{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "91397969",
   "metadata": {},
   "source": [
    "# Tutorial for HN module"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "8a0c1262",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import the necessary packages along with HavNegpy\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import HavNegpy as dd\n",
    "%matplotlib qt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d2df3e15",
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract the data\n",
    "\n",
    "filename = 'hn_example_data.txt'\n",
    "col_names = ['log f', 'log eps2']\n",
    "df = pd.read_csv(filename, sep=',',index_col=False,usecols = [0,1],names=col_names,header=None,skiprows=2,encoding='unicode_escape',engine='python')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50ea9f0d",
   "metadata": {},
   "source": [
    "## Fitting example of single HN function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "550f0c8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Example for HN fitting')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# plot the data \n",
    "\n",
    "x,y = df['log f'], df['log eps2']\n",
    "plt.scatter(x,y,label='example data')\n",
    "plt.xlabel('log f [Hz]')\n",
    "plt.ylabel('log $\\epsilon$\"')\n",
    "plt.legend()\n",
    "plt.title('Example for HN fitting')"
   ]
  },
  {
   "attachments": {
    "diel_loss_plot.png": {
     "image/png": 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ANy36XPcs266bFn2uSx79QPmF9kA3DQBQi8suu0xTpkwJyHMbhqE777xTcXFxslgs2r59u0+v//XXX+uiiy5SdHS0+vfvrz179jT6edatWyeLxaJffvnFp21EwxAAg0h+oV1ZeVtld5S7HC91lCsrbyshEADCiC+DUH5+vpYsWaK33npLdrtdKSkpTW/gKbKzs9WmTRvt3LlT77//vhITE12ex9tr8RSKBw0aJLvdLqvV6tM2omEYAg4SlVWGclYVyfBwnyHJIilnVZGGJycwHAwAHph5+szu3btls9k0aNCgRl/DMAxVVlaqRQv3aLB7925dddVV6t69u/NYQkJCo54nKiqq0Y+F79ADGCQKig+59fydypBkd5SroPiQ/xoFACHC39Nnjh49qltvvVVt27aVzWbT448/7nZOXl6eBg4cqNjYWCUkJOjmm2/W/v37JUl79uzRb3/7W0nSGWecIYvFonHjxlW/lvx8XXLJJWrfvr06dOigq6++Wrt37/balnHjxunuu+9WSUmJLBaLevToIUmqqKjQ5MmTFR8fr+joaF1yySXatGmT83E1vXbvvPOOBg4cqFatWmn9+vVu17dYLNqyZYtmz54ti8WiWbNmuQwBe3st48aN00cffaSnnnpKFotFFotFe/bscestXLJkidq3b6933nlH/fr1U9u2bTVy5EjZ7f/53Z08eVKTJ092viczZszQ2LFjdc0119T7dwZXBMAgsf+w9/DXmPMAwCwCMX3mvvvu04cffqg333xT7777rtatW6ctW7a4nHP8+HE99NBD+uKLL7RixQoVFxc7Q15iYqKWL18uSdq5c6fsdrueeuopSdXhctq0adq0aZPef/99RURE6Nprr1VVVZXHtjz11FOaPXu2unbtKrvd7gx5f/rTn7R8+XK9/PLL2rp1q3r37q0rrrhChw65diT86U9/0pw5c7Rjxw6dd955bte32+0655xzdO+998put2v69Oku93t7LU899ZTS09M1YcIE2e122e12JSYmenwNx44d07x58/TKK6/o448/VklJicvzPProo3r11Vf10ksv6dNPP1VZWZlWrFjh8VqoH4aAg0R8bP1qFNX3PAAwg0BMnzly5IgWL16spUuXavjw4ZKkl19+WV27dnU57/bbb3f+/549e+rvf/+70tLSdOTIEbVt21ZxcXGSpPj4eLVv39557nXXXedyncWLFys+Pl5FRUUe5/ZZrVbFxsYqMjLSObR69OhR5ebmasmSJcrIyJAkLVq0SGvXrtXixYt13333OR8/e/Zs5+vwJCEhQS1atFDbtm2d1z9w4IDz/sjISK+vJSoqSjExMXUO+Z44cULPPfecevXqJUmaNGmSZs+e7bz/6aef1syZM3XttddKkp555hmtWbOm1muidvQABom0pDjZrNHy9ufJIslmrZ7TAgCoFojpM7t379bx48eVnp7uPBYXF6c+ffq4nLdt2zaNGjVK3bt3V2xsrC677DJJUklJSZ3Xv/nmm9WzZ0+1a9dOSUlJ9Xrc6dc4ceKELr74Yuexli1bKi0tTTt27HA5d+DAgfW+bnOJiYlxhj9JstlszuFyh8OhH3/8UWlpac77IyMjNWDAAL+3M5wQAINEZIRF2ZnJkuQWAmtuZ2cmm2ZCMwDURyCmzxiGp/5GV0ePHtWIESPUtm1b5eXladOmTXrzzTclVQ8N1yYzM1MHDx7UokWLtHHjRm3cuLFej/PUxtO31TMMw+1YmzZt6n3d5tKyZUuX2xaLxe199vRa0HgEwCAyMsWm3DGpSrC6DvMmWKOVOyZVI1NsAWoZAASnQEyf6d27t1q2bKnPP//ceeznn3/WN99847z99ddf68CBA5o7d64GDx6svn37Onu0akRFRUmSKisrnccOHjyoHTt26MEHH9TQoUPVr18//fzzz41qY1RUlD755BPnsRMnTmjz5s3q169fg69XF0+vpeb46ccaymq1qnPnziooKHAeq6ys1LZt25p0XbNjDmCQGZli0/DkBNOWMgCAhqiZPlPqKPc4D9Ci6n9E+3L6TNu2bTV+/Hjdd9996tChgzp37qwHHnjAZeuxbt26KSoqSk8//bQmTpyowsJCPfTQQy7X6d69uywWi9566y1deeWVat26tc444wx16NBBCxculM1mU0lJif785z83uI1t2rRRVlaW7rvvPsXFxalbt27629/+pmPHjmn8+PFNfg9O5+m1tG3bVj169NDGjRu1Z88el3mPDXX33Xdrzpw56t27t/r27aunn35aP//8s1uvIOqPHsAgFBlhUXqvDhrV/0yl9+pA+AMALwI1feaxxx7TpZdeqt/97ncaNmyYLrnkEpc5aZ06ddKSJUv0P//zP0pOTtbcuXM1b948l2uceeaZysnJ0Z///Gd17txZkyZNUkREhJYtW6YtW7YoJSVFU6dO1WOPPdaoNs6dO1fXXXedbrnlFqWmpurbb7/VO++8ozPOOKNJr90TT69FkqZPn67IyEglJyerU6dODZrHeKoZM2bopptu0q233qr09HS1bdtWV1xxhaKjWRjZWBaDQfRGKysrk9VqlcPhULt27QLdHAAIOeXl5SouLlZSUlKTvszzC+3KWVXksiDEZo1WdmYy02fCUFVVlfr166cbbrjBrWe1Rm2fLb6/GQIGAIQBps+Et++++07vvvuuhgwZooqKCj3zzDMqLi7WzTffHOimhSwCIAAgLNRMn0H4iYiI0JIlSzR9+nQZhqGUlBS99957zbKgxSwIgAAAIKglJibq008/DXQzwgqLQAAAAEyGHsAQVFllMM8FAAA0GgEwxLDSDUA4oiAFfI3PVO3CZgj4448/VmZmprp06SKLxaIVK1bUev66detksVjcfr7++mv/NLgR8gvtysrb6rbvZamjXFl5W5VfaA9QywCgcWq2ADt27FiAW4JwU/OZOn2bOVQLmx7Ao0eP6vzzz9dtt92m6667rt6P27lzp0sNoE6dOjVH85qssspQzqoij5XuDVUXPM1ZVaThyQkMBwMIGZGRkWrfvr1zm7SYmBh2d0CTGIahY8eOaf/+/Wrfvr0iIyMD3aSgFDYBMCMjQxkZGQ1+XHx8vNq3b+/7BvlYQfEht56/UxmS7I5yFRQfogwCgJCSkJAgSW575QJN0b59e+dnC+7CJgA21gUXXKDy8nIlJyfrwQcf1G9/+9tAN8mj/Ye9h7/GnAcAwcJischmsyk+Pl4nTpwIdHMQBlq2bEnPXx1MGwBtNpsWLlyoAQMGqKKiQq+88oqGDh2qdevW6dJLL/X4mIqKClVUVDhvl5WV+au5io+t3xZJ9T0PAIJNZGQkX9qAn5g2APbp00d9+vRx3k5PT9fevXs1b948rwFwzpw5ysnJ8VcTXaQlxclmjVapo9zjPECLpARrdUkYAACA2oTNKmBfuOiii7Rr1y6v98+cOVMOh8P5s3fvXr+1LTLCouzMZEnVYe9UNbezM5NZAAIAAOpEADzFtm3bZLN5r6XXqlUrtWvXzuXHn0am2JQ7JlUJVtdh3gRrtHLHpFIHEAAA1EvYDAEfOXJE3377rfN2cXGxtm/frri4OHXr1k0zZ87Uvn37tHTpUknS/Pnz1aNHD51zzjk6fvy48vLytHz5ci1fvjxQL6FeRqbYNDw5gZ1AAABAo4VNANy8ebPLCt5p06ZJksaOHaslS5bIbrerpKTEef/x48c1ffp07du3T61bt9Y555yj1atX68orr/R72xsqMsJCqRcAANBoFoO9UhqtrKxMVqtVDofD78PBAACgcfj+Zg4gAACA6RAAAQAATIYACAAAYDIEQAAAAJMJm1XAcFVZZVAqBgAAeEQADEP5hXblrCqS3VHuPGazRis7M5li0QAAgCHgcJNfaFdW3laX8CdJpY5yZeVtVX6hPUAtAwAAwYIAGEYqqwzlrCqSp8KONcdyVhWpsorSjwAAmBkBMIwUFB9y6/k7lSHJ7ihXQfEh/zUKAAAEHQJgGNl/2Hv4a8x5AAAgPBEAw0h8bLRPzwMAAOGJABhG0pLiZLNGy1uxF4uqVwOnJcX5s1kAACDIEADDSGSERdmZyZLkFgJrbmdnJlMPEAAAkyMAhpmRKTbljklVgtV1mDfBGq3cManUAQQAABSCDkcjU2wanpzATiAAAMAjAmCYioywKL1Xh0A3AwAABCGGgAEAAEyGAAgAAGAyBEAAAACTIQACAACYDAEQAADAZFgFbFKVVQZlYgAAMCkCoAnlF9qVs6pIdke585jNGq3szGQKRQMAYAIMAZtMfqFdWXlbXcKfJJU6ypWVt1X5hfYAtQwAAPgLAdBEKqsM5awqkuHhvppjOauKVFnl6QwAABAuCIAmUlB8yK3n71SGJLujXAXFh/zXKAAA4HcEQBPZf9h7+GvMeQAAIDQRAE0kPjbap+cBAIDQRAA0kbSkONms0fJW7MWi6tXAaUlx/mwWAADwMwKgiURGWJSdmSxJbiGw5nZ2ZjL1AAEACHMEQJMZmWJT7phUJVhdh3kTrNHKHZNKHUAAAEyAQtAmNDLFpuHJCewEAgCASREATSoywqL0Xh0C3QwAABAADAEDAACYDAEQAADAZAiAAAAAJkMABAAAMBkCIAAAgMmwChheVVYZlIoBACAMEQDhUX6hXTmrimR3lDuP2azRys5Mplg0AAAhjiFguMkvtCsrb6tL+JOkUke5svK2Kr/QHqCWAQAAXyAAwkVllaGcVUUyPNxXcyxnVZEqqzydAQAAQgEBEC4Kig+59fydypBkd5SroPiQ/xoFAAB8igAIF/sPew9/jTkPAAAEHwIgXMTHRvv0PAAAEHwIgHCRlhQnmzVa3oq9WFS9GjgtKc6fzQIAAD5EAISLyAiLsjOTJcktBNbczs5Mph4gAAAhjAAINyNTbModk6oEq+swb4I1WrljUqkDCABAiKMQNDwamWLT8OQEdgIBACAMEQDhVWSERem9OgS6GQAAwMcYAgYAADAZAiAAAIDJEAABAABMhgAIAABgMiwCQaNVVhmsEgYAIAQRANEo+YV25awqkt3xnz2BbdZoZWcmUycQAIAgxxAwGiy/0K6svK0u4U+SSh3lysrbqvxCe4BaBgAA6iNsAuDHH3+szMxMdenSRRaLRStWrKjzMR999JEGDBig6Oho9ezZU88991zzNzTEVVYZyllVJMPDfTXHclYVqbLK0xkAACAYhE0APHr0qM4//3w988wz9Tq/uLhYV155pQYPHqxt27bp/vvv1+TJk7V8+fJmbmloKyg+5NbzdypDkt1RroLiQ/5rFAAAaJCwmQOYkZGhjIyMep//3HPPqVu3bpo/f74kqV+/ftq8ebPmzZun6667rplaGfr2H/Ye/hpzHgAA8L+w6QFsqA0bNmjEiBEux6644gpt3rxZJ06c8PiYiooKlZWVufyYTXxstE/PAwAA/mfaAFhaWqrOnTu7HOvcubNOnjypAwcOeHzMnDlzZLVanT+JiYn+aGpQSUuKk80aLW/FXiyqXg2clhTnz2YBAIAGMG0AlCSLxTXGGIbh8XiNmTNnyuFwOH/27t3b7G0MNpERFmVnJkuSWwisuZ2dmUw9QAAAgphpA2BCQoJKS0tdju3fv18tWrRQhw4dPD6mVatWateuncuPGY1MsSl3TKoSrK7DvAnWaOWOSaUOIAAAQS5sFoE0VHp6ulatWuVy7N1339XAgQPVsmXLALUqdIxMsWl4cgI7gQAAEILCJgAeOXJE3377rfN2cXGxtm/frri4OHXr1k0zZ87Uvn37tHTpUknSxIkT9cwzz2jatGmaMGGCNmzYoMWLF+v1118P1EsIOZERFqX38txbCgAAglfYBMDNmzfrt7/9rfP2tGnTJEljx47VkiVLZLfbVVJS4rw/KSlJa9as0dSpU/Xss8+qS5cu+vvf/04JGAAAEPYsRs3KBzRYWVmZrFarHA6HaecDAgAQavj+NvEiEAAAALMiAAIAAJgMARAAAMBkwmYRCIJTZZVBqRgAAIIMARDNJr/QrpxVRbI7yp3HbNZoZWcmUywaAIAAYggYzSK/0K6svK0u4U+SSh3lysrbqvxCe4BaBgAACIDwucoqQzmriuSpvlDNsZxVRaqsogIRAACBQACEzxUUH3Lr+TuVIcnuKFdB8SH/NQoAADgRAOFz+w97D3+NOQ8AAPgWARA+Fx8b7dPzAACAbxEA4XNpSXGyWaPlrdiLRdWrgdOS4vzZLAAA8P8RAOFzkREWZWcmS5JbCKy5nZ2ZTD1AAAAChACIZjEyxabcMalKsLoO8yZYo5U7JpU6gAAABBCFoNFsRqbYNDw5gZ1AAAAIMgRANKvICIvSe3UIdDMAAMApGAIGAAAwGQIgAACAyRAAAQAATIYACAAAYDIEQAAAAJNhFTACqrLKoEwMAAB+RgBEwOQX2pWzqkh2R7nzmM0arezMZApFAwDQjBgCRkDkF9qVlbfVJfxJUqmjXFl5W5VfaA9QywAACH8EQPhdZZWhnFVFMjzcV3MsZ1WRKqs8nQEAAJqKAAi/Kyg+5NbzdypDkt1RroLiQ/5rFAAAJkIAhN/tP+w9/DXmPAAA0DAEQPhdfGy0T88DAAANQwCE36UlxclmjZa3Yi8WVa8GTkuK82ezAAAwDQIg/C4ywqLszGRJcguBNbezM5OpBwgAQDMhACIgRqbYlDsmVQlW12HeBGu0csekUgcQAIBmRCFoBMzIFJuGJyewEwgAAH5GAERARUZYlN6rQ6CbAQCAqTAEDAAAYDIEQAAAAJMhAAIAAJgMARAAAMBkWASCoFdZZbBSGAAAHyIAIqjlF9qVs6pIdsd/9gW2WaOVnZlMrUAAABqJIWAErfxCu7LytrqEP0kqdZQrK2+r8gvtAWoZAAChjQCIoFRZZShnVZEMD/fVHMtZVaTKKk9nAACA2hAAEZQKig+59fydypBkd5SroPiQ/xoFAECYIAAiKO0/7D38NeY8AADwHwRABKX42GifngcAAP6DAIiglJYUJ5s1Wt6KvVhUvRo4LSnOn80CACAsEAARlCIjLMrOTJYktxBYczs7M5l6gAAANAIBEEFrZIpNuWNSlWB1HeZNsEYrd0wqdQABAGgkCkEjqI1MsWl4cgI7gQAA4EMEQAS9yAiL0nt1CHQzAAAIGwwBAwAAmAwBEAAAwGQIgAAAACZDAAQAADAZAiAAAIDJEAABAABMhjIwCHmVVQZ1AgEAaAACIEJafqFdOauKZHeUO4/ZrNHKzkxmpxAAALwIqyHgBQsWKCkpSdHR0RowYIDWr1/v9dx169bJYrG4/Xz99dd+bDGaIr/Qrqy8rS7hT5JKHeXKytuq/EJ7gFoGAEBwa1IPYElJicvtbt26NakxTfHGG29oypQpWrBggS6++GI9//zzysjIUFFRUa3t2rlzp9q1a+e83alTJ380F01UWWUoZ1WRDA/3GZIsknJWFWl4cgLDwQAAnKZJPYA9evRQUlKS838D6YknntD48eN1xx13qF+/fpo/f74SExOVm5tb6+Pi4+OVkJDg/ImMjPRTi9EUBcWH3Hr+TmVIsjvKVVB8yH+NAgAgRDQpAFZVVamystL5v4Fy/PhxbdmyRSNGjHA5PmLECH322We1PvaCCy6QzWbT0KFD9eGHH9Z6bkVFhcrKylx+EBj7D3sPf405DwAAM2nSEPDs2bNdbv/3f/93kxrTWAcOHFBlZaU6d+7scrxz584qLS31+BibzaaFCxdqwIABqqio0CuvvKKhQ4dq3bp1uvTSSz0+Zs6cOcrJyfF5+9Fw8bHRPj0PAAAzaVIALC4u9lU7fMJicZ3rZRiG27Eaffr0UZ8+fZy309PTtXfvXs2bN89rAJw5c6amTZvmvF1WVqbExEQftBwNlZYUJ5s1WqWOco/zAC2SEqzVJWEAAICrJgXAl156yVftaJKOHTsqMjLSrbdv//79br2CtbnooouUl5fn9f5WrVqpVatWjW4nfCcywqLszGRl5W2VRXIJgTWRPzszmQUgAAB4EBZlYKKiojRgwACtXbvW5fjatWs1aNCgel9n27ZtstmoHRcqRqbYlDsmVQlW12HeBGu0csekUgcQAAAvfFIIetiwYbr33nuVkZHhcryystJvq2qnTZumW265RQMHDlR6eroWLlyokpISTZw4UVL18O2+ffu0dOlSSdL8+fPVo0cPnXPOOTp+/Ljy8vK0fPlyLV++3C/thW+MTLFpeHICO4EAANAAPgmAmzdvVo8ePSRVzwusKQmzePFirV+/Xq+88oovnqZWo0eP1sGDBzV79mzZ7XalpKRozZo16t69uyTJbre71C08fvy4pk+frn379ql169Y655xztHr1al155ZXN3lb4VmSERem9OgS6GQAAhAyLYRie5tA3SExMjL755ht17dpV7dq10/bt29WzZ08VFhZqxIgR+uGHH3zR1qBTVlYmq9Uqh8PhUkwaAAAEL76/fdQD2Lt3b23cuFGxsbE6evSofvnlF0lSbGysDh2iEC8AAEAw8ckikD/+8Y+64447NGTIEJ1//vlauHChJGn9+vUNWoULAACA5ueTHsCJEyeqU6dO2rVrlyZMmKAbb7xRPXv2lN1u16RJk3zxFAAAAPARn8wBPN3Jkyf15ptv6vjx47rxxhvDdn9d5hAAABB6+P72UQ+g20VbtND111/fHJcGGqWyyqBUDAAA/1+zBEAgmOQX2pWzqkh2R7nzmM0arezMZIpFAwBMKSx2AgG8yS+0Kytvq0v4k6RSR7my8rYqv9AeoJYBABA4BECErcoqQzmriuRpkmvNsZxVRaqs8vk0WAAAghoBEGGroPiQW8/fqQxJdke5CoqpVQkAMBefzAGcNm2ax+MWi0XR0dHq3bu3Ro0apbi4OF88HVAv+w97D3+NOQ8AgHDhkwC4bds2bd26VZWVlerTp48Mw9CuXbsUGRmpvn37asGCBbr33nv1ySefKDk52RdPCdQpPjbap+cBABAufDIEPGrUKA0bNkw//PCDtmzZoq1bt2rfvn0aPny4brrpJu3bt0+XXnqppk6d6ounA+olLSlONmu0vBV7sah6NXBaEj3TAABz8Ukh6DPPPFNr165169376quvNGLECO3bt09bt27ViBEjdODAgaY+XdCgkGTwq1kFLMllMUhNKMwdk0opGAAwGb6/fdQD6HA4tH//frfjP/30k8rKyiRJ7du31/Hjx33xdEC9jUyxKXdMqhKsrsO8CdZowh8AwLR8Mgdw1KhRuv322/X444/rN7/5jSwWiwoKCjR9+nRdc801kqSCggKdffbZvng6oEFGptg0PDmBnUAAAPj/fDIEfOTIEU2dOlVLly7VyZMnJVVvBzd27Fg9+eSTatOmjbZv3y5J6t+/f1OfLmjQhQwAQOjh+9tHAbDGkSNH9O9//1uGYahXr15q27atry4dlPgAAQAQevj+9vFewG3bttV5553ny0sCAADAx3wWAH/55RctXrxYO3bskMViUb9+/TR+/HhZrVZfPQUAAAB8wCergDdv3qxevXrpySef1KFDh3TgwAE9+eST6tWrl7Zu3eqLpwAAAICP+GQO4ODBg9W7d28tWrRILVpUdyqePHlSd9xxh/7973/r448/bnJDgxFzCAAACD18f/soALZu3Vrbtm1T3759XY4XFRVp4MCBOnbsWFOfIijxAQoflVUGZWIAwCT4/vbRHMB27dqppKTELQDu3btXsbGxvngKoNnkF9qVs6pIdke585jNGq3szGQKRQMAwpJP5gCOHj1a48eP1xtvvKG9e/fq+++/17Jly3THHXfopptu8sVTAM2iZqu4U8OfJJU6ypWVt1X5hfYAtQwAgObjkx7AefPmyWKx6NZbb9XJkydlGIaioqKUlZWluXPn+uIpAJ+rrDKUs6pInuZAGKreLzhnVZGGJycwHAwACCs+LQR97Ngx7d69W4ZhqHfv3oqJifHVpYMScwhC24bdB3XTos/rPO/1CRcpvVcHP7QIAOAPfH83oQdw2rRp9T73iSeeaOzTAM1m/+Hyuk9qwHkAAISKRgfAbdu21es8i4WhMwSn+Nhon54HAECoaHQA/PDDD33ZDsDv0pLiZLNGq9RR7nEeoEVSgrW6JAwAAOHEJ6uAgVAUGWFRdmaypOqwd6qa29mZySwAAQCEHQIgTG1kik25Y1KVYHUd5k2wRit3TCp1AAEAYcknZWCAUDYyxabhyQnsBAIAMA0CIKDq4WBKvQAAzIIhYAAAAJMhAAIAAJgMARAAAMBkCIAAAAAmQwAEAAAwGVYBA/VUWWVQKgYAEBYIgEA95BfalbOqSHZHufOYzRqt7MxkikUDAEIOQ8BAHfIL7crK2+oS/iSp1FGurLytyi+0B6hlAAA0DgEQqEVllaGcVUUyPNxXcyxnVZEqqzydAQBAcCIAArUoKD7k1vN3KkOS3VGuguJD/msUAABNRAAEarH/sPfw15jzAAAIBgRAoBbxsdE+PQ8AgGBAAARqkZYUJ5s1Wt6KvVhUvRo4LSnOn80CAKBJCIBALSIjLMrOTJYktxBYczs7M5l6gACAkEIABOowMsWm3DGpSrC6DvMmWKOVOyaVOoAAgJBDIWigHkam2DQ8OYGdQAAAYYEACNRTZIRF6b06BLoZAAA0GUPAAAAAJkMABAAAMBkCIAAAgMkQAAEAAEyGAAgAAGAyrAIGfKSyyqBMDAAgJIRVD+CCBQuUlJSk6OhoDRgwQOvXr6/1/I8++kgDBgxQdHS0evbsqeeee85PLUW4yS+065JHP9BNiz7XPcu266ZFn+uSRz9QfqE90E0DAMBN2ATAN954Q1OmTNEDDzygbdu2afDgwcrIyFBJSYnH84uLi3XllVdq8ODB2rZtm+6//35NnjxZy5cv93PLEeryC+3Kytsqu6Pc5Xipo1xZeVsJgQCAoGMxDMMIdCN84cILL1Rqaqpyc3Odx/r166drrrlGc+bMcTt/xowZWrlypXbs2OE8NnHiRH3xxRfasGFDvZ6zrKxMVqtVDodD7dq1a/qLQMiprDJ0yaMfuIW/GhZVbxn3yYzLGQ4GgCDB93eY9AAeP35cW7Zs0YgRI1yOjxgxQp999pnHx2zYsMHt/CuuuEKbN2/WiRMnmq2tCC8FxYe8hj9JMiTZHeUqKD7kv0YBAFCHsFgEcuDAAVVWVqpz584uxzt37qzS0lKPjyktLfV4/smTJ3XgwAHZbDa3x1RUVKiiosJ5u6yszAetRyjbf9h7+GvMeQAA+ENY9ADWsFhch9gMw3A7Vtf5no7XmDNnjqxWq/MnMTGxiS1GqIuPjfbpeQAA+ENYBMCOHTsqMjLSrbdv//79br18NRISEjye36JFC3Xo0MHjY2bOnCmHw+H82bt3r29eAEJWWlKcbNZoeftnhkWSzVpdEgYAgGARFgEwKipKAwYM0Nq1a12Or127VoMGDfL4mPT0dLfz3333XQ0cOFAtW7b0+JhWrVqpXbt2Lj8wt8gIi7IzkyXJLQTW3M7OTGYBCAAgqIRFAJSkadOm6YUXXtCLL76oHTt2aOrUqSopKdHEiRMlVffe3Xrrrc7zJ06cqO+++07Tpk3Tjh079OKLL2rx4sWaPn16oF4CQtTIFJtyx6Qqweo6zJtgjVbumFSNTHGfTwoAQCCFxSIQSRo9erQOHjyo2bNny263KyUlRWvWrFH37t0lSXa73aUmYFJSktasWaOpU6fq2WefVZcuXfT3v/9d1113XaBeAkLYyBSbhicnsBMIACAkhE0dwECgjhAAAKGH7+8wGgIGAABA/RAAAQAATIYACAAAYDIEQAAAAJMJm1XAQCiorDJYKQwACDgCIOAn+YV25awqkt3xn32BbdZoZWcmUysQAOBXDAEDfpBfaFdW3laX8CdJpY5yZeVtVX6hPUAtAwCYEQEQaGaVVYZyVhXJU8HNmmM5q4pUWUVJTgCAfxAAgWZWUHzIrefvVIYku6NcBcWH/NcoAICpEQCBZrb/sPfw15jzAABoKgIg0MziY6N9eh4AAE1FAASaWVpSnGzWaHkr9mJR9WrgtKQ4fzYLAGBiBECgmUVGWJSdmSxJbiGw5nZ2ZjL1AAEAfkMABPxgZIpNuWNSlWB1HeZNsEYrd0wqdQABAH5FIWjAT0am2DQ8OYGdQAAAAUcABPwoMsKi9F4dAt0MIODqsy1iXeewtSLQeARAAIDP1RbO6rMtYl3nsLUi0DQWwzDYfqCRysrKZLVa5XA41K5du0A3BwCCQm3hTJKy8ra67YxT02+XOya1znPuvDRJCz8urvUaNSGQXkJ4wvc3AbBJ+AABMKO6evdqC2/WmJb65dgJj9e1qHphlGEYKi2r8HqOxSJ52zmx5hqfzLhca4tK6SWER3x/EwCbhA8QALOprXdveHKCLnn0g1q3PvSXqcPO0vz3dtXZS0gPoTnx/c0cQABAPXnr3St1lCsrb6umDDs7KMKfJL306R63dkrVe29bJOWsKlJVlaGHVu+ghxCmRA9gE/AvCPgavREIBp4+h5Jq7d2zqPbh3VDBPEJz4PubHkAgaLCqEcHA2+fwxt90q7V3z5CaHP5OnQP4Y1mFxx68+swBbEoQPbWHcHhyAvMIEbbYCQQIAjVDa6d/wdYMreUX2gPUMphJbZ/DJ9/7pl7XaN+6Za37Xp8R09L5/0+/T6reFnHW786p9ZwJg5Oqg6CX+28blFSvtnpjSLI7yvXMB7v47xJhiwAIBFhllaGcVUVe5ytJ1b0Rld66PAAfqM/nsD5uu7iHJO/hbM7vz9VzdWyLWNfWiTOvTK71/kmX95bNGu01iNZXbfMIpf/8d1lZZWjD7oP61/Z92rD7IP+tIiQwBAwEWEHxoTqH1uyOchUUH2IXETSbuj6HdakZvp10+VnqkxDrNmyacNqwaV3bIta1dWJd92dnJisrb6sscg2wp9+uzS+/eh9GPrWXcNmmvQwRI+QQAIEA23+4fl+69T0PqI23BQ0N+Xx5ClVSdeiKjLDUa9/r+myLWNc5td1f04voKYj+5apkPbS6SKWOcq/zDOs7j/DJ93a5HasZIj51IQkQbAiAQIDFx0bXfVIDzgO8qW2hUX0/X1OHneXW43V6754UHPte1xZEIyLktYdQqp5HWN95j6c7fSEJK4YRjAiAQIClJcXJZo2utTciwfqfUhxAY9RVw+/Zm1Pr9TmcdPlZmnT5WSFTFsVbEK2th7CmqPWyTSVe34+6nD51g1IyCDbUAWwC6gjBV2q+nCXPvREMJaEpKquMOmv4VQ+N9tNdr22TZJ7PYX22tZMaP4/wqRv7q1WLCErJBBm+v1kFDASFulY98iWBpqjvQqMz2rQy3eewpodwVP8zld6rg9tCFG/vx9RhZ9fr+nsOHKWUDIISQ8BAkKjPxHmgMRqy0GhU/zP5HJ7C23+XkmodIq7pVX29oKTOLemGJydIEu85/IoACASRYJg4j9DmaUizoQuN+By68vZ+1FZqRpJu/E23WheSUEoGgUQABIAw4W2V71+uSmahUTOoayFJxcmqel2HUjIIBAIgAISB2lb53vXaVt15aZIWflxcZw0/NExtUzc27D7Y6OtSSgbNjUUgABDi6rON28ov7Hr25gtMtcDDX7wtJKkp8dTY6HZqKRlJbDkHn6IHEABCXENW+X4y43IWG/hJZITFJ1vS7T9cXmsRb8I7GoMeQCDE0AuA0zVklW9tZU/ge5SSQbCiBxAIIfQCwBO2EwxulJJBMCIAAiGirq28mMcV/rztWsF2gsGPUjIINmwF1wRsJQN/qe9WXp/MuJx/8Yepunp/2U4wdNX2u604WaV7lm1v1HX53XvH9zc9gEBIqO8k/5qN5xFe6tv7W1tNOgJA8PJnKZna9j6GuRAAgRDQkEn+CC91lXg59Que7QRDl7ch4rqG9+ty6j8OHb8eZw4xnFgFDIQAJvmbV0N6fyXvNekQmmpKyUhyqyfYkN/se0WlrCSGCwIgEALqKihrUfW/5JnkH37o/YUvSsm8uX1frYXCc1YVUVLKZBgCBkJAXQVlJbbyClf0/kJqWimZuDZROnj0uNdrn9qLnJYUxxQCkyAAAiGCSf7mRIkX1GhsKZlR/bvoxU/31Hn994pKNe0f25kjaBKUgWkClpEjEFjFF768/W4p8YK61FZKxto6Sjct+rxR1/X0GQuHv0F8fxMAm4QPEABfqU+dP1ZwojbegllNHdHaepEtFsnbFMBT64yuLSoNi88h398EwCbhAwTAF7zV+Tu99yUcel4QGLX1Itc3BEwddpbmv7erzs9pKOD7m1XAABBQddX5k/6zQpMSL2is2lYS335xj3pd46VP99Trc1pZZWjD7oP61/Z92rD7IKuLgxSLQAAggNjlBf7ibSVxQfGhei0S+eXXE17vY0/i0EMABIAAos4f/MnTSuL6rDS3xrTUL8e8B8AaT763y+3Y6VsWSuGxkCTUEQCBMMMf1tBCnT8EWn3qjN42KElPvvdNo65/+paF9VlIwt+x5kcABMIIK0VDD3X+EAzqqjM6PDmh1oLTdTl1iNjTQpJTewkl8XfMD1gF3ASsIkIwqe9KUgQf6vwhWNTW8+aLlcTtW7f0OpfQIql9TEv97GGo2df/LfD9HSargH/++WfdcsstslqtslqtuuWWW/TLL7/U+phx48bJYrG4/Fx00UX+aTDgYw1ZSYrAqG1lZG0rNAl/8KfaVpr7Yk/iuhaSeAp/NfdJ/B3zpbAYAr755pv1/fffKz8/X5J055136pZbbtGqVatqfdzIkSP10ksvOW9HRUU1azuB5sJK0uBWn6F5bys0mfeEYNKUPYnru5DEG/6O+VbIB8AdO3YoPz9fn3/+uS688EJJ0qJFi5Senq6dO3eqT58+Xh/bqlUrJSQk+KupQLNhJWnw8jY072llpLe9XoFg0tg9iZuykORU/B3zjZAfAt6wYYOsVqsz/EnSRRddJKvVqs8++6zWx65bt07x8fE6++yzNWHCBO3fv7+5mws0C1aSBieG5mEmdU1lmHR5b9ms0WpqnzZ/x3wj5HsAS0tLFR8f73Y8Pj5epaWlXh+XkZGh66+/Xt27d1dxcbH+8pe/6PLLL9eWLVvUqlUrj4+pqKhQRUWF83ZZWVnTXwDgA6wkDU4MzcNs6prKUFcvoTWmpRzHTvB3zA+Ctgdw1qxZbos0Tv/ZvHmzJMlicf/3hGEYHo/XGD16tK666iqlpKQoMzNTb7/9tr755hutXr3a62PmzJnjXGhitVqVmJjY9BcK+EBNHS9Jbv+6rrmdnZnMfDI/Y2geZtTYhSS5Y1I19/fnSuLvmD8EbQ/gpEmTdOONN9Z6To8ePfR///d/+vHHH93u++mnn9S5c+d6P5/NZlP37t21a5d7FfMaM2fO1LRp05y3y8rKCIEIGnXV8WIlqf8xNA+4q6uXkL9j/hG0AbBjx47q2LFjneelp6fL4XCooKBAaWlpkqSNGzfK4XBo0KBB9X6+gwcPau/evbLZvH+4WrVq5XV4GAgGrCQNLgzNA57VtuCJv2P+ERaFoDMyMvTDDz/o+eefl1RdBqZ79+4uZWD69u2rOXPm6Nprr9WRI0c0a9YsXXfddbLZbNqzZ4/uv/9+lZSUaMeOHYqNja3X81JIEkBdKPIMBB++v4N4DmBDvPrqqzr33HM1YsQIjRgxQuedd55eeeUVl3N27twph8MhSYqMjNSXX36pUaNG6eyzz9bYsWN19tlna8OGDfUOfwBwKm+FninyDCAYhUUPYKDwLwgAUv0KPbO5PRA8+P4mADYJHyAA7MEMhB6+v8NkCBhAw9S2Ly3qj0LPAEJV0K4CBtA86jNcifqh0DOAUEUPIGAiNcOVp4eWmn1p8wvtAWpZaKLQM4BQRQAETILhSt+j0DOAUEUABEyiIcOVqJ+aQs/e1vJaVD28TqFnAMGGAAiYBMOVvscezABCFQEQMAmGK5sHhZ4BhCJWAQMmwb60jVdXEWf2LgUQagiAgEnUDFdm5W2VRZ73pWW40l19y+bUtrk9AAQbhoABE2G4smEomwMgXNEDCJgMw5X1U1fZHIuqy+YMT07gvQMQcgiAgAkxXFk3dvkAEM4YAgYADyibAyCc0QMIwE1dq17NgLI5AMIZARCAi/queg13lM0BEM4YAgbgxKrX/2CXDwDhjAAIQFLdq16l6lWvlVWezghPlM0BEK4YAgYgydyrXmub80jZHADhiAAIQJJ5V73WZ84jZXMAhBuGgAFIMueqV+Y8AjArAiAASf9Z9eptYNOi6p6xcFn1ypxHAGZGAAQgyXyrXhsy5xEAwg0BEICTmVa9mnXOIwBILAIBcBqzrHo145xHAKhBAATgpj6rXkN9uzh2+gBgZgRAAA0WStvFeQuqNXMes/K2yiK5hMBwnPMIAKeyGIbBErdGKisrk9VqlcPhULt27QLdHMAvakqnnP6HoyYmBdNcwfoE1VAKswB8g+9vAmCT8AGC2VRWGbrk0Q+8rp6tGTb9ZMblAe85a0hQDfXhbAANw/c3Q8AAGiBUtourq8afRdU1/oYnJziHg9npA4CZUAYGQL2FSukUavwBQO0IgADqLVRKp4RKUAWAQGEIGEC9NaR0SiDn1YVKUAWAQCEAAqi3+pZOWVtU6reVtZ6CJjX+AKB2rAJuAlYRwaxqK50iyW9lYurTDslzUA2mcjUA/IvvbwJgk/ABgpl56nmT5LcyMfUp8yKJGn8A3PD9zRAwgEbyVDplw+6DfikTU98yL5/MuNwU+xoDQEMRAAH4TENX39a1UMTb/Q2tR0iNPwBwRQAE4DMNWX1b1xZstd1fcbKqXs9DmRcA8Iw6gAB8pmb1rbcBVouqQ9zPRyuUlbfVrRev1FGurLytmrOmqNb79xw4Vq/2UOYFADwjAALwmZoyMZLcQmDN7b9clayHVu/wOn9PkhatL671/mWbSpTQrlWdQZMyLwDgGQEQgE+NTLEpd0yqEqyuvW8J1mjljknVGW2i6py/V1VLbYKa+X03pXWT5D1oZmcms9gDALxgDiAAnxuZYvO6+vZf2/f55Dl6dGyj3DGpbvMEEyjzAgB1IgACaBaeysRIvpuXFx8brfReHSjzAgCNQAAE4Ff12abNYvE+DHz6Nm7egiYAwDvmAALwq/osFJkwOKk6CHq5n/l9ANA0BEAAflfXQpGZVybXej/z+wCgadgLuAnYSxBomsbuBAIATcH3N3MAAQRQXfP3mN8HAM2DIWAAAACTIQACAACYDAEQAADAZAiAAAAAJkMABAAAMBkCIAAAgMkQAAEAAEyGAAgAAGAyBEAAAACTYSeQJqjZRa+srCzALQEAAPVV871t5t1wCYBNcPjwYUlSYmJigFsCAAAa6vDhw7JarYFuRkBYDDPH3yaqqqrSDz/8oNjYWFksvt2gvqysTImJidq7d69pN6rmPajG+1CN96Ea70M13odqvA/VGvo+GIahw4cPq0uXLoqIMOdsOHoAmyAiIkJdu3Zt1udo166dqf+jlngPavA+VON9qMb7UI33oRrvQ7WGvA9m7fmrYc7YCwAAYGIEQAAAAJMhAAapVq1aKTs7W61atQp0UwKG96Aa70M13odqvA/VeB+q8T5U431oOBaBAAAAmAw9gAAAACZDAAQAADAZAiAAAIDJEAABAABMhgAYAh555BENGjRIMTExat++faCb4zcLFixQUlKSoqOjNWDAAK1fvz7QTfK7jz/+WJmZmerSpYssFotWrFgR6Cb53Zw5c/Sb3/xGsbGxio+P1zXXXKOdO3cGull+l5ubq/POO89Z6DY9PV1vv/12oJsVUHPmzJHFYtGUKVMC3RS/mzVrliwWi8tPQkJCoJsVEPv27dOYMWPUoUMHxcTEqH///tqyZUugmxX0CIAh4Pjx47r++uuVlZUV6Kb4zRtvvKEpU6bogQce0LZt2zR48GBlZGSopKQk0E3zq6NHj+r888/XM888E+imBMxHH32ku+66S59//rnWrl2rkydPasSIETp69Gigm+ZXXbt21dy5c7V582Zt3rxZl19+uUaNGqWvvvoq0E0LiE2bNmnhwoU677zzAt2UgDnnnHNkt9udP19++WWgm+R3P//8sy6++GK1bNlSb7/9toqKivT444+bqrOksSgDE0KWLFmiKVOm6Jdffgl0U5rdhRdeqNTUVOXm5jqP9evXT9dcc43mzJkTwJYFjsVi0Ztvvqlrrrkm0E0JqJ9++knx8fH66KOPdOmllwa6OQEVFxenxx57TOPHjw90U/zqyJEjSk1N1YIFC/Twww+rf//+mj9/fqCb5VezZs3SihUrtH379kA3JaD+/Oc/69NPPzXlCFFT0QOIoHP8+HFt2bJFI0aMcDk+YsQIffbZZwFqFYKFw+GQVB1+zKqyslLLli3T0aNHlZ6eHujm+N1dd92lq666SsOGDQt0UwJq165d6tKli5KSknTjjTfq3//+d6Cb5HcrV67UwIEDdf311ys+Pl4XXHCBFi1aFOhmhQQCIILOgQMHVFlZqc6dO7sc79y5s0pLSwPUKgQDwzA0bdo0XXLJJUpJSQl0c/zuyy+/VNu2bdWqVStNnDhRb775ppKTkwPdLL9atmyZtmzZYtqRgBoXXnihli5dqnfeeUeLFi1SaWmpBg0apIMHDwa6aX7173//W7m5uTrrrLP0zjvvaOLEiZo8ebKWLl0a6KYFPQJggHiawHv6z+bNmwPdzICyWCwutw3DcDsGc5k0aZL+7//+T6+//nqgmxIQffr00fbt2/X5558rKytLY8eOVVFRUaCb5Td79+7VPffco1dffVXR0dGBbk5AZWRk6LrrrtO5556rYcOGafXq1ZKkl19+OcAt86+qqiqlpqbqr3/9qy644AL913/9lyZMmOAyfQietQh0A8xq0qRJuvHGG2s9p0ePHv5pTJDp2LGjIiMj3Xr79u/f79YrCPO4++67tXLlSn388cfq2rVroJsTEFFRUerdu7ckaeDAgdq0aZOeeuopPf/88wFumX9s2bJF+/fv14ABA5zHKisr9fHHH+uZZ55RRUWFIiMjA9jCwGnTpo3OPfdc7dq1K9BN8SubzebWC96vXz8tX748QC0KHQTAAOnYsaM6duwY6GYEpaioKA0YMEBr167Vtdde6zy+du1ajRo1KoAtQyAYhqG7775bb775ptatW6ekpKRANyloGIahioqKQDfDb4YOHeq20vW2225T3759NWPGDNOGP0mqqKjQjh07NHjw4EA3xa8uvvhit7JQ33zzjbp37x6gFoUOAmAIKCkp0aFDh1RSUqLKykrnqq/evXurbdu2gW1cM5k2bZpuueUWDRw4UOnp6Vq4cKFKSko0ceLEQDfNr44cOaJvv/3Webu4uFjbt29XXFycunXrFsCW+c9dd92l1157Tf/6178UGxvr7Bm2Wq1q3bp1gFvnP/fff78yMjKUmJiow4cPa9myZVq3bp3y8/MD3TS/iY2NdZv72aZNG3Xo0MF0c0KnT5+uzMxMdevWTfv379fDDz+ssrIyjR07NtBN86upU6dq0KBB+utf/6obbrhBBQUFWrhwoRYuXBjopgU/A0Fv7NixhiS3nw8//DDQTWtWzz77rNG9e3cjKirKSE1NNT766KNAN8nvPvzwQ4+/+7Fjxwa6aX7j6fVLMl566aVAN82vbr/9dud/D506dTKGDh1qvPvuu4FuVsANGTLEuOeeewLdDL8bPXq0YbPZjJYtWxpdunQxfv/73xtfffVVoJsVEKtWrTJSUlKMVq1aGX379jUWLlwY6CaFBOoAAgAAmAyrgAEAAEyGAAgAAGAyBEAAAACTIQACAACYDAEQAADAZAiAAAAAJkMABAAAMBkCIICgdtlll2nKlCnN/jxff/21LrroIkVHR6t///5e22KxWGSxWJw78vjKkiVLnNf2x+sFYG4EQACQlJ2drTZt2mjnzp16//33vZ43YcIE2e1259Zje/bs8RoIGxJeR48eLbvdrvT09MY0HwAahL2AAUDS7t27ddVVV9W5iXxMTIwSEhJ8/vytW7dW69atFRUV5fNrA8Dp6AEEEFJ+/vln3XrrrTrjjDMUExOjjIwM7dq1y+WcRYsWKTExUTExMbr22mv1xBNPqH379l6vabFYtGXLFs2ePVsWi0WzZs3yebvXrVvnHOI99WfcuHE+fy4AqAsBEEBIGTdunDZv3qyVK1dqw4YNMgxDV155pU6cOCFJ+vTTTzVx4kTdc8892r59u4YPH65HHnmk1mva7Xadc845uvfee2W32zV9+nSft3vQoEGy2+3Onw8++EDR0dG69NJLff5cAFAXhoABhIxdu3Zp5cqV+vTTTzVo0CBJ0quvvqrExEStWLFC119/vZ5++mllZGQ4Q9zZZ5+tzz77TG+99ZbX6yYkJKhFixZq27Zto4d3Bw0apIgI139T//rrr84FJVFRUc5rHzx4UBMmTNDtt9+u22+/vVHPBwBNQQAEEDJ27NihFi1a6MILL3Qe69Chg/r06aMdO3ZIknbu3Klrr73W5XFpaWm1BkBfeOONN9SvXz+XY3/4wx/czjtx4oSuu+46devWTU899VSztgkAvCEAAggZhmF4PW6xWNz+f12P86XExET17t3b5Vjr1q3dzsvKylJJSYk2bdqkFi34EwwgMJgDCCBkJCcn6+TJk9q4caPz2MGDB/XNN984e9/69u2rgoICl8dt3rzZr+305oknntAbb7yhlStXqkOHDoFuDgATIwACCBlnnXWWRo0apQkTJuiTTz7RF198oTFjxujMM8/UqFGjJEl333231qxZoyeeeEK7du3S888/r7ffftutV9Df3nvvPf3pT3/SvHnz1LFjR5WWlqq0tFQOhyOg7QJgTgRAACHlpZde0oABA3T11VcrPT1dhmFozZo1atmypSTp4osv1nPPPacnnnhC559/vvLz8zV16lRFR0cHtN2ffPKJKisrNXHiRNlsNufPPffcE9B2ATAni+GPyTEAEEATJkzQ119/rfXr1zfpOpdddpn69++v+fPn+6ZhAXoOAKAHEEDYmTdvnr744gt9++23evrpp/Xyyy9r7NixPrn2ggUL1LZtW3355Zc+uV6NV199VW3btm1ySAWA+qAHEEDYueGGG7Ru3TodPnxYPXv21N13362JEyc2+br79u3Tr7/+Kknq1q2bT7dtO3z4sH788UdJUvv27dWxY0efXRsATkcABAAAMBmGgAEAAEyGAAgAAGAyBEAAAACTIQACAACYDAEQAADAZAiAAAAAJkMABAAAMBkCIAAAgMkQAAEAAEzm/wEFiiPtQhG2RgAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "id": "d83dbfb3",
   "metadata": {},
   "source": [
    "![diel_loss_plot.png](attachment:diel_loss_plot.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b27545c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# instantiate the HN module\n",
    "hn = dd.HN()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be4655a1",
   "metadata": {},
   "source": [
    "**Select the region of interest (ROI) to fit the data using the select range method**. \n",
    ">The data in ROI is shown as image in the following cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2691ec1d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_lower_limit 2.5234707551868087 x_upper_limit 4.4693345833813005\n"
     ]
    }
   ],
   "source": [
    "#select range\n",
    "hn = dd.HN()\n",
    "x1,y1 = hn.select_range(x,y)"
   ]
  },
  {
   "attachments": {
    "ROI.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "6f48e461",
   "metadata": {},
   "source": [
    "**Plot of the ROI to fit the HN function**\n",
    "![ROI.png](attachment:ROI.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "348838d2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "enter the beta value:0.5\n",
      "enter the gamma value:1\n",
      "enter the fm:3.75\n",
      "enter the deps:0.5\n",
      "enter the cond:0\n",
      "enter the s:1\n",
      "dumped_parameters {'beta': 0.5, 'gamma': 1.0, 'freq': 5623.413251903491, 'deps': 0.5, 'cond': 0.0, 'n': 1.0}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dump the initial guess parameters using dump parameters method (varies for each fn), which dumps the parameters in a json file'\n",
    "#this is required before performing the first fitting as it takes the initial guess from the json file created\n",
    "\n",
    "hn.dump_parameters_hn()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "86b183cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loaded parameters \n",
      " {'beta': 0.5, 'gamma': 1.0, 'freq': 5623.413251903491, 'deps': 0.5, 'cond': 0.0, 'n': 1.0}\n"
     ]
    }
   ],
   "source": [
    "# view the initial fit based on the dumped parameters\n",
    "# the plot is shown as a image in the next cell\n",
    "\n",
    "hn.initial_view_hn(x1,y1)"
   ]
  },
  {
   "attachments": {
    "initial_guess.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "18257209",
   "metadata": {},
   "source": [
    "**Plot of the initial fit based on the supplied parameters**\n",
    "\n",
    "![initial_guess.png](attachment:initial_guess.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "5cf8aed0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Choose the fit function\n",
      " 1 -- HN, 2 -- HN with cond, 3 -- Hn-flank, 4 -- double HN, 5 -- double HN with cond:1\n",
      "0.7326563571608663 0.34641197051059136 1945.8637251236246 3.2548369440810547\n",
      "log fmax: 3.8521833734663224\n",
      "fit parameters dumped for next iteration {'beta': 0.7326563571608663, 'gamma': 0.34641197051059136, 'freq': 1945.8637251236246, 'deps': 3.2548369440810547, 'cond': 0, 'n': 0}\n"
     ]
    }
   ],
   "source": [
    "# perform least squares fitting\n",
    "# the plot is shown as a image in the next cell\n",
    "\n",
    "hn.fit(x1,y1)"
   ]
  },
  {
   "attachments": {
    "fit_example.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "9aec0e05",
   "metadata": {},
   "source": [
    "**Plot of the final fit of the HN function to the data**\n",
    "\n",
    "![fit_example.png](attachment:fit_example.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37ab42fa",
   "metadata": {},
   "source": [
    "**An analysis file has to be created only once during the whole run (i.e. all fit runs can be saved in the same file, unless you change the function or require saving separate processes in separate files.)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a9788ce9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Do you want to use an existing file to save fit results? \n",
      " eg: existing file to save HN parameters, y or n:n\n",
      "Choose the fit function\n",
      " 1 -- HN, 2 -- HN with cond, 3 -- HN-flank, 4 -- double HN, 5 -- double HN with cond:1\n",
      "Enter the analysis_file_name:hn_fit.TXT\n",
      "file did not exist, created hn_fit.TXT\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# before saving fit results an analysis file has to be created using create_analysis file method\n",
    "\n",
    "hn.create_analysis_file()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "010155cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#save the fit results using save_fit method of the corresponding fit function\n",
    "#takes one argument, read more on the documentation\n",
    "\n",
    "hn.save_fit_hn(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a09f3a0f",
   "metadata": {},
   "source": [
    "## HN function together with conductivity contribution.\n",
    "**We will use the same data set but will include the conductivity slope and analyze the data.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "759995ed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_lower_limit 1.0824713571766393 x_upper_limit 4.495941541576136\n"
     ]
    }
   ],
   "source": [
    "#select range\n",
    "# select peak along with conductivity slope\n",
    "hn = dd.HN()\n",
    "x1,y1 = hn.select_range(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ce974539",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Example for fitting HN with conducitivity')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# view the selected data\n",
    "plt.scatter(x1,y1,label='example data')\n",
    "plt.xlabel('log f [Hz]')\n",
    "plt.ylabel('log $\\epsilon$\"')\n",
    "plt.legend()\n",
    "plt.title('Example for fitting HN with conducitivity')\n"
   ]
  },
  {
   "attachments": {
    "diel_loss_cond_plot.png": {
     "image/png": 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GNc8+552jt3a7XRaLRZLcRhml0+f+0aNH5XA43ELg1q1bderUKY9/4DtT06ZNNXjwYK1YsUL9+vXTtm3bXNPZnmrbtq169OihFStW6Pjx4woJCdHVV19d5b4A3sIUMKDT1/w88cQTGj16tF566SUVFRXpkUcece3/7rvv1LNnT1111VWu8Jebm6v8/PxK79StijPvYpRO3/QQEhLiNn3s1KNHDxUWFsowDMXHx7t+/fjjj3rhhRd06tQpjz4zOjpaLVq0UGZmptv2PXv2KCcnp8IRxvNR3sjN+Y7mWCwWde3aVR9//LHb9k8//dTjWpyPpk2b6tFHH9Xu3bsrvZHFqV+/fjIMQxkZGYqKilKrVq3UqVMnNWvWTM8884yaNWumbt26VXh8TYx+NWnSRB07dtQnn3zitv2rr77S3Xffrf3796t79+767LPP3C5XsNvtysrKUnx8vBo2bOjRZyUmJio4OLjMjU+fffaZ22vn6PmZN+5kZ2e7tUlKSlJJSYk+//xz1zbDMDRnzhxlZGSU+/me1GvkyJHavHmz3njjDbVs2VK9evWqsG1F73fDDTdo7dq1+vDDDzVs2LAqjSAC3kYAhF8rLi5WTk5Ohb+cIWrOnDkKDg7WzJkz1apVK02dOlVZWVmu/7A6d+6sr776Sv/85z+1ceNGvfbaa7rrrrsUEBDguubnfK1cuVKPPfaYvvrqKy1YsEBvvPGGJk2a5Dat59S/f391795dkyZN0ptvvqkNGzZoyZIlmjdvngIDAz1esywwMFBTp07V2rVr9cADD+jzzz/XBx98oDvuuEOhoaG64447auS7nemCCy7Qr7/+qs8//9w1enTBBRdo06ZN+uabb6q9ZMbkyZO1bds2TZ48WV988YXeeustPfzww5Lklbsw+/btqxtvvLHMtZ3lueCCC5SYmKj//Oc/rpsWLBaLkpKSlJ2drSuvvLLSaxdrol7S6Zp9//33uv/++/XFF1/ogw8+UGpqqgYOHKiOHTvqT3/6k4qLizVu3DitWLFCn3zyicaPH689e/Z4fHONdDpsOs/V9PR0ffXVV3rsscfKBMD+/ftLkh5++GGtXbtWy5YtU2pqqpo0aeJqM2DAACUmJmr27Nn65z//qbVr1+qhhx7S9u3bddddd5X7+Z7Uq1+/fgoLC9Nbb72llJSUSkOj86asjz76SHv27HFtHzp0qBo1aqTNmzdr9OjRnhUH8BECIPzaoUOHdPPNN1f4a+fOnXrzzTe1du1azZkzxzUleuuttyoxMVHz5s3T4cOHNWvWLF111VV69tlndc899+idd97RxIkTddNNN2nTpk2uJT3Ox5QpU7Rz505NmjRJq1at0ty5c3X33XeX2zYwMFAvvfSShg8frhdffFF33nmn3nrrLd1+++0e34zgNHr0aD333HP66aefdO+99+qJJ55QYmKi3n333Wpdo+XJ57Vu3Vr33nuva8maCRMmaMuWLbrrrrs8XrblbElJSVq0aJF27dqlSZMm6dVXX3UFwDMDRG2aNWuW687xc3GGnTPvWnWOOlV0p7VTTdRLkgYOHKgXX3xRe/fu1b333qsFCxZo2LBhruVZLr/8cr355pu66KKL9NBDD2n69OkyDEOvvfaa20Lfnrjnnnv00EMPaeXKlZo4caJ++OGHMtOs0dHRevLJJ/XLL7/o7rvv1v/7f/9PaWlpbtfHWiwWLVmyRMnJyVq0aJEmTZqkXbt26eWXX3a7AetMntTLYrFo+PDhstvtZW7IOtvVV1+t+Ph4zZo1y+0Rc40aNVLv3r0VFRVVK6PnQE0KMFihEvCpvXv3avDgwXr88ccZNTgPn3zyiSIiItyW/fnxxx81YsQItyVDgNpis9nUv39/3XPPPfrjH//o6+4AleImEAB+4auvvtK///1vTZs2TdHR0dq/f78yMjJ06aWXlnnKBlCT9u3bp/fff9+1tM+NN97o4x4B50YABOAXZs6cqeDgYGVkZOjgwYNq3ry5rrjiCj344INq1KiRr7sHPxYYGKjXX39djRs31oIFC9zWTQTqKqaAAQAATIabQAAAAEyGAAgAAGAyBEAAAACTIQACAACYDHcBn4dTp06poKBAjRo1qtEHkwMAgNrjcDj022+/KTQ0tNKn7vgzc37rGlJQUKDdu3f7uhsAAKAaoqKiFB4e7utu+AQB8Dw41xaLioqq0kO/7Xa7tm/frpiYGFksltrqXr1ALUpRi1LUwh31KEUtSlGLUlWtRVFRkXbv3m3qNUIJgOfBOe0bEhKixo0be3yc87mxjRs35i8ttXChFqWohTvqUYpalKIWpapbCzNfvmXebw4AAGBSBEAAAACTIQACAACYDAEQAADAZAiAAAAAJkMABAAAMBkCIAAAgMkQAAEAAEyGhaABAPAhu8PQxl35OnjcppbNgtUjOkyWwABfdwt+jgAIVMHx48dVUlKisLAwX3cFQB1wvuFtZa5V8zPzZC2wubZFhgYrNSVWyXGRtdFlQBJTwHWe3WFo3c7DWp6zT+t2HpbdYfi6Sz63aNEijR07tkbea+/evWrfvr327t3rUfshQ4boxx9/rJHPBlC/rcy1qt+Tn+rWJes15a0c3bpkvfo9+alW5lo9Pn7i0my38CdJ+wtsmrg02+P3AaqDEcA6jJ8M654jR474ugsA6gBneDv7R3JneMsY07XSf6ftDkPzM/PKHC9JhqQASfMz8zQkNsKjEUWmkVFVfj8CWFhYqNmzZ6tnz57q1q2bZsyYoZMnT1bYftWqVRo5cqS6du2qQYMG6fnnn5fD4fBij0/z1U+GP//8syZMmKCePXtq4MCB+utf/6ri4mJJ0ty5c3XVVVe56vfGG2+oV69eOnDggAzD0EsvvaSUlBQlJSWpe/fuevDBB2Wzne7/rFmz9Mgjj+iee+5RYmKihgwZonXr1unRRx/V+PHjdcUVV+idd96RVDoq9/rrr6tv377q1q2bpk+frhMnTpTb57Vr1+qGG25QUlKShg8frg8//LDC73fixAnNnDlT3bp10xVXXKHly5e77c/Ozta4cePUr18/xcfHa/To0crJyZEkDR06VJJ01113acmSJef8zgD807nCm3Q6vFU2Y7NxV36Zf9/Pfh9rgU0bd+Wfsz+rvt9/XiORMCe/D4BpaWmyWq1atWqVVq9eLavVqvT09HLb5ubmasaMGbr//vv17bffasmSJVq2bJn+8Y9/eLXPNfGPS3UUFhbq9ttv1+WXX64vvvhCb775ptauXatFixZJkh566CEFBwfr6aef1rZt2/TUU0/pqaeeUqtWrbRixQq99tprWrRokb799lu99dZb+uqrr5SZmel6//fee0933XWXvvvuO3Xu3Fl33nmnoqKi9OKLL+ruu+/WI4884gqbkrR69WplZmZq5cqV+umnnzR//vwyfd62bZsmTpyou+++Wxs2bFBaWpr+8pe/6Msvvyz3Oz7yyCP66aeftHr1an344Yf67rvvXPtsNpsmTpyooUOH6osvvtCGDRt0ySWX6KmnnpJ0+ocDSVqyZInuuusuj74zgLrpfC6vqYnwdvC4Zz8onqvd+r023ftmDtPIqDK/DoBFRUXKzMzU5MmT1bx5c4WHh2vatGlatmyZioqKyrTft2+fbrnlFg0cOFCBgYFq166dhgwZom+++car/a7JnwyrYs2aNSouLtbUqVPVqFEjRUZGasqUKXrjjTckScHBwVqwYIE++OADTZgwQbfffruuvPJKSdKVV16pd999V1FRUcrPz9eRI0fUvHlzHThwwPX+vXr1UlJSkgIDA9WrVy81btxYY8aMkcVi0YABA1RcXKxff/3V1X727NkKCwtTixYtNHnyZK1cudItIErSW2+9pcGDB+vqq6+WxWJR165dddNNN7n6fKbi4mKtWLFC9913n8LDw3XhhRdqxowZrv1BQUF6++23ddttt6m4uFj79u0r8x3O5Ml3BlD3nO+1ezUR3lo2C/boPSprZ3cYeiXnmNcHC+Af6v01gDabrcL/cIuKilRSUqKYmBjXtnbt2slms2n37t3q2LGjW/uhQ4e6pvmc771mzRqlpKRU2ge73S673e5xn51tKzpmf0GhR++zv6BQdntzjz/3XPbu3av8/Hx1797dtc0wDJWUlOjgwYMKDw9Xu3btlJSUpK+//lqjRo1yfYdTp05pwYIF+uyzzxQeHq4OHTqouLjYVRvDMBQaGupqHxAQoGbNmrleG4bheh+nNm3auPa3atVKxcXFys/Pl8PhkGEYstvt2rt3rzZs2KCkpCTXcXa7XW3bti1T38OHD6u4uFitWrVy7bv44oslyTXNv27dOo0fP16FhYW67LLLFBQUJIfD4fZeztfn+s5Vda7zwkyohTvqUep8a7Hq+/26982cCq/de+G2BA3tFFHpe1zUJMijz7qoSVCF/ex2SagiLmikA8d+KzfABUiKCA1Wt0tCK3yPDf/7VYeLKr5EyTlYsH7nIfW6NNyjPtdXVT0v+LvkBwFw8+bNGjduXLn7pkyZIklq3Lixa1tISIgkVXodoHT6WrEpU6YoODhYt99+e6Vtt2/fXoUel9qyZUu5248d/M2j448d2KOcnIPV+uzy2Gw2tWzZUs8884xrW1FRkQoKCvTzzz9rz549Wr9+vbKzs5WUlKTJkydr7ty5CgwM1N///ndZrVYtWLDAVe/c3Fzt379fOTk5ys8/PVrpvJ7u559/VnFxsasGP/zwgyQpLy/P9dmff/65K6Dl5OSoUaNG+umnn7R//36dOHFCOTk5atCgga644grdeeedruOcN2o4P8vp1KlTCgoK0ueff66CggJJp0d9nZ/rvCZx3rx5uvTSSyVJWVlZ2rZtm9t77dixQw0bNjznd66uis4LM6IW7qhHqerUwm4YejjrUKUjZg+//19dVGyVJaDiGyiCDEPhIYGVhq/wkEAFFfysnJw9FbYZ2ylET68r/997Q9KY2GBt+e/mCo//7ueyM1nl+SZ3u4KPhXjU1m4Y2nqoWEdsDl0YHKiOLRpWWou6hr8jnqv3AbBnz56u8HC2vLw8LVy4UEVFRWrSpIkkuaZ+mzZtWuF7/u9//9PkyZMVHh6u1157rdK2khQTE+MWMs/Fbrdry5Ytio+Pl8ViKbM/3mEoY9Oac/5keOtVPWr0Lq/LLrtM77zzjr777juNHTtWNptNc+bMkdVq1bvvvqt9+/bpH//4h1JTUzVgwACNGjVKX3/9te677z4FBwcrLCxMiYmJCgwM1Jtvvqk9e/YoOTlZCQkJrnXzEhISJEm7du1Sw4YNFR8fry1btqh9+/aSpNjYWFd/VqxYoccff1yFhYX6y1/+olGjRikpKUnr16/Xnj17lJCQoLvvvlvjx4/XLbfcot69e+vnn3/WrFmzNHDgQM2cObPMdxw1apSysrKUnJysJk2aaMmSJa7P3b17tywWizp37qzLLrtMmzdv1ieffKKAgABXvxs2bKhWrVopISHhnN+5qs51XpgJtXBHPUqdTy3W/++wDhdVfonG4SKHSkIvUbdzjJilNTw9kijJ7d9p57/Iadd1VrdzjCQmJEjR0fv1yEdbtf9YaRCMDA3Ww8M7nHMksrDpIWnDd5W2kaTucTFK8GAEcNX3ZfsScUEjzR3R8Zx98bWqnheFhYXVHrzxF/U+AFYmOjpaQUFB2rFjh7p06SJJ2rlzp4KCghQVFVXuMZ9//rmmTp2qm266SQ8++KAaNDh3iSwWS7X+Ua7oOItFmndtJ01cmq0Alf+PS2pKrBoG1ewfX2hoqP7xj3/oiSee0CuvvCKHw6GePXtq8eLFkqSZM2eqd+/eGjlypCTp8ccf15133qm+ffvqgQce0OzZs3XFFVeocePG6tatm0aOHKkdO3bIYrEo4P9+gnR+38DAQAUEBLhen7nd6Xe/+51GjhypoqIipaSkaPr06bJYLG7Hdu3aVQsWLNCzzz6rBx54QCEhIRoxYoSmTp1abm0ffvhhPf744xo1apQaNGigcePG6bPPPlNgYKCuuOIK3XbbbRo3bpwcDofatGmjcePG6ZlnntGRI0d00UUX6eabb9b06dN1++23n/M7V1d1zyd/RC3cUY9S1anFrydLPG53rve+pnNrZQQGllmqK6KKS3Vd07m1hsZdXK0lXHpeepHCQwKVX+SodLCgV7sW53y/lbnWcqfGDxz7Tfe+mXPOZW3qCk/PC/4eSQGG8+IrPzV9+nTt379fCxculHR6Wrh169Z64oknyrTNycnRmDFjNG/ePN1www3nfO/CwkJt3bpVHTt2rPIIYE5OjhISEio9Cc2wDmB5tdi7d68GDx6sTz75RG3atPFxD73H0/PCDKiFO+pR6nxqsW7nYd26ZP052/3zrl7q3c6za+Z8uf6e3W7X4o/WK33dUUnlDxZ4EtzsDkP9nvy0wpsPnUHyq5mD6uzaglU9L6r7/7c/8esRQElKTU3Vk08+qZSUFJWUlGjw4MF6+OGHXfuHDx+ulJQUTZgwQYsXL9apU6f02GOP6bHHHnO16datm15++WWv9z05LlJDYiNY3BMAakCP6DBFhgZrf4Gt0hGzHtGeP+rREhjgcVisDb3aBOuF2xKUlrWt2iORVVl5wpffFTXL7wNg06ZNlZaWprS0tHL3Z2VluX7vnOqsS3z9jwsA1DV2w9D6/x3WrydLqvSDsSUwQKkpsee8vKa+/ZA9tFNEtaeRpZpbkxD1i98HQNQ/bdq0qfDGHgDmtur7/Xo465DbzRxVuTQmOS5SGWO6nve1e3XN+QwW1MSahKh/CIAAgHqhohsVPH3+rhOX17irjalx1H1+/SQQAIB/qOlHZDpHzEYmtFbvduGmDX9S6dS4VDoV7lSdqfHzecwevIcRQABAnceNCrWrpqbGzbB6hb8gAAIA6jxuVKh95zs1vjLXqolLs897ih7eQQAEANR53KjgHdW9meRcU/QBOj1FPyQ2wtTT7XUJ1wACAOo8540KFUWHAJ2eauRGBd+oyhQ96gYCIACgzjvzRoWz1ec1/PwFU/T1DwEQAFAvJMdF6oXbEhQe4v5fV0RoMNeX+RhT9PUP1wACAOqNoZ0idFGxVSWhl1T5SSCoPawlWP8QAAEA9YolIEDdLg2XxWLxdVfwf/z1MXv+jClgAIDXsEiw/3KuJRgR6j7NyxR93cQIIADAK1gk2P/V1GP27A6DR/XVMgIgAKDWsUiweVR3LUEnflDwDqaAAQC1qqaf4wv/5fxB4ew1BZ0/KKzMtfqoZ/6HAAgAqFUsEgxP8IOCdxEAAQC1ikWC4Ql+UPAuAiAAoFaxSDA8wQ8K3kUABADUKp7jC0/wg4J3EQABALXqzOf4nh0CWSQYTvyg4F0EQABArWORYJwLPyh4F+sAAgC8oqYWCYb/cv6gcPY6gBGsA1jjCIAAAK8530WC4f/4QcE7CIAAAKBO4QeF2sc1gAAAACZDAAQAADAZAiAAAIDJEAABAABMhptAAADnZHcY3JUJ+BECIACgUitzrWXWZYtkXTagXmMKGABQoZW5Vk1cmu0W/iRpf4FNE5dma2Wu1Uc9A3A+CIAAgHLZHYbmZ+bJKGefc9v8zDzZHeW1AFCXEQABAOXauCu/zMjfmQxJ1gKbNu7K916nANQIAiAAoFwHj1cc/qrTDkDdQQAEAJSrZbPgGm0HoO4gAAIAytUjOkyRocGqaLGXAJ2+G7hHdJg3uwWgBhAAAQDlsgQGKDUlVpLKhEDn69SUWNYDBOohAiAAoELJcZHKGNNVEaHu07wRocHKGNOVdQCBeoqFoAEAlUqOi9SQ2AieBAL4EQIgAOCcLIEB6t0u3NfdAFBD/H4KuLCwULNnz1bPnj3VrVs3zZgxQydPnqyw/RtvvKGrr75aiYmJuvrqq7V06VIv9hYAAKD2+X0ATEtLk9Vq1apVq7R69WpZrValp6eX2/bTTz/VwoULtWDBAm3atEnp6el66qmntH79ei/3GgAAoPb4dQAsKipSZmamJk+erObNmys8PFzTpk3TsmXLVFRUVKb9oEGD9OmnnyouLk6nTp3SkSNHFBAQoAsuuMAHvQcAAKgd9f4aQJvNpgMHDpS7r6ioSCUlJYqJiXFta9eunWw2m3bv3q2OHTuWOaZp06b63//+pxEjRshut+uOO+5QbGxsrfUfAADA2+p9ANy8ebPGjRtX7r4pU6ZIkho3buzaFhISIkmVXgfYtm1bbd68Wdu2bdOkSZMUFhamu+++u8L2drtddrvd4z4721blGH9FLUpRi1LUwh31KEUtSlGLUlWtBTWTAgzDMHzdidqSl5en6667TtnZ2WrSpIkk6cSJE+rWrZuWL1+uDh06nPM9lixZoszMTH344Ydl9hUWFmrr1q013m8AAFD7Onbs6DZIZCb1fgSwMtHR0QoKCtKOHTvUpUsXSdLOnTsVFBSkqKioMu3/8Y9/KCcnR88++6xrW3FxsUJDQyv9nJiYmCqdQHa7XVu2bFF8fLwsFovHx/kjalGKWpSiFu6oRylqUYpalKpqLQoLC7V9+3Yv9Kzu8usAGBISomHDhik9PV0LFy6UJKWnp2vEiBEKDi778PKkpCSlp6fr3//+t5KTk7Vp0ya99tprSk1NrfRzLBZLtf7yVfc4f0QtSlGLUtTCHfUoRS1KUYtSntaCevn5XcCSlJqaqqioKKWkpCg5OVlt2rTR3LlzXfuHDx+uxYsXS5Li4uL03HPPafHixUpKStK8efM0Z84cXXPNNb7qPgAAQI3z6xFA6fRdvWlpaUpLSyt3f1ZWltvrQYMGadCgQd7oGgAAgE/4fQAEALOzOwye4wvADQEQAPzYylyr5mfmyVpgc22LDA1WakqskuMifdgzAL7k99cAAoBZrcy1auLSbLfwJ0n7C2yauDRbK3OtPuoZAF8jAAKAH7I7DM3PzFN5C706t83PzJPd4bdLwQKoBAEQAPzQxl35ZUb+zmRIshbYtHFXvvc6BaDOIAACgB86eLzi8FeddgD8CwEQAPxQy2ZlF7s/n3YA/AsBEAD8UI/oMEWGBquixV4CdPpu4B7RYd7sFoA6ggAIAH7IEhig1JRYSSoTAp2vU1NiWQ8QMCkCIAD4qeS4SGWM6aqIUPdp3ojQYGWM6co6gICJsRA0APix5LhIDYmN4EkgANwQAAHAz1kCA9S7XbivuwGgDmEKGAAAwGQIgAAAACZDAAQAADAZAiAAAIDJEAABAABMhgAIAABgMgRAAAAAkyEAAgAAmAwBEAAAwGR4EkgdZHcYPLYJAADUGgJgHbMy16r5mXmyFthc2yJDg5WaEsuD2wEAQI1gCrgOWZlr1cSl2W7hT5L2F9g0cWm2VuZafdQzAADgTwiAdYTdYWh+Zp6McvY5t83PzJPdUV4LAAAAzxEA64iNu/LLjPydyZBkLbBp465873UKAAD4JQJgHXHweMXhrzrtAPgHu8PQ+v8d1pc/F2n9/w4zCwCgRnATSB3RsllwjbYDUP+VuSlswzfcFAagRjACWEf0iA5TZGiwKlrsJUCn7wbuER3mzW4B8BFuCgNQmwiAdYQlMECpKbGSVCYEOl+npsSyHiBgAtwUBqC2EQDrkOS4SGWM6aqIUPdp3ojQYGWM6cqUD2AS3BQGoLZxDWAdkxwXqSGxETwJBDAxbgoDUNsIgHWQJTBAvduF+7obAHyEm8IA1DamgAGgjuGmMAC1jQAIAHUMN4UBqG0EQACog7gpDEBt4hpAAKijnDeFrd95SN/kblf3uBj1ateCkT8A540ACAB1mCUwQL0uDVfwsRAlXBpO+ANQI5gCBgAAMBkCIAAAgMkQAAEAAEzG7wNgYWGhZs+erZ49e6pbt26aMWOGTp48ec7jDh48qD59+mjZsmVe6CUAAID3+H0ATEtLk9Vq1apVq7R69WpZrValp6dXeozD4dC0adN05MgRL/USAADAe/w6ABYVFSkzM1OTJ09W8+bNFR4ermnTpmnZsmUqKiqq8LgXXnhBERERioxknS0AAOB/6v0yMDabTQcOHCh3X1FRkUpKShQTE+Pa1q5dO9lsNu3evVsdO3Ysc8z69euVlZWl9957TykpKR71wW63y263e9xnZ9uqHOOvqEUpalGKWrijHqWoRSlqUaqqtaBmfhAAN2/erHHjxpW7b8qUKZKkxo0bu7aFhIRIUrnXAR4+fFgPPfSQnnvuOTVp0sTjPmzfvr0qXXbZsmVLtY7zR9SiFLUoRS3cUY9S1KIUtShFLTxX7wNgz5499cMPP5S7Ly8vTwsXLlRRUZEr0Dmnfps2berW1jAMzZgxQ2PHjlVcXFyV+hATE+MWMs/Fbrdry5Ytio+Pl8ViqdJn+RtqUYpalKIW7qhHKWpRilqUqmotCgsLqz144y/qfQCsTHR0tIKCgrRjxw516dJFkrRz504FBQUpKirKra3VatXGjRu1efNmvfDCC5KkEydOaP78+Vq1apVefPHFCj/HYrFU6y9fdY/zR9SiFLUoRS3cUY9S1KIUtSjlaS2ol58HwJCQEA0bNkzp6elauHChJCk9PV0jRoxQcLD7A9YvvvjiMkPHgwYN0p/+9CeNHj3aa30GAACobX59F7AkpaamKioqSikpKUpOTlabNm00d+5c1/7hw4dr8eLFPuwhAACAd/n1CKB0+lq/tLQ0paWllbs/KyurwmM//fTT2uoWAACAz/j9CCAAAADcEQABAABMhgAIAABgMgRAAAAAkyEAAgAAmIzf3wUMAL5gdxjauCtfB4/b1LJZsHpEh8kSGODrbgGAJAIgANS4lblWzc/Mk7XA5toWGRqs1JRYJcdF+rBnAHAaU8AAUINW5lo1cWm2W/iTpP0FNk1cmq2VuVYf9QwAShEAAaCG2B2G5mfmyShnn3Pb/Mw82R3ltQAA7yEAAkAN2bgrv8zI35kMSdYCmzbuyvdepwCgHARAAKghB49XHP6q0w4AagsBEABqSMtmwTXaDgBqCwEQAGpIj+gwRYYGq6LFXgJ0+m7gHtFh3uwWAJRBAASAGmIJDFBqSqwklQmBztepKbGsBwjA5wiAAFCDkuMilTGmqyJC3ad5I0KDlTGmK+sAAqgTWAgaAGpYclykhsRG8CQQAHUWARAAaoElMEC924X7uhsAUC6mgAEAAEyGAAgAAGAyBEAAAACTIQACAACYDAEQAADAZAiAAAAAJkMABAAAMBkCIAAAgMkQAAEAAEyGAAgAAGAyBEAAAACTIQACAACYDAEQAADAZBr4ugOoHXaHoY278nXwuE0tmwWrR3SYLIEBvu4WAACoAwiAfmhlrlXzM/NkLbC5tkWGBis1JVbJcZE+7BkAAKgLmAL2MytzrZq4NNst/EnS/gKbJi7N1spcq496BgAA6goCoB+xOwzNz8yTUc4+57b5mXmyO8prAQAAzIIA6Ec27sovM/J3JkOStcCmjbvyvdcpAABQ5xAA/cjB4xWHv+q0AwAA/okA6EdaNguu0XYAAMA/EQD9SI/oMEWGBquixV4CdPpu4B7RYd7sFgAAqGMIgH7EEhig1JRYSSoTAp2vU1NiWQ8QAACTIwD6meS4SGWM6aqIUPdp3ojQYGWM6co6gIAH7A5D63Ye1vKcfVq38zB3zgPwO36/EHRhYaHS0tL06aef6tSpUxo8eLBSU1PVpEmTctunpqbqvffeU1BQkGvbrFmzdPPNN3ury+ctOS5SQ2IjeBIIUA0spA7ADPw+AKalpclqtWrVqlWy2+26//77lZ6ertTU1HLbb9myRWlpabruuuu83NOaZQkMUO924b7uBlCvOBdSP3u8z7mQOqPoAPyFV6eAv/nmG23ZskXFxcVe+byioiJlZmZq8uTJat68ucLDwzVt2jQtW7ZMRUVFZdoXFxdr+/btiouL80r/ANQdLKQOwEy8OgI4duxYSdLFF1+sTz/9tEbe02az6cCBA+XuKyoqUklJiWJiYlzb2rVrJ5vNpt27d6tjx45u7bdt26ZTp07pueee03fffadmzZrp+uuv1/jx4xUYyOWSgD+rykLqjK4DqO+8GgA/+eQThYSEKCys5pYh2bx5s8aNG1fuvilTpkiSGjdu7NoWEhIiSTp58mSZ9sePH1ePHj00duxYLViwQFu3btW9996rwMBAjR8/vsI+2O122e12j/vsbFuVY/wVtShFLUr5ohb7Cwo9bme3N6/dzpyFc6MUtShFLUpVtRbUTAowDMNr8xkdOnRQcHCwLr/8cr3zzju1/nl5eXm67rrrlJ2d7brp48SJE+rWrZuWL1+uDh06nPM9Xn75Zf373//WsmXLyuwrLCzU1q1ba7zfALwv9+BvSv38yDnbze9/oeJaNvJCjwDUto4dO7oNEpmJV0cA//KXv6hx48bq1KmTVz4vOjpaQUFB2rFjh7p06SJJ2rlzp4KCghQVFVWm/ccff6xff/1Vt9xyi2tbcXGxgoMrf3JGTExMlU4gu92uLVu2KD4+XhaLxePj/BG1KEUtSvmiFvEOQxmb1ujAsd/KvQ4wQKeXU7r1qh5ev6Oec6MUtShFLUpVtRaFhYXavn27F3pWd3k1AI4ePVq333677rjjDrVt29Ztn91ur/ETOCQkRMOGDVN6eroWLlwoSUpPT9eIESPKDXWGYejxxx/X7373O/Xq1Us5OTl67bXXNHv27Eo/x2KxVKvv1T3OH1GLUtSilDdrYbFI867tpIlLsxUguYXAMxdSbxjku8UTODdKUYtS1KKUp7WgXj5YCDo3N1dt2rSRJO3Zs8e1/d1339X06dNr/PNSU1MVFRWllJQUJScnq02bNpo7d65r//Dhw7V48WJJ0pAhQzR79mzNmzdPiYmJmj59uu677z6NHDmyxvsFoO5hIXUAZuH1H2VLSkpc1+ONHDlSy5cvV9u2bZWYmKhFixbV+Oc1bdpUaWlpSktLK3d/VlaW2+tbbrnFbQoYgLmwkDoAM/B6ALzkkku0efNmNWnSREVFRTp27JgkqUmTJiooKPB2dwCgDBZSB+DvvD4FfNttt+nPf/6zxowZow4dOujtt9+WJH377be66KKLvN0dAAAA0/H6COCtt96qsLAw/fTTT7rxxhs1depUDR48WIcOHdLvf/97b3cHAADAdHxyO9vQoUNdv1+yZIn+85//qKSkRMOHD/dFdwAAAEzFd+sZODvQoIGGDRvm624AAACYBg+4BQAAMBkCIAAAgMkQAAEAAEyGAAgAAGAyPrkJZNCgQQoIKLuqflBQkMLCwjRw4EDdeeedCgwknwIAANQ0nwTAm266Sf/61780fvx4tW3bVvv27dMrr7yiPn366NJLL9Wbb74pm82m++67zxfdAwAA8Gs+CYCrVq3Siy++qMsvv9y1rUePHpo2bZrmzp2rAQMGaOzYsQRAAACAWuCTOdaffvpJUVFRbtvatm2rXbt2SZLatGnjekYwAAAAapZPAmCHDh304osvum175ZVXdNlll0mSvvjiC7Vu3doXXQMAAPB7PpkC/vOf/6y77rpL77zzjiIjI/XLL7/IMAxlZGQoOztb9957rxYuXOiLrgEAAPg9nwTA2NhYrVq1Sp999pn279+vFi1aKDk5WcHBwTp69KjWrFmj8PBwX3QNAADA7/kkAJ44cUIzZ87UJ598IkkKCAjQhx9+qGeffVbNmzf3RZcAAABMwyfXAD7zzDM6efKksrKytHnzZi1fvlwOh0NPP/20L7oDAABgKj4JgJ999pmeeeYZtWvXTo0aNVJMTIyefvppffzxx77oDgAAgKn4JAAWFRWpWbNmbtsuuOACORwOX3QHAADAVHwSALt06aKFCxfKMAxJkmEYWrhwoeLj433RHQAAAFPxyU0gDz74oMaNG6cPP/xQrVu31r59+xQQEKBXX33VF90BAAAwFZ8EwPbt22vVqlX6+OOPlZ+fr9atW6t///5q2rSpL7oDAABgKl4NgL/88ovb6z59+rh+f+zYMR07dkwXX3yxN7sEAABgOl4NgIMGDVJAQEC5+wzDUEBAgLZu3erNLgHwM3aHoY278nXwuE0tmwWrR3SYLIHl/7sDAGbl1QDoXPgZAGrDylyr5mfmyVpgc22LDA1WakqskuMifdgzAKhbvBoAW7du7c2PA2AiK3Otmrg0W8ZZ2/cX2DRxabYyxnQlBALA//HJMjAAUJPsDkPzM/PKhD9Jrm3zM/Nkd5TXAgDMhwAIoN7buCvfbdr3bIYka4FNG3fle69TAFCHEQAB1HsHj1cc/qrTDgD8HQEQQL3XsllwjbYDAH9HAARQ7/WIDlNkaLAqWuwlQKfvBu4RHebNbgFAnUUABFDvWQIDlJoSK0llQqDzdWpKLOsBAsD/IQAC8AvJcZHKGNNVEaHu07wRocEsAQMAZ/HJs4BRP/BEBdQ3yXGRGhIbwXkLAOdAAES5eKIC6itLYIB6twv3dTcAoE5jChhlOJ+ocPa6as4nKqzMtfqoZwAAoCYQAOGGJyoAAOD/CIBwwxMVAADwfwRAuOGJCgAA+D8CINzwRAUAAPyf3wfAwsJCzZ49Wz179lS3bt00Y8YMnTx5ssL227Zt0x/+8AclJiaqT58+evzxx3Xq1Ckv9ti3eKICAAD+z+8DYFpamqxWq1atWqXVq1fLarUqPT293Lb5+fm6/fbb1adPH23cuFH/+te/tGbNGv2///f/vNxr3+GJCgAA+D+/DoBFRUXKzMzU5MmT1bx5c4WHh2vatGlatmyZioqKyrT/4IMPFBUVpXvuuUdBQUFq06aNXnnlFQ0bNswHvfcdnqgAAIB/q/cLQdtsNh04cKDcfUVFRSopKVFMTIxrW7t27WSz2bR792517NjRrf1///tfxcTEaO7cufrkk08UEhKi66+/Xvfcc0+lfbDb7bLb7R732dm2Ksd425COLTWofQt9sztfB4//ppbNGql71OknKtRkv+tDLbyFWpSiFu6oRylqUYpalKpqLaiZHwTAzZs3a9y4ceXumzJliiSpcePGrm0hISGSVO51gAUFBfr44481b948Pfzww9q5c6cmTJighg0b6s4776ywD9u3b69W37ds2VKt47wpWNIlknRM2vLfPbX2OfWhFt5CLUpRC3fUoxS1KEUtSlELz9X7ANizZ0/98MMP5e7Ly8vTwoULVVRUpCZNmkiSa+q3adOmZdo3bNhQ8fHxuuGGGyRJHTp00JgxY7RixYpKA2BMTIxbyDwXu92uLVu2KD4+XhaLxePj/BG1KEUtSlELd9SjFLUoRS1KVbUWhYWF1R688Rf1PgBWJjo6WkFBQdqxY4e6dOkiSdq5c6eCgoIUFRVVpn27du20YcMGt20Oh0OGUflTLywWS7X+8lX3OH9ELUpRi1LUwh31KEUtSlGLUp7Wgnr5+U0gISEhGjZsmNLT05Wfn6/8/Hylp6drxIgRCg4uu47d9ddfr+3bt2vJkiWy2+364YcftHTpUo0cOdIHvQcAAKgdfh0AJSk1NVVRUVFKSUlRcnKy2rRpo7lz57r2Dx8+XIsXL5Z0egRw6dKlWrNmjXr16qXx48frlltu0dixY33VfQAAgBrn11PA0ulr/dLS0pSWllbu/qysLLfXXbp00RtvvOGNrgEAAPiE348AAgAAwB0BEAAAwGQIgAAAACZDAAQAADAZAiAAAIDJEAABAABMhgAIAABgMgRAAAAAkyEAAgAAmAwBEAAAwGT8/lFwAOoHu8PQxl35OnjcpouaBCnIMHzdJQDwWwRAAD63Mteq+Zl5shbYXNvCQwKV1nC/runc2oc9AwD/xBQwAJ9amWvVxKXZbuFPkg4XOXTvmzlamWv1Uc8AwH8RAAH4jN1haH5mniqb7J2fmSe7g+lgAKhJBEAAPrNxV36Zkb8zGZKsBTZt3JXvvU4BgAkQAAH4zMHjFYe/6rQDAHiGAAjAZ1o2C67RdgAAzxAAAfhMj+gwRYYGK6CC/QGSIkOD1SM6zJvdAgC/RwAE4DOWwAClpsRKUoUhMDUlVpbAivYCAKqDAAjAp5LjIpUxpqsiQt2necNDAvXCbQlKjov0Uc8AwH+xEDQAn0uOi9SQ2Aj3J4EU/KxunSJ83TUA8EsEQAB1giUwQL3bhUuS7Ha7cnL2+LhHAOC/mAIGAAAwGQIgAACAyRAAAQAATIYACAAAYDIEQAAAAJMhAAIAAJgMARAAAMBkCIAAAAAmQwAEAAAwGQIgAACAyRAAAQAATIYACAAAYDINfN0B+D+7w9DGXfk6eNymls2C1SM6TJbAAF93CwAA0yIAolatzLVqfmaerAU217bI0GClpsQqOS7Shz0DAMC8mAJGrVmZa9XEpdlu4U+S9hfYNHFptlbmWn3UMwAAzI0AiFphdxian5kno5x9zm3zM/Nkd5TXAgAA1CYCIGrFxl35ZUb+zmRIshbY9M3ufO91CgAASCIAopYcPF5x+HNv91st9wQAAJzN728CKSwsVFpamj799FOdOnVKgwcPVmpqqpo0aVKm7dy5c5WZmem2zWazqU+fPvr73//urS77hZbNgj1s10g6VsudAQAAbvx+BDAtLU1Wq1WrVq3S6tWrZbValZ6eXm7bRx55RJs2bXL9WrRokS644ALNmjXLy72u/3pEhykyNFgVLfYSoNN3A3ePCvNmtwAAgPw8ABYVFSkzM1OTJ09W8+bNFR4ermnTpmnZsmUqKiqq9Nj8/HxNmzZNc+bM0eWXX+6lHvsPS2CAUlNiJalMCHS+Tk2JZT1AAAB8oN5PAdtsNh04cKDcfUVFRSopKVFMTIxrW7t27WSz2bR792517NixwvdNT09XXFycrr322nP2wW63y263e9xnZ9uqHFMfDenYUi/clqBHPtqq/cdKr/WLCA3Ww8M7aEjHlqaphSeoRSlq4Y56lKIWpahFqarWgppJAYZh1Ot1ODZs2KBx48aVu2/KlClauHChtm7dqsDA04OddrtdsbGxeuONN5SUlFTucXv27NGwYcP0zjvvVBoSCwsLtXXr1vP/En7ObhjaeqhYR2wOXRgcqI4tGsoSwMgfAMC3OnbsqMaNG/u6Gz5R70cAe/bsqR9++KHcfXl5eVq4cKGKiopcN304p36bNm1a4Xu+9957SkxMrDT8nSkmJqZKJ5DdbteWLVsUHx8vi8Xi8XH1WbcKtpuxFhWhFqWohTvqUYpalKIWpapai8LCQm3fvt0LPau76n0ArEx0dLSCgoK0Y8cOdenSRZK0c+dOBQUFKSoqqsLjVq9erT/+8Y8ef47FYqnWX77qHuePqEUpalGKWrijHqWoRSlqUcrTWlAvP78JJCQkRMOGDVN6erry8/OVn5+v9PR0jRgxQsHB5S9TcuTIEe3cuVPdu3f3cm+B+svuMLRu52Etz9mndTsP84QXAKjj/HoEUJJSU1P15JNPKiUlRSUlJRo8eLAefvhh1/7hw4crJSVFEyZMkCTt3btXktSqVSuf9Beob1bmWjU/M8/tyS+RocFKTYlVclykD3sGAKiI3wfApk2bKi0tTWlpaeXuz8rKcnsdHx9f4TWFANytzLVq4tLsMs983l9g08Sl2coY05UQCAB1kF9PAQOoPXaHofmZeWXCnyTXtvmZeUwHA0AdRAAEUC0bd+W7TfuezZBkLbBp465873UKAOARAiCAajl4vOLwV512AADvIQACqJaWzcq/k7667QAA3kMABFAtPaLDFBkaXOZZz04BOn03cI/oMG92CwDgAQIggGqxBAYoNSVWksqEQOfr1JRYWQJ57B8A1DUEQADVlhwXqYwxXRUR6j7NGxEazBIwAFCH+f06gABqV3JcpIbERmjjrnwdPG5Ty2anp30Z+QOAuosACOC8WQID1LtduK+7AQDwEFPAAAAAJkMABAAAMBkCIAAAgMkQAAEAAEyGAAgAAGAyBEAAAACTIQACAACYDAEQAADAZAiAAAAAJkMABAAAMBkCIAAAgMkQAAEAAEyGAAgAAGAyBEAAAACTIQACAACYTANfdwDwhN1haOOufB08blPLZsHqER0mS2CAr7sFAEC9RABEnbcy16r5mXmyFthc2yJDg5WaEqvkuEgf9gwAgPqJKWDUaStzrZq4NNst/EnS/gKbJi7N1spcq496BgBA/UUARJ1ldxian5kno5x9zm3zM/Nkd5TXAgAAVIQAiDpr4678MiN/ZzIkWQts2rgr33udAgDAD3ANIOqsg8crDn/VaYfycYMNAJgPARB1VstmwTXaDmVxgw0AmBNTwKizekSHKTI0WBWNRQXodFjpER3mzW75DW6wAQDzIgCizrIEBig1JVaSyoRA5+vUlFimK6uBG2wAwNwIgKjTkuMilTGmqyJC3ad5I0KDlTGmK9OU1cQNNgBgblwDiDovOS5SQ2IjuFGhBnGDDQCYGwEQ9YIlMEC924X7uht+gxtsAMDcmAIGTIgbbADA3AiAgAlxgw0AmBsBEDApbrABAPPiGkDAxLjBBgDMye9HAAsLCzV79mz17NlT3bp104wZM3Ty5MkK22dlZWnYsGHq2rWrhg4dqn/+859e7C3gfc4bbEYmtFbvduGEPwAwAb8PgGlpabJarVq1apVWr14tq9Wq9PT0cttu375dc+bM0eOPP67s7Gw9/vjjeuyxx/Ttt996udcAAAC1x68DYFFRkTIzMzV58mQ1b95c4eHhmjZtmpYtW6aioqIy7Xfv3q1Tp07J4XDIMAwFBATIYrGoYcOGPug9AABA7aj31wDabDYdOHCg3H1FRUUqKSlRTEyMa1u7du1ks9m0e/dudezY0a19v379lJCQoFtvvVUWi0V2u10zZ85U586da/U7AAAAeFO9D4CbN2/WuHHjyt03ZcoUSVLjxo1d20JCQiSp3OsAi4uL1aZNG02aNEndu3fX119/rQceeEAxMTHq169fhX2w2+2y2+0e99nZtirH+CtqUYpalKIW7qhHKWpRilqUqmotqJkUYBiG3z7tPS8vT9ddd52ys7PVpEkTSdKJEyfUrVs3LV++XB06dHBrn5aWppKSEj3yyCOubX/+859VUFCgRYsWlXn/wsJCbd26tXa/BAAAqBUdO3Z0GyQyk3o/AliZ6OhoBQUFaceOHerSpYskaefOnQoKClJUVFSZ9r/88ouaN2/utq1BgwYKCgqq9HNiYmKqdALZ7XZt2bJF8fHxslgsHh/nj6hFKWpRilq4ox6lqEUpalGqqrUoLCzU9u3bvdCzusuvA2BISIiGDRum9PR0LVy4UJKUnp6uESNGKDi47DNOBw0apEcffVTXXHON+vXrp2+++UYffvihnnnmmUo/x2KxVOsvX3WP80fUohS1KEUt3FGPUtSiFLUo5WktqJefB0BJSk1N1ZNPPqmUlBSVlJRo8ODBevjhh137hw8frpSUFE2YMEE33nijbDabHn30UR06dEgXX3yx5s2bp4EDB/rwGwAAANQsvw+ATZs2VVpamtLS0srdn5WV5fZ67NixGjt2rDe6BgAA4BN+vQ4gAAAAyvL7EUDAye4weOYtAAAiAMIkVuZaNT8zT9YCm2tbZGiwUlNilRwX6cOeAQDgfUwBw++tzLVq4tJst/AnSfsLbJq4NFsrc60+6hkAAL5BAIRfszsMzc/MU3mrnTu3zc/Mk91R/9ZDtzsMrdt5WMtz9mndzsP18jsAAHyDKWD4tY278suM/J3JkGQtsGnjrnz1bhfuvY6dJ6a0AQDngxFA+LWDxysOf9VpVxcwpQ0AOF8EQPi1ls3KPvHlfNr5mj9PaQMAvIcACL/WIzpMkaHBqmixlwCdnjrtER3mzW5VW1WmtAEAqAgBEH7NEhig1JRYSSoTAp2vU1Ni6816gP44pQ0A8D4CIPxeclykMsZ0VUSo+zRvRGiwMsZ0rVc3TfjblDYAwDe4CximkBwXqSGxEfX+SSDOKe39BbZyrwMM0OlgW1+mtAEAvkEAhGlYAgPq1VIv5XFOaU9cmq0AyS0E1scpbQCAbzAFDNQz/jSlDQDwDUYAgXrIX6a0AQC+QQAE6il/mNIGAPgGU8AAAAAmQwAEAAAwGaaAAR+wO4wy1+8BAOAtBEDAy1bmWjU/M8/tkW6RocF6eHgHtfJhvwAA5sEUMFBFdoehdTsPa3nOPq3beVh2R3lLMpdvZa5VE5dml3me7/4Cm+59M0fr9/IINwBA7WMEEKiCikbvUlNiz7n+nt1haH5mXrlP8DB0eiHnV3KO6a5rDFksNdptAADcMAIIeKiy0buJS7O1Mtda6fEbd+WXOfZMhqTDRQ59szu/JroLAECFCICAB841eidJ8zPzKp0OPnjcs+ndg8d/q3oHAQCoAgIg4AFPRu+sBTZt3FXx6F3LZsEV7nNv16iq3QMAoEoIgIAHPB+9q7hdj+gwRYYGq6KHtQVICg8JVPcoloQBANQuAiDgAc9H7ypuZwkMUGpKrCSVCYHO139MuIDn+QIAah0BEPCAJ6N3kaHnXtA5OS5SGWO6KiLUPShGhAbrhdsS1KuNZ0ETAIDzwTIwgAeco3cTl2YrQHK7GcQZClNTYj0avUuOi9SQ2IiyTwIxHMrJ2V8b3QcAwA0BEPCQc/Tu7HUAIzxcB/BMlsAA9W4X7rbNbq+xrgIAUCkCIFAFFY3ecd0eAKA+IQACVVTe6B0AAPUJN4EAAACYDAEQAADAZAiAAAAAJkMABAAAMBkCIAAAgMkQAAEAAEyGAAgAAGAyBEAAAACTIQACAACYDE8COQ8Oh0OSVFRUVKXj7P/30NfCwkJZLJYa71d9Qi1KUYtS1MId9ShFLUpRi1JVrYXz/23n/+NmFGAYhuHrTtRXhw8f1u7du33dDQAAUA1RUVEKDzfnoz0JgOfh1KlTKigoUKNGjRQYyGw6AAD1gcPh0G+//abQ0FA1aGDOyVACIAAAgMkwbAUAAGAyBEAAAACTIQDWsvz8fA0ZMkQbNmyosM3nn3+ulJQUJSQkaNiwYfrss8+82EPv8aQW48ePV3x8vBITE12/vvjiCy/2snZt27ZNd9xxh3r06KG+fftqxowZys/PL7etv58XVamFv58XkrRu3TrdeOON6tq1q/r27au0tDTZbLZy2/r7uVGVWpjh3JBO3+U6duxYzZo1q8I2/n5eOHlSC7OcF+fFQK359ttvjauuusqIiYkx1q9fX26bXbt2GfHx8cZ//vMfo6SkxMjKyjI6d+5s7N+/38u9rV2e1MIwDKNnz57Ghg0bvNgz7ykqKjL69u1rLFy40Pjtt9+M/Px846677jLuueeeMm39/byoSi0Mw7/PC8MwjMOHDxvx8fHGe++9Z9jtduPAgQPGiBEjjIULF5Zp6+/nRlVqYRj+f244Pfvss0aHDh2MmTNnlrvf38+LM52rFoZhnvPifDACWEvef/99TZs2TQ888MA52yUlJemqq65SgwYNdM0116h79+56++23vdTT2udpLfbs2aOCggLFxsZ6qWfe9csvv6hDhw6699571bBhQ1144YW6+eab9c0335Rp6+/nRVVq4e/nhSSFhYVp7dq1Gj16tAICAnT06FH99ttvCgsLK9PW38+NqtTCDOeGdHpEdPXq1br66qsrbOPv54WTJ7Uwy3lxvgiAtaRfv376z3/+o2uuuabSdjt27FBMTIzbtssuu0zbtm2rze55lae12LJli5o0aaIHHnhAvXr10ogRI/Tuu+96qZe179JLL9XLL7/stkjpqlWr1KlTpzJt/f28qEot/P28cGratKkkqX///kpJSVGLFi00evToMu38/dyQPK+FGc6Nw4cPa86cOXrmmWcUEhJSYTsznBee1sIM50VNMOfiN17QokULj9qdPHmyzIkcHByswsLC2uiWT3hai+LiYiUkJOiBBx7Q5Zdfrg0bNui+++5TkyZNNGzYsFrupXcZhqFnn31Wn332mZYuXVpmvxnOC6dz1cJM54UkrV69WgUFBZo2bZomT56sl19+2W2/mc6Nc9XC388Nh8Oh6dOn64477lCHDh0qbevv50VVauHv50VNYQTQx0JCQspc3Gyz2dSkSRMf9ch3Ro0apZdfflmxsbEKCgpSv379NGrUKK1YscLXXatRJ06c0OTJk5WZmamlS5eqffv2ZdqY5bzwpBZmOS+cgoOD1apVK02fPl1ffvmlCgoK3Pab5dyQzl0Lfz83XnzxRTVs2FBjx449Z1t/Py+qUgt/Py9qCgHQx2JiYvTjjz+6bduxY4cuv/xyH/XId959990yf0GLi4vVqFEjH/Wo5v3888+6/vrrdeLECb377rvlBh7JHOeFp7Uww3mRnZ2t5ORkFRcXu7YVFxcrKCiozKiOv58bVamFv58by5cv18aNG5WUlKSkpCR99NFH+uijj5SUlFSmrb+fF1Wphb+fFzXG13ehmEFld77u2LHDiI+PN7Kyslx3bsXHxxv/+9//vNxL76isFq+++qrRu3dv4/vvvzfsdrvx2WefGZ07dza++eYbL/eydhw9etQYMGCAMWvWLMNut1fa1t/Pi6rUwt/PC8MwjBMnThj9+/c3/vKXvxi//fabsXfvXuOGG24wUlNTy7T193OjKrUww7lxppkzZ1Z456u/nxdnq6wWZjsvqosA6AVnh56EhARj+fLlrtdffPGFce211xoJCQnG8OHDjTVr1viim15RWS0cDofxwgsvGAMHDjQ6d+5sDB8+3FixYoWvulrjXnnlFSMmJsbo0qWLkZCQ4PbLMMx1XlSlFv5+Xjj9+OOPxh133GEkJSUZAwcONBYsWGD89ttvhmGY69wwDM9rYZZzw+ns0GO28+JMldXCbOdFdfEsYAAAAJPhGkAAAACTIQACAACYDAEQAADAZAiAAAAAJkMABAAAMBkCIAAAgMkQAAEAAEyGAAgAAGAyBEAA9cbevXvVvn177d27t8bfu7CwUHfeeae6dOmi3//+92X2z5o1S506dVJiYqIOHz6sRYsWVfhg+vbt22vDhg2Vft6rr76qxMREj9oCQE0jAAKApK1bt+qrr77S559/rjfeeKPcNikpKdq0aZPCw8PP+/PuuOMObdq06bzfBwCqo4GvOwAA1bVv3z49/fTT2rBhgwIDA9WrVy/NnDlTLVu2lCStXbtWTz31lH7++WfFxMSoW7du+u9//6vXX3/d7X0+/vhjTZ06VZI0cOBAPfTQQ7rxxhvPu38HDhxQcnKy2zabzabExES9+eab5/3+AFBdBEAA9VJJSYn++Mc/Ki4uTqtXr5ZhGJo/f74mTJigf/3rX9q/f78mTJigOXPm6Prrr1dOTo4mTJigjh07lnmvq666SkuWLNG4ceOqNCr33XffKSkpqcL9rVq1cnu/NWvWaOrUqZo1a1bVviwA1DACIIB66dtvv9WePXv03nvvqWnTppKk+fPnq0ePHsrNzdW6devUsWNH3XzzzZKkpKQk3XTTTdqyZUuN9aFbt25lRhOl09cAnu2///2vpk6dqqeeekqdO3eusT4AQHVwDSCAeunw4cO68MILXeFPkpo2barmzZtr3759slqtat26tdsxbdu29XY3JUk//fST7rnnHk2ZMkVXXXWVT/oAAGciAAKol1q3bq0jR47oxIkTrm3Hjx/XkSNH1KJFC7Vu3Vq//PKL2zFnv/aG/Px8jR8/XsOHD9cf/vAHr38+AJSHAAigXoqPj9dll12m1NRUHT9+XMePH9e8efN0ySWXqGvXrho5cqS2bt2qDz74QHa7XZs3b9a//vUvr/axsLBQd999tzp27KiHHnrIq58NAJUhAAKolxo0aKAXX3xRp06d0tChQzVw4ECVlJTo1VdfVYMGDRQREaHnnntOS5YsUVJSkp588kn169dPQUFBXuvj6tWrtWXLFm3YsEHdu3dXYmKi6xcA+BI3gQCoN9q0aaMffvjB9ToyMlILFy4st63ValWLFi2UlZXl2vbEE09U+N49e/Z0e+9zue+++yrcd+b7jBo1yuP3BABvYQQQgF86cuSIbrvtNuXm5kqStm3bpg8//FADBw70cc8AwPcIgAD8UmxsrObMmaOpU6cqMTFR9913n+6++26NGDGi2u+ZmZnpehTc+XI+Cg4AfCHAMAzD150AAACA9zACCAAAYDIEQAAAAJMhAAIAAJgMARAAAMBkCIAAAAAmQwAEAAAwGQIgAACAyRAAAQAATIYACAAAYDIEQAAAAJMhAAIAAJgMARAAAMBkCIAAAAAmQwAEAAAwGQIgAACAyRAAAQAATIYACAAAYDL/H5OY0IZ/93F6AAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "id": "1296e8fa",
   "metadata": {},
   "source": [
    "**ROI selected for fitting**\n",
    "\n",
    "![diel_loss_cond_plot.png](attachment:diel_loss_cond_plot.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "67455e73",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "enter the beta value:0.7\n",
      "enter the gamma value:0.35\n",
      "enter the fm:3.85\n",
      "enter the deps:3.2\n",
      "enter the cond:10\n",
      "enter the s:1\n",
      "dumped_parameters {'beta': 0.7, 'gamma': 0.35, 'freq': 7079.457843841381, 'deps': 3.2, 'cond': 10.0, 'n': 1.0}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dump the initial guess parameters using dump parameters method (varies for each fn), which dumps the parameters in a json file'\n",
    "#this is required before performing the first fitting as it takes the initial guess from the json file created\n",
    "\n",
    "hn.dump_parameters_hn()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8462132c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loaded parameters \n",
      " {'beta': 0.7, 'gamma': 0.35, 'freq': 7079.457843841381, 'deps': 3.2, 'cond': 10.0, 'n': 1.0}\n"
     ]
    }
   ],
   "source": [
    "# view the initial fit based on the dumped parameters\n",
    "# the plot is shown as a image in the next cell\n",
    "\n",
    "hn.initial_view_hn(x1,y1)"
   ]
  },
  {
   "attachments": {
    "initial_guess_cond.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "af51443d",
   "metadata": {},
   "source": [
    "**Plot of the initial fit based on the supplied parameters**\n",
    "\n",
    "![initial_guess_cond.png](attachment:initial_guess_cond.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5eac2052",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Choose the fit function\n",
      " 1 -- HN, 2 -- HN with cond, 3 -- Hn-flank, 4 -- double HN, 5 -- double HN with cond:2\n",
      "0.8032582310807094 0.23705517267041565 1429.0416095139626 3.6780528141976907 4.81979373031708 0.9999999999999999\n",
      "log fmax: 3.841362413197138\n",
      "fit parameters dumped for next iteration {'beta': 0.8032582310807094, 'gamma': 0.23705517267041565, 'freq': 1429.0416095139626, 'deps': 3.6780528141976907, 'cond': 4.81979373031708, 'n': 0.9999999999999999}\n"
     ]
    }
   ],
   "source": [
    "# perform least squares fitting\n",
    "# the plot is shown as a image in the next cell\n",
    "\n",
    "hn.fit(x1,y1)"
   ]
  },
  {
   "attachments": {
    "fit_example_cond.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "154e19bc",
   "metadata": {},
   "source": [
    "**Plot of the final fit**\n",
    "\n",
    "![fit_example_cond.png](attachment:fit_example_cond.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c84bc03e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Do you want to use an existing file to save fit results? \n",
      " eg: existing file to save HN parameters, y or n:n\n",
      "Choose the fit function\n",
      " 1 -- HN, 2 -- HN with cond, 3 -- HN-flank, 4 -- double HN, 5 -- double HN with cond:2\n",
      "Enter the analysis_file_name:hn_cond_fit.TXT\n",
      "file did not exist, created hn_cond_fit.TXT\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# before saving fit results an analysis file has to be created using create_analysis file methodd\n",
    "\n",
    "hn.create_analysis_file()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2b338cb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#save the fit results using save_fit method of the corresponding fit function\n",
    "#takes one argument, read more on the documentation\n",
    "\n",
    "hn.save_fit_hn(1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "78633690",
   "metadata": {},
   "source": [
    "## Fitting example for double HN function\n",
    "**We will now look at an example to fit two HN functions using a new datafile**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cb07b1ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = 'double_hn_example_data.txt'\n",
    "col_names = ['log f', 'log eps2']\n",
    "df2 = pd.read_csv(filename, sep=',',index_col=False,usecols = [0,1],names=col_names,header=None,skiprows=2,encoding='unicode_escape',engine='python')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "bd943e54",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_lower_limit 0.12476912070759627 x_upper_limit 4.0548939906347545\n"
     ]
    }
   ],
   "source": [
    "#select range\n",
    "# select peak along with conductivity slope\n",
    "hn = dd.HN()\n",
    "x,y = df2['log f'], df2['log eps2']\n",
    "x1,y1 = hn.select_range(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6dfb4c19",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Example for fitting HN with conducitivity')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# view the selected data\n",
    "plt.scatter(x1,y1,label='example data')\n",
    "plt.xlabel('log f [Hz]')\n",
    "plt.ylabel('log $\\epsilon$\"')\n",
    "plt.legend()\n",
    "plt.title('Example for fitting double HN function')"
   ]
  },
  {
   "attachments": {
    "ROI_double%20HN.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "a41b60e5",
   "metadata": {},
   "source": [
    "**ROI selected for fitting**\n",
    "![ROI_double%20HN.png](attachment:ROI_double%20HN.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "642a60f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "enter the beta1 value:0.5\n",
      "enter the gamma1 value:1\n",
      "enter the fmax1:0.76\n",
      "enter the deps1:0.35\n",
      "enter the beta2 value:0.5\n",
      "enter the gamma2 value:1\n",
      "enter the fmax2:3.25\n",
      "enter the deps2:0.7\n",
      "enter the cond:0\n",
      "enter the s:1\n",
      "dumped_parameters {'beta1': 0.5, 'gamma1': 1.0, 'freq1': 5.7543993733715695, 'deps1': 0.35, 'beta2': 0.5, 'gamma2': 1.0, 'freq2': 1778.2794100389228, 'deps2': 0.7, 'cond': 0.0, 'n': 1.0}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#dump the initial guess parameters using dump parameters method (varies for each fn), which dumps the parameters in a json file'\n",
    "#this is required before performing the first fitting as it takes the initial guess from the json file created\n",
    "\n",
    "hn.dump_parameters_double_hn()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "617d0444",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loaded parameters \n",
      " {'beta1': 0.5, 'gamma1': 1.0, 'freq1': 5.7543993733715695, 'deps1': 0.35, 'beta2': 0.5, 'gamma2': 1.0, 'freq2': 1778.2794100389228, 'deps2': 0.7, 'cond': 0.0, 'n': 1.0}\n"
     ]
    }
   ],
   "source": [
    "# view the initial fit based on the dumped parameters\n",
    "# the plot is shown as a image in the next cell\n",
    "\n",
    "hn.initial_view_double_hn(x1,y1)"
   ]
  },
  {
   "attachments": {
    "initial_guess_double%20HN.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "6c8ebe43",
   "metadata": {},
   "source": [
    "**Plot of the initial fit based on the supplied parameters**\n",
    "![initial_guess_double%20HN.png](attachment:initial_guess_double%20HN.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a20565ee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Choose the fit function\n",
      " 1 -- HN, 2 -- HN with cond, 3 -- Hn-flank, 4 -- double HN, 5 -- double HN with cond:4\n",
      "[0.5, 1.0, 5.7543993733715695, 0.35, 0.5, 1.0, 1778.2794100389228, 0.7]\n",
      "log fmax1: 0.6528760482656042 \n",
      "log fmax2: 3.3454996773912202\n",
      "fit parameters dumped for next iteration {'beta1': 0.5574923893637207, 'gamma1': 0.32191102439091196, 'freq1': 0.6634391099941143, 'deps1': 0.6070123067438288, 'beta2': 0.9684862515337489, 'gamma2': 0.19288873795787148, 'freq2': 539.4342107551406, 'deps2': 0.37175853830216565, 'cond': 0, 'n': 1}\n"
     ]
    }
   ],
   "source": [
    "# perform least squares fitting\n",
    "# the plot is shown as a image in the next cell\n",
    "\n",
    "hn.fit(x1,y1)"
   ]
  },
  {
   "attachments": {
    "fit_example_double%20HN.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "4b66eacf",
   "metadata": {},
   "source": [
    "**Plot of the final fit**\n",
    "![fit_example_double%20HN.png](attachment:fit_example_double%20HN.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "918f1d05",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Do you want to use an existing file to save fit results? \n",
      " eg: existing file to save HN parameters, y or n:n\n",
      "Choose the fit function\n",
      " 1 -- HN, 2 -- HN with cond, 3 -- HN-flank, 4 -- double HN, 5 -- double HN with cond:4\n",
      "Enter the analysis_file_name:double_HN_fit.TXT\n",
      "file did not exist, created double_HN_fit.TXT\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# before saving fit results an analysis file has to be created using create_analysis file method\n",
    "\n",
    "hn.create_analysis_file()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c0f07bcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#save the fit results using save_fit method of the corresponding fit function\n",
    "#takes one argument, read more on the documentation\n",
    "\n",
    "hn.save_fit_double_HN(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f308af88",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
