens to be a good fit then\n",
    "            dip_ind = dip_inds[dii] \n",
    "            res_tau = tau[dip_ind]\n",
    "            for phi, x in zip(diamond[\"phis_list\"][dii], diamond[\"xs_list\"][dii]):\n",
    "                for omega_tilde, cosphi in analysis.calc_omega_tilde(phi, x, res_tau, omega_larmor):\n",
    "                    A, B = analysis.calc_A_B(cosphi, res_tau, omega_larmor, omega_tilde)\n",
    "                    if analysis.valid_A_B(A, B):\n",
    "                        if (dip_ind, phi, x) in spin_dict:\n",
    "                            spin_dict[(dip_ind, phi, x)] += [(A, B, cosphi)]\n",
    "                        else:\n",
    "                            spin_dict[(dip_ind, phi, x)] = [(A, B, cosphi)]\n",
    "    def guess_classifier(features): # this defines a pipeline with scaler and classifier.\n",
    "        #flip a coin\n",
    "        the_coin = np.random.rand()\n",
    "        if the_coin < 0.1:\n",
    "            return np.array([0.])\n",
    "        else:\n",
    "            return np.array([1.])\n",
    "        #return guess_clf.predict(guess_scaler.transform([features]))\n",
    "    guess_As, guess_Bs, dataerrs, _, _, _, _ = analysis.choose_spin_guesses(spin_dict, N, omega_larmor, tau, data,\n",
    "                                                                guess_classifier, x_min = 1, error_fun = analysis.squared_error)\n",
    "    cluster_As, cluster_Bs, cluster_dataerrs = analysis.cluster_spin_guesses(guess_As, guess_Bs, dataerrs, eps = .075, min_samples = 1)\n",
    "    As, Bs, num_remove = cluster_As, cluster_Bs, 1\n",
    "    while num_remove <= 2:\n",
    "        As, Bs, num_remove = analysis.remove_spins(As, Bs, N, omega_larmor, tau, data, num_remove = num_remove, error_fun = analysis.squared_error)\n",
    "    As_list.append(As)\n",
    "    Bs_list.append(Bs)\n",
    "    guess_As_list.append(guess_As)\n",
    "    guess_Bs_list.append(guess_Bs)\n",
    "    \n",
    "    print \"num_removed: \", len(cluster_As) - len(As)\n",
    "    num_correct = 0\n",
    "    spins = set(zip(diamond[\"A\"], np.abs(diamond[\"B\"])))\n",
    "    for A, B in zip(As, np.abs(Bs)):\n",
    "        for spin in spins:\n",
    "            if learning.is_fit(A, B, spin, A_acc = .5, B_acc = 2):\n",
    "                num_correct = num_correct + 1\n",
    "                spins.remove(spin)\n",
    "                break\n",
    "    num_incorrect = len(As) - num_correct\n",
    "    num_correct_list.append(num_correct)\n",
    "    num_incorrect_list.append(num_incorrect)\n",
    "    print \"correct: \", num_correct, \"incorrect: \", len(As) - num_correct"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## And another with the 29 sets that Michael analyzed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# P(reject) = 0.5\n",
    "results={}\n",
    "results0=[0,374,2,18,6,1,429,0,14,5,2,431,0,8,6,3,357,0,13,1,4,426,0,7,1,5,406,0,18,2,6,406,0,12,2,7,375,0,11,2,8,390,0,9,0,9,445,0,14,2,10,388,0,8,0,11,385,0,8,3,12,375,0,7,1,13,402,0,7,1,14,397,0,15,2,15,379,0,12,2,16,372,0,12,2,17,387,0,12,3,18,407,0,17,0,19,401,0,10,6,20,375,0,9,2,21,381,0,20,0,22,433,2,13,2,23,368,0,5,3,24,337,0,11,1,25,405,1,20,6,26,378,0,7,0,27,390,0,10,3,28,374,0,11,2];\n",
    "results0=zip(results0[::5],results0[1::5],results0[2::5],results0[3::5],results0[4::5])\n",
    "results['p=0.5']=results0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# \"Machine learning\"\n",
    "results0=[0,374,4,19,6,1,429,0,21,4,2,431,0,16,9,3,357,1,14,2,4,426,1,11,2,5,406,1,22,3,6,406,0,14,2,7,375,0,14,1,8,390,0,16,1,9,445,0,18,7,10,388,0,10,0,11,385,0,10,3,12,375,0,9,1,13,402,0,12,1,14,397,0,18,0,15,379,1,13,2,16,372,0,15,3,17,387,0,14,4,18,407,3,22,2,19,401,1,12,4,20,375,1,13,3,21,381,1,23,1,22,433,5,13,4,23,368,0,9,0,24,337,1,12,3,25,405,8,26,7,26,378,0,11,1,27,390,2,15,2,28,374,2,13,1]\n",
    "results0=zip(results0[::5],results0[1::5],results0[2::5],results0[3::5],results0[4::5])\n",
    "results['machine learning']=results0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "results0=[0,374,2,19,6,1,429,0,22,4,2,431,1,13,8,3,357,1,13,3,4,426,1,10,4,5,406,1,21,4,6,406,0,13,3,7,375,0,9,3,8,390,0,14,2,9,445,0,18,6,10,388,0,10,1,11,385,0,8,6,12,375,0,9,1,13,402,0,11,2,14,397,0,18,0,15,379,1,11,3,16,372,0,15,4,17,387,0,12,5,18,407,3,22,3,19,401,1,11,9,20,375,1,12,6,21,381,2,20,1,22,433,4,13,4,23,368,0,9,3,24,337,1,13,4,25,405,4,21,11,26,378,0,11,1,27,390,2,14,5,28,374,2,13,1]\n",
    "results0=zip(results0[::5],results0[1::5],results0[2::5],results0[3::5],results0[4::5])\n",
    "results['p=0.1']=results0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "results0=[0,374,4,19,6,1,429,0,21,5,2,431,1,13,10,3,357,2,14,3,4,426,1,11,4,5,406,1,22,3,6,406,0,13,3,7,375,0,9,3,8,390,0,14,2,9,445,0,18,7,10,388,0,10,1,11,385,0,8,7,12,375,0,9,1,13,402,0,12,3,14,397,0,15,1,15,379,1,11,3,16,372,0,15,4,17,387,0,12,6,18,407,3,18,5,19,401,1,11,9,20,375,1,13,6,21,381,2,24,1,22,433,5,13,4,23,368,0,9,3,24,337,1,12,5,25,405,5,20,11,26,378,0,11,1,27,390,2,14,5,28,374,2,13,1]\n",
    "results0=zip(results0[::5],results0[1::5],results0[2::5],results0[3::5],results0[4::5])\n",
    "results['p=0.']=results0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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S+wK/LdK+uiOPb2F5fAvL41tYHt/C8vgWVvPje3pKqV8+K/UsXD3HJqW0FFha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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x103cdb410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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S+wK/LdK+uiOPb2F5fAvL41tYHt/C8vgWVvPje3pKqV8+K/UsXD3HJqW0FFha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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e051350>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_width=0.2\n",
    "bar_index=0\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.subplot(2,1,1)\n",
    "for key in results.keys():\n",
    "    these_results = np.array(map(lambda x: list(x),results[key]))\n",
    "    xdata = these_results[:,3]\n",
    "    plt.bar(np.arange(29)+bar_index*bar_width,xdata,bar_width,label=key)\n",
    "    bar_index+=1\n",
    "plt.legend()\n",
    "plt.title('correct')\n",
    "plt.xlabel('sample index')\n",
    "plt.ylim(0,25)\n",
    "plt.ylabel('correct')\n",
    "plt.subplot(2,1,2)\n",
    "bar_index=0\n",
    "for key in results.keys():\n",
    "    these_results = np.array(map(lambda x: list(x),results[key]))\n",
    "    xdata = these_results[:,4]\n",
    "    plt.bar(np.arange(29)+bar_index*bar_width,xdata,bar_width,label=key)\n",
    "    bar_index+=1\n",
    "plt.legend()\n",
    "plt.title('incorrect')\n",
    "plt.xlabel('sample index')\n",
    "plt.ylabel('incorrect')\n",
    "plt.savefig(fig_dir+'bar_charts.png',dpi=200)\n",
    "plt.savefig(fig_dir+'bar_charts.jpg',dpi=200)\n",
    "plt.savefig(fig_dir+'bar_charts.pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## And now the same as above but with additional samples, times taken, and statistical analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# P(reject) = 0\n",
    "# time taken: 23.3 minutes\n",
    "results={}\n",
    "results0=[0,388,0,12,4,1,404,2,16,4,2,370,0,15,4,3,382,1,15,1,4,408,2,9,5,5,408,0,4,10,6,420,1,13,5,7,365,0,12,2,8,379,0,12,5,9,373,0,7,5,10,352,3,17,2,11,376,2,17,3,12,455,1,17,11,13,408,0,13,6,14,349,0,14,3,15,388,0,11,4,16,389,4,19,4,17,382,2,14,1,18,425,1,17,4,19,433,4,17,5,20,429,0,19,6,21,382,2,15,5,22,405,0,11,1,23,383,1,9,3,24,354,0,13,4,25,372,0,21,3,26,420,4,16,5,27,407,0,13,9,28,415,1,13,5,29,390,2,13,6,30,383,0,17,7,31,413,2,20,6,32,387,1,16,5,33,365,4,11,7,34,377,0,14,2,35,355,1,9,4,36,390,1,12,3,37,438,2,19,6,38,407,2,13,4,39,400,1,12,3,40,423,0,4,3,41,424,0,14,10,42,360,3,16,3,43,401,1,13,5,44,397,0,8,2,45,372,1,8,0,46,426,3,15,5,47,356,1,14,1,48,400,0,9,1,49,419,0,10,5,50,450,2,20,10,51,396,3,15,3,52,372,3,12,6,53,417,1,10,5,54,398,2,18,5,55,375,3,12,4,56,366,0,17,9,57,389,1,9,5,58,409,3,20,8,59,416,2,21,2,60,380,1,14,4,61,368,2,11,7,62,414,0,8,4,63,350,0,13,3,64,389,1,9,3,65,382,2,13,2,66,373,2,9,2,67,385,0,17,2,68,423,0,9,6,69,374,1,10,4,70,385,2,11,6,71,389,0,7,2,72,410,0,21,1,73,394,0,13,3,74,379,3,6,4,75,377,0,16,3,76,389,2,12,2,77,342,3,20,1,78,435,2,13,5,79,369,2,13,10,80,386,3,14,3,81,392,0,8,2,82,416,4,26,9,83,419,0,11,9,84,406,1,13,6,85,385,0,9,2,86,414,1,13,3,87,415,3,13,11,88,396,0,12,6,89,370,0,12,5,90,380,0,4,4,91,402,2,15,2,92,419,0,13,3,93,404,0,12,8,94,432,6,22,10,95,345,2,15,7];\n",
    "results0=zip(results0[::5],results0[1::5],results0[2::5],results0[3::5],results0[4::5])\n",
    "results['p=0']=results0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# \"Machine learning\"\n",
    "# time taken: 20.9 minutes\n",
    "results0=[0,388,0,13,2,1,404,1,16,3,2,370,0,17,1,3,382,1,15,1,4,408,1,10,4,5,408,0,4,3,6,420,1,13,5,7,365,0,12,2,8,379,0,13,3,9,373,0,7,2,10,352,0,17,2,11,376,1,19,3,12,455,1,24,5,13,408,0,14,5,14,349,0,15,1,15,388,0,11,2,16,389,4,19,3,17,382,2,14,1,18,425,1,18,3,19,433,4,17,4,20,429,1,21,3,21,382,1,15,4,22,405,0,11,0,23,383,1,9,1,24,354,0,13,3,25,372,0,21,3,26,420,3,20,3,27,407,0,13,9,28,415,1,14,1,29,390,1,15,7,30,383,0,19,0,31,413,2,23,4,32,387,1,16,4,33,365,2,12,6,34,377,0,14,2,35,355,1,10,2,36,390,1,12,1,37,438,2,19,6,38,407,1,13,3,39,400,1,12,2,40,423,0,5,1,41,424,0,15,6,42,360,2,16,2,43,401,1,13,4,44,397,0,7,1,45,372,1,8,0,46,426,2,15,3,47,356,1,14,1,48,400,0,9,1,49,419,0,10,4,50,450,2,21,9,51,396,3,15,2,52,372,1,12,3,53,417,1,10,5,54,398,2,18,4,55,375,0,13,4,56,366,0,18,9,57,389,0,12,2,58,409,2,22,5,59,416,0,22,3,60,380,0,15,2,61,368,2,12,4,62,414,0,10,2,63,350,0,15,2,64,389,1,9,1,65,382,2,15,1,66,373,2,8,0,67,385,0,16,1,68,423,0,9,6,69,374,0,10,0,70,385,2,13,5,71,389,0,7,1,72,410,0,21,0,73,394,0,13,3,74,379,2,11,2,75,377,0,16,2,76,389,1,13,1,77,342,3,20,1,78,435,2,13,4,79,369,3,18,8,80,386,0,16,1,81,392,0,8,1,82,416,3,28,7,83,419,0,13,6,84,406,1,16,1,85,385,0,9,2,86,414,1,13,1,87,415,2,16,7,88,396,0,12,6,89,370,0,14,3,90,380,0,4,2,91,402,3,12,4,92,419,0,13,0,93,404,0,12,4,94,432,10,25,7,95,345,3,22,2]\n",
    "results0=zip(results0[::5],results0[1::5],results0[2::5],results0[3::5],results0[4::5])\n",
    "results['machine learning']=results0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p=0\n",
      "13.3229166667\n",
      "4.5625\n",
      "machine learning\n",
      "14.1875\n",
      "3.0\n"
     ]
    }
   ],
   "source": [
    "for llave in results.keys():\n",
    "    print(llave)\n",
    "    # correct average\n",
    "    print(np.mean(np.array(results[llave])[:,-2]))\n",
    "# incorrect average\n",
    "    print(np.mean(np.array(results[llave])[:,-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('svc > p=0', 42)\n",
      "('svc = p=0', 50)\n",
      "('svc < p=0', 4)\n"
     ]
    }
   ],
   "source": [
    "# corrects\n",
    "print(\"svc > p=0\",np.sum(np.array(results['machine learning'])[:,-2] > np.array(results['p=0'])[:,-2]))\n",
    "print(\"svc = p=0\",np.sum(np.array(results['machine learning'])[:,-2] == np.array(results['p=0'])[:,-2]))\n",
    "print(\"svc < p=0\",np.sum(np.array(results['machine learning'])[:,-2] < np.array(results['p=0'])[:,-2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('svc > p=0', 3)\n",
      "('svc = p=0', 21)\n",
      "('svc < p=0', 72)\n"
     ]
    }
   ],
   "source": [
    "# incorrects\n",
    "print(\"svc > p=0\",np.sum(np.array(results['machine learning'])[:,-1] > np.array(results['p=0'])[:,-1]))\n",
    "print(\"svc = p=0\",np.sum(np.array(results['machine learning'])[:,-1] == np.array(results['p=0'])[:,-1]))\n",
    "print(\"svc < p=0\",np.sum(np.array(results['machine learning'])[:,-1] < np.array(results['p=0'])[:,-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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SPdfbOk7lGmhsbgTmR8ReETEVOBRYvqudeYcAICJeS8/1MttvJ/WxJpekSkSc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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119b19890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bar_width=0.2\n",
    "bar_index=0\n",
    "plt.figure(figsize=(10,10))\n",
    "plt.subplot(2,1,1)\n",
    "for key in results.keys():\n",
    "    these_results = np.array(map(lambda x: list(x),results[key]))\n",
    "    xdata = these_results[:,3]\n",
    "    plt.bar(np.arange(len(these_results))+bar_index*bar_width,xdata,bar_width,label=key)\n",
    "    bar_index+=1\n",
    "plt.legend()\n",
    "plt.title('correct')\n",
    "plt.xlabel('sample index')\n",
    "plt.ylim(0,32)\n",
    "plt.ylabel('correct')\n",
    "plt.subplot(2,1,2)\n",
    "bar_index=0\n",
    "for key in results.keys():\n",
    "    these_results = np.array(map(lambda x: list(x),results[key]))\n",
    "    xdata = these_results[:,4]\n",
    "    plt.bar(np.arange(len(these_results))+bar_index*bar_width,xdata,bar_width,label=key)\n",
    "    bar_index+=1\n",
    "plt.legend()\n",
    "plt.title('incorrect')\n",
    "plt.xlabel('sample index')\n",
    "plt.ylabel('incorrect')\n",
    "#plt.savefig(fig_dir+'bar_charts.png',dpi=200)\n",
    "#plt.savefig(fig_dir+'bar_charts.jpg',dpi=200)\n",
    "#plt.savefig(fig_dir+'bar_charts.pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I will now test a simpler filter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def simple_filter(features,all_lattice,dA,dB):\n",
    "    # to make it compliant to the feature vector defined\n",
    "    # by Scheer, I assume that it has five components and only\n",
    "    # take the two corresponding to indices 2 and 3\n",
    "    # note that dA and dB must be converted to rad / s\n",
    "    simple_features = np.array([features[2],features[3]])\n",
    "    differences = np.abs(simple_features - all_lattice)\n",
    "    if np.any((differences[:,0] < dA) & (differences[:,1] < dB)):\n",
    "        return np.array([1.])\n",
    "    else:\n",
    "        return np.array([0.])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "full_lattice = np.genfromtxt('complete_lattice.csv',delimiter=',');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3141.592653589793"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "0.5*analysis.mag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simple_filter(np.array([100,100,10**8,100,100]), full_lattice, 0.1*analysis.mag, 0.5*analysis.mag)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing the individual results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# new diamonds \n",
    "diamonds=[learning.load_obj(\"diamonds/diamond_1\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "analysis.calc_M()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-2714391.6410000003"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "omega_larmor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plt.plot(10**6*diamonds[0]['tau'],analysis.calc_M([],diamonds[0]['B'],64,omega_larmor,diamonds[0]['tau']))\n",
    "plt.plot(10**6*diamonds[0]['tau'],diamonds[0]['data'],label='with added noise')\n",
    "plt.xlim(10,12.5)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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toktZsyrqijZ/UNRNh1A9RFppGDsRNEHCP4ZQYhm6la0TlIyFCz4ai/QSAiLe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NWGXTq/r6nt+aKrg2IWsNAQTjGzPizfQarHitiESa4pS8wmeMwmwTUJsE4BnTVz/loSRqWRTEEx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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e0f89d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,5))\n",
    "plt.plot(10**6*diamonds[0]['tau'],analysis.calc_M(diamonds[0]['A'],diamonds[0]['B'],64,omega_larmor,diamonds[0]['tau']))\n",
    "plt.plot(10**6*diamonds[0]['tau'],diamonds[0]['data'],label='with added noise')\n",
    "plt.xlim(10,12.5)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.1999999999999999e-05"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(diamonds[0]['tau'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# This to take data into Mathematica\n",
    "packet_tm=zip(diamonds[0]['tau'],diamonds[0]['data'])\n",
    "np.savetxt('packet_tm.csv',packet_tm,delimiter=\",\")\n",
    "packet_AB=zip(diamonds[0]['A'],diamonds[0]['B'])\n",
    "np.savetxt('packet_AB.csv',packet_AB,delimiter=\",\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['A',\n",
       " 'tau',\n",
       " 'B',\n",
       " 'successful_fits',\n",
       " 'windows',\n",
       " 'data',\n",
       " 'N_data',\n",
       " 'error_tol',\n",
       " 'N',\n",
       " 'N_vals',\n",
       " 'num_subsets',\n",
       " 'xs_list',\n",
       " 'costheta',\n",
       " 'scaled_errors',\n",
       " 'phis_list',\n",
       " 'r',\n",
       " 'dip_inds',\n",
       " 'sintheta',\n",
       " 'good_fits']"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diamonds[0].keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "diamond_ind:  0\n",
      "dips measured:  429\n",
      "num_removed:  0\n",
      "correct:  21 incorrect:  4\n"
     ]
    }
   ],
   "source": [
    "measured = []\n",
    "# He then iterates through all of the 29 diamonds.\n",
    "for diamond_ind in range(len(diamonds)):\n",
    "    print \"diamond_ind: \", diamond_ind\n",
    "    diamond = diamonds[diamond_ind]\n",
    "    tau = diamond[\"tau\"] # This is an array with all the free evolution times.\n",
    "    data = diamond[\"data\"] # These are the corresping M(tau) values for N = 64\n",
    "    N = diamond[\"N\"]\n",
    "    dip_inds = diamond[\"dip_inds\"] # indices for the dips in data\n",
    "    windows = diamond[\"windows\"] # these indices determine the window around each dip\n",
    "    min_dip_ind = 3220\n",
    "    measure_dii = filter(lambda dii: dip_inds[dii] >= min_dip_ind, range(len(dip_inds))) # only times after 15 micros are taken\n",
    "    print \"dips measured: \", len(measure_dii)\n",
    "    dips_measured.append(len(measure_dii))\n",
    "    spin_dict = {}\n",
    "    for dii in measure_dii: # this loop iterates over all dips\n",
    "        if diamond[\"good_fits\"][dii]: # If this happens to be a good fit then\n",
    "            dip_ind = dip_inds[dii] \n",
    "            res_tau = tau[dip_ind]\n",
    "            for phi, x in zip(diamond[\"phis_list\"][dii], diamond[\"xs_list\"][dii]):\n",
    "                for omega_tilde, cosphi in analysis.calc_omega_tilde(phi, x, res_tau, omega_larmor):\n",
    "                    A, B = analysis.calc_A_B(cosphi, res_tau, omega_larmor, omega_tilde)\n",
    "                    if analysis.valid_A_B(A, B):\n",
    "                        if (dip_ind, phi, x) in spin_dict:\n",
    "                            spin_dict[(dip_ind, phi, x)] += [(A, B, cosphi)]\n",
    "                        else:\n",
    "                            spin_dict[(dip_ind, phi, x)] = [(A, B, cosphi)]\n",
    "    def guess_classifier(features): # this defines a pipeline with scaler and classifier.\n",
    "        return guess_clf.predict(guess_scaler.transform([features]))\n",
    "    guess_As, guess_Bs, dataerrs, _, _, _, _ = analysis.choose_spin_guesses(spin_dict, N, omega_larmor, tau, data,\n",
    "                                                                guess_classifier, x_min = 1, error_fun = analysis.squared_error)\n",
    "    cluster_As, cluster_Bs, cluster_dataerrs = analysis.cluster_spin_guesses(guess_As, guess_Bs, dataerrs, eps = .075, min_samples = 1)\n",
    "    As, Bs, num_remove = cluster_As, cluster_Bs, 1\n",
    "    while num_remove <= 2:\n",
    "        As, Bs, num_remove = analysis.remove_spins(As, Bs, N, omega_larmor, tau, data, num_remove = num_remove, error_fun = analysis.squared_error)\n",
    "    As_list.append(As)\n",
    "    Bs_list.append(Bs)\n",
    "    guess_As_list.append(guess_As)\n",
    "    guess_Bs_list.append(guess_Bs)\n",
    "    \n",
    "    print \"num_removed: \", len(cluster_As) - len(As)\n",
    "    num_correct = 0\n",
    "    spins = set(zip(diamond[\"A\"], np.abs(diamond[\"B\"])))\n",
    "    for A, B in zip(As, np.abs(Bs)):\n",
    "        for spin in spins:\n",
    "            if learning.is_fit(A, B, spin, A_acc = .5, B_acc = 2):\n",
    "                num_correct = num_correct + 1\n",
    "                spins.remove(spin)\n",
    "                break\n",
    "    num_incorrect = len(As) - num_correct\n",
    "    num_correct_list.append(num_correct)\n",
    "    num_incorrect_list.append(num_incorrect)\n",
    "    print \"correct: \", num_correct, \"incorrect: \", len(As) - num_correct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "two_As={}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "two_As['ML']=[As,Bs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "diamond_ind:  0\n",
      "dips measured:  429\n",
      "num_removed:  0\n",
      "correct:  21 incorrect:  5\n"
     ]
    }
   ],
   "source": [
    "measured = []\n",
    "# He then iterates through all of the 29 diamonds.\n",
    "for diamond_ind in range(len(diamonds)):\n",
    "    print \"diamond_ind: \", diamond_ind\n",
    "    diamond = diamonds[diamond_ind]\n",
    "    tau = diamond[\"tau\"] # This is an array with all the free evolution times.\n",
    "    data = diamond[\"data\"] # These are the corresping M(tau) values for N = 64\n",
    "    N = diamond[\"N\"]\n",
    "    dip_inds = diamond[\"dip_inds\"] # indices for the dips in data\n",
    "    windows = diamond[\"windows\"] # these indices determine the window around each dip\n",
    "    min_dip_ind = 3220\n",
    "    measure_dii = filter(lambda dii: dip_inds[dii] >= min_dip_ind, range(len(dip_inds))) # only times after 15 micros are taken\n",
    "    print \"dips measured: \", len(measure_dii)\n",
    "    dips_measured.append(len(measure_dii))\n",
    "    spin_dict = {}\n",
    "    for dii in measure_dii: # this loop iterates over all dips\n",
    "        if diamond[\"good_fits\"][dii]: # If this happens to be a good fit then\n",
    "            dip_ind = dip_inds[dii] \n",
    "            res_tau = tau[dip_ind]\n",
    "            for phi, x in zip(diamond[\"phis_list\"][dii], diamond[\"xs_list\"][dii]):\n",
    "                for omega_tilde, cosphi in analysis.calc_omega_tilde(phi, x, res_tau, omega_larmor):\n",
    "                    A, B = analysis.calc_A_B(cosphi, res_tau, omega_larmor, omega_tilde)\n",
    "                    if analysis.valid_A_B(A, B):\n",
    "                        if (dip_ind, phi, x) in spin_dict:\n",
    "                            spin_dict[(dip_ind, phi, x)] += [(A, B, cosphi)]\n",
    "                        else:\n",
    "                            spin_dict[(dip_ind, phi, x)] = [(A, B, cosphi)]\n",
    "    def guess_classifier(features): # this defines a pipeline with scaler and classifier.\n",
    "        return np.array([1.0])\n",
    "        #return guess_clf.predict(guess_scaler.transform([features]))\n",
    "    guess_As, guess_Bs, dataerrs, _, _, _, _ = analysis.choose_spin_guesses(spin_dict, N, omega_larmor, tau, data,\n",
    "                                                                guess_classifier, x_min = 1, error_fun = analysis.squared_error)\n",
    "    cluster_As, cluster_Bs, cluster_dataerrs = analysis.cluster_spin_guesses(guess_As, guess_Bs, dataerrs, eps = .075, min_samples = 1)\n",
    "    As, Bs, num_remove = cluster_As, cluster_Bs, 1\n",
    "    while num_remove <= 2:\n",
    "        As, Bs, num_remove = analysis.remove_spins(As, Bs, N, omega_larmor, tau, data, num_remove = num_remove, error_fun = analysis.squared_error)\n",
    "    As_list.append(As)\n",
    "    Bs_list.append(Bs)\n",
    "    guess_As_list.append(guess_As)\n",
    "    guess_Bs_list.append(guess_Bs)\n",
    "    \n",
    "    print \"num_removed: \", len(cluster_As) - len(As)\n",
    "    num_correct = 0\n",
    "    spins = set(zip(diamond[\"A\"], np.abs(diamond[\"B\"])))\n",
    "    for A, B in zip(As, np.abs(Bs)):\n",
    "        for spin in spins:\n",
    "            if learning.is_fit(A, B, spin, A_acc = .5, B_acc = 2):\n",
    "                num_correct = num_correct + 1\n",
    "                spins.remove(spin)\n",
    "                break\n",
    "    num_incorrect = len(As) - num_correct\n",
    "    num_correct_list.append(num_correct)\n",
    "    num_incorrect_list.append(num_incorrect)\n",
    "    print \"correct: \", num_correct, \"incorrect: \", len(As) - num_correct"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "two_As['All']=[As,Bs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ -2.38987348e+05,   3.41023656e+04,  -1.30465267e+01,\n",
       "         3.49043371e+04,   9.54297173e+04,   1.83865650e+04,\n",
       "        -1.71046793e+04,   6.98492357e+04,  -3.49755316e+04,\n",
       "         1.35250400e+03,   4.07317227e+05,   8.27638371e+04,\n",
       "         3.39962021e+04,   8.43656436e+04,   6.43394305e+04,\n",
       "         3.60196521e+04,  -5.87689033e+04,   1.56581408e+04,\n",
       "         4.83515283e+04,   1.26738726e+04,   3.12131786e+05,\n",
       "        -6.78407062e+05,   3.47860872e+04,   1.52312121e+05,\n",
       "        -1.61135837e+04,   1.91340149e+04])"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "two_As['All'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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QBgBAQjUKYFt2H9AZm8e0ZfeBBc9BEPOHEAYAQEKNj48vOgK2c/8hlZ3Tzv2HFj1PLYiN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\nAVMIZWUAAAAESURBVEqXplB14LuwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10c93bb10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "#plt.plot(xtrain[:,2][ytrain==0]/analysis.mag,xtrain[:,3][ytrain==0]/analysis.mag,'ro',label='(train) false spin',ms=4,alpha=0.1)\n",
    "#plt.plot(xtrain[:,2][ytrain==1]/analysis.mag,xtrain[:,3][ytrain==1]/analysis.mag,'bo',label='(train) true spin',ms=5,alpha=0.5)\n",
    "plt.plot(diamonds[0]['A']/analysis.mag,np.abs(diamonds[0]['B'])/analysis.mag,'o',label='true',ms=2)\n",
    "plt.plot(two_As['ML'][0]/analysis.mag,two_As['ML'][1]/analysis.mag,'kx',ms=20,label='ML fit')\n",
    "plt.plot(two_As['All'][0]/analysis.mag,two_As['All'][1]/analysis.mag,'ro',ms=5,label='fit -ML')\n",
    "#plt.plot(lots_of_A/analysis.mag,lots_of_B/analysis.mag,'o',ms=5,label='all_C13',alpha=0.5)\n",
    "#plt.plot(full_lattice[:,0],np.abs(full_lattice[:,1]),'o',ms=5,label='all_C13',alpha=0.1)\n",
    "plt.legend()\n",
    "plt.xlim(-15,32)\n",
    "plt.ylim(0,35)\n",
    "plt.xlabel('A/kHz')\n",
    "plt.ylabel('B/kHz')\n",
    "plt.savefig(fig_dir+'all_spins_comparison.jpg',dpi=300)\n",
    "plt.savefig(fig_dir+'all_spins_comparison.png',dpi=300)\n",
    "plt.savefig(fig_dir+'all_spins_comparison.pdf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pickle.dump(two_As,open('two_As.pickle','wb'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:python2]",
   "language": "python",
   "name": "conda-env-python2-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}