Irfcc.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1bc10d01",
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "from lmfit import Parameters\n",
    "param = Parameters()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b8e38fcd",
   "metadata": {},
   "outputs": [],
   "source": [
    "path1 = \"//Users/akhiltayal/Library/CloudStorage/GoogleDrive-akhil.tayal.bnl@gmail.com/My Drive/feff_amp_phases/77_Ir_L3/\"\n",
    "path2 = \"//Users/akhiltayal/Library/CloudStorage/GoogleDrive-akhil.tayal.bnl@gmail.com/My Drive/Demo/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "94d28d73",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Irfcc_272_12_Ir_Ir.dat\n",
      "Irfcc_385_6_Ir_Ir.dat\n",
      "Irfcc_472_24_Ir_Ir.dat\n",
      "Irfcc_545_12_Ir_Ir_Ir_Ir.dat\n"
     ]
    }
   ],
   "source": [
    "feff_files = [f for f in sorted(glob.glob(path1+\"Irfcc*.dat\"))][:2]\n",
    "# feff_files = [f for f in sorted(glob.glob(path1+\"bccFe_cus*.dat\"))][:]\n",
    "feff_files += sorted(glob.glob(path1+\"Irfcc*.dat\"))[3:4]\n",
    "feff_files += sorted(glob.glob(path1+\"Irfcc*.dat\"))[5:6]\n",
    "# feff_files += sorted(glob.glob(path1+\"bccFe_[!391]*.dat\"))[2:]\n",
    "# feff_files.append(glob.glob(path1+\"Co_N*ZnS*.dat\")[0])\n",
    "# feff_files.append(sorted(glob.glob(path1+\"*hcp_Co.dat\"))[3])\n",
    "# feff_files.append(sorted(glob.glob(path1+\"*hcp_Co.dat\"))[4])\n",
    "\n",
    "for f in feff_files:\n",
    "    print(f[len(path1):])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "b50c9a90",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "param.clear()\n",
      "#Irfcc_272_12_Ir_Ir.dat\n",
      "param.add('R0', value=2.73, min=2.59, max=2.86, vary=True)\n",
      "param.add('N0', value=12.0, min=10.8, max=13.2, vary=True)\n",
      "param.add('sigma0', value=0.05, min=0.01, max=0.1, vary=True)\n",
      "param.add('C3_0', value=0, min=0.000, max=0.02, vary=False)\n",
      "param.add('C4_0', value=0, min=0.000, max=0.02, vary=False)\n",
      "param.add('DelE0_0', value=0, min=-20, max=20, vary=True)\n",
      "param.add('S02_0', value=0.8, min=0.8, max=1, vary=False)\n",
      "\n",
      "\n",
      "#Irfcc_385_6_Ir_Ir.dat\n",
      "param.add('R1', value=3.85, min=3.66, max=4.05, vary=True)\n",
      "param.add('N1', value=6.0, min=5.4, max=6.6, vary=True)\n",
      "param.add('sigma1', value=0.05, min=0.01, max=0.1, vary=True, expr='sigma0')\n",
      "param.add('C3_1', value=0, min=0.000, max=0.02, vary=False)\n",
      "param.add('C4_1', value=0, min=0.000, max=0.02, vary=False)\n",
      "param.add('DelE0_1', value=0, min=-20, max=20, vary=True, expr='DelE0_0')\n",
      "param.add('S02_1', value=0.8, min=0.8, max=1, vary=False, expr='S02_0')\n",
      "\n",
      "\n",
      "#Irfcc_472_24_Ir_Ir.dat\n",
      "param.add('R2', value=4.72, min=4.48, max=4.96, vary=True)\n",
      "param.add('N2', value=24.0, min=21.6, max=26.4, vary=True)\n",
      "param.add('sigma2', value=0.05, min=0.01, max=0.1, vary=True, expr='sigma1')\n",
      "param.add('C3_2', value=0, min=0.000, max=0.02, vary=False)\n",
      "param.add('C4_2', value=0, min=0.000, max=0.02, vary=False)\n",
      "param.add('DelE0_2', value=0, min=-20, max=20, vary=True, expr='DelE0_0')\n",
      "param.add('S02_2', value=0.8, min=0.8, max=1, vary=False, expr='S02_0')\n",
      "\n",
      "\n",
      "#Irfcc_545_12_Ir_Ir_Ir_Ir.dat\n",
      "param.add('R3', value=5.45, min=5.18, max=5.72, vary=True)\n",
      "param.add('N3', value=12.0, min=10.8, max=13.2, vary=True)\n",
      "param.add('sigma3', value=0.05, min=0.01, max=0.1, vary=True, expr='sigma2')\n",
      "param.add('C3_3', value=0, min=0.000, max=0.02, vary=False)\n",
      "param.add('C4_3', value=0, min=0.000, max=0.02, vary=False)\n",
      "param.add('DelE0_3', value=0, min=-20, max=20, vary=True, expr='DelE0_0')\n",
      "param.add('S02_3', value=0.8, min=0.8, max=1, vary=False, expr='S02_0')\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for i, ffile in enumerate(feff_files):\n",
    "    _, par = readfeff(ffile)\n",
    "    if i == 0:\n",
    "        print(f\"param.clear()\")\n",
    "        print(f\"#{ffile[len(path1):]}\")\n",
    "        print(f\"param.add('R{i:d}', value={par[2]:.2f}, min={par[2]*.95:.2f}, max={par[2]*1.05:.2f}, vary=True)\")\n",
    "        print(f\"param.add('N{i:d}', value={par[1]:.1f}, min={par[1]*.9:.1f}, max={par[1]*1.1:.1f}, vary=True)\")\n",
    "        print(f\"param.add('sigma{i:d}', value=0.05, min=0.01, max=0.1, vary=True)\")\n",
    "        print(f\"param.add('C3_{i:d}', value=0, min=0.000, max=0.02, vary=False)\")\n",
    "        print(f\"param.add('C4_{i:d}', value=0, min=0.000, max=0.02, vary=False)\")\n",
    "        print(f\"param.add('DelE0_{i:d}', value=0, min=-20, max=20, vary=True)\")\n",
    "        print(f\"param.add('S02_{i:d}', value=0.8, min=0.8, max=1, vary=False)\")\n",
    "    else:\n",
    "        print(f\"#{ffile[len(path1):]}\")\n",
    "        print(f\"param.add('R{i:d}', value={par[2]:.2f}, min={par[2]*.95:.2f}, max={par[2]*1.05:.2f}, vary=True)\")\n",
    "        print(f\"param.add('N{i:d}', value={par[1]:.1f}, min={par[1]*.9:.1f}, max={par[1]*1.1:.1f}, vary=True)\")\n",
    "        print(f\"param.add('sigma{i:d}', value=0.05, min=0.01, max=0.1, vary=True, expr='sigma{i-1:d}')\")\n",
    "        print(f\"param.add('C3_{i:d}', value=0, min=0.000, max=0.02, vary=False)\")\n",
    "        print(f\"param.add('C4_{i:d}', value=0, min=0.000, max=0.02, vary=False)\")\n",
    "        print(f\"param.add('DelE0_{i:d}', value=0, min=-20, max=20, vary=True, expr='DelE0_0')\")\n",
    "        print(f\"param.add('S02_{i:d}', value=0.8, min=0.8, max=1, vary=False, expr='S02_0')\")\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "ab0f5f15",
   "metadata": {},
   "outputs": [],
   "source": [
    "param.clear()\n",
    "#Irfcc_272_12_Ir_Ir.dat\n",
    "param.add('R0', value=2.73, min=2.59, max=2.86, vary=True)\n",
    "param.add('N0', value=12.0, min=10.8, max=13.2, vary=False)\n",
    "param.add('sigma0', value=0.05, min=0.01, max=0.1, vary=True)\n",
    "param.add('C3_0', value=0, min=0.000, max=0.02, vary=False)\n",
    "param.add('C4_0', value=0, min=0.000, max=0.02, vary=False)\n",
    "param.add('DelE0_0', value=0, min=-20, max=20, vary=True)\n",
    "param.add('S02_0', value=0.8, min=0.8, max=1, vary=False)\n",
    "\n",
    "\n",
    "#Irfcc_385_6_Ir_Ir.dat\n",
    "param.add('R1', value=3.85, min=3.66, max=4.05, vary=True)\n",
    "param.add('N1', value=6.0, min=5.4, max=6.6, vary=False)\n",
    "param.add('sigma1', value=0.05, min=0.01, max=0.1, vary=True, expr='sigma0')\n",
    "param.add('C3_1', value=0, min=0.000, max=0.02, vary=False)\n",
    "param.add('C4_1', value=0, min=0.000, max=0.02, vary=False)\n",
    "param.add('DelE0_1', value=0, min=-20, max=20, vary=True, expr='DelE0_0')\n",
    "param.add('S02_1', value=0.8, min=0.8, max=1, vary=False, expr='S02_0')\n",
    "\n",
    "\n",
    "#Irfcc_472_24_Ir_Ir.dat\n",
    "param.add('R2', value=4.7, min=4.48, max=4.96, vary=True)\n",
    "param.add('N2', value=24.0, min=21.6, max=26.4, vary=False)\n",
    "param.add('sigma2', value=0.05, min=0.01, max=0.2, vary=True)\n",
    "param.add('C3_2', value=0, min=0.000, max=0.02, vary=False)\n",
    "param.add('C4_2', value=0, min=0.000, max=0.02, vary=False)\n",
    "param.add('DelE0_2', value=0, min=-20, max=20, vary=True, expr='DelE0_0')\n",
    "param.add('S02_2', value=0.8, min=0.8, max=1, vary=False, expr='S02_0')\n",
    "\n",
    "#Irfcc_545_12_Ir_Ir_Ir_Ir.dat\n",
    "param.add('R3', value=5.42, min=5.18, max=5.72, vary=True)\n",
    "param.add('N3', value=12.0, min=10.8, max=13.2, vary=True)\n",
    "param.add('sigma3', value=0.05, min=0.01, max=0.2, vary=True)\n",
    "param.add('C3_3', value=0, min=0.000, max=0.02, vary=False)\n",
    "param.add('C4_3', value=0, min=0.000, max=0.02, vary=False)\n",
    "param.add('DelE0_3', value=0, min=-20, max=20, vary=True, expr='DelE0_0')\n",
    "param.add('S02_3', value=0.8, min=0.8, max=1, vary=False, expr='S02_0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "7e27e456",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['//Users/akhiltayal/Library/CloudStorage/GoogleDrive-akhil.tayal.bnl@gmail.com/My Drive/Demo/Ir_L3_calib.chik']"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_file = [f for f in sorted(glob.glob(path2+\"Ir_L3*.chik\"))]\n",
    "data_file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "12d15be6",
   "metadata": {},
   "outputs": [],
   "source": [
    "col_names = ['k', 'chi', 'chik', 'chik2', 'chik3', 'win', 'energy']\n",
    "dat = pd.read_csv(data_file[0], comment='#', sep='\\s+', names=col_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "4809f912",
   "metadata": {},
   "outputs": [],
   "source": [
    "from lmfit import minimize\n",
    "\n",
    "fit_range = [3.15, 18]\n",
    "out = minimize(residual, param, method='leastsq', args=(dat['k'], dat['chik2'], fit_range, feff_files, 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "46310f52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<h2>Fit Statistics</h2><table><tr><td>fitting method</td><td>leastsq</td><td></td></tr><tr><td># function evals</td><td>222</td><td></td></tr><tr><td># data points</td><td>297</td><td></td></tr><tr><td># variables</td><td>9</td><td></td></tr><tr><td>chi-square</td><td> 16.7786774</td><td></td></tr><tr><td>reduced chi-square</td><td> 0.05825930</td><td></td></tr><tr><td>Akaike info crit.</td><td>-835.466109</td><td></td></tr><tr><td>Bayesian info crit.</td><td>-802.222520</td><td></td></tr></table><h2>Variables</h2><table><tr><th> name </th><th> value </th><th> standard error </th><th> relative error </th><th> initial value </th><th> min </th><th> max </th><th> vary </th><th> expression </th></tr><tr><td> R0 </td><td>  2.70595368 </td><td>  8.6405e-04 </td><td> (0.03%) </td><td> 2.73 </td><td>  2.59000000 </td><td>  2.86000000 </td><td> True </td><td>  </td></tr><tr><td> N0 </td><td>  12.0000000 </td><td>  0.00000000 </td><td> (0.00%) </td><td> 12.0 </td><td>  10.8000000 </td><td>  13.2000000 </td><td> False </td><td>  </td></tr><tr><td> sigma0 </td><td>  0.05939174 </td><td>  3.7359e-04 </td><td> (0.63%) </td><td> 0.05 </td><td>  0.01000000 </td><td>  0.10000000 </td><td> True </td><td>  </td></tr><tr><td> C3_0 </td><td>  0.00000000 </td><td>  0.00000000 </td><td>  </td><td> 0 </td><td>  0.00000000 </td><td>  0.02000000 </td><td> False </td><td>  </td></tr><tr><td> C4_0 </td><td>  0.00000000 </td><td>  0.00000000 </td><td>  </td><td> 0 </td><td>  0.00000000 </td><td>  0.02000000 </td><td> False </td><td>  </td></tr><tr><td> DelE0_0 </td><td>  4.84060660 </td><td>  0.26800517 </td><td> (5.54%) </td><td> 0 </td><td> -20.0000000 </td><td>  20.0000000 </td><td> True </td><td>  </td></tr><tr><td> S02_0 </td><td>  0.80000000 </td><td>  0.00000000 </td><td> (0.00%) </td><td> 0.8 </td><td>  0.80000000 </td><td>  1.00000000 </td><td> False </td><td>  </td></tr><tr><td> R1 </td><td>  3.82570918 </td><td>  0.00301869 </td><td> (0.08%) </td><td> 3.85 </td><td>  3.66000000 </td><td>  4.05000000 </td><td> True </td><td>  </td></tr><tr><td> N1 </td><td>  6.00000000 </td><td>  0.00000000 </td><td> (0.00%) </td><td> 6.0 </td><td>  5.40000000 </td><td>  6.60000000 </td><td> False </td><td>  </td></tr><tr><td> sigma1 </td><td>  0.05939174 </td><td>  3.7359e-04 </td><td> (0.63%) </td><td> 0.05 </td><td>  0.01000000 </td><td>  0.10000000 </td><td> False </td><td> sigma0 </td></tr><tr><td> C3_1 </td><td>  0.00000000 </td><td>  0.00000000 </td><td>  </td><td> 0 </td><td>  0.00000000 </td><td>  0.02000000 </td><td> False </td><td>  </td></tr><tr><td> C4_1 </td><td>  0.00000000 </td><td>  0.00000000 </td><td>  </td><td> 0 </td><td>  0.00000000 </td><td>  0.02000000 </td><td> False </td><td>  </td></tr><tr><td> DelE0_1 </td><td>  4.84060660 </td><td>  0.26800517 </td><td> (5.54%) </td><td> 0 </td><td> -20.0000000 </td><td>  20.0000000 </td><td> False </td><td> DelE0_0 </td></tr><tr><td> S02_1 </td><td>  0.80000000 </td><td>  0.00000000 </td><td> (0.00%) </td><td> 0.8 </td><td>  0.80000000 </td><td>  1.00000000 </td><td> False </td><td> S02_0 </td></tr><tr><td> R2 </td><td>  4.70364452 </td><td>  0.00235088 </td><td> (0.05%) </td><td> 4.7 </td><td>  4.48000000 </td><td>  4.96000000 </td><td> True </td><td>  </td></tr><tr><td> N2 </td><td>  24.0000000 </td><td>  0.00000000 </td><td> (0.00%) </td><td> 24.0 </td><td>  21.6000000 </td><td>  26.4000000 </td><td> False </td><td>  </td></tr><tr><td> sigma2 </td><td>  0.07019316 </td><td>  0.00110055 </td><td> (1.57%) </td><td> 0.05 </td><td>  0.01000000 </td><td>  0.20000000 </td><td> True </td><td>  </td></tr><tr><td> C3_2 </td><td>  0.00000000 </td><td>  0.00000000 </td><td>  </td><td> 0 </td><td>  0.00000000 </td><td>  0.02000000 </td><td> False </td><td>  </td></tr><tr><td> C4_2 </td><td>  0.00000000 </td><td>  0.00000000 </td><td>  </td><td> 0 </td><td>  0.00000000 </td><td>  0.02000000 </td><td> False </td><td>  </td></tr><tr><td> DelE0_2 </td><td>  4.84060660 </td><td>  0.26800517 </td><td> (5.54%) </td><td> 0 </td><td> -20.0000000 </td><td>  20.0000000 </td><td> False </td><td> DelE0_0 </td></tr><tr><td> S02_2 </td><td>  0.80000000 </td><td>  0.00000000 </td><td> (0.00%) </td><td> 0.8 </td><td>  0.80000000 </td><td>  1.00000000 </td><td> False </td><td> S02_0 </td></tr><tr><td> R3 </td><td>  5.40733097 </td><td>  0.00294321 </td><td> (0.05%) </td><td> 5.42 </td><td>  5.18000000 </td><td>  5.72000000 </td><td> True </td><td>  </td></tr><tr><td> N3 </td><td>  10.8000000 </td><td>  0.95015309 </td><td> (8.80%) </td><td> 12.0 </td><td>  10.8000000 </td><td>  13.2000000 </td><td> True </td><td>  </td></tr><tr><td> sigma3 </td><td>  0.08410012 </td><td>  0.00206844 </td><td> (2.46%) </td><td> 0.05 </td><td>  0.01000000 </td><td>  0.20000000 </td><td> True </td><td>  </td></tr><tr><td> C3_3 </td><td>  0.00000000 </td><td>  0.00000000 </td><td>  </td><td> 0 </td><td>  0.00000000 </td><td>  0.02000000 </td><td> False </td><td>  </td></tr><tr><td> C4_3 </td><td>  0.00000000 </td><td>  0.00000000 </td><td>  </td><td> 0 </td><td>  0.00000000 </td><td>  0.02000000 </td><td> False </td><td>  </td></tr><tr><td> DelE0_3 </td><td>  4.84060660 </td><td>  0.26800517 </td><td> (5.54%) </td><td> 0 </td><td> -20.0000000 </td><td>  20.0000000 </td><td> False </td><td> DelE0_0 </td></tr><tr><td> S02_3 </td><td>  0.80000000 </td><td>  0.00000000 </td><td> (0.00%) </td><td> 0.8 </td><td>  0.80000000 </td><td>  1.00000000 </td><td> False </td><td> S02_0 </td></tr></table><h2>Correlations (unreported correlations are < 0.100)</h2><table><tr><td>N3</td><td>sigma3</td><td>0.8351</td></tr><tr><td>R0</td><td>DelE0_0</td><td>0.6711</td></tr><tr><td>DelE0_0</td><td>R3</td><td>0.5934</td></tr><tr><td>DelE0_0</td><td>R2</td><td>0.4833</td></tr><tr><td>R0</td><td>R3</td><td>0.3930</td></tr><tr><td>R2</td><td>R3</td><td>0.3492</td></tr><tr><td>R0</td><td>R2</td><td>0.3194</td></tr><tr><td>DelE0_0</td><td>R1</td><td>0.2780</td></tr><tr><td>R1</td><td>R3</td><td>0.1763</td></tr><tr><td>R0</td><td>R1</td><td>0.1701</td></tr><tr><td>R1</td><td>R2</td><td>0.1429</td></tr></table>"
      ],
      "text/plain": [
       "<lmfit.minimizer.MinimizerResult at 0x14229c130>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "84e1707b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"799.6333333333333\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Quick plot chi(k)\n",
    "#Quick plot chi(k)\n",
    "exafs_fit = calculate_exafs_lmfit(dat.k, out.params, feff_files, None, 2)\n",
    "fig, ax = plt.subplots(1,2, sharey=False, figsize=(8,4))\n",
    "kmin = fit_range[0]\n",
    "kmax = fit_range[1]\n",
    "\n",
    "ax[0].plot(dat.k, dat.chik2, 'b')\n",
    "ax[0].plot(dat.k, exafs_fit, 'r')\n",
    "ax[0].set_xlim(kmin,kmax)\n",
    "ax[0].axhline(0, color='black')\n",
    "\n",
    "\n",
    "test = Group()\n",
    "xftf(dat.k, dat.chik2, group=test, kweight=0, window='sine', kmin=kmin, kmax=kmax)\n",
    "fit = Group()\n",
    "xftf(dat.k, np.nan_to_num(exafs_fit), group=fit, kweight=0, window='sine', kmin=kmin, kmax=kmax)\n",
    "\n",
    "\n",
    "ax[1].plot(test.r, test.chir_mag, 'blue')\n",
    "ax[1].plot(test.r, test.chir_re, 'blue')\n",
    "ax[1].plot(fit.r, fit.chir_mag, 'r')\n",
    "ax[1].plot(fit.r, fit.chir_re, 'r')\n",
    "ax[1].plot(fit.r, abs(test.chir_mag-fit.chir_mag), 'black')\n",
    "ax[1].axhline(0, color='black')\n",
    "ax[1].set_xlim(0.5,5.9)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd55462a",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(data_file[0][len(path2):-24])\n",
    "file_name = data_file[0][len(path2):-24]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3a3824d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "save_data_files(file_name, out, path2, feff_files, data_file[0], dat.k, dat.chi, k_weight = 2,\n",
    "                    k_min=3, k_max=14)"
   ]
  }
 ],
 "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}