20250114_fft_ops_PR.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3ef0fed7-1cdc-4b2a-b5a2-66647d5688a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import sys\n",
    "import scipy\n",
    "sys.path.insert(0, \"/so/home/jsugiyama/git/sotodlib/\")\n",
    "import sotodlib\n",
    "from sotodlib.tod_ops import fft_ops, detrend_tod\n",
    "from sotodlib import core\n",
    "from sotodlib import hwp\n",
    "from sotodlib.io import load_smurf as ls\n",
    "from sotodlib.io.load_smurf import Observations, Files, TuneSets, Tunes\n",
    "from sotodlib.io import g3tsmurf_utils\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "614df904-08c2-4478-9bbb-eeb68ec71555",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:00:58.033336\n"
     ]
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "ctx_file = '/so/metadata/satp3/contexts/use_this.yaml'\n",
    "ctx = core.Context(ctx_file)\n",
    "obs_id = 'obs_1709601492_satp3_1111111'\n",
    "ws = 'ws0'\n",
    "bandpass = 'f150'\n",
    "debug = 1000\n",
    "meta = ctx.get_meta(obs_id, dets={'wafer_slot': ws, 'wafer.bandpass': bandpass})\n",
    "meta.restrict('dets', meta.dets.vals[:debug])\n",
    "aman = ctx.get_obs(meta)\n",
    "for idet in range(aman.dets.count) : \n",
    "    aman.signal[idet] *= aman.det_cal.phase_to_pW[idet]\n",
    "alive = np.where(np.any(np.isnan(aman.signal), axis=1)==False)\n",
    "aman.restrict('dets', aman.dets.vals[alive])\n",
    "detrend_tod(aman)\n",
    "signal=aman.signal\n",
    "freqs, pxx = fft_ops.calc_psd(\n",
    "            aman, signal=signal, timestamps=aman.timestamps, max_samples=2**20, merge=True, nperseg=len(aman.timestamps)\n",
    "        )\n",
    "stop = datetime.datetime.now()\n",
    "print(stop - start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7d8e8c37-fa74-402c-b271-a35deb157ec4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AxisManager(timestamps[samps], ancil*[samps], boresight*[samps], signal[dets,samps], biases[bias_lines,samps], primary*[samps], iir_params*, flags*[dets,samps], obs_info*, det_cal*[dets], pointing_model*, focal_plane*[dets], hwp_angle_model*, hwp_solution*[samps], abscal*[dets], det_info*[dets], freqs[nusamps], Pxx[dets,nusamps], dets:LabelAxis(661), samps:OffsetAxis(741367), bias_lines:LabelAxis(12), nusamps:OffsetAxis(370684))"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "aman"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce97d6c4-253e-471e-ac4c-c66140d23bf8",
   "metadata": {},
   "source": [
    "# New features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2502e7f5-144c-475a-97ae-63ecf996608c",
   "metadata": {},
   "source": [
    "* PSD mask\n",
    "    * Masking HWPSS or vibration signals makes the fitting stable\n",
    "* PSD binning\n",
    "    * Fitting becomes about 25 times faster than without binning\n",
    "    * Knee frequency and white noise level are unbiased\n",
    "    * The standard errors of the fit parameters become smaller\n",
    "* Other changes in the fitting functions\n",
    "    * Fitting parameters can be reduced (white noise or alpha can be fixed)\n",
    "    * Minimum frequency for the fit can be decrared\n",
    "    * IndexError Exception is added to the Hessian calculation. IndexError occurs when the 1/f fit fails in the case where, for example, the signal is nan."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7a8b02f-9cae-4dc8-8cff-66f42881c036",
   "metadata": {},
   "source": [
    "# \"calc_psd_mask\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f34ece7-28e7-4495-8943-dbf35b530523",
   "metadata": {},
   "source": [
    "``calc_psd_mask`` returns Ranges array to mask hwpss or single peak in the given PSD.\\\n",
    "If mode == \"replace\", it will return new mask in aman.PSD_mask.\\\n",
    "If mode == \"add\", new mask range will be added to the existing aman.PSD_mask.\n",
    "You can obtain masked PSD like:\\\n",
    "\"\"\"\\\n",
    "mask = ~aman.PSD_mask.mask()\\\n",
    "f = f[mask]\\\n",
    "pxx = pxx[:, mask]\\\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "13f3672e-afe8-44cb-b75b-779e8946ff61",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:00:00.126438\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "plt.figure()\n",
    "plt.loglog(aman.freqs, np.sqrt(aman.Pxx[0]), alpha=0.4, label=\"No mask\")\n",
    "# create hwpss mask\n",
    "fft_ops.get_psd_mask(aman, mask_hwpss=True, hwpss_width=((-0.4, 0.6),(-0.2, 0.2)), merge=True)\n",
    "mask = ~aman.psd_mask.mask()\n",
    "plt.loglog(aman.freqs[mask], np.sqrt(aman.Pxx[0][mask]), alpha=0.4, label=\"HWPSS mask\")\n",
    "\n",
    "# add single peak mask\n",
    "fft_ops.get_psd_mask(aman, psd_mask=aman.psd_mask.mask(),mask_peak=True, peak_freq=28, peak_width=(-5, +5), merge=True)\n",
    "mask = ~aman.psd_mask.mask()\n",
    "plt.loglog(aman.freqs[mask], np.sqrt(aman.Pxx[0][mask]), alpha=0.4, label=\"HWPSS+single mask\")\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Detected ASD (pW/$\\sqrt{Hz}$)')\n",
    "plt.legend()\n",
    "stop = datetime.datetime.now()\n",
    "print(stop - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d467846-e009-42e4-8d3c-1038469f65d0",
   "metadata": {},
   "source": [
    "# \"fit_noise_model\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9dffe3b-1837-4e3d-885a-12ec5824989b",
   "metadata": {},
   "source": [
    "New feature of fit_noise_model is that\n",
    "* Fit PSD with masks if ``mask``==True and PSD_mask in aman,\n",
    "* Parameters of white noise or alpha can be fixed to the initially estimated value. For example, we experimentally know that fixing alpha is good for fitting demodulated signals.\n",
    "* ``fft_ops.calc_wn`` returns \n",
    "* ``f_min`` has been added to limit the minimum frequency to fit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "fc40d7a1-ad33-4271-9b2c-ab34f56f4fc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "wn_initial_val = fft_ops.calc_wn(aman, pxx=aman.Pxx, freqs=aman.freqs, low_f=5, high_f=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "9c75cec0-696c-4654-82b2-6b1bc9048cb3",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:02:27.706427\n"
     ]
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "noise_fit_stats_fixed_wn = fft_ops.fit_noise_model(aman, \n",
    "                                                   f=aman.freqs, \n",
    "                                                   pxx=aman.Pxx, \n",
    "                                                   f_min=0.001, \n",
    "                                                   f_max=20, \n",
    "                                                   mask=True,\n",
    "                                                   wn_est=wn_initial_val,\n",
    "                                                   fixed_param=\"wn\")\n",
    "stop = datetime.datetime.now()\n",
    "print(stop - start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "28f65af0-1a10-4146-ad97-a1b5d8fedfb5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:02:29.637383\n"
     ]
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "noise_fit_stats_fixed_alpha = fft_ops.fit_noise_model(aman, \n",
    "                                                      f=aman.freqs, \n",
    "                                                      pxx=aman.Pxx, \n",
    "                                                      f_min=0.001, \n",
    "                                                      f_max=20, \n",
    "                                                      mask=True, \n",
    "                                                      fknee_est=1,\n",
    "                                                      wn_est=4E-5,\n",
    "                                                      alpha_est=3.4,\n",
    "                                                      fixed_param=\"alpha\")\n",
    "stop = datetime.datetime.now()\n",
    "print(stop - start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "b1eaff6b-ca8d-42db-8605-e59339c308c9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:05:14.785386\n"
     ]
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "noise_fit_stats_all_params = fft_ops.fit_noise_model(aman, \n",
    "                                                     f=aman.freqs, \n",
    "                                                     pxx=aman.Pxx, \n",
    "                                                     f_min=0.001, \n",
    "                                                     f_max=20,\n",
    "                                                     fknee_est=1,\n",
    "                                                     wn_est=wn,\n",
    "                                                     alpha_est=3.2,\n",
    "                                                     mask=True)\n",
    "stop = datetime.datetime.now()\n",
    "print(stop - start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "ea3d6bfc-aca8-4bbe-971b-a1b3c99932d8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: divide by zero encountered in divide\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7ff159be1f30>"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.loglog(aman.freqs[mask], aman.Pxx[0][mask], alpha=0.4, label=\"HWPSS+single mask\")\n",
    "\n",
    "noise_fit_stats = noise_fit_stats_fixed_wn\n",
    "plt.loglog(aman.freqs, fft_ops.noise_model(aman.freqs, noise_fit_stats.fit[0]), label=\"fit (fixed wn)\")\n",
    "\n",
    "noise_fit_stats = noise_fit_stats_fixed_alpha\n",
    "plt.loglog(aman.freqs, fft_ops.noise_model(aman.freqs, noise_fit_stats.fit[0]), label=\"fit (fixed alpha)\")\n",
    "\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "plt.loglog(aman.freqs, fft_ops.noise_model(aman.freqs, noise_fit_stats.fit[0]),\"--\",  label=\"fit (free params)\")\n",
    "\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Detected ASD (pW/$\\sqrt{Hz}$)')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "a67af9ae-02b9-4fff-8a49-199d36bdce6f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7ff151e4e560>"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15, 5))\n",
    "ax1 = fig.add_subplot(1, 3, 1)\n",
    "ax1.set_title(\"f_knee\")\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "f_knee = noise_fit_stats.fit.T[1]\n",
    "ax1.hist(f_knee[((f_knee>0)&(f_knee<2))], bins=100, label=\"free params\")\n",
    "noise_fit_stats = noise_fit_stats_fixed_wn\n",
    "f_knee = noise_fit_stats.fit.T[1]\n",
    "ax1.hist(f_knee[((f_knee>0)&(f_knee<2))], bins=100, label=\"fixed wn\")\n",
    "noise_fit_stats = noise_fit_stats_fixed_alpha\n",
    "f_knee = noise_fit_stats.fit.T[1]\n",
    "ax1.hist(f_knee[((f_knee>0)&(f_knee<2))], bins=100, label=\"fixed alpha\")\n",
    "ax1.set_xlabel('f_knee (Hz)')\n",
    "ax1.legend()\n",
    "\n",
    "ax2 = fig.add_subplot(1, 3, 2)\n",
    "ax2.set_title(\"alpha\")\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "alpha = noise_fit_stats.fit.T[2]\n",
    "ax2.hist(alpha[((alpha>0)&(alpha<4))], bins=100, label=\"free params\")\n",
    "noise_fit_stats = noise_fit_stats_fixed_wn\n",
    "alpha = noise_fit_stats.fit.T[2]\n",
    "ax2.hist(alpha[((alpha>0)&(alpha<4))], bins=100, label=\"fixed wn\")\n",
    "\n",
    "ax2.set_xlabel('alpha')\n",
    "ax2.legend()\n",
    "\n",
    "ax3 = fig.add_subplot(1, 3, 3)\n",
    "ax3.set_title(\"white noise level\")\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "wn = noise_fit_stats.fit.T[0]\n",
    "ax3.hist(wn[wn<0.0001], bins=100, label=\"free params\")\n",
    "noise_fit_stats = noise_fit_stats_fixed_wn\n",
    "wn = noise_fit_stats.fit.T[0]\n",
    "ax3.hist(wn[wn<0.0001], bins=100, label=\"fixed wn\")\n",
    "noise_fit_stats = noise_fit_stats_fixed_alpha\n",
    "wn = noise_fit_stats.fit.T[0]\n",
    "ax3.hist(wn[wn<0.0001], bins=100, label=\"fixed alpha\")\n",
    "\n",
    "ax3.set_xlabel('pW/$\\sqrt{Hz}$')\n",
    "ax3.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34e21721-a4e2-48fd-8ce4-08e355ced70a",
   "metadata": {
    "tags": []
   },
   "source": [
    "# \"get_binned_psd\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4dbb333-4b17-4326-83f2-6a3ef243e6ca",
   "metadata": {},
   "source": [
    "``get_binned_psd`` returns the binned PSD. This function is incorporated to ``fit_noise_model``.\\\n",
    "The parameters ``unbinned_mode`` and ``base`` changes the number of first un-binned modes and binning width, respectively.\\\n",
    "If the number of data points in a bin is less than ``limit_N``, that bin is handled with\n",
    "chi2 distribution and its error is \\<psd>. Otherwise the central limit theorem\n",
    "is applied to the bin and the error is estimated as  std(psd)/sqrt(len(psd))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "c5254835-ca9d-442e-9403-b03dba678810",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:00:02.277896\n"
     ]
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "mask = ~aman.psd_mask.mask()\n",
    "f = aman.freqs[mask]\n",
    "pxx = aman.Pxx[:, mask]\n",
    "f_binned, pxx_binned, bin_size = fft_ops.get_binned_psd(aman, f=f, pxx=pxx, unbinned_mode=3, base=1.2, merge=False)\n",
    "stop = datetime.datetime.now()\n",
    "print(stop - start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "4bbc04f3-ec3c-40e3-ad99-14c339c8f137",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0001, 50)"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.loglog(aman.freqs[mask], np.sqrt(aman.Pxx[0][mask]), alpha=0.4, label=\"HWPSS+single mask\")\n",
    "plt.scatter(f_binned, np.sqrt(pxx_binned[0]), c='tab:orange', label=\"binned\")\n",
    "plt.legend()\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Detected ASD (pW/$\\sqrt{Hz}$)')\n",
    "plt.xlim(1E-4, 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a378447-eecd-4f9a-8513-efe6c43fa424",
   "metadata": {
    "tags": []
   },
   "source": [
    "You can quickly utilize binning when binning=True is assigned in fit_noise_model.\\\n",
    "The calculation time cost becomes much smaller."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "d755bbdc-6665-4b66-84b4-67486011181d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:00:08.772663\n"
     ]
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "noise_fit_stats_bin = fft_ops.fit_noise_model(aman, \n",
    "                                              f=aman.freqs, \n",
    "                                              pxx=aman.Pxx, \n",
    "                                              f_min=0.001, \n",
    "                                              f_max=20, \n",
    "                                              fknee_est=1,\n",
    "                                              wn_est=4E-5,\n",
    "                                              alpha_est=3.4,\n",
    "                                              mask=True, \n",
    "                                              binning=True,\n",
    "                                              unbinned_mode=1, base=1.2)\n",
    "stop = datetime.datetime.now()\n",
    "print(stop - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbd04871-3d7a-4073-8496-07d56d2eac72",
   "metadata": {},
   "source": [
    "## Example of the fastest fit operation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b22638cc-02e4-418d-a627-991f0ed96672",
   "metadata": {},
   "source": [
    "Get binned PSD --> estimate white noise --> fit PSD will be the fastest but will have larger fit error.\\\n",
    "Just do binning without parameter fix, which is calculated in the former cell, is the second fastest and returns same result as unbinned procedure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "0a987734-60a9-46f9-87be-d46bb6778685",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n",
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: invalid value encountered in power\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0:00:06.645676\n"
     ]
    }
   ],
   "source": [
    "start = datetime.datetime.now()\n",
    "\n",
    "# get mask and binned PSD\n",
    "fft_ops.get_psd_mask(aman, mask_hwpss=True, hwpss_width=((-0.4, 0.6),(-0.2, 0.2)), merge=True)\n",
    "mask = ~aman.psd_mask.mask()\n",
    "f = aman.freqs[mask]\n",
    "pxx = aman.Pxx[:, mask]\n",
    "f_binned, pxx_binned, bin_size = fft_ops.get_binned_psd(aman, f=f, pxx=pxx, unbinned_mode=3, base=1.05, merge=True)\n",
    "\n",
    "# calculate white noise value\n",
    "wn_initial_val = fft_ops.calc_wn(aman, freqs=aman.freqs_bin, pxx=aman.Pxx_bin, low_f=5, high_f=10)\n",
    "\n",
    "# fit\n",
    "noise_fit_stats_bin_fixed_wn = fft_ops.fit_noise_model(aman, \n",
    "                                              f=aman.freqs_bin, \n",
    "                                              pxx=aman.Pxx_bin, \n",
    "                                              f_min=0.001, \n",
    "                                              f_max=20, \n",
    "                                              fknee_est=1,\n",
    "                                              wn_est=wn_initial_val,\n",
    "                                              alpha_est=3.4,\n",
    "                                              fixed_param=\"wn\")\n",
    "stop = datetime.datetime.now()\n",
    "print(stop - start)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a42a6ca-33f0-4606-98d5-933d55062a23",
   "metadata": {},
   "source": [
    "### comparison of fit results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "de1c54a3-3240-4b3c-bc65-1a293b787f27",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/so/home/jsugiyama/git/sotodlib/sotodlib/tod_ops/fft_ops.py:405: RuntimeWarning: divide by zero encountered in divide\n",
      "  return wn**2 * (1 + (fknee / f) ** alpha)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(0.0001, 50)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAksAAAG1CAYAAADpzbD2AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAC/IElEQVR4nOzdd1RURxvA4d/dpSwd6YgoYkfsvWPvxlhj1EhiNPYYv0TTjF2jRmPU2GONvcQeo7F3BUVFrAiiCKLSO+zu9wdhZaXLIorznMM5cnfunVkUeZl55x1JrVarEQRBEARBELIkK+oBCIIgCIIgvM1EsCQIgiAIgpADESwJgiAIgiDkQARLgiAIgiAIORDBkiAIgiAIQg5EsCQIgiAIgpADESwJgiAIgiDkQARLgiAIgiAIOdAr6gEUByqViidPnmBmZoYkSUU9HEEQBEEQ8kCtVhMTE0PJkiWRybKfPxLBkg48efIEZ2fnoh6GIAiCIAiv4dGjR5QqVSrb10WwpANmZmZA2hfb3Ny8iEcjCIIgCEJeREdH4+zsrPk5nh0RLJEW5AwcOJCwsDD09PSYOHEivXv3zvP96Utv5ubmIlgSBEEQhHdMbik0IlgC9PT0WLBgATVr1iQsLIzatWvTqVMnTExMinpogiAIgiAUMREsAY6Ojjg6OgJgZ2eHlZUV4eHhIlgSBEEQBKF4BEunTp1i7ty5eHt7ExISwl9//UX37t212ixZsoS5c+cSEhJC1apVWbBgAc2aNcv0LC8vL1QqlUjYFgSh0CmVSlJSUop6GIJQbOnr6yOXywv8nGIRLMXFxVGjRg0+/fRTevbsmen1rVu3MnbsWJYsWUKTJk1Yvnw5HTt2xM/Pj9KlS2vavXjxgk8++YRVq1bl2F9SUhJJSUmaz6Ojo3X3ZgRBKPbUajWhoaFERkYW9VAEodiztLTEwcGhQKV9JLVardbhmIqcJEmZZpYaNGhA7dq1Wbp0qeZalSpV6N69O7NmzQLSAqC2bdsyZMgQBg4cmGMfkydPZsqUKZmuR0VFiQRvQRByFRISQmRkJHZ2dhgbG4v6bIJQCNRqNfHx8YSFhWFpaalJt8koOjoaCwuLXH9+F4uZpZwkJyfj7e3Nt99+q3W9Xbt2nDt3Dkj7gnp6etKqVatcAyWA7777jnHjxmk+T996KAiCkBulUqkJlKytrYt6OIJQrBkZGQEQFhaGnZ3day/JFftg6fnz5yiVSuzt7bWu29vbExoaCsDZs2fZunUr1atXZ/fu3QBs2LCBatWqZflMQ0NDDA0NC3XcgiAUT+k5SsbGxkU8EkF4P6R/r6WkpIhgKTevTnOr1WrNtaZNm6JSqYpiWIIgvKfE0psgvBm6+F4r9gfp2tjYIJfLNbNI6cLCwjLNNgmCIAiCILyq2AdLBgYG1KlThyNHjmhdP3LkCI0bNy6iUQmCIAiC8K4oFsFSbGwsPj4++Pj4ABAQEICPjw9BQUEAjBs3jlWrVrF69Wpu3brFV199RVBQEMOGDSvCUQuCIAjvOg8PD8aOHavTZ544cQJJkt650hLv6rjzolgES15eXtSqVYtatWoBacFRrVq1+OmnnwDo27cvCxYsYOrUqdSsWZNTp05x8OBBypQpU5TDLlwqJRSvqhCCIBQxT0/PTAV/QfuHZGxsLPr6+mzdulWrTd++fZEkCX9/f63r5cqV4/vvvwfSyrJIkoQkScjlcpydnfn888959uyZpv3x48dp2bIlVlZWGBsbU6FCBQYNGkRqaqqmzfLly6lRowYmJiZYWlpSq1YtZs+ercOvxEu7du1i2rRphfJs4e1RLIIlDw8P1Gp1po+1a9dq2owYMYLAwECSkpLw9vamefPmRTfgN+HYdG5s7UV4REBRj0QQhPeIqakpdevW5fjx41rXT548ibOzs9b1x48f8+DBA1q2bKm5VrVqVUJCQggKCmLp0qXs27ePTz75BICbN2/SsWNH6tWrx6lTp7hx4waLFi1CX19fs0nnjz/+YNy4cYwZM4Zr165x9uxZxo8fT2xsbLZj9vT0ZPLkya/1fq2srHI9sV549xWLYEl4RXQILy4uYXTcLXru7sq5KyuLekSCIOQiVakqko/C0LJlS06cOKH5/NatWyQkJDBixAit68ePH0dfX58mTZporunp6eHg4ICTkxNdunRhzJgxHD58mISEBI4cOYKjoyNz5szB3d2dcuXK0aFDB1atWoWBgQEA+/bto0+fPgwePJjy5ctTtWpV+vXrV6DZnyVLllChQgUUCgX29vb06tVL89qry3AuLi7MnDmTzz77DDMzM0qXLs2KFSu0nnfu3Dlq1qyJQqGgbt267N69G0mSNKkkWTl37hzNmzfHyMgIZ2dnxowZQ1xcXLbtJ0+eTM2aNVm9ejWlS5fG1NSU4cOHo1QqmTNnDg4ODtjZ2TFjxgyt++bPn0+1atUwMTHB2dmZESNGaAWaDx8+pGvXrpQoUQITExOqVq3KwYMHsxxDQkICnTt3pmHDhoSHh2c71nfBe1M64L1i7khM7zWUODOB+zL44sZCBgYcYmzX9RgYiMOBBeFtk6pUsc3rcZH03aduKfTkuv29uWXLlsyaNYuQkBAcHR05fvw4zZo1o1WrVixevFjT7vjx4zRo0CDHmlNGRkaoVCpSU1NxcHAgJCSEU6dOZbs64ODgwMmTJ3n48KFOUi28vLwYM2YMGzZsoHHjxoSHh3P69Okc75k3bx7Tpk3j+++/Z8eOHQwfPpzmzZtTuXJlYmJi6Nq1K506dWLTpk08fPgw15ynGzdu0L59e6ZNm8Yff/zBs2fPGDVqFKNGjWLNmjXZ3ufv78/ff//NoUOH8Pf3p1evXgQEBFCxYkVOnjzJuXPn+Oyzz2jdujUNGzYEQCaTsXDhQlxcXAgICGDEiBGMHz+eJUuWADBy5EiSk5M5deoUJiYm+Pn5YWpqmqnvqKgounTpgkKh4OjRo+/8wfRiZqmYcqnYic19j/ORQUkANsTe5eNNTXnw8FQRj0wQhHfZ/v37MTU11fro2LGjVpsmTZqgr6+vmUU6ceIELVq0oHbt2kRFRXHv3j3N9YxLcK+6ffs2S5cupX79+piZmdG7d2/69etHixYtcHR05MMPP2Tx4sVa53NOmjQJS0tLXFxcqFSpEp6enmzbtu21a+kFBQVhYmJCly5dKFOmDLVq1WLMmDE53tOpUydGjBhB+fLlmTBhAjY2NpqvxcaNG5EkiZUrV+Lm5kbHjh355ptvcnze3Llz+fjjjxk7diwVKlSgcePGLFy4kPXr15OYmJjtfSqVitWrV+Pm5kbXrl1p2bIld+7cYcGCBVSqVIlPP/2USpUqac32jR07lpYtW1K2bFlatWrFtGnT2LZtm9bXo0mTJlSrVg1XV1e6dOmSKXB9+vQpLVq0wM7OjgMHDrzzgRKImaViTWFiww/9/qHJmVn8dPdP7shT6XtsBN+U7kTvVrNFUTxBeEvoyWX0qVuqyPrOj5YtW2qdswlw8eJFBgwYoPnc2NiY+vXrc+LECfr168fJkyf55ptv0NPTo0mTJpw4cQJDQ0MCAgJo1aqV1rNu3LiBqakpSqWSpKQkPDw8NMtYcrmcNWvWMH36dI4dO8aFCxeYMWMGs2fP5tKlSzg6OuLo6Mj58+fx9fXVzJ4MGjSIVatWcejQIWQyGRs3buSLL77Q9JmUlIQkSfzyyy+aa8uXL6d///60bduWMmXK4OrqSocOHejQoQMffvhhjrNh1atX1/xZkiQcHBwICwsD4M6dO1SvXh2FQqFpU79+/Ry/5t7e3ty/f5+NGzdqrqnValQqFQEBAVSpUiXL+1xcXLTyqezt7ZHL5chkMq1r6WODtNm+mTNn4ufnR3R0NKmpqSQmJhIXF4eJiQljxoxh+PDhHD58mDZt2tCzZ0+t9wvQpk0b6tWrx7Zt2167YvbbRswsvQc8mn7Hzk4baaQ2JFEm4XNrB9KuoZAYnfvNgiC8EXpyWZF85JeJiQnly5fX+nBycsrUrmXLlhw/fpybN2+SkJBA7dq1AWjRogXHjx/n+PHjKBQKzfJPukqVKuHj44Ofnx8JCQkcO3aM8uXLa7VxcnJi4MCB/P777/j5+ZGYmMiyZcu02ri7uzNy5Eg2btzIkSNHOHLkCCdPngSgW7dumnIzPj4+dOvWjWHDhmW6BmBmZsaVK1fYvHkzjo6O/PTTT9SoUSPH7fH6+vpan0uSpJnZynh6RLrczrNXqVR88cUXWuO7du0a9+7do1y5cvkaR05je/jwIZ06dcLd3Z2dO3fi7e3N77//Drw8pufzzz/nwYMHDBw4kBs3blC3bl0WLVqk9czOnTtz+vRp/Pz8cnxf7xIxs/SesHWoybIB59jx9wg6PfwLnm+DRxdR9ViBrHTD3B8gCIKQDy1btmT69Ols2rSJpk2bamYYWrRowaJFizA0NKRRo0ZaMyyQVkj41eAoJyVKlMDR0THHZGc3NzcATRszMzOtGRczMzOsrKyy7VdPT482bdrQpk0bzTLfsWPH6NGjR57Hma5y5cps3LiRpKQkzRmjXl5eOd5Tu3Ztbt68ma+vy+vw8vIiNTWVefPmaWafMi7BpXN2dmbYsGEMGzaM7777jpUrVzJ69GjN6z///DOmpqa0bt2aEydOaL7+7zIxs/QekekZ0KfrKkw9D4JladSRD/nywAB+/esjUlKyX/cWBEHIr8aNG2NoaMiiRYto0aKF5nq9evWIiopi586dOeYrZWX58uWaJSB/f39u3rzJhAkTuHnzJl27dgVg+PDhTJs2jbNnz/Lw4UMuXLjAJ598gq2tLY0aNcr3+9i/fz8LFy7Ex8eHhw8fsn79elQqFZUqVcr3swA+/vhjVCoVQ4cO5datW/zzzz+a5b/sUiMmTJjA+fPnGTlyJD4+Pty7d4+9e/dqBSi6UK5cOVJTU1m0aBEPHjxgw4YNmWbsxo4dyz///ENAQABXrlzh2LFjWS4D/vLLL/Tv359WrVpx+/ZtnY6zKIhg6X1UugEMO8PlKu04YWzE6uibDNzYmIePLxT1yARBKCbSl9hiYmLw8PDQXNfX16dRo0bExMTkO1iqX78+sbGxDBs2jKpVq9KiRQsuXLjA7t27NQFZmzZtuHDhAr1796ZixYr07NlTsyPL2to63+/D0tKSXbt20apVK6pUqcKyZcvYvHkzVatWzfezAMzNzdm3bx8+Pj7UrFmTH374QVNA+dVZtnTVq1fn5MmT3Lt3j2bNmlGrVi0mTpyIo6Pja40hOzVr1mT+/PnMnj0bd3d3Nm7cyKxZs7TaKJVKRo4cSZUqVejQoQOVKlXS7JR71a+//kqfPn1o1aoVd+/e1elY3zRJndtiqZCr6OhoLCwsiIqKwtzcvKiHky//npzCpAfbiJbJMFKp+d61Bx80nyKSvwWhkCQmJhIQEEDZsmWz/eEovF82btzIp59+SlRUFEZGRkU9nGInp++5vP78FjNL77k2LSaxs90a6qn0SZBJTAz8i/GbWxMdE1LUQxMEQSiW1q9fz5kzZwgICGD37t1MmDCBPn36iEDpLSaCJQEHp/qsHHCOL82roadWcyjlGV9taw9Prhb10ARBEIqd0NBQBgwYQJUqVfjqq6/o3bt3pirfwttFLMPpwLu8DPeqG9f/5Huvn5n+9Ck1UtTQeiI0Gg0yEVcLgi6IZThBeLPEMpygc9WqD2B33+PUcG0PqhQ48hP/bmjL45ArRT00QRAEQSgSIlgSMpGb2EKfDdB1IfeMzJigekrvQ59w4MyM3G8WBEEQhGJGBEtC1iQJ6gzCpN8Wqqr1iJVJfOu/he+3tCM2/llRj04QBEEQ3hgRLAk5Klm6KasHnGWEaSVkajX7kkLovbU112/vLuqhCYIgCMIbIYIlIVd6BiYM77mDtTXGUlKp5rFMzScXfmTVgSEg9gcIgiAIxZwIloQ8q1Xrc7Z/uJ+OkjlKSSL13iHY1AdixbKcIAiCUHyJYEnIF/MSLswecJrFpboyJCYJ7h2GpY2Ju72/qIcmCEIh8/DwYOzYsdm+7uLiwoIFC97YeHIiSRK7d+8u6mEIxYReUQ9AePdIMhktWs8E9wGwczBJz/wYePp/uF9bwrfdNmJsVKKohygI7wWlSs2lgHDCYhKxM1NQv6wVclnRHVV0+fJlTExMiqx/QSgsIlgSXp+9Gww5xsX9w7gf5c29xEdc2eLB7GazqFq+U1GPThCKtUO+IUzZ50dIVKLmmqOFgkld3ejgrtsDVvPK1ta2SPoVhMImluGKsYjt24k9e7ZwO9E3ovmH6/jDbTh2ShUPZSoGnBnPmkMjUKmUhdu3ILynDvmGMPzPK1qBEkBoVCLD/7zCId/CO9sxNTWVUaNGYWlpibW1NT/++CPpB0G8ugwnSRKrVq3iww8/xNjYmAoVKrB3717N6ydOnECSJI4ePUrdunUxNjamcePG3LlzR6vPffv2UadOHRQKBa6urkyZMoXU1FTN6/fu3aN58+YoFArc3Nw4cuRIob1/4f0kgqViKjkoiKfTZ/Bo8OcEjx9Panh4ofZXr/5Idn3wF20wIVWSmP/0NEP/bErYi7uF2q8gvG+UKjVT9vmR1T7U9GtT9vmhVBXOTtV169ahp6fHxYsXWbhwIb/++iurVq3Ktv2UKVPo06cP169fp1OnTvTv35/wV/4/+uGHH5g3bx5eXl7o6enx2WefaV77559/GDBgAGPGjMHPz4/ly5ezdu1aZsxIK5KrUqno0aMHcrmcCxcusGzZMiZMmFAo7114f4lgqZiSW1lh2bs3SBLRe/fxoGMnInfuojCPArSwrsj8AWeZbNccI5WKi+pYpu/8EAJOFVqfgvC+uRQQnmlGKSM1EBKVyKWAwvkFydnZmV9//ZVKlSrRv39/Ro8eza+//ppte09PT/r160f58uWZOXMmcXFxXLp0SavNjBkzaNGiBW5ubnz77becO3eOxMREzWvffvstgwYNwtXVlbZt2zJt2jSWL18OwL///sutW7fYsGEDNWvWpHnz5sycObNQ3rvw/hLBUjElNzXF4ccfcNm6BcPKlVFGRRHyww8EeX5KUkBAofUryeX07Pg7W5v9QoNUie+ehsC6bvDvZFCmFFq/gvC+CIvJPlB6nXb51bBhQyTpZRJ5o0aNuHfvHkpl1svu1atX1/zZxMQEMzMzwsLCsm3j6JiWb5Xextvbm6lTp2Jqaqr5GDJkCCEhIcTHx3Pr1i1Kly5NqVKltMYkCLokgqVizqh6dcpu34bdN18jKRTEX7xIYO8+KGNiCrXfsuU7smrgeRxrDADUcOZX1q5typ2Afwu1X0Eo7uzMFLk3yke7wqavr6/1uSRJqFSqbNukB2LpbVQqFVOmTMHHx0fzcePGDe7du4dCochytjxjMCcIuiB2w70HJH19rAcPxqx9e0InT8GoVk3kZmaF37GBCXRbCOVbc+afr5inF4/+ybGMu9+W/q3nIclErC4I+VW/rBWOFgpCoxKzzFuSAAeLtDICheHChQuZPq9QoQJyubxQ+qtduzZ37tyhfPnyWb7u5uZGUFAQT548oWTJkgCcP3++UMYivL/ET6v3iEGpUjivXIHNsGGaawnXrxMyaTLKqKjC69jtA9z676WFWkGKJDH7yb+M2NSc5xEPCq9PQSim5DKJSV3dgLTAKKP0zyd1dSu0ekuPHj1i3Lhx3Llzh82bN7No0SK+/PLLQukL4KeffmL9+vVMnjyZmzdvcuvWLbZu3cqPP/4IQJs2bahUqRKffPIJ165d4/Tp0/zwww+FNh7h/SSCpfeMJElI//0GqFapCJk0mcitW/Hv3IXogwcLLQHcys6dRQPP8711AwxVas4oo+i5+wNOX11ZKP0JQnHWwd2RpQNq42ChvdTmYKFg6YDahVpn6ZNPPiEhIYH69eszcuRIRo8ezdChQwutv/bt27N//36OHDlCvXr1aNiwIfPnz6dMmTIAyGQy/vrrL5KSkqhfvz6ff/65ZqecIOiKpC7M7VHviejoaCwsLIiKisLc3Lyoh5Mv8ZcvEzJpMskP0mZ5TFo0x2HiTxiUciq0Pu/d3s34cxO5/9+s/VDzqozu9ifIxaqwUPwlJiYSEBBA2bJlUSgKllf0tlXwFoS3UU7fc3n9+S1mlt5zxvXqUXb3X9iMGoWkr0/cyVM86NqVF6vXoM5Q9E2XKlTuzpa+x+hvkPbbb4X7J2FtJ4h4WCj9CUJxJZdJNCpnzQc1nWhUzloESoJQSESwJCAzMMB21EjK7tmNcb16qBMSCJszh5hCrIJraGLLt/0Os6PSUDqk6sGji7CsKSHefxRqLShBEARByC8RLAkahq6ulF6/DscZ0zFt0xqz9u0Lvc9KDUfDsNNQqj7PU2L56No8xmzyICL6UaH3LQiCIAh5IYIlQYskSVj27Inz4sWarf3K2DgCP+5PzLHjhdNpCRf49G+u1+lHjEzGidRweu7sxPnr6wunP0EQBEHIBxEsCbkKX7OGhCtXeDxiBI/HfEnK07Dcb8ovuR6tOi9hU92JuCrVPJPB0Ktzmb+7HykphVOJWBAEQRDyQgRLQq6sPx+M9ZDPQS4n5vBhHnTuTPimTahfqcKrC5Xd+7Kl97/00bMBYE2UL/03NiEw+KLO+xIEQRCEvBDBkpArmZERdv/7H2V37kBRvTqq2FieTp3Gw34fk3jnrs77MzJzYOLHx1hQ5kMslCpuScms2/sJ3Nqn874EQRAEITciWBLyTFG5Mi6bN2H/44/IjI1JuHaNF/+d/K1zkkRrj6nsbLeG7kpDvg57ClsHwL4vITmucPoUBEEQhCyIYEnIF0kux2pAf1wPHsC8a1fsvp2gea0w6jLZl6rPtE/OYdL4S0BC7b2Wyeua4HVzq877EgRBEISsiGBJeC36Dg44zZ2Dvp2d5lrwN98QPH48qeHhuu1MzwDaToFPdvOXTUl2Gij57PI0Fu4bREpqkm77EgQhW2q1mqFDh2JlZYUkSfj4+ODh4cHYsWNf63nHjh2jcuXKqDLkP65YsQJnZ2dkMhkLFizQzcDfU2FhYdja2hIcHFzUQ3nniWBJ0Imk+/eJOfQP0Xv38aBjJyJ37tJ9cUlXDzoMPEx3WQnUksTK8Ct4bmzKo9Cruu1HEIQsHTp0iLVr17J//35CQkJwd3dn165dTJs2TdPGxcUlz0HO+PHj+eGHH5D9V6YkOjqaUaNGMWHCBIKDgwv1zLn3gZ2dHQMHDmTSpElFPZR3ngiWBJ0wLF8el61bMKxcGWVUFCE//ECQ56ckBQTotB9jC2emDTjJXKdOmKlUXCeR3n8PZN/ZWTrtRxCEzPz9/XF0dKRx48Y4ODigp6eHlZUVZmZm+X7WuXPnuHfvHr1799ZcCwoKIiUlhc6dO+Po6IixsXGm+1JSUgr0HopCUY75008/ZePGjURERBTZGIoDESwJOmNUvTplt2/D7uv/ISkUxF+8SMAH3Xm2ZAnq5GTddSRJdGgzmx2tllFbKSdOJvH9/U38uu0DEDWZhHeRWp22caEoPvI4A+zp6cno0aMJCgpCkiRcXFwAtJbhPDw8ePjwIV999RWSJCFJ2Z9Vt2XLFtq1a6c52HTt2rVUq1YNAFdXVyRJIjAwkMmTJ1OzZk1Wr16Nq6srhoaGqNVqoqKiGDp0KHZ2dpibm9OqVSuuXbum1ce+ffuoU6cOCoUCV1dXpkyZQmoOuZWenp50796dKVOmaJ77xRdfkJzh/69Dhw7RtGlTLC0tsba2pkuXLvj7+2teDwwMRJIktm3bhoeHBwqFgj///JMXL17Qr18/SpUqhbGxMdWqVWPz5s1a/Xt4eDB69GjGjh1LiRIlsLe3Z8WKFcTFxfHpp59iZmZGuXLl+PvvvzX3RERE0L9/f2xtbTEyMqJChQqsWbNG83q1atVwcHDgr7/+yvZ9C7kTx7wLOiXp62P9+eeYdehA6OQpxJ05Q+S27Vh9Mgi5gYFO+ypZphmr+59l5b5PWBVzmzb3z8HKVtDrD7CrotO+BKFQpcTDzJJF0/f3T8DAJNdmv/32G+XKlWPFihVcvnwZuVyeqc2uXbuoUaMGQ4cOZciQITk+79SpU/Tr10/zed++fXF2dqZNmzZcunQJZ2dnbG1tAbh//z7btm1j586dmn47d+6MlZUVBw8exMLCguXLl9O6dWvu3r2LlZUV//zzDwMGDGDhwoU0a9YMf39/zbJeTstSR48eRaFQcPz4cQIDA/n000+xsbFhxowZAMTFxTFu3DiqVatGXFwcP/30Ex9++CE+Pj6a5USACRMmMG/ePNasWYOhoSGJiYnUqVOHCRMmYG5uzoEDBxg4cCCurq40aNBAc9+6desYP348ly5dYuvWrQwfPpzdu3fz4Ycf8v333/Prr78ycOBAgoKCMDY2ZuLEifj5+fH3339jY2PD/fv3SUhI0HpP9evX5/Tp03z22Wc5/p0I2RPBklAoDEqVwnnlCqIPHERuYY7cNO0/Y7VKhSouDvlrTNtnRW5owrBeO+l1cyc2BydA2E1Y4cGNZqOo0vRb9OT6OulHEN53FhYWmJmZIZfLcXBwyLKNlZUVcrkcMzOzbNukCwwMpGTJlwGikZER1tbWANja2mrdn5yczIYNGzTB07Fjx7hx4wZhYWEYGhoC8Msvv7B792527NjB0KFDmTFjBt9++y2DBg0C0marpk2bxvjx43MMlgwMDFi9ejXGxsZUrVqVqVOn8s033zBt2jRkMhk9e/bUav/HH39gZ2eHn58f7u7umutjx46lR48eWm2//vprzZ9Hjx7NoUOH2L59u1awVKNGDX788UcAvvvuO37++WdsbGw0wedPP/3E0qVLuX79Og0bNiQoKIhatWpRt25dAM2MX0ZOTk5cvSpyOwtCBEtCoZEkCYsunbWuRe7cybPfFuLw/XeYdeyY4zR9fthU7QllmsHu4dx9eBLPB1txf7ifWR1WU9Kuqk76EIRCo2+cNsNTVH0XgYSEBM0SXG7KlCmjCZQAvL29iY2N1QRXGZ+ZviTm7e3N5cuXNTNCAEqlksTEROLj47PMh4K0YCXja40aNSI2NpZHjx5RpkwZ/P39mThxIhcuXOD58+eanXxBQUFawVJ68JKx759//pmtW7cSHBxMUlISSUlJmJhoz+pVr15d82e5XI61tbVmeRLA3t4eSNvpBjB8+HB69uzJlStXaNeuHd27d6dx48ZazzQyMiI+Pj7L9yvkjQiWhDdGrVYTtesvlM+fEzzuf5js2YPDxJ8wKOWkmw5M7eDj7Tw59h36j/ZzRR1PrwN9+anKp3Ro+D/d9CEIhUGS8rQUVpzY2NjkOen41YBCpVLh6OjIiRMnMrW1tLTUtJkyZUqm2R0gz0FaRum/2HXt2hVnZ2dWrlxJyZIlUalUuLu7a+U1ZTXmefPm8euvv7JgwQKqVauGiYkJY8eOzXSfvr72bLgkSVrX0seRHqR17NiRhw8fcuDAAf79919at27NyJEj+eWXXzT3hIeHawWbQv6JBG/hjZEkidLr1mIzahSSvj5xJ0/xoGtXXqxeo7uCljIZHm1ms73Fb1RXSsTIJL65s5Yft3UmLkHsBhGEwmZgYIBSqcy1Xa1atfDz83utPmrXrk1oaCh6enqUL19e68PGxkbT5s6dO5leL1++vFZu0auuXbumlfNz4cIFTE1NKVWqFC9evODWrVv8+OOPtG7dmipVquQ54Dt9+jQffPABAwYMoEaNGri6unLv3r3Xev+vsrW1xdPTkz///JMFCxawYsUKrdd9fX2pVauWTvp6X4lgSXijZAYG2I4aSdk9uzGuWxd1QgJhc+YQ0KcPibdv66wfZ9c2rP34DF8YlUWmVrMnIYjeWzy4cf+gzvoQBCEzFxcXTp06RXBwMM+fP8+2Xfv27Tlz5sxr9dGmTRsaNWpE9+7d+eeffwgMDOTcuXP8+OOPeHl5AWm5PevXr2fy5MncvHmTW7dusXXrVk0+UHaSk5MZPHiwJml60qRJjBo1CplMRokSJbC2tmbFihXcv3+fY8eOMW7cuDyNuXz58hw5coRz585x69YtvvjiC0JDQ1/r/Wf0008/sWfPHu7fv8/NmzfZv38/Vaq83OASHx+Pt7c37dq1K3Bf7zMRLAlFwtDVldLr1+E4fRoyCwuSbt3WbXkBQF9hzqg+e/mjyhc4KFU8kqm4cHAUXNmQ5+3SgiDkz9SpUwkMDKRcuXI5Lv0MGDAAPz8/7ty5k+8+JEni4MGDNG/enM8++4yKFSvy0UcfERgYqMnpad++Pfv37+fIkSPUq1ePhg0bMn/+fMqUKZPjs1u3bk2FChVo3rw5ffr0oWvXrkyePBkAmUzGli1b8Pb2xt3dna+++oq5c+fmacwTJ06kdu3atG/fHg8PDxwcHOjevXu+3/urDAwM+O6776hevTrNmzdHLpezZcsWzet79uyhdOnSNGvWrMB9vc8ktc7LLL9/oqOjsbCwICoqCnNz86Iezjsn9cUL4s6cweKDDzTXkoOCMChdWmd9RD2/w+YDnzMk4DpyALcPUHdZgGRspbM+BCEvEhMTCQgIoGzZsq+VO1OcjB8/nqioKJYX1oHc+eTp6UlkZCS7d+8u6qHoTP369Rk7diwff/xxUQ+lyOT0PZfXn99iZkkocnrW1lqBUtKDAB507sLjMV+S8jRMJ31Y2FRi2MCTyNtMAZkeibf28umm5hz1WqyT5wuCkH8//PADZcqUyVOOk5B/YWFh9OrVS6uelfB6RLAkvHUSrl5BrVIRc/gwDzp3JmLzZtQZDtp8bTIZNB0Lgw+z0b4M3voSY28uZ8qOD4hPii748wVByBcLCwu+//77LAtcCgVnZ2fH+PHjdVai5X0mluF0QCzDvZ7kVBUbzgfyMDyeMlbGDGzkgoFeWvyeePs2IT9NIvH6dQCMatbEYeoUFBUr6qTvlPgIFu35mLVJj1BLEmXVcua0mEflsq118nxByI5YhhOEN0sXy3AiWNIBESzl36yDfqw8HYAqw78+mQRDmpXlu05uAKiVSiI2b+HZ/Pmo4uNBTw+b4cOwHTkyX30pVWouBYQTFpOInZmC+mWtkMvSftO6cO4Xfri9hjC5DH21mrGl2jGg9S/IJDHpKhQOESwJwpuli2BJFKUU3rhZB/1Yfiog03WVGs317zq5IcnlWA3oj1mb1oROn07sv0eR9LI+viS7gOiQbwhT9vkREvXygF1HCwWTurrRwd2Rho2/Zke59kz6+zOOS4nMDT5CxJZOfPnhNlCIwFcQBEEQM0s6IWaW8i45VUXliX9rzSi9SibB7WkdNUty6WJPn8akYUOk/6rZJt2/j9zKin+fJGUZEHWr4ciKUwG82lX66v3SAbXp4O4IgDo1he1/D2d52Dk2PgnFwawU9PwDnOsV9C0LghYxsyQIb5bYDSe8czacD8wxUIK0GaYN5wMzXTdt1kwTKKmTk3k8diy323Vk54zlhERqn7IdEpXI8iwCJUBzbco+P5T/DUbS06dP11UcbLUCBzMniHwIq9tz+OAoklLEmUqCIAjvMxEsCW+MSqXm2qOoPLV9GJ5zgJL6/DnI9ZDHRjPu6lZmnV2GU+yzPI9FTVpAdSkgXOu6YdmmMOwMuPfihMKA/z07yUcbm3Iv6HSeny0IgiAULyJYEgqdWq0m8Hkc+64/ITWPJQBMDfXIuEKsVKk57/+CPT7BnPd/gczBkbA5y/mjamcS5frUfO7PkmPz+OjOv+ip8n7OXFhMYuaLCgvouQqDJmOwUqq4L6Xw0bHhbDr+LWLVWhAE4f0jgqX/7N+/n0qVKlGhQgVWrVpV1MMpNoIjE/jbN5Rz/i+IS1LSsrItslxKfkiAg4WCf26GEhadyCHfEJrOPka/lRf4cosP/VZeoOnsY/xz5xk7KrRkeKuv8bKrhIEqlUG3DrH4+K9YJsbkaXx2ZtnkjEgSjZt+z86OG2iqMiBZkpgVdIDRmzwIj3qUvy+CIBQTarWaoUOHYmVlhSRJ+Pj44OHhwdixY1/receOHaNy5cqo/vslavLkydSsWTPHezw9PXVyTIguvM57v337Ng0bNkShUOT6XoXc9erVi/nz5xd6P2I3HJCamsq4ceM4fvw45ubm1K5dmx49emBlJY7CyElOW/KfxSRx7VEkYTFJAOjLJdxKmlPJ3oz7YbFZ7oZL16O2E0b6csLjUljw7z02XQrK1CYkKpG15x4CEGpizcRGn9Mi2IcvbuwhwtCUSEPTHMeeHpDVL5vz37GNY22WDDzPpgODmR9+lZOp4fTc1YmZdcfTqNrAHO8VhOLm0KFDrF27lhMnTuDq6oqNjQ27du1CX//lLlUXFxfGjh2bpyBi/Pjx/PDDD8hkef+9/bfffnunZ3gnTZqEiYkJd+7cwdQ05/+nhNz99NNPtGzZks8//7xQN1iJYAm4dOkSVatWxcnJCYBOnTrxzz//iBLxOchuS/7X7Spha2bI44i0hGu5DCrYm+HmaI5CP61Kb3odpZzqLCWmKPF5FMnsQ7dzHIck/XcmriRxslQtvO0qoUhNTnsBME5JoHbYPc6UrKa5lm5SVzdNcJdjH3oG9P9gA3VvbGbCpRn460nE/PMdREdAo1FplcEF4T3g7++Po6MjjRs31lx73V8qz507x7179+jdu3e+7rOwsHit/t4W/v7+dO7cOccDfVNSUrQC0LddcnIyBgYGRdJ39erVcXFxYePGjQwfPrzQ+ikW/8ufOnWKrl27UrJkSSRJyvIQxCVLlmi2DdapU4fTp18m7D558kQTKAGUKlWK4ODgNzH0d9Ih3xCG/3lFK1CCtNme/22/xiHfUCQJXG1N6FK9JLVLl9AESum+6+TG7Wkdmdi5Cp80KsPEzlW4Pa2jJpBS6MtRqyEqISXHsaT/gpke8sQaGPPc2BLpv2tzI8/yw+X1TLnwB3bxacnclkb6/P7xy7IBeVWpWj+29DnCLP3StIuNgSMT4c8PSYnMPPMlCK8jPiU+248kZVKe2yamJuapbX54enoyevRogoKCkCQJFxcXQHspysPDg4cPH/LVV18hSVKOx2xs2bKFdu3aZVk+Yfny5Tg7O2NsbEzv3r2JjIzUGkfGZTgPDw/GjBnD+PHjsbKywsHBgcmTJ2s9T5IkVq1axYcffoixsTEVKlRg7969Wm38/Pzo1KkTpqam2NvbM3DgQJ4/f655PS4ujk8++QRTU1McHR2ZN29e3r5wr4zD29ubqVOnIkkSkydPJjAwEEmS2LZtGx4eHigUCv78808A1qxZQ5UqVVAoFFSuXJklS5ZoPS84OJi+fftSokQJrK2t+eCDDwgMDMy2/xMnTiBJEgcOHKBGjRooFAoaNGjAjRs3NG1evHhBv379KFWqFMbGxlSrVo3NmzdrPcfDw4NRo0Yxbtw4bGxsaNu2LQDz58+nWrVqmJiY4OzszIgRI4iNjdXct3btWiwtLTVpL8bGxvTq1Yu4uDjWrVuHi4sLJUqUYPTo0VrnBS5ZsoQKFSqgUCiwt7enV69eWuPp1q1bpjHqWrGYWYqLi6NGjRp8+umn9OzZM9PrW7duZezYsSxZsoQmTZqwfPlyOnbsiJ+fH6VLl85ySjenb/KkpCSSkl7+xxUd/f6cK6ZUqZmyzy/LLfnpDt0M5ev2lbAyyfk3DQM9GYObuWb7epbJ11n4rIkLf/uGagVvDhYKJnWpQp3TD3lx6Sj1n96m7sn53O7wEQltelPV6fWmaxVmjnTptx+urIdD3/L84Sn67+rI5+V70avZZHEGk1AgDTY1yPa1Zk7NWNLm5Q9Lj20eJKQmZNm2rn1d1nRYo/m8w84ORCRFZGp3Y9CNTNey89tvv1GuXDlWrFjB5cuXszzPbdeuXdSoUYOhQ4cyZMiQHJ936tSpLGfv79+/z7Zt29i3bx/R0dEMHjyYkSNHsnHjxmyftW7dOsaNG8fFixc5f/48np6eNGnSRPNDHGDKlCnMmTOHuXPnsmjRIvr378/Dhw+xsrIiJCSEFi1aMGTIEObPn09CQgITJkygT58+HDt2DIBvvvmG48eP89dff+Hg4MD333+Pt7d3vvKOQkJCaNOmDR06dODrr7/G1NRUE5BNmDCBefPmsWbNGgwNDVm5ciWTJk1i8eLF1KpVi6tXrzJkyBBMTEwYNGgQ8fHxtGzZkmbNmnHq1Cn09PSYPn06HTp04Pr16znO9HzzzTf89ttvmvfRrVs37t69i76+PomJidSpU4cJEyZgbm7OgQMHGDhwIK6urjRo8PLf57p16xg+fDhnz57V/AyVyWQsXLgQFxcXAgICGDFiBOPHj9cK8uLj41m4cCFbtmwhJiaGHj160KNHDywtLTl48CAPHjygZ8+eNG3alL59++Ll5cWYMWPYsGEDjRs3Jjw8XGuyA6B+/frMmjWLpKQkDA0N8/z3kR/FIljq2LEjHTt2zPb1+fPnM3jwYD7//HMAFixYwD///MPSpUuZNWsWTk5OWjNJjx8/1vpH8apZs2YxZcoU3b2Bd8ilgPBMM0qvCo9L5k5oDI3KWReor2yTr1/R1s2BHzq7ZZ0/VW0E5h06EPrTJOK9vHDbs5Z4nzMEjvyaMt1avN7AJAnqDILSjdi852OeyJOYGrCLs8FnmNz1TyxN8zdjJQjvAgsLC8zMzJDL5Tg4OGTZxsrKCrlcjpmZWbZt0gUGBlKyZMlM1xMTE1m3bh2lSpUCYNGiRXTu3Jl58+Zl+8zq1aszadIkACpUqMDixYs5evSoVrDk6empCc5mzpzJokWLuHTpEh06dGDp0qXUrl2bmTNnatqvXr0aZ2dn7t69S8mSJfnjjz9Yv3695pkZx5hXDg4O6OnpYWpqqnkv6cHS2LFj6dGjh6bttGnTmDdvnuZa2bJl8fPzY/ny5QwaNIgtW7Ygk8lYtWqV5pe0NWvWYGlpyYkTJ2jXrl2245g0aVKm9/HXX3/Rp08fnJyc+PrrrzVtR48ezaFDh9i+fbvWz8Xy5cszZ84credmzFMrW7Ys06ZNY/jw4VrBUkpKCkuXLqVcuXJAWoL2hg0bePr0Kaampri5udGyZUuOHz9O3759CQoKwsTEhC5dumBmZkaZMmWoVauWVr9OTk4kJSURGhqa4/JmQRSLYCknycnJeHt78+2332pdb9euHefOnQPSolJfX1+Cg4MxNzfn4MGD/PTTT9k+87vvvmPcuHGaz6Ojo3F2di6cN/AWUavV3A7J2yxaXmeFclK/rBWOFgpCoxKznMnKmKQtl0nZBmeGrq6UXr+OqF27eDpnLsYP72M0YQQhyTNw7NX99QdoW5GRg05jts+T36JvcjQ5jBvb2zOr/g/Ur9r39Z8rvLcufnwx29fkMu2ZnBN9TmTb9tWzDQ/1PFSgcRWGhISELJfgSpcurRWENGrUCJVKxZ07d3IMljJydHQkLCws2zYmJiaYmZlp2nh7e3P8+PEsE679/f1JSEggOTmZRo0aaa5bWVlRqVKlPLzTvKlbt67mz8+ePePRo0cMHjxYa4YuNTVVk7Pl7e3N/fv3MTMz03pOYmIi/v7+OfaV1fu4desWAEqlkp9//pmtW7cSHBysWUkxMTHJdrzpjh8/zsyZM/Hz8yM6OprU1FQSExOJi4vT3G9sbKwJlADs7e1xcXHR+trb29tr/m7atm1LmTJlcHV1pUOHDnTo0EGznJrOyMgISJu1KizFPlh6/vw5SqUSe3t7rev29vaEhoYCoKenx7x582jZsiUqlYrx48djbZ39rIihoWGhTfW9jZJTVfg/i+Xu0xiCI7Oe9n9VXmeFciKXSUzq6sbwP68ggVbAlL7YleckbZkMy169MG3ZkhvfT0bP6yJPKlSjoHNAMn0jPHtspb7PWiZ4zyVQT8bnl6cxOOBvRnRcgb68aJIehXeTsb5x7o0Kue2bYmNjQ0RE5qXBV6XPmuS0xP1qMrQkSZpyBHlpo1Kp6Nq1K7Nnz870bEdHR+7du5frOAsqYzCSPq6VK1dmWuVIX/5UqVTUqVMny+VJW1vbfPef/vWdN28ev/76KwsWLNDkH40dO5bk5ORsxwvw8OFDOnXqxLBhw5g2bRpWVlacOXOGwYMHk5LyMvc0q7+HnP5uzMzMuHLlCidOnODw4cP89NNPTJ48mcuXL2NpaQlAeHj4a7/vvCr2wVK6V7/R1Gq11rVu3brRrVu3Nz2st1pUQgp3n8YQ8CyO1P+2rVVyMMPaxIDwuORcZ3t0oYO7I0sH1M60884hw2G4+aFnbY3DnDmcvngXdbI+Cfee8SIuGed/d1N1QC8MHexzf0gW3Gp6stWlFXP29mcnkax64Y3RpvYM/XAbmBbeN7AgvG0MDAy0knOzU6tWLfz8/DJdDwoK4smTJ5oluvPnzyOTyahYsaLOx5qudu3a7Ny5ExcXF/T0Mv9YLF++PPr6+ly4cIHSpUsDEBERwd27d2nR4jWX83Ngb2+Pk5MTDx48oH///tmOeevWrdjZ2eV7y3xW76Ny5coAnD59mg8++IABAwYAaUHZvXv3qFKlSo7P9PLyIjU1lXnz5mlKQWzbti1f48qOnp4ebdq0oU2bNkyaNAlLS0uOHTumWaL09fWlVKlS2NjY6KS/LMdQaE9+S9jY2CCXyzWzSOnCwsIyzTYJaUFkSFQid57GEBL5MjixNNanor0ZLtbGmCn0dDLbk1cd3B1p6+aQbU2n/HIwV3AnWZ/tB24TnZhCwxBfJl1ci++6VSR4fkGTr4YivUY5AGPL0kweeIomR79l7YPdDAi5Cksbw4dLoXyb1xqrILxrXFxcOHXqFB999BGGhobZ/gBr374969aty3RdoVAwaNAgfvnlF6KjoxkzZgx9+vTJNQeqIEaOHMnKlSvp168f33zzDTY2Nty/f58tW7awcuVKTE1NGTx4MN988w3W1tbY29vnuz5Ufk2ePJkxY8Zgbm5Ox44dSUpKwsvLi4iICMaNG0f//v2ZO3cuH3zwAVOnTqVUqVIEBQWxa9cuvvnmmxzzqaZOnar1PmxsbDQ7DMuXL8/OnTs5d+4cJUqUYP78+YSGhuYaLJUrV47U1FQWLVpE165dOXv2LMuWLSvw12H//v08ePCA5s2bU6JECQ4ePIhKpdJaAj19+nSOOVq6UCxKB+TEwMCAOnXqcOTIEa3rR44c0aoV8r5LUaq49zSGAzdCOHHnmSZQciphROsqdnSq5kh5O1P05DLNbI+DhfZSm4OFgqUD8r8lPy/Sc5I+qOlEo3LWBQrG/rkZyh9nAohOTJsaDjW24nYJZ4xTErFe+Rs+3XuTePfu6z1ckmjbZjZ/dtuJsW0ViAtD9WdP/tjZh+j457nfLwjvuKlTpxIYGEi5cuVyXBYZMGAAfn5+3LlzR+t6+fLl6dGjB506daJdu3a4u7tn2jKvayVLluTs2bMolUrat2+Pu7s7X375JRYWFpqAaO7cuTRv3pxu3brRpk0bmjZtSp06dbSeM3nyZE1JhYL6/PPPWbVqFWvXrqVatWq0aNGCtWvXUrZsWSAt9+fUqVOULl2aHj16UKVKFT777DMSEhJynWn6+eef+fLLL6lTpw4hISHs3btXs3tu4sSJ1K5dm/bt2+Ph4YGDg0OeKqbXrFmT+fPnM3v2bNzd3dm4cSOzZs0q8NfB0tKSXbt20apVK6pUqcKyZcvYvHkzVatWBdJytP76669cd18WlKR+l0uh/ic2Npb79+8DaVO78+fPp2XLllhZWVG6dGm2bt3KwIEDWbZsGY0aNWLFihWsXLmSmzdv6iRzPjo6GgsLC6Kiogq1gmhhiEtK5c7TGPzDYklRpv1T0JNLlLM1paK9KWaK7Auj5VTB+22lVKlpOvtYph19MrWKzgHn8PT7G+PUJNDTw/qzz7AZMRxZFkmoeZKSAEd+Yv3tzcy1LoGjSuLnxlOpXal7wd+I8M5KTEwkICBAU/ftfTZ+/HiioqJYvnx5UQ9FJzw9PYG0ekJvoxMnTtCyZUsiIiI0+T7vut9//509e/Zw+PDhbNvk9D2X15/fxWIZzsvLi5YtW2o+T9+pNmjQINauXUvfvn158eIFU6dOJSQkBHd3dw4ePFhoWwyLWl6CmLDotKW2xxEJmsKOpgo9Ktmb4Wprgr4890nHnHagva2yK32gkmTsc23KeUd3hl3fTZMQX16sWEGi7w1Kr179ep3pG0GnudS0q0Cpa7/xWE/Gp+d/5Av/AwxtvwQ9+btToVcQCsMPP/zA77//jlKpzLJu07vm5MmTnDp1qqiH8V7R19dn0aJFhd5PsZhZKmpv08xSdseQTOrqRls3Bx6+iONOaAwR8S93JzhYGFLJwZySFopiX1Rxj08wX27xybXdqnJxlPlzCY7TpmLavHmB+40N92fWvgHsJa2abU3JmFkdV1PKtmqBny28W8TMklBUiuPMUl6ImSVBS/oxJK9Gv6FRiQz78wqDGpWhkkPaPwY9mYSLjQmV7M2wMH5/ZjjyWtLApFVryg3sprUEF7l7N6jUWHzYPd9BpalVOWYMPEuTI18x7cm/+Mji6b2/LzOrDaNl3VH5epYgCMLr8PDweKcPIS5KxT7B+32R0zEk6dd2+zzBSF9GDWcLPqhVkvplrd6rQAleFrrMLtSRSJuJq1/WSitQSgkL4+n0GYR8/z1Bnp+SFBCQ/85lMjq1/40dzRdQM1UiUQK7w1Pg3ymgzPkMPEEQBKHoiJklHdrl/RhjU7PcGxYC/2exuR5DEpWQgr25gqol3+1Tuwsip0KX6TKWPtDkf0Uk4Nx7IMab1xB/8SIBH3THZvgwrAcPRsrnadtO5dqyxuk0Nw6OpmrgHjgzHx6cILLrfCwda+X+AEEQBOGNEjNLOpSqVpOqKpqPyPi8zUw8i03KvVExl13pAwsjfX77qKam9MEh3xCazj5Gv5UX+HKHLz0iyjG+07ck1KiLOjmZZ78t5EGPHsR7e+d7DHoKC2r1WA991oPCkjvPb9Du0EBW/jMKpTJVJ+9TEARB0A2R4K0D6QliwWEviizB+1JAOJ+tvZxru81DGr5zO9gKS8Zdg4HP47E2NaCKoznJqSqO+IWy+mxgpnskALWadS6ROGxYijI8HPT0KH/kMPqOr1lfKuoxv/3Vl1VS2rl7dWVmzOq0Bgdr3Z07Jbw9RIK3ILxZIsH7LWNqqIepYdF8SVtUtM3zobNCmoylDx6Fx7P0hD9z/7lDVEL2s3Rq0o7OmRDpyMn9+3k+7xfk5havHygBWJRizMCTuBwaxYyw03gRQ8+9vZhUbRjt6o58/ecKgiAIOiGW4YqJ9FwcIFPycmEdQ1Kc+AZHselSUI6BUjo1EBKViHeEipIzZmA3/hvNa0n37/No5ChSgoPz1b8k1+ODzsvY0WQOVVMhWgb/u7mMSTu7E58Uk9+3IwiCIOiQCJaKkaI4hqQ4UKrUTN2f+UDP3ITFpCXUZywjEDpjBrFHj+LfpSsvVq9BnZq//KPSFTuz4aMTDDZwQlKr2RXrz76NHSHiYb7HJwi6plarGTp0KFZWVkiShI+PDx4eHowdO/a1nnfs2DEqV66sOWF+8uTJ1KxZM8d7PD0983T8xpvwOu/99u3bNGzYEIVCQc2aNQkMDNR8LQuTi4sLCxYsKNQ+Mlq8eHGxOpxeLMMVM7o+dPZ9kF1V79xkVbPJYeJEQn+aRLyXF2Fz5hC1fx+OU6ZiVM09z8/VN7FmdN+/Kf33VC4+3EjvsBuolzVF6vIrVOuV73EKgq4cOnSItWvXcuLECVxdXbGxsWHXrl3o678sQeLi4sLYsWPzFESMHz8+3wfS/vbbb+90raBJkyZhYmLCnTt3MDU1xdLSkpCQkGwPHH5XDRkyhBkzZnDmzBmaNm1a1MMpMDGzVAzp8tDZ90H6DFFeZazF9CpDV1dKr1+H4/RpyCwsSPK7RWDfvoTOnIkyNi5Pz0/fhTfudF3OPvqOq6oKSEnRJOz6nKmb2/Is8jVqPAmCDvj7++Po6Ejjxo1xcHBAT08PKysrzMzyXzLl3Llz3Lt3j969e+frPgsLi3e6+rS/vz9NmzalTJkyWFtbI5fLNV/L4sTQ0JCPP/74jRxF8iaIYEl47+W1qndGOeV/STIZlr16Ue7Afsw7dwaVioj1G4javTvX56ZXYU+f6XqstqNP8k/8ltqDX0tYsj05lJ5/dePE1VX5HrPw9lPFx2f/kZSU97aJiXlqmx+enp6MHj2aoKAgJEnCxcUF0F6K8vDw4OHDh3z11VdIkpRjpfstW7bQrl27LHcELl++HGdnZ4yNjenduzeRkZFa48i4DOfh4cGYMWMYP348VlZWODg4MHnyZK3nSZLEqlWr+PDDDzE2NqZChQrs3btXq42fnx+dOnXC1NQUe3t7Bg4cyPPnzzWvx8XF8cknn2BqaoqjoyPz5s3L2xfulXF4e3szdepUJEli8uTJmZbhpk6dSsmSJXnx4oXmvm7dutG8eXPNcuW5c+do3rw5RkZGODs7M2bMGOLiXv4yFhYWRteuXTEyMqJs2bJs3Lgxx3HduHEDmUymeb8RERHIZDKtQHbWrFk0atQISDs2RZIkjh49St26dTE2NqZx48bcuXNH67ndunVj9+7dJCQk5Ptr9bYRwZLw3sutqndGFkb6LOz3shaTUqXmvP8L9vgEc97/BUrVy+UBPRsbnOb9gvPKFZi1bUOJj/pqXstqGSG7KuxK5Pya2ouLLwZSLklFhAxGX/+N6X/1JjE5b7NVwrvhTu062X48HjNGq+3dJk2zbftoyFCttvdbt8myXX789ttvTJ06lVKlShESEsLly5lLlezatYtSpUppDi0PCQnJ9nmnTp2ibt26ma7fv3+fbdu2sW/fPg4dOoSPjw8jR+a8K3TdunWYmJhw8eJF5syZw9SpUzly5IhWmylTptCnTx+uX79Op06d6N+/P+Hh4QCEhITQokULatasiZeXF4cOHeLp06f06dNHc/8333zD8ePH+euvvzh8+DAnTpzAO5811kJCQqhatSr/+9//CAkJ4euvv87U5ocffsDFxYXPP/8cgGXLlnHq1Ck2bNiATCbjxo0btG/fnh49enD9+nW2bt3KmTNnGDXq5bFJnp6eBAYGcuzYMXbs2MGSJUsICwvLdlzu7u5YW1tz8uRJIO3vxtraWutQ4BMnTtCiRYtMY503bx5eXl7o6enx2Wefab1et25dUlJSuHTpUr6+Tm8jnQZLKSkpPHr0iDt37mj+EQrC2y6nnYTpBjdx4as2FfimfSUq/3e+nlbRyi0+9Ft5gaazj3HIV/sHhGmzZpRatAhJTy8tuLodwtUuPfBeuIrUVKWmXW65U9eSGuIf8D191Gm5DVujb/PRpmbceXSmAO9eEPLGwsICMzMzzbKRra1tpjZWVlbI5XLMzMxwcHDAwcEh2+cFBgZSsmTJTNcTExNZt24dNWvWpHnz5ixatIgtW7YQGhqa7bOqV6/OpEmTqFChAp988gl169bl6NGjWm08PT3p168f5cuXZ+bMmcTFxWl+iC9dupTatWszc+ZMKleuTK1atVi9ejXHjx/n7t27xMbG8scff/DLL7/Qtm1bqlWrxrp161AqlVkNJ1vpy22mpqY4ODhgamqaqY1cLufPP//k6NGjfPvtt/zvf//j999/p0yZMgDMnTuXjz/+mLFjx1KhQgUaN27MwoULWb9+PYmJidy9e5e///6bVatW0ahRI+rUqcMff/yR4+yOJEk0b96cEydOAGmB0aBBg1CpVPj5+ZGamsq5c+fw8PDQum/GjBm0aNECNzc3vv32W86dO0dihllNExMTLC0tCQwMzNfX6W1U4EXS2NhYNm7cyObNm7l06RJJGaaKS5UqRbt27Rg6dCj16tUraFeCUGjSdxJO2eenFbA4WiiY1NWNDu6O3AqJxvthBH/7hrL5UlCWRStDoxIZ/ueVLHcfHvINYco+P2r5HGO0/21YcpsD23byfOg4PAe0yVPuVIzaErXVIpZb/sX397fgL0/h46PDmFNhAK2bfFvgr4NQtCpdyWGmQi7X+rTi2RyC5FcSpssf/bcgwyoUCQkJWS7BlS5dmlKlSmk+b9SoESqVijt37mQbfFWvXl3rc0dHx0wzKRnbmJiYYGZmpmnj7e3N8ePHswxe/P39SUhIIDk5WbMMBWmBYaVKhVM41tXVlV9++YUvvviCvn370r9/f81r3t7e3L9/X2tpTa1Wo1KpCAgI4O7du+jp6WnN2lWuXDnXPC8PDw9WrFgBwMmTJ5k2bRoBAQGcPHmSqKgoEhISaNKkidY9Gb+mjv/VmgsLC6N06dKa60ZGRsTnc8n3bVSgYOnXX39lxowZuLi40K1bN7799lucnJwwMjIiPDwcX19fTp8+Tdu2bWnYsCGLFi2iQoUKuhq7IOhUbjsJ7z6NyVvRSmDKPj/aujkgl0koVWoWH7vPr//eBeCpS0PkahWefn9T8XkgrrPGMntPa8wGD8nTOFefe0j9AZ+zs31HfvpnKNdIxP3YHAgPhfYzwcC4oF8KoYjIjPP+d1dYbd8UGxsbIiIicm2XnveUU/5Txt146W3T83vy0kalUtG1a1dmz56d6dmOjo7cu3cv13Hq2qlTp5DL5QQGBpKamqpJAFepVHzxxReMeWVZFtICzfS8oZy+Xlnx8PDgyy+/5P79+/j6+tKsWTP8/f05efIkkZGR1KlTJ1Mif8avaXp/r37dw8PDs5yFfNfkK1iSy+Va047nzp3j+PHjVKtWLcv29evX57PPPmPZsmX88ccfnDx5UgRLwlstY1XvjA75hjB2i0+W1dFflV608lJAOFEJyUzee5PQ6JczripJxj7Xppx3dGf49d00DvHlw5tHCJ54lSYN+nDW3DXH56cHY2cmtGLxwPM8/vc77INWg/caeHgW//ZTKFehU/7euCDoiIGBQZ6Wp2rVqoWfX+b6ZkFBQTx58kSzRHf+/HlkMhkVK1bU+VjT1a5dm507d+Li4pLlrrTy5cujr6/PhQsXNLMmERER3L17N1Mejy5s3bqVXbt2ceLECfr27cu0adOYMmWKZqw3b96kfPnyWd5bpUoVUlNT8fLyon79+gDcuXNHK0k+K+l5S9OnT6dGjRqYm5vTokULZs2aRURExGu9T39/fxITE6lV690/IDxfOUuvJqVu374920ApI0NDQ0aMGKFJWBOEd0l2ide5OeIXyvA/r2gFShk9N7JkWgNPptUfxHOFOU5xz+no+y/kUkMmYzAm6Rvi3HE+fLIbtakDx+Mf0f3cBH7Y0puE5Hd/B4rw7nFxceHUqVMEBwdr7SZ7Vfv27TlzJvNSokKhYNCgQVy7do3Tp08zZswY+vTpk2P+U0GNHDmS8PBw+vXrx6VLl3jw4AGHDx/ms88+Q6lUYmpqyuDBg/nmm284evQovr6+eHp65qs+VF49fvyY4cOHM3v2bJo2bcratWuZNWsWFy5cAGDChAmcP3+ekSNH4uPjw71799i7dy+jR48GoFKlSnTo0IEhQ4Zw8eJFvL29+fzzzzEyMsqx3/S8pT///FOTm1S9enWSk5M5evRopnylvDh9+jSurq6UK1cu3/e+bfL1N53faT1BKA5et2jlbp8neQqwzpWsxhetx7PbtRmLa/SE/77P9JUpOQZOGXOcDsZWonX8TPbppyWB7k26TY91jdh05mC+xy0IBTF16lQCAwMpV65cjssvAwYMwM/PL9N28/Lly9OjRw86depEu3btcHd3Z8mSJYU65pIlS3L27FmUSiXt27fH3d2dL7/8EgsLC01ANHfuXJo3b063bt1o06YNTZs2pU4d7R2FkydP1pRUeB1qtRpPT0/q16+v2d3Wtm1bRo0axYABA4iNjaV69eqcPHmSe/fu0axZM2rVqsXEiRM1OUMAa9aswdnZmRYtWtCjRw+GDh2KnZ1drv23bNkSpVKpCYwkSaJZs2YAr1VYcvPmzQwZkrf0gredpM5HKdRXl+EyWrBgAX369Mlyd0Nxl9dTi4V30x6fYL7c4vPG+x3ts4OSsc9YXLMXwaaZf+hsHtKQRuWsmXXQj+Wn0gtVqmljvpU7Dt5EyuUYqtT0LdGJrz+YLX7ZeUvkdAL6+2b8+PFERUWxfPnyoh6KTnh6egKwdu3aIh3H28DX15fWrVtz9+5dLCwsinQsOX3P5fXnt87mEMeNG0ezZs14/Pix1vXk5OQs63EIwrvidYpWFlSJxGhaPfKm5nN/lhybx0d3/kVPlXbOXMYK4vt9nmQIlNJe/Tf6I/QefE6NeEiSSayP+psvt7QhIib7rdeCUBR++OEHypQpk+8t+G+r9F1kAjx58oT169cXeaCkKzqbWZLJZAwfPpy///6bU6dOabZ+Pn36lJIlSxabb4asiJml4k2pUtN09jFCoxLznbdUEA5xLxh1bSd1wtJ20T00s2dRzV74WZdl6YDaqFRqRm66mu2YDEmkrc1SztqEkipJ/JaooNWH68Guypt7E0ImYmZJEN6st2pmSZIkJk2axKBBg2jevLnWDNO7fOihIOSlaGVhCDWx5sdGQ5hd52MiDUwoE/OUX07/zta4E0hxsYzIIVACSELB/udfUeFhB4ZGJdEq5C6s8IDLq3JNIhcEQRBe0nkqf1YBk8iVEN516UUrHSy0fyuxNNLP5o78yfasY0nihHNtxnT8joB6rdL69DrLLwczb7nOzqWElqx7Mpln9s0gNZGwQ+MZtqExgaE+BR+4IAjCe0BnxxxnnD2aNGkSAM2bN2fr1q266kIQilRWRStVajX9V13M13McLRRM7FyFmKRUrjyMJEWl4titMCKzKHaZHkN1a1aFSNt6mCf040nwC+7d+O9bV63GMimWSEXOp74/x4J2T0exs24Lfg9azll1LH0ODeC7Ch/TvfF34heaIvBq8T5BEAqHLr7XdBYszZgxAxMTE83n6QFT586dddWFIBS5V4tWKlVqHC0UueYzWSj06VXHiTZuDpqq4I/C47n2KIqtXsHZ3mdprM+sHtXQl8k4/+AFseYlibaxBe4D0PTJdf53ZQsbKrdnd7lmqGTybJ8Vkaik1Rk3GliMoo7+arwN4Kf7mzn7+BQTu/yJhYlNfr8cwmswMDBAJpPx5MkTbG1tMTAwEMGqIBQCtVpNcnIyz549QyaTYWBg8NrP0lmCd3amT5/OL7/8kmv10HeZSPB+vx3yDWH4n1cAsg2Y0n8UZjwz7kVsEi1/OUl0YvbHpziYG/JTl6pM3OPLi7jkTK9/e/lPWgT7AHDfwonfavXmvmWpTO1eHYuCBD6vsoY/1Q9JlSQc1DJ+bjyNOhW75XivoBvJycmEhIQUizOzBOFtZ2xsjKOjY5bBUl5/fhc4WFKr1e/9b0UiWBIO+YZkOtbkVRLgYKHgzIRWyGUSZ+49Y8AflwrUr6RW0fbhZT6/uR+zlASUSOwt15T1VTqQqGeY61iWtb7L9zcWE6QnQ6ZWM6FEJ/p2+Rm5XPeViQVtarWa1NTUYr1TWBCKmlwuR09PL9s4Ja8/vwu8DGdqakrNmjWpU6eO5sPNza1QysALwtuqg7sjZgr9HPOXMh5T0qicdZYzRfmllmQcdmnAJQc3hvrupeXjq3zof5omT27wa60++NhlfZ5W+lhORLdBCjOlkel8QhQJdPdZwYlrN1B3+ZU2tSsXeHxC9iRJQl9fP9MBr4IgvH0KHCzNnTuXK1eucPr0aZYtW4ZSqUShUFC9enVN8FS7dm1q1Kihi/EKwlvreWz2s0oZpR9Tostil5EKM+bU7c9R5zqMurYTh/jcT3MH+PXfu4AVflFT8dTfjb7sL1pL53i0pxN/hI5kcKf/6WyMgiAI76oCB0sjRozQ/DkpKQkjIyO++uorwsPD8fLyYvXq1SQlJYmpZqHYy2vwk96uflkrrEwMCNfBDFO6Zh93ZXLZKrjcvaI1q1QmOoQgM3vUUtYzvipkrE7pgZdUg9/0F3PKMp4Fz9Zyd/sxfuyyATMjK52NURAE4V2j07UyQ8O0HIk+ffqwZMkSLly4QExMDFevXtVlN4LwVqpf1gpHC0W2hSszHlMCaTvrPm9aNtu2r6OsrQnHfuzIkJ++wEg/bWecTXwk808tZu7pJZSJDsnx/uvqcnROnsUVtStytZqD8UH03toKn/t/v+aIBEEQ3n2Fnlgkl8upXr16YXcjCEUup0rf6Z9P6uqGPEMFytZV7Ghd2U4T2KRzsFCw5ONaOFrkb6nOzkyBXCbRtKIt/eo7A1A2+gkAVcMDWXz8Vwb5/Y2BMvsdePEo2PNsAtWCmlMyVUmwpMTzzDcsOzwKpUrMEAuC8P4RWdiCoEPZVfp2sFBolQ2AtB10A/+4xNHbYSSkpAUh5kZ6fNWmAmcmtKJT9ZKa4CsvrE0MNLNWAI1crWld2Q5f52p80eobzjlURU+t4qO7R9l0YSE1n93L8Xmn4zvT3fZXOqmMUEoSv4ec5LNNzQh5cTfPYxIEQSgOClw6YMiQIdSpU4e6detSrVo1jIyMuHbtGtWqVdP5YN9WonSA8CqlSq1V6Tu9EGW69NpMr37zZVWPadq+m/xxNjDXPj9r4sJPXatqnv/9X75a+VBG+nKGy4PocGwjyrAwAP4pXZ8FtXpDNttqJWDZx9VJDprOjGdnSJIkNsZIuHVfDc71chxPdGIK4bHJuNiY5NhOEAShqLyxg3Tv3LnDhAkTqF+/PmZmaUcuTJkyhcWLF3Pu3DlRdE14L6VX+v6gphONyllrBUpKlZop+/yyLGCZfm3KPj+UqrTP2rg55KnPtv+1Sw/EXk0cT0hRMj/RiYBf/qBE//6oJYkoQ5NsA6X08Uzaf4dOnZaxvfFsZsZJuL0IgtXt4dRcVDks552+84w/Lzzk9+P3Oe//QvN+BEEQ3jU6q+B97949vL29uXLlCt7e3ly9epXIyEjkcjkVK1bk5s2bOhv020bMLAn5cd7/Bf1WXsi13eYhDWlUzhqlSk3T2cdyPFLF8b9ilwBNZx8jJCox2+emnU3nxoLfd/PQzIEkvbSqtqViwlBJEk9MbTPd06t2KZpVtMHRMJm6N6cj892Bn4E+P5R0ZrrHPKq6tNJqf8g3hPE7bmhVJ3e0UDCpq5vWUqQgCEJRemMVvHMSEBCAl5cXV69eZebMmXm+710jgiUhP/b4BPPlFp9c2/32UU0+qOkEZH+kyqvLdnkNxF4tWSBTq5h3ajGuUU/YXKkNOyp4kCrLurKIo7khy2vcZ9HjBVxQ6KOnVjO6VHs8W89FJsnytcQoCIJQlN7YMlxOypYtS+/evYt1oCQI+ZXfekyQ98Tx9IKXuXl1ic44JZE4fQUGqlQG3TrE4uO/4vYiIMt7Q6OT+OC0M23KLaRFsh6pksSvwYcZuqkFAWH3mbw370uMgiAI74J8zSzJZDIWL16MsbExrVq1onTp0oU5tneGmFkS8iO3ZbVXz5B79d6cEsfzOrOUJbWalo+vMvTGHiyT4wA46NKQ1W6diTMwyjRGS2N9vmrlQsit79mhd4tEmQxzFRg8aUdATKssOngpfYlREAShKBXKMly6pKQkjh49SmBgIHK5XLMb7n0lgiUhv/K6rJZfeclvKmGsT0R89onZZslxDPY9QPugtEN+ww3NGN9sBMFZ5DKZGMiJS1ZSy/A8OO3ivmFavSiPx1XZH9MfdTaT1xmXGAVBEIpKoQZLr/L29sbLywuA0qVL07p1awwMDAr62HeGCJaE13HIN4Qp+/y0krF1kQSdXSCW7ovmZdnjE8LT6OwDKoBqz+4z5tpO4vUM+arFGFTZHJWSzpwomjv8RorhC5Y+fcZZpTvjUobzjBKZ2oqZJUEQ3gZvNFjK6PHjxxw9epSkpCTMzc1p06YNNjY2uuzirSOCJeF15bas9rqyCsQysjTSIzIhNdfn6CtTsEiK47mxJQAGyhRaB3nxT5n6qGTyLO5Q00d+lMl6GzGWkniMGSOM2nI9ogcgy3GJURAE4U0rsmAJ4PLly+zZs4fDhw/j5ubGwoULi3UQIYIl4W2kVKlZfOw+v/6ru4rbg/z+5qO7R7ln4cTCWr25b1kqy3blpGAW6i9mu20MO81NcYkz4V7wSJKUVmI3nCAIb403vhvuzJkzDB8+nBYtWrBlyxbatGnD+fPnWbt2rQggBKGIbLkclK/2g5u6kNOEzxMTa2L0jagQFcyCE78x9MYeFKlJmdr5q534MHkqLxIrYqhSEWgSh3W52UxoFSgCJUEQ3jk6m1nauXMnSqWSPn366OJx7xQxsyS8jfK7My59iez7TlUYvflqtu0sE2MY6ruXlo/T2jw1smRJjR5ccsj6HLu6ilOklNzHg/+Svz8uUZ1xnf7AUE+7DEJSqhKVCowMslreEwRB0L03PrPUs2dPunfvrqvHCYJQQHmtuZRODYREJWJjasiyAbWxMtHPsl2kwow5dfvzY6PPCTUugX1CJFMurKbnveNZtvdKbM6jgG/ppbQAYFPEdfptbEpgyBWtdju9g/nrajDJqSoAEpLzXgBXEAShMBU4WPr++++5dClti/H7tANOEN52eS1++aqwmEQ6uDty4bs2WJlk/z3tbV+ZYa2+Znt5D2L1FJx2qpFt2xRDe34cdIolpbpipVTyTBmP8aa+cP9fADJOcEclpHD9cSR/XQ3m4Yu413oPgiAIulTgYCkkJIQuXbrg6OjI0KFDOXDgAElJmXMYBEF4s+qXtcLRIv8BU3qQZaAnY+aH7jm2TdIzZLV7Fz5t9z1hxlaa6z3vHadMdIjm85jEVI7cekqz1jPZ2WYlC5NMsIsJgz97wj8/EBMfoWmrUqu5/jiKB89iWX7SXxzCKwhCkdNJzpJarebMmTPs27ePvXv3EhwcTNu2benWrRtdunQRpQMEoYgc8g1h2J9Xcm/4H8cstvX/9u9dfv33Xp6fUePZPX4+u5xUScaOCi3ZXKkNyXJ9rWdHRkVhcHwyxj6rOWpsxDRbOxobfYaby4dIEsz++06Oh/BGxiej0Jej0Bf5TYIgvL4iLR1w69Yt9u3bx549e/Dy8qJBgwZ069aNfv364eRU/Kr2imBJeJsdvP6EUZuvktvkjETWlcOVKjVNfj5GaHTecqBsEiIZfu0vGofeBCDYxIZFNXtyzbaCphjlpotB+AZHkXBzH2G267lulJYfVT6iDFdDPwe086UyVjZvVM6GA9fTZq0+biCOXBIE4fUVabCU0bNnz9i7dy979+6lWbNmfP3114XZXZEQwZLwtjt4PYQRm7KfYSphrM+sHtWy3daf2wyVZ6MyrD3/UOta4yc3GH79L2wSowH417kOZX74DisnO5ae8Oes/wsAbKQw6jsu5rRF2uG+Tol6hAR/TlSyi9bz0nfrrf20Pt4P05btRLAkCEJBvLFg6f79+5QvX74gj3jniWBJeBdkVdXbXKGHZ2MXvmxTMdeK2psvPWTWQe3lMQsjfb5sXYEqjuZZlikwTklkkN/fdAk4hww1jywc+cLjK9SvHJ0ioaKD+Z/ccLhBlFyOoUqNdVgj7kR8wMt5pTS/9qlBQkrajrl+9Z2RJFEJXBCE1/PGgiWZTIaTkxMtW7bUfLi4uBTkke8cESwJ74qCHK8SlZDCvmtPCHweR0xiKmYKPVxsTGhQ1gpXW1Oazj6W7fEqlcMfMsZnB1srtuJkqVrZ9lFJ3xebkuu5bpwWTH34qAKbYgeRip6mjWfjMlS0T/s+61WnFAZ6OquAIgjCe+aNBUunT5/m5MmTnDhxgvPnz5OYmEjp0qVp1aqVJngqjnlKGYlgSXgfpCpVbPN6nOl6/bJWlLczzXWpTq5SopRk8N9MUNPga5SKfcaOCh6kyl4GQ0bE085mMY4GD/k2PAIflStfpoziodoBAI+KNhgb6GGi0KOTuyPNK9qKc+YEQXgtRZKzlJKSwvnz5zlx4gQnTpzgwoULJCUlUb58ee7cuaOrbt46IlgS3hebLmY+PqWha9rMEsDGCw+ZfUh7qc5YX0b8f8tmmmspCaz6dzYlkmJ5aGbPwpq98LMuq9Wmg+wSP+uvxFKK44HMmK9MGnHt2SDIMMsEmXfKCYIg5FWRJngnJCRw5swZ/vnnH1auXElsbCxKZfGtxiuCJeF9ccg3hPC4FBwtFJolt8blrHGxMQHgSWQCx26HaZbq4pJTOXrrqSbHSEOtpuXjqwy9sQfL5LTCkwdcGrHGrRNxBkaaZo68YL7B76wqGc4lIwWlEvV5/PgLYlIyH+C7tH9tOlYTAZMgCHn3Ro87SUxM5NixY0ycOJFmzZpRokQJxowZQ2xsLEuXLiUoKH+HeQqC8HZqU8WerjUcKZGhsrcsQ4K1XCYhkyRcbU2RyyT2Xw/JHCgBSBLHnWsztM14/ildH4DOgedZcXQOTYOvwX+/w4VgTf/kH1FEVMNMqeKxIgUj10WUtzhA2gEtL/209yZPIhNIVWbRnyAIQgEUeGapRYsWXL58mXLlytG8eXNatGhBixYtsLe319UY33piZkl431x/HIlvcFpJgGYVbHC2MgbSjkr51y8MlVrNnFeW43JS7dl9xlzbSanYZwCMaDmOAIuSWm2q6vtg7rQJX6O03/Fco63wDRmJUmWiadPJ3YF+9UvTrKJtgd+jIAjF3xubWTp37hw2Nja0bNmS1q1b06pVq/cqUBKE91HG2aSMO/fTrwc+j8tzoARww7Y8I1qOY2Oltuwv2yhToARwM6UmNwJ/otULC+RqNQ/Mw3F2nYaDwct8yIO+oYzcdJVDviGZ7hcEQXhdBQ6WIiMjWbFiBcbGxsyePRsnJyeqVavGqFGj2LFjB8+ePdPFOAVBeItkDJa0luH++3NMYmq+n5ki1+fPKu35vXoPzTW7uHDmnP6d8pFpu/BiMWVP2HfUDGpKyRQlFuoU9srm0kV2XnNPdGIKw/+8ogmYEpKVRMQl53s8giAI6QocLJmYmNChQwd+/vlnLl68yPPnz5kzZw7GxsbMmTOHUqVK4e6e82GcRe3Ro0d4eHjg5uZG9erV2b59e1EPSRDearIM/3NkFTiZKfRevSXvMjzvM7+DVHsRwIITvzHkxl4UqWmHdJ+I70pswBiGhRhjRzyLDRYxR28pJnpPgbRspin7/FCq1Oy79oS/fUOJjBcBkyAIr0fn1dxMTEywsrLCysqKEiVKoKenx61bt3TdjU7p6emxYMEC/Pz8+Pfff/nqq6+Ii4sr6mEJwltLrhUgvbyeHkS52JhgrtCnoJZX68YJp5rIUdPD/xTLjs6lfqgfAMFKZ0bFT+a31A9RqiVirX0wdZ2Pq/lhAEKiErng/4K7T2O49iiSDecfEp+c/xkvQRCEAid4q1QqvLy8OHHiBMePH+fs2bPExcVlqupdpkwZXY250FWvXp0DBw7g7Oycp/YiwVt439wPi+VSQDgAbdzssDNTABCXlMoenycA+AZHsemSbnbC1n16i5HXduEQn3Ym3KmS1VlWvTsRirTvt7rSLQzKrOaGkRwA1yhbroeOQCE3JSHlZdkSS2N9fs7iDLyYxBRMDPSQieKWgvBeeWMJ3paWljRq1IiFCxdibW3N/PnzuXv3LkFBQaxbtw5PT88CB0qnTp2ia9eulCxZEkmS2L17d6Y2S5YsoWzZsigUCurUqcPp06dfqy8vLy9UKlWeAyVBeB9lrJidXf6Su5MFPWrlr3p/dqGKl30VhrX6mu3lPVBKMpo/uU7HwJdn0Xmpq3AjcCKtwk2RqdU8sHhG2bJTMZFf13pOZLx2PhPAo/B49l0L4dQ9kV8pCELWCpBYkGbu3Lm0bNmSihUr6mI8WYqLi6NGjRp8+umn9OzZM9PrW7duZezYsSxZsoQmTZqwfPlyOnbsiJ+fH6VLp51KXqdOHZKSkjLde/jwYUqWTNt58+LFCz755BNWrVqV43iSkpK0nhUdHV2QtycI7xxZFjvgQDuXCdIKVu66Gpzn5/at54ypoR4XHrzA94n291WSniGr3btwolQt+tw7zvYKLV/2q1YRI5mz5+kPtIndzUPHc4QayJG7rKfqc3duPu9Pxt8NJ+/1o62bA3KZxK2QtH6eRGZ9rp0gCEKhVPBOf2RhnAYuSRJ//fUX3bt311xr0KABtWvXZunSpZprVapUoXv37syaNStPz01KSqJt27YMGTKEgQMH5th28uTJTJkyJdN1sQwnvC8ehcdz+t5zADpVc8DSOK1IZYpSxfYM58fVKm3JZ2svExqVSE7/0diaGvJFC1eMDfTyvXwnU6uYe/p3rtmUZ0ulNiTL9SkjD6RCyeVcNFWjr1bj+dCFJQmfkYih5r4Nn9XH2FDOndBYzbW+9Zw1s2YvYpO4+SQadycLYhJTcLI0Qk8uDu0VhOLkjVbwTvfHH3/g7u6OQqFAoVDg7u6e6yxNQSUnJ+Pt7U27du20rrdr145z587l6RlqtRpPT09atWqVa6AE8N133xEVFaX5ePTo0WuNXRDeVRlze6QsSgdo2kkSk7q65fis1pXtWPtZPZqUt0GlVrP/ev5qJDUI8cMt/CH97h5lybF51Hh2j4dKF04+mkqrUGcmvIhgjPo0+w1+wE0K1Nz3t2+IVqAEcDs0mvP+L3gancg/N5/yOCKBQ76hnL3/QpOjJQjC+0dnwdLEiRP58ssv6dq1K9u3b2f79u107dqVr776ih9//FFX3WTy/PlzlEplpkKY9vb2hIaG5ukZZ8+eZevWrezevZuaNWtSs2ZNbty4kW17Q0NDzM3NtT4E4X2ivQyX4c9ZJEh3cHdkYb9amXbH2Zoa8nH90rSuYo9anRZY5beYJcB5x6pMqz+I5wpznOKe8/PZ5fzPezNGScnsiRjJ3hejeaq2pLzsCTNMp1HD8TckKZFNlx7hGxyFSq3mwbNYrj2K5K8rwfg/i+XorbBM/QS+iM/XuARBKD4KnLOUbunSpaxcuZJ+/fpprnXr1o3q1aszevRopk+frquusvTqkp9arc7zMmDTpk1RqcR5UoKQV3Ip65mlV6n/W3zrXM2RqIQUzQG7Zgo9etYpxdWgyLTnySQkKX/FLI0N5MQnK0GSOFeyGj625Rnk9zddAs7T5pE39Z7eYqV7N44616GD6mdm6a/gd6cQAg1CcDWeSsTjQfx1Vcb+6zKiM/RrpC+ncTlrWla208rHArj3NIYK9mZ5HqMgCMWDzmaWlEoldevWzXS9Tp06pKYWXm0TGxsb5HJ5plmksLAwceyKIBQSmSzrOksAdcqU0PzZxEBP0z79gN0azpaag3brl7XC0VJBeTtTJPJezHJ0q3JsHtKQz5uWxb1k2sxuvL4RS2v04H/NRxFg7ohFcjydA84joSYCc4al/I+ST+tjl6okzECFuuxqXMw3Ep2oXawyIUXJ0dthzDx4C9/gKK3XLgdGiGrggvAe0lmwNGDAAK0E63QrVqygf//+uuomEwMDA+rUqcORI0e0rh85coTGjRsXWr+C8D7LrlwAQCUHM1pXsaOms6XmgN3slLczpWUlO/TlMiQpb8UsHcwNGdumEhXsTXG1NaVqSQut129blWG0x1hWu3ViYc1eqKW0/+b0lakcje4JD4ZSLxZSJYnHdtdwLz0DQ70XmfqJT1ay6VJQpoApKiF/y4SCILz7dLYMB2kJ3ocPH6Zhw4YAXLhwgUePHvHJJ58wbtw4Tbv58+fn67mxsbHcv39f83lAQAA+Pj5YWVlRunRpxo0bx8CBA6lbty6NGjVixYoVBAUFMWzYMN28MUEQtGQMj7JahbM3V2Bvrsj3U2WSRJfqjmz+bzdcVjvoJnermrZsR/ZHqyhlcrZXbKV1beCtf6j39BYLa/bmrHIKHa2WcdY2mIcmcVi7zsEw8BMCkqtmetYen2BSVCosFPq42Jig0v0GYkEQ3nI6C5Z8fX2pXbs2AP7+/gDY2tpia2uLr6+vpt3rlBPw8vKiZcuXNVXSA69Bgwaxdu1a+vbty4sXL5g6dSohISG4u7tz8ODBd6pquCC8SzJ+G0vZlpJ8vWe6O1nwS+8a/HL4DiFRL2sfWRjp07mao6b6dnr79NmonBLDDVOTaPX4CtaJ0cw/vZgDLo1Y4zYU9/hLJJXcj4MymfnSHGbKB/Cnsg0Zw8G4ZKWmHIK5Qp9x7Srgamua6/tRq9U8i03C0sgAAz1RckAQ3mWFUmfpfSOOOxHeN5HxyRy8kZYn2KduqTzVH9p0Ubt2Ul2XElTMkCz94FksFx6kbc/vUsMREwM9Zh28pUkId7ExQSZJfNwgrdBsUqqSnd5pBS/zUpvJLDmOwb4HaB90CYBwQzOWVu/OLScnphqupLOUtgN2v6o2P0rdiUwqn+2zlg2onenIlFelHwljZaKfa1tBEIrGG6mzFBSUv3OfgoPzXslXEIS3V8bZpFdzll77ma/kQcll2gnhMiktITyrMbg7WfBx/dKZ8p0sjPSp9l8CeIyBCQtq92F8k2E8NrXFKimGHy5vYPT5PUyKHMbUlIEkqfW4bBeIzGUlFa12kPVCIEzae5Oz955zJShCc803OIprjyI1nz98kXYYd3icyHEShHddgYKlevXqMWTIEC5dupRtm6ioKFauXIm7uzu7du0qSHeCILwljAzkmj/r6vDZjE/J7pFlrF8mjL8ao7k7WTC+QyU+b1qW3nVK0cndgXZV7alX1grzDHlNN2zLM6LlODZVakOKJKfaiweAxGplR7onT+KhzIQUmUSIvRfupWeiL4/MNI6n0UmsPhvA7ZAYwuOSSVWquP44iptPoklITju4Vy4O5RWEYqNAOUu3bt1i5syZdOjQAX19ferWrUvJkiVRKBRERETg5+fHzZs3qVu3LnPnzqVjx466GrcgCEXIQE9G52qOmc6CK4i85EFp1XfK4nWZJBGfrOSfm0+1cpiM9OVa7VLk+myo0oGTTjUpFfuM50aWANxSlyP21ljalN7EKZswHprEYO/6M+qQ7gTHNtR6xtHbYSSkKLEy0cfF2kRzPVWlAuQ6m3ETBKHoFei/OisrK3755ReePHnC0qVLqVixIs+fP+fevXsA9O/fH29vb86ePSsCJUEoZiyM9THLZZt/RuVsTXJv9J/s4ozsjllJl5679Gqyd0JK1rM9QeYOnCtZTfN5rbC7LP33V6xPVKDa/ZaUTU4lSg+inXfj7rAUJO3nnvN/wbA/r9Bn+YVMJQZyCpZEqqggvFt0shtOoVDQo0cPevTooYvHCYJQDDVwtaZW6RLs8H6c5esZ44e8zMq82iIv58opVTkHKbXC7iJXq+jpf4qnTyzZWLMHZWr+zQnLFKLNHzArchGzEocSjfZuuOjEFDZdCuLj+qXpUkN7t96rElOUHLgeQqkSRjRwtc5xPIIgvB3EflZBEN6YjFvorUwMsm2Xl3SfV3OlXudcuVetdu/CT40GE2pcAvuESMad30W1PRXoeK8cU8Mi6IcXfxt+Rz3pNlklfx+4EUKqMu16dm/hwbM4klJV+D9LSwC/FBDOId8QVLkEcoIgFB0RLAmC8EZ1qeGIRyVbbEwNta5nDBVeJ98nP+fK5SS6ej2GtfqaHeVboJRkNHtynd67H3LMtycBKnucpBcMLvEL7s6zkctjtO6NSkhh06WHxCam8uB5nOaA3vP+LzSzWhnf2t5rT7gfFkt4XAq3QqN1Mn5BEHRPpxW8BUEQcmOu0M/ySJOMeTzps0b1y1pxKSA8T8/N67lyuXkckUCSniF/uHfleKnafOmznYqRj/GXnOicPIsf9dewwvoBL/QiKek6g5QnvQiNe3ku5i//3OX3Y/5IUtqRKQBbvR7haKFgUlc3ytq8XMKLzRDgXXsUlenoFkEQ3g5iZkkQhLdCVotQ5e1M6Vw9LQfI2jT7ZTvI27lyeZmvivsvwAF4YOnEVy3GMLW+J2dLViMeBd+nDKfB9bq4xqcSqQfxztuparcKeBn4JKQoNYFSupCoRIb9eYWz95/nYRSCILxNRLAkCMJbIbsNYhZG+vSqU4p2bvY53p9+rlxOmpa3yfe4VJKM8yXdNetn5klxfHj8Jl+tsqSfn4Rakgiyvk+lslMx1X+U6/OWnvAX58sJwjtGJ8GSSqVi9erVdOnSBXd3d6pVq0a3bt1Yv3692CIrCEKBGejJ8nSuZE6VvD+uX5qO1RyzfN3EQLsOU04c4l+QItPDPi6SD/ekMHWbMSVjUnmiSMbYdTHuetdzvP9ZbBKBz+Py3J8gCEWvwIv8arWabt26cfDgQWrUqEG1atVQq9XcunULT09Pdu3axe7du3UwVEEQijfd/GLl7mSBW0lzAp/HZTpXLrvXoxJTNIfl5uZuidJ80fobBvn9TZeA81T2j2bGCkP+bZmEyjWB8fI5/KruxVJlN1TZ/D6anoyuUqu1xvE0OhF7cwUqlZrw+GSsjA0IjkwAwNnKOMtnCYJQ+AocLK1du5ZTp05x9OhRWrZsqfXasWPH6N69O+vXr+eTTz4paFeCIBRjrzMJXdelBLdCoolLepkf1KyCDafvPcfV1jTb+2SSpPX6g2ex+eo3Xt+IpTV6cNy5DmN8dlA2OoQP/oFY+xLIW0Twjf423A18mMSHhCXUyHS/mUKPG8GR7PV5opUjtc3rMXN6VcPWTMGdUO2ddnk9sFgQBN0r8Hfe5s2b+f777zMFSgCtWrXi22+/ZePGjQXtRhCEYu515pUq2pvxQU0nSloqNNderd9kYpj7ElteksOzctuqDKM9xrLarRNJMj1OGdXgf6nDiFIr2G4fSVKZTbjZrgFeBkTmCj0uBLxg86VHWoESpBW3HPbnFXZmUbhTKVIaBKHIFDhYun79Oh06dMj29Y4dO3Lt2rWCdiMIQjGnX4BZk5wKXNq+Us8pK3lJDs+OUiZne8VWDG/9NWvcOrNL1ZyuKVOxe66gfDA8srlDZZepGOmnVRdPSFbiG5xzTaUDN0JyTQJPVao4fe8Zt0JEfSZBKGwFDpbCw8Oxt89+l4q9vT0REREF7UYQhGKujJUxLtbG1C9bIt/3Zix+nTHEaOtmj2ke6y9llxxurtDDOA8J4CEmNsQapOUVBSmdqP5PWaZvUDL871QipETMXBfgYnGYlDxU6o5KSMmUBK5UqXkUHk9yqorkVBXbvB7zKDyBq0GReXp/giC8vgLnLCmVSvT0sn+MXC4nNVU3lXUFQSi+ZDKJxq+xtR+gpIUCvyfR6Msl9DIcg2JtYoCZQo97T2MpbW3Mvac55yZllxzu9ySaTZeCsr3PwdyQ0Ogkzef6qlSeGVkC0NIH6t5TsqKdjIuVjuJueoObISNQq4xyHIt/WKxWYvrlwAiCIxKybBuVkIJXYDjuThbYmyuybCMIwuuT1AXc2y+TyejYsSOGhllPdSclJXHo0CGUSmWWrxcH0dHRWFhYEBUVhbm5eVEPRxDeSy9ikzAx1EOhL+d+WCx6MgkXGxMgbdeuJEn4PIrE70nOy1YWRvpEJWQ+Y843OIr910O0zp+zMNKno7sDe32eEJ+S+f+46s/uM9pnB6Xi0gpRepeDf1upGBBlw3fJw3lGzrNo5gp9ulR3xN0p58re5kZ6RCek/VL6cYPSObYVBOGlvP78LnCw9Omnn+ap3Zo1awrSzVtNBEuC8O7Yf/2JJrDISKEvIzFFRT2XElwOzDp14NWt/i42JgQ+j2PVmYBs+9NXpvDR3aP0vnscfbUStZ6ash7PibdW8E3KEI6papNbRsTH9UvnGDDpyyVS/jvAVwRLgpB3ef35XeBluOIcBAmCUPxkFSgBNK9oi75clmMh3VdLDkDuB/imyPXZUKUDJ51qMvraTmySolBb6FNVCqKx7SpCFI48CB5OUqpdts/Yf/0JlR3NCHoRn2XtqKx4P4wgJCqB9lUdCpQ8LwiCOEhXEAQBSKsSbq7QJzI+OV/35fUA3yBzB8Y3HU6JxBhilcaMlm9mu+l1ml2JI77GL6jDOxAU3SrLe6MTU5lx4BZJqSrNtYxLdOmzShml12kKeB5HRXuzfL0nQRC0FfjXjYsXL/L3339rXVu/fj1ly5bFzs6OoUOHkpSUlM3dgiAIb4f0ORplHnarZZSfGk1qSUa4kQXJ6DMv+RN6/luVAcdVTFutwiXhEO4lfwMpMct7MwZKkFaTadOlIHyDo7SuJyQrCYl6mQiuVkNMYgr3nsbk+70JgpCmwMHS5MmTuX795VlIN27cYPDgwbRp04Zvv/2Wffv2MWvWrIJ2IwiC8FYqSI2mk8aNeWZkgW00fLddRY9jj6lpN4USijt5fsarNZkCX8Rx/PYzrTb7roVwOTBC1GQShNdU4GDJx8eH1q1baz7fsmULDRo0YOXKlYwbN46FCxeybdu2gnYjCIJQqNLzf3IqcJmd7Go0GenLyOn43yv2lRjSejw7yrdAJUGj22p+XJtCu4hVNJJfzlPfUQkpnLv/XBMw5VR3KSwm61krQRByVuCcpYiICK2ilCdPntSq6F2vXj0ePXpU0G4EQRDeCCmHpOmcZFej6eaTKDZfyv7/wCQ9Q/5w78rxUrUZf+1PykQ8w/MfNSUq/sG+6neYm9qXZHJe5jvoG8qZ+y/yVGYgVakSZ8wJQj4V+DvG3t6egIC0bbPJyclcuXKFRo0aaV6PiYlBXz//Zy4JgiAUhuxioex2lrVxy36XWlbPcLU1pYazJa62psgkiWpOlnmqDP7A0okRzb9hVbXOpBjIKVEuniF6B/nFbCKlzE7n2nd2OUwRGRLWY5OUbPN6zKaLQTx8EffqIwRByEaBZ5Y6dOjAt99+y+zZs9m9ezfGxsY0a9ZM8/r169cpV65cQbsRBEHQifZVHbj5JIpH4VlXw87ITKGHnVnBK2LntTK4SpKxs1xL9pdpTFMDX6awnGX2KTS/so84kwvs0RsD6pzPutt//QluJc01wd+DZy+DotgMZQ7O3n9BGWuTAr83QXgfFHhmafr06cjlclq0aMHKlStZuXIlBgYv1/xXr15Nu3btCtqNIAiCTliZGNCsgm2m61lNLOly71hWs07Z5Tol6RlyVFWHD5Nm0CTAiP7HVQzb95RJdyfihG+O/UQnprLL+3GuB/EKgpB3BZ5ZsrW15fTp00RFRWFqaopcrn3g5Pbt2/H39y9oN4IgCMXSq7NO957GcOVRJADP1LZsSvyO8hUX4X7nOQ1vqnB7sJY99cqxqcRQkLI+4PfKo0huP42he02nXHOYBEHInc6y/CwsLLQCpaioKJYsWULbtm1p2LChrroRBEEoFK+Z160TGWedetQphXmGQpdx+iZMqPItC1t24Zk1mCfAwFP+/HblB5zjsj/cNz5ZyaZLQVx/HJlr/6lKVb6LcQrC+0TnWyKOHTvGgAEDcHR0ZNGiRXTs2BEvLy9ddyMIglAgFey1jy2Rctzk/+ak1W0qmen6PxYejGgymct1TUnWg4qPUll+eiGuquAcn7fl8iOuPc7mrLv/ilQe9nvKwRuhPI6IL/gbEIRiSCfB0uPHj5k+fTqurq7069ePEiVKkJKSws6dO5k+fTq1atXSRTeCIAg6U6d0CRwtXiZvF+XM0quyy2WKlZnyU6nJ/NG+GTKHFBzdI9lrNJEP5MdAyn5maOvlx2y++DBTHlP655HxKQDcfRqj43ciCAWTnKrSBPVFqcA5S506deLMmTN06dKFRYsW0aFDB+RyOcuWLdPF+ARBEAqFTCZhZ25ISFRaocasYiVDvaKrR5QxlykqIQX/sFhNLtNe/Q+43KAJCwx+p4F0BzPHXXzw+F/K3qjIisp9idc3yvS8G0+iuXfAjyblbLAxNcRMocch31CiM+yQC40SR1MJb4/EFCW7rgRjptCja43Ms61vUoGDpcOHDzNmzBiGDx9OhQoVdDEmQRCENy5jMcoWlWzxDY6iUTnrIhzRy1wmgFqlS1DZ0Zz910OITkwhRLKhX8pEPKUdnDW8xOTjydhF+dLgyV1+d+/LmZLVM02XJaaoOHo7TPN5xsN4BeFtE/rfLzIxGQL6olLgX5tOnz5NTEwMdevWpUGDBixevJhnz57lfqMgCMJbJGNY4WRpRPuqDpmWwUwMs959pid/M2t47k4WjO9Qic+blqVJOWtUyFid3AfThwM52hqelADLhGR+uLyBKRdXYBufda5SuqwKWb6ITeJWSDS3Q9POkYtJTMHnUSSJKUoi45PxDY4iVanK7pGCUCwVOFhq1KgRK1euJCQkhC+++IItW7bg5OSESqXiyJEjxMSINXBBEN5+BclZau/moLuB5CJ9tqlz9ZJ8XL80RvpybqTWYJdqCoc/sGZXY4lUGdQPvceKY7Ppfv8UMpUyx2dmPIz3n5tPuRoUyZWHkTyNTuTwzaf4PYnm7P3nHLwRyvXHUfg+EQfyCu8XnS3IGxsb89lnn3HmzBlu3LjB//73P37++Wfs7Ozo1q2brroRBEHQmYz5zq97JhyAhbE+VRzNdDCi/HF3suCHzlVoVcmWWEzYGvkd/mVasuATuFUKFKmpfOG7l+rPc651F5WQQuDzzMefHL0VRlJq2izSs5iX+UwRcaLMgFA0/J5E8zT6zR8IXSjZi5UqVWLOnDk8fvyYzZs3F0YXgiAIRaqkZdpOuvQSBHkNtmo6W+p0HDJJoo2bA33rlQLgWEIn7kSP5URXfWIax2HhGkf/kscw4b/jXbKp7H3hwYscq36/BRuShPfc44h4fB5FcvRWWO6NdaxQt3rI5XK6d+/O3r17C7MbQRCENyJjQNS0vA0tKtlSu3SJfD3D1izns91eV41SJWhW3gaAx6pSHAiZzvmSrbCvF01vvVN8V+JHqhv+xeITv1Iv1C/T/b5Popm67yZHbz3N9agUtU4PghGEzFQqNc9itXdnxiYVXaJ30e2LFQRBeIfpyWU4WRohl2U9o9TGzY7O1R3f6Jg6VnOkX31nDPVkKJHza2pv+iX/yDWZDUts5bTwP0e5qCdMvbCa7y6tp0Sidu5RslLN0dthzDx4Syvp+1WixIBQ2C4EvODe09iiHoaGCJYEQRAKgYSEhZF+7g11rJqTJRO7uFH7v+W+S+oqDIifQZMIC7Y3l9jbQEIpQfMn11nx7xw6BZxDUmvvbks/KiWngOlehgKWd0JjOHgjhORUsUtO0I3A529XNXkRLAmCIBSCoj5rLuMZczGYsf3Z91QPbcLJpmq+85Tj7wCmqYmMvraLuaeXUDo6NNNzMu6Se9XlwAi2ez3i4oMXeD+MIDI+hR3ejwv1fQlCURHBkiAIgg5UfOWsuaKW+Yw5icPxHxAfMJoyxjK+HyRnTRsZSfpQNTyQToEXMj0jKiGF+2ExPHgWy7VHkTx4FqsVPKUo1fg/y7yLThAKQy6pdIWqwBW8BUEQBDA20KNnHSd2eud8sO2bTI5OP2Muveo3QKCqDMHB0/jAciVnagdQ0jGRDmcUXHRz09xnoEwhWZ62hLj23EOtZ+al6vfz2CSCwuOp7mSBnlz8Ti68+woULI0bNy7PbefPn1+QrgRBEN568gxrb6+7Ctesgg2n7z3XzYDQPmPuVkg0Z/1fkIIeOyKHUy/+Aj1l63Fu8ISt6mlMpxt/pnRg2ukNRCjMWeHelXAj7aAover3R/WcqV7KMlN/qUoVh28+BdJmt3RdKkEQikKBgqWrV69qfe7t7Y1SqaRSpUoA3L17F7lcTp06dQrSjSAIwntDls3uugI987+q3662ppSxNuGvq8EkpCi5nNyQbrjxs/4q2si9eOh4lkbPvXAPVyFTq6n39Bbrq3RgX9nGqGTaR71svfwISUpLKM9om9fLvKXohBRO3AnDUE+uOWdPpVIXynsUirfkVBVXgyKLrP8CBUvHjx/X/Hn+/PmYmZmxbt06SpRIqzsSERHBp59+SrNmzQo2SkEQhLdAbj/iM9ZhKkhF8MKUPtN0/HYYJ+8+I0JlzhcpX9FFdpgXsiM8LCXxraeMkQf0KBOWxLAbe2gbdJnFNXpy26qM5jlqYPOlR6jrkeUME6TNQkUnpNXGaehqRYpSze6rwVibGtC6iv0beLdCcXH3adEenaazxeR58+Yxa9YsTaAEUKJECaZPn868efN01Y0gCILOFGXCaF4UVrwlkyRaV7Hnw9pO6T2xP6k9EQFf0TpSTqCDxPjPUtnUVo9YA0PKRT1h3qnFjPbZgSJVu8bS1suPuBEcmWU/ygxlv6MSUgiOTCBVpeZptKjTJGTmGxzF/utPOH47c4Xu3AqlFjadBUvR0dE8ffo00/WwsDBxmK4gCO+Ft3MuKXsWCu06UMEqJ/aGTKPVYzdslCp214VxX6RwsaIVMtRUCQ8kRaa9IJE+w5RVTaa4pJcH+B68Ecr9sLenyKDw9rn+OIrohFRCot782W+50Vmw9OGHH/Lpp5+yY8cOHj9+zOPHj9mxYweDBw+mR48euupGEAThnZBV4GSq0MPGJO/HneQl+NKTv36I5mJjgvkrAZMKGXtiPkH/wWAax6qJNJWxr8tz/DycWVqrO8r/cpf0VKlatZl2XnlMqirnopQZD+NNSFZqXQ99C39ACm8PqYh/FdFZsLRs2TI6d+7MgAEDKFOmDGXKlKF///507NiRJUuW6KobQRCEt1ZOy2ZlbUzoWt1Rp8nNViYGWBagSnhaLaasj2S5o6zMiUdTaR/qxKxnL+jpcJGF9r9TQ7oLqOlx/yRLjs9nsO8+FKlJJKWqmLrPL09nywH8dfVliYUjfk85djuMxBRlDncIQtHRWbBkbGzMkiVLePHiBVevXuXKlSuEh4ezZMkSTExMdNWNIAjCOyGrwOnVpO9KDqbUdLbUOkPuTf/+nF6L6dUZJoAkDNkRMZrJcd/wRG1FWdlT2tn9ipvzLFxiHiFXq+h1/yQrjs6h8ZMbpCpVeTpbLt2Nx9ptksRxKcJbSqfVwk6fPs0XX3zBsGHDsLGxwcTEhA0bNnDmzBlddiMIgqAT+S0QmVvCdX53wMllMtxKmmd7htyb2lDn7mTB+A6V+LxpWRq5Wmd6/ZzKnQ5Js9mobsh6SzMemUazod9tfmtZnxBjK2wToph4aR1TL/xBydhneTpbDuBGcBThcckvL2Tz16FUqXkWk4T6bc/IFwpNVEJKkfavs2Bp586dtG/fHiMjI65cuUJSUtradExMDDNnztRVN4IgCEXGxDDv1VaMDV6vMkvGcEChL8+2Heg2mEqvxdS1RsksZ5qiMeGHpDG4PWxNhaRUYuVwtuEVFg4wYHPlZqTI5NR7eptlR3+hVZA3kPPZcukO+WY+k+5Vp+4944jfU24+iX79Nyi80yLik3NvVIh0FixNnz6dZcuWsXLlSvT1X36TNW7cmCtXruiqG0EQBJ3Ja/DTuoodtUpb4mRplGvbrjUc6VzNEQO91/vvNWNKU24Bl7FBzsHU68o409S3rjOfNy1Ly0q2ABxPbE/wg/G0CzdEplbjb/2co13PM7lrcy7bVQIJbv1XjykqIYXA5wU/Oy4kMi35+16Y2FmdHzGJKUU+I1Nc6CxYunPnDs2bN8903dzcnMjISF11IwiCoDOuNia4lTSnZWXbHNvZmyuo4miep3wiM4U+FsaZl9VymwWq7GiGo4UCB3NFrn20qmxHaStj6paxysOIXk/6TFMNZ0tcbU1pXcVeE5w9xY6dTyfTIKgRZZNTidaDoMqnuNeiBCNbfkWIqY3mOYY7N6N4cCdffT94FktwZIJO38/7Rq1Ws+9aCAeuh5CiFLlgBaWzYMnR0ZH79+9nun7mzBlcXV111Y0gCILOSP+dXeZokfuMUUHltqRWu3QJWla2064Cnk1bBwsFTSvYYGQgz9fSYEHIJInuNZ0yXJE4HN+dsAff0C7ckHHhEUyT72Kh9RLKSWk73SpEPKLT+Z1UmvIlytnTuHUrkAfPYrNdmktSKjni95QLD8I5eecZMYnasyIJyeKHfl5lqAdaLHcZhkYlcvBGCM9jcy5wqlJp/1tTq9VcDYrIdzCus2Dpiy++4Msvv+TixYtIksSTJ0/YuHEjX3/9NSNGjNBVN4IgCO+UZhVsKG1lTNWS5oXy/DplSmh9XtHetFD6gZc754wyBH6hant2Pp3M1fCPiVYbUUt2nxnmk6jq9AuRJjKOl6qFDDV1/c7Q7Zcveb52HfMO+mWZ/P2vX5hWLaa/s8hn0vUsiUqlJir+3Vqq8g2O4mpQBABhMYns8QnWyUxcdGIKZ+49JyJOd/lBsUmpeAWGa/29vupWSDR/3wjJ8Tkxialanx+7HUZkfArHMlT7VqnUPAqPx/thOH5PovENjmLL5UeExbys4eX1MIJbITGcvPMsX+9DZ7+SjB8/nqioKFq2/H97dx4dVZXvC/x7ah5TlVTmOQwhJAQCYWhAkKAyKTi3t7UZFHzy1Ne4uBH1+rS7vSqvW229rS1K31Zsr1M7oN22E60og4qMCjKYQCAhZE5IUkmqkqo674+QIkVqTFWlkvD9rFVrWefsc86uTUn92MNvF8FisWD27NlQKpUoLi7G3XffHarHEBENKWkxGqTFaMJ2f5VcikyTBicb2gEA+akG/FQTvkzZvfeW215Sj067A4CAt+1zsN2ej8flf8Z/xdahXFEP/bhn8XbcXHx04k6s/uEDjG6uxB2H/o4rT36Dl08uAq5ehHEe9pUDAJu9+8evt32nmjDNzYo9X0RRdLta8cufalHdbMX0kSZkxQ7ONDc/1bTi4OlmXDY2HkaNAj+cS7kwKl6HL47UwiECXx2rw83T0oN6zpfH6mC22HC6qR3/NjW4e/X4+4EzAICfasy4cnyS25WfwWyQa7Of7zk6dKYZhyr7LgLYc7IJi/K703OU9PP/jZD23z722GN48MEHcfjwYTgcDuTm5kKnC9+/coiIaOD17C1XlBOPN74rd65Sq4YJt3Xdh3lVf4eQuB3HlTIg+QtojLvwHwkrMLP0DFYc/gip5jr8nwPvYHVyDnKSCyCTeB7k2F5S7/L+eF0bcpKiIJcKHifAVzdbsL2kDjqlDLOz43C8zoyjVa2YPy7R+WPd3mnD50dqnT0WP9W0Bh0s2ewOyKQhzcgDoPvHHujeMqY3h8N1uM2T8sZ2KGVSWLrsGJdicB7vtDngEEXnELH5XFv4uqfDIeJYTSuMGjkS9Cq0ddqg77V60mqz458/VCE7Qe9yXW2LBRIB2H2yEWOTopBkUPvsUfLHF0drkBClchsoAYDNwwd6fVc59FL/etFCFiyVl5cjLS0NGo0GkydP7nMuPT00UWq4tLe3Y+zYsbjxxhvx5JNPRro6RET9MpCpiCSCgOkjTBcs6RfwWfvViDsxE/PiX8RX0c04rWmDYuRzOBU9DitT78UNP21HtSYGzZDjsX8ewfUTUzBJaUFnXKJfz/3nD90/sNdNSoFSJnHpMerotDuHZprau/CP7884f/wPnm7GJaO7J58fqDjbZ2gnGJ/+WI0GcydykvTITzFA7iFocjhEWG0OnKg3IzVa47anpfJsBzptDp/BW0VTu9vjNrvDpU2+rzg/5Fne2O7sZXln72kAwLQRMYjWKFzuceZsB+L0SsgkAsxWG3RKGQRBgCiKOFrdigMVZ13KF2ZEY0yiHntONjp7Nn+4IOno7nNBHwBUN9ehIM2IphAMgVY3W1Hd7HmYz2yx4R/fn0Gioe/iCX83dQ5ZsJSVlYWqqirEx8e7HG9oaEBWVhbs9sE9weyxxx7DtGnTIl0NIiK3RsRpcaKuDZmm8A3p9UfP/nItF0zGrkMs3q19ENObt0OR+Hfs00hRGfsjbu06jXdkd6AG3Sv5rDYHKt7/B27e9wYa5i5GzZJfwBZl9OvZ7+3rnkj+i6lpEAQBnTaHy/wUwLWXpMvuQFVzBySCgJP1roFGgzm4eTo91x+takVpjRk/n5IGURSx+2STxw2Ev69oRkKUEhJBQFHO+d/Onvk00Ro5dF4m8F8YjADAztJ6nGpo9zhH7mx7FyrPdiBWdz442nWisU+5LwOc07P3VBOi1LKAhoAvDLjCqdViQ6ul/8PTIQuWPI0Hm81mqFS+l8JGUklJCY4ePYrFixfj0KFDka4OEREA13QDKUY1JqQaoXaTW0n0cM1A6Nlf7vXvyt2e/8Y6C6pTU7DI+BIUuiMotpTjfyuL8SfbNXjJfjms0GBC3XFI7XbEb3kfpm2foO6Kq1G78AbYdf5Niv/kUDUyTFqfP75VzZYB2dHe5hDR1NaJVovNY6DUo6dn42x7J4wahUvQeeGwmy8Oh4hT5+aueUvg+dWxOsRo+7+noCdbjwYWYA0lQQdLa9euBdC9BPehhx6CRnP+Xz12ux27du1CQUFBv++/bds2PPHEE9i7dy+qqqqwefNmXHPNNS5lnn/+eTzxxBOoqqpCXl4ennnmGcyaNcvvZxQXF+OJJ57A119/3e96EtHwF+h2Jj7vF2B5d4HShfwZhps5yoSdpQ0BPt2znlVym/dXosPNMnULVHjv7J3IaS7HPvlfUCgpwWrl3/Bp8g6omvPw3MR/w47kfNz24z8xurkSiR++hbh//QO1869B3fzrYNfq3Tz1vKb2LjS1nw3Z5wkFdyv5vPnoYDVunpaOrb1WdwXqzd0VfpdtbBtaKwAjLehgaf/+/QC6e5YOHjwIheJ8155CocCECRNQXFzc7/u3tbVhwoQJuPXWW3H99df3Of/WW2/hnnvuwfPPP4+ZM2fixRdfxMKFC3H48GHnPKnCwkLn9iu9ffbZZ9i9ezeys7ORnZ3NYImIvMo0aXCsuhWJBmVI7hfI9KIYrcJ3IT9lmLQhDZYAT6vkXB0V03FD569xteRrjI59B3VyCRB7BOmG36BJfxl+FbcGP6s+jF8e+QwjW84g6YPXoS09guPr/l9I6zqYtVkH95SVi1XQwdLWrVsBALfeeiv++Mc/Qq/3/i+AQC1cuBALFy70eP4Pf/gDVq5ciVWrVgEAnnnmGXz66afYsGED1q9fDwDYu3evx+u//fZbvPnmm3j77bdhNpvR1dWFqKgoPPzwwx6vsVqtLsFXSwv3KyK6GMikElw5PmlAn3ntxBRYbXa/k08O9DBcb71XyW09WoudpfWw2FyDJhESvO+4BOraQlzR+VcciS1BtVwGpPwLOaZtOKW7Cv8ncQ1m1xzGytJ/4cj0K6F2OFDe0A5r01kYBTsSRqVDEskPeoHhmPSRXIVsjePo0aPx9ttv9zn+0ksv4Xe/+12oHuOis7MTe/fuxbx581yOz5s3z+9eovXr16OiogInT57Ek08+idtvv91roNRzjcFgcL7S0tL6/RmIiLxRK6QwavzvVervaji5NHTBR0/Q9H+vysVlOfFuy3RAjb+fvQNtx9fiigY91A4HKlWdMKe/h3GZj+JoYiKWz1yD9XUG/PqDH/HfO8rgeOdNzHtsNVp/8zBO7z0YsvoG68LJ7TT8hCxY2rhxI3Jycvocz8vLwwsvvBCqx7ior6+H3W5HQkKCy/GEhARUVwc2XhyIBx54AM3Nzc5XRYX/48RERD1CFZ705z5JFyyjNulCN8zXoydoujDrd29nxGS8V/sgTMeXYc5ZJRQOEYW2OmxTFuPX8r8iVVLnHK7MbK2GTHRgzsnvsPiPxUj4z3th2LMTGOSrrWnoC9lquOrqaiQl9e2ejouLQ1VV8EmnvLlw0qWnlXm+rFixwq9ySqUSSmVo5iwQ0cVLFsLenECZdIoBWRkGnJ/P9MWRGnzhYUn6Eds4HKkahwn1ezFD9iGUQiNWyD7DZPWXuDc2DZaGS/HY1KXIbjqNG0q+xMwzB5Fc+gPw7A/oNJpQN/9a1C66cUA+D4WXQxRxsr4NrRYb9CoZMmO1ER92DVmwlJaWhp07dyIrK8vl+M6dO5GcnByqx7iIjY2FVCrt04tUW1vbp7eJiGiwmJoVjYqmDoxJCO0cz0AIvfqjZow04UR9+LZIAbp7mS7PTUSCQYU3vvPcG/99VyH+V9ckTJccxmrpP/BJXCVOq7qAlH8hK/5zqM/m4KnYxfhLy5VYcGoXFlXsRtTZBlhPnYJDFLt/VB0OSKwWONR9c1L5+iG2O0R8V9aI2lYL4vUqTM2KgVQyeOZHDXeHKpvx4Q9VLkObUSo5rhqf5JJ9fKCFLFhatWoV7rnnHnR1dWHu3LkAgM8//xzr1q3Dv//7v4fqMS4UCgUKCwuxZcsWXHvttc7jW7ZswdVXXx2WZxIRBWtUvB6j4n0HSuH8x3TvACAlWh32YKlHfooRwlTBY5qBbgK+ceThG0cesquOYI5pM/YbmlAvl6I+7gjUsYeRbDbgy4TZeC3nAcw4cxhl2iQ0f3IMi/ITkXGmBJe8+FuUZU/CqfEzUJqeB0WUDo3mTuw+2YiWXpm7NXIplhQkY3yqEZ8cqsJv/3HYpcctyaDCrxfnYsE4zxP7hZANqF7cDlU2u83X1WLpwuvflePfpqRBp5RFpMcppBvpNjY24s4770RnZ3cmU5VKhfvuuw8PPPBAv+9rNptRWlrqfF9WVoYDBw4gJiYG6enpWLt2LZYuXYrJkydj+vTp2LhxI8rLy7F69eqgPxMR0VAwIk7n3EgXAGaNjsWphnaUN7rfDgMAFLLzPzKetuYIl55huff2nsY+H4kkf7KNxU81Y5FYW4VLjB+g3ngcR1VSlOpbkKHajI8738dHmdNQbTehwmLFm7srsPTwl5DZujD68C6MPrwLl0qk+D52FHYl5kKVOBYtmhjn/du77HhzdwW+rziLo9WtfdI5VDdb8L//Zx82/HKS14DJH4NxeGmwsDkc+OBApdcyb+2ucPnzGcgeJ0EUQ7uTkNlsxpEjR6BWqzF69Oig5/Z8+eWXKCoq6nN8+fLl2LRpE4DupJS///3vUVVVhXHjxuHpp5/G7Nmzg3puIFpaWmAwGNDc3IyoKP8yzhIRefL6ru5/XScalJib49+Ugk9/rIZCJkHRmPOrz3ruc6Gbp6WjpKbVuVfXzdPS8cXRGq/7a4WDQxTx+0+OuvT0+CKBA5PVXyHGuA2F9mrc3tK95YdVAK5MSUW0JQpdrdlwnM7G1JPlmF79I5LbXHNKrbpsHSr13e0kt3ehSyLz2o0nAEg0qLDjvrluh+TqzVZ8cqgaJ+rMOFFrRlNHd4eBUaNw7u+2p6wJJXVmWHulUtArZZiaFYNYnRJ6lQwPLBqLt3olluwJrpo7umC2dKG9yw6JICArVosRcTqPgZZDFHGizoyyujaIEKFWSKFVytButUOrksGgkvcJ1HpfAwHIOLetzqn6dkCAyzN7B31aZffE/Tar3W0A6K5sq8WGNqsNGqUUbRYbTjW2o6TGjC5/dgV247KceBTlxPcr8Gxva8Xtl43z+fsd8mDpYsRgiYhCqSfIyTBpMHNUbND3uZC7YKmprTPgrNOh4GnoxR96tOMyyT5cKf0W0B3D2kSTy/nETsDUoUd0dTxSSqOQc7oOie2N+OX8h5zB0X27/wfj64+j1JiCUmMqSoypOG5IQb3aAFFw7XF74/afYfpI12cAwN/2VODXH/zoZVjRPzFaOXISo5CTqEdZfRu+Pt7gElz1JhOA7EQ94vVKqBVS6FRy6JUynGxow46SBrdJQXvTK2WYkhkNh0PEycZ2nG7qgM1HsCKXAKnRGlS3WD1+VpVMgrGJekRp5Ggwd+JEfRvaO8O/WlEhFTAqXocMkwZapQxtFhvau+wQAKjkEnR0OSAAzrbqCRgt7eaBD5a2b9+OF198ESdOnMDbb7+NlJQUvPrqq8jKysIll1wSqscMOgyWiCiUKhrb8VNNK2aMjPVrixNPAgmWAKDV0oV/fB/e1cvuuJvUGygt2pCn3QGD9gc0autQqhTg6NXT8EB9I65p6UKpLQnfKBOwTSuDxZqMte/sR0x73+FKi1SO44YUFM++23nshWlaFBVkQJ6QAMm5rb0+OVSF1f+zr9/1pshRSCXIiAL+df8in7/fIZuz9O6772Lp0qW45ZZbsG/fPmeG69bWVjz++OP46KOPQvUoIqJhLS1Gg7SYviu5wi1S82d65jD1DDmV1rZif0VzQPdogxbftc0H2uYDAJIkFcjU7oVGfRxt6gbkWezQCFaMl5/EcU0dfog1AajAr+4UkVEjRXa1A2POAJk1QHyDCJW9C6mOOlyveh+nlV3osuuR+MxenKjpDjAFvQ6yhHiYWyV4QKrBaV08Xs1d4KxPfl0ppBDRIVXAIlOgQ6qEVaaARaqAVSqPbKp1AgB02h04Vu15Xl9vIQuWHn30UbzwwgtYtmwZ3nzzTefxGTNm4JFHHgnVY4iIaBiSCAJGxOkAABPTozE2KbjepipHGqpa04DW7vfXwY50oRbZwmnoLIcxqeUUWhQdaJI5UJoioCRVin+eu3ZjZQ0KG2xw2ARU6s7gN3HdQ28Vgg0pCkDdCYitZnS1mpF37hq50YbCmf/AcyYtZCKwbqsDsR7iPbtOgj3X6rHF2AkBwM2brTC2iHBIALsUsEsEqEUJlJCiSyPD/llGfGswAxBQtLMDxhZH90RnARAFQG+TQeuQwq6Q4tBUI3YZu7fgmnLAguhmO0QA4rngzNglQ5RdBlEi4EhhNL6N7q5kwSELTE09w2XdZaNsMhht3WHC0UITvok+CwAYd9SC+AbXobXusnKIEHB8vAk747qDypwSKxLqbS7rBbU2KWK6upOgnsozYVtCd9nRZVYk1bjOX9PapIjt7J77XJkTgy+Su8uOONWJ1CrX74bGJkXcubI12TH4LLW7bGZFJ9IrXcuq7VLEW5Vo67Jhsfs/JhchC5aOHTvmdlJ1VFQUzp49G6rHEBHRRaB3b1OrxYZ6sxVfH69HR5f3uTie2CFFmZiEMjEJME8BemVKUKIdcYoKxMgroJbX4+8WNXarrYhBK87Y6pDd0QK7HPjTchk6IMJhFaEzC4hpFXFPVQtGmu2QyB0QpRLUyLtTQpTHimiXi1B1AapOQNkFKM/FARqZFYmKRvyg656Pdmu7A9EuW4yKABwAbIjStiFXUYE/GbonpN9YY8OIPlPLugMBqcqOQuUJ/MnYvSjgqtM25PZJadU96iPIHIiZXornjIkAgCsq7Zh4wtOsHBEp03/Cs9HdORNnV9kx+ZjnGTyjCo/gmegUAMDUGjumHvJcNn/cETx1ruyEXXZMO+CubPcf1uScI/jduTrk7PNedsbII3jsXNnMg57Lmv3M/h6yYCkpKQmlpaXIzMx0Ob5jxw6MGDEiVI8hIqJ+yjRpMDJeF+lq+K13bxMA5wa920vqfU5gDoQVGpzuHIMrf7YAf/++Crs6e+VZElX49SXn8yzVtliwo7Qe7dZOVNTX4H/tPA5NjA0ywQ7JWTPi2xohFbrw6s9skAmdkAhdkAg2SAQbYtoM0FvlkDnsOGvuRI6jHgIc2HxpBxQ2G6QOB2QOB6R2ETEdWug7FRAlAko6NBhXXwsBInaPM+PH0XYIIiCIgEQEjFY1dF1K2KUSHOqIQX5DDQCgZKQZtQk2CL0mbuu7VNDalHBIJPje+jNn2VPpZrQabRB6xRTaLgV0NhUEAAesP0N+Q/d8tqrkNuxQn++pEQBobApEdXX36hzsmoz8xu771ie042tpp0t7a2xyRHV1b7fzT8f5ss2x7fhmvGtZtU2GqC41AOBT8XzZtugOfDPedfWmyi6DobO77OeS82W7ojrwzXjXbPVKuwzRnWq0d9mA0hI33wpXIQuW7rjjDqxZswYvvfQSBEHAmTNn8M0336C4uNjnxrRERBR+M4JYWTcY9Ow1d+mYOPzu46NoC9EqK4Najivzk/DAolysWzDWYwbvn2pase9UExwiYNKpsbhgMj442IbKFmt3Z5Dt3Msb6bmXFT2dPK7He/SesmY59wLwtQ6At3jXCqD2XFkjAGOIynb2KmsA4C21kR1AzbmyegC+8q/2lNUC8NW30lNWHUBZpeeyDms78Ol2HzcKcVLK5uZmFBUVwWKxYPbs2VAqlSguLsbdd9/t+wZERDRgAl0GfWV+Ej49XA2bPfLZZmQSCa4uSPGackAu6c4WPiJeixO1bThS3eqy3F2rkGJCmhG5SVEuuYGkEqFPegC7Q8Tuk404UdcGoLuHbmpWDGRSCX6zJI+r4S4CIQuWysvL8Z//+Z948MEHcfjwYTgcDuTm5kKr1aK8vBzp6emhehQREQ2gEXFaGDRyGNTduXMGg3EpBtw8Nb3PJHC1XIoZI00uSQonpcf0O3t2e6cN20vq0WDuhCAABWlGjE06v8R8wbgkPLIkD+s/Php0niVypZRJYHeIPvM/DYSQBUtZWVmoqqpCfHw8Jk+e7Dze0NCArKws2P2cREVEROEXyML1SenRYatHMC6cBO4tCLpw/pM/alst2FFSD0uXAwqZBDNHmZBkUPcpNzs7DhKJ4JLB+2xHF6qarejslVRSJgEAoc+Pv0wCSCUSjwkoAUACQCLpe603CqkE8XoF6s2dsPS6t1ImgSjC7bwvmQQYkxiFKZndf+buMo8HSyWTIDcpCiPitc7kkRJBQIZJA4kguGQDB+CSWVwQgD0nmwLK+h4KIQuWPOW2NJvNUKlUoXoMERGFgLu/sWVS9yGUQjawe8cFoj9BkD9Kalqx99z8JKNGjtnZcdApPf9kSgShzwbJ7nqzANcf/55tRAC4bAviEMU+W430lOm9/UnvrNT6c/W7cOsRb/U4UWvGWUsXDGo5Rsbp+myjkp0Q5bLtSpvVBq1K1udZ6SYNyhva3W7NkhmrRXlDe7/3xLuwXefmJLhtq95bu3jK4N3c0YUfz7QGvEAg6GBp7dq1AABBEPDwww9Dozk/K81ut2PXrl0oKCgI9jFERBRmSln3EJZEEPD18XoMgtGPAWd3iNhzshHHz81PyjBpMO3c/KRAeQrkLvzx75GfakCb9fwoTHZC34zS/QkMA62Hv9cHUrdQBrTu6uOurTy5vtc+eNYOM97w45qgg6X9+/cD6O5ZOnjwIBQKhfOcQqHAhAkTUFxcHOxjiIhoAPT0Ovx4Ro6m9i6PiaZ1KhnM54ZCkowqVJ21uC84hFw4P2lCqhG5yQO3hVWyUY2SGrPvghSU3r2A7W2tAxMsbd26FQBw66234r/+67+4NxoR0TAwKzsOB083Y2yS756H4eKTQ9U+5yeFE4OlwStkc5ZefvnlUN2KiIgiTKeU9VlCP9xZuhwwauSYNToWepV8wJ+foFcO+DPJPyGdtbd9+3b88pe/xPTp01FZWQkAePXVV7Fjx45QPoaIiAYRbxOfh5L0GA2uyE2ISKAEoF/zomhghOxP5t1338X8+fOhVquxf/9+WK3dqUlbW1vx+OOPh+oxREQUAh4WMHulUUjdHpcIAm6cnAqZJJCEBIPPJaNjIWfAQm6E7Fvx6KOP4oUXXsCf//xnyOXno/IZM2Zg3z5mNyUiGuomZ8Qg2ajCnDFxfc7JpRJIhniw1F9KOQOs4S5kfafHjh3D7Nmz+xyPiorC2bNnQ/UYIiIKgf50oKgVUswZE9/95lRTrzMXYY4BuqiELBxOSkpCaWlpn+M7duzAiBG+drsjIqKBlGnSIlanQH6Ktx1RPZuWFdPn2MXZr0QXg5D1LN1xxx1Ys2YNXnrpJQiCgDNnzuCbb75BcXExHn744VA9hoiIQkAmlWBeXmK/r0+I4s4MdPEIWbC0bt06NDc3o6ioCBaLBbNnz4ZSqURxcTHuvvvuUD2GiIgGKbnM+/5mRENVSNd7PvbYY3jwwQdx+PBhOBwO5ObmQqcL/Z49REQ0+Mgv0gneNPyFJFhyOBzYtGkT3nvvPZw8eRKCICArKws33HADli5dCiGADfOIiGho4l/1NFwFPcFbFEUsWbIEq1atQmVlJfLz85GXl4dTp05hxYoVuPbaa0NRTyIiCtBABS+B5GyakNa/CeVEkRR0z9KmTZuwbds2fP755ygqKnI598UXX+Caa67BX//6VyxbtizYRxERUQCunZiC9/ZVRuTZcqmALnt3FKVVStFmtQMAshP0qG62oKbFGpF6hYNK5j5ZJw0fQfcsvfHGG/iP//iPPoESAMydOxf3338/XnvttWAfQ0REAVLJI/cjHqU+n5y4d8+TXCrBZWMTYNREZkuRcIjWKiJdBQqzoIOlH374AQsWLPB4fuHChfj++++DfQwREQ0h+l77xcXqlNCrZEgyDN50AzIpJ1yRZ0EPwzU2NiIhIcHj+YSEBDQ1NXk8T0REQ5u7KUuTMqJxsqEdACARgKvGJw3qxT55yVGRrgINYkH3LNntdshknmMuqVQKm80W7GOIiGgIuXAI0FugdGV+Urir4xM30CVvgu5ZEkURK1asgFKpdHveah0+k/iIiMh/WbFalNW3YWyS914bwzCav0TDU9DB0vLly32W4Uo4IqKLz/SRJkzJjIZsCPTaBJL+gC4+QQdLL7/8cijqQUREQ5xM0jcoGgqBEpEv/BYTEQ1jPSvQsmK1YX/W1BExMGrkmDHSFPZnEQ2kkO4NR0REg8vMUbGobrYg2Rj+ZftRKjkWDYLJ2kShxp4lIqJhTCGTIN2kCetwWDjm+3BbFBpMGCwRERERecFgiYiIBh2uTqPBhMESERENOJ0y8CmzsTrXPdiSjSpoldzElsKPE7yJiGjATcmMgUzShFEJOr+vYWcTRQqDJSIiCorYjzEztUKKGaNiw1AbotDjMBwREQ0J7naXM2ndb7VFFEoMloiIaNAxqP3bL25KVnSYa+KfxRO855fydZ4GNwZLREQ0aEzJjMa1E1MgvyAvlFohgU7Vd+aIUjY4JnjrVd6DO71KjpunpQ9QbSjUOGeJiIgGDblUArVCCqnk/KDbgnGJMKrl+O5ko9dr9SoZWi22fj1X5PRx8oLBEhERDToKmQQ3FKZCIvi/Ge+UzBh8cbQ2zDWjixGDJSIiCopGEZ6fEoWMM0X8JZUAdkekazF88ZtIRET9MmdMHEbGaTE2SR/pqgwKBWnGiD4/Ss3+j3BhsERERP2SbFRj2ghTWDfp9SbQWUbXTEzGtRNTwlIXAMhNjsKi/MSw3d+XJIMqYs8e7hgsERHRsOBrkrZGIYNaEd7Vc0aNAnPGxIX1GTTwGCwREdFFL5Qb9/ZeyQcA0RrfOaMuGxsf1DMFtyk7KVQYLBEREYWRSu69N+vSMXFIiPJ/CC0rVnvB/SWYk8PerHBisERERMPGpWPioJJLkJscFemq+C1B73vLFpNO4fxv/QXJOa+blIp4vapPIk8KHbYsERENCfkpBih9pBNIMapx3aRUjIjTei03kGRS/4fIVPLzn08uFTBzlAnXTkzB/DzfE8dTozX9qh/5xmCJiIiGBK1ShusmpaCnA8Xb6q8olRyzRscOUM08i9EqMCnd//3rtMrzvUYSQUCGSev3pHRJiKctcXXdeQyWiIho0PA1v0cQBCyekIyZo0zIjvee3ykt5nxPy/hUQ0jqF6gF4xJdAiBfJML5iEcT5pV7vnha1fezETEDXJPIYwYrIiKKuJmjTDjb3oVEP3ozNAoZMkx9f77crWibmxOP003tyEn0HljJQt0t48GUzGjUmzuhVkhx+EyL17LjUiIT4HkjkwgYEadDslGN9/ZVRro6A4bBEhERRVyGSYsMU+jvm2hQeQ3ACtKMqGru6LPCLBgXpg7obXSCHqMTgFZLlzNYEgT35Xv3jHmiVYan98nTnK8F55JuSjzUebhisERERBet3OSokK+ci9UpkRmrgV7pOb9SMGmdescpo30MRfaXzsPQYZTKd86o4YhzloiIaFiI1ih8FxogM0bGIj9C86R6xGjdt0fv3qglBcker/eWqNNXtvThhj1LREQ0pF1fmAKbXQz7ViYDIcWoRl2rFQofKRISDUpUN1uRYfI8VDdnTJzbeUUGtRyTM2OgkUs99iCRK7YSERENaUqZFP35zc9JCs8QVjByEvXQKqWI13uf6D43JwE2u8NlE+MLk1Kq5FIoZRJYbY4+16cY1c7/lkkF2OyuPUW98z0NpCUFyfj7gTMRebY3HIYDUFZWhqKiIuTm5iI/Px9tbW2RrhIREYVJQZoRRo0cuUmDI8t376nSEon/uZVkFwRHgaQo8PT8HiNidf26V7AGa0/X4KzVAFuxYgUeffRRzJo1C42NjVAqfaeeJyKioSkck7oDFcqNewPlafVdbxKJAIfj4pqX5M1F37P0448/Qi6XY9asWQCAmJgYyGSMIYmIaOjJOxcEZicE3zPkLVSKZLAXCYM+WNq2bRsWL16M5ORkCIKA999/v0+Z559/HllZWVCpVCgsLMT27dv9vn9JSQl0Oh2WLFmCSZMm4fHHHw9h7YmIiPqSB7BfXCAmpBmxKD8RhRn+b7ESqwvPaEqcXtmvuU8T0gZhMs5IV8CXtrY2TJgwAbfeeiuuv/76Puffeust3HPPPXj++ecxc+ZMvPjii1i4cCEOHz6M9PR0AEBhYSGsVmufaz/77DN0dXVh+/btOHDgAOLj47FgwQJMmTIFV1xxhcc6Wa1Wl/u1tHjPwkpERNSbRiHDxHQj5FIBkhBnDzf2SqHgT+7I6SNNYcnGfUVuAr6vOIsffWQq79GTRT0v2YA2qx2lteaQ16m/Bn2wtHDhQixcuNDj+T/84Q9YuXIlVq1aBQB45pln8Omnn2LDhg1Yv349AGDv3r0er09NTcWUKVOQlpYGAFi0aBEOHDjgNVhav349fvvb3/bn4xAREQEAxg6SCeYquRQT0gz4vqLZ5bjYj7G2Gyen4mR9W8CTzWO0CkwfEYYU7iEy6IfhvOns7MTevXsxb948l+Pz5s3D119/7dc9pkyZgpqaGjQ1NcHhcGDbtm0YO3as12seeOABNDc3O18VFRX9/gxERESRlpdswJRM/4fuPJFLJRidoEdyr9QE/piSGQ2D5nx28MG2m8qg71nypr6+Hna7HQkJCS7HExISUF1d7dc9ZDIZHn/8ccyePRuiKGLevHm46qqrvF6jVCq5Yo6IiCJC6SNhpS961ZD+6Y+IYdFiFy6DFEXRr6WRPXwN9REREUXatBExqGm2BJQDSSWXwtLVnZTy8rHxONXYjvwU9xOodWEIorIT9Dha3YL0GC3K6sOTw1AiAP3NcrBkQjJu96PckA6WYmNjIZVK+/Qi1dbW9ultIiIiGspGxukwMi6wlAAzR8Xiu7JGjEuJQnyUCvFRnjODJxnUmJhuDOkee2qFFDcWpkEiEcIWLAVDJfdvi5whPWdJoVCgsLAQW7ZscTm+ZcsWzJgxI0K1IiIiGhwMajmuyE1AksG/OURjk6KQaOgOqEKVSinUq/0iYdD3LJnNZpSWljrfl5WV4cCBA4iJiUF6ejrWrl2LpUuXYvLkyZg+fTo2btyI8vJyrF69OoK1JiIiGr6kbgKgSO21F61VoMHcGdZnDPpgac+ePSgqKnK+X7t2LQBg+fLl2LRpE2666SY0NDTgkUceQVVVFcaNG4ePPvoIGRkZkaoyERHRsHbhpr2LJyRBr5J7KO1qXEoUDlW65l4KZJ7xhWaMNOFodSvsDhEn6sIz1Dfog6U5c+b4zPVw55134s477xygGhEREQ1/vtIsxemVqGvtTtDsT6C0KD8RZqsNqdGaPsFSoM/uTaOQYUpmDI5UBZYgOpBVhUN6zhIRERENDLXCNWQoSDMCgN+bEhs1CqRGa0JSF6PGv14sby7P9X8h2KDvWSIiIqLIyzBpXd7H6ZW4aUqa2/lLwfI2Knfl+CQAwD9/qHI5Hkhv1PhUAwxqOVq6Ovwqz54lIiIi6kPmRxAUjkDJF4NajoF+LIMlIiIi6kMiEZy9OABgVAc/9DVUMVgiIiIit3pPgg50v7fhhMESERERDVqLJyT5LuTDjJGmoK5nsEREREQDSqPwb5sRwL+0BL5kxmoxa3Rsv69nsEREREQ+BbLazJc4vTJ0N3MjIarv/aOCCLoYLBEREZFbQSTW9n5fH+c9rXbLMHXnadIpZTDpFEg0KJ0r8kbGa6FWSDAqXoefjQhu2O1CzLNEREREg0pesgFVzRaMiNW5HFecm3AuCALm5yW6nFPKpLimIMW5dcqs0bHYXlJ//ry8//1DDJaIiIhoUFHJpbhqfHLA1/XeY+7CYUOVXNqrXGD35TAcERERkRcMloiIiIi8YLBEREREg1pOkh4yqYDcJP827Q01zlkiIiKiQW1SejQmphld5iQFQ68MLI0AgyUiIiIa9EIRKF0+Nh51ZivSYgLbuoXDcERERDSgRsS5pgTwlFcp1OKjVMhLNgQceLFniYiIiAZUokGFxROS8FONGZ02B4waRaSr5BWDJSIiIhpwepUchRnRka6GXzgMR0REROQFgyUiIiIadkK5rx2H4YiIiGjYSTGqkRClRIw2+PlQDJaIiIho2JFIBFw2NiE09wrJXYiIiIiGKQZLRERERF4wWCIiIiK3BAxQtshBjsESERERkRcMloiIiIi8YLBERERE5AWDJSIiIiIvGCwRERERecFgiYiIiMgLBktERETkVu/91UK519pQw+1OiIiIyC25VILsBB0cIqCSSyNdnYhhsEREREQeTc6MiXQVIo7DcEREREReMFgiIiIi8oLBEhEREZEXDJaIiIiIvGCwREREROQFgyUiIiIiLxgsEREREXnBYImIiIjICwZLRERERF4wWCIiIiLygsESERERkRcMloiIiIi8YLBERERE5AWDJSIiIiIvGCwRERERecFgiYiIiMgLBktEREREXjBYIiIiIvKCwRIRERGRFwyWiIiIiLyQRboCw4EoigCAlpaWCNeEiIiI/NXzu93zO+4Jg6UQaGhoAACkpaVFuCZEREQUqNbWVhgMBo/nGSyFQExMDACgvLzca2OHwpQpU7B79+6wX+urrLfzns65O+7rWEtLC9LS0lBRUYGoqCi/6t5fbNvwGSxt660M2zb4smzb/l3Ltg3ftb7KiqKIwsJCJCcne70Pg6UQkEi6p34ZDIawf8GkUmm/nxHItb7Kejvv6Zy74/4ei4qKYtt6Oce29b9sIG3o6TjbNrAybNvgy7Jt+3etP2UVCoXzd9wTTvAeYu66664BudZXWW/nPZ1zd9zfYwOBbRs+g6VtvZVh2wZflm3bv2vZtuG7Npi27U0Qfc1qIp9aWlpgMBjQ3Nwc9mj8YsO2DR+2bfiwbcOHbRs+bFvP2LMUAkqlEr/+9a+hVCojXZVhh20bPmzb8GHbhg/bNnzYtp6xZ4mIiIjIC/YsEREREXnBYImIiIjICwZLRERERF4wWCIiIiLygsESERERkRcMliKgvb0dGRkZKC4ujnRVho3W1lZMmTIFBQUFyM/Px5///OdIV2nYqKiowJw5c5Cbm4vx48fj7bffjnSVhpVrr70W0dHRuOGGGyJdlSHvww8/xJgxYzB69Gj893//d6SrM6xc7N9Tpg6IgAcffBAlJSVIT0/Hk08+GenqDAt2ux1WqxUajQbt7e0YN24cdu/eDZPJFOmqDXlVVVWoqalBQUEBamtrMWnSJBw7dgxarTbSVRsWtm7dCrPZjFdeeQXvvPNOpKszZNlsNuTm5mLr1q2IiorCpEmTsGvXLufenRSci/17yp6lAVZSUoKjR49i0aJFka7KsCKVSqHRaAAAFosFdrsd/HdAaCQlJaGgoAAAEB8fj5iYGDQ2Nka2UsNIUVER9Hp9pKsx5H333XfIy8tDSkoK9Ho9Fi1ahE8//TTS1Ro2LvbvKYOlXrZt24bFixcjOTkZgiDg/fff71Pm+eefR1ZWFlQqFQoLC7F9+/aAnlFcXIz169eHqMZDx0C07dmzZzFhwgSkpqZi3bp1iI2NDVHtB7eBaNsee/bsgcPhQFpaWpC1HhoGsm0vdsG29ZkzZ5CSkuJ8n5qaisrKyoGo+qDH73HwGCz10tbWhgkTJuC5555ze/6tt97CPffcgwcffBD79+/HrFmzsHDhQpSXlzvLFBYWYty4cX1eZ86cwQcffIDs7GxkZ2cP1EcaNMLdtgBgNBrx/fffo6ysDK+//jpqamoG5LNF2kC0LQA0NDRg2bJl2LhxY9g/02AxUG1Lwbe1u55kQRDCWuehIhTf44ueSG4BEDdv3uxybOrUqeLq1atdjuXk5Ij333+/X/e8//77xdTUVDEjI0M0mUxiVFSU+Nvf/jZUVR4ywtG2F1q9erX4t7/9rb9VHLLC1bYWi0WcNWuW+Ne//jUU1RySwvm93bp1q3j99dcHW8Vhoz9tvXPnTvGaa65xnvvVr34lvvbaa2Gv61ATzPf4Yv6esmfJT52dndi7dy/mzZvncnzevHn4+uuv/brH+vXrUVFRgZMnT+LJJ5/E7bffjocffjgc1R1SQtG2NTU1aGlpAdC9c/a2bdswZsyYkNd1qAlF24qiiBUrVmDu3LlYunRpOKo5JIWibck//rT11KlTcejQIVRWVqK1tRUfffQR5s+fH4nqDin8HvtHFukKDBX19fWw2+1ISEhwOZ6QkIDq6uoI1Wp4CEXbnj59GitXroQoihBFEXfffTfGjx8fjuoOKaFo2507d+Ktt97C+PHjnXMdXn31VeTn54e6ukNKqP5OmD9/Pvbt24e2tjakpqZi8+bNmDJlSqirO6T509YymQxPPfUUioqK4HA4sG7dOq6G9YO/3+OL/XvKYClAF46Bi6LYr3HxFStWhKhGw0cwbVtYWIgDBw6EoVbDQzBte8kll8DhcISjWsNCsH8ncMWW/3y19ZIlS7BkyZKBrtaw4KttL/bvKYfh/BQbGwupVNrnX4y1tbV9InIKDNs2fNi24cO2HThs6/Bh2/qHwZKfFAoFCgsLsWXLFpfjW7ZswYwZMyJUq+GBbRs+bNvwYdsOHLZ1+LBt/cNhuF7MZjNKS0ud78vKynDgwAHExMQgPT0da9euxdKlSzF58mRMnz4dGzduRHl5OVavXh3BWg8NbNvwYduGD9t24LCtw4dtGwIRW4c3CG3dulUE0Oe1fPlyZ5k//elPYkZGhqhQKMRJkyaJX331VeQqPISwbcOHbRs+bNuBw7YOH7Zt8Lg3HBEREZEXnLNERERE5AWDJSIiIiIvGCwRERERecFgiYiIiMgLBktEREREXjBYIiIiIvKCwRIRERGRFwyWiIiIiLxgsERERETkBYMlIqJBoLOzE6NGjcLOnTtDet8PP/wQEydOhMPhCOl9iS4mDJaIKORWrFgBQRD6vHpv5kmuNm7ciIyMDMycOdN5TBAEvP/++33KrlixAtdcc41f973qqqsgCAJef/31ENWU6OLDYImIwmLBggWoqqpyeWVlZfUp19nZGYHaDT7PPvssVq1aFZZ733rrrXj22WfDcm+iiwGDJSIKC6VSicTERJeXVCrFnDlzcPfdd2Pt2rWIjY3FFVdcAQA4fPgwFi1aBJ1Oh4SEBCxduhT19fXO+7W1tWHZsmXQ6XRISkrCU089hTlz5uCee+5xlnHXE2M0GrFp0ybn+8rKStx0002Ijo6GyWTC1VdfjZMnTzrP9/TaPPnkk0hKSoLJZMJdd92Frq4uZxmr1Yp169YhLS0NSqUSo0ePxl/+8heIoohRo0bhySefdKnDoUOHIJFIcPz4cbdttW/fPpSWluLKK68MsJWBkydPuu3FmzNnjrPMkiVL8N133+HEiRMB35+IGCwRUQS88sorkMlk2LlzJ1588UVUVVXh0ksvRUFBAfbs2YNPPvkENTU1+PnPf+685t5778XWrVuxefNmfPbZZ/jyyy+xd+/egJ7b3t6OoqIi6HQ6bNu2DTt27IBOp8OCBQtceri2bt2K48ePY+vWrXjllVewadMml4Br2bJlePPNN/HHP/4RR44cwQsvvACdTgdBEHDbbbfh5ZdfdnnuSy+9hFmzZmHkyJFu67Vt2zZkZ2cjKioqoM8DAGlpaS69d/v374fJZMLs2bOdZTIyMhAfH4/t27cHfH8iAiASEYXY8uXLRalUKmq1WufrhhtuEEVRFC+99FKxoKDApfxDDz0kzps3z+VYRUWFCEA8duyY2NraKioUCvHNN990nm9oaBDVarW4Zs0a5zEA4ubNm13uYzAYxJdfflkURVH8y1/+Io4ZM0Z0OBzO81arVVSr1eKnn37qrHtGRoZos9mcZW688UbxpptuEkVRFI8dOyYCELds2eL2s585c0aUSqXirl27RFEUxc7OTjEuLk7ctGmTx/Zas2aNOHfu3D7HAYgqlcqlHbVarSiTycSrr766T/mOjg5x2rRp4lVXXSXa7XaXcxMnThR/85vfeKwDEXkmi2yoRkTDVVFRETZs2OB8r9Vqnf89efJkl7J79+7F1q1bodPp+tzn+PHj6OjoQGdnJ6ZPn+48HhMTgzFjxgRUp71796K0tBR6vd7luMVicRkiy8vLg1Qqdb5PSkrCwYMHAQAHDhyAVCrFpZde6vYZSUlJuPLKK/HSSy9h6tSp+PDDD2GxWHDjjTd6rFdHRwdUKpXbc08//TQuv/xyl2P33Xcf7HZ7n7IrV65Ea2srtmzZAonEdeBArVajvb3dYx2IyDMGS0QUFlqtFqNGjfJ4rjeHw4HFixfjd7/7XZ+ySUlJKCkp8euZgiBAFEWXY73nGjkcDhQWFuK1117rc21cXJzzv+VyeZ/79iy9V6vVPuuxatUqLF26FE8//TRefvll3HTTTdBoNB7Lx8bGOoOxCyUmJvZpR71ej7Nnz7oce/TRR/HJJ5/gu+++6xMMAkBjY6PLZyQi/zFYIqKImzRpEt59911kZmZCJuv719KoUaMgl8vx7bffIj09HQDQ1NSEn376yaWHJy4uDlVVVc73JSUlLr0pkyZNwltvvYX4+Ph+zQ8CgPz8fDgcDnz11Vd9enx6LFq0CFqtFhs2bMDHH3+Mbdu2eb3nxIkTsWHDBoiiCEEQAq7Tu+++i0ceeQQff/yx23lRPT1nEydODPjeRMQJ3kQ0CNx1111obGzEL37xC+eqrc8++wy33XYb7HY7dDodVq5ciXvvvReff/45Dh06hBUrVvQZapo7dy6ee+457Nu3D3v27MHq1atdeoluueUWxMbG4uqrr8b27dtRVlaGr776CmvWrMHp06f9qmtmZiaWL1+O2267De+//z7Kysrw5Zdf4m9/+5uzjFQqxYoVK/DAAw9g1KhRLsOH7hQVFaGtrQ0//vhjAK3W7dChQ1i2bBnuu+8+5OXlobq6GtXV1WhsbHSW+fbbb6FUKn3Wg4jcY7BERBGXnJyMnTt3wm63Y/78+Rg3bhzWrFkDg8HgDIieeOIJzJ49G0uWLMHll1+OSy65BIWFhS73eeqpp5CWlobZs2fj5ptvRnFxscvwl0ajwbZt25Ceno7rrrsOY8eOxW233YaOjo6Aepo2bNiAG264AXfeeSdycnJw++23o62tzaXMypUr0dnZidtuu83n/UwmE6677jq3w4O+7NmzB+3t7Xj00UeRlJTkfF133XXOMm+88QZuueUWr0OBROSZIF44wE9ENETMmTMHBQUFeOaZZyJdlT527tyJOXPm4PTp00hISPBZ/uDBg7j88svdTkAPRl1dHXJycrBnzx63SUGJyDf2LBERhZDVakVpaSkeeugh/PznP/crUAK650L9/ve/d0mQGQplZWV4/vnnGSgRBYETvImIQuiNN97AypUrUVBQgFdffTWga5cvXx7y+kydOhVTp04N+X2JLiYchiMiIiLygsNwRERERF4wWCIiIiLygsESERERkRcMloiIiIi8YLBERERE5AWDJSIiIiIvGCwRERERecFgiYiIiMiL/w+1Iq+mpbI6dAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.loglog(aman.freqs[mask], np.sqrt(aman.Pxx[0][mask]), alpha=0.4, label=\"HWPSS+single mask\", zorder=0)\n",
    "plt.scatter(f_binned, np.sqrt(pxx_binned[0]), label=\"binned\", zorder=1)\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "plt.loglog(aman.freqs, np.sqrt(fft_ops.noise_model(aman.freqs, noise_fit_stats.fit[0])),  label=\"fit (free params)\")\n",
    "noise_fit_stats = noise_fit_stats_bin\n",
    "plt.loglog(aman.freqs, np.sqrt(fft_ops.noise_model(aman.freqs, noise_fit_stats.fit[0])), label=\"fit (binned, free params)\", ls=\"--\")\n",
    "noise_fit_stats = noise_fit_stats_bin_fixed_wn\n",
    "plt.loglog(aman.freqs, np.sqrt(fft_ops.noise_model(aman.freqs, noise_fit_stats.fit[0])), label=\"fit (binned, fixed wn)\", ls=\"--\")\n",
    "plt.legend()\n",
    "plt.xlabel('Frequency (Hz)')\n",
    "plt.ylabel('Detected ASD (pW/$\\sqrt{Hz}$)')\n",
    "plt.xlim(1E-4, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "56fbef60-66be-4d17-a315-54f0cdfb3f83",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7ff144623400>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15, 5))\n",
    "ax1 = fig.add_subplot(1, 3, 1)\n",
    "ax1.set_title(\"f_knee\")\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "f_knee = noise_fit_stats.fit.T[1]\n",
    "ax1.hist(f_knee[((f_knee>0)&(f_knee<2))], bins=100, label=\"free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin\n",
    "f_knee = noise_fit_stats.fit.T[1]\n",
    "ax1.hist(f_knee[((f_knee>0)&(f_knee<2))], bins=100, label=\"binned, free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin_fixed_wn\n",
    "f_knee = noise_fit_stats.fit.T[1]\n",
    "ax1.hist(f_knee[((f_knee>0)&(f_knee<2))], bins=100, label=\"binned, fixed wn\")\n",
    "\n",
    "ax1.set_xlabel('f_knee (Hz)')\n",
    "ax1.legend()\n",
    "\n",
    "ax2 = fig.add_subplot(1, 3, 2)\n",
    "ax2.set_title(\"alpha\")\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "alpha = noise_fit_stats.fit.T[2]\n",
    "ax2.hist(alpha[((alpha>0)&(alpha<4))], bins=100, label=\"free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin\n",
    "alpha = noise_fit_stats.fit.T[2]\n",
    "ax2.hist(alpha[((alpha>0)&(alpha<4))], bins=100, label=\"binned, free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin_fixed_wn\n",
    "alpha = noise_fit_stats.fit.T[2]\n",
    "ax2.hist(alpha[((alpha>0)&(alpha<4))], bins=100, label=\"binned, fixed wn\")\n",
    "\n",
    "ax2.set_xlabel('alpha')\n",
    "ax2.legend()\n",
    "\n",
    "ax3 = fig.add_subplot(1, 3, 3)\n",
    "ax3.set_title(\"white noise level\")\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "wn = noise_fit_stats.fit.T[0]\n",
    "ax3.hist(wn[wn<0.0001], bins=100, label=\"free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin\n",
    "wn = noise_fit_stats.fit.T[0]\n",
    "ax3.hist(wn[wn<0.0001], bins=100, label=\"binned, free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin_fixed_wn\n",
    "wn = noise_fit_stats.fit.T[0]\n",
    "ax3.hist(wn[wn<0.0001], bins=100, label=\"binned, fixed wn\")\n",
    "ax3.set_xlabel('pW/$\\sqrt{Hz}$')\n",
    "ax3.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70715807-0857-49e5-8760-1718e9d22225",
   "metadata": {},
   "source": [
    "### comparison of fit parameters std errors between binned and not binned"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "d04988ec-fab9-41eb-b0c2-ac8abd1d8421",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_98715/2886714995.py:15: RuntimeWarning: invalid value encountered in sqrt\n",
      "  f_knee.append(np.sqrt(noise_fit_stats.cov[i][1][1]))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7ff093385a80>"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15, 5))\n",
    "ax1 = fig.add_subplot(1, 3, 1)\n",
    "ax1.set_title(\"f_knee fit error\")\n",
    "f_knee = []\n",
    "alpha = []\n",
    "wn = []\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "for i in range(aman.dets.count):\n",
    "    f_knee.append(np.sqrt(noise_fit_stats.cov[i][1][1]))\n",
    "f_knee=np.array(f_knee)\n",
    "ax1.hist(f_knee, bins=np.linspace(0, 0.2, 100), label=\"free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin\n",
    "f_knee = []\n",
    "for i in range(aman.dets.count):\n",
    "    f_knee.append(np.sqrt(noise_fit_stats.cov[i][1][1]))\n",
    "f_knee=np.array(f_knee)\n",
    "ax1.hist(f_knee, bins=np.linspace(0, 0.2, 100), label=\"binned, free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin_fixed_wn\n",
    "f_knee = []\n",
    "for i in range(aman.dets.count):\n",
    "    f_knee.append(np.sqrt(noise_fit_stats.cov[i][1][1]))\n",
    "f_knee=np.array(f_knee)\n",
    "ax1.hist(f_knee, bins=np.linspace(0, 0.2, 100), label=\"binned, fixed wn\")\n",
    "ax1.set_xlabel('f_knee error (Hz)')\n",
    "ax1.legend()\n",
    "\n",
    "ax2 = fig.add_subplot(1, 3, 2)\n",
    "ax2.set_title(\"alpha fit error\")\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "for i in range(aman.dets.count):\n",
    "    alpha.append(np.sqrt(noise_fit_stats.cov[i][2][2]))\n",
    "alpha=np.array(alpha)\n",
    "ax2.hist(alpha, bins=np.linspace(0, 0.1, 100), label=\"free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin\n",
    "alpha = []\n",
    "for i in range(aman.dets.count):\n",
    "    alpha.append(np.sqrt(noise_fit_stats.cov[i][2][2]))\n",
    "alpha=np.array(alpha)\n",
    "ax2.hist(alpha, bins=np.linspace(0, 0.1, 100), label=\"binned, free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin_fixed_wn\n",
    "alpha = []\n",
    "for i in range(aman.dets.count):\n",
    "    alpha.append(np.sqrt(noise_fit_stats.cov[i][2][2]))\n",
    "alpha=np.array(alpha)\n",
    "ax2.hist(alpha, bins=np.linspace(0, 0.1, 100), label=\"binned, fixed wn\")\n",
    "ax2.set_xlabel('alpha error')\n",
    "ax2.legend()\n",
    "\n",
    "ax3 = fig.add_subplot(1, 3, 3)\n",
    "ax3.set_title(\"white noise fit error\")\n",
    "noise_fit_stats = noise_fit_stats_all_params\n",
    "for i in range(aman.dets.count):\n",
    "    wn.append(np.sqrt(np.abs(noise_fit_stats.cov[i][0][0])))\n",
    "ax3.hist(np.log10(wn), bins=np.linspace(-2.1, -1.9, 100), label=\"free params\")\n",
    "wn = []\n",
    "noise_fit_stats = noise_fit_stats_bin\n",
    "for i in range(aman.dets.count):\n",
    "    wn.append(np.sqrt(np.abs(noise_fit_stats.cov[i][0][0])))\n",
    "ax3.hist(np.log10(wn), bins=np.linspace(-2.1, -1.9, 100), label=\"binned, free params\")\n",
    "noise_fit_stats = noise_fit_stats_bin_fixed_wn\n",
    "for i in range(aman.dets.count):\n",
    "    wn.append(np.sqrt(np.abs(noise_fit_stats.cov[i][0][0])))\n",
    "ax3.hist(np.log10(wn), bins=np.linspace(-2.1, -1.9, 100), label=\"binned, fixed wn\")\n",
    "#ax3.set_xlim(1E-8,1E-1)\n",
    "#ax3.set_xscale('log')\n",
    "ax3.set_xlabel('log10(pW/$\\sqrt{Hz}$)')\n",
    "ax3.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "05d4eb1f-bb0f-4c8d-83e4-cf1d87b4fe78",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "SO shared + LOCAL",
   "language": "python",
   "name": "so-stack-local"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}