{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "de8dcf4e-dd5d-4411-9951-0ad258aba344",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "eb3aafb4-af64-4b54-a16a-607152f57b01",
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy.io import ascii"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d88134c-c288-4e72-a550-952516c16f30",
   "metadata": {},
   "source": [
    "# Scattering intensity Iq"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "296f2525-1c32-4128-bb51-c171cae06a9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "Iq_table = ascii.read('Iq_values.dat')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "a45fe934-6df8-4d19-9de0-3e0350c2e37d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=200</i>\n",
       "<table id=\"table139717783099520\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>q</th><th>Iq0</th><th>Iq1</th><th>Iq2</th><th>Iq3</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>0.049119</td><td>269.666667</td><td>19.333333</td><td>18.333333</td><td>20.0</td></tr>\n",
       "<tr><td>0.049781</td><td>282.333333</td><td>24.666667</td><td>15.0</td><td>15.0</td></tr>\n",
       "<tr><td>0.050279</td><td>289.25</td><td>24.75</td><td>16.75</td><td>18.0</td></tr>\n",
       "<tr><td>0.051018</td><td>274.166667</td><td>22.25</td><td>17.25</td><td>18.25</td></tr>\n",
       "<tr><td>0.05173</td><td>266.666667</td><td>20.444444</td><td>16.444444</td><td>19.111111</td></tr>\n",
       "<tr><td>0.05228</td><td>259.222222</td><td>20.444444</td><td>16.666667</td><td>18.666667</td></tr>\n",
       "<tr><td>0.052786</td><td>260.4</td><td>22.5</td><td>16.0</td><td>16.3</td></tr>\n",
       "<tr><td>0.053482</td><td>255.0</td><td>18.263158</td><td>16.052632</td><td>17.421053</td></tr>\n",
       "<tr><td>0.05417</td><td>240.894737</td><td>20.473684</td><td>14.052632</td><td>17.894737</td></tr>\n",
       "<tr><td>0.054768</td><td>239.318182</td><td>19.636364</td><td>13.636364</td><td>16.545455</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>0.168699</td><td>5.77839</td><td>0.932745</td><td>0.960309</td><td>0.947078</td></tr>\n",
       "<tr><td>0.169327</td><td>5.877076</td><td>0.939092</td><td>0.913621</td><td>0.921373</td></tr>\n",
       "<tr><td>0.169961</td><td>5.774617</td><td>0.95733</td><td>0.978118</td><td>0.90372</td></tr>\n",
       "<tr><td>0.170583</td><td>5.7876</td><td>0.920781</td><td>0.95178</td><td>0.943743</td></tr>\n",
       "<tr><td>0.171214</td><td>5.746285</td><td>0.977707</td><td>0.893843</td><td>0.981953</td></tr>\n",
       "<tr><td>0.171855</td><td>5.725789</td><td>0.961915</td><td>0.952122</td><td>0.966268</td></tr>\n",
       "<tr><td>0.172484</td><td>5.816667</td><td>0.974444</td><td>0.901111</td><td>0.958889</td></tr>\n",
       "<tr><td>0.173106</td><td>5.736667</td><td>0.964444</td><td>0.962222</td><td>0.988889</td></tr>\n",
       "<tr><td>0.173697</td><td>5.681046</td><td>0.976471</td><td>0.891503</td><td>0.909804</td></tr>\n",
       "<tr><td>0.174301</td><td>5.930328</td><td>1.053279</td><td>0.971311</td><td>0.971311</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=200>\n",
       "   q        Iq0        Iq1       Iq2       Iq3   \n",
       "float64   float64    float64   float64   float64 \n",
       "-------- ---------- --------- --------- ---------\n",
       "0.049119 269.666667 19.333333 18.333333      20.0\n",
       "0.049781 282.333333 24.666667      15.0      15.0\n",
       "0.050279     289.25     24.75     16.75      18.0\n",
       "0.051018 274.166667     22.25     17.25     18.25\n",
       " 0.05173 266.666667 20.444444 16.444444 19.111111\n",
       " 0.05228 259.222222 20.444444 16.666667 18.666667\n",
       "0.052786      260.4      22.5      16.0      16.3\n",
       "0.053482      255.0 18.263158 16.052632 17.421053\n",
       " 0.05417 240.894737 20.473684 14.052632 17.894737\n",
       "0.054768 239.318182 19.636364 13.636364 16.545455\n",
       "     ...        ...       ...       ...       ...\n",
       "0.168699    5.77839  0.932745  0.960309  0.947078\n",
       "0.169327   5.877076  0.939092  0.913621  0.921373\n",
       "0.169961   5.774617   0.95733  0.978118   0.90372\n",
       "0.170583     5.7876  0.920781   0.95178  0.943743\n",
       "0.171214   5.746285  0.977707  0.893843  0.981953\n",
       "0.171855   5.725789  0.961915  0.952122  0.966268\n",
       "0.172484   5.816667  0.974444  0.901111  0.958889\n",
       "0.173106   5.736667  0.964444  0.962222  0.988889\n",
       "0.173697   5.681046  0.976471  0.891503  0.909804\n",
       "0.174301   5.930328  1.053279  0.971311  0.971311"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Iq_table # q [nm^-1], Iq [ph/pix/s]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "8761c462-3a9f-45be-a2de-5e61ff55ed15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '$I(q)$ (ph/pix/$\\\\mu$s)')"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "q = np.array(Iq_table['q'])\n",
    "\n",
    "plt.figure()\n",
    "for i in range(4):\n",
    "    Iq = np.array(Iq_table['Iq'+str(i)])\n",
    "    plt.plot(q,Iq*1e2*1e-6) # per binned 10x10 pixel\n",
    "plt.yscale('log')\n",
    "plt.xlabel(r'$q$ (nm$^{-1}$)')\n",
    "plt.ylabel(r'$I(q)$ (ph/pix/$\\mu$s)')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ec099008-acac-4239-9af2-21289c3ce351",
   "metadata": {},
   "source": [
    "# Intensity autocorrelation functions g2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "cf91c4b6-75a7-43b6-bbd2-692a1752a8aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "g2_table = ascii.read('g2_NPwater.dat') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "9ff6ab5e-7421-4118-adf8-36a0c1607d42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=398</i>\n",
       "<table id=\"table139717779191936\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>q</th><th>tau</th><th>tau_err</th><th>beta</th><th>beta_err</th><th>t</th><th>g2_0</th><th>g2_stdev_0</th><th>g2_1</th><th>g2_stdev_1</th><th>g2_2</th><th>g2_stdev_2</th><th>g2_3</th><th>g2_stdev_3</th><th>g2_4</th><th>g2_stdev_4</th><th>g2_5</th><th>g2_stdev_5</th><th>g2_6</th><th>g2_stdev_6</th><th>g2_7</th><th>g2_stdev_7</th><th>g2_8</th><th>g2_stdev_8</th><th>g2_9</th><th>g2_stdev_9</th><th>g2_10</th><th>g2_stdev_10</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>0.06427808621839916</td><td>147.02681867662096</td><td>1.0267322694650738</td><td>0.509882328714025</td><td>0.001741756729689579</td><td>1.0</td><td>1.5304</td><td>0.045598</td><td>1.514879</td><td>0.045766</td><td>1.486739</td><td>0.051042</td><td>1.500675</td><td>0.057612</td><td>1.451705</td><td>0.073617</td><td>1.405687</td><td>0.087904</td><td>1.379833</td><td>0.09897</td><td>1.33219</td><td>0.115188</td><td>1.280977</td><td>0.161159</td><td>1.255267</td><td>0.195201</td><td>1.244293</td><td>0.204093</td></tr>\n",
       "<tr><td>0.06688745273512944</td><td>132.59212228836068</td><td>0.8840524401215853</td><td>0.4934276846499262</td><td>0.0016711153756487523</td><td>1.5</td><td>1.540761</td><td>0.050569</td><td>1.521638</td><td>0.043165</td><td>1.492033</td><td>0.051916</td><td>1.496215</td><td>0.05729</td><td>1.454328</td><td>0.068563</td><td>1.433436</td><td>0.097692</td><td>1.394315</td><td>0.102638</td><td>1.333047</td><td>0.125586</td><td>1.307952</td><td>0.14843</td><td>1.238203</td><td>0.195677</td><td>1.226338</td><td>0.211659</td></tr>\n",
       "<tr><td>0.07111541054674533</td><td>114.30545576373476</td><td>0.7558277769254081</td><td>0.47055425132775486</td><td>0.001666199575704337</td><td>2.0</td><td>1.534985</td><td>0.047612</td><td>1.516716</td><td>0.040749</td><td>1.478968</td><td>0.049853</td><td>1.493817</td><td>0.058253</td><td>1.44923</td><td>0.073915</td><td>1.41475</td><td>0.095282</td><td>1.387924</td><td>0.093008</td><td>1.326856</td><td>0.123225</td><td>1.293016</td><td>0.161382</td><td>1.266842</td><td>0.196152</td><td>1.220088</td><td>0.207794</td></tr>\n",
       "<tr><td>0.0745149872914487</td><td>106.94385289754742</td><td>0.7130366126273988</td><td>0.4643615401888108</td><td>0.0016902212254410525</td><td>2.5</td><td>1.516596</td><td>0.049194</td><td>1.500995</td><td>0.046885</td><td>1.473123</td><td>0.049559</td><td>1.484388</td><td>0.059272</td><td>1.434708</td><td>0.073862</td><td>1.400209</td><td>0.090837</td><td>1.370163</td><td>0.091366</td><td>1.316904</td><td>0.124385</td><td>1.28336</td><td>0.156579</td><td>1.228699</td><td>0.180868</td><td>1.19925</td><td>0.205896</td></tr>\n",
       "<tr><td>0.07851203940359536</td><td>92.84927165022535</td><td>0.7442826909600457</td><td>0.41984136914464626</td><td>0.0019247411471789303</td><td>3.0</td><td>1.52365</td><td>0.047991</td><td>1.503269</td><td>0.043213</td><td>1.470447</td><td>0.051265</td><td>1.48049</td><td>0.05556</td><td>1.431478</td><td>0.073944</td><td>1.382867</td><td>0.093052</td><td>1.372962</td><td>0.099258</td><td>1.316266</td><td>0.12276</td><td>1.274071</td><td>0.164122</td><td>1.245617</td><td>0.185568</td><td>1.201211</td><td>0.201973</td></tr>\n",
       "<tr><td>0.08113533563085039</td><td>87.36313308178282</td><td>0.7676113446522906</td><td>0.38992571042521457</td><td>0.0020230103635840053</td><td>3.5</td><td>1.533951</td><td>0.052941</td><td>1.511201</td><td>0.04361</td><td>1.483262</td><td>0.051773</td><td>1.49121</td><td>0.062728</td><td>1.443786</td><td>0.073267</td><td>1.40742</td><td>0.090018</td><td>1.382741</td><td>0.098213</td><td>1.325985</td><td>0.117951</td><td>1.284509</td><td>0.158843</td><td>1.236478</td><td>0.180587</td><td>1.20982</td><td>0.221846</td></tr>\n",
       "<tr><td>0.08475168369037077</td><td>77.35115362405445</td><td>0.7584258775230884</td><td>0.35646730853328107</td><td>0.0021429148670754667</td><td>4.0</td><td>1.511937</td><td>0.047303</td><td>1.491018</td><td>0.042768</td><td>1.4593</td><td>0.047977</td><td>1.472008</td><td>0.052536</td><td>1.41983</td><td>0.067312</td><td>1.386331</td><td>0.091917</td><td>1.363332</td><td>0.098038</td><td>1.322037</td><td>0.127676</td><td>1.271382</td><td>0.158192</td><td>1.236745</td><td>0.195684</td><td>1.182184</td><td>0.196326</td></tr>\n",
       "<tr><td>0.08839429637328979</td><td>69.77889272569925</td><td>0.9163944203885372</td><td>0.30844489222913646</td><td>0.0025728229298977927</td><td>4.5</td><td>1.506414</td><td>0.048192</td><td>1.486719</td><td>0.041932</td><td>1.456541</td><td>0.04744</td><td>1.462336</td><td>0.055831</td><td>1.414627</td><td>0.070645</td><td>1.381902</td><td>0.090078</td><td>1.356826</td><td>0.093196</td><td>1.296715</td><td>0.123658</td><td>1.265894</td><td>0.155453</td><td>1.212357</td><td>0.181479</td><td>1.187778</td><td>0.205402</td></tr>\n",
       "<tr><td>0.09212256818164052</td><td>61.32405448556333</td><td>1.0412940379212459</td><td>0.2680051745661163</td><td>0.003012993536907304</td><td>5.0</td><td>1.512245</td><td>0.049099</td><td>1.495262</td><td>0.043251</td><td>1.459659</td><td>0.048402</td><td>1.465266</td><td>0.056249</td><td>1.418759</td><td>0.072762</td><td>1.386928</td><td>0.090458</td><td>1.357552</td><td>0.091278</td><td>1.302191</td><td>0.11493</td><td>1.267099</td><td>0.15323</td><td>1.21766</td><td>0.190982</td><td>1.211053</td><td>0.191793</td></tr>\n",
       "<tr><td>0.095256660562808</td><td>52.29744498299846</td><td>1.3216691365213564</td><td>0.2197805576912435</td><td>0.0037743277753138973</td><td>5.5</td><td>1.509429</td><td>0.045824</td><td>1.487515</td><td>0.039543</td><td>1.457822</td><td>0.048503</td><td>1.469588</td><td>0.051352</td><td>1.420583</td><td>0.077357</td><td>1.383826</td><td>0.09309</td><td>1.346741</td><td>0.104347</td><td>1.305408</td><td>0.127708</td><td>1.260484</td><td>0.157454</td><td>1.22369</td><td>0.178472</td><td>1.185836</td><td>0.207985</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>40613.0</td><td>1.020453</td><td>0.038196</td><td>1.017752</td><td>0.03969</td><td>1.017741</td><td>0.040102</td><td>1.029927</td><td>0.048204</td><td>1.027914</td><td>0.066405</td><td>1.027374</td><td>0.082116</td><td>1.037234</td><td>0.087156</td><td>1.032907</td><td>0.108891</td><td>1.012186</td><td>0.133139</td><td>1.021983</td><td>0.194787</td><td>1.04218</td><td>0.200666</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>41562.5</td><td>1.025252</td><td>0.039325</td><td>1.024484</td><td>0.033463</td><td>1.015459</td><td>0.043167</td><td>1.036454</td><td>0.048552</td><td>1.034986</td><td>0.062299</td><td>1.030543</td><td>0.083449</td><td>1.03889</td><td>0.087399</td><td>1.032738</td><td>0.109851</td><td>1.018634</td><td>0.140183</td><td>1.035065</td><td>0.179457</td><td>1.039235</td><td>0.218015</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>42533.5</td><td>1.027862</td><td>0.041397</td><td>1.029133</td><td>0.038068</td><td>1.025811</td><td>0.042583</td><td>1.040004</td><td>0.04551</td><td>1.028913</td><td>0.066407</td><td>1.022844</td><td>0.07362</td><td>1.036828</td><td>0.087665</td><td>1.051425</td><td>0.117466</td><td>1.024506</td><td>0.143754</td><td>1.045356</td><td>0.179321</td><td>1.050067</td><td>0.196252</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>43528.0</td><td>1.027043</td><td>0.037393</td><td>1.020157</td><td>0.034642</td><td>1.01528</td><td>0.04407</td><td>1.039472</td><td>0.048956</td><td>1.037603</td><td>0.058567</td><td>1.032308</td><td>0.0774</td><td>1.04229</td><td>0.082043</td><td>1.035456</td><td>0.115668</td><td>1.042416</td><td>0.137143</td><td>1.040878</td><td>0.190229</td><td>1.047782</td><td>0.186232</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>44545.0</td><td>1.023537</td><td>0.039658</td><td>1.024585</td><td>0.037018</td><td>1.017487</td><td>0.043841</td><td>1.032965</td><td>0.049848</td><td>1.032909</td><td>0.066806</td><td>1.025937</td><td>0.084512</td><td>1.037545</td><td>0.086138</td><td>1.024829</td><td>0.115391</td><td>1.017206</td><td>0.139927</td><td>1.027825</td><td>0.182775</td><td>1.044813</td><td>0.194496</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>45586.0</td><td>1.01512</td><td>0.040441</td><td>1.017752</td><td>0.040384</td><td>1.013979</td><td>0.042347</td><td>1.032996</td><td>0.046491</td><td>1.027525</td><td>0.061907</td><td>1.020877</td><td>0.083348</td><td>1.034645</td><td>0.084745</td><td>1.04394</td><td>0.105785</td><td>1.021416</td><td>0.141242</td><td>1.038815</td><td>0.175758</td><td>1.032542</td><td>0.198698</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>46651.5</td><td>1.017367</td><td>0.038563</td><td>1.017847</td><td>0.033723</td><td>1.014726</td><td>0.041768</td><td>1.037929</td><td>0.046866</td><td>1.025454</td><td>0.065786</td><td>1.026989</td><td>0.077732</td><td>1.033916</td><td>0.083448</td><td>1.034364</td><td>0.11358</td><td>1.032466</td><td>0.13652</td><td>1.023432</td><td>0.189305</td><td>1.01433</td><td>0.194328</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>47742.0</td><td>1.013714</td><td>0.037805</td><td>1.017816</td><td>0.03518</td><td>1.010967</td><td>0.04014</td><td>1.035778</td><td>0.051908</td><td>1.023425</td><td>0.06473</td><td>1.018506</td><td>0.08368</td><td>1.027439</td><td>0.082158</td><td>1.032132</td><td>0.117378</td><td>1.029514</td><td>0.133269</td><td>1.028887</td><td>0.18227</td><td>1.024019</td><td>0.213836</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>48858.0</td><td>1.023491</td><td>0.041736</td><td>1.025027</td><td>0.036336</td><td>1.021952</td><td>0.039518</td><td>1.039793</td><td>0.048474</td><td>1.04067</td><td>0.064319</td><td>1.033917</td><td>0.082113</td><td>1.039699</td><td>0.083852</td><td>1.041469</td><td>0.105984</td><td>1.041782</td><td>0.149518</td><td>1.043159</td><td>0.183062</td><td>1.040165</td><td>0.215605</td></tr>\n",
       "<tr><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>50000.0</td><td>1.016387</td><td>0.038854</td><td>1.014175</td><td>0.033171</td><td>1.012324</td><td>0.041576</td><td>1.028302</td><td>0.051298</td><td>1.020526</td><td>0.065633</td><td>1.031886</td><td>0.085646</td><td>1.027323</td><td>0.0921</td><td>1.019549</td><td>0.108405</td><td>1.025723</td><td>0.139578</td><td>1.038108</td><td>0.191637</td><td>1.01887</td><td>0.20661</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=398>\n",
       "         q                 tau         ...  g2_10   g2_stdev_10\n",
       "      float64            float64       ... float64    float64  \n",
       "------------------- ------------------ ... -------- -----------\n",
       "0.06427808621839916 147.02681867662096 ... 1.244293    0.204093\n",
       "0.06688745273512944 132.59212228836068 ... 1.226338    0.211659\n",
       "0.07111541054674533 114.30545576373476 ... 1.220088    0.207794\n",
       " 0.0745149872914487 106.94385289754742 ...  1.19925    0.205896\n",
       "0.07851203940359536  92.84927165022535 ... 1.201211    0.201973\n",
       "0.08113533563085039  87.36313308178282 ...  1.20982    0.221846\n",
       "0.08475168369037077  77.35115362405445 ... 1.182184    0.196326\n",
       "0.08839429637328979  69.77889272569925 ... 1.187778    0.205402\n",
       "0.09212256818164052  61.32405448556333 ... 1.211053    0.191793\n",
       "  0.095256660562808  52.29744498299846 ... 1.185836    0.207985\n",
       "                ...                ... ...      ...         ...\n",
       "                nan                nan ...  1.04218    0.200666\n",
       "                nan                nan ... 1.039235    0.218015\n",
       "                nan                nan ... 1.050067    0.196252\n",
       "                nan                nan ... 1.047782    0.186232\n",
       "                nan                nan ... 1.044813    0.194496\n",
       "                nan                nan ... 1.032542    0.198698\n",
       "                nan                nan ...  1.01433    0.194328\n",
       "                nan                nan ... 1.024019    0.213836\n",
       "                nan                nan ... 1.040165    0.215605\n",
       "                nan                nan ...  1.01887     0.20661"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g2_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "e326b71b-54b7-4b80-b7a0-b6d21a038afe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.06427809 0.06688745 0.07111541 0.07451499 0.07851204 0.08113534\n",
      " 0.08475168 0.0883943  0.09212257 0.09525666 0.09889776]\n"
     ]
    }
   ],
   "source": [
    "q = np.array(g2_table['q']) # nm^-1\n",
    "tau = np.array(g2_table['tau']) # microseconds\n",
    "tau_err = np.array(g2_table['tau_err'])\n",
    "t = np.array(g2_table['t'])\n",
    "\n",
    "print(q[~np.isnan(q)]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "0cc011d5-37a2-471f-8bfc-76490b10a29c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '$g_2$')"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "for i in range(0,len(q[~np.isnan(q)]),2):\n",
    "    g2 = np.array(g2_table['g2_'+str(i)])\n",
    "    g2_stdev = np.array(g2_table['g2_stdev_'+str(i)])\n",
    "    #plt.errorbar(t,g2, yerr=g2_stdev, label=r'%.3f nm$^{-1}$' %q[i])\n",
    "    plt.plot(t,g2,label=r'%.3f nm$^{-1}$' %q[i])\n",
    "plt.xscale('log')\n",
    "plt.legend(loc='upper right')\n",
    "plt.xlabel(r'$t$ ($\\mu$s)')\n",
    "plt.ylabel(r'$g_2$')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "42e22e5d-9c88-4b86-bb25-9a7c97105498",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, '$\\\\tau$ ($\\\\mu$s)')"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.errorbar(q,tau,yerr=tau_err,fmt='o')\n",
    "plt.xlabel(r'$q$ (nm$^{-1}$)')\n",
    "plt.ylabel(r'$\\tau$ ($\\mu$s)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c1c21d14-9ccf-452c-86e5-079499d33c67",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "22d84c63-e6dc-464b-a6c7-9f905c7c6ec9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}