CdCalibration.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1815ae65",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from scipy.optimize import curve_fit\n",
    "from scipy.special import erf\n",
    "import csv\n",
    "import sys\n",
    "sys.path.append('/storage/home/hcoda1/4/ashelby8/Manitoba/pyNab/src/')\n",
    "import nabPy as Nab\n",
    "sys.path.append('/storage/home/hcoda1/4/ashelby8/calibration/calibration/')\n",
    "from FitClass import SnCalibration\n",
    "from config import conf\n",
    "import FitFuncs\n",
    "import pandas as pd\n",
    "import pylab as py\n",
    "np.set_printoptions(threshold=sys.maxsize)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "504b3aba",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option(\"display.max_colwidth\", 15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "c8b542b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('/storage/home/hcoda1/4/ashelby8/output1304.csv') as f:\n",
    "    csv.DictReader(f)\n",
    "    data = pd.read_csv(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "8f959f41",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>run</th>\n",
       "      <th>pixel</th>\n",
       "      <th>Bias Voltage</th>\n",
       "      <th>Proton</th>\n",
       "      <th>Proton Energy</th>\n",
       "      <th>Cd109</th>\n",
       "      <th>Sn113</th>\n",
       "      <th>Date Time [UTC]</th>\n",
       "      <th>trap rise</th>\n",
       "      <th>trap length</th>\n",
       "      <th>trap decay</th>\n",
       "      <th>ecap</th>\n",
       "      <th>chi2_e</th>\n",
       "      <th>xray</th>\n",
       "      <th>chi2_x</th>\n",
       "      <th>CE</th>\n",
       "      <th>Xray</th>\n",
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       "      <td>[ 5.4012051...</td>\n",
       "      <td>1128.700105</td>\n",
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       "      <td>3</td>\n",
       "      <td>[[16, 16, 1...</td>\n",
       "      <td>[555 508 51...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1304</td>\n",
       "      <td>87</td>\n",
       "      <td>-240</td>\n",
       "      <td>False</td>\n",
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       "      <td>3346.216808</td>\n",
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       "      <td>1304</td>\n",
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       "      <td>False</td>\n",
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       "      <td>True</td>\n",
       "      <td>False</td>\n",
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       "      <td>False</td>\n",
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       "      <td>1304</td>\n",
       "      <td>107</td>\n",
       "      <td>-240</td>\n",
       "      <td>False</td>\n",
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       "      <td>1304</td>\n",
       "      <td>113</td>\n",
       "      <td>-240</td>\n",
       "      <td>False</td>\n",
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       "      <td>True</td>\n",
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       "      <td>2021-11-20 ...</td>\n",
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       "      <td>1304</td>\n",
       "      <td>115</td>\n",
       "      <td>-240</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>2021-11-20 ...</td>\n",
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       "      <td>1304</td>\n",
       "      <td>116</td>\n",
       "      <td>-240</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>2021-11-20 ...</td>\n",
       "      <td>1250</td>\n",
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       "      <td>[ 2.5720479...</td>\n",
       "      <td>955.563247</td>\n",
       "      <td>[0, 0]</td>\n",
       "      <td>0</td>\n",
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       "      <td>1304</td>\n",
       "      <td>121</td>\n",
       "      <td>-240</td>\n",
       "      <td>False</td>\n",
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       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>2021-11-20 ...</td>\n",
       "      <td>1250</td>\n",
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       "      <td>[[17.141436...</td>\n",
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       "      <td>[ 1.0300173...</td>\n",
       "      <td>342.260411</td>\n",
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       "      <td>575.138091</td>\n",
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       "      <td>3</td>\n",
       "      <td>[[6, 6, 9, ...</td>\n",
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       "      <th>17</th>\n",
       "      <td>1304</td>\n",
       "      <td>123</td>\n",
       "      <td>-240</td>\n",
       "      <td>False</td>\n",
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       "      <td>762.900169</td>\n",
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       "      <td>[[4, 8, 10,...</td>\n",
       "      <td>[715 707 46...</td>\n",
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       "      <th>18</th>\n",
       "      <td>1304</td>\n",
       "      <td>124</td>\n",
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       "      <td>False</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     run  pixel  Bias Voltage  Proton  Proton Energy  Cd109  Sn113  \\\n",
       "0   1304     76          -240   False              0   True  False   \n",
       "1   1304     77          -240   False              0   True  False   \n",
       "2   1304     78          -240   False              0   True  False   \n",
       "3   1304     87          -240   False              0   True  False   \n",
       "4   1304     88          -240   False              0   True  False   \n",
       "5   1304     96          -240   False              0   True  False   \n",
       "6   1304     97          -240   False              0   True  False   \n",
       "7   1304     98          -240   False              0   True  False   \n",
       "8   1304    101          -240   False              0   True  False   \n",
       "9   1304    103          -240   False              0   True  False   \n",
       "10  1304    105          -240   False              0   True  False   \n",
       "11  1304    107          -240   False              0   True  False   \n",
       "12  1304    113          -240   False              0   True  False   \n",
       "13  1304    115          -240   False              0   True  False   \n",
       "14  1304    116          -240   False              0   True  False   \n",
       "15  1304    121          -240   False              0   True  False   \n",
       "16  1304    122          -240   False              0   True  False   \n",
       "17  1304    123          -240   False              0   True  False   \n",
       "18  1304    124          -240   False              0   True  False   \n",
       "\n",
       "   Date Time [UTC]  trap rise  trap length  trap decay            ecap  \\\n",
       "0   2021-11-20 ...       1250           50        1250  [[67.309267...   \n",
       "1   2021-11-20 ...       1250           50        1250  [[59.572546...   \n",
       "2   2021-11-20 ...       1250           50        1250  [[38.765647...   \n",
       "3   2021-11-20 ...       1250           50        1250  [[32.717400...   \n",
       "4   2021-11-20 ...       1250           50        1250  [[49.189179...   \n",
       "5   2021-11-20 ...       1250           50        1250  [[20.865379...   \n",
       "6   2021-11-20 ...       1250           50        1250  [[35.864973...   \n",
       "7   2021-11-20 ...       1250           50        1250  [[37.574231...   \n",
       "8   2021-11-20 ...       1250           50        1250  [[10.783606...   \n",
       "9   2021-11-20 ...       1250           50        1250  [[24.601137...   \n",
       "10  2021-11-20 ...       1250           50        1250  [[20.774367...   \n",
       "11  2021-11-20 ...       1250           50        1250  [[20.668248...   \n",
       "12  2021-11-20 ...       1250           50        1250  [[9.5158465...   \n",
       "13  2021-11-20 ...       1250           50        1250  [[15.715351...   \n",
       "14  2021-11-20 ...       1250           50        1250  [[-0.758594...   \n",
       "15  2021-11-20 ...       1250           50        1250  [[17.141436...   \n",
       "16  2021-11-20 ...       1250           50        1250  [[10.806655...   \n",
       "17  2021-11-20 ...       1250           50        1250  [[11.248456...   \n",
       "18  2021-11-20 ...       1250           50        1250  [[20.131482...   \n",
       "\n",
       "            chi2_e            xray       chi2_x      CE  Xray         CE hist  \\\n",
       "0   [np.float64...  [ 3.0778278...  3104.077276  [1, 2]     3  [[24, 16, 1...   \n",
       "1   [np.float64...  [ 4.6938587...   885.596444  [1, 2]     3  [[17, 13, 1...   \n",
       "2   [np.float64...  [ 5.4012051...  1128.700105  [1, 2]     3  [[16, 16, 1...   \n",
       "3   [np.float64...  [ 4.2950038...  5655.672552  [1, 2]     3  [[13, 15, 1...   \n",
       "4   [np.float64...  [ 4.8919238...  3901.020369  [1, 2]     3  [[16, 12, 1...   \n",
       "5   [np.float64...  [ 2.6037786...   431.124599  [1, 2]     3  [[12, 9, 9,...   \n",
       "6   [np.float64...  [ 5.3641047...  2352.013772  [1, 2]     3  [[16, 19, 1...   \n",
       "7   [np.float64...  [ 3.6153483...  3346.216808  [1, 2]     3  [[7, 13, 15...   \n",
       "8   [np.float64...  [ 1.1959726...   107.330347  [1, 2]     3  [[7, 11, 12...   \n",
       "9   [np.float64...               0     0.000000  [1, 2]     3  [[3, 7, 8, ...   \n",
       "10  [np.float64...  [ 2.6155531...   548.680083  [1, 2]     3  [[12, 11, 1...   \n",
       "11  [np.float64...  [ 3.7000540...   792.617487  [1, 2]     3  [[11, 13, 7...   \n",
       "12  [np.float64...  [ 1.3104697...   143.608922  [1, 2]     3  [[4, 8, 7, ...   \n",
       "13  [np.float64...  [ 2.8274575...   532.078751  [1, 2]     3  [[4, 8, 12,...   \n",
       "14  [np.float64...  [ 2.5720479...   955.563247  [0, 0]     0  [[1, 0, 0, ...   \n",
       "15  [np.float64...  [ 1.0300173...   342.260411  [1, 2]     3  [[3, 6, 8, ...   \n",
       "16  [np.float64...  [ 2.4868012...   575.138091  [1, 2]     3  [[6, 6, 9, ...   \n",
       "17  [np.float64...  [ 1.4528777...   762.900169  [1, 2]     3  [[4, 8, 10,...   \n",
       "18  [np.float64...  [ 6.8087888...   335.441477  [1, 2]     3  [[14, 7, 7,...   \n",
       "\n",
       "         Xray hist  \n",
       "0   [1716 1633 ...  \n",
       "1   [1773 1441 ...  \n",
       "2   [555 508 51...  \n",
       "3   [2155 2138 ...  \n",
       "4   [2429 2296 ...  \n",
       "5   [1090  863 ...  \n",
       "6   [2167 1871 ...  \n",
       "7   [1858 1727 ...  \n",
       "8   [361 244 15...  \n",
       "9                0  \n",
       "10  [1134  937 ...  \n",
       "11  [1565 1322 ...  \n",
       "12  [625 484 36...  \n",
       "13  [1267 1083 ...  \n",
       "14  [1124 1031 ...  \n",
       "15  [602 581 48...  \n",
       "16  [973 842 51...  \n",
       "17  [715 707 46...  \n",
       "18  [294 239 20...  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "579ed29a",
   "metadata": {},
   "outputs": [
    {
     "ename": "IndexError",
     "evalue": "list index out of range",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[74], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mdata\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mCE hist\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreplace\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m[\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreplace\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m]\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreplace\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m(\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreplace\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m)\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msplit\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43marray\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m]\u001b[49m\n",
      "\u001b[0;31mIndexError\u001b[0m: list index out of range"
     ]
    }
   ],
   "source": [
    "data['CE hist'][0].replace('[','').replace(']','').replace('(','').replace(')','').split('array')[1]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "b1b068e5",
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "could not convert string to float: '[np.float64(39.158641189429545), np.float64(29.306732018928827)]'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[142], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mSeries\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mchi2_e\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfloat64\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/Manitoba/lib/python3.9/site-packages/pandas/core/series.py:584\u001b[0m, in \u001b[0;36mSeries.__init__\u001b[0;34m(self, data, index, dtype, name, copy, fastpath)\u001b[0m\n\u001b[1;32m    582\u001b[0m         data \u001b[38;5;241m=\u001b[39m data\u001b[38;5;241m.\u001b[39mcopy()\n\u001b[1;32m    583\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 584\u001b[0m     data \u001b[38;5;241m=\u001b[39m \u001b[43msanitize_array\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindex\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    586\u001b[0m     manager \u001b[38;5;241m=\u001b[39m _get_option(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmode.data_manager\u001b[39m\u001b[38;5;124m\"\u001b[39m, silent\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m    587\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m manager \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mblock\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n",
      "File \u001b[0;32m~/Manitoba/lib/python3.9/site-packages/pandas/core/construction.py:651\u001b[0m, in \u001b[0;36msanitize_array\u001b[0;34m(data, index, dtype, copy, allow_2d)\u001b[0m\n\u001b[1;32m    648\u001b[0m     subarr \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray([], dtype\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39mfloat64)\n\u001b[1;32m    650\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m dtype \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m--> 651\u001b[0m     subarr \u001b[38;5;241m=\u001b[39m \u001b[43m_try_cast\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcopy\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    653\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    654\u001b[0m     subarr \u001b[38;5;241m=\u001b[39m maybe_convert_platform(data)\n",
      "File \u001b[0;32m~/Manitoba/lib/python3.9/site-packages/pandas/core/construction.py:820\u001b[0m, in \u001b[0;36m_try_cast\u001b[0;34m(arr, dtype, copy)\u001b[0m\n\u001b[1;32m    818\u001b[0m     subarr \u001b[38;5;241m=\u001b[39m maybe_cast_to_integer_array(arr, dtype)\n\u001b[1;32m    819\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m copy:\n\u001b[0;32m--> 820\u001b[0m     subarr \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43masarray\u001b[49m\u001b[43m(\u001b[49m\u001b[43marr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    821\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    822\u001b[0m     subarr \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(arr, dtype\u001b[38;5;241m=\u001b[39mdtype, copy\u001b[38;5;241m=\u001b[39mcopy)\n",
      "\u001b[0;31mValueError\u001b[0m: could not convert string to float: '[np.float64(39.158641189429545), np.float64(29.306732018928827)]'"
     ]
    }
   ],
   "source": [
    "pd.Series(data['chi2_e'][0],dtype=np.float64)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "696679da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'[1, 2]'"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['CE'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e039d667",
   "metadata": {},
   "outputs": [],
   "source": [
    "nrows,ncols=2,2\n",
    "py.figure(figsize=(4*ncols,3*nrows))\n",
    "\n",
    "\n",
    "x = np.arange(500,800)\n",
    "\n",
    "#initializes the electron capture peak fitting\n",
    "conf['xray'] = 'OFF'\n",
    "\n",
    "for i in range(len(data)):\n",
    "    if data['CE'][i]==3:\n",
    "        \n",
    "        #need to initialize the class to get the correct fit function based on the same recorded initilizing flag in column \"CE\"\n",
    "        conf['capture'] = 'three'\n",
    "        Sn = SnCalibration()\n",
    "        \n",
    "        #plot all the fits with the same initilization on the same graph\n",
    "        ax=py.subplot(nrows,ncols,1)\n",
    "        \n",
    "        #need to convert the stored parameter string into the corresponding numerical values and plot Sn.get_fit (the fitting function)\n",
    "        ax.plot(x,Sn.get_fit(x,*np.float64(data['ecap'][i].replace('[','').replace(']','').split())),label = '%d'%i)\n",
    "        ax.legend()\n",
    "        \n",
    "    if data['CE'][i]==2:\n",
    "        \n",
    "        conf['capture'] = 'two'\n",
    "        Sn = SnCalibration()\n",
    "        \n",
    "        ax=py.subplot(nrows,ncols,2)\n",
    "        \n",
    "        ax.plot(x,Sn.get_fit(x,*np.float64(data['ecap'][i].replace('[','').replace(']','').split())),label = '%d'%i)\n",
    "        ax.legend()\n",
    "        \n",
    "    if data['CE'][i]==1:\n",
    "        \n",
    "        conf['capture'] = 'one'\n",
    "        Sn = SnCalibration()\n",
    "        \n",
    "        ax=py.subplot(nrows,ncols,3)\n",
    "        ax.plot(x,Sn.get_fit(x,*np.float64(data['ecap'][i].replace('[','').replace(']','').split())),label = '%d'%i)\n",
    "        \n",
    "        ax.legend()\n",
    "        \n",
    "    if data['CE'][i]==0:\n",
    "        print('not enough counts for fit: pixel %d'%i)\n",
    "        conf['capture'] = 'zero'\n",
    "#         Sn = SnCalibration()\n",
    "        \n",
    "#         ax=py.subplot(nrows,ncols,4)\n",
    "#         ax.plot(x,Sn.get_fit(x,*np.float64(data['ecap'][i].replace('[','').replace(']','').split())),label = '%d'%i)\n",
    "        \n",
    "#         ax.legend()\n",
    "\n",
    "py.tight_layout()"
   ]
  }
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