MoS2_Hiten_Dec_2017.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "pd.set_option('display.max_rows',8)\n",
    "%matplotlib inline\n",
    "path='/dls/science/users/spc93/data/MoS2/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f87f594aed0>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f88274ee510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f882053af10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "file='MoS2_I16_MoS2_Point detector.txt'\n",
    "d=pd.read_csv((path+file),header=250,skip_blank_lines=False)\n",
    "d.plot(x='     Angle',y=' Det1Disc1', logy=True)\n",
    "d.plot(x='     Angle',y=' Det1Disc1', xlim=[59.75,60.5], ylim=[0,200000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Angle</th>\n",
       "      <th>Det1Disc1</th>\n",
       "      <th>Unnamed: 2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00</td>\n",
       "      <td>8225090.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.01</td>\n",
       "      <td>8259520.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02</td>\n",
       "      <td>7869910.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03</td>\n",
       "      <td>6882650.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10997</th>\n",
       "      <td>109.97</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10998</th>\n",
       "      <td>109.98</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10999</th>\n",
       "      <td>109.99</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11000</th>\n",
       "      <td>110.00</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11001 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Angle   Det1Disc1  Unnamed: 2\n",
       "0            0.00   8225090.0         NaN\n",
       "1            0.01   8259520.0         NaN\n",
       "2            0.02   7869910.0         NaN\n",
       "3            0.03   6882650.0         NaN\n",
       "...           ...         ...         ...\n",
       "10997      109.97         3.0         NaN\n",
       "10998      109.98         5.0         NaN\n",
       "10999      109.99         5.0         NaN\n",
       "11000      110.00         3.0         NaN\n",
       "\n",
       "[11001 rows x 3 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f87f58f5dd0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f882053a8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "file='MoS2_I16_MoS2_Vantec.txt'\n",
    "d=pd.read_csv((path+file),header=221,skip_blank_lines=False)\n",
    "d.plot(x='     Angle',y='       PSD', logy=True)\n",
    "#d.plot(x='     Angle',y=' Det1Disc1', xlim=[59.75,60.5], ylim=[0,200000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "c=12.302; lam=1.5406; refs=np.arange(1,6); angles=2*np.arcsin(lam/2./c*refs)*180/np.pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "d['l']=pd.Series(2.*c/lam*np.sin(d['     Angle']/2.*np.pi/180))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f87f5555d90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f87f594a610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d.plot(x='l',y='       PSD', logy=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0         0.696619\n",
       "1         0.697379\n",
       "2         0.698140\n",
       "3         0.698900\n",
       "           ...    \n",
       "19223    13.080988\n",
       "19224    13.081387\n",
       "19225    13.081867\n",
       "19226    13.082267\n",
       "Name: l, Length: 19227, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['l']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Angle</th>\n",
       "      <th>PSD</th>\n",
       "      <th>Unnamed: 2</th>\n",
       "      <th>l</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.00000</td>\n",
       "      <td>241.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.696619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.00546</td>\n",
       "      <td>226.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.697379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5.01092</td>\n",
       "      <td>234.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.698140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.01638</td>\n",
       "      <td>191.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.698900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19223</th>\n",
       "      <td>109.98500</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.080988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19224</th>\n",
       "      <td>109.99000</td>\n",
       "      <td>9.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.081387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19225</th>\n",
       "      <td>109.99600</td>\n",
       "      <td>13.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.081867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19226</th>\n",
       "      <td>110.00100</td>\n",
       "      <td>10.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.082267</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>19227 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Angle         PSD  Unnamed: 2          l\n",
       "0         5.00000       241.0         NaN   0.696619\n",
       "1         5.00546       226.0         NaN   0.697379\n",
       "2         5.01092       234.0         NaN   0.698140\n",
       "3         5.01638       191.0         NaN   0.698900\n",
       "...           ...         ...         ...        ...\n",
       "19223   109.98500         6.0         NaN  13.080988\n",
       "19224   109.99000         9.0         NaN  13.081387\n",
       "19225   109.99600        13.0         NaN  13.081867\n",
       "19226   110.00100        10.0         NaN  13.082267\n",
       "\n",
       "[19227 rows x 4 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "#    (h,k,l)           Intensity           Norm. Int.        Amplitude                               TwoTheta (deg)                d_spacing (A)       \n",
      "1    (0, 0, 2)         5828.92727755       70.9761027269     (-76.3474117279+0j)                     14.3902010581                 6.147               \n",
      "2    (0, 0, 4)         477.57027121        5.8151483137      (21.8533812306+0j)                      29.0138233105                 3.0735              \n",
      "3    (1, 0, 0)         3279.72137362       39.9356228076     (-57.2688516876+0j)                     32.6793242057                 2.73664027596       \n",
      "4    (1, 0, 1)         977.958191777       11.9081363992     (-31.2723230953+0j)                     33.5024626442                 2.67125914202       \n",
      "5    (1, 0, 2)         1028.08643883       12.5185244591     (32.0637870319+0j)                      35.8716814179                 2.50007256324       \n",
      "6    (1, 0, 3)         6987.52281695       85.0837750494     (83.5914039657+0j)                      39.5460182113                 2.27583226991       \n",
      "7    (0, 0, 6)         4623.65777116       56.3001034862     (-67.9974835649+0j)                     44.1407547916                 2.049               \n",
      "8    (1, 0, 4)         120.355106529       1.46550745926     (-10.9706474982+0j)                     44.2576808379                 2.04385748166       \n",
      "9    (1, 0, 5)         5097.07119044       62.0646357713     (-71.3937755721+0j)                     49.7881103778                 1.82899885723       \n",
      "10   (1, 0, 6)         954.721947025       11.6251995884     (30.8985751617+0j)                      55.9900553638                 1.64020066734       \n",
      "11   (1, 1, 0)         8212.52091          100.0             (90.6229601702+0j)                      58.3238776117                 1.58                \n",
      "12   (0, 0, 8)         7868.88452445       95.815701545      (88.7067332531+0j)                      60.1315133081                 1.53675             \n",
      "13   (1, 1, 2)         2792.04504183       33.9974177531     (-52.8398054674+0j)                     60.4131223487                 1.53025828323       \n",
      "14   (1, 0, 7)         496.630280166       6.04723306776     (22.2852031664+0j)                      62.7824560536                 1.47808217463       \n",
      "15   (1, 1, 4)         370.285077498       4.50878702843     (19.2427928716+0j)                      66.4455905476                 1.40519690242       \n",
      "16   (2, 0, 0)         1780.97258065       21.6860644882     (-42.2015708316+0j)                     68.4802012006                 1.36832013798       \n",
      "17   (2, 0, 1)         625.893301762       7.62120801421     (25.0178596559+0j)                      68.9624855998                 1.35992293684       \n",
      "18   (1, 0, 8)         1716.5658576        20.9018141495     (-41.431459757+0j)                      70.1403948808                 1.33993944755       \n",
      "19   (2, 0, 2)         608.128399359       7.40489316281     (24.6602595152+0j)                      70.4001931836                 1.33562957101       \n",
      "20   (2, 0, 3)         4157.08860356       50.6189104309     (-64.4754883933+0j)                     72.7686622712                 1.29788184883       \n",
      "21   (1, 1, 6)         2910.09228019       35.4348233883     (-53.9452711569+0j)                     75.9512049069                 1.2512100071        \n",
      "22   (2, 0, 4)         80.3853601938       0.978814679131    (-8.96578831971+0j)                     76.0352184857                 1.25003628162       \n",
      "23   (0, 0, 10)        1681.69312229       20.4771852726     (-41.0084518397+0j)                     77.5468069338                 1.2294              \n",
      "24   (1, 0, 9)         773.550108951       9.41915542655     (-27.8127688113+0j)                     78.0899583594                 1.22220173731       \n",
      "25   (2, 0, 5)         3355.90329864       40.863254236      (57.9301588004+0j)                      80.1695479909                 1.19564773259       \n",
      "26   (2, 0, 6)         657.369134596       8.00447440925     (25.6392108809+0j)                      85.1553816276                 1.13791613495       \n",
      "27   (1, 0, 10)        379.912802975       4.62601930806     (19.4913520048+0j)                      86.7124180027                 1.12143628688       \n",
      "28   (1, 1, 8)         5610.33666557       68.314427775      (74.9021806463+0j)                      88.6747509163                 1.10161928062       \n",
      "29   (2, 0, 7)         345.389333708       4.20564327925     (-18.584653177+0j)                      91.0034562112                 1.07939514053       \n",
      "30   (1, 0, 11)        3609.56023567       43.9519153159     (60.0796158083+0j)                      96.1635876711                 1.03467626869       \n",
      "31   (2, 1, 0)         1331.76572152       16.2162840876     (-36.4933654453+0j)                     96.2035094963                 1.03435279972       \n",
      "32   (2, 1, 1)         454.995738313       5.54026885654     (-21.330629112+0j)                      96.655759301                  1.03071120635       \n",
      "33   (0, 0, 12)        288.518881183       3.51315855807     (16.9858435523+0j)                      97.4392880708                 1.0245              \n",
      "34   (2, 0, 8)         1293.6221904        15.7518282702     (-35.9669597047+0j)                     97.7682434765                 1.02192874083       \n",
      "35   (2, 1, 2)         454.135542326       5.52979465504     (21.3104561736+0j)                      98.0151286185                 1.02001295105       \n",
      "36   (2, 1, 3)         3165.2005118        38.541156199      (56.260114751+0j)                       100.291279952                 1.0028996881        \n",
      "37   (2, 1, 4)         59.7921096781       0.728060364574    (-7.73253578576+0j)                     103.506609594                 0.980326351756      \n",
      "38   (1, 1, 10)        1294.44331126       15.7618266723     (-35.9783728268+0j)                     105.025030116                 0.970277488571      \n",
      "39   (2, 0, 9)         594.050569555       7.23347405827     (24.3731526388+0j)                      105.575461123                 0.966727111693      \n",
      "40   (1, 0, 12)        67.1782464802       0.817997874421    (-8.19623367653+0j)                     106.724489157                 0.959469668394      \n",
      "41   (2, 1, 5)         2625.62024227       31.9709413351     (-51.240806417+0j)                      107.707018552                 0.953425250553      \n",
      "42   (2, 1, 6)         521.90467915        6.35498752294     (22.8452331822+0j)                      112.981204367                 0.923370406418      \n",
      "43   (2, 0, 10)        303.027059095       3.68981780888     (17.4076724204+0j)                      114.679079072                 0.914499428613      \n",
      "44   (3, 0, 0)         4619.51699453       56.249683199      (67.9670287311+0j)                      115.128441461                 0.91221342532       \n",
      "45   (3, 0, 1)         3.03520165338e-30   3.6958221314e-32  (1.74218301374e-15+0j)                  115.625843014                 0.909712595273      \n",
      "46   (3, 0, 2)         1583.72007565       19.2842136172     (-39.7959806469+0j)                     117.130788922                 0.902331736441      \n",
      "47   (1, 0, 13)        2068.67767028       25.1893138897     (-45.4827183695+0j)                     118.937769732                 0.893828107254      \n",
      "48   (2, 1, 7)         280.982907484       3.42139655488     (16.7625447795+0j)                      119.498164895                 0.891268155738      \n",
      "49   (3, 0, 3)         5.23406366447e-32   6.37327286205e-34 (-2.2878076109e-16+0j)                  119.685650975                 0.890419714006      \n",
      "50   (0, 0, 14)        2442.63004825       29.7427559092     (-49.4229708562+0j)                     122.502862001                 0.878142857143      \n",
      "51   (3, 0, 4)         214.733223623       2.61470535023     (14.653778476+0j)                       123.377041886                 0.874508540535      \n",
      "52   (2, 0, 11)        2936.72309332       35.7590942599     (-54.1915407911+0j)                     125.608987004                 0.865591057689      \n",
      "53   (1, 1, 12)        242.627228755       2.95435751597     (15.5764960359+0j)                      127.182695964                 0.85960645637       \n",
      "54   (2, 1, 8)         1054.85664949       12.8444927087     (-32.4785567642+0j)                     127.593074114                 0.858085933912      \n",
      "55   (3, 0, 5)         3.47671285255e-28   4.2334295287e-30  (-1.86459455447e-14+0j)                 128.370076381                 0.855251650679      \n",
      "56   (1, 0, 14)        575.318490984       7.0053823581      (23.9857976933+0j)                      134.07792447                  0.836149742469      \n",
      "57   (3, 0, 6)         1849.94881363       22.5259555976     (-43.0110313016+0j)                     134.99278903                  0.83335752108       \n",
      "58   (2, 1, 9)         500.994583473       6.10037513405     (-22.382908289+0j)                      138.021019531                 0.824618502638      \n",
      "59   (2, 0, 12)        58.4103508812       0.711235338348    (-7.64266647716+0j)                     139.698628463                 0.82010033367       \n",
      "60   (3, 0, 7)         1.29563364129e-27   1.57763207605e-29 (-3.59949113249e-14+0j)                 143.99681572                  0.809530060128      \n",
      "61   (2, 1, 10)        256.927413797       3.12848413554     (16.0289554805+0j)                      153.178717453                 0.791483407646      \n",
      "62   (2, 2, 0)         3843.32090065       46.7983088599     (61.9945231504+0j)                      154.096599903                 0.79                \n",
      "63   (1, 0, 15)        190.185116362       2.31579460736     (13.7907619935+0j)                      157.383556045                 0.785144261614      \n",
      "64   (3, 0, 8)         3746.53693222       45.6198160502     (61.2089612085+0j)                      157.916666621                 0.784422997291      \n",
      "65   (2, 2, 2)         1339.42320218       16.3095256238     (-36.5981311296+0j)                     158.576514896                 0.783555558781      \n",
      "66   (2, 0, 13)        1736.79236115       21.148102759      (41.6748408654+0j)                      163.484396738                 0.777967984337      \n",
      "\n",
      "(h,k,l)\t\ttth\tIrel\n",
      "-------\t\t---\t---\n",
      "(0, 0, 2) \t14.39\t70.98\n",
      "(0, 0, 4) \t29.01\t5.82\n",
      "(0, 0, 6) \t44.14\t56.30\n",
      "(0, 0, 8) \t60.13\t95.82\n",
      "(0, 0, 10) \t77.55\t20.48\n",
      "(0, 0, 12) \t97.44\t3.51\n",
      "(0, 0, 14) \t122.50\t29.74\n",
      "\n",
      "(h,k,l)\t\ttth\tIrel\td\tE(tth=90)\n",
      "-------\t\t---\t---\n",
      "(0, 0, 2) \t14.39\t70.98\t6.147\t1.426\n",
      "(0, 0, 4) \t29.01\t5.815\t3.074\t2.853\n",
      "(0, 0, 6) \t44.14\t56.3\t2.049\t4.279\n",
      "(0, 0, 8) \t60.13\t95.82\t1.537\t5.706\n",
      "(0, 0, 10) \t77.55\t20.48\t1.229\t7.132\n",
      "(0, 0, 12) \t97.44\t3.513\t1.025\t8.558\n",
      "(0, 0, 14) \t122.50\t29.74\t0.878\t9.985\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "sys.path.append('/dls_sw/i16/software/python/crystal/')\n",
    "\n",
    "import Crystal as Cr\n",
    "cifpath='/home/spc93/spc_cifs/'\n",
    "mc = Cr.Crystal()\n",
    "mc.load_cif(cifpath+'MoS2_icsd_49801_cifbib.cif','49801-ICSD')\n",
    "\n",
    "energy=12.4/1.54\n",
    "refs=mc.reflection_list(energy)\n",
    "\n",
    "#(1,0,l)\n",
    "#look at 10l 20l 11l\n",
    "shortlist=[ref for ref in refs if ref[0][0]==0 and ref[0][1]==0]\n",
    "print; print '(h,k,l)\\t\\ttth\\tIrel'; print '-------\\t\\t---\\t---'\n",
    "for ref in shortlist[0:25]:\n",
    "    print ref[0],'\\t%.2f\\t%.2f' % (ref[4], ref[2])\n",
    "\n",
    "\n",
    "#refs=mc.reflection_list(energy)\n",
    "#refs=[ref for ref in refs if ref[0][0]==ref[0][1]==ref[0][2]] #filter refs hhh\n",
    "print; print '(h,k,l)\\t\\ttth\\tIrel\\td\\tE(tth=90)'; print '-------\\t\\t---\\t---'\n",
    "for ref in shortlist[0:25]:\n",
    "    d=ref[5]\n",
    "    E90=12.4/np.sqrt(2)/d\n",
    "    print ref[0],'\\t%.2f\\t%.4g\\t%.3f\\t%.3f' % (ref[4], ref[2], d, E90)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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