1087 lines
579 KiB
Text
1087 lines
579 KiB
Text
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "d0850083-6fec-4a51-8128-219c643397ce",
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"from matplotlib import animation\n",
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"import numpy as np\n",
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"import math\n",
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"import os\n",
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"import scipy"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"id": "3c65dafa-2226-4d12-a61e-f92a5f92bc97",
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_pointset(path: str) -> ([], []):\n",
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" xs = []\n",
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" ys = []\n",
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" \n",
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" with open(path, 'r') as points_file:\n",
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" for line in points_file.readlines()[1:]:\n",
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" x, y = line.split(\" \")\n",
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" y.replace(\"\\n\", \"\")\n",
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" \n",
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" xs.append(float(x))\n",
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" ys.append(float(y))\n",
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" return (xs, ys)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 38,
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"id": "b08c4be6-e653-499c-803b-e125f2e24f4b",
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_spectrum_to_matrix(freqpath: str) -> np.ndarray:\n",
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" minfreq = 1.0e36\n",
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" maxfreq = 0.0\n",
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" \n",
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" freqs = []\n",
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" \n",
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" with open(freqpath, 'r') as spectrum:\n",
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" dimension = int(spectrum.readline())\n",
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" for line in spectrum.readlines():\n",
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" freqs.append(float(line))\n",
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" minfreq = min(float(line), minfreq)\n",
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" maxfreq = max(float(line), maxfreq)\n",
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" \n",
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" matrix = np.zeros((dimension, dimension))\n",
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" \n",
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" for row in range(dimension):\n",
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" for col in range(dimension):\n",
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" frequency = freqs[row * dimension + col]\n",
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" # normalize\n",
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" #frequency = (frequency - minfreq) / (maxfreq - minfreq)\n",
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" frequency = math.sqrt(frequency / maxfreq);\n",
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" matrix[row][col] = frequency\n",
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" return matrix"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 39,
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"id": "3a4fff42-a5fe-4b80-93ba-54482e755c79",
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_pcf(pcfpath: str) -> ([],[]):\n",
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" xs = []\n",
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" ys = []\n",
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" with open(pcfpath, 'r') as pcffile:\n",
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" for line in pcffile.readlines():\n",
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" ys.append(float(line))\n",
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" xs = range(len(ys))\n",
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"\n",
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" return (xs, ys)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 40,
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"id": "4bc08371-8322-4f1a-b78a-8a0f94dd8a7f",
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_radspec(specpath: str) -> ([], []):\n",
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" xs = []\n",
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" ys = []\n",
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"\n",
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" with open(specpath, 'r') as specfile:\n",
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" for line in specfile.readlines():\n",
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" x, y = line.split(\", \")\n",
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" xs.append(float(x))\n",
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" ys.append(float(y))\n",
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" return (xs, ys)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 41,
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"id": "c08e9726-cd2b-4d8a-a0ec-ef63fc8d7334",
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_pcfseries(folderpath):\n",
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" pcffiles = os.listdir(folderpath)\n",
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" values = {}\n",
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"\n",
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" for pcffilename in pcffiles:\n",
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" cutoff = pcffilename.split(\"_\")[1].split('.txt')[0]\n",
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" values[cutoff] = load_pcf(os.path.join(folderpath, pcffilename))\n",
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"\n",
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"\n",
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" return values"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 42,
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"id": "63bb5f2d-d222-47b8-99c8-1ebb0e1839ca",
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_heck_pcf(filepath):\n",
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" xs = []\n",
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" ys = []\n",
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"\n",
|
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" with open(filepath, 'r') as specfile:\n",
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" for line in specfile.readlines():\n",
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" x, y = line.split(\" \")\n",
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" xs.append(float(x))\n",
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" ys.append(float(y))\n",
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" return (xs, ys)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 43,
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"id": "168ce96b-c7ba-49fd-b35f-f06529305a4b",
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_heck_pcfseries(folderpath):\n",
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" pcffiles = os.listdir(folderpath)\n",
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" values = {}\n",
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"\n",
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" for pcffilename in pcffiles:\n",
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" filename, file_extension = os.path.splitext(os.path.join(folderpath, pcffilename))\n",
|
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" if file_extension != \".txt\":\n",
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" continue\n",
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" cutoff = pcffilename.split(\"_\")[1].split('.txt')[0]\n",
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" values[cutoff] = load_heck_pcf(os.path.join(folderpath, pcffilename))\n",
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"\n",
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"\n",
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" return values"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 44,
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"id": "f15def42-e258-4ff4-bcff-d8cd3a1e927d",
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"metadata": {},
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"outputs": [],
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"source": [
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"def load_utk_rdfseries(folderpath):\n",
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" rdffiles = os.listdir(folderpath)\n",
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" values = {}\n",
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"\n",
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" for rdffilename in rdffiles:\n",
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" filename, file_extension = os.path.splitext(os.path.join(folderpath, rdffilename))\n",
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" if file_extension != \".txt\":\n",
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" continue\n",
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" cutoff = rdffilename.split(\"_\")[1].split('.txt')[0]\n",
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" values[cutoff] = load_radspec(os.path.join(folderpath, rdffilename))\n",
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"\n",
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"\n",
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" return values"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "cd9f363e-99f6-495d-a64c-793175509699",
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"metadata": {},
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"outputs": [
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{
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"ename": "CalledProcessError",
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"evalue": "Command '['ffmpeg', '-f', 'rawvideo', '-vcodec', 'rawvideo', '-s', '3840x2880', '-pix_fmt', 'rgba', '-framerate', '3.3333333333333335', '-loglevel', 'error', '-i', 'pipe:', '-vcodec', 'h264', '-pix_fmt', 'yuv420p', '-y', 'animation_UTK_Heck.mp4']' returned non-zero exit status 255.",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/animation.py:243\u001b[0m, in \u001b[0;36mAbstractMovieWriter.saving\u001b[0;34m(self, fig, outfile, dpi, *args, **kwargs)\u001b[0m\n\u001b[1;32m 242\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 243\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m \u001b[38;5;28mself\u001b[39m\n\u001b[1;32m 244\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/animation.py:1109\u001b[0m, in \u001b[0;36mAnimation.save\u001b[0;34m(self, filename, writer, fps, dpi, codec, bitrate, extra_args, metadata, extra_anim, savefig_kwargs, progress_callback)\u001b[0m\n\u001b[1;32m 1108\u001b[0m frame_number \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m-> 1109\u001b[0m \u001b[43mwriter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgrab_frame\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43msavefig_kwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/animation.py:371\u001b[0m, in \u001b[0;36mMovieWriter.grab_frame\u001b[0;34m(self, **savefig_kwargs)\u001b[0m\n\u001b[1;32m 370\u001b[0m \u001b[38;5;66;03m# Save the figure data to the sink, using the frame format and dpi.\u001b[39;00m\n\u001b[0;32m--> 371\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msavefig\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_proc\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstdin\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mframe_format\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 372\u001b[0m \u001b[43m \u001b[49m\u001b[43mdpi\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdpi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43msavefig_kwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/figure.py:3390\u001b[0m, in \u001b[0;36mFigure.savefig\u001b[0;34m(self, fname, transparent, **kwargs)\u001b[0m\n\u001b[1;32m 3389\u001b[0m _recursively_make_axes_transparent(stack, ax)\n\u001b[0;32m-> 3390\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcanvas\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprint_figure\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/backend_bases.py:2193\u001b[0m, in \u001b[0;36mFigureCanvasBase.print_figure\u001b[0;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)\u001b[0m\n\u001b[1;32m 2192\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m cbook\u001b[38;5;241m.\u001b[39m_setattr_cm(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfigure, dpi\u001b[38;5;241m=\u001b[39mdpi):\n\u001b[0;32m-> 2193\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mprint_method\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2194\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2195\u001b[0m \u001b[43m \u001b[49m\u001b[43mfacecolor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfacecolor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2196\u001b[0m \u001b[43m \u001b[49m\u001b[43medgecolor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43medgecolor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2197\u001b[0m \u001b[43m \u001b[49m\u001b[43morientation\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43morientation\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2198\u001b[0m \u001b[43m \u001b[49m\u001b[43mbbox_inches_restore\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_bbox_inches_restore\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2199\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2200\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/backend_bases.py:2043\u001b[0m, in \u001b[0;36mFigureCanvasBase._switch_canvas_and_return_print_method.<locals>.<lambda>\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 2042\u001b[0m skip \u001b[38;5;241m=\u001b[39m optional_kws \u001b[38;5;241m-\u001b[39m {\u001b[38;5;241m*\u001b[39minspect\u001b[38;5;241m.\u001b[39msignature(meth)\u001b[38;5;241m.\u001b[39mparameters}\n\u001b[0;32m-> 2043\u001b[0m print_method \u001b[38;5;241m=\u001b[39m functools\u001b[38;5;241m.\u001b[39mwraps(meth)(\u001b[38;5;28;01mlambda\u001b[39;00m \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: \u001b[43mmeth\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2044\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m{\u001b[49m\u001b[43mk\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mskip\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 2045\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m: \u001b[38;5;66;03m# Let third-parties do as they see fit.\u001b[39;00m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/backends/backend_agg.py:433\u001b[0m, in \u001b[0;36mFigureCanvasAgg.print_raw\u001b[0;34m(self, filename_or_obj, metadata)\u001b[0m\n\u001b[1;32m 432\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmetadata not supported for raw/rgba\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m--> 433\u001b[0m \u001b[43mFigureCanvasAgg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 434\u001b[0m renderer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_renderer()\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/backends/backend_agg.py:388\u001b[0m, in \u001b[0;36mFigureCanvasAgg.draw\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 386\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m (\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtoolbar\u001b[38;5;241m.\u001b[39m_wait_cursor_for_draw_cm() \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtoolbar\n\u001b[1;32m 387\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m nullcontext()):\n\u001b[0;32m--> 388\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 389\u001b[0m \u001b[38;5;66;03m# A GUI class may be need to update a window using this draw, so\u001b[39;00m\n\u001b[1;32m 390\u001b[0m \u001b[38;5;66;03m# don't forget to call the superclass.\u001b[39;00m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/artist.py:95\u001b[0m, in \u001b[0;36m_finalize_rasterization.<locals>.draw_wrapper\u001b[0;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[1;32m 93\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(draw)\n\u001b[1;32m 94\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdraw_wrapper\u001b[39m(artist, renderer, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m---> 95\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 96\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m renderer\u001b[38;5;241m.\u001b[39m_rasterizing:\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/artist.py:72\u001b[0m, in \u001b[0;36mallow_rasterization.<locals>.draw_wrapper\u001b[0;34m(artist, renderer)\u001b[0m\n\u001b[1;32m 70\u001b[0m renderer\u001b[38;5;241m.\u001b[39mstart_filter()\n\u001b[0;32m---> 72\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/figure.py:3154\u001b[0m, in \u001b[0;36mFigure.draw\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m 3153\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mpatch\u001b[38;5;241m.\u001b[39mdraw(renderer)\n\u001b[0;32m-> 3154\u001b[0m \u001b[43mmimage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_draw_list_compositing_images\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 3155\u001b[0m \u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43martists\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msuppressComposite\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3157\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m sfig \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msubfigs:\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/image.py:132\u001b[0m, in \u001b[0;36m_draw_list_compositing_images\u001b[0;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[1;32m 131\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m artists:\n\u001b[0;32m--> 132\u001b[0m \u001b[43ma\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 133\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 134\u001b[0m \u001b[38;5;66;03m# Composite any adjacent images together\u001b[39;00m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/artist.py:72\u001b[0m, in \u001b[0;36mallow_rasterization.<locals>.draw_wrapper\u001b[0;34m(artist, renderer)\u001b[0m\n\u001b[1;32m 70\u001b[0m renderer\u001b[38;5;241m.\u001b[39mstart_filter()\n\u001b[0;32m---> 72\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/axes/_base.py:3070\u001b[0m, in \u001b[0;36m_AxesBase.draw\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m 3068\u001b[0m _draw_rasterized(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfigure, artists_rasterized, renderer)\n\u001b[0;32m-> 3070\u001b[0m \u001b[43mmimage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_draw_list_compositing_images\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 3071\u001b[0m \u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43martists\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msuppressComposite\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3073\u001b[0m renderer\u001b[38;5;241m.\u001b[39mclose_group(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124maxes\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/image.py:132\u001b[0m, in \u001b[0;36m_draw_list_compositing_images\u001b[0;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[1;32m 131\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m artists:\n\u001b[0;32m--> 132\u001b[0m \u001b[43ma\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 133\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 134\u001b[0m \u001b[38;5;66;03m# Composite any adjacent images together\u001b[39;00m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/artist.py:72\u001b[0m, in \u001b[0;36mallow_rasterization.<locals>.draw_wrapper\u001b[0;34m(artist, renderer)\u001b[0m\n\u001b[1;32m 70\u001b[0m renderer\u001b[38;5;241m.\u001b[39mstart_filter()\n\u001b[0;32m---> 72\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mdraw\u001b[49m\u001b[43m(\u001b[49m\u001b[43martist\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 73\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/patches.py:588\u001b[0m, in \u001b[0;36mPatch.draw\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m 587\u001b[0m affine \u001b[38;5;241m=\u001b[39m transform\u001b[38;5;241m.\u001b[39mget_affine()\n\u001b[0;32m--> 588\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_draw_paths_with_artist_properties\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 589\u001b[0m \u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 590\u001b[0m \u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maffine\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 591\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# Work around a bug in the PDF and SVG renderers, which\u001b[39;49;00m\n\u001b[1;32m 592\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# do not draw the hatches if the facecolor is fully\u001b[39;49;00m\n\u001b[1;32m 593\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# transparent, but do if it is None.\u001b[39;49;00m\n\u001b[1;32m 594\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_facecolor\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_facecolor\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/patches.py:573\u001b[0m, in \u001b[0;36mPatch._draw_paths_with_artist_properties\u001b[0;34m(self, renderer, draw_path_args_list)\u001b[0m\n\u001b[1;32m 572\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m draw_path_args \u001b[38;5;129;01min\u001b[39;00m draw_path_args_list:\n\u001b[0;32m--> 573\u001b[0m \u001b[43mrenderer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw_path\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdraw_path_args\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 575\u001b[0m gc\u001b[38;5;241m.\u001b[39mrestore()\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/backends/backend_agg.py:132\u001b[0m, in \u001b[0;36mRendererAgg.draw_path\u001b[0;34m(self, gc, path, transform, rgbFace)\u001b[0m\n\u001b[1;32m 131\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 132\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_renderer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdraw_path\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtransform\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrgbFace\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 133\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mOverflowError\u001b[39;00m:\n",
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"\u001b[0;31mKeyboardInterrupt\u001b[0m: ",
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"\nDuring handling of the above exception, another exception occurred:\n",
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"\u001b[0;31mCalledProcessError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[10], line 23\u001b[0m\n\u001b[1;32m 20\u001b[0m plot\u001b[38;5;241m.\u001b[39mset_ydata(functions[keys[frame]][\u001b[38;5;241m1\u001b[39m])\n\u001b[1;32m 22\u001b[0m anim \u001b[38;5;241m=\u001b[39m animation\u001b[38;5;241m.\u001b[39mFuncAnimation(fig\u001b[38;5;241m=\u001b[39mfig, func\u001b[38;5;241m=\u001b[39mupdate, frames\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mlen\u001b[39m(keys), interval\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m300\u001b[39m)\n\u001b[0;32m---> 23\u001b[0m \u001b[43manim\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msave\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43manimation_UTK_Heck.mp4\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdpi\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m600\u001b[39;49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/animation.py:1089\u001b[0m, in \u001b[0;36mAnimation.save\u001b[0;34m(self, filename, writer, fps, dpi, codec, bitrate, extra_args, metadata, extra_anim, savefig_kwargs, progress_callback)\u001b[0m\n\u001b[1;32m 1085\u001b[0m savefig_kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtransparent\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m \u001b[38;5;66;03m# just to be safe!\u001b[39;00m\n\u001b[1;32m 1086\u001b[0m \u001b[38;5;66;03m# canvas._is_saving = True makes the draw_event animation-starting\u001b[39;00m\n\u001b[1;32m 1087\u001b[0m \u001b[38;5;66;03m# callback a no-op; canvas.manager = None prevents resizing the GUI\u001b[39;00m\n\u001b[1;32m 1088\u001b[0m \u001b[38;5;66;03m# widget (both are likewise done in savefig()).\u001b[39;00m\n\u001b[0;32m-> 1089\u001b[0m \u001b[43m\u001b[49m\u001b[38;5;28;43;01mwith\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mwriter\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msaving\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_fig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdpi\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m\\\u001b[49m\n\u001b[1;32m 1090\u001b[0m \u001b[43m \u001b[49m\u001b[43mcbook\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_setattr_cm\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_fig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcanvas\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m_is_saving\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmanager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m 1091\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43manim\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mall_anim\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m 1092\u001b[0m \u001b[43m \u001b[49m\u001b[43manim\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_init_draw\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# Clear the initial frame\u001b[39;49;00m\n",
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"File \u001b[0;32m/nix/store/k3701zl6gmx3la7y4dnflcvf3xfy88kh-python3-3.11.9/lib/python3.11/contextlib.py:158\u001b[0m, in \u001b[0;36m_GeneratorContextManager.__exit__\u001b[0;34m(self, typ, value, traceback)\u001b[0m\n\u001b[1;32m 156\u001b[0m value \u001b[38;5;241m=\u001b[39m typ()\n\u001b[1;32m 157\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 158\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgen\u001b[38;5;241m.\u001b[39mthrow(typ, value, traceback)\n\u001b[1;32m 159\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m 160\u001b[0m \u001b[38;5;66;03m# Suppress StopIteration *unless* it's the same exception that\u001b[39;00m\n\u001b[1;32m 161\u001b[0m \u001b[38;5;66;03m# was passed to throw(). This prevents a StopIteration\u001b[39;00m\n\u001b[1;32m 162\u001b[0m \u001b[38;5;66;03m# raised inside the \"with\" statement from being suppressed.\u001b[39;00m\n\u001b[1;32m 163\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m exc \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m value\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/animation.py:245\u001b[0m, in \u001b[0;36mAbstractMovieWriter.saving\u001b[0;34m(self, fig, outfile, dpi, *args, **kwargs)\u001b[0m\n\u001b[1;32m 243\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m \u001b[38;5;28mself\u001b[39m\n\u001b[1;32m 244\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m--> 245\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfinish\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m/nix/store/zkknd8lr320pzg0ip9y95d7wcq5gryaf-python3-3.11.9-env/lib/python3.11/site-packages/matplotlib/animation.py:360\u001b[0m, in \u001b[0;36mMovieWriter.finish\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 356\u001b[0m _log\u001b[38;5;241m.\u001b[39mlog(\n\u001b[1;32m 357\u001b[0m logging\u001b[38;5;241m.\u001b[39mWARNING \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_proc\u001b[38;5;241m.\u001b[39mreturncode \u001b[38;5;28;01melse\u001b[39;00m logging\u001b[38;5;241m.\u001b[39mDEBUG,\n\u001b[1;32m 358\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMovieWriter stderr:\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m\"\u001b[39m, err)\n\u001b[1;32m 359\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_proc\u001b[38;5;241m.\u001b[39mreturncode:\n\u001b[0;32m--> 360\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m subprocess\u001b[38;5;241m.\u001b[39mCalledProcessError(\n\u001b[1;32m 361\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_proc\u001b[38;5;241m.\u001b[39mreturncode, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_proc\u001b[38;5;241m.\u001b[39margs, out, err)\n",
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"\u001b[0;31mCalledProcessError\u001b[0m: Command '['ffmpeg', '-f', 'rawvideo', '-vcodec', 'rawvideo', '-s', '3840x2880', '-pix_fmt', 'rgba', '-framerate', '3.3333333333333335', '-loglevel', 'error', '-i', 'pipe:', '-vcodec', 'h264', '-pix_fmt', 'yuv420p', '-y', 'animation_UTK_Heck.mp4']' returned non-zero exit status 255."
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]
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},
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{
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"data": {
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"from matplotlib import animation\n",
|
|
"\n",
|
|
"functions = load_utk_rdfseries(\"../result_data/rdffiles_Heck_UTK/\")\n",
|
|
"\n",
|
|
"keys = sorted(functions.keys())\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots()\n",
|
|
"\n",
|
|
"plot = ax.plot(functions[keys[0]][0], functions[keys[0]][1])[0]\n",
|
|
"ax.set(xlim=[0, 0.02], ylim=[-0.1, 0.1])\n",
|
|
"\n",
|
|
"def update(frame):\n",
|
|
" # determine maximum for plot scaling\n",
|
|
" maxx = max(functions[keys[frame]][0])\n",
|
|
" maxy = max(functions[keys[frame]][1])\n",
|
|
" \n",
|
|
" ax.set(xlim=[0, maxx * 1.05], ylim=[0, maxy * 1.05])\n",
|
|
" ax.set_title(\"max_distance: \" + keys[frame])\n",
|
|
" plot.set_xdata(functions[keys[frame]][0])\n",
|
|
" plot.set_ydata(functions[keys[frame]][1])\n",
|
|
"\n",
|
|
"anim = animation.FuncAnimation(fig=fig, func=update, frames=len(keys), interval=300)\n",
|
|
"anim.save(\"animation_UTK_Heck.mp4\", dpi=600)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"id": "05a629ba-af59-4d1d-8bc8-7c55888db52c",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"ename": "NameError",
|
|
"evalue": "name 'load_utk_rdfseries' is not defined",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
|
|
"Cell \u001b[0;32mIn[17], line 6\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m animation\n\u001b[1;32m 4\u001b[0m LINEWIDTH \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.6\u001b[39m\n\u001b[0;32m----> 6\u001b[0m utk_rdfdata \u001b[38;5;241m=\u001b[39m \u001b[43mload_utk_rdfseries\u001b[49m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m../result_data/rdffiles_Heck_UTK/\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 7\u001b[0m psa_rdfdata \u001b[38;5;241m=\u001b[39m load_heck_pcfseries(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m../result_data/pcffiles_PSA/\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 8\u001b[0m utk_pcfdata \u001b[38;5;241m=\u001b[39m load_pcfseries(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m../result_data/pcffiles_UTK/\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
|
"\u001b[0;31mNameError\u001b[0m: name 'load_utk_rdfseries' is not defined"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# Plotting of compound animation\n",
|
|
"from matplotlib import animation\n",
|
|
"\n",
|
|
"LINEWIDTH = 0.6\n",
|
|
"\n",
|
|
"utk_rdfdata = load_utk_rdfseries(\"../result_data/rdffiles_Heck_UTK/\")\n",
|
|
"psa_rdfdata = load_heck_pcfseries(\"../result_data/pcffiles_PSA/\")\n",
|
|
"utk_pcfdata = load_pcfseries(\"../result_data/pcffiles_UTK/\")\n",
|
|
"\n",
|
|
"utk_rdf_keys = sorted(utk_rdfdata.keys())\n",
|
|
"psa_keys = sorted(psa_rdfdata.keys())\n",
|
|
"utk_pcf_keys = sorted(utk_pcfdata.keys())\n",
|
|
"\n",
|
|
"assert utk_rdf_keys == psa_keys == utk_pcf_keys\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(2,2, sharex=False, sharey=False)\n",
|
|
"fig.tight_layout()\n",
|
|
"\n",
|
|
"plot_utk_rdf = ax[0][0].plot(utk_rdfdata[utk_rdf_keys[0]][0], utk_rdfdata[utk_rdf_keys[0]][1], linewidth=LINEWIDTH)[0]\n",
|
|
"ax[0][0].set(xlim=[0, 0.02], ylim=[-0.1, 0.1])\n",
|
|
"\n",
|
|
"plot_psa_rdf = ax[0][1].plot(psa_rdfdata[psa_keys[0]][0], psa_rdfdata[psa_keys[0]][1], linewidth=LINEWIDTH)[0]\n",
|
|
"ax[0][1].set(xlim=[0, 0.02], ylim=[-0.1, 0.1])\n",
|
|
"\n",
|
|
"plot_utk_pcf = ax[1][0].plot(utk_pcfdata[utk_pcf_keys[0]][0], utk_pcfdata[utk_pcf_keys[0]][1], linewidth=LINEWIDTH)[0]\n",
|
|
"ax[1][0].set(xlim=[0, 0.02], ylim=[-0.1, 0.1])\n",
|
|
"\n",
|
|
"ax[1][1].set_axis_off()\n",
|
|
"ax[1][1].set(xlim=[0, 1.0], ylim=[0, 1.0])\n",
|
|
"ax[1][1].text(0.4, 0.4, \"max_distance: \\n\" + utk_pcf_keys[0])\n",
|
|
"\n",
|
|
"def update(frame):\n",
|
|
" # determine maximum for plot scaling\n",
|
|
" maxx_0 = max(utk_rdfdata[utk_rdf_keys[frame]][0])\n",
|
|
" maxy_0 = max(utk_rdfdata[utk_rdf_keys[frame]][1])\n",
|
|
"\n",
|
|
" maxx_1 = max(psa_rdfdata[psa_keys[frame]][0])\n",
|
|
" maxy_1 = max(psa_rdfdata[psa_keys[frame]][1])\n",
|
|
"\n",
|
|
" maxx_2 = max(utk_pcfdata[utk_pcf_keys[frame]][0])\n",
|
|
" maxy_2 = max(utk_pcfdata[utk_pcf_keys[frame]][1])\n",
|
|
" \n",
|
|
" ax[0][0].set(xlim=[0, maxx_0 * 1.05], ylim=[0, maxy_0 * 1.05])\n",
|
|
" ax[0][0].set_title(\"Heck in UTK\")\n",
|
|
" \n",
|
|
" plot_utk_rdf.set_xdata(utk_rdfdata[utk_rdf_keys[frame]][0])\n",
|
|
" plot_utk_rdf.set_ydata(utk_rdfdata[utk_rdf_keys[frame]][1])\n",
|
|
"\n",
|
|
" ################\n",
|
|
" \n",
|
|
" ax[0][1].set(xlim=[0, maxx_1 * 1.05], ylim=[0, maxy_1 * 1.05])\n",
|
|
" ax[0][1].set_title(\"PSA implementation\")\n",
|
|
" \n",
|
|
" plot_psa_rdf.set_xdata(psa_rdfdata[psa_keys[frame]][0])\n",
|
|
" plot_psa_rdf.set_ydata(psa_rdfdata[psa_keys[frame]][1])\n",
|
|
"\n",
|
|
" ################ \n",
|
|
" \n",
|
|
" ax[1][0].set(xlim=[0, maxx_2 * 1.05], ylim=[0, maxy_2 * 1.05])\n",
|
|
" ax[1][0].set_title(\"UTK implementation\")\n",
|
|
" \n",
|
|
" plot_utk_pcf.set_xdata(utk_pcfdata[utk_pcf_keys[frame]][0])\n",
|
|
" plot_utk_pcf.set_ydata(utk_pcfdata[utk_pcf_keys[frame]][1])\n",
|
|
"\n",
|
|
" ################\n",
|
|
" ax[1][1].clear()\n",
|
|
" ax[1][1].set_axis_off()\n",
|
|
" ax[1][1].set(xlim=[0, 1.0], ylim=[0, 1.0])\n",
|
|
" ax[1][1].text(0.4, 0.4, \"max_distance: \\n\" + utk_pcf_keys[frame])\n",
|
|
"\n",
|
|
"maxkeylen = max(max(len(utk_rdf_keys), len(psa_keys)), len(utk_pcf_keys))\n",
|
|
"\n",
|
|
"anim = animation.FuncAnimation(fig=fig, func=update, frames=maxkeylen, interval=300)\n",
|
|
"anim.save(\"animation_compound.mp4\", dpi=600, writer=\"ffmpeg\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"id": "2a1e9a6e-a307-47c8-8aa6-de7c5a3166f3",
|
|
"metadata": {
|
|
"scrolled": true
|
|
},
|
|
"outputs": [
|
|
{
|
|
"ename": "FileNotFoundError",
|
|
"evalue": "[Errno 2] No such file or directory: '../cmake-build-debug/spectrum.txt'",
|
|
"output_type": "error",
|
|
"traceback": [
|
|
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
|
"\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
|
|
"Cell \u001b[0;32mIn[19], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m spectrum \u001b[38;5;241m=\u001b[39m \u001b[43mload_spectrum_to_matrix\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m../cmake-build-debug/spectrum.txt\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3\u001b[0m (px, py) \u001b[38;5;241m=\u001b[39m load_pointset(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m../result_data/sampled.txt\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 5\u001b[0m (pcfx, pcfy) \u001b[38;5;241m=\u001b[39m load_heck_pcf(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m../psa/cmake-build-debug/sampled_rdf.txt\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
|
|
"Cell \u001b[0;32mIn[16], line 7\u001b[0m, in \u001b[0;36mload_spectrum_to_matrix\u001b[0;34m(freqpath)\u001b[0m\n\u001b[1;32m 3\u001b[0m maxfreq \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.0\u001b[39m\n\u001b[1;32m 5\u001b[0m freqs \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28;43mopen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mfreqpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mr\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m spectrum:\n\u001b[1;32m 8\u001b[0m dimension \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(spectrum\u001b[38;5;241m.\u001b[39mreadline())\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m line \u001b[38;5;129;01min\u001b[39;00m spectrum\u001b[38;5;241m.\u001b[39mreadlines():\n",
|
|
"File \u001b[0;32m/nix/store/7km40f9z07gb81vd3041jm5l4v7xk4aa-python3-3.11.9-env/lib/python3.11/site-packages/IPython/core/interactiveshell.py:324\u001b[0m, in \u001b[0;36m_modified_open\u001b[0;34m(file, *args, **kwargs)\u001b[0m\n\u001b[1;32m 317\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m file \u001b[38;5;129;01min\u001b[39;00m {\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m2\u001b[39m}:\n\u001b[1;32m 318\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 319\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIPython won\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt let you open fd=\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfile\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m by default \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 320\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mas it is likely to crash IPython. If you know what you are doing, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 321\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124myou can use builtins\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m open.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 322\u001b[0m )\n\u001b[0;32m--> 324\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mio_open\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfile\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
|
|
"\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '../cmake-build-debug/spectrum.txt'"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"\n",
|
|
"spectrum = load_spectrum_to_matrix(\"../cmake-build-debug/spectrum.txt\")\n",
|
|
"\n",
|
|
"(px, py) = load_pointset(\"../result_data/sampled.txt\")\n",
|
|
"\n",
|
|
"(pcfx, pcfy) = load_heck_pcf(\"../psa/cmake-build-debug/sampled_rdf.txt\")\n",
|
|
"\n",
|
|
"(specxs, specys) = load_radspec(\"../cmake-build-debug/radSpec.txt\")\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(2, 2)\n",
|
|
"fig.tight_layout() \n",
|
|
"plt.rcParams['figure.dpi'] = 800\n",
|
|
"\n",
|
|
"\n",
|
|
"ax[0][0].set_aspect(1.0)\n",
|
|
"ax[0][0].scatter(px, py, s=0.2)\n",
|
|
"ax[0][0].set_title(\"Points\")\n",
|
|
"\n",
|
|
"ax[0][1].imshow(spectrum, cmap=\"gray\")\n",
|
|
"ax[0][1].set_title(\"Spectrum\")\n",
|
|
"\n",
|
|
"ax[1][0].plot(pcfx, pcfy, linewidth=0.5)\n",
|
|
"ax[1][0].set_title(\"PCF\")\n",
|
|
"\n",
|
|
"ax[1][1].plot(specxs, specys, linewidth=0.5)\n",
|
|
"ax[1][1].set_title(\"Power spectrum\")\n",
|
|
"plt.savefig(\"fullfig_generated_utk.png\", dpi=800)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"id": "41753602-44bb-44a9-a050-f1887589bd96",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
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"text/plain": [
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"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
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"fig, ax = plt.subplots(1,2)\n",
|
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"ax[0].set_aspect(1)\n",
|
|
"#ax[1].set_aspect(1.0)\n",
|
|
"\n",
|
|
"pointset = load_pointset(\"../utk/cmake-build-debug/src/samplers/points.txt\")\n",
|
|
"ax[0].scatter(pointset[0], pointset[1], s=0.1)\n",
|
|
"\n",
|
|
"rdf = load_radspec(\"../utk/cmake-build-debug/src/samplers/rdf.txt\")\n",
|
|
"ax[1].set(xlim=[0.0, 0.26], ylim=[min(rdf[1]), max(rdf[1])])\n",
|
|
"ax[1].plot(rdf[0], rdf[1], linewidth = 0.2)\n",
|
|
"\n",
|
|
"plt.rcParams['figure.dpi'] = 400\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 45,
|
|
"id": "a217ce8d-fd36-4e2d-8c4a-90dba8c06cb4",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import os\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"from matplotlib import animation\n",
|
|
"\n",
|
|
"\n",
|
|
"def generate_forceseries(path: str):\n",
|
|
" forces = []\n",
|
|
" for i in range(len(os.listdir(path))):\n",
|
|
" with open(os.path.join(path, \"force\" + str(i) + \".dat\"), 'r') as forcefile:\n",
|
|
" xs = []\n",
|
|
" ys = []\n",
|
|
" for line in forcefile.readlines():\n",
|
|
" x, y = line.split(\" \")\n",
|
|
" y.replace(\"\\n\", \"\")\n",
|
|
" xs.append(float(x))\n",
|
|
" ys.append(float(y))\n",
|
|
" forces.append((xs, ys)) \n",
|
|
" return forces"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 106,
|
|
"id": "122d231d-483c-46e8-8600-883a0e7b11fb",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
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"text/plain": [
|
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"<Figure size 640x480 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"forces = generate_forceseries(\"../result_data/forces_unmodified\")\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(1,2)\n",
|
|
"\n",
|
|
"\n",
|
|
"def update(frame, n):\n",
|
|
" maxx = max(forces[frame][0])\n",
|
|
" maxy = max(forces[frame][1])\n",
|
|
"\n",
|
|
" ax[n].clear()\n",
|
|
" ax[n].set(xlim=[0.0, maxx * 0.2], ylim=[0.0, maxy * 0.2])\n",
|
|
" #ax.set_title(\"frame \" + str(frame))\n",
|
|
" ax[n].plot(forces[frame][0],forces[frame][1])\n",
|
|
"\n",
|
|
"update(len(forces) - 1, 1)\n",
|
|
"update(0, 0)\n",
|
|
"\n",
|
|
"ax[0].set_aspect(0.12)\n",
|
|
"ax[1].set_aspect(56)\n",
|
|
"\n",
|
|
"fig.tight_layout()\n",
|
|
"\n",
|
|
"\n",
|
|
"plt.savefig(\"/home/clara/repositorys/bachelor-thesis/thesis/media/f_converged_non_converged.png\", dpi=300, bbox_inches='tight')\n",
|
|
" \n",
|
|
"#anim = animation.FuncAnimation(fig=fig, func=update, frames=len(forces), interval=300)\n",
|
|
"#anim.save(\"animation_forces_16384.mp4\", dpi=600, writer=\"ffmpeg\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"id": "da02f09d-7498-423a-af68-e2e1a729efd4",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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1NXXqVCcrK8td0+9+97sOAOfpp5/2nLdhwwYnPT3dOffcc50lS5Y4zz//vDN27FgnLy/Pqaqq8pz7/e9/31m8eLHzxhtvOI899pgzfvx4Jycnx/nkk0/E+f7mN79xADivvvqqdk1WrFjhJCUlOWeeeabzwgsvOC+++KJzzjnnOImJic7KlSvd8+bOnet8//vfd5599lnnjTfecIqLi53TTz/dAeA88cQTnjarq6udQYMGOXl5ec5jjz3mvPLKK+7877//fve8jRs3Ojk5OU52drZTUlLirFq1yvOPzv+qq65yfvKTnziLFi1y137UqFFOQkKCs3TpUu38LD4/AHBeeOEF9/9bt251QqGQU1FR4TlvypQpzt13333E/S1cuNCJj4/3tW9hYdF9YYndUcL69eudyy+/3MnJyXGSkpKcQYMGOddee62H7Lz//vvOpEmTnLS0NGfAgAHOf/7nfzp/+ctffMSurKzMmTZtmtOzZ08HgDN48GD3s88++8y5+uqrnZycHCcxMdEZNWqU8/vf/95pb2/3jKcrxO4///M/HQDOG2+8EdNcX331VefMM890UlJSnOzsbGfOnDnO3r17PeeoZLzf+c53fNf/9a9/dcaNG+ckJSU5/fr1c2677Tanvr7ed159fb1z2223Of369XOSkpKccePGOc8++6w4pg8//NCZMmWKk5qa6mRkZDizZs1ytm7d6jvv0ksvdfr37+8kJiY6/fr1c6699lqnrKxMO9eRI0c6BQUFTkdHh3FN3n77bWfy5MlOamqqk5qa6lxwwQXOihUrPOc89thjzoQJE5zs7GwnISHBycrKcqZPn+688sorYps7d+50vvnNbzpZWVnu/B9//HHPOU888YQDQPuPEsZ58+Y5hYWFTmZmphMfH+/06dPHueyyy5z333/fODeLzw+c2P3tb39zADhpaWmefwkJCc4VV1zhOE7n35rpH/+bV5g2bZpzySWXfB5Ts7Cw+JwQcpwYkmJZWFhYWBxzhEIhvPDCC5g1axYAYOHChW4Ud3x8vOfc9PR09OvXD21tbdi2bZux3aysLDfdkcJnn32GoUOH4vnnn8ell156VOdhYWFx/GDz2FlYWFh8QXHqqaeivb0dVVVVOOecc8RzVILvruKJJ55A3759cfHFFx/pMC0sLL5AsMTOwsLC4jiioaEBW7dudf+/Y8cOrFmzBtnZ2Rg5ciS+9a1vYc6cOXjggQdw6qmnYv/+/Xj99ddxyimnYMaMGYfVZ0dHB5544gl85zvf8VV3sbCw6N6wplgLCwuL44g333xTjGj/zne+gyeffBJtbW341a9+heLiYlRUVCAnJwcTJ07Evffe66YQ6ipeffVVTJ8+HZs2bRLLzllYWHRfdDndyeFkSV++fDmKioqQkpKCoUOH4s9//vPhjNXCwsLiqON4f6edd955cCKBbJ5/Ki1QYmIi7r33XuzYsQOtra2orKzE888/f9ikDgCmTZsGx3EsqbOwOAHRZWLX1SzpO3bswIwZM3DOOedg9erV+OlPf4rbbrvNl5/MwsLC4njAfqdZWFicSDgiUyyP4JLwk5/8BP/4xz+wYcMG99jNN9+MtWvXYtWqVYfbtYWFhcVRh/1Os7Cw6O445l6zq1atwrRp0zzHpk+fjsceewxtbW1ITEz0XdPS0uIpvdXR0YGamhrk5OTY7OgWFl9COI6D+vp65OXlxVSm7VjCfqdZWFgcDRyr77VjTuz27Nnjy5+Um5uLcDiM/fv3i0Xt582bh3vvvfdYD83CwqKbYdeuXcjPzz+uY7DfaRYWFkcTR/t77XOJc+dvpE5A0fG7774bd9xxh/v/2tpaDBo0CLt27cLidfvx3o4anDEkGwDc368/eygA4OFlW/DSx5UY0KsHfjd7HLLTk912ahpa8OKaCswqHOAef/yd7XhnSzWSE0O4b9YpnvMppGspHn9nu2cs0vn8GL1mVuGAwPOlsby4psLTr2pz3IBM9EiKF8cbNJeuzovj4WVb8PKne3DRyf1w65QRvjZou6ZxxroGAMRzDmfsQeOS5qJ7rt7bUYO4ENDhwHd/pOdXNz7Tc8KvifXeSvPQfc7HqRvT5JF9sHzzvpieK2nd+Jjo/6cMy8C40cPQs2fPwHY/DxzN77SMjIxjN1ADfvPyRtx1Udfz31lYWBwd1NXVYeDAgUf9e+2YE7t+/fphz549nmNVVVVISEgQi6oDQHJyMpKT/RtDRkYGrjm3D3qklWN2UYTdqt8zohtJSno6klPTMXFMfxTk9UF1QwsWl0bOeWXLPqze04oeW+pw0+RhAIBrzh2DHmnlmDK6L17ZWIXZRfnIibalu3Z2Ub57PCc9GdUNLXASemDCyAG4ZmIBMtKT8ezqbb6++DHVt2ov6Hw6nttn9ImMPyPDswa0zRzN5iqNjc9XXUvbawPwypZ9uObcMdq21T1ISElDSnp69J5521hcWo5LioahR1pP3zj5GNRYnU9qkJqc4B7PyABuz+vjXkd/V21cUjQMTmIPOA7QFpcs3n8ONdamljBWl9f61p6OOyN676U1oc/VsuhzlZGejEuKhmHt3lZcUjQMWWlJnntH7wt9xug1Bbk9PXPl6yCtF6JrTn/n86DgzzOAwPt3e14fLFguj5/2r/5e+HPMnzX+LD/1VsSf7Ytgtjza32nHi9ilpKYft74tLCw6cbS/1445sZs4cSJKSko8x1599VWcdtppoi9KEHLSkz2bMt+g50wsQGqSd0Nbua0aANxj6idtb8Hybe55qk3dtfT4TZOHYXFpOdaU12LSsBx3c5f64sfoXGI5n/er2uBEU0fWVBtTRvf1tKvOaWoJY015ra999TtdI9PGze+Brg1pnHwMqo2m1rDvuuqGFhSvLANCkfuu1p6uU2pSAlZuq0YqGevsonwfgVT/V2szc3yejxhJ/d+5aC0amsN4d3s17r98vI/wZqUleea5bGMVOhygZN1ud41U/00tYRQOzPQ9Y0BE9Vu2sQrDc3v67qs0frpeAMTfdc+J9DzHcv+aWsMozJfHT68pXlmGknWVaGoJY+60UZ6+dc/yrMIBmIsvBo72d5qFhYXF0USXiZ0pS/qgQYNw9913o6KiAsXFxQAi0WL//d//jTvuuAPf/e53sWrVKjz22GN49tlnj8oE+AbHiQ3dzOln/LrZRfloagmjqTWM6oYW3zEAWhJmIozVDS1YsHybpx+uiulgmgudAydDfJMO2tTVOYUDMzFpWI5IfHj/unaD5ietlW4MfB1Tk8o91y0uLUfJukoAEQIXRJJpW3cuWovmtg53LVT/726vRocTIUapSZ1/HlNG98W726td4qT6b27rQE1TKxLi4zxrrrsnLvFqCRtfDugcDjS2+vouXlWGkrWVaGoNY+7UUT7iKa0X/133nKjzpozu63l2OfkEyDPYGsaaXZHxq/nR8zz9q5fTkPfeK/B5LC4tx/QRx05Z+qJ9p1lYWFgcCbpM7D788ENPlnTlN6KypFdWVmLnzp3u50OGDMGSJUswd+5cPPzww8jLy8N//dd/4Rvf+EaXB1vT0IJnV2/zkAadkqI20WUa86raiNR1OenJSE2OqjtJ5dpjOqVE939J3TORq6aWsMfkSMfMFQ0dGQpSKfmmTBU81aekzFBiRNUZ2i7vW1L1uMpKCQNV3ujnEllUxBshP6mmffP+FpeWoyXcgZTEON/6qGeGEy+ltFHVjF9juieSSqVURGk9KalfXFru6xsqSVH0Jyee0ksBXw+uwNJnQFKxFfkszM/0P4P5nfPlJLW6oTMaFOhU1RVx5Aoy/V21f6ixHscKx/M7zcLCwuJoo8vETmVJ10FlS6eYPHkyPvroo6525cOLayqwek8rAK96xpU2rr7Q86WNSOFwzKFB/49F3aP/l0yOJnVM/VQbKN8oTRu8jmTStrlqo8aj1BluqtOpek2tYY/CRCGZ/gA9CaegJFhSoCSiTOfGzX6KhHBTrM6Mq8ZDyV5TaxhwvESZq1TcPL1mVy0KB2Z6xiMRb4U5kwo845OIJ19jfq8lMkcVZt0zS59R6e+Dj1f3nJWs3e0z/XMSqNqYPiLjmJlij+d3moWFhcXRRreq/jyrcIDrmK0gqWqSkqLANzMF6q9FwdUfE1GTTFX0ej4eSphMJscg06ICJzNqXjoFUWqXkxZJudORU8m8rc4rXlkWOckxnyeRM0XCOck0kWpKQpZv3ufxgYvFr5KbYrkZt17jV5eTnuzx61PtUr9D3fwl86yOeAeZ6fn90N0zDunFhJPfrXvrsa68FlNG9w30n5TUSJPpn5uwVftlu/cZx21hYWFhEUG3InbZbDNT4JsW3WwkZ3PJ903nryX5Y/HrPcqLoDxJCiIg+xJxc6u6nv+uM9MCesd5riByckDHSs/niihH0KYMeBUm3ocpQIOOlRMHripKSmV1QwvWldeiua0Di0u95nR1PiWMOpJF16cl3IEDTa1ISohz26TrQMchqXt8Hh61cGWZu9Z87fn958EjPJgh6LkNUvGk5wGQ1UGdeV6pu1SNlF6u1JpwE7bCi2sq+GNnYWFhYSGgWxE7CTr/K45YTKaSv5bkjyW1p9vYANkXi3+mM7fqfpfMtGrzpopKVlqSpx/T+gF+p3dJEdWtpbQpS8RGZ+blaxikSpmUN4Wc9GTcf/l4HzmmKp52DStqPQELSpE9vSALM8fl+e6l5F+ozMhKAVTEpqk1jKYWL1mW1pr+n99/3cuIGkvQcxtkXtadIxFXRer5S41ElKVnUSJ7dExfpKhYCwsLiy8yuh2xCwpO0J3PNyPJWX3OpAIsLi33XK/bcCTzEvc7M/liqTZNprKu/E6PUUVFERUFE8EFYNycY/nJybXp/pSs2+3xneNrKKVqkfqIxTTMycq726tdFS9oDdU9o76Aw3N7IistyUuKhXQfyozMFUDJXBvLGvNj0suI6Z5QFZDeE0WOJZ9EBelecqWNknV6zwC4wSK6ABuTenzVqX1gYWFhYRGMbkfsgoITYiF+ylldZzKl5+rMlfx6SYWSVL0gfzfVp27D05lpTUSMoivEIVao8RavKgOciNlVlx5DjVkKYDGZAQG96VoHHYGQVDyOIEKlTJ0t4Q73c/pMcGJFo2ABOX2KpD6b8jbmpCdj7rRR7rWSz6bULlcF6Xia2to95nS6htKY+TypegrAp4Tya2IJ4JldlI+aujrxPllYWFhYeNHtiJ3OHKc2Nh5BGcsGLalmJhOv1KZkFjQRFT62IFOxgo7sqDZMKV6kz0wkUheVKo1tcWk5StZGzYLJCZ70GCYFkAce0HtJVVaey01aB642mdaX+/VJARZ8TaUcdtzUGSsppoqgUv5M+QhVn9LzyNeDk9iglyE6ntTEeC3ZXlzqTbtiynU4ZXRflKzb7SqY/FxOKHUEV5331FvWx87CwsIiFnQ7YicpaIBeBeLEhUegUtWFqgrSZs/HwFUSwE9aPNGBgv+azmldp7rpiKoUoMH98HjyXb7xc2JkUtbEZM4kzYd7HvMl42SFrx8dL58DJRXSOqigETo/aX2lqFRqmtWtG11biZzGavJW68erTJjyEQIyeZWeiyAiJ/0NKYI1c3yex12AP6P0fppMqlwV1/lB6kze/FzrY2dhYWERG7odsTMlq1U/Y/Xz0qkuqh1ps9dl6+emWynq1pSrjatlpjQp9BwpIEGpSzzSU5d8V33Oc+iZlDUpmTPPTyel/jCZV9V66JIf05/SOqhUMdxRn6/vH17d5CYLVn6V98wY466xFDWr1rRk3e6IXxsbs6RcURLEiZeuykSQSV1XWo0TVTVuGrktvYgo6PLg+cy4mhJtPCDF9KISlIZFOpZtCIyysLCwsOhEtyN2Jr+1rmx0/Ljk28T9sLjCp2tXGiffrKiZ8/0dB0RlUFLhAH35LhqgwRUS+hn39+LESKfsBG3IEsHhpjbpOu6XKPk/Bj0HvnkYyDdNFmwKCJDWWAp6oOW95kwscM/n57rR0wblVmeyVOOT8hzqzMxS5Qiu+qnrpdQvJjMu/5uRXoTo2pnunRTJzNfjWJYUs7CwsDiR0O2IHScGOrNdLBudKV2GRFK4wme63qQw0TEW5mciJTEOLWG/MqiUq5nj/ak1JJXEE7UrBC3o5iUd183flLJCuhemigg6v0Qpbx4vyaUjypwQSeSbJgum68l/j8WsCcBT3ktaI07CjFU2mJ8dh6QI6541nWpmynMo5Qrk5nTd35KUVkbnD8rHy3Py8Weu5sBB31pYWFhYWPjR7YgdR6ymHEB21KbnmSJaebu6FBJSIln1fxNB4MqGIjIzx/XH8NyeHlJEx6PzDZPIAx2Hzp9OtR80f7cd4s8WFDXJ10G1wxMLS1GbVGULIp0SIeKpVSiBVjDl3OMmWto/L+9F58IVTx3hlvzsTGRbUr2kyFhJ1eWqn85krKASPKugGOm+mgIpuDorvVgsLpVz8qlra2oO+u6phYWFhYUf3Y7YmaIbg6BTj2KJaKXnUagNDYiku5ASyUrtmdJYAPDVFuX9qY1RStthMhFLqg0nmiYCwvug/mwAfJGelCTxddCRMWntqcqmI52S0qcLAFGIJUCBmmjf3LQPf/twF/r2THH7lyKLJX82Trh1pm11vs6UqlujWNRriYBJJmPappTomGNxaTne3KSPLFbroguiUPeP5+RT61+2ex9+qu3dwsLCwkKh2xE7E2nRpefg13ITkG5zlQijLhedVHWBj5GbeXn6EY/TvgPMHN8fcyYWePrmUbwmPzhJVVObbfGqMl+CZkpgTKXRVN/cn42us04ZNEUC86AFCtN16nNTfjYa7RnkKygFKKhz3t1ejezUpMBKJBKh0tVMVedwdU1nSqWfm86Xrg1SYjl0KrU09ne3V/tcCkw+evzvV5cYGbDBExYWFhaxIu54D6ArePyd7QAiG8SyjVVYua3aVcsAsok48JizFizf5vEPkjaoxaXlns/pdUBnAtjilWWefmcX5WPSsBy3ViclLyXrdmPhB7siiXsJVJ/3LdngaYseX1Nei9SkBN9Ym9s6kJygV0/ofNTY4MDXz5pdtW7wADVH0jnxPmYX5aNwYKZrtgPgWTP6u9t3qLNvvqb8fujWha4/v4/0uDRuqtLq7rkiSOrZmjOxwFNFgY73/svH48KTcgN9GqeM7ou4EDx599bsqkVqcuc95eOl4zIlK+brpcYuPd90fro1kqDWVY1TXU9zDNI1AoD7Lx+PySP7eNaN96fGyP9++Vz4s2JhYWFhERu6lWL33o4a9Egr97z569QJnTkLCFZsAL0Cw5U5oynYYT/ZOIsG9cLDb27zRYzq0pso9emeGWPEAAdOMKQoUdqPrtC9DlJUqC4YQ/LnCjILmuavM9sG+ZpJ95f7ApqCbbh5UQI1sQKRZ66pJWzMuxfkkybNV7deOgXa5N8pqc60L13gA/1dMq3qjnHTtEmNNN1vCwsLCwszuhWxO2NItkiodLngANn3SiIDvJ0gMxiFjtwop3pudqLEocOJOPbThLo6lYL7CErkUzKhcvKpI3wKOhOutB6xEBBdhKrOZJ6VluS7j7oKBVLOO939VShZtxufVTehZN1uzJ06SnxG1Hi5eTEo+COWFwDJpM7PkUibdF/43GIxtUpEj0e+ml6c6D3kLyW6exVE1LhpmfZf3dCCp6JqvYWFhYWFGd2K2F1/9lBkMH+6WJQg7nsVq0oXi1JAN2mdP5nJYRzwK2e6+ehywUk/dWSTQvLTMo1LXSM5veuIM2+frgcPaDCRRK6AqfOlnHc6ouaCKan0GQHKPGSWB6eYVDVKNGnKDgU6F11i7KCXFN194efQdqV7xs/hka9S4IOC9ExTRU4ql8af3VgCPajP53s7amBhYWFhEYxuRewAOd9XLIoE/VxnPpWUCwWdiqX83lIS41x/MtWWpD5s3VuP+5ZswD0zxmB4bk+fcib5a9EEuLS6g061zEn3l3DSBWyYlJSZ4/N8aTykvkzEOUhB4oSM/qTrLgWn6Ai6NCY6Zl16EiDYPE3VTn6fJKIpvYAUDszEeaP6iKTbRIpNSitXm7mJnt/7WCJfTWMx/c3FYlIOqi7C53OosR7P+e6GhYWFhQVHtyN20kYfpEjoIkc5yZF8yHibunJc6qfOn0y1deeitViz6yDuW7IBT1w3wTc+MSJV46tnUi11Gy+vJWsiU+p4LD5buvWWzHKmSF4pcli1TUlQdUNLJChFsyZBChFXmRTOGdEb6ypqRf87uhaS2Vu1o8uHqCO0OheAIOWTQucTRxVgqY6wNC5pDYOeCd6GOkcy1eqUVt18bpo8DNefPdTWirWwsLCIAd2O2LnpK8bJ6SsAf3JgDtNGZzJnuv5vK8s8Zj5upuLtUNwzYwzuW7IBt543TKzbKamGXGGS0roEkVlKOmhgQlDaDJO5MUgBBSCa5fh9CjLL6chlydpoQluSOFd3XZDfFwDPM6FMvvQ63jY390qmd3o/6fx095G+BAQpX7QNiUDxZyKWmsN8XWIZS1cTRksEWDLh8/lYHH04joNQKBR8ooWFRbdBtyN2UpJhnVphMkkB8kbH1TPJx4ya+STSoc6jn6lxzi7KxxPXTTBG6wKIpDspldtXVSlUyglOPKkKJak8vLQX34RNTvxcbTFVRzCRRH6fOEkKIjWKMMHRkxneH39uJPLAnwn6vHFVyvXLc8o8xJtHJutUYFd9ztdXm+Dz5W4COgLFnwV672nKEqpY0zXkfQWZoE1EUOfvWbJ2t6d8miVzny8sn7OwODHR7Yid9LYvbQgSIZA2ILrRmUxRgKyOmNQLk3lMIjPSRi9u3NEv5NTk+C6Z5HQbrE5BAfx+fEFJdmNRavh90pGkIHMu9Tfk5lyJgKj+dAEKEvHlZE40z7PaqzoTLScsvG3AnJ4HTifhN62Ngu5eBJlm1VhK1lUCIXjWWZmgCwdm+szHuoTcugoapshhdY1SOpubGnzzs+hEbVMbdlQ3onBgr5ivCQFwHEvwLCxONHQ7YqeLNI3FHKrbYE3khCpmsSgTNI2FjsgorKuoRUu4w62NqcieKqukSztBy2txf0GTSW5xqb/sEwVXUDgk36igNdb5GvK1lUiSOlepZiVrd3uijk0+hpIPnI80kEAYAL4i9NzELymhbjADqb3K159Cp8jx6+j1pgASXZk81YYujQsQIWIla3fL0cMBORi5r6lkgpb8BvlPtc6m0nclaysRbm4U19MigoOHWrGu/CBG9E1HWnJsX+uhkO/2WlhYnADodsROQVIJAK/pUcrfxk2bkgqlM+fxz6VIVJrGwpQyYnFpuS/lhRTNyaGLfpXUF6mihKnsk0QcaJ8SaZTWVOeYz8euC2jQkSRO+kz3xnSvJHICwFeEXqd+0t/p3NVackVUaoenxuFjpMeU8iilUAl6Jk3RwbrnTT03vKQdYM6BqPu7US8tkr+qSua8przWF3Hu+rQ6EcXubViY4DjAg0s34z8uOel4D8XCwuI4olsRu5qGFjy72mvqoSoBEGx6FJUdpkLpfMyCnMz5Jks3LXUO0LlZTxiS5dusdVURFBHg7VGCG1StQcrLJs2RKygm86pSKZvbvMl2JXPnH17dhJJ1lWhqCWPutFGiOiURRQ+ZIKTPdG84FpeWY/nmTrXSJQ2rytDUEsbM8XketdSUkuNAY6sYUAFAXCdpnpIyqQsikZJO68zJQc8k/1wy5Sofzpnj+vuIpCmCmR4L6pceUy8UuryJc6eNQl1dHX7Kb6oF/r6mApcWDkAo6p/xSUUtlm/eh8kj+wReGwqF4DgOXN8OCwuLEwLditjd8+LH6EhIBWCOPqVmUU44+EbG/8/JoCkIQlINubmPqmCeKEhWgkq1dd+SDWgJd/hKUSkiYPJLolGnOjMu95nrCjmQfPAWlwbnQOO+geqnLu0JJ69BZIKuISfwSgVS97m5rVOt9AQ2JCdg7rROX7IFy7f5gkQUdAEVCpJ6JgU2KJIaFNlqCprgyp80Hgr+uWjKZfeJghNkifhL92bK6L7G6hZqjaVKKBZ6rNl1EJcWDgAQiXBta+9AfXPbcR6VhYXF8cRhEbv58+fj97//PSorK3HyySfjoYcewjnnnKM9/5lnnsHvfvc7bNmyBZmZmfjqV7+K+++/Hzk5OV3qtzXsIL1HnM+sJ/nXLVi+TSQcfCMLKtMFmAMSdL5FUv41qeICb1syz3IioDPdSZs9j46kvmNSSS9TOhPJsZ9vzgoSwVC+gTrzuc4k3NV7QvulKpBOrTT5oUlj4HOmxJ+uo1Q2TCEo+pqep8gnVnYGlnDCryszJqm29JmQyCT14VRzoS8znCBz8qm7Nzw6WHKVoOtHfR4TcWxxvL7TjhZUAERCXBzC7bF5zoVgfewsLE5EdJnYLVy4ELfffjvmz5+Ps846CwsWLMBFF12E9evXY9CgQb7z33nnHcyZMwd/+MMfMHPmTFRUVODmm2/GjTfeiBdeeKFLfZ81PAfXnDvG9S3jgQC6RK+mSFfdT13ULTXDAV4fKEpOFLmicHPwjc8LTLnB/QAldUqnrJl80TxRifl+nzrJNO3OUzBN6lQ3KUozyHwukUTer5SypmTtbnf9pejYVLKWInESInJjIUB0zSTiKZUNk9wDYlXZ+H2lhF9XMUPXtsm8HuRywAkyT+liUjEBs18s7ZP6PF51arBp8XBxPL/Tjjbi40IIdzg40NiKlz/Zg6vP8I/fRSjil2dhYXFiocvE7sEHH8QNN9yAG2+8EQDw0EMP4ZVXXsEjjzyCefPm+c5/9913UVBQgNtuuw0AMGTIENx000343e9+1+XB0lqxSjnQFWjnEZjSRqZL/wH4I0Tphs0VPuoDpduEAb9aSEkKJSNcAaQmZUAmQoCs7knn6QgUJ7486lRH+CTVUKk6EvE2Re7ydpVZVvXL1S1eqYMS/ntmjPHlaeNKEL9nQWZGwB9VK6XFaWoNY0JBFuZMKvARFv5CQlU/Kbec7r6qz2YX5aN4ZZkntQt/yQkKGOLPAB2D7jmj4M+UpKLTe+YLJmGBE0pJVT6P6PAGAh1NHM/vtKMJB0BcXMQkG+5wUHvImmQtLL6M6BKxa21tRWlpKe666y7P8WnTpmHlypXiNZMmTcI999yDJUuW4KKLLkJVVRUWL16Miy++WNtPS0sLWlo6v8jr6uoAAI+/s91V7KRAAPrTlChXIRaHbk44uE+eiVw1tW7DW5v3Ycrovh5/OTU+ZaqjEa1qQ6MKIDcp6yoZABDJIlefuLlOtxacYEpra/LHU/6COuKti/BVkO4DN51K914R/vuWbPBFCislqL3DwbryWpdcqfGsK6/1mRn5cyOZeflLhK5klvRCQtdfF90suR14+mMBFiZTtW580hg4KVTjUeXc5kwqcK+VXpCklyf6N5SVliSupQqaUNdPH5Hhm/fRwPH+TjuWcJih9bPqSMqYwTlpAIAQQr5zLCwsuj+6ROz279+P9vZ25Obmeo7n5uZiz5494jWTJk3CM888gyuvvBLNzc0Ih8P42te+hj/96U/afubNm4d7773Xd/ydLdVYu3etR+nQqW8Llm/zqS+c3EgRgZJvFd2UTHnDKHLSk7G1qgHrK+vcurBUmWlqCbumOqos6RRAOgbJ54pv6BJB4H5iQcRXp8J4kseGoC0vZiLefDw6EqXUI7quPEUHn4vqt2hQLzz85jbf/W1qCaN05wEPgVNtS2ZG9dz8Yekml8zoUn5I8+TPhSkyWRfdLLkdKOVx5rg88d6pF4CZ472f08+oX6H6e7j1vGEo3XlQJO5qPLScG6CPRpeup39DHpNy9IVEisg+1FjvW8ujgeP9nXY0sbHSvEZl1U0AOondm5uqMHN8f5ycl3lMx2VhYfH5Iu5wLuK1BU31BtevX4/bbrsNP/vZz1BaWop//etf2LFjB26++WZt+3fffTdqa2vdf7t27QIAJCeGXKVDQRG14lVlWLmt2v1sdlE+khPi3M1bQW0Ui0vLPRuMAiUmdy5ai+Wb93mun12ULzr2F68qw4Ll27B1bz0WLN+G6oYW3DNjDAoH9sI9M8b4+kcIOG9UH9x/+XgMz+3pqhSqfbXBAZ0KBh8DQsDyzftw56K1btSm+uyeGWN8iiMdO10HHSgRpVGhtP81u2qRmpzgU2p07dG5TBndF3EhuMSLrr0iBss2VvnGqbsH6hzVTunOg+L9nTOpAEWDszChIEskXxIUmSlZV+nrh6aIUUSJkmCeT5CvAz1GnwU635TEOM+zr5THkrWVLkHi7aUmJWBNea3vc/qZem6rG1rcv4fSnQc9z2NhfqarkKrxzBzfHzPH9XdNvbr7wT9T1xcOzHSJJZ0/v9/q+lnRyM9jheP1nXY0sajU2+brG6qwZtdB9/8Oc6iraWxFa7gDFhYWJxa6pNj17t0b8fHxvjfZqqoq3xuvwrx583DWWWfhRz/6EQBg3LhxSEtLwznnnINf/epX6N+/v++a5ORkJCf7icLY/plISU/3bBLFq8pQsrYSU8b09aUBCcrZxgMhAG9hdsn5XedUr0xJXClTY8hKS0JOenJnAMW4PI/ix81tVBXjqpzJdKiQlZYkmu2kdQCCy0/x40BEKeIVMCT1UF3Lg0B4ahepT8kEzAMzuHlWtcFTbKjjKhqYp5vR+dS5fbDatEHKlBtIw/zH+LUmn0VAfpa5D5opKENKUyOZk3Xmdq6Q5qR7y7nROXP/PV1wjVQejY/h88Dx/k47Fig/cAihENAS7kB7h564dTgO4mw9MQuLEw5dInZJSUkoKirC0qVLcdlll7nHly5diksvvVS8pqmpCQkJ3m7i4+MB+N8gg7Budy3OG9vLqw5Fm0hNjBdTe5gi/ngghDqmIkbPG9XH3WB4FB9PFUJNSdSUxjd8XQAFb4/60+nMp9KGbzK3moJLdBuqdFwiMX9YugklayvR1BrG3KmjfNHC/DqgM7ULJx6UkEg+eIo8U8JEyQcgp9hQx021eCUypMbOk0nrCChfO8kXTxfMI+VeBPwBC8oHTUFKmUKjkLlbgicgg/li8vZ0hE9SaU3+hXTeOh9W/uKk/i6OlSn2eH+nHQs8ubIM10wc7POf4wpkhwNL7CwsTkB0OSr2jjvuwDXXXIPTTjsNEydOxKOPPoqdO3e6Zoi7774bFRUVKC4uBgDMnDkT3/3ud/HII49g+vTpqKysxO23344JEyYgLy+vS32fMSTbtxHMmVTgKlqAf7OlTt6xpO+QUpKITv35/kTBlEip64LSq1AiyRMZq3NUJOTiUm9yWHW9pMSYSAtfQ106Fd6+KaqV1xalvoK6tZDGSdfQRLqWbazSqk20bd3v0nrpFDhAH7lJ29O9WFQ3tAAryzy58nSEuaE5jJqmVlFFliJmFUyJtmcX+XPP6SDdYx3hkwJgdCqhrl1tjsVoNLT6u5g+IgNztaM+MhzP77SjhVAoQtQ+KDvAzKudxI2bl2ec0g8ZPbpVjnoLC4sY0OW/6iuvvBLV1dX4xS9+gcrKSowdOxZLlizB4MGDAQCVlZXYuXOne/61116L+vp6/Pd//zf+/d//Hb169cIFF1yA3/72t10erEp3wjcTnfLEnbzpRkTNcZ4NpTXsU/Ek8y0lfpLqBvgdymlEqpQfTW3WvPSWmh/doItXlmFdRa0vAS5dj1jNWroISj4HybSq5sQJtolg0nvFN3t6LicrdG5K7VQqKSe4pnQbOlVXp1IpSJGbvD1prlLAhy5lyLvbq5EQHyeqyKZo1aBE25JbAr/30j3m4GZv3fkl63Z7FOhYTf2SopeTnnxMo0iP53fakSLEyoNQUieJh/Tsgpw0xMdZxc7C4kTDYb2u3XLLLbjlllvEz5588knfsR/84Af4wQ9+cDhdiTD5LnFiw/2iJIVMd1xKMxFkvpUcxek5QOcGxs1jLjQlnajpVecDqBCLzxsfo86MqEstIpki6VjdtC8tYYzMTfdVd5DGwwkhX2uuLgJ+EsHP4WqXTiGkRFLKxbZ1bz3WVdT6fPyCTLL0/5K/G12zWCNm3b+BqA9mkDKsUxR159PnnyuFlKTGokDr1kVSzbkK+nnheH+nHS5M6UqUrx0ANLe14+l3d2LOxMHu57rgEAsLi+6NbqnDU9JhMgtJTt66jUM6LpmddIXhpTZ1DuXqXGoeowSDl3Si8PhGEVKrSxRMx8E3T11+NPo7V5pM6qg2p1t5LeKipiLVjmk8SoGTkiXTOrKAbBbnCuTyzfvwtw93oW/PFOO4gcgYS9bu9gWsAHKqG1OwgKQs8+TGdMySAk1BA2LcvwEhETbgdw2gZJqnTpEUZQA+n0bVB3/eaT/S34LOL0/yx5PmX93Qgkdf3yKuiUUE722v8R2jCYo7HAeVtYc8n4dgK09YWJyI6JbETnL8BoDilWUeE6bpWgqdjxk3BfKNSCpfZarJyjcwqs7oAhukSgnSPGLxp+OkQ1fLlPtn0XZ0ZnCljvLcaFRtKlm726faUUgmR04yCgdmuuk3eP42PuYpo/uiZN1uhABkpyW56qZHTRSIulSBQgoGkZ4JaT50HtJLCeCvdUvXmpJZbnLfurce68r9KqIuEEO9UOgSJEtj5QFBQc8e//sKUop1/nj0JeXlT+ScchYRvLZhr+f/nLBxky3QWV/WwsLixEK3JHbaTPyCCTOWLPkmHzOq0JhMkZIfETVL0bxdUtoSiTSoPmjNzCACRjdJk5P84lJ9LVNOCHRRm1wR0iVOVtdz9S8oOEKniqrr6HpwdVWpY2t21eK0giyPOkb94TgpU/eDp5GhwSA6pTfWQALppYS2Re+RKYIU0CfMXlzaWbGE969eKKR6yLqx0ueDB9RItXzp35eO9HMVU62/9FzUHDiIt32zt9Dhrc37AESqTfTPTEGvHkm+c6xiZ2FxYqJbEjvJnARANGHyAArAW2tVF+Up/c6VCq7omcqNuWQkShR4BKZEGtS1Kl+ZLis/4CUzUhoNabNVP7l5jJcw032mI2a6FC2cPPB1koIjJJKhM4dTf0ApahWIPY3HPTPG4L4lG7S+a9LLBV97HXGRniWT/xuvvkH7p8+ezneO3yefWZjkSpTUNd2Lj0t4d+lr+aq50rQz/Pnna8t/5qQn46oJg/BTWCi8uakK543qi0176lF7qM2nvoWj+es27WlAydpKPHz1V3xthEJHVlLMlMTZwsLi+KFbEjtqTipeVab1R1Pn8gAKdVzaxKg6wTdfvvlztUT9n/po6fzJuMM9JyW0P5WqhW+asZREk/oS1U7heolk0s90KmHE/09vYl6wfJtYIksX5ED90UymTxUlrJQ8KQWN5A8nqZT83vryqzHzqI5w6u6JhCMhYDpSaepfR8T5ubpjktKsI8tBarfpJQQAXlxTYVy7Lxve3rIf543qiw/LDqCmsdX3eXs0OPZvH+7CgF49AAjm2dCRKXYPLt2MfycuL6+t34sLT5KTOltYWHx+6JbEzhMdqvFVohs6DaCgxE0iJjqyJ/k66RQG7tAu+fDxNCfcTAkE+81JZjhdGg26JkEBJ1w9UmPhZFCnSNEx6Mgn9/OS/Ovc9WT56iSzHjUt6+4nALHihKRS6siQzjxqIpxBLwgK0lp51sFAwCQ1lEayBvmV0ghXADjQ2OozK0sKJVeadeljTIE3QRU8AGBW4YBjlseuW0MjmHVEGVtNY6tL7ACvX10IOAK9Dmhqbff8f9X2akvsLCy+AOhWxO7xd7bjmnPH+AiI5KtkitKUVCCTYhGLrxPAI1blahCA7CgvbeqmPG66sepKUulUpaB10o3ZpMZQ6MinVCJLzZkTEl4dgZv11PXKZF2ydrdLwHVqk+6e0zXjah8328fqaxdLxLJurfj9U88VfxY4yZZy3ulSvlDSpYuENQVXqJ+x+hjS8dI++XNACer0ERmwEOAAZfsbfcrbtn0N0qlehELHrVJG8aoyzJlYcFz6trA40dGtiN17O2rQI61c3NAUJKVIIiFS1QKaZkPaoPhmrvP1U+2rLy+TeUtB2tR1Gz0gEzhTSSo1Xq4q6TbSIL9DSU2UxsOJpDbwJQqa0kM615MXj6h2VPVUBFy6nxIpkVRKTsAAmZBL9yKWYAC+nnxMvF215vwZ5OdJBFmnhkrmf1cRbW1HamK8VhnkqWkksigpuvw54eZcHUE9ViXFTgQsKt3Fqk0AL3/cGUV88FCrNgL2waWb8d+C/92xxmfVTZ97nxYWXxZ0K2I3Ls9LEGgaEMC78VFSBMC3sRavKvP5WunUCgmKtMRFi20rk6IaB49k5UqbKZjBbV8TKav6kJzcuUkxSFmLde58zFyhkgilRCSLV5V5asoGzUc65smLR5zxFYlUaWG6cj+l/qT1ktSnoOtMap50jySiBMhuBrogGgC+yimmRMM80CEov5zJdG4irHysusAhPuZjWVKsuyMSBOHFnrpm9/ddNYfgOH6rbQhAY0v4sPps79ArfWX7G5GWnIA+PT+/BNMWFhad6FbErkdyvGczpeQJ8JM3QFacdP5Q0gaozufKnGqDp9JQ7egiWVV73Ble2jj5hhdE0iRlUdr0uTJlmjsdj5TYFoiY0iRCKQYTsJqypuhOyZRnukcmNVKdy3ML0nsg9cfVYEl9MkX38v9LUaMmAifd41gVQEnxpMqvq84Zcg/y50S6X5LpnF5nCuTQKYfcFJ7Y0ekba+FFXIwmVa7ahUKH72P3m5c3YNmGvbhnxhjEsbJkH1fUIj+rhyV2FhbHCd2K2M0qHOD+TskT3/h06T1MpIhfwzdA7uwvkSiFnPRkN0GytJErM3FTW7sv8awai0SKdMoM7ZebMSWTqqSE0Wuz0pLE9ZMS29K2OaGUAhV4Tdmg6E7dMcCbEmXK6L4+giDNiReX54Euuqhdaa46Xzm6/vz5MJFV/hzr3AyCFEDTfaag/opS7kGJxErJkrmbAPdf5P59nPQq5RAo81RToe1cdWof3/gt4PqUnjfKvD7hjg4xabGOD+6qacLA7FRtex0OUFbddETBFxYWFscG3YrYPfv+TqSk1rjpP3h1iVhVEcm0qTMRKozLz/SkTOEkSqoOoTOnKjNxalK8JxiDR99KiqKkbtBrdeY5iiBFRjKr8oAHXQUK3odEgEwBIEFKJJ8vJRrctChFW/Li8jzQRfWjI7Em9Unqj9cz1kUS02fJhCB/Pn4PTGl0KKmUSpNJ99AUQCS9TEgmW35v3DGwEoGe9bWKnRFBgt3H5bWoPdSGF1fvRm5GCkbm9hQVu1c+3YOpY3KxtarBSOy8fTuoOxQx6b69ZV/MZG9PbTP6ZabEePaxR21TGxACMnskHu+hWFgcEboVsXv5kz1ISElDarK+AgP3/1KgwRQi6dGYCNXmJKlPOrMw9wfj1+nUvqDNM1Z1g2+KupQmUt1S7qenI3A6h3g1D6rMmIikZL6j7XEVKpa1ktRA/kxIc6Jz5VG7Up49nd8Z7YeTFT5Gfo/5fQwi7CZyqfOjk1wBgEjKE3qPKPgzu3VvPe5ctBb3zBjjKqe6Embq3nPTueQigJVlLhG1iAHR76uOAGbXHv38k4paLPxgF/7jkpOilSc6r/uvZVtQd6gNF47JNfrQebp3HHQghDXlBwEAb27ah/EDe6GxJZIKZf3uOvRIiseQ3mm+a//n7e34j0tOCuxjb10zeiTFIyPl2BKu0p01SE6Ix1nDex/TfiwsjjW6FbG7aGw/pKSmazdD7i+lC6aQNlXJRKjMcffMGOOeL5FCbhY2KRfqOomY8lQaJl84o7qBYL8uXVt8Aw+6ls8NgK/OaizRkaYIVN2a03EqmEzEfD24j6NEmrgCJ6UR4S8UNFIUgC8dj5TXkLZB/d6CiJyJXNLzJdOvzgytuw+0n/uWbMCaXQdx35INeOK6CWLgDh+fMtnqXA04EaX9W1OsjNZoJuK3t+w3ntfhwOeHp3zu/uet7fjuuUMjFSyinyki2NzWjoS4EBLi47TtxsGB4zj4uLwWp+RnAgC+/dh7KPvNxdhZ04Ss1ESR2IUQScsyrE86AH0li1XbqjGkdxrGD+xlnKOFhUUE3YrY3XrBCLTFJWsjSulGBeiDKbhjNvfHUucpc9yyjVWB6hM1C3MljF5nMtupsSpIvkpKCZPy93GY/OwAlh9NY1Y1KX86k+S726s9dVbVWOhmHksAAD/Gx6BT9nQpVfh6cGIjqXpSShxfZQxCECUza1dILPV7o/eXEzlO+nX32mT61Zmh6U+d6V+VXKMvPeonNflKLgq64CWpf/d3a4oVEWv1iI4OffEwGkFLzweAl9ZV4qT+GTgprzOPYHNbZ2Li37+yET+aPhoOgPfLalxi1wnHF1wBRMackBDC8k37XGL3ztb9SIyPw5lDc4xz2by3HiOZX+fhINze4SGsah3X765D/8wUZKUl4ZOKWuSkJ6F/Zg9NK18s2DJvFgAgv4Z9QVFDFIziVWVYsHybu+HcNHkY5kwscPOXmVKFAJ2b9uLScneTrG5ocX8HgPsvH4/JI/uIbZSs2+1ezzG7KD9ifnXgnkPJJFVi1IYvmV7pcXo+0Llh8+hXOh51TBFTnVkzVkh9qLGoMap1O2+Ud93UZp6anOCeX5if6SENaox8brT94lVl7hh091CprXcuWusx6RWvLMPCD3ahZO1u3/Oi7jntV7ovKs+eGtOkYTlACJ514dfxcVKCq85VY6huaPFcz5VGNR9+L6R7TddE94xx0P4Wl5YDoUi1DnrPqxtasGxjFe6/fLyv4gl3LShZV4mStZWe66eM7ou4EFA0qJdnTlL/nLRbdGIVeTkIQofjoLK2Gc3hdpfA6IInHMdxFTsJv39lk/v7M+/tjNSbjZ7e1t7hUQY7omlWlm3Y62snPhTCJxW17v9bwx1Yut5/HsfCD3YZP3/u/Z3YVx/8IvCblzeKx9eWH8T+6DO5bV8DquqO/KVCilpeu+tgpNzlUcT9r24KPsnihEe3UuxeXFOBa86NKARNLWGjyY8HH0gKkVIjileVYc2uzi8YyUyn4Pp25Xf6dpnKclHVRacA6cxyFJKSAZhVOUldVOOgv0uRjqrtOxetRUs0+alJvdMFC+jGb/IX5HOjxJauO22br60Y/KBeZKM/fb6Gmnsu3Tufesr80+g5dO6SWtVVlU9SF6Xnw2Ra9tyzqBsBHLiBSabnXKWK4WshPbNS5Lpyi3j4zW3agAqdim3Ridc27I251qvymfusugnN4ajiFgIcONha1YD2Dgf/91E5Lo/eJ3X+waZWPLJ8G/501aliu02t7dh9sBlKD3xhdQVSEuPdzx0nkmdv5bZq9OmZjHH5vbCdVMVwxwJ9bjy91hipTzu0TxqyUpOQlZYEANhS1YDNexvws5kR/71XP92DaSf3E9r1oqEljJTEeF++vyOJ/G3vcBAfF/LV1QWA5z7YhdsvHOFadXRY+MFOXHn6oJj6a27rQENLGOnJ3WprtzjK6FZ3/1DUIVdtAusqaj0mvyCSw3N2uZUKBLIgRQl6kuBO6jQtLVi+zUcyJXBzVZBPk84vL2gD5KZIXR/q98KBmT71DOisvxofihBp2odERAB9sIBpPfg1EoFQwS8zx+f5UtFI/on3Xz4excQRPyc9GXMmFvhyDnrGwe65LviCr7npXnKiK5FtKeDHROSkFCdBkcmmNptawyhZGw3+iQYmSaZVNT/696IjvOoFZ+60UcZSY7qACt2LjEUnnlxZFvO5f1+72/1dmVkjwRMRn9jf/WsjDja1AYgQGRWM8at/bsBEZhp9YsUOXHfWEPf///P2dvfvr77Zq0B1OA7uf2UTEhPicNn8ldj26xn4/l9XY31lHW6ePMxTMaPDcbB210Gs3XXQ50/39LufYVx+ps/MuGLbfqzYth9xoRD+45KTcKCxFRUHDmFAVqfp9L0dNZh2cj+8sakK54/q65pgG1n+xg/LDuCrY/t5iFzoCMuurdi6P5pWqd332bPv78QPp4wIbGPz3ga0tXeg4sAhFAi+ihwPvrrZJbXHAs++vxNXTYiNaJ4oWLF1f7cKqulWxG7d7lqXxPH0G4A+b5faWOAAa8pr3WoF0ualrpX8j3S+QUohqm8O485Faz1JjCUCwCNAVRu0PfVT8nEK2gC74r+mflfX0OhJuvGv2VXrq83K2wGAmePzPEEoCsUry1CyrhJNLWHXHzFI2eQEQiqvxudK15ZHhOoiYD3jIPecRlJzn0JdOS6+JjqiW7Jut0ta+diktroakSy9XOjadE2hLJ0PJ2rS34sUbR4UlELnQnMm0pcvvl4WfsQauQoAa3YedH9/7oNd+M03xiEUCrlkLj7qB6eIUwepUEZVNQDg3VbVtXiUw0ff2g4gUoHiUGs7Ptld6yF86yvrAETMky2E2IU7HNQ1t+FAU6t77Fcvrcfwvun4rLoJv39lE3781dHGeW7d14DVuw54iJ3C25v34/xRffHbf23EPRefhC1VDVixrRpfG5+HtzbvQ7vjYGdNkyfCOCpkHzbaO5xo4Ir8OVUjN+6pw+h+ck3k+uYwStbuxg8YEaxrbvNECx/r0r9vbKrC1iqhDnH0XlK19kiglM4jxbINezFlTO4Rt/P6xiojsTta4z1a6FY+dmcMyfZsmnSD+MPSTdjf0OKrS7pg+TbXLwsheJQ5yS+Itq02NuV7J1ZSQGeOt54pCa75D5B9tIBOMlK8skwbwKF8vlKTE3w+TrRdPgdpnNwHTvJlm12Uj8KBma6iSddH+aIptUjyRwv052NmUAVdMulJw3IwZ1KBz59NUtt0/mz0M+pvxs/TgZelo/db3Rfu68nXec6kAnF8cKAdG18T/jmdF50Hn5PyKSyOKjv0ftM2c9KTMXfqKMydNkp0O6B+nfRvgq+RGpfJ59B0H1TgyJryWhSvLPP531l0oqvrIpHAEDpJ1oEowQMiKVFqGjvJ1eqdB+E4Dprb2rEhej7Faxv2ij55r2+swrKNXp85qn45AFraOtyxtXc4iAuFPMTqL+/swP99FHmOWlg93M55hPDYOzuwdtdBXP7nVYHk5uVP9uAPSzdj9c4D7rHlm/eho8PB39dUoO5QGK3tHejocDzBKYtLy1FV7w80+cvb2z3/f434CYY7HHc+n+6uRelnBzznUsWy4sAhbbuRoAj/XP742hYAkZyAtYci97CrsRO1h9o85nGKXTVN+D/yHfmOEH1de6gN9S1hrCuv9X12uGrnW5v3HdZ1HNSCcizxm5c3uL87jtOll65jgW5F7HRYXFqOkrWVWLahynXOV8fpJjpnYoGPdGzdW4/rnngfW/dGioxzJ3y6aVLnf36uInc02IJuhFv31vsc2fkGSOdjCqyQNlhKYvk4eZt8c1Vtqk3VRHYWl5Zj+WZ/YII0TtrPnIkFuPL0gZg5Ls9IsCSip8bHCawimHQtdKTXFMAgrRGfk45c0QAZ2oYiJoCXAKvAgZnj89xxF68sE9vQ/Z8TcjVG3z3QkGkgkpB74Qe7ULyqzHM8KODCtEZSEBNfA9P1nnXV/G1YRPAPYlqNBVLkKyUAz76/M3IMEaf+qvpmz6b8wKub8cqne/DGpipI+GBHje9YfFwIr3y61yN53ffPzg2wo8PBlqp6NxiivSMS0bn7oHesH5QdcD+XgiI+q24E0BmtS7fU/1q2xSUJSh0rP3AIe2qbXeXxmfc+w6e7axGOEsviVWX4zcsb8btXNiEU1ew+KKvBwaZWd8MuP9Dk9lFZ2zneTXvq8X8flWNblCi1R4ldKATUNLai9lCrZ11pAEdbu5cMVNY2o+LgIWyorIsEoWgYW1NrGO/tqMbWqgb3nvJ1WvjBTvFaIJIn8H3h/gHAg0s3i88OxV/e3o6DjW1iLsXnP6rQkkYTKInfVdOE5z8q90Rjxwo6pINECVY4Gi+OO6ub0E7eOX69ZIOHDEs4nDXpCroVsXtvR434Jj+7KB8zx/fHzHH9fSZGrvzwDZrm4wL0pGp2kTeKk56rVJsDjf4HR51z35INHmVC2gAlRaarUZFUCaLgKk8QOdMR3NlF+UhOiHN9GxUkssnVmJsmD8OyjVW+jZ0qhUFKmktgV8rRsdI4pPlL5FenCkrrreYzc3we4qI1gWkbiphQRQ/wKlzuPWNKMr8PNMKbP78m1VmR6TkTC/xkniXkVqAqn6TwTRndNzC6VnevgU5iq9ZLN/6Z4/I8fxs1Vrk76pB4Ql1zGMs2VqGt3fGYXJ//qByvE+WaR7lScqOg0pzUt3SaYf/yzg7397e27ENjSzvCUbtvxJwF/MffP3H9ABXeL6tBXXMbFn6wEy+t243yA014IzqejXsiL+XXPP4+AO9mXtPYii1R02GIvOFQhXH7vka8u70mSiwjc3GcSDqUTXvqcP8rm/Hqp3sQJmM6+7dvAIhs6o4TIakPv7EVb26qwobKOnz02YEoIetUb37/yias3nkQVyxY5bbjOMBDr20GAHcddtU0udfsqW3Gjv2NcBAhnWX7Gz3r8uFnB/DAq5uxv6EVcx57z13HP0dfqB5+YyuAiJ/eP9buFqOOlSL63na/upUQF0JbeweWbdjrUXE7x+/gT69H+uD3DIjkWaw4eAgvrq7wfabwyqd7fMdK1u3G36KE/8mVZXj63c9EP0WOJR9Xaj/747ItvmPz39yGjXs6VeiPoiru7EdWAgAaybOrw/+yl+MNlfWB1zz17meB5xwJuhWxO2NItudNnqo21JSkU3MA/wZ9z4wxKBzYy83HRTceuulQ8xtXG5RqQ8mbgjrnnhljfMSQb4CKBADwbXaxKh06EstVHk7OdFGunOAqZZKmM5HIljRG6RhXCvnnOtMdJUMmc6yCTuXSrRFvRzeuknW7PeZaTtq5oicpbFRJlu7DmvJapCYliIoXhUnZ45/NmRQlfZMKvI0wlY/fW55O5c5Fa/Hmpn2+8XBCqrBsYxWa2zpw35IN4tsyN+mrv40X1+g3hi8L5r8Z2UD/9cmeI67RqlPe1lfW4cOyA9jf0IKy6k4Ssbu2GX9fs9vdvMuqmzzX/VPYUJ8J2Lw2721Aa3sHqhtaUd/chprGVsSFIilYdtcewhMrdnjOX7PrIABgb10Lyg8ccjdUlTKklZlqH31rm+v3VPpZDZ4jqhUlE3ujilS4w8GKrRFy887W/fho5wEsKi1HU1s73ty0D63hDg85BIBNUUvP716JuALFhUKIiwvhode24Bcl6/FxRS06nEhJt101TdhT24y9dS0uKXXgoL45jMaWsEvmzvndG5j0m2XRHiLHlm2oQigUIQTv76jBt/8SIXFro2sSAtAYJT40qOb1jVXuPVu76yD+9ckeFNz1T4TbO1B+oAkflNVgQ2U9nlxZhlejpK+msRV765pxoLEV4Q4H72zZj8+qm9x1pj526hoH3hcBNb8QIpG69c1taGgJ4/mPyj2k5lBrO97avM8logr1zWH87cPOtDYdjt+dgKten1TUelLxAJGXl9LPDuDvayrwGXlmaduLPuz87vpntILUh1GT+WXzV2DlVq/5+U+EIL6+ca+P/HUQs/l3iz90jx9JEE5X0a2CJ64/eyja4pJdB3fqlE0dvelxwJ+omDq+D8/tiSeum+CeSxUVXtycX8ud/3mUH0VWWpJY3km1C/grQFCneJPfHFf2gM5UJQ3NYV+0biyBJ7OL9I7svC91LS3vJZlUadQy/YySU6ltVQHk/svH+85V0AUeBEWQmlKdBI1LBXhQxZH2MbsoH8WrykS/TGkddfeBj0U3t1g/o+Pja8Mjh6V7S8fKq014Ipo19Y55Kho6Vj4H9dzPGpuNub4V/HJhf31EMXlvR/URO8m/s2U/ThnAkwlHEBeK+NVNeWC577N3t8smOwlKSQvCH5dtwdtb9uEjEuDxq5c2YPNe7/W7aprwVtTH65OKWry5aR+G9k7HIWaiq4v6mu2ta4HyZ1/y8R6P4qOCOV5bvxcvRTdzrjgpnzUgkkIl3OFg1fb92BvNa/ffr2/BkN7pONQWhtpKQyEgMS4O2w82ouLgIVTWHsKU0X2xuaoeB5vasCj6AvTWlqh5ONrl71/ZhFMGZLqb/14SkFJZ24x3tu7H+PxMbNpTj1XbqrG+ss4lWk2t7VrH/dLPDuDXSzZEyAZCaIkGwjS1tWNDZT3u+r91qI4qcWcOzcHCD3ZiUHYa/vDaZnzrjEHYtq8B68prcfG4/u54lm/eh9pDbcjskYi3o/PocCLpYlZs3Y9R/Xri7S37cX5UlVcm9iXrKvHj/1uHnikJuObMwQAi0aYf7TzoCbp4Z8t+tIU7PC8vHU7EpP3yx5W46JT+2LSnHs99sBO3XTACbe0d6NMzGc9/VIEdTNHscBxXEf0oStZ27G/Epj31aG5rxwurK3DZqQM81/z1vc4XgM17G7BsYyRgpGx/Iwp6p2HT3nqUH2hCflYqNlTWY09dM4b2TseO/Y0Y0jsN7R0OqqKm8KXr9+K/lm3BbVNGiClvjhW6FbHjoJsAJ3n0J+BNL6EjWOo8FeXHoVQ7fi3doGnZpMWl3hxxfFw8LQmNDuXkVIrG1RFbpdA0t3WgpqkVCfFx7iYay1q6UcTwRhHzMasx8FQjgFzGTI2XF4SXCA4dFycCXYmW5ERJN28pvQ0lP7xGrPTspbI1Xlxajg/KDiA5Ic5zTErtEkTO1JqqZwWIBAyVrK1EU2sYc6eO0kbO6tY4aCx0fej91hFy2qaUQkitaSwvFfRvZ9KwHGQLpmaLI4PosuWYssZFlKxjgc17verLhj11HoUFiJAH5QumVJYOx3HrEyu0RU2aFQcOYXBOKoBOsrerxtvmu8T8yFXHbfsa0T8zxSVb/1hTgbLqJpwcrcKxtaoBz76/CxUHD2FcfiZ6piRgxdb9nrm0Ow5m/3kVTKg7FCF8d04b6VGl2js6oKTzf66rxLaqBg9ZfuDVCGF59v2d+E+W3qSmsRUFd/0TANDYGsaz7+9CVmqiG9kZbo+Ugasm5lXHcfDEijJcM3EwdlY3IRTq1CcjSmOnuf2eFz7GA1eMx4urd0fH6qCpNYytVfW46alSOI6Dey4eEw0+iZiRn3kvotTVN4dx9/MfIz+rBwb06oENlXVuPXUAWLZxL9qiTmv/VvwhQqGIGvtfy7Zg14FDGNY33VXcfvuvjVjycSUuHpfn+okCERP02cN744kVZe6x1KR4rN9dh4ff2Ip+mSn447ItqGlsdc3l8XERtViK+v2suhEvf7IH10wcjK1VDTj7t2+g7DcXA4jURwaAp1Z9hp/NPAntHZF1PHVQLwCdLwjqxUK9QCz6cBemj5Rfro4Uh0Xs5s+fj9///veorKzEySefjIceegjnnHOO9vyWlhb84he/wNNPP409e/YgPz8f99xzD66//vou9803ASn9BlXSJBXPRLC4YkdVpmUbq8QcedKGqNJ7TBnT12PGpASJJv/lmy8lmFlpSYHpNXRKj6Qiqr5pwXaJFEibs0kNpe1LwQm6MfE15uoaJwKmdedjpH1KyZ89qmuSvw8dGaWQXiTU/3l5Na76qvZpvjuJnIlrrfGTk8YURMjVMV3Sbz4eHVnk95iCv8ioY9xkK6qEx7ik2PH8TosVXY12TE9OQEMMPkIUja3taGptR3ZwurSjCj5OTuoArylOmUBfEHy3HCeSOmTF1mrcdO5QAHCVsk93eyM3g4IXK2ubkR1NfKzMz2rjX19Z51ao2FvXjLhQDx9B7ZADeVHd0Or2r8a24K3tuPGcoe45tYfa8KfXO81+XAH9mFTtUEEYygePrsuz70dI0IGmNjcAI9ze4foeKrQ7DjbuqceC5duxp645EkgTFSUWvLUdC97ajhvOjuQvfPmTPTjQ1Orxj9y+rxF/Xr7N9UUc87N/4Yazh+CRN7dh3tdP8fg1UhIGRII93t6yLyJGNLaiLZprUJl6e6YkYHBOKioPHsL2fQ14ad1uHGptR11UeX1/R+f35Kpt1fj9K5vEaifXPhHxwzxzaA72RP1Cn1hRhsT4OPRIjMfjK3bgq9Fk1or0Pxb1C/3nx7uxvrLOVS7f2bIfJdEgJqUeb9lb75pxX1sf+f7bffAQXv640n32rvqfd5GaFFEovzDEbuHChbj99tsxf/58nHXWWViwYAEuuugirF+/HoMGyUkLr7jiCuzduxePPfYYhg8fjqqqKoTDXfvCASIlxXSbqIQgFS+W82LZ2KUcbepVJzUpXsyp19QaRnObv2i6AiWYN00e5lEKqTrnya3GEjBzFZHOVyrYTgmWapOSIJ3fFCdNKjiBK4y6MQWtsc5s6JIiZkaVSL6kIHKyQ8HXIpZkuvza2UX5PlJKVV+gDABQmJ/p+uJRgic9s/T3OZMKxJyB1Q2dNVr5GitIhFwiohQSWeS1YOl6UxM69fOj/SofQvqsSEpg3VEo66TD8fxOOxxs2etXFCQE+fRIUZaSWvFFBjWXUihfuX8xx/zf/svrg6WImQmf7vameFEv447T+fu++hbXREtRcfCQ7xhAo5o771F9cxij/+Nf7v9fXGOOfK4jc1cKF3+Z4lD3d+EHu/C3Um9ptqffjZCtnVFVc8FbXr83ig4n4o+YEDUBP/3uZ3hhdYUnwKQ13IFH3oy08V/LtiArNUnb3kc7D6Bk3W6cNay3qwp/Jap4AZG1ae9wcKCpDTc//ZHv+m37Ok2wV/3Pu9E2D3rOaWptR2J8HGoPtWFPXTPWVXR+vr+hBc9/FCHD6pn5n7e8aWziQiGUrN2NlMSIBeaF1RUesv34ih2uSgcA6ysjRO7lT/ag/MAhl4i/F1WdL05KQLhdw/yPEF0mdg8++CBuuOEG3HjjjQCAhx56CK+88goeeeQRzJs3z3f+v/71Lyxfvhzbt29HdnY2AKCgoOCwBvvimgrcPqOPuDFLm4aOzIn+ZFEVhV5PrzX5z0lpJXRVDqipSgUgcB80aVM3mZ3VNbR4vM60JrWpSJm0hnyN+SYskSaJZCqYzH1TRvdFybrd4nUSedaZUXVKEh+TieyYzNym+8GvlUzH7riJqXF2UT5So+ZH3bXSOCQsLo3UaAWA1CR/JYkDja2iu4GkjnLyxk3NvB86Vm5C52ql5Pt3PHA8v9MOB0crVYJJAPwc/byPKXgkJ/fBOhJ4fcAOs40jWGdKKmLtX/nYPbB0M/KFJM4Un1T4cxYq9UqNWxG5oCjPytpmMXJaoTyaw4+a+vmU2tqdmIi4CepF4IOyGs/aK1JHwUmyytOnLF0qmpjiPaIcUn9URepKSJqicEcHCn+xtKtTiAldInatra0oLS3FXXfd5Tk+bdo0rFy5UrzmH//4B0477TT87ne/w1NPPYW0tDR87Wtfwy9/+Uv06GF+sDhmFQ6I2bwKmLP105863zn1mbSh0nHMHJeHdeW1mDkuT+ybni+pYVTF+6DsgKtySORK598lzYub+Sg51a0L33ipeU5FDksmVN96MpKpIJFHula66yTyLJlRTUEbpsojCkFEWvVHFTFu7p0yuq9nHdW8+fpTn0oeiCOZUIMIJJ0Dr9FK13hxqVzFg5+nzjWRN95PzGqlU+aqjbH4/j31jvft+WjheH+ndRXtHQ7aYtzFdXnPOj/Xf6ZTmrobeImzowmay+5wEaSwHW1sJ8pW+YHudY+XH6WkxcCxe3F5+t2dSE2KR1NrOwb06uH7O/rBs6vd31/51G8qPlroErHbv38/2tvbkZvrLdGRm5uLPXv8uWgAYPv27XjnnXeQkpKCF154Afv378ctt9yCmpoaPP744+I1LS0taGnpZOZ1dZE3h+z0ZDyrITJ0Y1SbK3d216lyqg2dyiRtNNRHDYBvo5TSVujqyVIVj6Yh4UEHqn/u1E/Xgs8J6Iy2paZO6XqJ4FLznDILq/lxPz0FyWSrI4G6MXOSRhVQvrYmPzDP+rLITu7zSMevI9KqPU52uHJJ1xGANmhkdlG+z5ypI8I6FZeawtU1tJZxrGsspVsJIm9zWZSXyURNj1GVlb84Sev9niaB6pHieH+ndRWfVNSKSXolZPZI7LKP3ZFgZG66z8fsRAYP2rA4uljNTKlfZKQlxbvpZlSQxPF8OTqs4An+JhgpdyK//nV0dCAUCuGZZ55BZmbEUfDBBx/E7Nmz8fDDD4tvuPPmzcO9997rO/74O9txSVGnmZWTOapqSJuoKRpWpzJJgQA6HzX6u2Tu1fkvcTPZfUs2eMxkOiWNExhTDVGejkVnapTUTCl4QbcG6jNusg0y85pSkahrTORNWkvpmI7s6Myys4siKUuoXUAiO4A/4IX2HXlpaEdqcrxvHSlJpISbB+voUtwEBVlIgRPqer6W0kuEibyZ1t+kzlKVNRaz96HGejwn3rmjg+P1ndZVxCI0SEoBx2Pv7MDDV3/liMdDkRAXW1rUnskJnqTFRxO0BJjF54N+GSmB1SlOdPQgxO6LgC4Ru969eyM+Pt73JltVVeV741Xo378/BgwY4H4BAsCYMWPgOA7Ky8sxYsQI3zV333037rjjDvf/dXV1GDhwIN7bUYMeaT2NphuqYnCfuCB/HinViRQIIBGFIMWKEiRJYaHKHlf/ctKTgRBQsjZCAOZOHSWqLtTRn0fc8qAF0wYsEQLTBi7lqePrLK29jiAEqXtSW9UNLS4B42qVySyunhEdIVxcWu6ue2pygofscGLKA15on6lJkeTWhQMzjYpYUCBJrL6kunUG/HkdpTZ4QIwp15xkZlaf61Rwek+CyOCxxPH+TjsWGNY3Hb17JmNfwGbb1SjbIIzITXdrz5oglZ46WohUSvj8mV1i/PHptyuYdlKuG2V6NDF2QMaXnth90V4mukTskpKSUFRUhKVLl+Kyyy5zjy9duhSXXnqpeM1ZZ52FRYsWoaGhAenp6QCAzZs3Iy4uDvn5MsFKTk5GcrJfWTljSLbWvCMl05XMoiZzrZScWLfRcaWQkhtlojxvVB9xMzMpLFryyVJbmJStBcu3eSJudYpN0AbMo04l8zYnpV3ZlHVrG6Tg6PrmBIzDkzx3V62PPNE2+drAMQfhqPMK8zNF4q5IqpSEmhJR04sJ/Zwe58SVE3MT0ZaeZSkgRkf+1XkSEZVU8FhMv/yZOJam2OP9nXYs4DiOMTBC4SjzuphxLOujR1TWz3+XTUmIR1v752f2HtonzeMvFwtU2pajjb9853Q3Z97RRHpyAgoH9jpmuRO7gq9/ZYAYYKGgi84+XuiyKfaOO+7ANddcg9NOOw0TJ07Eo48+ip07d+Lmm28GEHkzraioQHFxMQDg6quvxi9/+Utcd911uPfee7F//3786Ec/wvXXX99lR+Przx6KDCF4weSsD/hVDp0qYto0Tb5b6phb7aEljHQhDYWCSWFx/a6Y+iSlttBt3FxNCzLV6daPmhGl9dIRG2mMikzxfnVRtapNaY2l9iQCxiM6qS+jqkOqS2FC+1K+b6Z1p8quKoMlrbcuCTV/ZrPSkkRyykmtGreknNLk2JIvIYXkOqDmBvjV7KB0MOocXueW+2VKpl/+TBxrU+zx/E47GuDmx1gVsSNR7FIS49z7OOOUfljy8Z6YCRuvFHGkSIgLudGZOWlJqKxt9oxPQtphms5yM5LFtCZfGZx1RM79dA6xYEz/DB+xO3VQL6Nf2tFUlS4e198tv6Vwcl6GLzXM4SApPg4lPzgbv39lE751xiDkZqSIEagKRYOzUBrNHSfh2kkFnjJrANA7PblLEbbxAX8ssdy7rvZ5JOgysbvyyitRXV2NX/ziF6isrMTYsWOxZMkSDB4cKRFSWVmJnTs7kw+mp6dj6dKl+MEPfoDTTjsNOTk5uOKKK/CrX/2qy4N9/J3tuObcMaI6xDeiWFKH6FSRA42top8P/SkdU35n6ckJngAJnelPZ+bUmf+4EqM2bqWoKfBzOeFS/npb99b7TJE6ZTI1yV8yjRMwU3UMXSUC1SclDToznam9nPRkzJ3q9wXj/muqLTVGGhWq6wswk0o+B+Vfp9K3jMxN9+UX1OUE1KmV6jNOCAE/UdcFi0hzonOXyuUpcDVbakfKl0h9LRcs3+bzy9T93XLfwuvPHnrMSoodz++0rkC3MceFQmh3HEwcmoNV26vR0QFMHtnHUw9TxuEzu8S4ODQjQpxUEt6umljPHt67y2rMlacNxKeVtW4qjuy0JHxv8jDct2QDTuqf4QbHRfz99MQuaKRxIVlZ1G3w007OdYmd7loTvjOpwE0lEgvaBbNvD1KWi2LsgAx8UlGHUAj4xaUn48kVZdh+hGlfeI7EUAhIi+5BZw3PcfMIclJ1zoje2FBZh/0Nrfjm6QPx3Af+Z7RXaiLi44CkhBDi40K44rR8/N9H5bjh7CFo73B8JO2ui0bjckN1D1pu7Y/fLMQPn1uD/Q0tSEqI89UXVhjWJ82TGy8uet8LclJ9dZLPGdEba3YedP1G50wcjHe27vcRb1WB6P9dPAa/+ucGDOmdhkmD+uDXD2mHftiIzduV4ZZbbkFZWRlaWlpQWlqKc8891/3sySefxJtvvuk5f/To0Vi6dCmampqwa9cuPPDAA4f1ZvvejhosLpULzFMlg2b0X1xa7m5S3HFeqSLc9Hjfkg3utQq0/a1767EgWrSYmqSmjO6LySP7uKROmbeKV5X52qXjA7zF7mcX5WPm+P6YOa6/Z8NTn7ubagiRUiwhaNtShCs1OcGNIE1Njvh70fGoNVJqk1pHOs/huT0960XXdcrovogLwZcbTd2nmePzoAMlDRy0D0pS50wq8Ky9pETNLsrHzHH9MXN8fw9RpfeGXsfN21NG9/U8Y+66O/DUxF2wfBtK1u5250DXcs2uWmytasCa8lrP86RIDxy4a03XixI4/rzQc/jfAW1D5Z2jz736TBF41S99Lug4qdsC7Ufql56vnmN+Df37UP1Kf7fKT1Hdq8ePUboTheP1nXY0wKlGdloSzh3Zx/3/OSN6y9d1gdcNzPbOLZGUyVMVBVTG/ljRPzPFd0x9T/ROT0KfnsmYfrLXz3He10/B8D7p7v+H9E7D1woj1/RMSUBSdFwTSYkqAG4ZMAXKS3itUAC4c3rkJfE7Ewe7x/KzeiBOU5OV1pkd3jfdHccfv1noHh/QqwcuPqU/vv4Vf38K4/P9lQge+85p7u+XRudKqzi8dkfkWf3lrLGe62ac0g/fPH0gzhiSgxvOHoLpJ/dDv4wUsa7smUMj+RjPGt65bunJCeIz0jM5wfeSce2kAvTtGfmb/t3s8dhy30UAgHsuHuM575QBmbjitIhvaUaPRM9n6nvim6cPxPC+PZEUH4eEuBBG98/AuSP7uH2qsZ4zojdOGZDpe45um9Lp4/o1su/8aPoojOrX+fJ59vDe+M+ZJ7nr2y+js525U0fi/743yf2/igt68MpC99j1Z0WqcIzM7YkrTh/oJlROjI/Dn646FSmJcUhLisePos9SbkYyxg/sheui1915DOvGdqtasTofOwUpiEJtvrH4glHViibKVW0rhcxkkpQc3XWmP9rn4lJvsXtJfeJmT2p2pOWwXN+46DlcFVK/Fw3qhYff3OYxr1EVKRb1SG3QlJxlpSV5PpfMrZKianLYV/eNq4ImfzxdkAPQmfB4f30LevdM9nwmKXWK3Kh+1Llu+TWijsVipuRmblo9IygogptjpcAQOkYKk2uB1J/u2eaKnu78WHwtdX+39PNj5WN3IoBvvv3YRjdnYgE+KKtBc1sH4uNCbmmuruh1Xz81H39cFilvdc2Zg/Hq+s5gE0VqZo7Pw1PvfobMHolYGuCkf+VpAzHt5Fy3nJZCn+gzm56cgCljclE4sJcn31dcXMhVT7595iB8UlGH3IwUJCfEISUxHonxkR142km5xjHQiriJ8f6VmDomF7/71yYPkZtQkI3SnX6T3z0zxrj7wVdP7ocBWT2Q2eMgPig7gKkndRLTH391FFZs3Y/CgVl4/qMKnDuyD7ZVNbgRzKcNzsIp+ZlYW16LnLQkt45rYnwcrjxtIBZ+uAvpyQlIS4pHL0KKhhGiC0SI/fmj+mJAVg/cev4w7K1tweLSXTh/dF/UN7d5iJ0yLd80eRje3V6DMf0ykJWahJfWVWLaybk4a1hv/PuitZ72n7x+AlKT4vHyJ53PwNi8TKyvrMPofj2RltR5H9RPhRvPGeoqyd86YxAejVZ3CIWAwdmpyMtMwdypIwFETJfxcSHAiaxN7aE25KQm4bqzhuDkvAgBzkpNRH5WpB7w+aP6YEjvdNwxdSReWrsb2/c34rKvDMDqzw6gICcVt54/HEDkuZldNBCPvLkVpwzIxGkFEaL41bH98HFFrWvWDYWAv900EUs+rnQDEU8Z0Em877poNB5fsQMFvdPQq0ciPtp5AC/cMgkvravEsD7pyE5NwhlDczBn4mCUrN2NUwdlAYgouheP64+Lx/XHyo1Bqvrh4bAUu+OF688e6tt8qbpAVSOqzvBzTaqFUqZSkxJclYUrZPfMGONRIoLUKqUuUcWLq4izi/KRkhjnZuoH9OqH8olT45PamjQspzMhb1KEv6u21PmlOw96lDKuIlGVRq1B8coy3LloLd7ctM+z9jqlSfqc3z+dWsj7MalTun51z4ra1TbsqYt5rDRrOH/mZo7L8z1vSnVS9126B3MmFvhUV6qUqnkB8NxjaU7SmvHnSJojV2aposmVOqk99f+te+vF/IVcaebPN+2DP8vqZWPcAL+SYRGBS9QYP3Ec4MIxfTGhIBvfmxzZ1DSCUyAKB/Zyf8/okeBJbULJT4/EeFw4xvs9CETMTzedOxRDeqe5Yz19SDb+PbqJu21Fmzp/dF84TqfJtG/PZFwQ/X5VaWjOHdEHZw6NKEzfPnMw8nqluMXkzxgS+XnqoF5ISYxz1R6lCKry9krB4oqeWssQob9XnzEIlxYO8HzP33JexA1oSO80TBqWg0e+HUkhkxtVf9R3LwBcWjgAPVMSXTVxOCNk4/J7AYiolVQQS4gPITdK1h0A155V4FG7QqEQbjh7CBwnoqwWDc7Cv0Vr5CYnxGNQTqpLlnqmJLrE7meXnIRrJw3BDWcPwVcGRkjHj786GpcWRhTF80f1xZj+3nUBIj5t6cleTSg5WmbrrOG90YuVDpsyui+mjO6LV+eei54pnWrf4Jw0V+Xt1SMRYwdkIikhzr2/d88YgzF5GUhPScBVEyKl/XqlJmJkbk+3BvD3L4ioc9NPzsU5I/rgzumReT5/yyR89eR+GN4nHXOnjsRrd0x2x/PTGWMwpn9PTBiSg5FEwbvs1AF4/NrTkRQfh1MGZGJQdiomDMn2EOHE+DjMKszDhCHZSEqIQ/H1E3DNmYMRCgE/nDLCJW8pifH4yUWjkZ2WhJ4pibjvslM894uqg8cC3UqxA8yRftwPyFQZQadaKJjUEsDrT6Trl6opsSgpPF+cSf3QObP7fOMMjvq8Da4iqXOpkgdAzF9n8ovjn5vWV/1U/oq0HykalrZL52PysQQ6S75RNU2X3kW129TW7vFpnF2Ur42k5v5q6n7y+qlBed0AOS8d9ZukPpfSvVlc6k+ObYqqVtfo8uHxoAx1rlKyTYoq/WlSW+nY15TX4tR+xyairztBZzql/lxXnzHIc+7A7FQg1KlQRYiKIoKxszy6ucXHxXlUrjOH5rjq2LA+6bjy9EHYtKcBj6/o9BmLC4Vw9RmDcKitHZ9VR3yPHAco6J3mOr9npSa6444LhSLEznFw2uAs7Kxpwg8uGO7ObUz/DCRGTXUKqUkJOK0gG//z9g70zUjG8L7p+N7kYbj/1U0Y2icNDiKKYEpiHEKhCIGKj4v4cf3v9RNw2q9ew/C+6dha1YA+6f6Nd0RuT9S3hDH3whH46Qsf49n3d+HHXx0NADh3ZB8s37zPXdN/O3coXor69+Zn9fBUeUhg7HpcfiYGZvXArgOH4DjAP287B1996C13LAlxcbjhrCG4asJAxIdCKF71Gc4cmuPzyUuIC2FI73T0SIz3PSv0XivF8/SCbGzb14DvnRf5+/7KoF5ISojD1JNy8dQNE1DfHMZJeRm44ewhvr4cJ6J0PjonYsZMToj35U/MSInQi8euPd23lgrfPXcI/vXpHozpn4HcjBTcPaPTdBsfF0JGSoTA9omaeUfm9kR6coL7f4XcjBQkxIdcIt0rNQmzTh0Qef4RIccK6pwzhmS77QPA+OjLy6KbJ2JwTpqn/asmDMT63ZHvvIvH5WFjNK2PcnkIIYSeKV46lZIYjxmn9AcQIcNLPq50za/HOj1KtyN2OtMQEOz8DshBFbQUFE3nIaWQ4G3QFA2mfmmt0zmTCrRmTbrBcYJAz9U5s1PSQduj5I0GAdA2aEQuT8jsqWma1Nm+lEqFK5dS8EhQdCddU77Rc3KkwH31OKGgoPdXETId0VftpibFY9KwHF/VBKmPdRW1aAl3eMpwTRndF3/7cBeyo6ZqHennbUrJqalJmpqDJ4/s41uz2UX65Ni6OZjMsjwog/4dmXJHmsh9kHvE9BEZxyx44kRBKBRRzEbmphtOEn/VIikhDrdfOMJD7JIT4nD3jDG46alSAF5Hek4oslITcaCpzXPcIb/06ZnsOt3/+rJTfE79jgNMGJKNlMR418QcAhAfBw9hVUiMD+H0giykJMbjl5eOdYMprp4wCL/85wY4cPDj6aNx/6ubcMHovli1vRr9MlLQO/r3khgfh/+ceZK7Sacnx+PkvAycMSQHcaFI8EQoFMJ3zxnqWyulKKYlxSOEkKtqxbFFUaSEHr72rCH45UvrAURIiiKhWamJGJXbE2nJ8chMTUR7h4PLvjLAZ34FIiT5a+PzcLCp1fcZxcDsHvi4ohZ9eiZ7Al6U2gRESElDtBzbT746Gtv2NeDNTftcBS8UAm6/cCTOHxWZ85DeqZh6Ui62VnXWr1338+li/6P6pePXUQWraHA2stOSMKZ/Bk7Ky/CRI44zhnb6ACrSBABf/0o+dtZ4gxq+Otbs8zmWWAEevGK8+/t4ok4rjMvv5ZpsiwZnucROITcj2UMSgYg7QdHgzjWddlIueiR5A1yUv+DRRrcjdrqNVFLEYvEZosqdlItLSnzL24hFjaK1Tk2KDG9bKk0l9aFT26QN0yUCQqSq5Mcmbc7KjEYjRNX4dD6IJt9Evg46Hy5FUmhxedO6m0gDBVXBuK8fnz9V16RxLi4t9+QRVFi2scr1B9I9k5JyJZV5k+YrEWSFcQMyfZUyeDoYer40Lx3Zpudy/0pJZZWUUT4Hfk7Z7qNXJ7I7YxX5e1EY0KsH9hEz+5WnD8JHOw/g+rMLUFnbjLhQp1n2rS2dUaixCHbfiDr6x4VCbsWIjB6JmH5yPwzKTsXOmia8sLrC40sGdBKuScN6458fd6bFCCEyFtW3Uvve2rwPF53SH0+tKsNDVxaiurEVFQcOwYGDi8b2R0u4A/0ze7hjUXxE/Rw7IAPVDa04OS/TNWlOHJaDZRs6/eymjumLlvYODMjqgV9cOhaJ8SG8v6MGt5w33DP2QdmpiIsL4bxRfdAzJRFnDs3BuPxMxIVCLsEd2ifdY2YFImZIIOJ4/+nuOjcKkpu/UxLj8atZYzFzfB7OH9UXz34Qibi+bcoI1DdH8qHd+7WT8WHZAdxw9hBkpnYShvi4kEvqqEKWGiUMifEhTD+5n49AUNxw9hCUfnYA/TJTPP6YPMhGqXxJCXEY0jsNzW3tuCRaD31gdipuOa/z+2F4356enyZcMNr7rFxamIdBUWVNKWyxgJImwB+p2xV8/St6332OjJQEzJlY4DmmSB8AfCf6mXoeFCgpveGcSADF5JF+t4WjgW5H7DixUJuFtHnzzUmXYsKkOCwu9acekSpUSKoL/T+tdcr7pb8H/eS/83XZurce68prPY773DwpBQEoSHOT1pwHhtAx6dKi8GCNWObG11UyWetMqBJp0CVrpoR22cYqn+mSz99E/GcXdQa3UNDnjCqYPB+eFNTAE0jrxqMzq/ISb+o4r3mrW3fdc0DXUPd3yI9JwSm8L37Oi2v0yUG/DGhsCWPp+r0+VQKIbPYpCV536YyURIyNOpinJiXg8tPy8cnfIy9gyQkRX9629lhqnUZIVHxcCE9efzq+8cgqdwNV5Gzz3no3MvGaMwd7rp4ypi/++XEl4uNCHvNTcoKXeNxwdmSjO3NoDnIzU5CRkog/L9+GEEI+AtojKR6zon5gqsnLTpU35uSEeLevcfm9sLb8IM4a3hvbqhpQVt2Igt5pro/g1JNysaumye2P+kFdWjgAh1rbPerbhCGy2qIIkRrb1WcMwq+XbPSc8+3oOp09ojfe2BSxMGT2SERm1Hfu0sIBqG5oRUFvr0mQ4vlbJuGh1yIBLXdEfegS4uIwMDvVWCM4FArhh1NG+o6fN6rzO79oUJbn62tE3564asIgrCbBI10x5Zvw7TMHiwpkV5CVmojW8LGJSs/PirSrImoT4uOQmaoPTxiUE0xOB/Q6thH03YrYBeWx4yYrMapS2OAks5wC3aTVRib5VXEToUnV06XYoP+XNm3VFuDfwKn/Ex2bZJ5sag373jbVuO5bsgHNbR1udCslLTp/KbqWOuVGKaPc9MsVt6ANXkKQyV3nT6bWg88HgM90qQITaJk21beUczA1KQHLN+/Duopan1+bSSGWSJxqTyWQVusk5dOTlC8pcbTbl1DzVs1LZ/I2Ka2xmHUlhTEoQndW4YAvtSn28Xd2iKQOkJW34X3TMbxvOiZFVYP8rFQ4AM4d0RtvR1W7bTFWLujocBAf10mwFEFT3X7jK/moqo98p3EiMiKq4Khzp53cD63tDjJ7JPrMqEDEj03h5snD0N7hIC4ET+DSKQMy0SuqYgWJNGeP6I1lGyMkJRSKmFodx4n+P+QhFHdOG4UfPrfa/f9tU0ZgyceVLtlKSYzD6QWdKtH0gPQuigCPzO2Jb54eSfEhpVZR6T84ro+SXR1yM1JwUdTcqEiWFOHLMT6/lye6UwJP63L1GYPQ2BL2mRuPBo6U1AGRQAzuF3e0oNKT6O7TFxHdithFasXK5iiVh4uarCTyB/jTaijofMF46hHd5kVNhBLRVNAREalKAj2HgitrQf5PdKy0rBVPz0Kd7zlpMZlk+VrGslnTNdepVbr6vUH3Nchni987TjKlQBbJvCoRf3VcIodUMZUUYk7i3OAVQs50aqlO+eKmdXreXE0uJf48xxr4wmFS/tTnEvHk9yNbCDiyiKDTyyN4Uz9vVF8xKfCEIdl4n6SU6ZEYj0Nt7UiIC+GqMwbhYFObqwJ1uIpdCKP79cS4/F54d7vfRAwAp5C8bA4igTVvbKzyKXg6KNPnT6JBCgDwjaJ8rN11MFJxQyCHJwmRnJHxAt8/fzji4kJi2bVR/XpGzMTRT9KSEjAyt2eng3wo5HHCNyEUgksI40Ihl2CPFQgVza3WVdB8hYA/vYiE+LgQ4g8jOXVacoLrD3k88P3zhwefZAGgmxE7mscuyAdI+hkUDavzBaPQRbdyE6FENHXjVH3rqiRI5kMe+MAJhimHGY2W1UWPcpOibuPmEZfqGDe38jlIBExSm6iCyOv3mu5rEIlU66NT+PjzpQjmPTPG+NaWBpPQtQ6Kcgb8CrHkLsDJmU4tdQNoooosv6f8PHVcF8BCx69TQHliaJ3ZlQf10PPp3HSm8qOvE5w4CIVCcACkJev9qiTsqe0s3M7TV4Si6ZuSEuLQOz0ZDc1h11dMfTfmZiTjYFMbBmWn4rxRXoJBcf1ZQzyy4uWnDcSnu2tjJkmAX0EaP7AX2to7fGWtgAjx41AkUpdg2D0PjsuUM1MTfcQpVqQmJeA/LjkJQCSvnErDcqxx5tDPp5/jgaxjVOv2RES3InbXnz0UbYBPIeLkRNqAFIJMU4DfF4xeK5njFCTTIjer6cDNYkHmQ6mkllTvVbeJ68yLfP2oWqlLakuVKQCiCU9nvpNUQAWuIPJ15mqhREyD/L9oXyaFVJeAOVaS5N5j4XngqiV3F9ARWX6t+pwqshIhp+3FGsAS9DKkjuteqqQUOtILgG48V516eBvsiYyRuenYvLcBXxufh4qDh3DjOUOw6EN9TU1lGlQ1VGn0LKc7ZwzJ9phV40KdiYFVO/8z5zT86qUNOFtT2UI59KscZ0CEhI7q19OnUilTZVfBCamEMf2ikZxkljqx0HH8a3E4GNI7zc3ZJ6l0xwoqaKJHYvxhr6lF90e3InaAvAGbNidA2DijCgHgJYk6XzDat2SO431Qk5OObEl5xZRZzERYFCRVTlK8dJUklJrC56MjKjnpyaJZFPBHXEomvFhNoLr56HwmTZG0JtIhBbuYfDR1ZCgWkkTXUT0PWFnmKli8PT4OiaTSOdJniSuyOsUs6L4oSOZj07Np8hmVqqOoeyPdc8+xjs+nePYXFQ2tfmd4RVTGD8xEXq+UQFNsanIC8nqloHBgL6zZddDj/B4KhZCTloSpJ+XiuQ92YWifdBT0TkNZNP1IKASfj13PlERtSokfThmBn0Zzkv14+ii0hDuMZsIRTLmOBYnxcfj+BcHmuStOH4hPKmo9hdpVZK5K5Ktw6qBe+AqLtuyOiI8LIe8YO+hbfHHRrYjd4+9sxyVFnRuSKVkx/ZwmVNVtxD6lTfCP45sOzX3Hk7YCenWQq1xB6hHfLE3mYU5sPvjsgBt2r1NTVJSmicDcNHmYNmiEK0ymqNUgE6jO5CetS1CSZol0qHnxwINYfDRNZEh3XEcEaSkxoLPsm86EryNo0rMkETeumClIz5YU/aw+MyX15jDdS90aUiJIr62r+3ITu/pmgdiRZL7q/zr1DADOHJKNC0bn4k+vbxXbCoVCHh+qa84c7OZWAzqJJM19dv5oOV0DrT4QCoWQoilQf6SINTKTq2ZDe6ehf2aKWyFCoXe6Px+ZhUV3Q7cidpHgCW95JmmT4Z/TgAK+6UkETre5SqYp5Y/HgxYA2XFdtcPJD2CuqqE+56k1uDmVKjvSpq9TMTmBkaob6EiqNFaKrphA+f9NFSR0SZrVtZIaqAs8kOZyOHOTSAlXHqmCpQgm9TGjKit/JjhBo8+SFBTE+5POMSmhQWtiul/SfY+1KkuQadyiE2cN742m1nakJMZhpEH5uiaaX8sNtiCcKI4ocoVCgta4uJBbCL0jhqCHLzqy0pIg6XKqYLuFRXdGtyJ24/IyPSRMt/HGkq8N0BM42qYugpZ+TiNodf3zsXF1DfA7v3MsLvWn1uDmVL4h6tQzqljNLvL7fnFSumD5Nq2TexBZM61lV4mDSfWR+lFt6EiWdE94qhlTzkTpGYyFlJhMlFQBldLa0PO7SqRiKR9mIrTcv9HkI2daG6o8SuPm93L6CDnS0SJC1DJ7xK4yuQofQvjLnNNwY/GHkXxx0c954lcASEmIQ0f0O0mKRD1RcLRys1lYHE90K2LXIzkeq3fVempqSqStK2/7fPOJZSMEzLnvYlGopChB12ymSUeiCBiNUuVERTI/SuZMqlhRX0Dl+6VLIqwjXKY1VWP4w9JNKFlbiabWsC+FjLSuUlumc6XoWCC4okWQamgyAUv+b7GqWtJLQVdVQ4lImdK+SM87j8I9nKAJBToG6e9TMg2bkmKr/g811ovz/7JAlxrkurMKutyW4i7xcZ3pROLiOo+rGqUUOenJyIlee6zrXFpYWBwZuhWxm1U4AD221Ikblslkp6DbUOnGHIt6IZmOgvoPMqkBcjoSDp5aQ4oQpRstnzPPoaYgbbg6J3il1Ojq2GrhsJ8wE0TTOkukiM9FMrNK7QaRKf4zyATMoSN6UlqdoPtpej4lYhsLMVQKIeCPONddP7tI78ZAx8BfYCSlcnFpuRisRPv9steK1QlJseQt87UFVWmhH9qjD+A5I/rgYFOknNVVEwahua1dvPbfp47EGZqKCxYWFl8MdCtil22I5tP5OkkmNFPNUklt4orM4lJ/Vn6TyVAaHzepAWaTYFfSdUhElc+ZKzHShiuRKNqPro4t/Z2Oc86kAk+iYzVWXUoYab7SfPj9CQo2CSJiUjoRXYAJoE8WzddWtacUspnj8jwJioPMqrr14s+KpOLG8uJiWpcDja2+Nda5MdC10aU5oYTVpJpbRKAzEIagT90R1FgInQXpLxjdFxkpifgoWjJKBTsM75vuubSgd5qnLqaFhcUXD92K2NU0tODZ1Z1Eh24mXa1QINUyldrVtcNTegQpe0EmUqmfWH2fdJUJ6Lm6OSuzHf1cFyDC10pB9zv3qZPmzFPCUBJi6ouTTZ4+hq8/9QuU/MKk6+k94cSYzoPnuONBJro8dcNze7oKlQqCUTnGJLOqS6gC8hXy8QW9uEgEi/ti6sqf8fNNypw0Tj4Gfg4Aa4qFrNiFQiHMOnUA4rvoFyZFfYY0fVw1YZDn/13ty8LC4vNHtyJ2L66pwPsVzeIGLKXikDZHyS9OUmhM5igpqlVqg6dA4coSheTrZDKj6XLzSQECUr/cZGbauLnZU6eGmaIiTXM3qUYSEeT3UBFtnj4miCjT/nXpZ3TE2DR+HgkdFFCgzqHJmCWzqk7hUuOTcgzy86XnQVLR3IjyqC8mnb/pfDpO099SrAEuCl92U2xNY6t4fIymfJYJpwzIxGsb9nqJXCgSGXv7hSOM1wZVbjgc3HXR6OCTLCwsYkbXHTSOI2YVDkByQpynyoHC7KJ8FOZneny+1Oa4bGMVVm6rxuLSctdkRUsh0WNqE6btc2dyagKjJEW1U7yqLLLJheBJqcHb5v2uKa9FalKCGMHLr6e/zy7Kd/sxpY4oXlnmm/uU0X0RFwK+fcYgxEXLCNF5zy7Kd33z1PrRcfP11I2LHufX0LWk10j3R4Ii2ueN6uNT93jdXEVSeP/qeukztQaUCC1Yvg1b99ZjwfJtAGAcv1pjHmxB5zO7KB+TR/bxvbBIY5aePfpiw9eMn8+fQ6VY3rlorTsm9fekEk8Pz+3ptiH9jdA5KhSvLMPCD3ZFaiCTe8X/JvmzwZW/2UX5eHFNhXjvvyxY8vGeY9uBE4mW7RmQwy3uGCh2h+MnaGFhoUe3UuyyBaVMIZbUJTo/olgUFX4eV6fohscjTo80NYTqT2ea1EUxqvmaAjYUIXj6vZ3aahtc0QP0/nRUkdGpMCYlT/IZi0X5k66T1CmdCmb6TKf86YIfeJ9BwRZBwTimYAT6HNBgBuk515miJcXS9PckqYOSYk6q0/uge5Z1f5/vkQL1FhEcKcXilSriY1DjLAezsPjio1sRu8ff2Y5rzh0jmnoAaGvA6vyIFLipirZfvLIMCAFzJhb4rjURr6AgANpOUGoIydxL29L58sUSsBFkajR9zlUpau7WBWfweenWRkd6YyXX6nP1f5UbkK+RFCHLoz35fZDWxBT4wNsMeo6kY/QZ182fErHZRXJuQl3Es/TCpHvJ4SROl7x65rg8rCuvxcxxeZ7rJSIb9Pd5qLEez+HLidpotCrH4YpnDhzcePYQ3/FY1LjsNH29awsLiy8GuhWxi1SekH2oAGgT6Or8iExJdlX7JeuiCYGTEnw+XyaCQKHzfzKpREEqjok4cqWOE0OualGfNaou8mAKquRRVcqjKEUJlK56hhqHbozS2pqIeZCq6RIilhtQ5xsmKVWcUEt+fjRH35xohn+67rxN3XOkOxZLMAJfMx5kwdvkz5Pp2dDdGzUGqcKKqOIJY6aEUqfGXn/20C+tj119i5/YDcpOPfKGozzuvsvGomdKIk7KC/bXk6pSWFhYfLHQrYjdGUOyPSRKVyMW8CcClmq5Bpn4lNJCC9wDMiGUTKA6UxyHtLHHouKYojxN6TwWl/rTtfB+uZkxSBnTESiKrlRJkEgFV2gl87YuEAaAG3UrKZxUcZSOqbXREhCSoy8oBQmdD1WEJdMyB2+bV1cxEUb+efHKMpSsq0RTSxhzp41y58WfMVrGTpq7TtmL5Th/OdOpkbZ659EDTzD8rTMGAwB6JMUfh9FYWFgcbXQrYnf92UORke4vs6QgbWrKdCXVcg0yCeakJ7sbHoW0IZraCiIK0iYei4oTZOLVKYlTRvfF3z7chezUJNenSkGpi7eeNwylOw96+qIpQYyKEiFApihZPr9YCKkpV55EPumYdSqdpJryY7Q/+rua18zxeb4cfdJ8+Xy4IqxTZYOIdazwkF3BB056xmgZOzp3k38gr2nM+47FNYK+gPzndL/p8ETHc+/vxDdZuhGFmyYP9QSvdAUODt+Ma2Fh8cVHtyJ2gJwWRNpcJNMVN5FSQmVKF+GDsCGazIuSyRWAqJp1xWSsU0QoJAKwbGMV+vZMcVNrUCh1sXTnwcCUIDozGveVU+Tqnhlj3LYkMsvvQVCFCP67RKilNCaSSVLyEQvqT/dCIM1HOk9ShCWfQJNCqrv3Ki9eS7jD0ydtZ87EArcPHWYX+cvY0X51yjKvaawbD4WkOKp8kV/GqNgtrKwXxbfOGIzt+xoPq92zh/fGtn0NSDgGqUssLCyOPw4rxmn+/PkYMmQIUlJSUFRUhLfffjum61asWIGEhAQUFhYeTrcAOksg0bQganNRb7CmVA+61BnUXGpK5wFENsQrTx/o+lLRsa3cVo1lG6s86hBNIaFUw9lF+UhJjHOTHNM23tzkTT3B56egS51Bz6d9Kswuysd5o/ypNfgYeV88pQjtRzfG2UX5booatS66dC48ZQdvk278kkrEyRkfs7qXADzjUD5iCMGzllJaEX6cp/mgzwudj7SuShGeO3WUx6w5aVgO4MCTAiSonit/nheXlqO5rQPJCXG+e08jtvn8pDWfO3UU5k4b5YlaVv1OGd1XfL5mju+PmeP6e54VaTy654bev8kj+2BW4QDf50cTx/M77fPGhCHZuGrCIKQld7v3egsLixjQ5b/shQsX4vbbb8f8+fNx1llnYcGCBbjooouwfv16DBokmw0AoLa2FnPmzMGUKVOwd+/ewx6wpFQElXQCSNLgaCZ9+hlvN8jk1xWncl1kKADcM2MM7luywaMSUpWCKmN8zgo6JUh3vuSnJqmZ/Fzp8yBFC9BHXMaSCFo3D51KtGZXLQoHZnraDUoFo0g2oPcP5FUh6GemVCbUBE/HFIu5FYCnEoeqVsHvA/clldRNSQ1W68HHEKtybfJPVWSQQhoPXyMetEPz2D362ifG8RwJjvd3moWFhcXRRJcVuwcffBA33HADbrzxRowZMwYPPfQQBg4ciEceecR43U033YSrr74aEydOPOzBArKKwpUeSR1xNyIH2iS1ql2urJkS5prUwdlFnUmTVTJbqqzwcatxKJUiSJ2RlBw+F66ISCobTVxsUuHo/2nghvqcjpHOVxq/pNTw9dPNW6dCcqWLg15H+6dEiK+lInUNzWHRdM3HIiliNBmvtI7SmuieR64gu/MOQVQ3dWqcTilbtrEKLeEO3Ldkg08FpH3r1lI6VxoPV0/VGt23ZIOvrcWl5Xj5k2OXoPd4f6dZWFhYHE10SbFrbW1FaWkp7rrrLs/xadOmYeXKldrrnnjiCWzbtg1PP/00fvWrXwX209LSgpaWzk2lrq7Od44udxsgJ4nlikFQihEelKFLmAuYnclVmot15bXGWpsUutQTXKmSlJwgvzSpT5obzaTCSaomj57VHQf8Kg/N7aY+l9RBHgRhSs2hgjd4jdWgddGpYsqEmJ6S4PZNSS1Vl+i9o+AqmE4dDnoeADk9C/Ul5fNW0L0ESERV8kuUfORMz7HO91CnnFPlTsqXWHPgIGIzjnYNX6TvNAAIt3dg14FDGNI7LbDNs4bnBJ5jYWHx5UOXiN3+/fvR3t6O3Nxcz/Hc3Fzs2SO/UW/ZsgV33XUX3n77bSQkxNbdvHnzcO+99xrP4RsH30yDzKB0M3I3GyElitQe3YRK1u72bJY6J3e1YfGNV9r0dESOb6CS2Sxo3tI6FK8qc33T+OecQPHNnG/ELmFra0dqYryWIFLSm5oUUWd0BFlHNiTyIAWqUMJJgxJiCUSRTIicvHIzKL+P3FxL15i3LxFW+mzo8v7p5k2fC05cddHEkulcEVxJtZSeY+7vyP/GaHUW3oaUEuhYpeL4In2nAUBzuAMvrK7AHVNHAgAcx0FHR+fnSQlxuPncoQCAC0bnSk1YWFh8yXFY3rMhFivvOI7vGAC0t7fj6quvxr333ouRI0fG3P7dd9+NO+64w/1/XV0dBg4c6DmHb8SxRFDq8qS5Bc9ZShSdKkg3Ub5Zzi7yZ/ynG9aC5dt80bBBKoa0+QFyAthY5k2hfNNMqp9EinQbsSJsQUqibqw6gqyrjMDXWvd8qJ+SHx03K+sIGm9bkVpeDYKvFyVjvE1JXdb5EMaS3iQWgsoR9DLAr9f5BfJgFHr/VR8jc9MRFwJmjs/zPDfc/4+vx7EuKfZF+E4jnbu/lh84hGfe+8z9f++0pMB6rhYWFl9udInY9e7dG/Hx8b432aqqKt8bLwDU19fjww8/xOrVq/H9738fANDR0QHHcZCQkIBXX30VF1xwge+65ORkJCf7nfVVSTHJkT+WjU93jm7T0hEa6TqFnHR/xn8KpT7R4AjVD1cxFA40thoJhrRZ83nryKQiHVRJ1BETTop0JslYTXNUoQoifbqAlXXltWgJd7hpNQBv4l96X6ipVhqbzqzM50vVPlWtg1aDMJHIBcu3+czKQcqstB4KJkIknRMUBKM7V7f+0hqZTL5NreHAahSAv/7wsSopdry/04Kw60CT5/8/vXgMLj6lf5fbsbCw+PKgS8QuKSkJRUVFWLp0KS677DL3+NKlS3HppZf6zs/IyMDHH3/sOTZ//ny8/vrrWLx4MYYM6VrSUVpSLGgzlIiESeUzRbmaqilIMBEuydQVRCwp4eDqTpAJWl2jI5PqPB4xKs2bkyKTP520JjqfOhOBMil+OvPg4lJ/4l9dG4A+KTNXBGNVzdR92bq3HusqasWo5+a2DhSvLENqslnRC8praCJEClJCbd6Ozocv6F5If3eSryL3BeSKsokM5qQfu5Jix/s7LQiPv1OGniner2lJSbSwsLBQ6LIp9o477sA111yD0047DRMnTsSjjz6KnTt34uabbwYQMTlUVFSguLgYcXFxGDt2rOf6vn37IiUlxXc8FqiSYoDfv4yTnKBkt0CwymdSedT1OiVMnatz4Nf5rkmbJlXEgpzSJR+sIDKpfiripdrm8+ZmQ2l8fF3p+TqfulhIeRBR50qmVApOt3a6pMxcfdWZfnXESTKV03vBTbjqeZHMurq1MKl7LoSE2roULodzL/gzoTOP64i1yf9PXffUO9txrHA8v9M4/JTNwdtb9pHPLamzsLAwo8vE7sorr0R1dTV+8YtfoLKyEmPHjsWSJUsweHCk3mBlZSV27tx51AcKdJYUA4CStbvxWXUTStbuFst+mfKL6UxG1IRHa3dKflBAsBIGwLhJS2Pimy33Y9OZzWIhqSa1jwczSPMF9HnTqFmNjtFEQhQB4GOWgkJ0Zm9pnDnpcik4HemQ2paIstbMLhAn3TwoZo7L81V+4Pc3qCKGyZytIFWYWFxajpawX+00BRnpjvFnT1ojHZHkc9S9gB1LH7vj+Z0WC/Y3tB63vi0sLLofDit44pZbbsEtt9wifvbkk08ar/35z3+On//854fTrReazVSnXMViMtKZ8NRnkgoVpIRJx2gyVj4mutlKm5wu9YWJnKjrdaRMGqfOPOr62wlqk9SnREIUdL6IipSXrNvtC9YISgGjG4daO96nSUWS2pXImq40l+7lI1aTrhSEEOt4dYFCCjq1Uwru4NfqlFvT34COSPI5SqbgppYwxg3IPCY+dgpfiO80ASSOAgBgq4BZWFgEodvWlKGbaZBy1ZWITMmEB5jrftJNTodY1DW+2Qb5O+mUGynfHvVDlEhZLHnefP52Sf45S+QxVr87fm8k38Yg30pdhLG0xlJ7qg3J5wvQm1fFOcao5OmeDUmdPZJ58b5iCYagMD3DQb6n9G+LH1dronvZWVNei1P7JRnbP1HRwZjd9JP7HaeRWFhYdBd0W2LXFeUqFud81ebcaaPEz3ndT9qHzvyq+10aowS+sXNTVlDwBO/H5MDO14gTRb7h0r6pmqcIEZ2vaoebubn5l0bLzi7KR/HKMq1DvTQOOg9dhHEspkZdAIB0vs58X93QAjjAzPH9fTWFYylDxpU2NyWPYV4mFY2vj7ovHKZnM8i3z9SHdK+78rIzfUTGMQme+KKiJdyOcHsH3ti0z3M8zkp2FhYWAeh2xC5IfdMRDnpekJrBVRGu4HTFD0n6XecbpiNXQGRjl0xZXVXxqHmNHtf5g0mkWF2jPldJZ1V0rCIelDzqzNymfim5MgWeqPM5odGZL3VmSul5CUoVopuXRA51zyNdA2k8sc5LIl4ckgqoWxfTtfxvgF6ru6emFyLpb4i2Wa+p1HAiwgGw+2AzKg42H++hWFhYdEN0O2KnUwNiIUpcfeJVIHRqj0nB4eAbnk4hdE2WJEeezqyo29ilOcaaAoUfB+DWCFURvnQsJnVSJXbm+ew4+ZXM3FS9ykpL0ipOpsATNQ71WdD8Y1mPWKNUdfOaXeQN1AAgBg/wNaBBKMWrylCythJNrWHMnToqcF50zWJxSTDNTfp70r0o8LEA8M0nVncI3fwONdaL55yocBwHEYpnYWFh0TV0K2L3+DvbcUmRNy2DyfcoiBzwjU1HnkyES1JKgggmbYv7kZmIRldNZwqxKihS2a4gkyxfL91GbopUpeummy8fq0klNamYUqSpKVlzUL856cmYM6kAi0s7i9ar4zRQA4BWcdX587n7OtvfdcofJdPS+gT5J5ruRZDZNEi1DnKH0AVNqHWpr6v7UpliHfgDJywsLCxiQbcidpEExT2NPlVchaNEy7SRmcxQkh8XzV9HTWpBucEkk6LKkRZESCSzmS6VBgVXhHQO9FLZLr7OdF5KiZIgKZLquM70JxHQoAS9Ut4zUwDHguXbtOWuVDucZHCVSqec8QolSs1rag1j5rg8ALLiqlOD50wqcMevuxfSiwQgq9gSKeUpb2J5KTI9zwp8zejfyILl2wLL5/F1SezoetWG7giVe9hx/HpdvPWvs7CwiAHditipBMUmE2WQ6Uy3kemKpwOyAsTz1ylCwFWZIGWCKmJ3LlqLlrAcHKGbF6/6IDnzBymXfD24qU2XT01KzOtLi0IUScCc108ySUpjDVJ/XDVUiP41KUsmwq/8CHmqGKoswYHv3nYGDCT4nivAnOtO52IQq8lVjZmOR+cXZ/I95H3G+ncj/e3pgkB4f0E5AE9UdKp0TtQc2wnL6ywsLGJBtyJ2swoHiOTIZCoMUuVMFRsUJD82XVF69VNSg5SCI5ndFpfK5bGktulPqeoDd+bX+bvRNCMmU9viUn8+NQCedB6mwBNetSPIvGk6VyKZOoUuoiiWeRISq7XYurcedy5ai3tmjMHw3J4iwQVINGrUj5CTRaoszS7K981VR1Ao+TL5owX5lErPratiD/RH0AbdZ5NfXlBQB++Dj42SYBpBzNvMSU/W+h1+GRACMP+Nbe4Lm3vclhKzsLCIAd2K2L24pgK35/URN0tdoAQ3w3ECYLrO5OStU7d0JijVVyxpNHQbno588KoPulx89FqeesIUoSjNH/DmEtQFnkikkqtrOvOvLujkg7IDSE6I860dJ13cz42qe29v2YdPd9fhviUb8MR1E3z9qb545QmVKkbKuyYFrugIio58ceVWIraSGkehe5Zov1Lb0n2ORTENUgppW7rnXxeUol4+EvHlgOJy+xpafERucHbq5z8gCwuLboduRexmFQ4AIG+WPh8eYXORCECQmTLIXNWVjU+3SetIoa59E6QghaCIRK6CSQRF15c0N106DmlteDRlkIKkzOA0yIOuHU2xIgUmqDbH9MtAYnwc7pkxxu3bNBY+Z8nZ35R+ZcrovvjD0k2AE/Gd05Evrtxy8isRQilQRTLhSvfJ5LfIz1cISo0jKYW660yBIPTl46pT++BLg1AoapL1SnY3njPkuAzHwsKie6FbEbvsGBQ0bjrTqWyKAJh8iYDgVBmSqVeXB40jFlI4u8hf3zQo3xiFlNiYrgUQUTK5Cqau5QoMV9h0Pll0LqaULibzq0QElBm8eGWZq+bQcegUIjVPrrBRmMbC18SUGxHwp19ZsHwbStZGTeTJCaLSxddHZ87nn0t+bl19IejK+ToVUt2vmePyPKlr1Dhj9aFU8NyPDn2gzokIBw7W7/ameLGmWAsLi1jQrYgdICsLseR7O9y2g4hIkCM5PQZASwoVpPa5OTFIVaRYXNpZo5NHDNM+pVQnkgKjIzCSQqQ2+qaWdl8EpMlJX32mIxBczeHrKpGvWIgLV7pUW394dZMbjKJrh5NQTkgVQYcTbFYNMq0aCZBmPAo6PzopOEZ3PjeTSsQN8N8TqQ+dokmVx+KVZWhuauC364SECphwHKCmsdXzWZwldhYWFjGg2xG7WE2fOtMYNW/yCEeujOh822Ixc8VyTGcKC9q4g1RF3bW684KCQVSAhmk+Uttqo09NjvclfNYRQp06Rcnaso1V2nx6uvWQ2lJ9BgUU0GAUaf50rmqdpHqyc6eO8vW1fPM+xIWAokFZnjb5fLv6oqIjxdL4tcEx0KumUik407Ou64Mq7VzRVNeVrKtEuLkx5rl3d4TgrxEL2KhYCwuL2NCtiF2NJpmrpCCYTGPqWu5sHwsJArpmtuIKiy5Aw0R2TPnG1Pnqp+RvFQu5MY1dikKmfevMzzqzp2mddeqUGgNP78LHIZl7+ZotWL7Nk4cwKKBAF4wSFB0qrTPvSymlqckJPl87Pl/+XJiCFXQE1KT4SYpuVwiiSX3l50spariiSde/uakBb+PLAyk5sVXsLCwsYkG3InYvrqnAmj2t4ls/VxDoRnKgsdWjOuic7XUkiEP3Wawm0iBFSUccde2ZzMG63GS6vHhcxeRjiyV4pKs5AaW2VTt8429qbUdqYrzvfIkg6kz2SoVSeQgpseHX8GAUOrem1rBY8osmbubrysnu/ZePR/Eqb0oWNZZ3t1fj1vOGoXTnQa2aaApW4Ah6fqT7Zrr3upcUPnfVHvd/5P6Xc6f6K5MAEQXvsrGD8FPj7E4MqGhozusKclIRZyU7CwuLGNCtiN2swgHosaUuJrJFSczi0nKtr5aJeHTlM2kMXfFnioVUxqIUxmqmlZQpwB8xzOdLN3+lpkgKqjR+aTw6sgkIyX6TEjzmPD6WoHnTY9T0zIkNryChwO9d8cqyyAdsF5YUQClZMiD7UAKdSlnpzoNe3zYSSMPVTdM6647p5kbHp54DqWyfRNBMaYIU3HVp8a+LRNi/LLViV22rjlSfYM+UA2uKtbCwiA3dithlp3sTs+p8j2JRhXTXd8UEazJ7qv7oT9WGzp8pCCb1REc6YzHJcaVMqZiSiseVRZqXTDcGyWQpmf105kz+O88hJyltunuujplMkk0tYSzf3GmqpeZyeu90Jb844ZpdlI/iVWUuaTI9n2q9dCSLk0BduhLTWuoIt+65dJXBfL8yyAkaLyGnIP3duao58+2kZBEOUDgwE7NOzv5S1IpVvnWOT7OzplgLC4vY0K2I3ePvbIeT0ANrymt9vlYmn7pYfLX45k/Jg9qITKoQVbfUZ5KyJ22usZg3AbPJVacO6syR9JjOZKZTm3TKoo74SlGfOnVMMmfy+fO5SyZEairkCX85weD3q7qhBesqaj1RwhLZ4uSQE1iqOklKo1TLVo2Fnh/kyyetvQSJzKpx6yqi8PvMSZ/HrSF6r6W/Q/U7/7uTgpEoWVQvDtldfAnqrnAcIISQr+rE2LxMS+wsLCxiQrcidu/tqMGEkQMwaViOb2OmP7lPHQVVffjGLpEFvhHp1DATsVSI1edOmTh5OglpHrqfUrvqGA0c0Kk7OhWPgvtZ6XK7ST5gkimOkyFdMEnQ3Lkpjyb8lYIS1P2iJJNHCevIFn2OdM+AbpycMMeSI0+K+pbWJIjo8TXSVYTQPbM6tVpS4Ojv/O9OGqvY1pckj52r2LHoiUsL847HcCwsLLohuhWxO2NINq6J1pjkio7Op44nSqXn0c90my/fiHTBCEFmRAAoXlmGknWVaGoJexzy+bW6dBK6vvn81bm6vGE0cECn7pgc32kfOt8raQ0pJBOl5JvGjwdFIfOxS2ZROia6NtzfKxbSqghiU0sYADyqlyLnqj1Kxm6aHKlXu6681m27eFWZJxiDr2MQGaIEmF4TpNIGmWglJVhKei31o4uSlaKkdXkWv0xQLxtCUKxNUGxhYRETuhWxm1U4QBsFSSGRAina00RedPnqTGZSer5IQELsJ7k2FpNtrOZWda4ub5ikRpmiITm4iVXyvaLz0kXJ8jFyEqbO5bnUFpeWe3zg+Pjp+SYCPDy3p1+Z1Ph78bFzgqjILV1vTs45sfelEonu5k2t7R6Co3s+eEUS3fMsRUpT06spwlXXj0p6Hcta8c+5+V33nNDzQ22HfO2diOhwHIRC/nQnJw/IxMbKuuMzKAsLi26FbkXsXlxTgdV7ItnYpbd8wO/bpjN7qc/4pqXAfbN0JIPCRCKBSOUCtaGZgh/UZhdkgjT1GWReldQdrpioOW/dW4/7lmzAPTPGYHhuT9HEquagq2zBxyId1wV0cAKkVEflA8fboedLpa1o+1RtlEgsXZs/LN2EppZ2pCbHY87EAh9B9NWp5YopI/Z83CoYQ2ee5gSdB1LoVDrJTCuZXnXPEu1ndlHETeD0gizMIeq5ZELm95EqmbFEi9Pz39tR47s3JyKWb9qHUf16+hS7Ab16YPPeL0dksIWFxZGhWxE7mu5EessH/L5tHn8d5icmbVo63ywFRRpK1u3WpncwpbboSvCDzveIQtenRAxNfoCmgIb7lmzAml0Hcd+SDXjiugk+ZU2BK2nqM53TvgkmUyFXHTkhpARB56snRXrqzlVrU7K2EgebWtErNQmpSQkiCdVF0AIysecRvepZRbQWbvGqMry/44BvTXXronu+dGqj5KcXlLibk0KTkiwFzugiYfl60fUIhQ/huS48P90Vb26qihA7IUPxSf0zjsOILCwsuhu6FbHLFkxGdNPRBU0EJb5V15t8sxRMqoNnY3bKPMEPukz7Uk4yBZM6qGAirlJQBu9D+p3P7Z4ZY1zFzgSupAUFjpgIgSmViSnal5tEKYmhfmH8/nLzpBjQ0hp2FTtRNSWEmJMnnl6HB+dwMq3MuIX5mUhJjAv0iZTuBe2frpXO9Ck9S4ebRsUUOCP6g2qiclX/swoHnPDpThynM8mJVHkiNyPlcx2PhYVF90S3InYK3FeJB01wNc2kVOkCIEypLKjqoNs4uX+VpL7pcpIpSOWcdHn4TGoeHSM9R/KrkhSV4bk98cR1E9zrTH6GUs1Z3TUmQqDOk/zzTOom9/ejJIb6hfH14kqUpIbxygichErBF7roanpvlm2s8l0rmU9Na8rVWU7egiqK0PnQ52TB8m0+FZY/Z0FuAyYzvbT2FOpvvaamJ050OE4noZPy2FlYWFjEgm5J7HRBCDrFyaQymCJNTSWrfBsnU1y42nY4ipz0OY/GVOOR5hIUvEDbM+WT4+oYnYspSbPOz8tUwYOvk0ROudopETHTmAH4/DL5feJkRWqTPxMS2afjL1m726Pi0ujs4pVl2jxysazp4lJ/Ghs6H517gPQs0HO4CssJnBoT90flARnUJMvXlap1vudN87d+omHTnnoM75vuEjpJsbOwsLCIBXGHc9H8+fMxZMgQpKSkoKioCG+//bb23Oeffx5Tp05Fnz59kJGRgYkTJ+KVV1457AEDEV+lK08fiJnj8rBg+TY39YnaTOZMKvCpNmozATo3nuqGFvzwudX463s7UbyqzNeP2ujURqPy59E+1XE4cM8FvGqbDrpz1GZYsm6373PV3z0zxvhMXHS8FOoaSmbVHKTx08+lNtU6UzWU98nHE3SN6pPeH9rXso1VnrZSkxKwprzWHa/kSyiNiY9L/b5sY5WnX0VWlm/e5zmPtjlldF/EheCrQazGWryyzB3X8NyeSE2OlEQrXlXmeYaUYpWalOAjjdK5yzfvw52L1nrWanZRvsdky+/VnIkFxufFVO3i/svH47xRfTwvOPQ5KV5Zhua2DiQnxPmIqUsWQ/D5Mqp1pXPn6zxnYgFmjusv3sejieP9nfa3D3d5/OossbOwsDhcdFmxW7hwIW6//XbMnz8fZ511FhYsWICLLroI69evx6BBg3znv/XWW5g6dSp+/etfo1evXnjiiScwc+ZMvPfeezj11FMPa9AmJSrWJMDq2K6aQ6hvbhMTR0lpM4x+SUSFkBQkbtLS+UHpzIoUWWlJPuWFK3w6ZYznS+PjNwUuxOJzpaD7LBYTbFBbXK2S/eHkVCC8DSkyenGpHDxDVaWm1rAYfctVMmUG5SZbfpy2rTPvcgWN+ndSM7hJSZXWlAcvxJKvkfrRKeIH6H1Ydeqp6f4qt4b3t9T6nomjhS/CdxoQ+QpyWB67sQMy8EmFTXNiYWERO7pM7B588EHccMMNuPHGGwEADz30EF555RU88sgjmDdvnu/8hx56yPP/X//61/j73/+OkpKSLn8J1jS04NnV3k0jKJeX2qCKBvXymTXV9XAiqSYAc5oNdQ3gJ2OSnxGPROQbso4s0nHFQlAV+Hi15zrsJyBu3lLgQhABo9BFwwaRDEBvVjaN10MGkhKwfPM+rKuoxf2Xj/cRDNoW93Xkbaq584hTKaKW10pNTSoXK0yklvqP07b5uXRu3I9R5xsnmdgVggi6KbDFRNpMZn/d/Tf93ajPDzXWH7Oo2OP5nUbhOJE/yXe3V7vqXVJ8HL55+sDDbtPCwuLLhy6ZYltbW1FaWopp06Z5jk+bNg0rV66MqY2Ojg7U19cjOztbe05LSwvq6uo8/4BIHjtqppFMctycpDaoh9/c5jNrKof4udNG+YgLNb9KalTJ2t2iSUoyZ6q+qEmLQjLp0XlRzC7KR2F+puurBXSaMaeM7usZr278cyZFTNmUzEombWr+pP3TNrnpjLfF/68DNdUCEVVx4Qe7PCZyqS2dQju7KB/JCXEukebt0+slEySHZL6eM6nAYwrlJm2dGZSSIqkyCL2/9IVBt4bFK6NrtbLM047kIqDA7xtdH12UqnQNHxt/PmK5j9S8zOdIo2KPBY73d5qE2kNtaG2P+CvecPZQJMSf4A6GFhYWRxVdInb79+9He3s7cnNzPcdzc3OxZ8+emNp44IEH0NjYiCuuuEJ7zrx585CZmen+Gzgw8sY6q3CAz1eM5yxbs6sWqcmdvkqSTxrdWPgmQzcmaeMy+Qzp/Ih0/mMKkq8d3yBpG8pXS22wOj8xHSngx02+eYUDM11FVLo2iOiZiJ/pPkiqojRO3dh1RFoiFeqZAaD1LZT8Ben53L+T+mLqniP6rMZyf3X/lwIMJH9TTk75CwJdU+7zp56HIL9OH4GO4T5yEk6hiOGz7+/EscDx/k6jcBCR7Jpa27F9XyMAYMYp/TBxaO8uzMjCwuLLjsOKiuU1Cx3HiamO4bPPPouf//zn+Pvf/46+ffW52e6++27ccccd7v/r6uowcOBAZDNzJ/cLml2U79bnVBsq3YSVOTUoqTHF4lJvtGEsPkPUR0qNU0rcy/2p1OZbvLIMCMHN7K/a1PmIST5LdPzS/HTtcQVMMlPyNrlZzfSTXkvXnt8HVYVB54clrR1dU07M1f8lfzx6n3RrLPkv8nqpuijq2UX57rnKNKqrPSv1FTQWlfjYlLMO8JtJpXrEUn98rSmkvzmKoPuoxqhLkyMRw2OB4/Wd5vYPoCPyKGHH/kbPuC7+HIJHLCwsThx0idj17t0b8fHxvjfZqqoq3xsvx8KFC3HDDTdg0aJFuPDCC43nJicnIznZXwS8pqEFr2zZp918laM13aykvG8SEdL5FinfOJogVsrjpds8VdtSyghazopeX7KuEgA81Q04odT5JZn8oHSpMkzjN62VjkzpfOGka3W/S75WdN7S2kn3TwysYEREt8a0Xcl/kddL1RFDei4cGNOSqPO5bycFH0uswURBBFG6l3ReNMUOff7o3xx/LqVnNeje0r4VMZw+IgM/9a3EkeN4f6dR/PZfGz35664/a0jA6C0sLCz86BKxS0pKQlFREZYuXYrLLrvMPb506VJceuml2uueffZZXH/99Xj22Wdx8cUXH/ZgX1xTgWvOHeMGTAB+lU2nEPG8b/Q6+jvf7ExqAt0EVV9SvUzehhqTFPWqiAdCsgKnEIsSx6N2ea4xKWeflM+N5iOTSM+RBFTofqeQlDBdxLCkFPIAG0mp0vnqmdpVPzk540En/Jp1FbVoCXegeFWZmDuQP4N8fXWETPIVNKmrnCBKKiSfl3o5MpHYWBJKm+4tPU+ti8kn7UhwvL/TFEIhoCXc7klzEoNgaGFhYeFDl02xd9xxB6655hqcdtppmDhxIh599FHs3LkTN998M4CIyaGiogLFxcUAIl+Ac+bMwR//+EeceeaZ7ptxjx49kJmZ2aW+ZxUO0JoHeWQgDSgAOjclyVylUN3QgvuWbEBzW4dHLdEpYjqzIu9fbYamiEuFnPRkzJ02SpubTbWvM7/qji8uldN30M8lJYl+rqtyoOuTz8FEniSSLM2dr51unSkR5c+LpGJKCmB1Q0vE6T8aNW1SIukxXUocBUXypbJ0gL8eMSfbUrQ2d0tQ4AolXVvpJYirkHRe1BdPUjd15NKkDNJ1l54jdd70EceuTurx/E5TCIVCrinWwsLC4kjQZWJ35ZVXorq6Gr/4xS9QWVmJsWPHYsmSJRg8eDAAoLKyEjt3djo6L1iwAOFwGLfeeituvfVW9/h3vvMdPPnkk13qO9uQByvIBAdEfOyCqjBIG5sCVzRiMelKFSJigYnImQiTDiYyqY5zk7PuepMqKOXjU+eZlBsTSTaZSHXrHKsPoZS6hLZdsjZqFk9O8PSr84WMNcoWAM4Z0RvrKmq1ypuKaOXrJRElqqrxNDxUoeRry83kKs2OBJP6pz6XyKWOiPJ1l16gFPE71FhvXMsjwfH8TlMIAehwbCExCwuLI8dhBU/ccsstuOWWW8TP+Bfbm2++eThdiHj8ne245lxvIXqdCdGkaFHTHOBVMJQZlLZNiUpLuANxoUjyWcBvStQphToSOrsoH8Wrytzi8ookUKVl6956sYC86tNEihR0Pkx0nvfMGOMbq7QOJlXQpCqaCJaJJOuIIz2Hr7OODJp8CDnhpUSHz7V4VRmeevcz9ExJ9PhCSuRGp74qMqpT3mYX5Xty2ClIREmhZO1ut3SXpBAfaGzVlrFTajjN/8fVP7XWkuqtey5MRJQrr3yNFPGbPiIDc30jPno4Xt9pLkJAhwO0d1hqZ2FhcWToVrVi39tRgx5pXtWB/h6LvxQ35fLrTeqG2oyUisCjCQHZn4hvvlz9KllbiYNNreiVmuSSBKq0rCuvFQvI637qohRj9cvj0Cl0HHwcpkCKIHOl5P/HzXbU9M7XWUdkpTHqCC8AMbkvAMABeqYkYmBWDx8Z5evPzdzuOW3tSE2KF8ksN3HS2rYmX7rCgX7lka4tD8yQCLZU2SLIF870NycRUa7Ocf9Pvg7HysfuiwSu110bzTNpYWFh0RV0K2J3xpBst5g6T55qUsS6EhUbq3KUmuQt9q76lYInpMhcqqZEFMSIYif1K/kHmjbU1OSo6lJeq428NEVL8nZ1SozUv05Z49dI5ERHDiSzXSzkQvIblEipzn+Q90Hbp2k86Fil4AxFlqiZOzU5koCamy0lcEVWUgTVelKzsHSfeAUWibRLwUKSaZs+jyYfzSClT/L/5IQ70bhC3R8hhHz1YQdmpx6fwVhYWHRrdCtid/3ZQ/Hs6ip3QwTgIwI8a77OB4tuGlyx4Zs4ANFBX8qHp/KUUUhjoH3OnTpKnC8lITr/QIng6FQXU7qQIOVRR9hMUZC6clY6XywdkaJkWae8SddzQqVT5riCqkunI7Uf1J5ad06WdGRZdz/5uZScN7WEA0mizvzLSRd9xqn/Jr8H/PmXyCtgVvpM95eOuakljFD4kDivEwWhUMTHzsLCwuJI0a2IXY1QaUIiFXST0yliQX5p0ucSOQS8Gy6PdKREc+a4PDFdhOpz69563LdkA+6ZMcZTVF6NR1IDJf8lU4oWSf2SEAtx0p1HTcKSiVdHaoKIVBCCCJVOmYs1l13Q+EyJfHWR1dwPLyjhMl0LN/BDML9ylVjn88lJmikIxRRQ0xWlL9b76z5HrWG8t6PG9/mJhEjwxPEehYWFxYmAbkXsXlxTgTV7Wj2kDTCbVJVPHVeITNfqPtdtilzdS2WETBHN4bk9XR8jqf37lmzAml0Hcd+SDThzaE5gKpXZRflaR3pOSoLUEX4eNfea1sSU9qO6wVvAXte27rjJBCyRAtNYeHsmM2us0cs6oqLIEVcsucJG++Y+Zrp5mpJM07VUiqwUla1866j6SpU7XRBKECTyKil9dP0kf1ApdVGo7RCei+mudC9U1TUjIyOSysWxip2FhcVRQLcidrMKB6DHljofsQIOn5DQDYgqI9ImpHMOl8yW9DqeIJePXeGeGWM8ih0fs6R06NrnaxKrw7tJ1dIFTeigS01Cx6COSyXXdOSUkhrJb8uUDkanNJrUIx0h0yl6ihxxxVIX4CD5mHFipOZJx2AivEqRlaKypflysz+/hyYzfFNL2OdvqFtPX8k6IVl0V5Xa7ownVpbhviv6IhQCDjS1Hu/hWFhYnACIO94D6Aqy01mBcXQWdS9eWYaV2yKFxdUxmlCVn09TnazcVo37lmxwrzedJ30+uyjfV2h96976zqLuSRFHeTo29Tkd4/Dcnnjiugm+KNocNm/an6tIlncWjVdQhOnORWsxZXTfwALuvG16PV9LOn++Vrr/8zHQ47oi8LQtOl61Jss2VvnmwOclzZNDuof83iME0eSpzlVjGp7bEzdNjtS7peerPuZMLPDczymj+yIlMQ73zBjjI0bLNlZ55knHYLp/KqGyGgsAz5zofKW5cKjgCPosqDYQgjiOwvxMT2Jk6V7wcXAfWXXNiW+KDWHF1urgEy0sLCwC0K0Uu5qGFjy7WlYNqArC3/hN/nQ6E5TkKE+VMZ1KJ/kqSSZAXSCFTw0h5jx1PFaT5eyiziAKRRAodP55QUEYfH34mprWX9dGkE+gbp6xHJPOMSlWXcl1F6vC2dV0IKY56NwJTH1I8+XjNc1FPQtSAuuZ4/LcZ5SOQVLjpGeOj5MHgkwZ3RdvffqZeP6JAls+zMLC4mihWxG7F9dUYPWeiLmCbxQzx+X5NkUa6aeO8wStOhMU3zR5/jsTmVJ90+hCbgLU1d3k51FzHgAf2VMEQrXD+9URJsBLKGiwBjWF6q4/HEJlaiNWn0DJhy7IZCxdpzNhS4qRyRwpkXbAXFmDjzeI7PA56NwOYvHH4ylKdARWIoL8WZDmyyNl6U/AT2JNY+DXnMiwvM7CwuJooVsRO+VjRzcnU/JTXXoQKdhAKhFlcgSnkEp6ZaUlGf2D6Od8YzcFYwBytKmkBHIlircrpYWhbQYleqbzk4gUJULSWsTiv8XbVgjyH5TO4/52Us1hSTFSCArYkEiJ9Ozwdkwlt+g1Qcoa719SlU3Ei78gqM+6EtwSRNY5adaRforZRfk41Fh/QgZPAEDHic5aLSwsPld0K2KnfOz+sHQTStZWoqk1jDkTCwAEb6YKuo1kcWk5StZF64ImJRiVEMCrTADmShi8H/55kIrBN9PiVWVuyhfJyZ4nM5bIEgBfWhi+LkFkT50jkSZOQKToYRMxC9rwg0y0uoAH6Tq6VqZ+TcXsuVJqWkOTohkLETQpa7pgDml+kpIZ9KwHkX6JrKt2m1q9+faCgndUO8WrytDc0u67HycKfvvKRiQnxHuODe2TdpxGY2Fh0d3RrYidC6fzp2SKK15ZhpJ1lWhqCWPuNH/y36bWMIpXlmHOpAKPSU3VieXJWmMliK4SJpj4VI66W88bFtgW/8nVKZq6Rdp0dcmMTWOOVaEM8q3jpbPo9bprpXEF+adJBIWSCcn3UncdXytpHVSUq05Z40qptIY65Ys+wzxxtLqWpwXR3VO+VrHMT7eu/BmRngMeESsRanWvee5EqQ3pmSlZW4lwcyNORMSFgNZwB1IYsTt/lN4sb2FhYWFCtyR2tJwTIKgMymFFcFxRGwUQKb1FTWqKBOqStVJIpki1qcGJqGHUxKdy1D385jY8cd0E4/w4UZFSXASZsiS1xmQ+5WukS1XBTWl8DNzBPhbTXRCJMyl/OnWMEzi+trGsFSdtUiJgeq0p+AaQlS8+dilxtC4tiG6teGmvoPkFratpzZpaY0vpIt0LXRv8mWlqDaO5oQFv48RDKBQpJWaDJywsLI4WuhWxo1GxJsIwZ2IBUpMSRHOk2ijg6GtX6jZrkxlS/V+3qdEcdQo8mSwgR43S9rrqvxZkRpPmYTJXc/8zrjyZgjWk8XH/ulhVHIkgBZkZdWZT3VpJzwH3u1PgPpVByhcnUToiSq/lSrDOzMvJNZ+fWluuyJr8+vgaqueuuiFSN1mniCoE+Vjy2sv02tSkBFx2xiD8VFz57o0QbGJiCwuLo4tuReykqFhJZTCRmpz0ZLc2q05BkSJleXUAAL5NUKrqQMfHlTqdSqOLCJWuVWPXkTVJrZFMojytigQd4aPoakCEzn8sSMXh49CpTVKQhU6J5T50uojpWAI3FFkrXlUGOHDN/rroUT52Ph8ela2LII0lkpmvrbSuOpLH52t60dDdE1o6b3huz8Bgp5XbqnGosR4nIkKhEDoQyWNnYWFhcTTQrYjdoZZ21wyoc46nMCkkQOdGXjSol4eE6ExcvDqAajvWCEbT+IIc7gG58oKktgDwkaKgNBRSWhXeP/dnVP3GQjx1/UrEU1KCghALEaF9lazb7fOD1JVno1AEv7mtwzcnKXhEMvvz66Sxc/O75PMo+ZfGEsksra1JQQwKVOHrL5F2Ok5aOo++7FBizV9upo/IwFzxjnRvhAC8u70a5xtS3VhYWFh0Bd2K2K3bXYvzxvbyBA1ws6fkPM7VNh6N+vCb2zwKTvGqMjfqVql7EgmTCIspgtG06Sro/NgAOX0Frd5Ax8LNdroN2bPZM5VH2vglp3i6Fro50I2aK1GSWiOZUlU70r2MhYjQNqVUJ7p7pdZetd0S7iT4OhVO3Xtl9u8qiTIl3Kbgn0nnSupfUDu6AA0phYkuSEQX2Su5JQBeYg14FfGn3tqAExEhAJv3NsBaYy0sLI4WuhWxO2NItmeToZsmVdZ43VGT2gb4felo1K1CkIM/b5OqKrqNX6dy6PKoSek2dJs+Jy6mcfBxquOxRJmqcXE/OT6HrkSP0jXm/m26exmUT45DR+KkNQLkCN6g+0PN/hRdIVFB8+F9SufGEiQhKafctQHwP/tBQSKS2piTnuxR6oLSEy0uPXFLiqmgiS1VDe6xMf0zjtNoLCwsTgR0K2JHIfkcAZ3O47QMlrRZ8g2Kmt7mTCqI/BKCq3iZ/KqClDRFTPimK22m/DPar1QpQpc0eXaRP0WGaq+pNezmwZPWQsGkfCmYgg50JJqaQXXEVEcE+Th0ypqJxPL58nMkxVGtJR9n0P3h48pJ11eaMCVT1kUwc/Ox5PPGnzMerBPkM6j7XD1jpihpk9qo2qambenloqkljHEDMk/IBMVxQjjsyz88B798af1xGI2FhcWJgG5F7N7bUYMeaea6k7FGZgapGDy9xOLSzjQSyoSkI2q0fU5MpCANXZ4xPk6TuVEiZusqatES7vAkXF5c6s2Dp47xFBmcAEr+XIDZdEyhM4PqlDOdmsqVRZNvoeneUFWXnyMpjlK6kVjvDx+Xzpevq2ZVAD6SrmuLPme6fHKm9dLNUVKXTeqppPhR0zaH6uPUfkm+z04E2JAJCwuLo41uReyUKZb6e+lqnUqbb1dSaEikTaWRoDVedWRGIiY6ZUzaTHWRsbH49an5mMzP/BhPkaEjgLGYjoNIJ1fdTD5qJp/EoLx6pvWWVF1OKnXrxgmo8mek6xLUBuA3e8ai6HLCyO+Rri9p3XXHdYqf7hnk85B8CLWKX2sYpw/OclVybgZWL2+TR/bBCQmbwM7CwuIoo1sRu+vPHooMTeCEiUxQdYOn9pDIhi6FClUCTYoMv16RTh7BW93gr0+rYDJh6ZzvTaWjpPxjdBPlKmcsxCSWY9I8JOd9iaQFEURKKtX/6ee8Agldg6CC9tIaUQJKFU7JJYBC56Mm+dpNGd0Xdy5a66YCiSWimb9cdCXRsDrO11d6GQpKI6PmYfq/T/ETqqjQPpW6uXzzPt+4TwTEWV5nYWFxlNGtiJ2CpDyYyARP80BTe9ANjStHnAAGOejrSIIu8GBxqb4+rUnF4wSxqyZdafOVNneJjOhUtAONreK1fB4mfz6u/PF7yoNigggkr0DikhUNsdclAObnc4VTule6a4PMnlIqEErc+dpJBDTIhCv5meoUa5rzzqS8qZ/chM8JO33OdAEfvE/gRE53YpmdhYXF0UW3Ina88oROUZE2acCbNFZtPJKvndqI4PiT90qRgvRaKfWIyQSm6tNKxIdvysrpXYpMlfqj104Z3dezJiYyouYjHQf89WElX0IddEqQzl/SFBQTNHdVgcRHHFr8CXqlYBx+Ph0zVfwkEqzmwfvizwInylIqEB1x1903ScHVmdG5WZT+zdCXIROZ42omV+FMpnqd76DqU63RCZvuhPG6sQNsRKyFhcWRoVsRO155whQAkZqUgDc37cO6ilpX4QE6gwcKB2aKqgFVjmYX5SO1tFwkApIZVRoPT7pLiWhOemd9WgXTBkyd3iXVRQJtjxMXky+VQpAfGyURyzZWBdYjlVQZHlDA/SUBOShGMp+aQMkKVpZ5IoalaGEPuYkSa1N/UoQnzQ+oS3xN2xye29NV6iSTu/TCwu+FRAS5qib5b0omZUraKPnmLza6lCVB/SqYTOFNrWG8f4KnO+Eo6J32+Q7EwsLihEHc4Vw0f/58DBkyBCkpKSgqKsLbb5vLcy9fvhxFRUVISUnB0KFD8ec///mwBjurcIBHqZpdlC9G96nNMCUxzjWXKahrlBq3bGOVa4qUIkFvmjwMcyYV+JIg37loLV5csxslayvd9k3jkf4vgbdBj82ZVOCOVYG2KbWvrp0yuq9I0Og1XHlRG/Ga8lqkJiW4ZFSpN1TZUf5gyzZWecbA5+Ou6cQC7b2MZZ34NdUNLfjD0k34w6ubIsQNndG+dy5a6x5TY0hNTsCaXbWee7NmVy1SkxO0vmR0zIp0bN1b71krHuGp5ktJbvGqMveaKaP7Ii4Et9qCOi49L4p8rSmv9awN7UO3PtI46LOve/bomHgCYQpdm6Zz6HM2uygfhfmZLtmm58OJBE4dSxyv7zRO7JRp9pozBx9WexYWFhZdVuwWLlyI22+/HfPnz8dZZ52FBQsW4KKLLsL69esxaNAg3/k7duzAjBkz8N3vfhdPP/00VqxYgVtuuQV9+vTBN77xjS71na1x/gb8ylJQ2pOZ4/Ncs5oCV/MoQeMqS3NbB/KzeuC0giytWiapFuqnLv+aFJWoU0e4ynagsVVrzpRMYkBw0uOumGxNc6QKoxQwEuS/KPXLiSgv36XMt9QXjq+bUhilygmUZHLTsVLDqAmaj/sPr27yzFMyBQPQVluQUpnw+2V6jnTBErr1lZ49ky+dUt+UUkvXU1Jseb/8fvKUMvT8+rq6Y+Zjdzy/0ywsLCyONrpM7B588EHccMMNuPHGGwEADz30EF555RU88sgjmDdvnu/8P//5zxg0aBAeeughAMCYMWPw4Ycf4v777+/ylyD1seObBgAfcZF8n2KpLRtUN5X7FynoCA8NLJBSe0h9mPyQ+BzoNTw/msn8Bcj1UXX+U3yduLJjmiMdoy5gRAfVdtGgXmJiXzUWXr7LFMms1k0ao2TC5GZYboKWfM3UPNVcqUlemWcpGc9KS3L7VC8ZnIjz+6Xzf6QkVq07f175+qpzdbVw+fwk30oeMay7XjLxS6Zmdf5Tb1X4xn20cDy/02y2EwsLi6ONLhG71tZWlJaW4q677vIcnzZtGlauXCles2rVKkybNs1zbPr06XjsscfQ1taGxMTEmPvnPnYSwdCpZ2oDHJmb7pq+ONRGsnVvPdZV1LqbLd9sJKd32jdXJKTAgqCxm5S0rgRPBDmqc+VKzUeaH18nnbITNEceMEIh+anxdeSJfdWY5k4d5VMJdT5iqq+mljBG5qZ7/O0kMkKDCHgffCx8nsrsr+ZDx0TJOCXpuuoUJhWYnhNLwIv0fwDaWrixJJDmKqn6O5VUb+lFTJc6ZlbhgGOi2B3v7zQeFWuJnoWFxZGiS8Ru//79aG9vR25urud4bm4u9uzZI16zZ88e8fxwOIz9+/ejf//+vmtaWlrQ0tLpE1VbG1GnpgzLAFCH6SMyUFdXh0Tg/7d393FRlvn+wD/zxAwgMybKkyBCi8/rQ5Am5tojrprlnt2NXS3N9LxkswQ5Vpp7Mj0lW3vymKm0mQ91QmPTbN3fIZOzuwGKWRK0JZw0IUGFCIwZEB1g5vr9QUyOMzwMzj0D93zer9f9qrm87rm/37nhmi/X/YTfThoCWNv7dvy/yWR2eM+ZcXpcudyIK+YruNrchP9XdBaP3h7rNOb/V1Ru10fRegUnKi5B0XbFts5/Hy3HiYpLuHK50dZ2bTwmk9m2zRkjhiDv9He2uK/v6yz262O4Nod5Ywdh0ACtQ67Xb//ada7d9vWx/3bSEOw6etauzVl+17u2z7yJQx224yweDYAlt/2wz53sq/8+Wo6mxkb4qRW29+rqc+wqpuvjvv4z/e+j5fik4hKUivbDoYrW9v17fdyXmsx4v+QC5k0cCo3VjF2dbOPafoMGaG15XmoyQ9F2xWnczvZPZ/vf2Wfa2c/Rte8LwG4b12/TWd+OXK/dP85+bgDhEM+6mTF4v+SC7f1f/9sZfHCqBpcuNWD53XFd5t1Zu/qH/IS45gHObuDtMc1oNCE8wIoL318FAEyOCOv0Z5uI5KXjd93d4xqECy5cuCAAiMLCQrv2559/XowcOdLpOnFxcWLjxo12bUePHhUARHV1tdN11q1bJwBw4cKFi91y9uxZV4asbnFM48KFi7eXqqoq9wxoP3Bpxm7w4MFQqVQOf8nW1tY6/AXbISwszGl/tVqN4OBgp+usWbMG6enpttcNDQ2Ijo5GZWUlDAaDKyH3OSaTCVFRUaiqqoJe3//vWSWnfOSUCyCvfIxGI4YNG4ZBg9x7dSzHNPeQ08+anHIB5JWPnHIBACEEGhsbERER4db3damw8/PzQ3x8PHJzc/GLX/zC1p6bm4sHHnjA6TpTp07FX//6V7u2I0eOICEhodNzUbRaLbRax5O8DQaDLHYmAOj1etnkAsgrHznlAsgrH6WyV3do6hTHNPeS08+anHIB5JWPnHKR4g87l0fJ9PR0vPHGG9i1axfKysqwcuVKVFZWIiUlBUD7X6YLFy609U9JScG5c+eQnp6OsrIy7Nq1Czt37sSqVavclwURUS9xTCMiOXH5difJycmor6/Hhg0bUF1djXHjxiEnJwfR0dEAgOrqalRWVtr6x8TEICcnBytXrsS2bdsQERGBLVu28H5PRNQncEwjIllx6xl7Erl69apYt26duHr1qrdDuWFyykUIeeUjp1yEkFc+cspFCObTl8kpFyHklY+ccpGSQgh3X2dLRERERN7g3jORiYiIiMhrWNgRERERyQQLOyIiIiKZ6DOF3fbt2xETEwOdTof4+HgUFBR02T8vLw/x8fHQ6XSIjY3Fa6+95qFIu+dKLu+99x7uvfdeDBkyBHq9HlOnTsWHH37owWi75+q+6XDs2DGo1WpMnDhR2gBd4GouZrMZa9euRXR0NLRaLW6++Wbs2rXLQ9F2z9V8srKyMGHCBAQEBCA8PByLFy9GfX19l+t4Qn5+PubOnYuIiAgoFAq8//773a7T18YAKcawAwcOYMyYMdBqtRgzZgwOHjwoVfh23J3Lnj17oFAoHJarV69KmYaNK/lUV1dj/vz5GDlyJJRKJdLS0pz26w/7pie59Kd909PvS2/tmz7D21dvCCHEO++8IzQajdixY4coLS0VqampIjAwUJw7d85p//LychEQECBSU1NFaWmp2LFjh9BoNGL//v0ejtyRq7mkpqaKF198UXzyySfi9OnTYs2aNUKj0YjPPvvMw5E752o+HRoaGkRsbKxISkoSEyZM8Eyw3ehNLvfff7+YMmWKyM3NFRUVFeLEiRPi2LFjHoy6c67mU1BQIJRKpXjllVdEeXm5KCgoEGPHjhXz5s3zcOSOcnJyxNq1a8WBAwcEAHHw4MEu+/e1MUCKMaywsFCoVCqxceNGUVZWJjZu3CjUarX4+OOP+10uu3fvFnq9XlRXV9stnuBqPhUVFWLFihXizTffFBMnThSpqakOffrLvulJLv1p3/Tk+9Jb+6Yv6ROF3eTJk0VKSopd26hRo8Tq1aud9n/qqafEqFGj7NqWLVsmbrvtNsli7ClXc3FmzJgxYv369e4OrVd6m09ycrL4/e9/L9atW9dnCjtXc/nggw+EwWAQ9fX1ngjPZa7m88c//lHExsbatW3ZskVERkZKFmNv9KSw62tjgBRj2IMPPih+/vOf2/WZOXOm+M1vfuOmqJ2TIpfdu3cLg8Hg9lh74kbG5BkzZjgthvrLvrlWZ7n0133T4frvS2/tm77E64diW1paUFRUhKSkJLv2pKQkFBYWOl3n+PHjDv1nzpyJkydPorW1VbJYu9ObXK5ntVrR2Njo9mdi9kZv89m9ezfOnj2LdevWSR1ij/Uml0OHDiEhIQEvvfQShg4dihEjRmDVqlW4cuWKJ0LuUm/ySUxMxPnz55GTkwMhBL799lvs378fc+bM8UTIbtWXxgCpxrDO+vR0LOkNKcfjpqYmREdHIzIyEvfddx+Ki4vdn8B13DEmO9Nf9k1P9dd94+z70hv7pq/xemFXV1cHi8Xi8MDt0NBQhwdtd6ipqXHav62tDXV1dZLF2p3e5HK9l19+GZcvX8aDDz4oRYgu6U0+Z86cwerVq5GVlQW12uUHm0imN7mUl5fj6NGj+PLLL3Hw4EFs3rwZ+/fvx/Llyz0Rcpd6k09iYiKysrKQnJwMPz8/hIWFYeDAgXj11Vc9EbJb9aUxQKoxrLM+PR1LekOqXEaNGoU9e/bg0KFD2LdvH3Q6HaZNm4YzZ85Ik8gP3DEmO9Nf9k1P9Od94+z70hv7pq/xemHXQaFQ2L0WQji0ddffWbs3uJpLh3379uG5555DdnY2QkJCpArPZT3Nx2KxYP78+Vi/fj1GjBjhqfBc4sq+sVqtUCgUyMrKwuTJkzF79mxs2rQJe/bs6ROzdoBr+ZSWlmLFihV49tlnUVRUhMOHD6OiosL2TNT+pq+NAVKMYb0dS26Uu3O57bbb8NBDD2HChAmYPn06/vznP2PEiBEe+6NCis+xv+yb7vTXfdPV96W39k1f4fUplcGDB0OlUjlU07W1tQ5Vd4ewsDCn/dVqNYKDgyWLtTu9yaVDdnY2lixZgnfffRf33HOPlGH2mKv5NDY24uTJkyguLsbjjz8OoL04EkJArVbjyJEjuOuuuzwS+/V6s2/Cw8MxdOhQGAwGW9vo0aMhhMD58+cRFxcnacxd6U0+GRkZmDZtGp588kkAwPjx4xEYGIjp06fj+eefR3h4uORxu0tfGgOkGsM669PdWHIjPDUeK5VK3HrrrZLPCt3ImNyV/rJveqM/7Juuvi+9sW/6Gq/P2Pn5+SE+Ph65ubl27bm5uUhMTHS6ztSpUx36HzlyBAkJCdBoNJLF2p3e5AK0/+XxyCOPYO/evX3qfCdX89Hr9fjiiy9QUlJiW1JSUjBy5EiUlJRgypQpngrdQW/2zbRp03Dx4kU0NTXZ2k6fPg2lUonIyEhJ4+1Ob/Jpbm6GUmn/K69SqQD8OMPSX/SlMUCqMayzPl2NJTfKU+OxEAIlJSWS/zHR2zG5O/1l3/RGX9833X1femPf9DkevFCjUx2XPO/cuVOUlpaKtLQ0ERgYKL755hshhBCrV68WDz/8sK1/x+X1K1euFKWlpWLnzp197nYnPc1l7969Qq1Wi23bttldat7Q0OCtFOy4ms/1+tJVsa7m0tjYKCIjI8WvfvUrcerUKZGXlyfi4uLE0qVLvZWCHVfz2b17t1Cr1WL79u3i7Nmz4ujRoyIhIUFMnjzZWynYNDY2iuLiYlFcXCwAiE2bNoni4mLbbQ/6+hggxRh27NgxoVKpxB/+8AdRVlYm/vCHP3j0lhruzOW5554Thw8fFmfPnhXFxcVi8eLFQq1WixMnTkiaS2/yEULYfhbj4+PF/PnzRXFxsTh16pTt3/vLvulJLv1p3/Tk+9Jb+6Yv6ROFnRBCbNu2TURHRws/Pz9xyy23iLy8PNu/LVq0SMyYMcOu/0cffSQmTZok/Pz8xPDhw0VmZqaHI+6cK7nMmDFDAHBYFi1a5PnAO+HqvrlWXyrshHA9l7KyMnHPPfcIf39/ERkZKdLT00Vzc7OHo+6cq/ls2bJFjBkzRvj7+4vw8HCxYMECcf78eQ9H7egf//hHl78H/WEMkGIMe/fdd8XIkSOFRqMRo0aNEgcOHJA6DSGE+3NJS0sTw4YNE35+fmLIkCEiKSlJFBYWeiIVIYTr+Tj7WYyOjrbr01/2TXe59Kd909PvS2/tm75CIUQ/OwZDRERERE55/Rw7IiIiInIPFnZEREREMsHCjoiIiEgmWNgRERERyQQLOyIiIiKZYGFHREREJBMs7IiIiIhkgoUdERERkUywsCMiIiKSCRZ2RERERDLBwo6IiIhIJljYEREREckECzsiIiIimWBhR0RERCQTLOyIiIiIZIKFHREREZFMsLAjIiIikgkWdkREREQywcKOiIiISCZY2BGRT8vPz8fcuXMREREBhUKB999/v9t18vLyEB8fD51Oh9jYWLz22mvSB0pE1AMs7IjIp12+fBkTJkzA1q1be9S/oqICs2fPxvTp01FcXIxnnnkGK1aswIEDBySOlIioewohhPB2EEREfYFCocDBgwcxb968Tvs8/fTTOHToEMrKymxtKSkp+Pzzz3H8+HEPRElE1Dm1twPoCavViosXLyIoKAgKhcLb4RCRhwkh0NjYiIiICCiV3j3QcPz4cSQlJdm1zZw5Ezt37kRrays0Go3DOmazGWaz2fbaarXi0qVLCA4O5phG5KOkGtf6RWF38eJFREVFeTsMIvKyqqoqREZGejWGmpoahIaG2rWFhoaira0NdXV1CA8Pd1gnIyMD69ev91SIRNSPuHtc6xeFXVBQEID25PV6vZejISJPM5lMiIqKso0F3nb9LFvHGS2dzb6tWbMG6enpttdGoxHDhg3jmEbkw6Qa1/pFYdcxWOr1eg6CRD6sLxy2DAsLQ01NjV1bbW0t1Go1goODna6j1Wqh1Wod2jmmEZG7xzVeFUtE5IKpU6ciNzfXru3IkSNISEhwen4dEZEnsbAjIp/W1NSEkpISlJSUAGi/nUlJSQkqKysBtB9GXbhwoa1/SkoKzp07h/T0dJSVlWHXrl3YuXMnVq1a5Y3wiYjs9ItDsUREUjl58iTuvPNO2+uOc+EWLVqEPXv2oLq62lbkAUBMTAxycnKwcuVKbNu2DREREdiyZQt++ctfejx2IqLr9Yv72JlMJhgMBhiNRp6PQuSD5DYGyC0fInKdVOMAD8USERERyYQsC7uCM995OwQiIiIij5NlYWft8weXiYiIiNzvhgu7/Px8zJ07FxEREVAoFHj//fft/l0Igeeeew4RERHw9/fHHXfcgVOnTt3oZomIiIjoOjdc2F2+fBkTJkzA1q1bnf77Sy+9hE2bNmHr1q349NNPERYWhnvvvReNjY03umkiIiIiusYN3+5k1qxZmDVrltN/E0Jg8+bNWLt2Lf7lX/4FAPDmm28iNDQUe/fuxbJly25080RERET0A0nPsauoqEBNTQ2SkpJsbVqtFjNmzEBhYWGn65nNZphMJruFiIiIiLomaWHX8TzF0NBQu/bQ0FCHZy1eKyMjAwaDwbZERUVJGSYRERGRLHjkqtjrH3ArhOjyobdr1qyB0Wi0LVVVVVKHSERERNTvSfpIsbCwMADtM3fh4eG29traWodZvGtptVpotVopQyMiIiKSHUln7GJiYhAWFobc3FxbW0tLC/Ly8pCYmCjlpomIiIh8zg3P2DU1NeHrr7+2va6oqEBJSQkGDRqEYcOGIS0tDRs3bkRcXBzi4uKwceNGBAQEYP78+Te6aSIiIiK6xg0XdidPnsSdd95pe52eng4AWLRoEfbs2YOnnnoKV65cwWOPPYbvv/8eU6ZMwZEjRxAUFHSjmyYiIiKiayiEEH3+AVwmkwkGgwFGoxF6vb7b/nmnv8OMEUM8EBkReYKrY0BfJ7d8iMh1Uo0DsnxWLBEREZEvYmFHREREJBMs7IiIiIhkQpaFnQKA1drnTx0kIiIicitZFnZqlQKtVqu3wyAiIiLyKFkWdhqVEm0WztgRERGRb5FlYadWKljYERERkc+RZWGnUSl5KJaIiIh8jiwLO7WKM3ZERETke+RZ2CmVaLVwxo6IiIh8iywLO41KgTbe7oSIiIh8jCwLO7VKiTbO2BFRD23fvh0xMTHQ6XSIj49HQUFBl/2zsrIwYcIEBAQEIDw8HIsXL0Z9fb2HoiUi6pwsCzuNUoFWnmNHRD2QnZ2NtLQ0rF27FsXFxZg+fTpmzZqFyspKp/2PHj2KhQsXYsmSJTh16hTeffddfPrpp1i6dKmHIyciciTLwk6tUqKNV8USUQ9s2rQJS5YswdKlSzF69Ghs3rwZUVFRyMzMdNr/448/xvDhw7FixQrExMTg9ttvx7Jly3Dy5EkPR05E5EimhR1n7Iioey0tLSgqKkJSUpJde1JSEgoLC52uk5iYiPPnzyMnJwdCCHz77bfYv38/5syZ44mQiYi6JMvCTqPkOXZE1L26ujpYLBaEhobatYeGhqKmpsbpOomJicjKykJycjL8/PwQFhaGgQMH4tVXX+10O2azGSaTyW4hIpKCLAs7Na+KJSIXKBQKu9dCCIe2DqWlpVixYgWeffZZFBUV4fDhw6ioqEBKSkqn75+RkQGDwWBboqKi3Bo/EVEHeRZ2ShZ2RNS9wYMHQ6VSOczO1dbWOszidcjIyMC0adPw5JNPYvz48Zg5cya2b9+OXbt2obq62uk6a9asgdFotC1VVVVuz4WICJBpYdfZX9pERNfy8/NDfHw8cnNz7dpzc3ORmJjodJ3m5mYolfZDp0qlAtA+0+eMVquFXq+3W4iIpCDLwo6IqKfS09PxxhtvYNeuXSgrK8PKlStRWVlpO7S6Zs0aLFy40NZ/7ty5eO+995CZmYny8nIcO3YMK1aswOTJkxEREeGtNIiIAABqbwdARORNycnJqK+vx4YNG1BdXY1x48YhJycH0dHRAIDq6mq7e9o98sgjaGxsxNatW/Fv//ZvGDhwIO666y68+OKL3kqBiMhGITo7dtCHmEwmGAwGGI3GHh/CyDv9HWaMGCJxZETkCb0ZA/oyueVDRK6TahzgoVgiIiIimZC8sGtra8Pvf/97xMTEwN/fH7GxsdiwYQOsfDIEERERkVtJfo7diy++iNdeew1vvvkmxo4di5MnT2Lx4sUwGAxITU2VevNEREREPkPywu748eN44IEHbI/bGT58OPbt28fnKhIRERG5meSHYm+//Xb87W9/w+nTpwEAn3/+OY4ePYrZs2d3ug4fv0NERETkOsln7J5++mkYjUaMGjUKKpUKFosFL7zwAn772992uk5GRgbWr18vdWhEREREsiL5jF12djbefvtt7N27F5999hnefPNN/Od//ifefPPNTtfh43eIiIiIXCf5jN2TTz6J1atX4ze/+Q0A4Kc//SnOnTuHjIwMLFq0yOk6Wq0WWq1W6tCIiIiIZEXyGbvOnqvI250QERERuZfkM3Zz587FCy+8gGHDhmHs2LEoLi7Gpk2b8Oijj0q9aSIiIiKfInlh9+qrr+Lf//3f8dhjj6G2thYRERFYtmwZnn32Wak3TURERORTJC/sgoKCsHnzZmzevFnqTRERERH5ND4rloiIiEgmWNgRERERyQQLOyIiIiKZYGFHREREJBMs7IiIiIhkgoUdERERkUywsCMiIiKSCRZ2RERERDLBwo6IiIhIJljYEREREckECzsiIiIimWBhR0RERCQTLOyIiIiIZIKFHREREZFMsLAjIp+3fft2xMTEQKfTIT4+HgUFBV32N5vNWLt2LaKjo6HVanHzzTdj165dHoqWiKhzam8HQETkTdnZ2UhLS8P27dsxbdo0/OlPf8KsWbNQWlqKYcOGOV3nwQcfxLfffoudO3fiJz/5CWpra9HW1ubhyImIHLGwIyKftmnTJixZsgRLly4FAGzevBkffvghMjMzkZGR4dD/8OHDyMvLQ3l5OQYNGgQAGD58uCdDJiLqFA/FEpHPamlpQVFREZKSkuzak5KSUFhY6HSdQ4cOISEhAS+99BKGDh2KESNGYNWqVbhy5Uqn2zGbzTCZTHYLEZEUOGNHRD6rrq4OFosFoaGhdu2hoaGoqalxuk55eTmOHj0KnU6HgwcPoq6uDo899hguXbrU6Xl2GRkZWL9+vdvjJyK6HmfsiMjnKRQKu9dCCIe2DlarFQqFAllZWZg8eTJmz56NTZs2Yc+ePZ3O2q1ZswZGo9G2VFVVuT0HIiJA5jN2XQ3ORESDBw+GSqVymJ2rra11mMXrEB4ejqFDh8JgMNjaRo8eDSEEzp8/j7i4OId1tFottFqte4MnInJCtjN2GqUCrRbh7TCIqA/z8/NDfHw8cnNz7dpzc3ORmJjodJ1p06bh4sWLaGpqsrWdPn0aSqUSkZGRksZLRNQd2RZ2apUSbVart8Mgoj4uPT0db7zxBnbt2oWysjKsXLkSlZWVSElJAdB+GHXhwoW2/vPnz0dwcDAWL16M0tJS5Ofn48knn8Sjjz4Kf39/b6VBRATAQ4XdhQsX8NBDDyE4OBgBAQGYOHEiioqKJN2mWsUZOyLqXnJyMjZv3owNGzZg4sSJyM/PR05ODqKjowEA1dXVqKystPUfMGAAcnNz0dDQgISEBCxYsABz587Fli1bvJUCEZGNQgghafXz/fffY9KkSbjzzjvxu9/9DiEhITh79iyGDx+Om2++uUfvYTKZYDAYYDQaodfre7TOF+eNiBioQ/AAntdC1N/1Zgzoy+SWDxG5TqpxQPKLJ1588UVERUVh9+7dtjZP3MxTrVKgzcoZOyIiIvIdkh+K7biZ569//WuEhIRg0qRJ2LFjh9SbhUalQKuF59gRERGR75C8sCsvL0dmZibi4uLw4YcfIiUlBStWrMBbb73V6TruuEu7WqlEG8+xIyIiIh8i+aFYq9WKhIQEbNy4EQAwadIknDp1CpmZmXZXml3LHXdpV6sUuNpquaH3ICIiIupPJJ+xCw8Px5gxY+zaRo8ebXeV2fXccZd2jUrJq2KJiIjIp0g+Yzdt2jR89dVXdm2nT5+23UrAGXfcpV2tVPBQLBEREfkUyWfsVq5ciY8//hgbN27E119/jb179+L111/H8uXLJd2uWqVEK29QTERERD5E8sLu1ltvxcGDB7Fv3z6MGzcO//Ef/4HNmzdjwYIFkm5Xo+KMHREREfkWyQ/FAsB9992H++67zxObsmm/KpYzdkREROQ7ZPusWI1KgVbeoJiIiIh8iGwLO4VC4e0QiIiIiDxKtoUdERERka9hYUdEREQkEyzsiIiIiGSChR0RERGRTLCwIyIiIpIJFnZEREREMsHCjoiIiEgmWNgRERERyQQLOyIiIiKZYGFHREREJBMs7IiIiIhkgoUdERERkUywsCMiIiKSCRZ2RERERDLBwo6IiIhIJljYEZHP2759O2JiYqDT6RAfH4+CgoIerXfs2DGo1WpMnDhR2gCJiHqIhR0R+bTs7GykpaVh7dq1KC4uxvTp0zFr1ixUVlZ2uZ7RaMTChQtx9913eyhSIqLusbAjIp+2adMmLFmyBEuXLsXo0aOxefNmREVFITMzs8v1li1bhvnz52Pq1KkeipSIqHss7IjIZ7W0tKCoqAhJSUl27UlJSSgsLOx0vd27d+Ps2bNYt25dj7ZjNpthMpnsFiIiKbCwIyKfVVdXB4vFgtDQULv20NBQ1NTUOF3nzJkzWL16NbKysqBWq3u0nYyMDBgMBtsSFRV1w7ETETnDwo6IfJ5CobB7LYRwaAMAi8WC+fPnY/369RgxYkSP33/NmjUwGo22paqq6oZjJiJypmd/bhIRydDgwYOhUqkcZudqa2sdZvEAoLGxESdPnkRxcTEef/xxAIDVaoUQAmq1GkeOHMFdd93lsJ5Wq4VWq5UmCSKia3h8xi4jIwMKhQJpaWme3jQRkR0/Pz/Ex8cjNzfXrj03NxeJiYkO/fV6Pb744guUlJTYlpSUFIwcORIlJSWYMmWKp0InInLKozN2n376KV5//XWMHz/ek5slIupUeno6Hn74YSQkJGDq1Kl4/fXXUVlZiZSUFADth1EvXLiAt956C0qlEuPGjbNbPyQkBDqdzqGdiMgbPFbYNTU1YcGCBdixYweef/55j2xTCOGR7RBR/5WcnIz6+nps2LAB1dXVGDduHHJychAdHQ0AqK6u7vaedkREfYVCeKj6WbRoEQYNGoT/+q//wh133IGJEydi8+bNTvuazWaYzWbba5PJhKioKBiNRuj1+h5vM+/0d5gxYsiNhk5EXmYymWAwGFweA/oqueVDRK6TahzwyIzdO++8g88++wyffvppj/pnZGRg/fr1EkdFREREJC+SXzxRVVWF1NRUvP3229DpdD1ax523BuDhWCIiIvIVks/YFRUVoba2FvHx8bY2i8WC/Px8bN26FWazGSqVym4dd90awF+jwtVWK/z9VN13JiIiIurnJC/s7r77bnzxxRd2bYsXL8aoUaPw9NNPOxR17hSkU8N0tZWFHREREfkEyQu7oKAgh9sABAYGIjg4WPLbA+j9NWi82opQfc8OARMRERH1Z7J+pJhep4bxSpu3wyAiIiLyCK88Uuyjjz7yyHYC/dS4bGZhR0RERL5B1jN2SqUCvCaWiIiIfIWsCzsiIiIiX8LCjoiIiEgmWNgRERERyQQLOyIiIiKZYGFHREREJBMs7IiIiIhkgoUdERERkUywsCMiIiKSCRZ2RERERDLBwo6IiIhIJmRf2KkUCrRZrN4Og4iIiEhysi/sgnRqNJnbvB0GERERkeRkX9jp/TUwXWFhR0RERPIn+8IuSKeG6Wqrt8MgIiIikhwLOyIiIiKZkH1hp1Wr0GoR3g6DiIiISHKyL+yIiIiIfAULOyLyedu3b0dMTAx0Oh3i4+NRUFDQad/33nsP9957L4YMGQK9Xo+pU6fiww8/9GC0RESdY2FHRD4tOzsbaWlpWLt2LYqLizF9+nTMmjULlZWVTvvn5+fj3nvvRU5ODoqKinDnnXdi7ty5KC4u9nDkRESOFEKIPn8CmslkgsFggNFohF6vd3n9/NPf4WcjhkgQGRF5wo2OAV2ZMmUKbrnlFmRmZtraRo8ejXnz5iEjI6NH7zF27FgkJyfj2Wef7VF/KfMhov5BqnHAJ2bs+nzlSkRe0dLSgqKiIiQlJdm1JyUlobCwsEfvYbVa0djYiEGDBkkRIhGRS9TeDoCIyFvq6upgsVgQGhpq1x4aGoqampoevcfLL7+My5cv48EHH+y0j9lshtlstr02mUy9C5iIqBuSz9hlZGTg1ltvRVBQEEJCQjBv3jx89dVXUm+WiKjHFAqF3WshhEObM/v27cNzzz2H7OxshISEdNovIyMDBoPBtkRFRd1wzEREzkhe2OXl5WH58uX4+OOPkZubi7a2NiQlJeHy5ctSb5qIqEuDBw+GSqVymJ2rra11mMW7XnZ2NpYsWYI///nPuOeee7rsu2bNGhiNRttSVVV1w7ETETkj+aHYw4cP273evXs3QkJCUFRUhJ/97GdSb56IqFN+fn6Ij49Hbm4ufvGLX9jac3Nz8cADD3S63r59+/Doo49i3759mDNnTrfb0Wq10Gq1bomZiKgrHj/Hzmg0AkCXJxq7+3wUjVIBc5sFWrXqht6HiOQnPT0dDz/8MBISEjB16lS8/vrrqKysREpKCoD22bYLFy7grbfeAtBe1C1cuBCvvPIKbrvtNttsn7+/PwwGg9fyICICPHxVrBAC6enpuP322zFu3LhO+7n7fJThgwPxTV3zDb0HEclTcnIyNm/ejA0bNmDixInIz89HTk4OoqOjAQDV1dV297T705/+hLa2Nixfvhzh4eG2JTU11VspEBHZePQ+dsuXL8f//M//4OjRo4iMjOy0n7MZu6ioqF7f60UIgbzT3+GOkZ2f3ExEfZfc7vsmt3yIyHVSjQMeOxT7xBNP4NChQ8jPz++yqAPcfz5KT65uIyIiIurvJC/shBB44okncPDgQXz00UeIiYmRepNEREREPknywm758uXYu3cv/vKXvyAoKMh2orHBYIC/v7/UmyciIiLyGZJfPJGZmQmj0Yg77rjD7kTj7OxsqTdtR6lQwGLlw8WIiIhIvjxyKLYviLzJHxe+v4JhwQHeDoWIiIhIEh693Yk3DRsUgHOX+LQLIiIiki+fKezUKuUNHYq19nDdljYr2izWXm+HiIiIqLc8/uSJ/qi5pQ1/KbmIML0OAgIKKNBmFdCqlZgeN9h2O5XSiyac/74ZfmolrEJA+UN7q0XgjpFDoFH5TB1NREREXsDCrgeOnqnDgwlRUCnt74fX0NyCD0/VwN9PDatVIGpQAJLGhjmsb26z4G9ltQjVazExamC399UrvWhCuEGHmwL93JoHERERyZtPFXaKH66Mvb5A60qt6SqCB/g5XWdggB9+Pi682/fQqlX4+bgw1Jqu4u//VwulUoGOd/NTKeHvp0JLmxXNLRa0WqwYE6FHRf1llJxvgFKhgBACbRaBoTf5Y3Q471JPREREzvlUYTcuQo9/nm/ApGE39Xidzyob8PNxjrNwvRGi1+Fuvc6uraXNiistFmg1SmjVSttsXuRNjlfvVtY344MvqvHzcWFOZ/2sVoETFZdwtc0CBdoL2faZRH/8JCTILTkQERFR3+VThV3wAC0+P9/Q4/5tFit0GmnPi/NTK+Gn7tk2hgUHYNAAPxz6/CL0/hpYLAKtFitGhgUhSKfBx+X1uGPkEATpNHbrfVN3Gf9b+i10GhVuix0EtZfO9Wu1WKFWKviINwIAXLrcgkE83YCIyK18qrBzVWm1CWMjDN4Ow84ArRpzfhoOAdguxiirNqGmthFzJ0Q4XWf44EAMHxyIKy0WFJypg1UI3BYbjEBt++6/bG5Djekqzn9/xe6iDyEEFD8cCu74LwBYhYAQwC3DburyPMDvL7egpKoBAu3vqVYq0XClBZOHD0LIdTOX3Wlps/a4AKa+TwiBT7+5hJlOzkklIqLe87nCbnhwIMq/a0LskAHd9q1vasH4yIHSB+Wi62fcenrenb+fCneOCoHFKnCioh6tlvZCLdBPhVC9Drf/ZHCPzz+0WgWKqxpgqmoAFO1P9rAKgZAgLcaE63G8vB4AcMfIIQ4zdB+X1+PURROgAAb6azA8OBBajRJl1SY0Xm1rP4R8zY2tFWgvYlvarBAQGDJAh3FD9TC3WVFc2QCLVSA6OAARA/1t8QshUH+5BZWXmmG80mo7p/H6QlUACA70Q/AALQz+GgzQ/vgrYW6zoKG5Fc0tFtu5mVYh0NLWfjsbf40KAkBdkxlKhQITowY6fH7NLW1ovNqGJnMbqi41oyMrBX78zMZGGDAkSGu3nsUqcPa7JlxouAIhBGIGD0DEQB0Kv65Hi8UKvU6D22IH2fJoswpYrAI6jcr2Ht9fboFOo4K/n8rufZUKoMViRa3JDLVKgXCD46P9vqppxIWGZiiggEKBH/atDuOGtv+hc7XVgu+bW6BSKlD+3WU0XW2DQgEoFMCkqK4LfgA4UXEJU2IGddmHiIhc53OFXeyQAfj7/33bo8JOrlRKBRJvHnxD76FUKhAf7Xiu4sWGK8gt/RaTht3kUKx0uC022Pb/Dc0t+Ka+GVdbLRgdrofBX+N0nWt9a7qKj776Dlq1EhOHDYRGpcS5+mYUnq2z3atQoVAgONAPNw8eAENA1+9Z32TGpcstuNhwBU3mNlu7n0qJQYF+8NeooFUrIQSgVipsxd/V1vZzGUeH69FmsSL/zHftn01HYSrai2mDvwaBfmr8LG4IlD8UflZbnEBxVQM+q/wefiolOipQtVKB2CEDcMeI9sK4/LsmHD9bj8SfBEOrVuH7yy34W1kt1Kr2FTQqJZQKBa60tkGI9gLupkA/mFutuNJqQUe92X4rHkCjVCDUoENDswX/PG9EXMgAxA4ZACEEPjr9HaJu8sddo0LtPqdz9Zdx+MtqaFRK6DQqDB6gRavFirERetvhf4tV4PPzDSipavih0PtxpvdqqwV3jAyBVq2E8UorBgbwMCwRkbspRF955lcXTCYTDAYDjEYj9Pobvyr07//3rcOX1vVa2qw4UVGP6XFDbnh7RH3d2e+acK7+Mq62WjE1NliSW+20WazI+bIGep0ao8P1CHXhcLy7xwBvk1s+ROQ6qcYBn5uxA4BQvQ5Vl5oRNajz58Z+ccGInw7tW+fXEUnl5iEDcLPEs9hqlRJzx4fj8/NGl4o6IiLqOZ88G31shAFfXjB22cd4pYWHiojcTPHDuYhERCQNnyzsAGBC1EAUV37v7TCIiIiI3MZnC7uIgf6obTSjzWJ1+LeSqgbJD0sRERERuZvPFnZA+604PviyBt81mm1t319uQePVVkQHB3oxMiIiIiLX+eTFEx20ahXmTohA4dd1+PKCEUqlAg3NLbi/kxv9EhEREfVlPl3YdUj8Sfs93SxWAesPN68lIiIi6m9Y2F1DpVRABRZ1RERE1D/59Dl2RERERHLCwo6IiIhIJljYEZHP2759O2JiYqDT6RAfH4+CgoIu++fl5SE+Ph46nQ6xsbF47bXXPBQpEVHXWNgRkU/Lzs5GWloa1q5di+LiYkyfPh2zZs1CZWWl0/4VFRWYPXs2pk+fjuLiYjzzzDNYsWIFDhw44OHIiYgcKYQQwttBdIcPzCbybVKOAVOmTMEtt9yCzMxMW9vo0aMxb948ZGRkOPR/+umncejQIZSVldnaUlJS8Pnnn+P48eM92ibHNCKSahzoF1fFdtSeJpPJy5EQkTd0/O67++/QlpYWFBUVYfXq1XbtSUlJKCwsdLrO8ePHkZSUZNc2c+ZM7Ny5E62trdBoNA7rmM1mmM0/3gjdaGx/VjXHNCLfJdW41i8Ku8bGRgBAVFSUlyMhIm9qbGyEwWBw2/vV1dXBYrEgNDTUrj00NBQ1NTVO16mpqXHav62tDXV1dQgPD3dYJyMjA+vXr3do55hGRPX19W4d1/pFYRcREYGqqioEBQX16ObBJpMJUVFRqKqq8unDHPwcfsTP4kf98bMQQqCxsREREdI8Feb6cUV0c6NyZ/2dtXdYs2YN0tPTba8bGhoQHR2NyspKtw7o3tIff6Y6I6dcAHnlI6dcgPaZ+2HDhmHQoEFufd9+UdgplUpERka6vJ5er5fFzr9R/Bx+xM/iR/3ts5CiABo8eDBUKpXD7Fxtba3DrFyHsLAwp/3VajWCg4OdrqPVaqHVah3aDQZDv9oH3elvP1NdkVMugLzykVMuQHuN49b3c+u7ERH1I35+foiPj0dubq5de25uLhITE52uM3XqVIf+R44cQUJCgtPz64iIPImFHRH5tPT0dLzxxhvYtWsXysrKsHLlSlRWViIlJQVA+2HUhQsX2vqnpKTg3LlzSE9PR1lZGXbt2oWdO3di1apV3kqBiMimXxyKdZVWq8W6deucHvrwJfwcfsTP4kf8LOwlJyejvr4eGzZsQHV1NcaNG4ecnBxER0cDAKqrq+3uaRcTE4OcnBysXLkS27ZtQ0REBLZs2YJf/vKXPd6m3PaBnPKRUy6AvPKRUy6AdPn0i/vYEREREVH3eCiWiIiISCZY2BERERHJBAs7IiIiIplgYUdEREQkE7Ir7LZv346YmBjodDrEx8ejoKDA2yF5XEZGBm699VYEBQUhJCQE8+bNw1dffeXtsPqEjIwMKBQKpKWleTsUr7hw4QIeeughBAcHIyAgABMnTkRRUZG3w5IlV8eivLw8xMfHQ6fTITY2Fq+99pqHIu0ZV/J57733cO+992LIkCHQ6/WYOnUqPvzwQw9G27Xefk8cO3YMarUaEydOlDZAF7maj9lsxtq1axEdHQ2tVoubb74Zu3bt8lC0XXM1l6ysLEyYMAEBAQEIDw/H4sWLUV9f76FoO5efn4+5c+ciIiICCoUC77//frfruG0MEDLyzjvvCI1GI3bs2CFKS0tFamqqCAwMFOfOnfN2aB41c+ZMsXv3bvHll1+KkpISMWfOHDFs2DDR1NTk7dC86pNPPhHDhw8X48ePF6mpqd4Ox+MuXbokoqOjxSOPPCJOnDghKioqxP/+7/+Kr7/+2tuhyY6rY1F5ebkICAgQqamporS0VOzYsUNoNBqxf/9+D0funKv5pKamihdffFF88skn4vTp02LNmjVCo9GIzz77zMORO+rt90RDQ4OIjY0VSUlJYsKECZ4Jtgd6k8/9998vpkyZInJzc0VFRYU4ceKEOHbsmAejds7VXAoKCoRSqRSvvPKKKC8vFwUFBWLs2LFi3rx5Ho7cUU5Ojli7dq04cOCAACAOHjzYZX93jgGyKuwmT54sUlJS7NpGjRolVq9e7aWI+oba2loBQOTl5Xk7FK9pbGwUcXFxIjc3V8yYMcMnC7unn35a3H777d4Owye4OhY99dRTYtSoUXZty5YtE7fddptkMbrCHWPrmDFjxPr1690dmst6m0tycrL4/e9/L9atW9enCjtX8/nggw+EwWAQ9fX1ngjPJa7m8sc//lHExsbatW3ZskVERkZKFmNv9KSwc+cYIJtDsS0tLSgqKkJSUpJde1JSEgoLC70UVd9gNBoBwO0PGu5Pli9fjjlz5uCee+7xdihec+jQISQkJODXv/41QkJCMGnSJOzYscPbYclOb8ai48ePO/SfOXMmTp48idbWVsli7Ql3jK1WqxWNjY1eH4N6m8vu3btx9uxZrFu3TuoQXdKbfDrGgZdeeglDhw7FiBEjsGrVKly5csUTIXeqN7kkJibi/PnzyMnJgRAC3377Lfbv3485c+Z4ImS3cucYIJsnT9TV1cFisTg8uDs0NNThgd2+RAiB9PR03H777Rg3bpy3w/GKd955B5999hk+/fRTb4fiVeXl5cjMzER6ejqeeeYZfPLJJ1ixYgW0Wq3dI7PoxvRmLKqpqXHav62tDXV1dQgPD5cs3u64Y2x9+eWXcfnyZTz44INShNhjvcnlzJkzWL16NQoKCqBW962vzN7kU15ejqNHj0Kn0+HgwYOoq6vDY489hkuXLnn1PLve5JKYmIisrCwkJyfj6tWraGtrw/33349XX33VEyG7lTvHANnM2HVQKBR2r4UQDm2+5PHHH8c///lP7Nu3z9uheEVVVRVSU1Px9ttvQ6fTeTscr7JarbjllluwceNGTJo0CcuWLcO//uu/IjMz09uhyZKrY5Gz/s7avaW3Y+u+ffvw3HPPITs7GyEhIVKF55Ke5mKxWDB//nysX78eI0aM8FR4LnNl31itVigUCmRlZWHy5MmYPXs2Nm3ahD179nh91g5wLZfS0lKsWLECzz77LIqKinD48GFUVFTYnvPc37hrDOhbf37cgMGDB0OlUjlU9rW1tQ5VsK944okncOjQIeTn5yMyMtLb4XhFUVERamtrER8fb2uzWCzIz8/H1q1bYTaboVKpvBih54SHh2PMmDF2baNHj8aBAwe8FJE89WYsCgsLc9pfrVYjODhYslh74kbG1uzsbCxZsgTvvvtunzgNwtVcGhsbcfLkSRQXF+Pxxx8H0F4YCSGgVqtx5MgR3HXXXR6J3Zne7Jvw8HAMHToUBoPB1jZ69GgIIXD+/HnExcVJGnNnepNLRkYGpk2bhieffBIAMH78eAQGBmL69Ol4/vnnvTrT7Sp3jgGymbHz8/NDfHw8cnNz7dpzc3ORmJjopai8QwiBxx9/HO+99x7+/ve/IyYmxtshec3dd9+NL774AiUlJbYlISEBCxYsQElJic8UdQAwbdo0h9venD592vawe3KP3oxFU6dOdeh/5MgRJCQkQKPRSBZrT/R2bN23bx8eeeQR7N27t8+c8+RqLnq93mH8SElJwciRI1FSUoIpU6Z4KnSnerNvpk2bhosXL6KpqcnWdvr0aSiVSq9OAPQml+bmZiiV9mVMx5jeMdvVX7h1DHD5cos+rONS6Z07d4rS0lKRlpYmAgMDxTfffOPt0Dzqd7/7nTAYDOKjjz4S1dXVtqW5udnbofUJvnpV7CeffCLUarV44YUXxJkzZ0RWVpYICAgQb7/9trdDk53uxqLVq1eLhx9+2Na/41YHK1euFKWlpWLnzp198nYnPc1n7969Qq1Wi23bttmNQQ0NDd5KwcbVXK7X166KdTWfxsZGERkZKX71q1+JU6dOiby8PBEXFyeWLl3qrRRsXM1l9+7dQq1Wi+3bt4uzZ8+Ko0ePioSEBDF58mRvpWDT2NgoiouLRXFxsQAgNm3aJIqLi223bpFyDJBVYSeEENu2bRPR0dHCz89P3HLLLT55iw8ATpfdu3d7O7Q+wVcLOyGE+Otf/yrGjRsntFqtGDVqlHj99de9HZJsdTUWLVq0SMyYMcOu/0cffSQmTZok/Pz8xPDhw0VmZqaHI+6aK/nMmDHD6Ri0aNEizwfuhKv75lp9rbATwvV8ysrKxD333CP8/f1FZGSkSE9P7zN/+Luay5YtW8SYMWOEv7+/CA8PFwsWLBDnz5/3cNSO/vGPf3T5OyDlGKAQop/NVxIRERGRU7I5x46IiIjI17GwIyIiIpIJFnZEREREMsHCjoiIiEgmWNgRERERyQQLOyIiIiKZYGFHREREJBMs7IiIiIhkgoUdERERkUywsCMiIiKSCRZ2RERERDLBwo6IiIhIJv4/Fk7vBc4J+tQAAAAASUVORK5CYII=",
|
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"text/plain": [
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"<Figure size 640x480 with 4 Axes>"
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|
]
|
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},
|
|
"metadata": {},
|
|
"output_type": "display_data"
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}
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],
|
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"source": [
|
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"def load_pointset_series(path: str):\n",
|
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" pointsets = {}\n",
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" for pointset in os.listdir(path):\n",
|
|
" key = float(pointset.replace(\"pointset_\", \"\").replace(\".txt\", \"\"))\n",
|
|
" pointset = load_pointset(os.path.join(path, pointset))\n",
|
|
" pointsets[key] = pointset\n",
|
|
"\n",
|
|
" return pointsets\n",
|
|
"\n",
|
|
"def load_radspec_series(path: str):\n",
|
|
" radspecs = {}\n",
|
|
" for radspec in os.listdir(path):\n",
|
|
" key = float(radspec.replace(\"pointset_\", \"\").replace(\".rdf\", \"\"))\n",
|
|
" radspec = load_radspec(os.path.join(path, radspec))\n",
|
|
" radspecs[key] = radspec\n",
|
|
"\n",
|
|
" return radspecs\n",
|
|
" \n",
|
|
"\n",
|
|
"pcfs = load_utk_rdfseries(\"../result_data/pointset_series/rdffiles/\")\n",
|
|
"pointsets = load_pointset_series(\"../result_data/pointset_series/pointsets/\")\n",
|
|
"radspecs = load_radspec_series(\"../result_data/pointset_series/radspecs/\")\n",
|
|
"\n",
|
|
"keys = sorted(pointsets.keys())\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(2,2)\n",
|
|
"pointplot = ax[0][0].scatter(pointsets[keys[0]][0], pointsets[keys[0]][1], s=0.2)\n",
|
|
"rdfplot = ax[0][1].plot(pcfs[str(keys[0])][0],pcfs[str(keys[0])][1], linewidth=0.2)[0]\n",
|
|
"radspecplot = ax[1][0].plot(radspecs[keys[0]][0], radspecs[keys[0]][1], linewidth=0.2)[0]\n",
|
|
"\n",
|
|
"fig.tight_layout()\n",
|
|
"\n",
|
|
"\n",
|
|
"def update(frame):\n",
|
|
"\n",
|
|
" ax[0][0].clear()\n",
|
|
" pointplot = ax[0][0].scatter(pointsets[keys[frame]][0], pointsets[keys[frame]][1], s=0.2)\n",
|
|
" ax[0][0].set(xlim=[0, 1], ylim=[0.0, 1.0])\n",
|
|
" ax[0][0].set_title(\"cutoff: \" + str(keys[frame]))\n",
|
|
"\n",
|
|
" maxx = float(max(pcfs[str(keys[frame])][0]))\n",
|
|
" maxy = float(max(pcfs[str(keys[frame])][1]))\n",
|
|
" \n",
|
|
" rdfplot.set_xdata(pcfs[str(keys[frame])][0])\n",
|
|
" rdfplot.set_ydata(pcfs[str(keys[frame])][1])\n",
|
|
"\n",
|
|
" ax[0][1].set(xlim=[0, maxx], ylim=[0.0, 1.0e-7])\n",
|
|
" #ax[1].set_xbound(lower=-0.01, upper=maxx) \n",
|
|
" #ax[1].set_ybound(lower=0, upper=maxx)\n",
|
|
"\n",
|
|
" radspecplot.set_xdata(radspecs[keys[frame]][0])\n",
|
|
" radspecplot.set_ydata(radspecs[keys[frame]][1])\n",
|
|
"\n",
|
|
"\n",
|
|
"anim = animation.FuncAnimation(fig=fig, func=update, frames=len(keys), interval=300)\n",
|
|
"anim.save(\"animation_cutoffs_with_radspec.mp4\", dpi=600, writer=\"ffmpeg\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 28,
|
|
"id": "9130e7ed-06ba-40f9-afd5-0506022c4156",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 4 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"from matplotlib import animation\n",
|
|
"\n",
|
|
"\n",
|
|
"def load_gradient(path: str):\n",
|
|
" xs, ys, us, vs, cs = [], [], [], [], []\n",
|
|
" with open(path, 'r') as gradfile:\n",
|
|
" for line in gradfile.readlines():\n",
|
|
" x, y, u, v = line.split(\" \")\n",
|
|
" x = float(x)\n",
|
|
" y = float(y)\n",
|
|
" u = float(u)\n",
|
|
" v = float(v)\n",
|
|
" \n",
|
|
" xs.append(x)\n",
|
|
" ys.append(y)\n",
|
|
" us.append(u)\n",
|
|
" vs.append(v)\n",
|
|
" cs.append(np.hypot(u,v))\n",
|
|
" \n",
|
|
" return (xs, ys, us, vs, cs)\n",
|
|
" \n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(2,2)\n",
|
|
"fig.tight_layout()\n",
|
|
"\n",
|
|
"ax[0][0].set_xlim([-0.1, 1.1])\n",
|
|
"ax[0][0].set_ylim([-0.1, 1.1])\n",
|
|
"ax[1][0].set_xlim([-0.1, 1.1])\n",
|
|
"ax[1][0].set_ylim([-0.1, 1.1])\n",
|
|
"\n",
|
|
"def update(frame):\n",
|
|
" fig.suptitle(f'frame: {str(frame)}')\n",
|
|
"\n",
|
|
" for axis in ax:\n",
|
|
" for a in axis:\n",
|
|
" a.clear()\n",
|
|
" \n",
|
|
" ax[0][0].set_title('no cutoffs')\n",
|
|
"\n",
|
|
" \n",
|
|
" (xs, ys, us, vs, cs) = load_gradient(f'../result_data/gradients_no_cutoff/forces_{str(min(222,frame))}.txt')\n",
|
|
" ax[0][0].quiver(xs, ys, us, vs, cs)\n",
|
|
" ax[0][0].scatter(xs, ys, s=1.0)\n",
|
|
" ax[0][0].set_aspect(1.0)\n",
|
|
"\n",
|
|
" (radspec_x, radspec_y) = load_heck_pcf(f'../result_data/gradients_no_cutoff/pointset_{str(min(222,frame))}_rp.txt')\n",
|
|
" radspec_y = scipy.ndimage.gaussian_filter(radspec_y, 2.0)\n",
|
|
" ax[0][1].plot(radspec_x, radspec_y, linewidth=0.5)\n",
|
|
" ax[0][1].set_ylim([-0.1, 2.0])\n",
|
|
" ax[0][1].set_aspect(57)\n",
|
|
"\n",
|
|
"\n",
|
|
" ax[1][0].set_title('cutoff 0.1')\n",
|
|
" (xs, ys, us, vs, cs) = load_gradient(f'../result_data/gradients_cutoff_0.1/forces_{str(frame)}.txt')\n",
|
|
" ax[1][0].quiver(xs, ys, us, vs, cs)\n",
|
|
" ax[1][0].scatter(xs, ys, s=1.0)\n",
|
|
" ax[1][0].set_aspect(1.0)\n",
|
|
"\n",
|
|
" (radspec_x, radspec_y) = load_heck_pcf(f'../result_data/gradients_cutoff_0.1/pointset_{str(frame)}_rp.txt')\n",
|
|
" radspec_y = scipy.ndimage.gaussian_filter(radspec_y, 2.0)\n",
|
|
" ax[1][1].plot(radspec_x, radspec_y, linewidth=0.5)\n",
|
|
" ax[1][1].set_ylim([-0.1, 2.0])\n",
|
|
" ax[1][1].set_aspect(57)\n",
|
|
" \n",
|
|
"anim = animation.FuncAnimation(fig=fig, func=update, frames=258, interval=200)\n",
|
|
"anim.save(\"animation_gradients_combined.mp4\", dpi=600, writer=\"ffmpeg\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 47,
|
|
"id": "fb39474d-914c-40a0-adee-70d00c953794",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"converting file 222\n",
|
|
"Config file 'psa.cfg' not found. Using defaults.\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"def convert_to_pointset(path: str):\n",
|
|
" xs, ys = [], []\n",
|
|
" with open(path, 'r') as gradfile:\n",
|
|
" for line in gradfile.readlines():\n",
|
|
" x, y, _, _= line.split(\" \")\n",
|
|
" x = float(x)\n",
|
|
" y = float(y)\n",
|
|
"\n",
|
|
" \n",
|
|
" xs.append(x)\n",
|
|
" ys.append(y)\n",
|
|
"\n",
|
|
" with open(path.replace('.txt', '') + '_pointset.txt', 'w') as pointsetfile:\n",
|
|
" for i in range(len(xs)):\n",
|
|
" pointsetfile.write(str(xs[i]) + \" \" + str(ys[i]) + \"\\n\")\n",
|
|
"\n",
|
|
"for i in range(222,223):\n",
|
|
" print(f'converting file {i}')\n",
|
|
" #convert_to_pointset(f'../result_data/gradients_no_cutoff/forces_{i}.txt')\n",
|
|
" os.system('../psa/cmake-build-debug/psa --rp --raw ' + f'../result_data/avggrads_no_cutoff/pointset_{str(i)}.txt')\n",
|
|
" os.system('mv ' + f'./pointset_{str(i)}_rp.txt' + ' ' + f'../result_data/avggrads_no_cutoff/')\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 146,
|
|
"id": "a6e4e026-faee-42e8-b433-525974ebf411",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
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"text/plain": [
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"<Figure size 640x480 with 2 Axes>"
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]
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},
|
|
"metadata": {},
|
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"output_type": "display_data"
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}
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],
|
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"source": [
|
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"def load_histogram(path: str) -> [([float], [float])]:\n",
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" contributions = []\n",
|
|
" with open(path, 'r') as histfile:\n",
|
|
" for line in histfile.readlines():\n",
|
|
" if ' ' in line:\n",
|
|
" dist, force = line.split(' ')\n",
|
|
" contributions[-1][0].append(float(dist))\n",
|
|
" contributions[-1][1].append(float(force))\n",
|
|
" else:\n",
|
|
" contributions.append(([], []))\n",
|
|
" return contributions\n",
|
|
"\n",
|
|
"\n",
|
|
"def fold_histogram(histogram_data: [([float], [float])], nbins: int):\n",
|
|
" binsize = 0.5 / nbins\n",
|
|
" bins = [0.0] * nbins\n",
|
|
" n_contribs = [1] * nbins\n",
|
|
" \n",
|
|
" for point_contrib in histogram_data:\n",
|
|
" for i, dist in enumerate(point_contrib[0]):\n",
|
|
" binidx = math.floor(dist / binsize)\n",
|
|
" bins[binidx] += point_contrib[1][i]\n",
|
|
" n_contribs[binidx] += 1\n",
|
|
"\n",
|
|
" for i in range(len(bins)):\n",
|
|
" bins[i] = bins[i] / float(n_contribs[i])\n",
|
|
" \n",
|
|
" return bins\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(1,2)\n",
|
|
"\n",
|
|
"DATAPATH = \"../result_data/avggrads_cutoff_0.3\"\n",
|
|
"\n",
|
|
"def update(frame):\n",
|
|
" hist = load_histogram(f'{DATAPATH}/contribution_histogram{frame}.hst')\n",
|
|
" #pts = load_pointset(f'{DATAPATH}/pointset_{frame}.txt')\n",
|
|
" #rps = load_heck_pcf(f'{DATAPATH}/pointset_{frame}_rp.txt')\n",
|
|
" \n",
|
|
" # ax[0].clear()\n",
|
|
" # ax[0].scatter(pts[0], pts[1], s=0.5)\n",
|
|
" # ax[0].set_aspect(1.0)\n",
|
|
"\n",
|
|
" # ax[1].clear()\n",
|
|
" # rps_y = scipy.ndimage.gaussian_filter(rps[1], 2.0)\n",
|
|
" # ax[1].plot(rps[0], rps_y, linewidth = 0.5)\n",
|
|
" # ax[1].set_ylim([-0.1, 2.5])\n",
|
|
" # ax[1].set_aspect(48)\n",
|
|
" \n",
|
|
" nbins = 100\n",
|
|
" bins = fold_histogram(hist, nbins)\n",
|
|
"\n",
|
|
" ax.plot([(0.5 / nbins) * i for i in range(nbins)], bins, linestyle = \"-\", marker = 'o', markersize=1.5)\n",
|
|
"\n",
|
|
"\n",
|
|
"hist_0 = load_histogram(f'{DATAPATH}/contribution_histogram0.hst')\n",
|
|
"hist_222 = load_histogram(f'{DATAPATH}/contribution_histogram222.hst')\n",
|
|
"\n",
|
|
"nbins = 100\n",
|
|
"bins_0 = fold_histogram(hist_0, nbins)\n",
|
|
"bins_222 = fold_histogram(hist_222, nbins)\n",
|
|
"\n",
|
|
"ax[0].plot([(0.5 / nbins) * i for i in range(nbins)], bins_0, linestyle = \"-\", marker = 'o', markersize=1.5, linewidth=0.8)\n",
|
|
"ax[1].plot([(0.5 / nbins) * i for i in range(nbins)], bins_222, linestyle = \"-\", marker = 'o', markersize=1.5, linewidth=0.8)\n",
|
|
"\n",
|
|
"ax[0].set_aspect(100)\n",
|
|
"ax[1].set_aspect(15000)\n",
|
|
"\n",
|
|
"ax[0].set_xticks([0.0, 0.3, 0.5])\n",
|
|
"ax[1].set_xticks([0.0, 0.3, 0.5])\n",
|
|
"\n",
|
|
"#fig.tight_layout()\n",
|
|
"\n",
|
|
"plt.savefig(\"/home/clara/repositorys/bachelor-thesis/thesis/media/avggrads_both_cutoff_0.3.png\", dpi=600, bbox_inches='tight')\n",
|
|
"\n",
|
|
"#anim = animation.FuncAnimation(fig=fig, func=update, frames=222, interval=400)\n",
|
|
"#anim.save(\"with_average_forces_no_cutoff_allforces.mp4\", dpi=300, writer=\"ffmpeg\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 23,
|
|
"id": "5cd7055b-cc7c-4027-be82-180370081145",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x7f5aadbac290>]"
|
|
]
|
|
},
|
|
"execution_count": 23,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": 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De5fmyL17H3/byaUhIiJqWlhYrISjwg7Lxj9YGtrwnxzsP5cvcSIiIqLGw8JiRUI7tsIr/TsAAGYnnoD2HpeGiIioaWBhsTLvDPODT2tH3NDpseiH01LHISIiahQsLFammYMcyycEQSYAW3/LRfKZG1JHIiIiMjsWFisU4u2M1yI6AgDmbD2JO8WlEiciIiIyLxYWK/XW0K7o0rYFCor0WLCDS0NERGTbWFislNL+wdKQXCbg+4zr2HVSI3UkIiIis2FhsWJBXi3xP091AgDM33YKBUV6iRMRERGZBwuLlXtzcBf4uTnhdnEp5iWdhI18lyUREZERFhYr52Anw4qJQbCTCdhz+gZ2ZFyXOhIREVGDY2GxAQEeavz1mS4AgAXbTyNfVyJxIiIioobFwmIj/ndQJ3Rvp4L2fhnmbOXSEBER2RYWFhthL5dhxYSecJDL8O+z+dhy/JrUkYiIiBoMC4sN8XVzwvShD5aGFn9/BhrtfYkTERERNQwWFhvzekRH9PRqiUJ9Od7ZcoJLQ0REZBNYWGyMnVyG5ROCoLCT4VBWARJ+zZE6EhERUb2xsNigzm1b4O1hvgCAv+08g5zb9yROREREVD8sLDbqlf4+6NPBGcWlFXhnywlUVnJpiIiIrBcLi42SywQsGx+EZvZypF66hX/9clXqSERERHXGwmLDOrR2xOwRfgCAD3afxZWCYokTERER1Q0Li42L7ueNsI6tcL+sAm9vyUAFl4aIiMgKsbDYOJlMwIfjA+HoIMd/rtzB+sOXpY5ERERkMhaWJsDLpTnmjfIHACzbcw4XbxZJnIiIiMg0LCxNxB/7eiGiS2voyysxY1MGyisqpY5ERERUaywsTYQgCIgbFwgnhR3Sc+7iy0NcGiIiIuvBwtKEeLRshgVjHiwNfZR8HufyCiVOREREVDssLE3M+BBPDPZri9KKSszYnI4yLg0REZEVMLmwpKSkYMyYMfDw8IAgCNi2bVuN4w8cOABBEKpsZ8+eNRqXmJgIf39/KBQK+Pv7IykpydRoVAuCICD2+R5QN7PHqVwdPjtwUepIRERET2RyYSkuLkZQUBBWr15t0vPOnTsHjUZj2Lp06WL4WWpqKqKiohAdHY2MjAxER0dj4sSJOHr0qKnxqBbaqpRY/GwAAGDVv7Nw+rpW4kREREQ1E0RRrPMniQmCgKSkJIwdO7baMQcOHMCgQYNw584dtGzZ8rFjoqKioNPpsHv3bsO+4cOHw9nZGQkJCbXKotPpoFarodVqoVKpTJlGkySKIqZ8cxx7Tt+An5sTdrwxAA52XCEkIqLGVdvf3432Gyo4OBju7u4YPHgw9u/fb/Sz1NRUREZGGu0bNmwYjhw5Uu3x9Ho9dDqd0Ua1JwgC/vZcD7g4OuBsXiE++SlL6khERETVMnthcXd3xxdffIHExERs3boVvr6+GDx4MFJSUgxj8vLy4OrqavQ8V1dX5OXlVXvc2NhYqNVqw+bl5WW2Odiq1i0UWPJsdwDAmgMXkZFzV9pARERE1TB7YfH19cVrr72GXr16ISwsDGvWrMGoUaOwfPlyo3GCIBg9FkWxyr7fmzNnDrRarWHLyckxS35bNyrQHaMD3VFRKWLm5gyUlFVIHYmIiKgKSd600K9fP2Rl/d8ShJubW5W7Kfn5+VXuuvyeQqGASqUy2qhuljzbHa1bKJCVX4SP9p2XOg4REVEVkhSWtLQ0uLu7Gx6HhYUhOTnZaMzevXsRHh7e2NGaJGdHByx97sHS0Jcpl3D86h2JExERERmzM/UJRUVFuHDhguHx5cuXkZ6eDhcXF7Rv3x5z5sxBbm4uvv76awDAypUr0aFDBwQEBKC0tBTffPMNEhMTkZiYaDjGtGnTMHDgQMTFxeHZZ5/F9u3bsW/fPvz8888NMEWqjcgANzwf3A5b03Ixc3MGdr0ZgWYOcqljERERAajDHZZjx44hODgYwcHBAICYmBgEBwdjwYIFAACNRoPs7GzD+NLSUsycOROBgYGIiIjAzz//jJ07d+L55583jAkPD8eGDRuwfv16BAYGIj4+Hhs3bkRoaGh950cmeG9MAFxVClwuKMayPeekjkNERGRQr89hsST8HJaGsf9cPl5Z/x8IArDhtX4I7dhK6khERGTDLO5zWMg6DPJti6jeXhBF4O0tJ1CsL5c6EhEREQsLVTV/dDd4qJXIvn0PH+w+++QnEBERmRkLC1XhpLTHh+ODAAD/+uUqDl8okDgRERE1dSws9FgDurTGi/3aAwDe2XIChSVlEiciIqKmjIWFqjVnRDd4uTRD7t37+NvOTKnjEBFRE8bCQtVyVNhh2X+Xhjb8JwcHzuVLnIiIiJoqFhaqUb+OrfBK/w4AgNmJJ6G9z6UhIiJqfCws9ETvDPODT2tH5OlKsOj701LHISKiJoiFhZ6omYMcyycEQiYAW3/LRfKZG1JHIiKiJoaFhWolxNsFr0V0BADM2XoSd4pLJU5ERERNCQsL1dpbQ7uic9sWKCjSY8EOLg0REVHjYWGhWlPay7FiQhDkMgHfZ1zHrpMaqSMREVETwcJCJgnyaon/eaoTAGD+tlMoKNJLnIiIiJoCFhYy2V8Hd4afmxNuF5diftIp2MgXfhMRkQVjYSGTKezkWDExCHYyAT+ezsOOjOtSRyIiIhvHwkJ1EuChxl+f6QIAWLD9NPJ1JRInIiIiW8bCQnX2v4M6oXs7FbT3yzA36SSXhoiIyGxYWKjO7OUyrJjQEw5yGfZl5iPxt1ypIxERkY1iYaF68XVzwvShD5aGFn1/GhrtfYkTERGRLWJhoXp7PaIjgrxaorCkHLMSuTREREQNj4WF6s1OLsOKCUFwsJMh5fxNbPhPjtSRiIjIxrCwUIPo3LYF3o70BQC8/8MZ5Ny+J3EiIiKyJSws1GD+3wAf9PZ2RnFpBWYlnkBlJZeGiIioYbCwUIORywQsnxAEpb0MRy7ewjdHr0odiYiIbAQLCzWoDq0dMXu4HwAgdtdZXCkoljgRERHZAhYWanCTwjogrGMr3C+rwNtbMrg0RERE9cbCQg1OJhPw4fhAODrI8Z8rd7Du8GWpIxERkZVjYSGz8HJpjrmjugEAlu05h4s3iyRORERE1oyFhczmT33bI6JLa+jLKzFzcwYquDRERER1xMJCZiMIAuLGBcJJYYe07Lv4IuWS1JGIiMhKsbCQWXm0bIZ3x/gDAD5KPo/zNwolTkRERNbI5MKSkpKCMWPGwMPDA4IgYNu2bTWO37p1K4YOHYo2bdpApVIhLCwMe/bsMRoTHx8PQRCqbCUlJabGIws0IcQTz/i1RWlFJWZsykBZRaXUkYiIyMqYXFiKi4sRFBSE1atX12p8SkoKhg4dil27duH48eMYNGgQxowZg7S0NKNxKpUKGo3GaFMqlabGIwskCAJin+8BdTN7nMzV4rMDF6WOREREVsbO1CeMGDECI0aMqPX4lStXGj1eunQptm/fju+//x7BwcGG/YIgwM3NzdQ4ZCVcVUos+kMApm9Mx6p/Z2Fwt7YI8FBLHYuIiKxEo7+HpbKyEoWFhXBxcTHaX1RUBG9vb3h6emL06NFV7sA8Sq/XQ6fTGW1k2Z7t6YFhAa4orxQxY1MGSsu5NERERLXT6IVlxYoVKC4uxsSJEw37/Pz8EB8fjx07diAhIQFKpRL9+/dHVlZWtceJjY2FWq02bF5eXo0Rn+pBEAS8P7YHnJvb42xeIT75qfrXl4iI6PcEURTr/OEYgiAgKSkJY8eOrdX4hIQEvPrqq9i+fTuGDBlS7bjKykr06tULAwcOxKpVqx47Rq/XQ6/XGx7rdDp4eXlBq9VCpVKZNA9qXDtPaDD1u98glwlI+t9wBHq2lDoSERFJRKfTQa1WP/H3d6PdYdm4cSMmT56MTZs21VhWAEAmk6FPnz413mFRKBRQqVRGG1mHUYHuGB3ojor/Lg2VlFVIHYmIiCxcoxSWhIQEvPzyy/juu+8watSoJ44XRRHp6elwd3dvhHQkhcXPdkfrFg7Iyi/Cyn1cGiIiopqZXFiKioqQnp6O9PR0AMDly5eRnp6O7OxsAMCcOXMwadIkw/iEhARMmjQJK1asQL9+/ZCXl4e8vDxotVrDmEWLFmHPnj24dOkS0tPTMXnyZKSnp2PKlCn1nB5ZKhdHByx9rgcA4IuUi/gt+47EiYiIyJKZXFiOHTuG4OBgw58kx8TEIDg4GAsWLAAAaDQaQ3kBgH/84x8oLy/H1KlT4e7ubtimTZtmGHP37l28/vrr6NatGyIjI5Gbm4uUlBT07du3vvMjCxYZ4Ibng9uhUgRmbsrA/VIuDRER0ePV6023lqS2b9ohy6K9V4bIlQdxQ6fH5AE+eHe0v9SRiIioEVncm26JHkfd3B4fjAsEAKw7fBm/Xr4tcSIiIrJELCwkuUG+bRHV2wuiCMzcnIFifbnUkYiIyMKwsJBFmDe6GzzUSmTfvoe4H89KHYeIiCwMCwtZBJXSHh+ODwIAfJ16FYcvFEiciIiILAkLC1mMAV1a48+h7QEA72w5gcKSMokTERGRpWBhIYsyd2Q3eLk0Q+7d+1i6K1PqOEREZCFYWMiiOCrssOy/S0MJv+bgwLl8iRMREZElYGEhi9OvYyu8HN4BADA78SS097k0RETU1LGwkEWaNdwPPq0dkacrweLvz0gdh4iIJMbCQhapmYMcyycEQhCAxN+uIfnMDakjERGRhFhYyGKFeLvgtYiOAIC5SSdxp7hU4kRERCQVFhayaDFDu6Jz2xa4WajHeztOSx2HiIgkwsJCFk1pL8eKCUGQywTsyLiO3Sc1UkciIiIJsLCQxQvyaokpTz1YGpq37RQKivQSJyIiosbGwkJW4c3BXeDn5oTbxaV4d9spiKIodSQiImpELCxkFRR2ciyfEAQ7mYDdp/KwI+O61JGIiKgRsbCQ1ejeTo03nukMAFiw/TTydSUSJyIiosbCwkJWZeqgzgjwUEF7vwxzk05yaYiIqIlgYSGrYi+XYcXEINjLBezLzMfW33KljkRERI2AhYWsjp+bCtOHdAUALPz+NDTa+xInIiIic2NhIav0l4EdEeTVEoUl5ZiVyKUhIiJbx8JCVslOLsOKCYFwsJMh5fxNbPxPjtSRiIjIjFhYyGp1buuEtyN9AQDv78zEtTv3JE5ERETmwsJCVu3/DfBBb29nFOnL8c6WE6is5NIQEZEtYmEhqyaXCVg2IQhKexmOXLyFb49elToSERGZAQsLWT2f1o6YPdwPALB011lcvVUscSIiImpoLCxkEyaFdUC/ji64X1aBtzdzaYiIyNawsJBNkMkELBsfBEcHOX69chvrj1yROhIRETUgFhayGV4uzTF3VDcAwIc/nsXFm0USJyIioobCwkI25U992yOiS2voyysxc3MGKrg0RERkE1hYyKYIgoC4cYFwUtghLfsuvjx0SepIRETUAEwuLCkpKRgzZgw8PDwgCAK2bdv2xOccPHgQISEhUCqV6NixIz7//PMqYxITE+Hv7w+FQgF/f38kJSWZGo0IAODRshneHeMPAPj73vM4f6NQ4kRERFRfJheW4uJiBAUFYfXq1bUaf/nyZYwcORIRERFIS0vD3Llz8eabbyIxMdEwJjU1FVFRUYiOjkZGRgaio6MxceJEHD161NR4RACACSGeGOTbBqUVlZixKQNlFZVSRyIionoQxHp8a5wgCEhKSsLYsWOrHTNr1izs2LEDmZmZhn1TpkxBRkYGUlNTAQBRUVHQ6XTYvXu3Yczw4cPh7OyMhISEWmXR6XRQq9XQarVQqVR1mxDZlBu6EkR+lALt/TLMGNoVfx3cRepIRET0iNr+/jb7e1hSU1MRGRlptG/YsGE4duwYysrKahxz5MiRao+r1+uh0+mMNqLfc1UpsegPAQCAVT9l4cx1/jdCRGStzF5Y8vLy4OrqarTP1dUV5eXlKCgoqHFMXl5etceNjY2FWq02bF5eXg0fnqzesz09EOnvirIKETM2Z6C0nEtDRETWqFH+SkgQBKPHD1ehfr//cWMe3fd7c+bMgVarNWw5OTkNmJhshSAI+NtzPeDc3B6ZGh1W/5QldSQiIqoDsxcWNze3KndK8vPzYWdnh1atWtU45tG7Lr+nUCigUqmMNqLHaeOkwPtjewAAPj1wESeu3ZU2EBERmczshSUsLAzJyclG+/bu3YvevXvD3t6+xjHh4eHmjkdNxKhAd4wKdEdFpYgZmzKgL6+QOhIREZnA5MJSVFSE9PR0pKenA3jwZ8vp6enIzs4G8GCpZtKkSYbxU6ZMwdWrVxETE4PMzEysW7cOa9euxcyZMw1jpk2bhr179yIuLg5nz55FXFwc9u3bh+nTp9dvdkS/s+TZ7mjdwgFZ+UX4KJlLQ0RE1sTkwnLs2DEEBwcjODgYABATE4Pg4GAsWLAAAKDRaAzlBQB8fHywa9cuHDhwAD179sSSJUuwatUqjBs3zjAmPDwcGzZswPr16xEYGIj4+Hhs3LgRoaGh9Z0fkYGLowP+9tyDpaEvUi7it+w7EiciIqLaqtfnsFgSfg4L1dZbG9ORlJaLjm0csevNCCjt5VJHIiJqsizmc1iILM3CMQFo66TApZvFWLbnnNRxiIioFlhYqMlRN7dH3LhAAMC6w5fx6+XbEiciIqInYWGhJmmQX1tM7O0JUQTe3pKBe6XlUkciIqIasLBQkzV/tD881EpcvXUPH+w+K3UcIiKqAQsLNVkqpT3ixj9YGvo69SqOXCiQOBEREVWHhYWatIgubfDn0PYAgLe3nEBhSZnEiYiI6HFYWKjJmzuyGzydmyH37n0s3ZUpdRwiInoMFhZq8hwVdlg2PggAkPBrDg6evylxIiIiehQLCxGAsE6t8HJ4BwDArC0noL3PpSEiIkvCwkL0X+8M90WHVs2RpyvBkh/OSB2HiIh+h4WF6L+aO9hh+YQgCAKw5fg1/DvzhtSRiIjov1hYiH6ndwcXvBbREQAwe+tJ3CkulTgREREBLCxEVcQM7YpObRxxs1CPhd+fljoOERGBhYWoCqW9HCsm9oRMALanX8ePpzRSRyIiavJYWIgeo6dXS/zP050AAPOSTuFWkV7iRERETRsLC1E13hzcBX5uTrhVXIr5205BFEWpIxERNVksLETVUNjJsXxCEOxkAnafysP3J7g0REQkFRYWohp0b6fGG890BgAs2H4K+YUlEiciImqaWFiInmDqoM4I8FDh7r0yzN16kktDREQSYGEhegJ7uQwrJgbBXi5gX2Y+tv6WK3UkIqImh4WFqBb83FSYPqQrAGDh96eRp+XSEBFRY2JhIaqlvwzsiCCvligsKcesxBNcGiIiakQsLES1ZCeXYcWEQDjYyXDw/E1s/E+O1JGIiJoMFhYiE3Ru64SZkQ+Wht7fmYlrd+5JnIiIqGlgYSEy0eQBHdHb2xlF+gdLQ5WVXBoiIjI3FhYiE8llApZNCILSXobDF27h26NXpY5ERGTzWFiI6sCntSNmDfcDACzddRbZt7g0RERkTiwsRHX0UlgH9OvogvtlFZi5JYNLQ0REZsTCQlRHMpmAZeOD0NxBjl8v38b6I1ekjkREZLNYWIjqwculOeaO7AYA+PDHs7h0s0jiREREtomFhaie/hzaHhFdWkNfXomZmzNQwaUhIqIGV6fCsmbNGvj4+ECpVCIkJASHDh2qduzLL78MQRCqbAEBAYYx8fHxjx1TUsKPPyfLJwgC4sYFwklhh9+y7+Kfhy5JHYmIyOaYXFg2btyI6dOnY968eUhLS0NERARGjBiB7Ozsx47/+OOPodFoDFtOTg5cXFwwYcIEo3EqlcponEajgVKprNusiBqZR8tmeHe0PwBgRfJ5ZN0olDgREZFtMbmw/P3vf8fkyZPx6quvolu3bli5ciW8vLzw2WefPXa8Wq2Gm5ubYTt27Bju3LmDV155xWicIAhG49zc3Oo2IyKJTOjtiUG+bVBaXokZmzNQXlEpdSQiIpthUmEpLS3F8ePHERkZabQ/MjISR44cqdUx1q5diyFDhsDb29tof1FREby9veHp6YnRo0cjLS2txuPo9XrodDqjjUhKgiDgg3GBUCntcOKaFp8fvCh1JCIim2FSYSkoKEBFRQVcXV2N9ru6uiIvL++Jz9doNNi9ezdeffVVo/1+fn6Ij4/Hjh07kJCQAKVSif79+yMrK6vaY8XGxkKtVhs2Ly8vU6ZCZBauKiUWPfvg/Vkf/zsLZ66zSBMRNYQ6velWEASjx6IoVtn3OPHx8WjZsiXGjh1rtL9fv3548cUXERQUhIiICGzatAldu3bFJ598Uu2x5syZA61Wa9hycvjNuWQZxvZsh0h/V5RViJixOQOl5VwaIiKqL5MKS+vWrSGXy6vcTcnPz69y1+VRoihi3bp1iI6OhoODQ82hZDL06dOnxjssCoUCKpXKaCOyBIIg4G/P9YBzc3tkanRYvf+C1JGIiKyeSYXFwcEBISEhSE5ONtqfnJyM8PDwGp978OBBXLhwAZMnT37ieURRRHp6Otzd3U2JR2Qx2jgpsGRsdwDAp/sv4OQ1rcSJiIism8lLQjExMfjnP/+JdevWITMzE2+99Rays7MxZcoUAA+WaiZNmlTleWvXrkVoaCi6d+9e5WeLFi3Cnj17cOnSJaSnp2Py5MlIT083HJPIGo0O9MCoQHdUVIqYsTkd+vIKqSMREVktO1OfEBUVhVu3bmHx4sXQaDTo3r07du3aZfirH41GU+UzWbRaLRITE/Hxxx8/9ph3797F66+/jry8PKjVagQHByMlJQV9+/atw5SILMeSZ7vj6KVbOH+jCCv3ZRm+4ZmIiEwjiKJoE58jrtPpoFarodVq+X4Wsih7TufhL/86DpkAbPmfcPRq7yx1JCIii1Hb39/8LiEiMxsW4IbngtuhUgRmbs5ASRmXhoiITMXCQtQIFo4JQFsnBS7dLMbyPeekjkNEZHVYWIgagbq5PeLGBQIA1h6+jF8v35Y4ERGRdWFhIWokg/zaYmJvT4gi8PaWDNwrLZc6EhGR1WBhIWpE80f7w0OtxNVb9xC3+6zUcYiIrAYLC1EjUintETf+wdLQV6lXceRCgcSJiIisAwsLUSOL6NIGfwptDwB4e8sJFOm5NERE9CQsLEQSmDuyGzydmyH37n38bWem1HGIiCweCwuRBFoo7LBsfBAAIOHXbBw8f1PiRERElo2FhUgiYZ1a4eXwDgCAWVtOQHu/TNpAREQWjIWFSELvDPdFh1bNkacrwZIfzkgdh4jIYrGwEEmouYMdlk8IgiAAW45fw78zb0gdiYjIIrGwEEmsdwcXvDrABwAwe+tJ3L1XKnEiIiLLw8JCZAFmRPqiUxtH3CzU470dp6WOQ0RkcVhYiCyA0l6OFRN7QiYA29Ov48dTGqkjERFZFBYWIgvR06slpjzVCQAwL+kUbhXpJU5ERGQ5WFiILMi0IV3g6+qEW8WleHf7KYiiKHUkIiKLwMJCZEEUdnKsmBgEO5mAXSfz8MMJLg0REQEsLEQWp3s7NaYO6gwAeHf7KeQXlkiciIhIeiwsRBbojWc6w99dhbv3yjB3K5eGiIhYWIgskL1chr9HBcFeLmBf5g0kpeVKHYmISFIsLEQWys9NhelDugIA3ttxGnlaLg0RUdPFwkJkwf4ysCOCPNUoLCnHrMQTXBoioiaLhYXIgtnJZVgxMQgOdjIcPH8Tm47lSB2JiEgSLCxEFq5zWyfMjHywNLTkh0xcu3NP4kRERI2PhYXICkwe0BEh3s4o0nNpiIiaJhYWIisglwlYPiEISnsZDl+4hW+OZksdiYioUbGwEFkJn9aOmDXcDwAQuysT2be4NERETQcLC5EVeSmsA0J9XHCvtAIzt2SgspJLQ0TUNLCwEFkRmUzAsvFBaO4gx6+XbyP+yBWpIxERNQoWFiIr075Vc8wd2Q0A8OGes7h0s0jiRERE5lenwrJmzRr4+PhAqVQiJCQEhw4dqnbsgQMHIAhCle3s2bNG4xITE+Hv7w+FQgF/f38kJSXVJRpRk/Dn0PYY0Lk1SsoqMXNzBiq4NERENs7kwrJx40ZMnz4d8+bNQ1paGiIiIjBixAhkZ9f8Vwvnzp2DRqMxbF26dDH8LDU1FVFRUYiOjkZGRgaio6MxceJEHD161PQZETUBgiAgbnwgnBR2+C37Lv556JLUkYiIzEoQTfxAh9DQUPTq1QufffaZYV+3bt0wduxYxMbGVhl/4MABDBo0CHfu3EHLli0fe8yoqCjodDrs3r3bsG/48OFwdnZGQkJCrXLpdDqo1WpotVqoVCpTpkRktTb9JwfvJJ6Ag50MO/86AF1cnaSORERkktr+/jbpDktpaSmOHz+OyMhIo/2RkZE4cuRIjc8NDg6Gu7s7Bg8ejP379xv9LDU1tcoxhw0bVuMx9Xo9dDqd0UbU1Ezo7YlBvm1QWl6JGZszUF5RKXUkIiKzMKmwFBQUoKKiAq6urkb7XV1dkZeX99jnuLu744svvkBiYiK2bt0KX19fDB48GCkpKYYxeXl5Jh0TAGJjY6FWqw2bl5eXKVMhsgmCIOCDcYFQKe1w4poWnx+8KHUkIiKzqNObbgVBMHosimKVfQ/5+vritddeQ69evRAWFoY1a9Zg1KhRWL58eZ2PCQBz5syBVqs1bDk5/FI4appcVUosejYAAPDxv7OQqeHdRiKyPSYVltatW0Mul1e585Gfn1/lDklN+vXrh6ysLMNjNzc3k4+pUCigUqmMNqKmamzPdhjq74qyChEzNmWgtJxLQ0RkW0wqLA4ODggJCUFycrLR/uTkZISHh9f6OGlpaXB3dzc8DgsLq3LMvXv3mnRMoqZMEAQsfa4HnJvb44xGh9X7L0gdiYioQdmZ+oSYmBhER0ejd+/eCAsLwxdffIHs7GxMmTIFwIOlmtzcXHz99dcAgJUrV6JDhw4ICAhAaWkpvvnmGyQmJiIxMdFwzGnTpmHgwIGIi4vDs88+i+3bt2Pfvn34+eefG2iaRLavjZMCS8Z2xxvfpeHT/RcQ6e+K7u3UUsciImoQJheWqKgo3Lp1C4sXL4ZGo0H37t2xa9cueHt7AwA0Go3RZ7KUlpZi5syZyM3NRbNmzRAQEICdO3di5MiRhjHh4eHYsGED5s+fj3fffRedOnXCxo0bERoa2gBTJGo6Rgd6YPfJPOw8qUHMpnR8/9cBUNjJpY5FRFRvJn8Oi6Xi57AQPXC7uBSRHx1EQVEp/ufpToZveCYiskRm+RwWIrJ8Lo4OeH9sDwDAPw5eRFr2HYkTERHVHwsLkQ0a3t0NY3t6oFIEZmzOQElZhdSRiIjqhYWFyEYt/EMA2jopcOlmMZbvOSd1HCKiemFhIbJRLZs74INxD5aG1h6+jP9cuS1xIiKiumNhIbJhz/i5YkKIJ0QRmLk5A/dKy6WORERUJywsRDbu3TH+cFcrcfXWPXz4I5eGiMg6sbAQ2TiV0h5x4wIBAPFHruDIxQKJExERmY6FhagJGNi1Df4U2h4A8M6WEyjSc2mIiKwLCwtREzF3ZDd4OjfDtTv3sXRXptRxiIhMwsJC1ES0UNjhw/EPloa+O5qNlPM3JU5ERFR7LCxETUh4p9Z4ObwDAGBW4glo75dJG4iIqJZYWIiamHeG+6JDq+bQaEvw/g9npI5DRFQrLCxETUxzBzssnxAEQQA2H7+Gf2fekDoSEdETsbAQNUG9O7jg1QE+AIDZW0/i7r1SiRMREdWMhYWoiZoR6YtObRxxs1CPhTtOSx2HiKhGLCxETZTSXo7lE4IgE4Bt6dfx46k8qSMREVWLhYWoCQtu74wpT3UCAMxLOolbRXqJExERPR4LC1ETN21IF/i6OuFWcSkWbOfSEBFZJhYWoiZOYSfHiolBsJMJ2HlSg+8zrksdiYioChYWIkL3dmpMHdQZAPDu9lPILyyROBERkTEWFiICAEwd1Bn+7ircvVeGeUmnIIqi1JGIiAxYWIgIAOBgJ8Pfo4JgLxeQfOYGktJypY5ERGTAwkJEBn5uKkwf0hUAsHDHaeRpuTRERJaBhYWIjPxlYEcEeaqhKynH7K0nuDRERBaBhYWIjNjJZVg+IQgOdjIcOHcTm47lSB2JiIiFhYiq6uLqhBlDHywNLfkhE7l370uciIiaOhYWInqsVyM6IsTbGUX6cszawqUhIpIWCwsRPZZcJmDZ+EAo7WX4+UIBvj2aLXUkImrCWFiIqFod27TAO8P8AABLd2Ui+9Y9iRMRUVPFwkJENXo5vANCfVxwr7QCb2/JQGUll4aIqPGxsBBRjWQyAcvGB6G5gxxHL9/GV6lXpI5ERE1QnQrLmjVr4OPjA6VSiZCQEBw6dKjasVu3bsXQoUPRpk0bqFQqhIWFYc+ePUZj4uPjIQhCla2khB9aRWQJ2rdqjjkjuwEA4n48i0s3iyRORERNjcmFZePGjZg+fTrmzZuHtLQ0REREYMSIEcjOfvwb8lJSUjB06FDs2rULx48fx6BBgzBmzBikpaUZjVOpVNBoNEabUqms26yIqMG9GNoeAzq3RklZJWZuzkAFl4aIqBEJool/qxgaGopevXrhs88+M+zr1q0bxo4di9jY2FodIyAgAFFRUViwYAGAB3dYpk+fjrt375oSxYhOp4NarYZWq4VKparzcYioerl372PYRyko0pdj7kg/vD6wk9SRiMjK1fb3t0l3WEpLS3H8+HFERkYa7Y+MjMSRI0dqdYzKykoUFhbCxcXFaH9RURG8vb3h6emJ0aNHV7kD8yi9Xg+dTme0EZF5tWvZDO+OfrA0tHzveWTdKJQ4ERE1FSYVloKCAlRUVMDV1dVov6urK/Ly8mp1jBUrVqC4uBgTJ0407PPz80N8fDx27NiBhIQEKJVK9O/fH1lZWdUeJzY2Fmq12rB5eXmZMhUiqqOJvb0wyLcNSssfLA2VV1RKHYmImoA6velWEASjx6IoVtn3OAkJCVi4cCE2btyItm3bGvb369cPL774IoKCghAREYFNmzaha9eu+OSTT6o91pw5c6DVag1bTg6/74SoMQiCgNjnA6FS2iHjmhb/SLkkdSQiagJMKiytW7eGXC6vcjclPz+/yl2XR23cuBGTJ0/Gpk2bMGTIkJpDyWTo06dPjXdYFAoFVCqV0UZEjcNNrcTCPwQAAFbuO49MDZdkici8TCosDg4OCAkJQXJystH+5ORkhIeHV/u8hIQEvPzyy/juu+8watSoJ55HFEWkp6fD3d3dlHhE1IieC26Hof6uKKsQMWNTBsq4NEREZmTyklBMTAz++c9/Yt26dcjMzMRbb72F7OxsTJkyBcCDpZpJkyYZxickJGDSpElYsWIF+vXrh7y8POTl5UGr1RrGLFq0CHv27MGlS5eQnp6OyZMnIz093XBMIrI8giDgb891R8vm9jij0WH1TxekjkRENszkwhIVFYWVK1di8eLF6NmzJ1JSUrBr1y54e3sDADQajdFnsvzjH/9AeXk5pk6dCnd3d8M2bdo0w5i7d+/i9ddfR7du3RAZGYnc3FykpKSgb9++DTBFIjKXtk5KLHm2OwDg0/0XcCpX+4RnEBHVjcmfw2Kp+DksRNKZ+u1v2HlSA19XJ+z4a38o7ORSRyIiK2GWz2EhInqcxc8GoJWjA87dKMTH+6p/szwRUV2xsBBRvbVqocDfnusBAPj84EWkZd+ROBER2RoWFiJqEMO7u2FsTw9UisDMzRkoKauQOhIR2RAWFiJqMAv/EIC2TgpcvFmMFXvPSR2HiGwICwsRNZiWzR3wwbgHS0P//Pky/nPltsSJiMhWsLAQUYN6xs8VE0I8IYrA25szcK+0XOpIRGQDWFiIqMG9O8Yf7molrty6hw9/5NIQEdUfCwsRNTiV0h5x4wIBAPFHriD14i2JExGRtWNhISKzGNi1Df7Ytz0A4O0tGSjSc2mIiOqOhYWIzGbeqG7wdG6Ga3fuY+muTKnjEJEVY2EhIrNpobDDh+MfLA19dzQbKedvSpyIiKwVCwsRmVV4p9Z4KezBl6POSjwBXUmZxImIyBqxsBCR2c0a4YcOrZpDoy3Bku/PSB2HiKwQCwsRmV1zBzssmxAEQQA2H7+Gn87ekDoSEVkZFhYiahR9Orhgcn8fAMDsxJO4e69U4kREZE1YWIio0cwc5otObRyRX6jHwh2npY5DRFaEhYWIGo3SXo7lE4IgE4Bt6dfx46k8qSMRkZVgYSGiRhXc3hl/eaoTAGD+tpO4XcylISJ6MhYWImp004d0ga+rEwqKSvHu9lNSxyEiK8DCQkSNTmEnx4qJQZDLBOw8ocEPJ65LHYmILBwLCxFJons7NaYO6gwAeHfbKdws1EuciIgsGQsLEUnmjUGd4e+uwp17ZZibdBKiKEodiYgsFAsLEUnGwU6GFRODYC8XkHzmBral50odiYgsFAsLEUmqm7sK0wZ3AQC8t/008rQlEiciIkvEwkJEkpvyVCcEeqqhKynHnK0nuDRERFWwsBCR5OzkMqyYEAQHOxn2n7uJzceuSR2JiCwMCwsRWYQurk6YMbQrAGDxD2eQe/e+xImIyJKwsBCRxXg1oiN6tW+JIn05Zm3h0hAR/R8WFiKyGHKZgOUTgqC0l+HnCwX49mi21JGIyEKwsBCRRenYpgXeGeYHAFi6KxM5t+9JnIiILAELCxFZnJfDO6CvjwvulVZg5uYMVFZyaYioqatTYVmzZg18fHygVCoREhKCQ4cO1Tj+4MGDCAkJgVKpRMeOHfH5559XGZOYmAh/f38oFAr4+/sjKSmpLtGIyAbIZAKWjw9Ccwc5jl6+ja9Sr0gdiYgkZnJh2bhxI6ZPn4558+YhLS0NERERGDFiBLKzH7/WfPnyZYwcORIRERFIS0vD3Llz8eabbyIxMdEwJjU1FVFRUYiOjkZGRgaio6MxceJEHD16tO4zIyKr1r5Vc8wZ2Q0AEPfjWVwuKJY4ERFJSRBNfBt+aGgoevXqhc8++8ywr1u3bhg7dixiY2OrjJ81axZ27NiBzMxMw74pU6YgIyMDqampAICoqCjodDrs3r3bMGb48OFwdnZGQkJCrXLpdDqo1WpotVqoVCpTpkREFqqyUkT0uqM4fOEWQrydsekvYZDLBKljEVEDqu3vbztTDlpaWorjx49j9uzZRvsjIyNx5MiRxz4nNTUVkZGRRvuGDRuGtWvXoqysDPb29khNTcVbb71VZczKlSurzaLX66HX/9+3u+p0OlOmQkRWQCYT8OH4IAz7KAXHr97B/357HB4tm0kdi6jJ+n/9feDl0lySc5tUWAoKClBRUQFXV1ej/a6ursjLy3vsc/Ly8h47vry8HAUFBXB3d692THXHBIDY2FgsWrTIlPhEZIXatWyGd0d3w6zEk9hz+obUcYiatDFBHtZRWB4SBONbsqIoVtn3pPGP7jf1mHPmzEFMTIzhsU6ng5eX15PDE5HVmdj7wbWdzT9xJpKUq0op2blNKiytW7eGXC6vcucjPz+/yh2Sh9zc3B473s7ODq1atapxTHXHBACFQgGFQmFKfCKyUoIgIKpPe6ljEJGETPorIQcHB4SEhCA5Odlof3JyMsLDwx/7nLCwsCrj9+7di969e8Pe3r7GMdUdk4iIiJoWk5eEYmJiEB0djd69eyMsLAxffPEFsrOzMWXKFAAPlmpyc3Px9ddfA3jwF0GrV69GTEwMXnvtNaSmpmLt2rVGf/0zbdo0DBw4EHFxcXj22Wexfft27Nu3Dz///HMDTZOIiIismcmFJSoqCrdu3cLixYuh0WjQvXt37Nq1C97e3gAAjUZj9JksPj4+2LVrF9566y18+umn8PDwwKpVqzBu3DjDmPDwcGzYsAHz58/Hu+++i06dOmHjxo0IDQ1tgCkSERGRtTP5c1gsFT+HhYiIyPrU9vc3v0uIiIiILB4LCxEREVk8FhYiIiKyeCwsREREZPFYWIiIiMjisbAQERGRxWNhISIiIovHwkJEREQWj4WFiIiILJ7JH81vqR5+YK9Op5M4CREREdXWw9/bT/rgfZspLIWFhQAALy8viZMQERGRqQoLC6FWq6v9uc18l1BlZSWuX78OJycnCILQYMfV6XTw8vJCTk6OzX5HEedo/Wx9fgDnaAtsfX6A7c/RHPMTRRGFhYXw8PCATFb9O1Vs5g6LTCaDp6en2Y6vUqls8j++3+McrZ+tzw/gHG2Brc8PsP05NvT8arqz8hDfdEtEREQWj4WFiIiILB4LyxMoFAq89957UCgUUkcxG87R+tn6/ADO0RbY+vwA25+jlPOzmTfdEhERke3iHRYiIiKyeCwsREREZPFYWIiIiMjisbAQERGRxbP5wrJmzRr4+PhAqVQiJCQEhw4dqnbszz//jP79+6NVq1Zo1qwZ/Pz88NFHH1UZl5iYCH9/fygUCvj7+yMpKale562vhp7jl19+iYiICDg7O8PZ2RlDhgzBr7/+ajRm4cKFEATBaHNzc7OK+cXHx1fJLggCSkpK6nze+mroOT799NOPneOoUaMMYxrzNTR1jr93+PBh2NnZoWfPnlV+ZknXYkPPz9KuQ6Dh52jt1+LvVTdHS7sWTZnfgQMHHpv97NmzRuMa7ToUbdiGDRtEe3t78csvvxTPnDkjTps2TXR0dBSvXr362PG//fab+N1334mnTp0SL1++LP7rX/8SmzdvLv7jH/8wjDly5Igol8vFpUuXipmZmeLSpUtFOzs78ZdffqnzeS1tjn/605/ETz/9VExLSxMzMzPFV155RVSr1eK1a9cMY9577z0xICBA1Gg0hi0/P98q5rd+/XpRpVIZZddoNPU6r6XN8datW0ZzO3XqlCiXy8X169cbxjTWa1iXOT509+5dsWPHjmJkZKQYFBRk9DNLuhbNMT9Lug5F0TxztPZr8aGa5mhJ16Kp89u/f78IQDx37pxRtvLycsOYxrwObbqw9O3bV5wyZYrRPj8/P3H27Nm1PsZzzz0nvvjii4bHEydOFIcPH240ZtiwYeILL7zQoOetLXPM8VHl5eWik5OT+NVXXxn2vffee1UuTHMwx/zWr18vqtVqs5+3thrjNfzoo49EJycnsaioyLCvsV5DUaz7HKOiosT58+c/NqslXYvmmN+jpLwORdE8c7SVa9GU11HKa9HU+T0sLHfu3Kn2mI15HdrsklBpaSmOHz+OyMhIo/2RkZE4cuRIrY6RlpaGI0eO4KmnnjLsS01NrXLMYcOGGY7ZEOetLXPN8VH37t1DWVkZXFxcjPZnZWXBw8MDPj4+eOGFF3Dp0iXTJ1EDc86vqKgI3t7e8PT0xOjRo5GWltag562txnoN165dixdeeAGOjo5G+839GgJ1n+P69etx8eJFvPfee4/9uaVci+aa36Okug4B887R2q9FU19Hqa7F+vxbBgcHw93dHYMHD8b+/fuNftaY16HNFpaCggJUVFTA1dXVaL+rqyvy8vJqfK6npycUCgV69+6NqVOn4tVXXzX8LC8vr8Zj1ue8pjLXHB81e/ZstGvXDkOGDDHsCw0Nxddff409e/bgyy+/RF5eHsLDw3Hr1q36Tep3zDU/Pz8/xMfHY8eOHUhISIBSqUT//v2RlZVV7/OaqjFew19//RWnTp2q8vPGeA2Bus0xKysLs2fPxrfffgs7u8d/R6ulXIvmmt+jpLoOAfPN0dqvRVNfRymvxbrMz93dHV988QUSExOxdetW+Pr6YvDgwUhJSTGMaczr0Ga+rbk6giAYPRZFscq+Rx06dAhFRUX45ZdfMHv2bHTu3Bl//OMfTTpmXc5bV+aY40MffvghEhIScODAASiVSsP+ESNGGP53jx49EBYWhk6dOuGrr75CTExMPWdkrKHn169fP/Tr188wtn///ujVqxc++eQTrFq1ql7nrStzvoZr165F9+7d0bdvX6P9jfkaArWfY0VFBf70pz9h0aJF6Nq1a72P2Vivoznm95AlXIdAw8/Rmq/FuryOlnAtmvJv6evrC19fX8PjsLAw5OTkYPny5Rg4cKBJx2yI19BmC0vr1q0hl8urNLj8/PwqTe9RPj4+AB78h3Pjxg0sXLjQ8IvAzc2txmPW57ymMtccH1q+fDmWLl2Kffv2ITAwsMbjOTo6okePHob/Z9QQzD2/h2QyGfr06WPIbkuv4b1797BhwwYsXrz4iVnM8RoCps+xsLAQx44dQ1paGt544w0AQGVlJURRhJ2dHfbu3YtnnnnGYq5Fc83vIamvQ8D8c3zImq5FU+co9bXYUP+W/fr1wzfffGN43JjXoc0uCTk4OCAkJATJyclG+5OTkxEeHl7r44iiCL1eb3gcFhZW5Zh79+41HLOhzlsb5pojACxbtgxLlizBjz/+iN69ez/xGHq9HpmZmXB3d6/1eZ/EnPN79Ofp6emG7LbyGgLApk2boNfr8eKLLz7xGOZ4DQHT56hSqXDy5Emkp6cbtilTpsDX1xfp6ekIDQ0FYDnXornmB1jGdQiYd46/Z03XoqlzlPpabKh/y7S0NKNcjXodmvQWXSvz8E+p1q5dK545c0acPn266OjoKF65ckUURVGcPXu2GB0dbRi/evVqcceOHeL58+fF8+fPi+vWrRNVKpU4b948w5jDhw+Lcrlc/OCDD8TMzEzxgw8+qPZPuKo7r6XPMS4uTnRwcBC3bNli9KdshYWFhjEzZswQDxw4IF66dEn85ZdfxNGjR4tOTk4NPkdzzG/hwoXijz/+KF68eFFMS0sTX3nlFdHOzk48evRorc9r6XN8aMCAAWJUVNRjz9tYr2Fd5viox/0VhSVdi+aYnyVdh+aao7Vfi7WZ40OWcC2aOr+PPvpITEpKEs+fPy+eOnVKnD17tghATExMNIxpzOvQpguLKIrip59+Knp7e4sODg5ir169xIMHDxp+9tJLL4lPPfWU4fGqVavEgIAAsXnz5qJKpRKDg4PFNWvWiBUVFUbH3Lx5s+jr6yva29uLfn5+Ri9ebc5r6XP09vYWAVTZ3nvvPcOYqKgo0d3dXbS3txc9PDzE559/Xjx9+rRVzG/69Oli+/btRQcHB7FNmzZiZGSkeOTIEZPOa+lzFEVRPHfunAhA3Lt372PP2ZivoSiaNsdHVfeLwJKuxYaen6Vdh6LY8HO09mvxUdX9d2pJ16Ip84uLixM7deokKpVK0dnZWRwwYIC4c+fOKsdsrOtQEEVRNO2eDBEREVHjstn3sBAREZHtYGEhIiIii8fCQkRERBaPhYWIiIgsHgsLERERWTwWFiIiIrJ4LCxERERk8VhYiIiIyOKxsBAREZHFY2EhIiIii8fCQkRERBaPhYWIiIgs3v8HDMPE5XWm3TEAAAAASUVORK5CYII=",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"def load_curve(path: str):\n",
|
|
" with open(path, 'r') as curvefile:\n",
|
|
" xs, ys = [], []\n",
|
|
" for line in curvefile.readlines():\n",
|
|
" x,y = line.split(' ')\n",
|
|
" xs.append(float(x))\n",
|
|
" ys.append(float(y))\n",
|
|
" return (xs, ys)\n",
|
|
"\n",
|
|
"xs, ys = load_curve('../utk/cmake-build-debug/src/samplers/tailcurve.crv')\n",
|
|
"\n",
|
|
"plt.plot(xs, ys)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 91,
|
|
"id": "48faebc0-2e7c-492a-87de-5974533ddaf9",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"calculating oscillation 99"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import subprocess\n",
|
|
"\n",
|
|
"DATAPATH = '../result_data/cutoff_boxplots/pointsets_0.25'\n",
|
|
"\n",
|
|
"with open(f'{DATAPATH}/oscillation.txt', 'w') as oscifile:\n",
|
|
" for i in range(0, 100):\n",
|
|
" print(f'\\rcalculating oscillation {i}', end='')\n",
|
|
" result = subprocess.check_output('../psa/cmake-build-debug/psa --spectral ' + f'{DATAPATH}/pointset_{i}.txt', shell=True, text=True)\n",
|
|
" oscillation = result.split('\\n')[2].split('\\t')[-1]\n",
|
|
" oscifile.write(str(oscillation) + '\\n')\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 94,
|
|
"id": "2568546e-a826-479b-93e0-9ca140e9decb",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"def load_oscillation(path: str) -> ([],[]):\n",
|
|
" xs, ys = [], []\n",
|
|
" with open(f'{path}/oscillation.txt', 'r') as oscillation_file:\n",
|
|
" for line in oscillation_file.readlines():\n",
|
|
" ys.append(float(line))\n",
|
|
"\n",
|
|
" return (range(len(ys)), ys)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 148,
|
|
"id": "95757408-6d9d-428b-a46a-9be00a862da0",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x7f82e3598650>]"
|
|
]
|
|
},
|
|
"execution_count": 148,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
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",
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"text/plain": [
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"<Figure size 1500x1050 with 3 Axes>"
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]
|
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},
|
|
"metadata": {},
|
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"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"DATAPATH_NO_CO = '../result_data/avggrads_no_cutoff'\n",
|
|
"DATAPATH_HARD_CO = '../result_data/avggrads_cutoff_0.3'\n",
|
|
"DATAPATH_TAILCORRECT = '../result_data/avggrads_tailcorrect_lin_0.3'\n",
|
|
"\n",
|
|
"\n",
|
|
"oscillation_no_co = load_oscillation(DATAPATH_NO_CO)\n",
|
|
"oscillation_hard_co = load_oscillation(DATAPATH_HARD_CO)\n",
|
|
"oscillation_tc = load_oscillation(DATAPATH_TAILCORRECT)\n",
|
|
"\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(1,3)\n",
|
|
"\n",
|
|
"fig.tight_layout()\n",
|
|
"\n",
|
|
"fig.set_size_inches(15, 10.5, forward=True)\n",
|
|
"\n",
|
|
"ax[0].set_aspect(1100.0)\n",
|
|
"ax[1].set_aspect(600.0)\n",
|
|
"ax[2].set_aspect(750.0)\n",
|
|
"\n",
|
|
"ax[0].set_title(\"no cutoff\")\n",
|
|
"ax[1].set_title(\"hard cutoff at 0.3\")\n",
|
|
"ax[2].set_title(\"linear TC at 0.3 to 0.4\")\n",
|
|
"\n",
|
|
"ax[0].plot(oscillation_no_co[0], oscillation_no_co[1], marker = 'o', markersize= 1.0, linewidth = 0.1)\n",
|
|
"ax[1].plot(oscillation_hard_co[0], oscillation_hard_co[1], marker = 'o', markersize= 1.0, linewidth = 0.1)\n",
|
|
"ax[2].plot(oscillation_tc[0], oscillation_tc[1], marker = 'o', markersize= 1.0, linewidth = 0.1)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 88,
|
|
"id": "155bc34c-4620-4b7f-b55a-445fcca20c2d",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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p5oypU15x/74rv4TXh/Ju76f49UfJ3DwtTcmIiIh0iu5NE2jqq+DYNnNeEDdp1SQTOxiiejGj+1eaM0RERLxKyYi/OLIRjAbo7b5kpFWnVpsNek6BYx3fZ0hERMTdlIz4i5K3oWsadHPflOttOrX2mmwO720847ZjiIiInI/THVjFIqU50Ptyt+6yTafWXlOgqc5MSHpNceuxRERE7FFlxB/UlkN1vlm58KS4i83ROkffb/fXGvYrIiKeoGTEH5R9aP5MnODZ44SEQs9L4Gj7/UbOe9M9ERERFygZ8Qfl280p4GNSPX+snpOhbBs0NbT51XlvuiciIuIC9RnxB2XbzaqInZsRulWvKfDZUvOGfD3GtvrVeSdOExERcYEqI77OaILyD12addUl3cdCaJTdfiMiIiLupmTE11V9aU545un+Is1CI6DHBM03IiIiXqNkxNeVbQdbiFmx8JZek81kxGjy3jFFRCRoKRnxdeUfQtxwCO/mvWP2mmIOJ6760nvHFBGRoKVkxNed2AEJY7x7zMRMsIWp34iIiHiFkhFf1tQIFZ9DwkjvHjcsBrqPsTvfiIiIiDspGfFlJ/dBYw3Ej/D+sXtNgWPvg2F4/9giIhJUlIz4soqd5k8rkpGek+H0ITilqd9FRMSzlIz4shOfQXQfiOrp/WP3vMT8qX4jIiLiYUpGfFnFTmuqIgCR3SEu3WyqERER8SAlI76s4jPrkhEw+42oE6uIiHiYkhFfVVdp9teI9/JImrP1nAzV+VBTal0MIiIS8JSM+KrmzqsJVlZGJps/j22xLgYREQl4SkZ8VcXn5sRj3QZbF0OXftB1kDqxioiIRykZ8VXV+dAtzbxxnZV6TdFN80RExKOUjPiq6r3Q7SKrozD7jZz4DOoqrI5EREQClJIRX1WVD90utDoKszKCAce2WR2JiIgEKCUjvqixDk4d8I3KSNc0iOqt+UZERMRjlIz4olMHwGiEWB9IRmw2zTciIiIepWTEF1Xlmz99oTICZjJy/GNoqLE6EhERCUBKRnxR9V4I7QLRfa2OxNRzMjTVQ/mHVkciIiIBSMmIL6rON5tobDarI2HN9gIuefwotSGxmm9EREQ8QsmIL6r2kZE0QPbGfRyqqOXjU8M034iIiHiEkhFfVJXvM/1Fbp6WRr/4aLr0u9Qc3ttUb3VIIiISYJSM+Jr6k1BT7FIysmZ7AZPu28Ca7QVuC2fuhBS2LpnOmLHfhcbTcDzPbfsWEREBJSO+5+TX5k8XhvVmb9xHcUUN2Rv3uTkoIGGM2alW842IiIibKRnxNdV7zZ8uVEaam1Runpbm5qAw75GTOEHzjYiIiNuFWR2AnKMqHyJ7QGR3pzedOyGFuRNSPBDUN3pNga/+AEYT2JTHioiIe+iK4muq86Grb4ykaaPnZKg7AZW7rY5EREQCiJIRX1OV7xvTwLcncTzYQuHYVqsjERGRAKJkxNdU+86w3jbCYsyOrMe2WB2JiIgEECUjvqS2HOqO+25lBKDnJaqMiIiIW7mUjKxatYrU1FSioqLIyMhg82b7Iyw2btyIzWZr8/jyyy9dDjpgdWIkjdf0ugROHYTTh6yOREREAoTTyci6detYtGgRy5YtIy8vj8mTJzNz5kwKCws73O6rr76ipKSk5XHhhT7aSdNKLXfrvcDaODqSOMn8qeqIiIi4idPJyEMPPcT8+fNZsGABQ4cOZeXKlSQnJ5Odnd3hdr169aJ3794tj9DQUJeDDljV+RDdz+yb4auik8z75qjfiIiIuIlTyUhdXR25ublkZWW1Wp6VlcW2bds63Hb06NH06dOHGTNm8N5773W4bm1tLVVVVa0eQaHah0fSnK3nJCUjIiLiNk4lI2VlZTQ2NpKUlNRqeVJSEqWlpe1u06dPH1avXs1LL73Eyy+/zODBg5kxYwbvv29/WvEVK1YQFxfX8khOTnYmTP/lQzfI61DiRKjYCQ2nrI5EREQCgEszsNpstlb/NwyjzbJmgwcPZvDgwS3/z8zMpKioiAcffJApU6a0u83SpUtZvHhxy/+rqqoCPyExDLMDa+r1Vkdyfj3Gg9HE25tf594PE7l5WppnZ34VEZGA5lRlJDExkdDQ0DZVkKNHj7aplnRkwoQJ7N271+7vIyMjiY2NbfUIeDWHzbvi+kMzTdxwCIth7553PXdjPhERCRpOJSMRERFkZGSQk5PTanlOTg4TJ050eD95eXn06dPHmUMHvurmkTR+kIyEhEL3sXynf5HnbswnIiJBw+lmmsWLFzNv3jzGjh1LZmYmq1evprCwkIULFwJmE0txcTHPPPMMACtXrmTgwIEMHz6curo61qxZw0svvcRLL73k3mfi76ryzanWu6ZaHYljeown5eTzbF0y3epIRETEzzmdjMyePZvy8nKWL19OSUkJ6enprF+/npQUs89ASUlJqzlH6urquPPOOykuLiY6Oprhw4fz+uuv8+1vf9t9zyIQVOdDTCqEhFsdiWMSx8MXD8Dpw9Clr9XRiIiIH7MZhmFYHcT5VFVVERcXR2VlZeD2H9n0XTAaYdrrVkfimNPF8I/+MPllSL7G6mhERMQHOXr91r1pfIUv3yCvPV36mRO0lX9odSQiIuLnlIz4gqYGqN7nHyNpztZjHJR/YnUUIiLi55SM+IJTB8Fo8K/KCEDCaDiRZ86RIiIi4iIlI76g5QZ5fnbzwO6joe44nO74JokiIiIdUTLiC6r3QmgUdOlvdSTOSRht/jyeZ20cwJrtBUy6bwNrthdYHYqIiDhJyYgvqM43qyI2P3s5ovtCVC+zqcZi2Rv3aTZYERE/5WdXvwDlbyNpmtlsZnXk+KdWR8LN09I0G6yIiJ9SMuIL/OBuvXabQZo7sVps7oQUti6Zrhv2iYj4ISUjVmuoMTuA+ljn1XOTD7vNIAmjoaYYzhyzIEoREQkESkasdvJr86ePzTFybvJhtxmkuROrBdURdVoVEQkMSkasVr3X/OljzTTnJh92m0G6pUFYV0uSEXVaFREJDEpGrFaVD+HxEJlodSStONwHwxYCcelQscs7gZ2lOWHKSElQhURExI8pGbFadb7ZRGOzWR2J6+LTodLzyUhzs8xta/OYdN8GALYumU5uwQlVSERE/JiSEav567Des8VfDJVfmPfY8aDmZpnXdx52rD+LiIj4BSUjVqvK97mRNE6LS4emWjjp2cpEc9Jx5Yi+jvVnERERvxBmdQBBra4Cao8FQGUk3fxZ8TnEDvbYYeZOSFHCISISgFQZsVLzSBofG9brtKhe5sOCTqwiIuL/lIx4Wau5Mfz1br3tifNOJ1YREQk8Ska8rNXcGNVfQVRvCO9mdVidF5duNtOIiIg4ScmIl7Ua+VH5BcQNtTok94hPN2eTbaixOhIREfEz6sDqZa06Yb7+JfSaYm1A7hJ/MRhNUPUFdB9jdTQiIuJHVBmxSlPDNxOeuV4Z8al7szQ/j8ovrI1DRET8jpIRq5w8AE11nWqm8al7s0TEQXRfszIiIiLiBCUjVmm+aMcOcXkXPjfzaNwwqNxjdRQiIuJn1GfEKlVfQlg3s5rgIp+bBCx2GJS+ZXUUIiLiZ1QZsUrVNyNp/PkGeeeKGwrVX0NjndWRiIiIH1EyYpXKLzrVedUnxQ0Do/HfM8uKiIg4QMmIFQzDrIx0or+IT4odZv5UJ1YREXGCkhErnCmF+io2lvbwnaG57hCVCJGJ6sQqIiJOUTJihW8u1o/lRfjO0Fx30YgaERFxkpIRK5z4DEKjuWrSZN8amusOsUPVTCMiIk7R0F4rVOyE+Iv578xB/HfmIKujca+4YbD/KWhqhJBQq6MRERE/oMqIFSo+g/gRVkfhGXHDoKkWTh2wOhIREfETSka8rane7FMRP9LqSDyj5R416jciIiKOUTLibVVfmfekSQjQykh0XwiPVTIiIiIOUzLibSc+M38GajONzWbON6JOrCIi4iAlI95WsRO6DICIeKsj8Zy4oW6rjKzZXhBYc7GIiEgbSka8reIzSDh/fxG/vgjHfVMZMZo6vavsjfsCby4WERFpRcmIt1XsdKiJxq8vwrFDoeEUnD7U6V3dPC0t8OZiERGRVjTPiDfVlJiPhNHnXfXmaWlkb9znnxfhuG/uUVO5B2IGdGpXcyekALQkZc3/FxGRwOFSZWTVqlWkpqYSFRVFRkYGmzdvdmi7rVu3EhYWxqhRo1w5rP8r227+TJxw3lXnTkhh65Lp/nnxjUmB0Gi3dWL16yqRiIicl9PJyLp161i0aBHLli0jLy+PyZMnM3PmTAoLCzvcrrKykuuvv54ZM2a4HKzfK/8QovtBl35WR+Ixa7YXMOn+jRwPHeS2TqxqqhERCWxOJyMPPfQQ8+fPZ8GCBQwdOpSVK1eSnJxMdnZ2h9vddNNNzJkzh8zMTJeD9Xtl2x2qivi6jjrXNlcxPj7R26VkpL19+3WVSEREzsupZKSuro7c3FyysrJaLc/KymLbtm12t/vrX//Kvn37uPvuux06Tm1tLVVVVa0efq+pAco/DohkpKNmk+YqRq/+Y74ZUWO4bd8iIhKYnEpGysrKaGxsJCkpqdXypKQkSktL291m7969LFmyhOeee46wMMf6y65YsYK4uLiWR3JysjNh+qbKXdB4Gnr4fzLSUbNJcxVjdHom1J2AM0dc2ndGSkLb6kvVXti9AkrehsYznX0aIiLiI1zqwGqz2Vr93zCMNssAGhsbmTNnDvfeey8XXXSRw/tfunQplZWVLY+ioiJXwvQtZR+CLQy6j7E6kk5zqNmkeUSNk51Ym/edW3CidYWkpgQ2zICdv4b3roANWU5XXURExDc5lYwkJiYSGhrapgpy9OjRNtUSgOrqaj755BNuueUWwsLCCAsLY/ny5Xz22WeEhYWxYcOGdo8TGRlJbGxsq4ffK99uzi8S1sXqSLyjaxqEhLvcibVV9aWhBjZdZU6idvUBmPIaHNsMBX9zc9AiImIFp+YZiYiIICMjg5ycHK655pqW5Tk5OVx99dVt1o+NjeXzzz9vtWzVqlVs2LCBF198kdTUVBfD9kNHN0Of/7A6Cu8JCYNuF7mcjMydkPLvysvex+BEHlzxMXTpbz76z4Idv4T+VwdPgiciEqCcnvRs8eLFzJs3j7Fjx5KZmcnq1aspLCxk4cKFgNnEUlxczDPPPENISAjp6emttu/VqxdRUVFtlge0kwfg5D7ofZnVkXhXnBtumGcY8NUfod/VrZu4Rv8OXh8GXz8OQ+7o3DFERMRSTicjs2fPpry8nOXLl1NSUkJ6ejrr168nJcX8FltSUnLeOUeCTmkO2EIh6VKrI/Gu2KFmstAZpTlmQvOtc4aOd7sA+l4JhS8oGRER8XM2w/D9XoBVVVXExcVRWVnpn/1HNv8Aaoohy/7w54BUsA62/id8rxwiu7u2j41XwulimJkH53aS3v80bP8hXFMM0X06H6+IiLiVo9dv3SjP05oa4ci70PtyqyPxPhdH1LSoKYHDb8BFt7RNRAD6fcdcXvxP12MUERHLKRnxtBOfmvNtBGMy0u0isIW4Pi180Stm81byte3/PrIH9JwCRf9wOUQREbGekhFPK3kbwrpB4nirI/G+0EjodiFU7HRt+6IXofeMjpt4+s8yK0/1ATBLr4hIkFIy4mHHv1zLu5VjWPPRYatDsUbCGHNYrrPOHIWjmyD5+x2v1/8qaKqDI++5Fp+IiFhOyYgnVX1F97rd/P3YpOC910r3MXA8z+w744xD/wBsZuWjIzGp5p2QjwVZ52ARkQCiZMQDmu88+9nWx6mzdSU/9JJ27+MSDHJK+0HjaV7bstG5DQtfgl5TISqx4/VsNug5Ecq2uhyjiIhYS8mIB5h3nj1N3NGXiEi5hvd+ObPj+7gEsAc/igEgb8c7jm9UXwVH3zt/VaRZ4iQo/wQaa50PUERELKdkxI7m6karu8Y66OZpaUztWcLA8EJI+U8PROc/5k0dyaH6vlyXdszxjUrehqZ66HeVY+v3nAhNta71TREREcspGbHDrG7UuNTXY+6EFJ6e/AlE9Q6+KeDPMXdCCv3TJjE0cq/jGx16DeIvhq4DHVs/YRSERqvfiIiIn1IyYkeru8Y660wZHHjGnKwrNML9wfmb7hlmJ1aj6fzrNjVCyXrHqyJg3h24xzj1GxER8VNO35smWLS6a6yzvn4MsMEFN7k1Jr+VMAYaqqH6a4i9qON1yz6A2nLnkhGAxImw/0nzxnrtzdYqIiI+S5WRszT3E7ltbZ7L/UVoqIH8RyD1hvOPBAkWPcYCNjjmQOWi+FWI6mVWOpyROAHOHIHTh1wKUURErKNk5CzN/URe33nY5f4ifPmQ+c1+6M/dH6C/ikgwm2qOvNvxeoYBhS9C/2vNaeSdkTDa/KlOrCIifkfJyFma+4lcOaKva/1FThfD7v+Dwbebt7iXf+s9A0rfMRMOe47nwqmDMOA8s662p0t/8141SkZERPyO+oycpVP9RAB2/BLCYiD9f9wXVKDofRnsuR8qd0N8evvrFL0IkYnmZGfOstnM6oiSERERv6PKiLscXAsHn4PRD0BEnNXR+J7ESRASaVZH2mMYUPgC9L8GQlzMkRNGm6N2RETErygZcYeqvfDRTyBljtlxVdoKi4ael9hPRk58Cif3u9ZE0yxhNJwuNPvsiIiI31Ay0lk1pbDpSojuw99s/49J97/n2iicYNB7BhzdaI44Olf+I2a/j6RLXd9/SyfWHa7vQ0REvE7JSCe8sPVT9q2byOnTVXDpm/zp/SOuj8IJBgOug4bT5oRwZ6spMZu4LrrNnMDMVd0uhNAu6jciIuJnlIy4quJzJu27kljbCebs+w2THjlIRkqC67O2BoNuaZB8LXz5e3Om1Wb5qyAkAi74cef2HxIKCSPVb0RExM8oGXHSmg8O8PtHbqP+jQlEdUngpqOrOFg/gOKKGnILTrB1yfSgvUPv2ezeaHDoXVC9F4pfM/9/qgi+zoZB8yEivvMH1ogaERG/o2TEQWu2F/DTh1dy8Z4r+Xn3P/F61XS6z/qYl+/6L+68YrAqIuewe6PBxPHQczLkLoJ9T8K70yGsGwz7pXsOHD8CqvOh8Yx79iciIh6nZOR8GuugYB3D9lzNqqQ7iLDV87MjD3Fy5CPmnCKY85OoItJahzcanPAkxA2DD+dDUy3MeA+69HXPgeNHgNEIlV+4Z38iIuJxNsPoaEpM31BVVUVcXByVlZXExsZ6/oCGYY7IKFwH+/8KZ45yJGocfyyaydBxNzA3M9XzMQSD8o8hup/7EhGA+mp4IRYmPAWDNMxaRMRKjl6/NQNrszNlUP4hlLwJh14z56sIj4fU6+HCm0iKG8ZvO7H7NdsLyN64j5unpamC0qzHt9y/z/Bu0HUQVOx0/75FRMQjgjsZObIJPl0Mp4ug9pi5rEsy9L/afPSa2rmhpmc5uw+FkhEPix8BFZ9bHYWIiDgouJORyO7m7e2Tr4GuF0DiOIhJNe9z0knnVkJunpbW8n/xsPgR8PXjVkchIiIOUp8RD5l03waKK2roFx/N1iXTrQ4nuBS+BFu+D9eUQnSS1dGIiAQtR6/fGk3jIR2OJhHPih9h/qxUU42IiD8I7mYaD5o7IUV9Q6zSddA308LvhN6XWR2NiIichyojLrI7w6hYLyQU4tM1okZExE8oGXGR3RlGxTfEj1AyIiLiJ5SMuEh9Qnxc/Aio3A1NDVZHIiIi56E+I7g2IZn6hPi4+Iuhqc68T03cMKujERGRDqgygppcAlL8xeZPTX4mIuLzlIygJpeAFNnDvO+N+o2IiPg8NdOgJpeAFT/CHN4rIiI+TZURCVwJGlEjIuIPlIxI4IofYd59ua7C6khERKQDSkYkcDVPC6/qiIiIT3MpGVm1ahWpqalERUWRkZHB5s2b7a67ZcsWJk2aRI8ePYiOjmbIkCE8/PDDLgcs4rDYwRASCSc+szoSERHpgNMdWNetW8eiRYtYtWoVkyZN4vHHH2fmzJns2bOHAQMGtFk/JiaGW265hREjRhATE8OWLVu46aabiImJ4Sc/+YlbnoRIu0LCzSG+Jz61OhIREemAzTAMw5kNxo8fz5gxY8jOzm5ZNnToUGbNmsWKFSsc2se1115LTEwMzz77rEPrO3oLYme5MtmZPx83KH34Eyj/EL6t6oiIiLc5ev12qpmmrq6O3NxcsrKyWi3Pyspi27ZtDu0jLy+Pbdu2MXXqVLvr1NbWUlVV1erhCVZNdqZJ1ryo+xio3AONZ6yORERE7HAqGSkrK6OxsZGkpKRWy5OSkigtLe1w2/79+xMZGcnYsWP52c9+xoIFC+yuu2LFCuLi4loeycnJzoTpMKsmO9MkayZP3Pm4zT4TxoDRABW73HYMERFxL5c6sNpstlb/NwyjzbJzbd68mU8++YTHHnuMlStXsnbtWrvrLl26lMrKypZHUVGRK2Ge19wJKWxdMt3rTSVWHdfXeKJC1Gaf8ReDLVT9RkREfJhTyUhiYiKhoaFtqiBHjx5tUy05V2pqKhdffDE//vGPueOOO7jnnnvsrhsZGUlsbGyrh1U88e1dTJ6oELXZZ1g0J8Iu4B/v/lOvoYiIj3IqGYmIiCAjI4OcnJxWy3Nycpg4caLD+zEMg9raWmcObRn17/AcT1SI2tvn9hMDGBiar9dQRMRHOT20d/HixcybN4+xY8eSmZnJ6tWrKSwsZOHChYDZxFJcXMwzzzwDwKOPPsqAAQMYMmQIYM478uCDD3Lrrbe68Wl4zs3T0lpGvoh/SkzJZGjZRn46te3QcxERsZ7Tycjs2bMpLy9n+fLllJSUkJ6ezvr160lJMb+JlpSUUFhY2LJ+U1MTS5cu5cCBA4SFhZGWlsZ9993HTTfd5L5n4UG6iZ53eHK487dGXw7vLOe/B1e7db8iIuIeTs8zYgVPzTMivmPSfRsorqihX3w0W5dMd+/OG2rghVjI+ANc9FP37ltEROzyyDwj4hnB1kn23Oe7ZnsBp2obiI8O90xzWFg0JIyGsg/cv28REek0JSM+INg6yZ77fLM37qOipp6YyDDPNYklZioZERHxUUpGfECwTYJ27vP1yvNPzIST++DMUc8dQ0REXKI+IxIcThXAqwNhyqvQ/7t2V9N9g0RE3Ed9RkTO1mUARPeBso7voRRsTWYiIr5AyYgEB5vNoX4jwdZkJiLiC5yeZ0TEb/W8BHYsNYf6hkW3u4rmlRER8T5VRiR49L4cmmrh2GarIxERkbMoGZHgETfc7DdSmnP+db8RbHPAiIhYQcmIBA+bDZIugxLHkxF1aBUR8TwlIxJc+mRBxWdQc8Sh1dWhVUTE85SMiFf4THNH78vMn0fedWj1uRNS2LpkukudWn3mOYuI+DglI+IVPtPcEd0b4i+Gw296/FA+85xFRHyckhHxCp9q7uh/LRS/Co1nPHoYn3rOIk5SZU+8SdPBS/Cp/AJeHwZT/gH9r7Y6GhGfNOm+DRRX1NAvPpqtS6ZbHY74KU0HL2JP3FCIHwEFf7M6EhGfpcqeeJNmYJWAZvfGdyn/Cbt+Aw2nICzGugBFfJRmIxZvUmVEAlJze/eDb33VfifSlNnQeJp7V/3W59vE1XbvGp0336bXR86mZEQCUvNIFqD9UnPXQXx8ZgxXd3mR7I1fWxCh4zQqxzU6b75Nr4+cTcmIBKTm9u47rxhsd56QqoG3MarLXu4eX+b247vzW5/a7l2j8+bb9PrI2TSaRoKXYcD6ERCTAtP+5dZdaySCiIhG04i00aZaYbPB0Dvh8OtwPNc9+/yGvvWJiDhOlREJGu1WK5rq4c2xEBIOWdshxLkBZqqAiIjYp8qIyDnarVaEhMO4x+H4p5D/qHv2KSKtaOSMnI8qI+I1duf88AUf/wz2/xVmbITEcVZHIxJQVEEMXqqMiM/x6aF8ox+EhFGw6TtQ7YPxScDyh6pBZ2P05QqiP5z/YKBkRLzGlz+QCIuGKa9BRAK8MxmObbM6IgkSPp2kf6OzMc6dkGJ3iL3V/OH8BwMlI+I1vvyBBEBUIly2CbqmwbvTYOc9UH/S4qAk0Pl0kv4Nf4jRVYH83PyJ+oyInKupHnb+Gr58yKyUDPoRpM6F2KHmcOAO+HS/GC/w9PMP9vMr4m/UZ0TEVSHhMGoFXJUPydfC3mx4fTi80hc2f58db9zJL/7wG17e8oE5cdpZgr3k6+nnf+7+1d7vPjqXYiUlIyL2xKTAt1bBtSUw7Q0YdAPUHWdQ2Woe6Pk/XFs4EV5KhA1ZfPj2b5n5wCtkpCQEdcnX0yXvc/fvzuQn2C/GwZ5Ii7XUTCPipDUfHOTlLR9w65jTXNrrMBzbTEPJu9Q2RbC2ejYLfvwIhHe1Osyg4M5mm2AffqomMO8ItvPs6PVbyYiIG7ywNZfaz3/Hf8W9QmjMAJjyMsRf3GqdYPsQcjf1R5FAEGxJr/qMiHjRDyZlMHfh3wj9zm4I6wJvTYDi1jffc6YMHuxNBu3xdDOCz4/28jH+9B71pVg1eqd9SkZE3KnbBZD1AfTJgs3fg+LXW37lzIeQ2u/b0oe4b/Gn96irsXoiiVHS2z4lIyLuFtYFLvk79L0SNl8LR7cAzn0IeeLC6+gHqy99izybPsR9iz8lh67G6k8Jl79TnxEJao70E3C5L0FjHbx3BVTuhv/4BGIGuClq1zjaVh1sbdrupr4ngUOvZeepz4iIA5q/+Tz41ld2qwEufzsKjYBLXoCwGHj/amg45aaoXePot0N/+sbri/RtOnCoGuc9SkYkqDVfeAG7F5DmdTJSEpxvvohKhKmvQfVe+OBGMJrcFLnzHP1g1Qewc85t1lIyJ+I8JSMSdM6+eDRfeO+8YrDdC0jzOrkFJ1z7xht/MWSugaIXYdf/uulZBIaO+qf4at+Vc51bCWl+vwB+/9z8ic6pf3MpGVm1ahWpqalERUWRkZHB5s2b7a778ssvc/nll9OzZ09iY2PJzMzkrbfecjlgkc5qr4zuSDWgU994k2fBiP+Fz++Bwpec397NfOWDu6MmDX9p7rD3vgiE5+ZPdE79m9PJyLp161i0aBHLli0jLy+PyZMnM3PmTAoLC9td//333+fyyy9n/fr15Obmcumll3LVVVeRl5fX6eBFXOFqUnFuwuL0BX34MhgwGz64Ho5b+/73lQ/us18Le80dLjWPeZG9RLaj95mactrqbIKsc+rfnB5NM378eMaMGUN2dnbLsqFDhzJr1ixWrFjh0D6GDx/O7Nmz+fWvf+3Q+hpNI77IpVEnDafhnalwuhAu2wKxFwLe77XfmeOt2V7Ag299BcCdVwx2W7z2zqc3Rvdo1MS/WXUuNIorMHlkNE1dXR25ublkZWW1Wp6VlcW2bdsc2kdTUxPV1dV0797d7jq1tbVUVVW1eoj4Gpe+iYV1gWnrISIB3rscTh4EvFup6OzFJnvjPipq6qmoqXdrvPbO5+2Tu/OD3jt4dOQb8Pm98MVD5twtjbVuO7avVIqscG5FwqpzocrGv/lKM6o3OZWMlJWV0djYSFJSUqvlSUlJlJaWOrSP3//+95w6dYrrrrvO7jorVqwgLi6u5ZGcnOxMmCJe4fKok6iecGkO2MLg7QlwPNerH8RnX2yc+dBrXjcjJYH46HDio8Pd2oTS5nye+Ay2zuG6onH8rtevGHXqCfh6Nez8H3hnMrzcG3IXwckDnT62v1wIPXGROjf5sOpcnP36W3ExXrO9gFH3vs2oe992+biuxu1MQhioiYpLHVhtNlur/xuG0WZZe9auXcs999zDunXr6NWrl931li5dSmVlZcujqKjIlTBFfEK7Hx4xyZC1DWJSIGcycxP+ydZfTvNKWfzsi40z34Kb180tOMGOu7PYcXeW6yOMOtJYBzvvhjfHQvlHMOp++O4B+F45XFMMP6g0J5G78CY4+Bz8azDkLoba4y4f0l+GM3uianFu8uHJc7F22xfc8Ps/s2HDU3DsA6g50u56VlRn3FHxc/X+U84khIFaxXMqGUlMTCQ0NLRNFeTo0aNtqiXnWrduHfPnz+fvf/87l112WYfrRkZGEhsb2+oh4q/sfnhE9YIZ70HafMi9Fd6ZAkc2tfzaU9+Azr7YOPMtuL113f4t+sRn8NY42P1/kP4r+M4XMOQO6DoQmr/whIRB9wwYdR9cXQDpd8O+P8NrabDnd9BQ455YfJAnqhbtJh+1x6FgHXz1J/hyJRx+E86UuXaA+pPw9V9gQxbfPzCCp/v8hOmlP4ScifBKb8i5BPY/DU2NLZtYUZ25eVpaS8Xv3OM6+rfo6v2nnEkI/aWK5yyXOrBmZGSwatWqlmXDhg3j6quvttuBde3atfzoRz9i7dq1zJo1y+kg1YFV/JlDfTRKN0DeXXDiU0i6FC6+l0lP1rfboS8gO1s21cPu+2DXcogbChOehu6jHd/+zFGzP8nXj5tJ3vBfQdoCcxZccdzJg+b7sPhV8zUJiTSTwMYzYAuBnlNgwPeh/zXQpW/H+6r4HPY+BgeehYaTkDSdjxqm8Jfd3endO40DJcUsHFHFpLB3oOQNiB8J38qGnpleeao0nIbDr0PRP6DiMzhdBKFREJUEiZOg739A329DSHiHnWtd/XsMyL/jdjh6/XY6GVm3bh3z5s3jscceIzMzk9WrV/PnP/+Z3bt3k5KSwtKlSykuLuaZZ54BzETk+uuv5w9/+APXXntty36io6OJi4tz65MR8WuGAcWvmU0UFZ9xOHoy9xy4jikTr2r1YRVwow4qdsEHN5gXhGFLIf1/XE8iqr8253I5+LzZBDb0Lhg4ByLi3Rlx4DEMyH8UdvwCInuY523ADyC6jzlr8KmDUPouFL4IRzaA0QCJE6H/dyF+FHTpDzTByYPs3PkOXY7+kwsiDkBUbzMpvGCB+Xp8o817uGw75N4Ox3Ph4nth2BIICfXMc204Dfl/4szO3xHVVM7xiGF0HzgdugyAplo4VQhHN0F1vvn8L7qFtZXX8Mj7Je0mDgH39+hmHktGwJz07IEHHqCkpIT09HQefvhhpkyZAsCNN97IwYMH2bhxIwDTpk1j06ZNbfZxww038NRTT7n1yYi4i6XfWowmKHrFvKhW7oKBc2H07yC6d5vYAM/GWV8NRzdD2Qdm1ebkAThzxPy2HNYVul0ICaOh92XQa4r5zdJRjWdgzwOw+zdUhA7k50V3cOnEb7v0PNq8XhW7zfN36BWzo3DvGdA7C7qPMWfE7SA5cdtr31gLlXug6guor4SmBrNq03WQWQVwU9Xm3Hidjr+pHj65xewcfOHPYNQKCO9mf/3a41D8Tyh6CUrfgcbWzWKVjd14r2oMHzTM4P5bl0BIeIcxg/ke/unUFP67y1Ow+7dmRWLicxDh2BdWhx1+Cz6+GWoO8Y/KK1hZfBX1XS5oP4k48ZlZ2dn/pDn6Lf3X7VbbgqXC4SqPJiPepmREvM0nvu0YTbD/r7BjifnvzKeh33c8G2djrZl4lL5rfgMu/8j8FhzVCxIyzOQjujdgMy+w1fnm+jUlENYN+l9tfqPucwWERto/RsE6M1moOQRD7mTam1M4WNHo8vOwex5qSswqyeH1cGwLNNWZy7skQ/wIPj89iOf3JjJuzAyumTyp432dxe4FqPGMOcNu4d+hNOffF2pbmNnM0Xz80CjodSmkzDbPV1iXDp9fRxe8c+N16j3ReAY2fx9K3oJxj0Pajzpe/1xNjWbV5MwR8/lF92XNziayN+13+OLcJt7Db8LW/zTfZ1NehdjBHW7f0blp/t2iyXH8gIeg4HlImgHjHmPN7nDHkoiTB8336oFnoGuq2aE6+Xv/7sMkHVIyItIJnvy24/S+a8th+w/Nb6NDfm5+c/3m26Zb4qzeZ1YQSt42L9iNNWapvtel0Hu6+eHd7UL7H76GAZW7oehl8yJcudusmvSaComZZiUgJBxqy9n3xTvEV75Lj9AT0Pc7MOZBiB3s9PNorxpw3onYGuug+is4sRMqP4cTOzh+6EO6h1aYv48dAv1n8UbFeH67vSsLp11ot9LQ5gJavQ++fsxMHmvLoeck6Pdd6DkZ4tPNSoNhQH2VWSk5thUOvYpxbAsVjbEUJv6IkdOXQWQPx453nnPh0LlsOAWbroaybTD5Feh7xXnPuye0G29Vvnmn65rDMPF56Hel3e07OjeT7nuXSbbX+FXfvxLbJQJGPwSp81xLJCp2wY5fmoltz0tgzEPQ41vO7yfIKBkR8VEuVTMMA75aCXm/MEeSXPJ3iBngehAnD8KBp80EomLnv7+p954BSdMhYaT5TdcVlXvg0KtmdeVEHtQ1D7m1sbduEBsrL+a9+u/y/J0/dDn89s6hK+d1zQcHeWHLRywec4KpMR+afXZqyyG6r9lJc8D3mPLXBgor6lrtd832Ap7ctJu7MwqZGvIKlL5tlvIH/RAuuAliL3Lo+D/43RqujFzHf3bPISo8FNIWcPV7E/msvGub47k1Oa6rhE1Xmk0R0143m9hc5LHEvb4Kts39dxI+8v/abdqye/zKLzny7g0knfmIfV2vJS3rMXOOn84qyYG8n5sddAfONb8cdOnvW19gfIiSEREf1akPlrIPYct10HjK/MbYJ+v827TafjvsXmF+wId3M6sTydeaIwfCYpzbl6Pqq8FohLCurPmo2C0fqu2dQ2fOq911mxq+qVq8YiZqp4s4E9KdT09dSHzvixnWv5f5fCr3mBWFxhroMR4uvBkGXAdh0Y4fi7ObERL4QbdXIf+PNNaf4h9VM7ENX8K1l0xw+RzZjWFkFGz6jtnZ99I3IXF8p/bdnATGR4cTExnm1gvmmg8OcPzTB/hZwhOExl4AGX+APpd3vFFNqdkXae+jZqfUcY+ZSXbzPjt5YV+zvYDHN+bzuzG5TDj5sPl+uPCnXP3uOD4rj/FI065PNBu7SMmISKCqLYdt/202qwy5A0b8pt2LYCtHNsGu/4Uj75rNEUMWm6NMOkhAmj+0M1ISyC044ZEEwioOfbgbBpR/bCZuJ/Kgeq/Z5yOsi3kOe0ww+8icpwpy9rGaJ5qzew7qq76Z2+Mhczhs2gJzZElM52ahbo5hTNxhHun3axIiG4m+/C3nhk/b0fy6nqptoKKm3rHn6WTcU3oe5pkRz8KxzdBjnHleek7+d/Ph6SLztSp8wazKhUaZ7/Ghd7X52+jshb3V9j8fa85tk/8nGutreP3kZRhD7uTqKZe6/Jzb40t/O85SMiISyJoazQvWzv+BLv1g+P+DgfNaythrthfw1KZd3DPmay5p+huUbzdHcKT/yqyEONAE0/yhG2qDRgOXP7zbu1h589tdZ6sorqxvb9vmia7Oew7qqyD/Efji99BQDf2uMpuA+vyHOembk9Z8cJDDuX/g1vhsCmp78/+Or+Dlu/7L6f10eAxXnqcT+5w7fgAbNzxB1MHVjI/+BBvtXLriR0LqXDNZsTNiypHX0pFqVqvf1VeZI2++fBjOlJp9hgb8p1lx7HaBy8/fHaxOZJSMiASDyi9g56/MJoXQaLNDXVg3dh3Yz+CIfMJtjWYH1MG3myNxnOi4567KiCfL+M4cP9QG916d3qnn4NaLqyNx1FfDvifNjrEVn5nzdgz4vtmvp9dUiLR/w1HArO6U5pgTwpVtI7/bHH66Zw43TnXtPDjK3RfAcxPaIQkNvHlDV3MkD5gTlSWMNhNzN3D59W48Y/4tHnjWHPZsNJixxY80q1uRvcyRaZGJZrIUkWA+ugyA8K5uid1tz8VNlIyI+Dh3fGNvUfml2cu/fDs01nKgMoSXC5NJG/k9Zk2e6qFn4BhvViHs7e/uV3e5pbpjaZn8eJ6ZlBx+HU7uB2xmR+P4kWZTUVRvsx9QU4M5pLlyN5S8aY5I6THObM47X38LH+XthNYtr3d9NRzZCMc/NjuJ15SYMwWfOdJmbhbAfP16fMscqdN/lsOdoDty9iizKRf1JLfgRMuXi7N/vp9/DOhgJFonKBkR8XHuGhESaDxxDryRTDhd2u+MUwVw5D04+r6ZdFR/fdaoJcwqWbcLzQpK8jVm/wo/nhfDJ5LBc3QqpobTUFcB9RXmJHKnDkLVl1D+odmBurHGrPRcuNAcsXOeeWjsOftvCWjV7Bpqg2jbacbF7CE18hBJ4eU8XXOL2z93lIyI+Di3VkYCiL+eg47nu3BvgtXuOWqqNy9ythBznhc3JB9WvBb+8vp74n41gPkalrz9TRXsX2bTzvBlcMGP7U8kaEd7M91mDIgn9Og7/KTXK1xofEyYrZGapkiK6vvyyeA3mDOx40nmnKVkRES8xl8uIFbNBeHu43qrgmZFpc6Tx3Tn6+DMrLguO7kfPl8OB581Zw1Ov9uctM2FTsw0NZpT+O+5zxwd1n0sDLrRnC256yDX5xU6D0ev3545uogElbNvh+7o7datcHac7tbRbd87+p09HZ1HR24jv2Z7AaPufZtR977t8mthxe3qPXnMzrz+574eHb2mbnsOXQdB5lPw7V1m8vDhj2D9xeYtBxytIzSeMe879K/BsHW2Obvy9Hfhio/gop+Zo308lIg4Q5URkQDg1f4K5zm+u4Z1eoK/VHDAffNhgOsddwNNZ15/l2b4dXMlZsPWN/jNoOfpW7PZTE6GLzUnLmzvpos1JbD/Kfjqj2an2eTvwbBfQo+xnYrDWWqmEQki3uyvcD7uniwtWLljptCO7tfjT4lZe7wdvyvHc+ffXqt9/TDEHNJ/bKs5TLjXVIgfASERUHvMnACubCvYws1mnaF3uWV0jiuUjIgEGFerH1ZddDQyyLd15vXxhUTGH95fHu+jUrHLvCt12QdQtce87UJ4HCSMMYdxD7jO7uRv3qJkRCTA+MOH79l8MUFyN39+Ht5usnA3fz737uAvz1/JiEiA8ZcPH0f4wsXMHTz9PHz1NffVuIKJv/wNaTSNiB9wZuSJKyMyfJUVozQ8wdPPw5OjfzrDyveiL4/W8qZA+RtqpsqIiIV85duNvum25QvnxJkYfCFeb3BksjFf7DztyusTCK+pKiMifsDd325c/dboq9/AreQL5+R8FYizX29fiPdcnqhidPQ303wOXt952OfOhSuvjy++pp6iZETEQq6Wu+19yLv64dX8AZ+RkqAS+De8XQZ35cJ99uvti2V7T1xMHZls7MoRfX3uXNh7fTo7uV2gUDONiB+yV6rubFnXV5qNgpHVk2p5gq/H5wvc+Tfni+dbzTQiAczeN6bOdiwMpm9ivsaVc+/tjqTOVm8CqdO1p7jzb86fm3VUGREREYeocubbVBkREQkCwT6sVJUzz3Ll/XX2DREBv61EKRkRkYDiyYTBn8vg7qBmF89ydcRNRU09FTX1Ldv5Y9KsZEQkQPnjB5I7eDJhUGVAXOHo36Ir76+bp6URHx1OfHR4y3b+mDSrz4hIgArW9n1fbDeX4GbVnbN94W9A96YRCXK+9IEkEsyC+W9RyYiIiIhYSqNpRESkXcHan0h8l5IREZEg448dHCWwKRkREQkyGhUkvkZ9RkRERMQj1GdERERE/IKSEREREbGUkhERERGxlJIRERERsZSSEREREbGUkhERERGxlJIRERERsZRLyciqVatITU0lKiqKjIwMNm/ebHfdkpIS5syZw+DBgwkJCWHRokWuxioiIiIByOlkZN26dSxatIhly5aRl5fH5MmTmTlzJoWFhe2uX1tbS8+ePVm2bBkjR47sdMAiIiISWJyegXX8+PGMGTOG7OzslmVDhw5l1qxZrFixosNtp02bxqhRo1i5cqVTQWoGVhEREf/jkRlY6+rqyM3NJSsrq9XyrKwstm3b5lqk7aitraWqqqrVQ0RERAKTU8lIWVkZjY2NJCUltVqelJREaWmp24JasWIFcXFxLY/k5GS37VtERER8i0sdWG02W6v/G4bRZllnLF26lMrKypZHUVGR2/YtIiIiviXMmZUTExMJDQ1tUwU5evRom2pJZ0RGRhIZGdny/+ZuLWquERER8R/N1+3zdU91KhmJiIggIyODnJwcrrnmmpblOTk5XH311S6E6Zjq6moANdeIiIj4oerqauLi4uz+3qlkBGDx4sXMmzePsWPHkpmZyerVqyksLGThwoWA2cRSXFzMM88807LNjh07ADh58iTHjh1jx44dREREMGzYMIeO2bdvX4qKiujWrZtbm4OqqqpITk6mqKhIo3Q8TOfaO3SevUfn2nt0rr3DE+fZMAyqq6vp27dvh+s5nYzMnj2b8vJyli9fTklJCenp6axfv56UlBTAnOTs3DlHRo8e3fLv3Nxcnn/+eVJSUjh48KBDxwwJCaF///7Ohuqw2NhYvcG9ROfaO3SevUfn2nt0rr3D3ee5o4pIM6eTEYCf/vSn/PSnP233d0899VSbZU5OZSIiIiJBRPemEREREUsFdTISGRnJ3Xff3WrkjniGzrV36Dx7j8619+hce4eV59np6eBFRERE3CmoKyMiIiJiPSUjIiIiYiklIyIiImIpJSMiIiJiqYBPRlatWkVqaipRUVFkZGSwefPmDtfftGkTGRkZREVFMWjQIB577DEvRer/nDnXJSUlzJkzh8GDBxMSEsKiRYu8F6ifc+Y8v/zyy1x++eX07NmT2NhYMjMzeeutt7wYrX9z5lxv2bKFSZMm0aNHD6KjoxkyZAgPP/ywF6P1X85+TjfbunUrYWFhjBo1yrMBBhBnzvXGjRux2WxtHl9++aX7AzMC2N/+9jcjPDzc+POf/2zs2bPHuP32242YmBijoKCg3fX3799vdOnSxbj99tuNPXv2GH/+85+N8PBw48UXX/Ry5P7H2XN94MAB47bbbjOefvppY9SoUcbtt9/u3YD9lLPn+fbbbzfuv/9+46OPPjLy8/ONpUuXGuHh4cann37q5cj9j7Pn+tNPPzWef/55Y9euXcaBAweMZ5991ujSpYvx+OOPezly/+LseW5WUVFhDBo0yMjKyjJGjhzpnWD9nLPn+r333jMA46uvvjJKSkpaHg0NDW6PLaCTkXHjxhkLFy5stWzIkCHGkiVL2l3/F7/4hTFkyJBWy2666SZjwoQJHosxUDh7rs82depUJSMO6sx5bjZs2DDj3nvvdXdoAccd5/qaa64x5s6d6+7QAoqr53n27NnGr371K+Puu+9WMuIgZ891czJy4sQJj8cWsM00dXV15ObmkpWV1Wp5VlYW27Zta3ebDz74oM36V1xxBZ988gn19fUei9XfuXKuxXnuOM9NTU1UV1fTvXt3T4QYMNxxrvPy8ti2bRtTp071RIgBwdXz/Ne//pV9+/Zx9913ezrEgNGZ9/To0aPp06cPM2bM4L333vNIfC7dm8YflJWV0djYSFJSUqvlSUlJlJaWtrtNaWlpu+s3NDRQVlZGnz59PBavP3PlXIvz3HGef//733Pq1Cmuu+46T4QYMDpzrvv378+xY8doaGjgnnvuYcGCBZ4M1a+5cp737t3LkiVL2Lx5M2FhAXsJcztXznWfPn1YvXo1GRkZ1NbW8uyzzzJjxgw2btzIlClT3BpfwL+SNput1f8Nw2iz7Hzrt7dc2nL2XItrXD3Pa9eu5Z577uHVV1+lV69engovoLhyrjdv3szJkyfZvn07S5Ys4YILLuC//uu/PBmm33P0PDc2NjJnzhzuvfdeLrroIm+FF1CceU8PHjyYwYMHt/w/MzOToqIiHnzwQSUjjkpMTCQ0NLRNxnf06NE2mWGz3r17t7t+WFgYPXr08Fis/s6Vcy3O68x5XrduHfPnz+eFF17gsssu82SYAaEz5zo1NRWAiy++mCNHjnDPPfcoGbHD2fNcXV3NJ598Ql5eHrfccgtgNj0ahkFYWBhvv/0206dP90rs/sZdn9MTJkxgzZo17g4vcIf2RkREkJGRQU5OTqvlOTk5TJw4sd1tMjMz26z/9ttvM3bsWMLDwz0Wq79z5VyL81w9z2vXruXGG2/k+eef58orr/R0mAHBXe9pwzCora11d3gBw9nzHBsby+eff86OHTtaHgsXLmTw4MHs2LGD8ePHeyt0v+Ou93ReXp5nuix4vIushZqHMT3xxBPGnj17jEWLFhkxMTHGwYMHDcMwjCVLlhjz5s1rWb95aO8dd9xh7Nmzx3jiiSc0tNdBzp5rwzCMvLw8Iy8vz8jIyDDmzJlj5OXlGbt377YifL/h7Hl+/vnnjbCwMOPRRx9tNTSvoqLCqqfgN5w914888ojx2muvGfn5+UZ+fr7x5JNPGrGxscayZcusegp+wZXPjrNpNI3jnD3XDz/8sPHKK68Y+fn5xq5du4wlS5YYgPHSSy+5PbaATkYMwzAeffRRIyUlxYiIiDDGjBljbNq0qeV3N9xwgzF16tRW62/cuNEYPXq0ERERYQwcONDIzs72csT+y9lzDbR5pKSkeDdoP+TMeZ46dWq75/mGG27wfuB+yJlz/cc//tEYPny40aVLFyM2NtYYPXq0sWrVKqOxsdGCyP2Ls58dZ1My4hxnzvX9999vpKWlGVFRUUZCQoJxySWXGK+//rpH4rIZxjc9NEVEREQsELB9RkRERMQ/KBkRERERSykZEREREUspGRERERFLKRkRERERSykZEREREUspGRERERFLKRkRERERSykZEREREUspGRERERFLKRkRERERSykZEREREUv9fw9YbBxOCUdOAAAAAElFTkSuQmCC",
|
|
"text/plain": [
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"from scipy.ndimage import gaussian_filter, gaussian_filter1d\n",
|
|
"\n",
|
|
"\n",
|
|
"def load_oscillations(path: str):\n",
|
|
" oscillations = []\n",
|
|
" with open(path, 'r') as oscifile:\n",
|
|
" for line in oscifile.readlines():\n",
|
|
" r_c, osci = line.strip().split(' ')\n",
|
|
" oscillations.append((float(r_c), float(osci)))\n",
|
|
" return oscillations\n",
|
|
"\n",
|
|
"oscis = load_oscillations('../result_data/cutoff_series/oscillation.txt')\n",
|
|
"oscis = sorted(oscis, key=lambda x: x[0])\n",
|
|
"\n",
|
|
"xs = [x[0] for x in oscis]\n",
|
|
"ys = [x[1] for x in oscis]\n",
|
|
"plt.plot(xs, ys, linestyle='None', marker='o', markersize =1)\n",
|
|
"\n",
|
|
"smoothed = gaussian_filter1d(ys, 4)\n",
|
|
"plt.plot(xs, smoothed, linewidth=1.0, color='orange')\n",
|
|
"\n",
|
|
"plt.savefig(\"/home/clara/repositorys/bachelor-thesis/thesis/media/oscillation_series.png\", bbox_inches='tight', dpi=400)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 193,
|
|
"id": "7bf8a7af-188d-47d5-a0a5-6bfafd48a786",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.lines.AxLine at 0x7f1b337a4ad0>"
|
|
]
|
|
},
|
|
"execution_count": 193,
|
|
"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": [
|
|
"oscis_05 = load_oscillation('../result_data/cutoff_boxplots/pointsets_0.5/')[1]\n",
|
|
"oscis_025 = load_oscillation('../result_data/cutoff_boxplots/pointsets_0.25/')[1]\n",
|
|
"\n",
|
|
"fig, ax = plt.subplots(1,1)\n",
|
|
"\n",
|
|
"plot = ax.violinplot([oscis_025, oscis_05], showmedians=True, positions=[0.25, 0.5], widths=[0.1, 0.1], quantiles=[[0.25, 0.75], [0.25, 0.75]])\n",
|
|
"ax.set_xticks([0.25, 0.5])\n",
|
|
"plot['cmedians'].set_edgecolor('orange')\n",
|
|
"\n",
|
|
"ax.set_yticks([np.median(oscis_025), max(oscis_025), min(oscis_025)])\n",
|
|
"ax.set_xlim([0.15, 0.6])\n",
|
|
"\n",
|
|
"axr = ax.secondary_yaxis('right')\n",
|
|
"axr.set_yticks([np.median(oscis_05), max(oscis_05), min(oscis_05)])\n",
|
|
"\n",
|
|
"\n",
|
|
"ax.axline((0, 0.1785), (1, 0.1785), linestyle='dashed', linewidth=0.2, color='gray')\n",
|
|
"ax.axline((0, 0.1805), (1, 0.1805), linestyle='dashed', linewidth=0.2, color='gray')\n",
|
|
"\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e8b1e71d-cabf-4d79-a974-00073edab3f6",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.11.9"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|