Analiza_danych_L4.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from __future__ import division, print_function\n",
    "\n",
    "import pandas\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.mlab as mlab\n",
    "from  matplotlib import rc\n",
    "from scipy.optimize import curve_fit\n",
    "from scipy import stats\n",
    "# from scipy.stats import chisqprob, chi2\n",
    "# from scipy.constants import k as k_boltzman, e as e_charge\n",
    "\n",
    "import os\n",
    "import sys\n",
    "from datetime import datetime\n",
    "import cPickle as pickle\n",
    "from collections import namedtuple, OrderedDict\n",
    "import itertools as it\n",
    "from functools import partial\n",
    "from PIL import Image\n",
    "\n",
    "from uncertainties import ufloat\n",
    "from uncertainties import unumpy\n",
    "from uncertainties.umath import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "rc('font', family='Arial') #Plotowanie polskich liter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dir_path = 'data'\n",
    "\n",
    "data_labels = {\n",
    "    'natAzotOdKv' : (u'Natężenie lasera azotowego', u'w funkcji napięcia zasilania'),\n",
    "    'natAzotOdHz' : (u'Natężenie lasera azotowego', u'w funkcji częstości repetycji'),\n",
    "    'natAzotOdHg' : (u'Natężenie lasera azotowego', u'w funkcji ciśnienia azotu'),\n",
    "    'natBarw'     : (u'Natężenie lasera barwnikowego', u'w funkcji napięcia zasilania'),\n",
    "    'nat2Harm'    : (u'Natężenie drugiej harmonicznej', u'w funkcji napięcia zasilania'),\n",
    "    'nat2HarmOdDwojYellow': (u'Natężenie drugiej harmonicznej', u'w funkcji skrecenia kryształu dwójłomnego'),\n",
    "    'nat2HarmOdDwoj'      : (u'Natężenie drugiej harmonicznej', u'w funkcji skrecenia kryształu dwójłomnego'),\n",
    "    'nat2HarmOdFresnela'  : (u'Natężenie drugiej harmonicznej', u'w funkcji kąta skręcenia płaszczyzny polaryzacji'),    \n",
    "}\n",
    "\n",
    "data_labels = {key : value + (os.path.join(dir_path, key + '.csv'),) for key, value in data_labels.iteritems()}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "Labels = namedtuple('Labels', ['x', 'y', 'label_y', 'label_x', 'key'])\n",
    "Labels._title = lambda self: self.label_y + ' ' + self.label_x\n",
    "\n",
    "Data = namedtuple('Data', ['x', 'y', 'labels'])\n",
    "Data._names = lambda self: (self.labels.x, self.labels.y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "unv  = unumpy.nominal_values\n",
    "ustd = unumpy.std_devs\n",
    "\n",
    "uplot      = lambda x, y, *args, **kwargs: plt.errorbar(x=unv(x), y=unv(y), xerr=ustd(x), yerr=ustd(y), *args, **kwargs)\n",
    "ucurve_fit = lambda x, y, *args, **kwargs: curve_fit(xdata=unv(x), ydata=unv(y), sigma=ustd(y), *args, **kwargs)\n",
    "# def ucurve_fit(x, y, *args, **kwargs):\n",
    "#     popt, pcov = curve_fit(xdata=unv(x), ydata=unv(y), yerr=sigma(y), *args, **kwargs)\n",
    "#     return unumpy.uarray(popt, np.sqrt(np.diag(pcov)))\n",
    "\n",
    "myplot      = lambda xy,  *args, **kwargs:      uplot(xy.x,xy.y, *args, **kwargs)\n",
    "mycurve_fit = lambda xy,  *args, **kwargs: ucurve_fit(xy.x,xy.y, *args, **kwargs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def crop_image(filepath):\n",
    "    image=Image.open(filepath)\n",
    "    image.load()\n",
    "    image_data = np.asarray(image)\n",
    "    image_data_bw = image_data.min(axis=2)\n",
    "    non_empty_columns = np.where(image_data_bw.min(axis=0)<255)[0]\n",
    "    non_empty_rows = np.where(image_data_bw.min(axis=1)<255)[0]\n",
    "    cropBox = (min(non_empty_rows), max(non_empty_rows), min(non_empty_columns), max(non_empty_columns))\n",
    "    image_data_new = image_data[cropBox[0]:cropBox[1]+1, cropBox[2]:cropBox[3]+1 , :]\n",
    "    new_image = Image.fromarray(image_data_new)\n",
    "    new_image.save(filepath)\n",
    "    # http://stackoverflow.com/questions/14211340/automatically-cropping-an-image-with-python-pil\n",
    "\n",
    "def _Data_curve_fit(self, *args, **kwargs):\n",
    "    popt, pcov = ucurve_fit(self.x, self.y, *args, **kwargs)\n",
    "    return unumpy.uarray(popt, np.sqrt(np.diag(pcov)))\n",
    "\n",
    "def _Data_plot(self, loc = 4, title = False, fun = None, tight = True, show = False, crop = True, rc = [5,4], rc_multi = 1.5, dpi = 140, *args, **kwargs):\n",
    "    plt.clf()\n",
    "    myplot(self, label = self.labels.label_y, *args, **kwargs) \n",
    "    plt.xlabel(self.labels.x)\n",
    "    plt.ylabel(self.labels.y)\n",
    "    if title:\n",
    "        plt.title(self.labels._title())\n",
    "    \n",
    "    plt.grid()\n",
    "    plt.rcParams['figure.figsize'] = np.array(rc)*rc_multi   \n",
    "    if fun != None:\n",
    "        fun()\n",
    "    plt.legend(loc = loc)\n",
    "    if tight:\n",
    "        plt.tight_layout()     \n",
    "    if show:\n",
    "        plt.show()\n",
    "    else:       \n",
    "        filepath = os.path.join('plots',self.labels.key + '.png')\n",
    "        plt.savefig(filepath, dpi = 140) \n",
    "        if crop:\n",
    "            crop_image(filepath)            \n",
    "        \n",
    "def _Data_print(self, latex = False):    \n",
    "    if latex:\n",
    "        for x,y in zip(self.x,self.y):\n",
    "            print('{:L} : {:L}'.format(x,y))    \n",
    "    else:\n",
    "        for x,y in zip(self.x,self.y):\n",
    "            print('{} : {}'.format(x,y))    \n",
    "        \n",
    "Data._plot = _Data_plot\n",
    "Data._curve_fit = _Data_curve_fit\n",
    "Data._print = _Data_print"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def AnalyzeCSV(key, value, verbose = True):\n",
    "    df = pandas.read_csv(value[2], sep =';', decimal = ',', encoding ='cp1250')\n",
    "    if verbose:\n",
    "#         print df\n",
    "        df.plot(x=0, y=0, xerr='xerr', yerr='yerr') \n",
    "#         help(df.plot)\n",
    "    data = df.as_matrix().T\n",
    "    columns = list(df)\n",
    "    if verbose:\n",
    "        print(columns[0], columns[1])\n",
    "    single_column_zeros = np.zeros(data[0].shape)\n",
    "                                     \n",
    "    labels = Labels(x = columns[0], y = columns[1], label_x = value[1], label_y = value[0], key = key)\n",
    "    data = Data(x = unumpy.uarray(data[0], data[2]), y = unumpy.uarray(data[1], data[3]), labels = labels)\n",
    "    return data\n",
    "\n",
    "AnalyzeCSVwrapper = lambda key: AnalyzeCSV(key, data_labels[key], False)\n",
    "\n",
    "myData = {key: AnalyzeCSV(key, value, False) for key, value in data_labels.iteritems()}\n",
    "# map(partial(print, end=\" \"), myData['natBarw'].labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGoCAYAAAAemnx2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f9073c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "normalize = lambda y: y/y[y.argmax()].n\n",
    "\n",
    "# Uśrednienie pomiarów\n",
    "myData['natAzotOdHg'] = AnalyzeCSVwrapper('natAzotOdHg')\n",
    "x, y = myData['natAzotOdHg'].x, myData['natAzotOdHg'].y\n",
    "do_usrednienia = [100,150,200,125,250,300]\n",
    "for i in do_usrednienia:\n",
    "    i_m = i - 10\n",
    "    i_p = i + 10\n",
    "    if i in [125,150,300,200]:\n",
    "        warunek = (x>=i_m) & (x<=i_p) & (y>=750)\n",
    "    else:\n",
    "        warunek = (x>=i_m) & (x<=i_p)\n",
    "    mean = y[warunek].mean()\n",
    "    val_x = x[np.where(warunek)[0][0]]\n",
    "    y = np.delete(y, np.where(warunek)[0])\n",
    "    x = np.delete(x, np.where(warunek)[0])\n",
    "    y = np.append(y, mean)\n",
    "    x = np.append(x, val_x)\n",
    "\n",
    "myData['natAzotOdHg'] = myData['natAzotOdHg']._replace(x=x, y=y)\n",
    "# myData['natAzotOdHg']._plot(title = True,show=True, fun = lambda: plt.ylim(0,1200) ,fmt='None')\n",
    "\n",
    "myData['natAzotOdHg'] = myData['natAzotOdHg']._replace(y=normalize(y))\n",
    "myData['natAzotOdHg']._plot(title = True,show=False, fun = lambda: plt.ylim(0,1.1), loc = 3 ,fmt='None')\n",
    "\n",
    "# nalezy zaznaczyc jeszcze 4 punkty na kolorowo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGoCAYAAAAemnx2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XmYXFWZ+PHvm4SdYBRFQZG4ICNrCJFd0qAh0RC2AQUV\nSMCVUUEWR1RWNxRhAAFlRBZ/A6go4AASwtYsUZBVgXFYxOCAiCMOBAhLlvf3x72dVJrqTqerq6vr\n9vfzPP30vbfucuq+tbx1zrnnRmYiSZLUiBGtLoAkSWp/JhSSJKlhJhSSJKlhJhSSJKlhJhSSJKlh\nJhSSJKlhJhTDWESsFxGLIuLAbssPj4jz+rD90RExrY/H2iIi7u5vWWv2My0iTl3Obc6LiMMaPfZQ\nFBFrRMT1rS7HQIuIERHxy4j474g4uJ/7WK64R8TxEfGxcvruiFijP8dtVERcExGv6+O660TEcxGx\n6TLW2yIifjYwJVw+EfHvEbF5P7f9YUTsFBFrR8StA102DaxRrS6AWm4R8N2IuDkzH6lZ3pcBSnYC\nHujLQTLzLmB8P8rXfT9XAFc0up8KeR3wnlYXogneAkwCVstBGiwnM4+tmW74tdqAScux7i7AUZn5\n+95WKt9/H2qoVP03CfhBfzbMzE/UzG4/MMVRs1hDoReBk4GfRMSrEsyIWD8iZkXE7Ij4U0RcFhEr\nlr8aJwAnRcRuEbFCRJwSEXdGxD0RcW5ErB4Rbynn7y7/PxkRz5b7XqP8FXlHRNwbESdHxIjysRcj\n4tiIuDUi/hgRny+XHxARVyxr+55ExIERcVtE3FU+n0+Xy99Y/jK8s/w7ods2d5bbzIqId5XLzyt/\nRd8XEd/q6Vwtxzndstu5ejoibiq3eW9E/KZ8nr+NiMnl7s4FVi23iTrr7Vz+2v9bRLy93NeXImJO\nTXlmRcSUZcTjgxHx+/I450XE/0TEW8vHjo6IB8ptfhYRb+z2fPt0/Jr51YGrgRWAuyLi7VHUpL2u\nZp1FEfG6iJhYvkZ+XJbt/oiYWOecnxIR10bEqhGxWvn6fLBc/+s18Tysdv919rNV+fq5r3xN7LiM\nuL27fF3dUT4+vVy+Wnmu7i73c3YZv3PLQ90YEW+OiI0i4oaI+F257/1qtwc+DUyPiH/v9nq9v4zH\ndVG8BydGxH11ns/Ecr3Z5f5XiKIWsOs9cktEbFWue2xZ5pvLc/eTMlZdNSWX1rx2vlQu/zqwDnBh\nROwQEXMjYnTN8R+MiE2ieP9dFhF/KMv+2fLxGyNizyhqU5/rXn4NMZnp3zD9A9YD5pbTNwEnldOH\nA+eW098BPlJOjwJ+B+xRzt9YM3008O2afX8NOLPb8cYCjwGTyvkfAf9STo8AfgwcUc4vAj5TTo+n\nSHxWBA4A/rOX7Y+s8zzPAw4DVgNmA68tl29V8/y/CpxVTq8KXASMBnYoz83K5WOTgAdq9jur5jg9\nnqtu5VnmehTJ2hxgfYpaiL8CE8rHNgT+t4xfbQx7W+8c4OCauD0BvBNYA3iqLEfdeJT7/TuwcfnY\n/sBC4K3ADODWmvNzLHB1nee8zOP39Nos5xcCr+s+D0wEXgE2KZcfBtxYE58jgDOAn3cdgyKBvrCc\nXqEszw5dr5N6x6uJ1V+AKTWvy9/1EreRwP3AuPKxNYD7gC2BjwG/qjnXZwNvr3ntv7bc/hFgt3L5\n2sD/ULxu624PbAr8DVinfOzzwFnlefp9nbhMBOYDbynn3wn8niXvkQ3L57xKGdvHgNeXj10IfKec\nvh6YWk6vVM7vVc7/Cdi8nL4U+HQ5vRMwu2b5iTXn6ffl87kR2LP768G/oflnk4e6fAy4OyKu6bb8\nX4FJEXEk8C6KD7XVax6P8v8uwGsiYudyfhTFB1uxUsTrgZnAMZl5bc0274mIj5fzK1N8mHb5T4DM\nvDuKX/qrdStbve17rB7PzBei6POxS0SsD4yr2edM4KqIWA+4DvhSZj4XEVOBdwC/joiu5zomIsaU\n07Xtuss6V31aLyLeSfEB+5HMfDgiPgA8nJl3ls/jvyJiNtABdNbsd6s6691arnc58KmI+HF5vIuA\nnYF/ADMzc0FE9HQ+d6BIou4v9/vjiDitXGcKcF5mvlTOnwZ8JSJGZeaCmrIt8/h1zlOt6GX+sczs\n+vV9N0XS2eUw4A0UX+pdx3g/8IXyucwHdgSIiBm9HA9gE2BBZs4st70b2GzxBq+O27spXjvn1rx2\nVgE2B64BvhERNwLXAqdl5qPdjv8uYKXM/GV5vCcj4hcU5/z8btufmpmPRsQXKM7nX8ptTi/L9qpa\nmxr/k5mPl9OTgDcB19eUeQFFogFwSWb+vZz+EfBvEXEcRWLy2q7aHor31WYUiVzX84Eiufk2RRPI\nJ8t5gPdRJH9k5lyKxIglRVA7MKEQAJn5PxHxGeACil+mXX5C8QvoZ8CVFL9K673LRwKHZOY1ABGx\nKsUXEhGxCkW/hwsz84KabUYAe2fmg+V6r2HphOLFbsfoftyR3bZfg14Sioh4M/Abil9zt1B82E0t\nn/+dEfE2ii+bnYA7ImL38hj/LzOPqtnPOpn5TPlh93zNIfp6rnpcLyLWAn5FUdPSlazUa8YZQfHr\nuvuy7kaW611LUUswleJX37XAwcC8sjxd63Y/n1AkFN333RWn7stHln/dn3dfjr8sXedoBZaOc+3r\nJLsdu5OiVuqCiNgqMxdSfEEu3j4i3lKWY1mW2q7cdiPgD8DreXXcRgL/lzX9Mcr4PpOZr5QJSAfF\n6+26iPhsZl5as/se456Zj5VJ8cRy++sj4nN1ntvKFL/ue1P7Gh4JXJ+Z+9bs4y0UtRR7lvuvLctC\nlsR7m8x8udxmTV79/iUzr4ui2Wkn4L0UtV1Q1JLUlvttFLViaiP2odDiD9/M/DlF2/WhNY/vDJyQ\nmZeU625F8QECxYdL15faNcBnyzbYERS/Xr4VESOBS4D7M/Nr3Y59DcUvSCJiJYoaic8uq5y9bH9F\nL9tDUR39t8z8RllLMq3cNiLiWxS1J/+ZmYdSdDZdH5gF7BsRbyrXPZiiOreeSfR8rpa5XkSsBlwF\n/Cgzf1qz/m3ABhExoSzDRhQfxjdSxGDkstYrP+hvoqi2ngXcDGxD0dFtZrn9zDrn818ovpDXj4iN\ny8f+GRhD8QVwDTCjTCChqGK/ufzlv1gfj99dbcz/RhE/gH/uYf167szMM4H/A44vl10HHFDGfSWK\nxHKHPuzrQSAj4n0AETGe4rXQU9weBF6KiI+W669L0QSyRRR9d87PzGvLZPUaYONyu4UU76sHgVfK\nxJaIWIfiS/3acvvzum2/EcVr4v2xpB/LpylqBKD+e6i7G4CdI2KD8pgfpGiSW6l8fLeIGF2+xz9B\n0fz4HEWifkS5zRiK18xu5Ta1nxMA36dILi/MzFfKZddRNJ91/bC4niW1Il2srhjirKFQ91/0nwe2\nq1n+ZeDyiHia4ldcJ0ve6FdQXCGyInACRdv0PcCbKX6tHQ7sDXwAuDOKy0aj3PeHgUOA06LoLDaK\n4lfrd3ooV72ah88Dp/awfb1trwEOjIgHKX6V/Zaij8E7gVMpfsX+HniZ4kP04sycHxHfpvgQXwjM\nBfbooUy9nau+rPc5ymr1iPgw5bnKzPER8SHgjPKLeyEwPTP/WH6w3xMR/0URt73rrVce9zKKL6Qb\nMvOliLgXeLrmQ/2QeuczMxdGxEeA/1eeg7soviTmUSSObwF+W1aRPwJ8tM5z7svxu6s9v58HzoqI\n/yvL9WQP2/TkIIrzdCVFYnEaRYxHAD/JzMsjYrea9V/1eitrFfakeM1+l+J1sidF0tVT3HYv1/8q\nRRL2lcz8TUT8DphYxu0Fir4JXc1Il1I0pe0G7A58LyKOp0gcj8/MmyLijnrbZ+azUTSlXRMRWZ6n\nA4EN6j2nOs/xvyLikxSdtKGI87TMfLGcf4rivf16iqTwW+WmHwHOLN8/K1AkCxeXj10O/DQiPp6Z\n11HUgH6Xoqawy+eA75fnJYBvZOY93Zo8vDX2EBeZxkgDJ4o+Cu/KzJNbXRYNjCh65X8VOLZMBDYH\nrszMN7e4aAMqiv4JszLz7GWuvPz7/inw+cx8aqD3PVgi4lhgzcz8fIP72Rf4WGZO7cO6dwFf7mpK\n1dBmDYUG2msomj7+OzOvanVh1Liyc+orFLVM8ymuqti7xcUaUBHRSdEZ8QtNOsQawH9GxHt7qZGp\nvCg6ka7FMpqtyqbSP1A0Vc0ehKJpAFhDIUmSGmanTEmS1DATCkmS1LAh3Yei7KUsSZIGSWb26xLd\nIZ1QANjHo7qmT5/O+eef3+piqAmMbbUZ3+qKBkYntclDkiQ1zIRCLTN27NhWF0FNYmyrzfiqHhMK\ntUxHR0eri6AmMbbVZnxVjwmFJElq2JDvlClJA2Xs2LE89thjrS6G1HLrrbcec+bMGdB9DumRMiMi\nh3L5JLWXiPDKMYme3wvl8n5d6mGThyRJaphNHmqZzs5OO3dVVLvFtrOz+Oua7ip6R8eS6cHYh9TO\nTCgkDXu1X/oRSxKDwd6H1M5s8lDLtNMvWC0fY7v8HnvsMUaMGMG555671PKTTz6ZGTNmLHP7r33t\na1xxxRV9OtZdd93F+PHj+1XOWldccQWHHnrocm0zY8YMTjnllIaPPRTNnTuX973vfa0uRsuYUGjI\n6uyE444r/jo6lkz7y08DYXlfR/XWH4h91BoxYgRHHHEEjzzyyFLL+zIc8g033MD8+fP7VI4tttiC\nu+++u0/r9mbatGmceuqpDe+nKv7xj39wxx13tLoYLWNCoZbpXMana20ScdNNSycXGtqWFduhYCgm\nFKussgqHH344++yzDwsWLHjV4w8//DA777wz2223HW9729vYY489eOWVVzjrrLO48847OfLII/nl\nL3/J/PnzOeyww5gwYQKbb745Bx54IM8//zyPP/44m2++OePHj2fzzTdn7bXX5jWveQ1Q/LqeMWMG\n73nPexg3bhyHH344ixYtWlyu448/nu233553vOMdnH766QBccMEFTJs2bZnb9+Tcc89l6623Zost\ntuBtb3sbP/jBDwB46qmnmDx5MhMmTGDChAkcc8wxS20zYcIEtthiC3beeWceeughoKj52G233dhk\nk0046qijejxXfT2nv/3tb5c6V2uuuSYTJ04E4JZbbmGbbbZh3LhxbLnlllxzzTUAHHjggcybN4/x\n48eTma9ab9asWSxatIi11lqLRx99FIATTzxxqZFHd955Z2bOnNnr+fzVr37Fpptuyvjx45kxYwbr\nrrsuf/7zn4GipmqjjTZi3LhxfOhDH+Kpp57qNQYDKjOH7F9RPFXVjTfe2Od1fSm0l+WJ7WCq/Uw5\n9tie1qm/vN76A7GPLnPmzMnRo0dnZuYOO+yQRxxxRGZmfve7380ZM2ZkZuaRRx6ZF154YWZmzp8/\nPzfddNO89NJLMzOzo6Nj8fQJJ5yQX/ziFxfv+6tf/WoefPDBSx3vT3/6U771rW/NWbNmZWbmgQce\nmGeccUZmZi5cuDD322+/POmkkzIzMyLyrLPOyszMu+66K1deeeV8+eWX8/zzz89p06b1uP13vvOd\nVz3P6dOn58knn5zPP/98brvttvmPf/wjMzNvu+22xc//a1/7Wn7mM5/JzMwXXngh991335w7d27e\ndNNNucMOO+SLL76YmZmzZs3KDTfccPF+J02atPg4vZ2rWn1Z74477sj11lsvH3rooXz66afzjW98\nY95xxx2ZmfnAAw/k61//+pwzZ85SMextvYMOOijPPPPMxXFbZ5118uGHH85nn30211prrZw/f36P\n8Xj66adzzTXXzPvuuy8zMy+44IIcMWJEPvbYY3nuuefmdtttt/j8HHfccTllypRXPefMpd8LdZb3\n6zvbTplqGdvZq6sdYtvZWXSerKfe8vLH6YDvo57/+I//YPz48UyePHmp5d/+9re59tprOemkk3jo\noYd48sknef755xc/nuW4AldeeSXPPvsss2bNAmDBggWstdZai9f7+9//zpQpUzjhhBOYNGnS4m3u\nuOMOzjnnHABeeuklRoxYUom96667AjB+/HheeeUVXnjhhaXKVm/73ppqVlttNa644gquvPJKHn74\nYe69997F+5wyZQpTp07lscce4/3vfz8nnngio0eP5qqrruKPf/wj22677eLn+swzz/DMM88AsP32\n2/f5XPV1vUceeYQ999yTiy66iPXXX5+rr76a9ddfnwkTJgCw4YYbst12273qyqbbb7/9Vettv/32\ndHZ2svvuu3P22Wez//778+STT/KRj3yEWbNm8brXvY4pU6YwatSoHs/nzTffzEYbbcTGG28MwP77\n788hhxwCwMyZM5kxYwYrr7wyAIcccgjf+MY3WLBgAaNGNf/r3oRC0rDU0VG/CSIC6o19ddxxzdlH\nPeuuuy7f//73OeCAA9h///0XL99nn31YtGgRH/rQh9hll13485//XHdwooULF3LaaactTkjmzZvH\nSy+9BMCLL77ItGnT+OhHP8oBBxyweJtFixZxySWXsMEGGwDw7LPPLpVQrLLKKksdo/txFy5cuNT2\nc+fO7TWheOKJJ9hmm2341Kc+xXvf+1722msvrrrqKgAmTJjAn/70J6677jpuuOEG3vOe93D55Zez\ncOFC9ttvP771rW8t3s9f/vIXxowZA8Dqq6++3Oeqt/X+9re/8cEPfpCTTjppcbJSrxln0aJFr+q/\nUm+9hQsXMn/+fCZNmsTHP/5xrrrqKnbccUcmTZrEWWedxaqrrso+++zT4/kEuPnmm1+17644dV++\ncOFCFi5cOGiDudmHQi3TDu3s6h9j2z+1H/x77bUXH/jAB5bq9Dhr1iyOOeYY9t57bzKT22+/nYUL\nFwIwatSoxV9qkydP5owzzmD+/PksWrSIgw46iKOOOoqFCxey9957s/HGG3P00UcvdezJkycvvvri\n5ZdfZtddd+WMM85YZjl72n7atGk9bg9w5513stZaa/GVr3yFSZMmLb5CJTM56qijOOGEE9h11105\n9dRT2WijjRb3dbj44ov561//CsBZZ53V41UV1157bY/nqi/rvfDCC0ydOpWDDjqID3/4w4vX33rr\nrXnwwQe58847AXjggQe45ZZb2HHHHRk1atTiY/S23korrcTEiRM5/vjj2Xnnndlhhx34zW9+w623\n3sqUKVOAopam+/k888wz2W677Xj44Ye5//77AfjFL37BM888Q0QwefJkzjvvPObNmwfA6aefzg47\n7MAKK6zQYxwGkjUUkoal5W2Vqbf+QOyjVvdf9KeffjqzZ89evPyb3/wmu+++O2uuuSarrroqHR0d\ni68ImTZtGkcccQSvvPIKxxxzDIcffjibb745TzzxBB/84Ac5+eSTueSSS7j66quZMGHC4o6DEcFP\nf/pTTjvtNA455BA22WQTFixYwKRJk/jiF79Yt1z1ah5OP/10Dj300Lrb19t28uTJnHvuuWywwQas\nvvrqbLnllrzhDW/gkUce4dBDD+WAAw5g0003ZaWVVmKzzTZj3333ZYUVVuBf//VfmTRpEiNHjmSN\nNdbgsssuq1um3s5VX9b73ve+x3333ceoUaP46U9/uvhc3X333fzsZz/js5/9LPPmzWPkyJGcf/75\nvOMd72DRokVsvvnmbLjhhsyePZtLLrmk7noAe+yxB5deeik77bQTK6+8MuPGjWPNNddkxRVXBOC0\n006rez5HjhzJRRddxH777cfIkSPZYostGDVqFKuuuioHHXQQjz/+OFtuuSWZyTvf+U4uvPDC3l90\nA8h7eagt9FSFLC2PvtzLYyBea0Pl9XrFFVfw0EMPcfjhh7e6KBogzz33HF//+tc5/vjjWXnllbnn\nnnvYZZddeOKJJ5ZrP824l4c1FJJUUc8++yxnnHEG//RP/8TUqVNbXRwNgNGjR7PiiisyYcIEVlhh\nBVZccUUuueSSVhcLsIZCLbQ893sYKr/41DdD9V4ePf0q814eGm6soZCkJhiIL30TBw131lCoLVhD\noYHQlz4U0nDQjBoKLxuVJEkNM6FQyzhWQXUZW2n4sQ+FpGFjvfXW69OdO6WqW2+99QZ8n/ahUFuw\nD4UkNZ99KCRJUks1NaGIiK0i4sY6y6dFxG8jYnZEfLyZZdDQZTt7dRnbajO+qqdpfSgi4khgP+D5\nbstHAacAWwAvArMj4peZ+b/NKoskSWquZtZQPALsUWf5u4GHM3NuZs4HbgV2aGI5NEQtayTFej+C\n/GHUHobiKJkaOMZX9TQtocjMy4AFdR5aA3i2Zv454DXNKofalwmFJLWPVnTKnEuRVHQZDTzTgnKo\nxWyHrS5jW23GV/UMxjgU3S8/+QPwzogYA8yjaO44qaeNp0+fztixYwEYM2YM48aNW1zd1vWidr49\n5++9995eH7/88k6OPx6gmI/oZLPN4Ljjhkb5nXfeeefbfb5res6cOTSqqeNQRMR6wMWZuW1E7Aus\nlpnnRMRU4FiKZONHmfmDHrZ3HIph7Ljjij9YMg5F7TJJ0sAasncbzczHgG3L6Ytrll8FXNXMY0uS\npMHjwFZqmdoqt3rqdSS3c3l7WFZs1d6Mr+oxodCQZUIhSe3De3moLXgvD0lqPu/lIUmSWsqEQi1j\nO2x1GdtqM76qx4RCkiQ1zD4Uagv2oZCk5rMPhSRJaikTCrWM7bDVZWyrzfiqHhMKSZLUMPtQqC3Y\nh0KSms8+FJIkqaVMKNQytsNWl7GtNuOrekwoJElSw+xDobZgHwpJar5G+lCMGujCaOjr7Cz+uqa7\n7uDZ0eHdPCVJ/WMNxTDXyl/+nZ2ddPQxg7GGor0sT2zVfoxvdXmVhyRJailrKIa5ofzL36YZSRpc\njdRQmFAMc0M5oZAkDS6bPNSWvJa9uoxttRlf1WNCIUmSGmaTRx3Dqe3eJg9JUhf7UDS1DNX+wq36\n85Mk9Z19KNSWbIetLmNbbcZX9ZhQSJKkhtnkscwyVLtJoOrPT5LUdzZ5SJKkljKhUMvYDltdxrba\njK/qMaGQJEkNsw/FMstQ7T4GVX9+kqS+sw+FJElqKROKYaq2CbRVzaFVb4ft7ITjjiv+OjqWTFf8\naQPVj+1wZ3xVz6hWF2A4GIpDedeWo3ZaA6c2vhHDI5GQNHyZUAwCv1jq6zCLqSxjW23GV/XY5DFM\ndXYWyU3XtCRJjTChGKY6OpZc3dG6ZpfO1hxYTWdsq834qh4TCkmS1DDHoVhmGQZ2nIahMu5DV0fM\nCLjxRjtlNttQibsk9cZxKJqk9sqMqqlNIEwmJEmNMqHoRZUTiqHAdtjqMrbVZnxVjwmFJElqmH0o\netHRATfdBBMnDlwtxVBrSx9q5akqz7OkdmAfiiapHdFSkiT1zIRCLWM7bHUZ22ozvqrHhKIX1lBI\nktQ39qFYZhmqOQ5Fl6FWnqryPEtqB/ahkCRJLWVCoZapejtsb0+v4k+98rEd7oyv6qns7cs7O5ce\nmKq2P0Trboa15L/9Mqqvtzj7GpBUNZVNKGoTh4ih8YvQhGJpHZ6EyjK21WZ8VU9lEwqp1To7i2S2\nS+30xImDXhxJair7UAwi7w2ytKq3w3Z0FFd2dF3d0TWdWf0aqqrHdrgzvqrHhGIQOa6FJKmqTCjU\nMlVvh+3t6VX8qVc+tsOd8VU9w2Jgq0YGFRrIAYk6O2HHHeHGG1v7hTIUr4CpOge2ktQOGhnYyoSi\nidsOxv7aWWdn57D5pTPc4j6cYjscGd/qcqRMSZLUUtZQNHHbwdif2oNxl9QOrKGQJEkt1bSEIgrf\nj4hfR8QNEfH2bo9/NCLuiojbI+LTzSqHhi6vZa8uY1ttxlf1NHOkzN2BlTJz24jYCjilXNblJODd\nwDzgvyLi4sx8tonl6bPaqyAmToTjjiumvQpCkqT6mtaHIiJOBm7PzJ+V849n5ltqHr8a+AzwD+Au\nYIvMnNttHy3vQzHQhlJZNHiMu6R20EgfimbWUKwB1NY4LIiIEZm5qJx/gCKReB64tHsyIUmS2kcz\nE4q5wOia+cXJRERsAkwF1gNeAC6MiH/OzF9038n06dMZO3YsAGPGjGHcuHGLr3/uasdb1jws3/r9\nme/shPPPL+bnzOmgowPmzOlk3Dg49NDBL087zJ966qn9iqfzQ3++to19KJTHeePrfP35ruk5c+bQ\nqGY2eewJ7JKZB0bE1sDRmTm1fOytwGXA1pk5PyJOBe7PzHO67aMtmzx6O55V30t0DqPBcYZb3IdT\nbIcj41tdQ3KkzIgI4Cxg03LRDGALYLXMPCciPgUcCLwM/BH4RGYu6LYPEwpVgnGX1A6GZEIxEEwo\nVBXGXVI7cGArtaXaNjxVi7GtNuOrekwoJElSw2zyaAKbPNSdcZfUDuxDscz9mFBo8NWOuNrZuWSU\nVUdclTRUmVAscz+tTSj8YqnPS8+qy9hWm/GtrqE6UuaQNphf8sM9cZAkVZ81FH14fKCPJ0nSUORl\no5IkqaVMKNQyXsteXca22oyv6jGhkCRJDbMPRR8eH+jjSZI0FNmHYgipvXJEkqThwoRigJlQ9J3t\nsNVlbKvN+KoeEwpJktQw+1D04fHl0dEBN90EEydaSyFJai/2oRhCakfclCRpuDChUMvYDltdxrba\njK/qMaEYYNZQSJKGo8r2oViem385DoUkSd6+fACOY0IhSZKdMhtgU2Dr2A5bXca22oyv6jGh6Gx1\nCSRJan/DvsnjuOPg+ONt8pAkySaPBlhDIUlS44Z9QuHlna1jO2x1GdtqM76qZ9gnFJIkqXHDvg9F\nZyfsuKN9KCRJchyKho9jQiFJkp0y1ZZsh60uY1ttxlf1mFBIkqSG2eSBTR6SJIFNHpIkqcWsoWBg\nahSW5+6mKnR2dtLhyakkY1ttxre6GqmhGDXQhRmuTBwkScOZNRTY50GSJLAPhSRJajETCrWM17JX\nl7GtNuOrekwoJElSw+xDgX0oJEkC+1BIkqQWG7Y1FI4b0Xpey15dxrbajG91OQ5FP5g4SJI0cIZt\nDYUkSVqafSgkSVJLmVCoZbyWvbqMbbUZX9VjQiFJkhpmHwpJkgTYh0KSJLVYjwlFRLxrWX+DWVBV\nj+2w1WXNW0deAAAWTUlEQVRsq834qp7exqG4HbgH6KnqYzPgdQNeIkmS1HZ67EMRET/MzE/0uOEy\nHh8I9qGQ2pMj0UrtqZE+FMvdKTMi3pKZj/fnYMvLhEJqf958T2ofg90p8xv9OZDUne2w1WVsq834\nqp7lTigy84BmFESSJLWvZTZ5RMQx3Zdl5glNK9HSx7bJQ2pzNnlI7aPZdxt9qus4wHgcu0KSJHWz\nzOQgM88u/36QmZ8E3jwI5dIwYDtsdRnbajO+qmeZNRTdBrBaG1ivecWRJEntqC99KG6smX0R+F5m\nXt3UUi05tn0opDZnHwqpfQzqOBR93nFEAGdRjKj5EvDxzHy05vH3ACeXs38FPpaZr3TbhwmF1OZM\nKKT2MajjUETEGX1cdXdgpczcFjgKOKXb4/8OTM/MHYCZ2JQy7NgOW13GttqMr+rpzxUbZ/Zxve0p\nEgUy83ZgQtcDZb+Mp4HDIqITeF1mPtyPskiSpCGgt3t5vCUzH+/hrqKvAI/11h4RET8Efp6Z15Tz\nc4C3Z+aiiNgWuBbYHHgUuBI4MTM7u+3DJg+pjdTet6NL9yaPeutIGhqaNQ7FYeXf2XUeWwFYAHT0\nsv1cYHTN/IjMXFROPw08kpkPAUTETIoajM7uO5k+fTpjx44FYMyYMYwbN46O8tOoq9rNeeedHxrz\n55//6se7Pia65js7O+joGBrldd754T7fNT1nzhwa1VsNxT6Z+ZMeN4x4MDM36OXxPYFdMvPAiNga\nODozp5aPrQD8NzApMx+NiF8A53S/esQaimrr7Oxc/OJWNRx3XPFXG9vuNRRd66h9+d6trmbVUBwf\nEWv08viyvukvAyZFxOxyfkZE7AuslpnnRMRBwMXFxSD8erAuRZXUPJ2dRQLRXe2yiRMHrTiSBlFv\nNRTHLmvjzDx+wEu0dBmsoZDaSL3aB2sopPbRlBqKZicLkiSpOrzRl1qmtlOQqqGrWb232Nr03v58\n76oeEwpJA6YvyYIJhVRNfbmXx2jgX4F1KMaL+H1mPjIIZbMPhVQBDr0ttY9mD719LsXgU+tT3HPj\nR/05kCRJqq6+JBRrZua5wPzM/HUft5GWyXbY6jK21WZ8VU+fkoOI+Kfy/1soRsiUJElarC99KDah\nuDPouylGtzw4M+8ehLLZh0KqAPtQSO2jkT4Uy0woWsmEQmp/JhRS+2hKp8yI+Hn5/8mI+Ev592RE\n/KW/BZVq2Q5bXca22oyv6ultpMy9yv9rD15xJElSO+pLH4pxwCeBlbuWZeaBTS5X17Ft8pDanE0e\nUvto1t1Gu5wPnAH8T38OIEmSqq8vl43+NTPPycxruv6aXioNC7bDVpexrTbjq3r6UkMxJyK+BNwD\nJEBmzmpqqSS1tXvvha7vnIkTl9yuvKPDe3lIVdWXPhTndVuU9qGQJKl6mj4ORUS8C3gn8HvgL5m5\nqD8HW14mFJIkDZ6m3hwsIj4LfB/4BvDPwOn9OZDUne2w1WVsq834qp6+dMrcB5gEPJOZpwFbNbdI\nkiSp3fSlD8Wvge2A6zNzp4i4NTO3H5TC2eQhSdKgafY4FBcDNwPrRcSvgMv7cyBJklRdy2zyyMzv\nUYyUeTjwJeCcZhdKw4PtsNVlbKvN+KqevnTK/COwYmZekpm/By5tfrEkSVI76bEPRUTsnJmzIuJ3\nwP8Bx2fmjRFxY2buOCiFsw+FJEmDpll9KD4AzAKeBvYALouINwAL+nMgSZJUXT02eWTmF8rJyMxn\ngV2A6cBmg1AuDQO2w1aXsa0246t6+nKVx1EAmTkvInYDDmlukSRJUrvpyzgUbwFOBNYCLgF+n5m3\nD0LZ7EMhSdIgaurQ28DZwLnAChTjUfywPOjh/TmgJEmqnr4kFKtk5g0Udxl9ECAizqfoqCn1m+2w\n1WVsq834qp6+9KF4KSImAyMjYmuKu41Ob26xJElSO+lrH4rvApsAfwCOyMw5zS+afSgkSRpMze5D\nMSUz98nMjTJzL2DX/hxIkiRVV48JRUTsGxEXA1+PiIvKv58Anxq84qnKbIetLmNbbcZX9fTWh2Im\n8CSwJsWVHgCLgD82u1CSJKm9LLMPBUBErE1x2WgA62Tmb5pdsPK49qGQJGmQNOteHl07/xGwDbAa\nsCpFDcXW/TmYJEmqpr50ytwM2Ai4Bng38FJTS6Rhw3bY6jK21WZ8VU9fEoqny3aH1TLz780ukCRJ\naj99GYfim8A/gDcC6wJvy8ytBqFs9qGQJGkQNdKHoq+dMkcDLwIfAH6bmU/152DLy4RCkqTB05SB\nrSJi/64/ivt2fAR4LTC5f8WUlmY7bHUZ22ozvqqnt6s83t1tPoAZwDzgx00rkSRJajt9bfJ4B3AB\n8CBwaGY+1+yClce1yUOSpEHS7HEo/gU4FPhCZl7Zn4NIkqRq660PxZsjYhbwXmBLkwkNNNthq8vY\nVpvxVT291VA8ALwM3ACcGbGkBiQzP9LkckmSpDbSYx+KiJjY00aZeVPTSrR0GexDIUnSIGn6OBSt\nYkIhSdLgaco4FFKz2Q5bXca22oyv6jGhkCRJDbPJQ5IkATZ5SJKkFjOhUMvYDltdxrbajK/qMaGQ\nJEkNsw+FJEkC7EMhSZJazIRCLWM7bHUZ22ozvqrHhEKSJDWsaX0oorib2FnAZsBLwMcz89E6650N\nPJ2ZX67zmH0oJEkaJEO1D8XuwEqZuS1wFHBK9xUi4lPAxk0sgyRJGgTNTCi2B2YCZObtwITaByNi\nG+A9wNlNLIOGMNthq8vYVpvxVT3NTCjWAJ6tmV8QESMAIuJNwLHAZ4F+Va1IkqShY1QT9z0XGF0z\nPyIzF5XTewNrAr8C1gZWiYj/zswfd9/J9OnTGTt2LABjxoxh3LhxdHR0AEuyZOfbc75r2VApj/MD\nN9/R0TGkyuO88XW+/nzX9Jw5c2hUMztl7gnskpkHRsTWwNGZObXOegcAG9gpU5Kk1hqqnTIvA16O\niNnAycAXImLfiPh4E4+pNlKbIatajG21GV/V07Qmj7Jq4TPdFj9UZ70LmlUGSZI0OLyXhyRJAoZu\nk4ckSRomTCjUMrbDVpexrTbjq3pMKCRJUsPsQyFJkgD7UEiSpBYzoVDL2A5bXca22oyv6jGhkCRJ\nDbMPhSRJAuxDIUmSWsyEQi1jO2x1GdtqM76qx4RCkiQ1zD4UkiQJsA+FJElqMRMKtYztsNVlbKvN\n+KoeEwpJktQw+1BIkiTAPhSSJKnFTCjUMrbDVpexrTbjq3pMKCRJUsPsQyFJkgD7UEiSpBYzoVDL\n2A5bXca22oyv6jGhkCRJDbMPhSRJAuxDIUmSWsyEQi1jO2x1GdtqM76qx4RCkiQ1zD4UkiQJsA+F\nJElqMRMKtYztsNVlbKvN+KqeUa0ugCSpGjo7i7+u6Y6OYrqjY8m0qss+FJKkARcBfny3H/tQSJKk\nljKhUMvYDltdxrbajK/qMaGQJEkNsw+FJGnA2YeiPdmHQpIktZQJhVrGdtjqMrbVZnxVjwmFJKlf\nGskrzEmqx4RCLdPhSDeVZWyrrSu+JhSqZUIhSZIaZkKhlrEdtrqMbbV1xbezs7iao94f9PxYhDUU\nVWRCIUnql46O4tLQen/Q82OZ3tujikwo1DK2s1eXsa0246t6TCgkSf3SSF5hTlI9JhRqGdvZq8vY\nVltXfE0oVMuEQpIkNcx7eUiSBpz38mhP3stDkiS1lAmFWsZ29uoyttVmfFWPCYUkSWqYfSgkSQPO\nPhTtqZE+FCYUkqQB0dm5ZEjtzs4ll4Z2dHiZaLswoVBb6uzsdMS9ijK21WZ8q8urPCRJUktZQyFJ\nkgBrKCRJUouZUKhlvJa9uoxttRlf1dO0hCIK34+IX0fEDRHx9m6P7xsRt0XELRFxVrPKIUmSmq9p\nfSgiYg9gWmYeGBFbAUdl5u7lYysD9wEbZ+bLEXERcFFmXtltH/ahkCRpkAzVPhTbAzMBMvN2YELN\nYy8D22bmy+X8KOClJpZFkiQ1UTMTijWAZ2vmF0TECIAs/C9ARHwOWC0zr2tiWTQE2Q5bXca22oyv\n6hnVxH3PBUbXzI/IzEVdMxERwHeA9YE9m1gOSZLUZM1MKGYDuwA/j4itKfpM1Pp34MWufhU9mT59\nOmPHjgVgzJgxjBs3bvEIbV1ZsvPtOd+1bKiUx/mBm+/o6BhS5XHe+Dpff75res6cOTSqmZ0yAzgL\n2LRcNAPYAlgNuAu4A7ilfCyB0zLzl932YadMSZIGiffyUFvq9H4AlWVsq834VtdQvcpDkiQNE9ZQ\nSJIkwBoKSZLUYiYUapnaXsaqFmNbbcZX9ZhQSJKkhtmHQpIkAfahkCRJLWZCoZaxHba6jG21GV/V\nY0IhSZIaZh8KSZIE2IdCkiS1mAmFWsZ22OoyttVmfFWPCYUkSWqYfSgkSRJgHwpJktRiJhRqGdth\nq8vYVpvxVT0mFJIkqWH2oZAkSYB9KCRJUouZUKhlbIetLmNbbcZX9ZhQSJKkhtmHQpIkAfahkCRJ\nLWZCoZaxHba6jG21GV/VY0IhSZIaZh8KSZIE2IdCkiS1mAmFWsZ22OoyttVmfFWPCYUkSWqYfSgk\nSRJgHwpJktRiJhRqGdthq8vYVpvxVT0mFJIkqWH2oZAkSYB9KCRJUouZUKhlbIetLmNbbcZX9ZhQ\nSJKkhtmHQpIkAfahkCRJLWZCoZaxHba6jG21GV/VY0IhSZIaZh8KSZIE2IdCkiS1mAmFWsZ22Ooy\nttVmfFWPCYUkSWqYfSgkSRJgHwpJktRiJhRqGdthq8vYVpvxVT0mFJIkqWH2oZAkSYB9KCRJUouZ\nUKhlbIetLmNbbcZX9ZhQSJKkhtmHQpIkAfahkCRJLWZCoZaxHba6jG21GV/VY0IhSZIaZh8KSZLa\nUGdn8dc13dFRTHd0LJleXo30oTChkCSpzUXAQHxd2ilTbcl22OoyttVmfFVP0xKKKHw/In4dETdE\nxNu7PT4tIn4bEbMj4uPNKoeGrnvvvbfVRVCTGNtqM76qp5k1FLsDK2XmtsBRwCldD0TEqHL+/UAH\n8MmIeEMTy6Ih6Jlnnml1EdQkxrbajO/gGcjKoGZXLDUzodgemAmQmbcDE2oeezfwcGbOzcz5wK3A\nDk0siyRJbceEorAG8GzN/IKIGNHDY88Br2liWTQEzZkzp9VFUJMY22ozvqqnaVd5RMTJwG8y8+fl\n/J8z863l9CbAiZk5tZw/Bbg1My/ttg8v8ZAkaRD19yqPUQNdkBqzgV2An0fE1sB9NY/9AXhnRIwB\n5lE0d5zUfQf9fVKSJGlwNTOhuAyYFBGzy/kZEbEvsFpmnhMRhwGzgADOycwnm1gWSZLUREN6YCtJ\nktQehuTAVssaw0LtJyLuKmN5Q0T8KCLeERG3RMRNEXFmq8un/omIrSLixnK6bkwj4hMRcUf5fp7a\nutJqeXSL7biIeLzmPbx3udzYtpmIGBURP46ImyPitnJMqAF57zazyaMRi8ewiIitKMas2L3FZVI/\nRcRKAJm5U82yXwJfzsxbyuRxt8z8ZcsKqeUWEUcC+wHPl4tOoVtMgduAzwHjgVWBWyNiVnm5uIao\nOrHdAjg5M/+tZp03Ymzb0ceAv2fm/mU/xt8B9zIA790hWUNB72NYqP1sBqwWEddExHVlkjg+M28p\nH7+aYpAztZdHgD1q5rfoFtNJwJYUV3AtyMy5wMPApoNbTPXDq2ILTC1/wf4wIlbH2LarnwFHl9Mj\ngQW8+vO4X+/doZpQ9DaGhdrPPOCkzJwMfAa4kKIzbhfHIWlDmXkZxYdRl+4xXQMYzdLv5ecx1kNe\nndjeDhyZmROBR4FjefXntLFtA5k5LzNfiIjRwCXAVxig9+5Q/ZKeS/FkuozIzEWtKowa9hBFEkFm\nPgw8Dbyx5vHRgGP5tr/a92hXTOdSfDh1X672cnlm3tM1DYyj+LIxtm0oItYFbgAuyMyfMEDv3aGa\nUMwGPghQZwwLtZ8DgZMBImIdihfprIiYWD7+AeCWHrZV+7g7IrqG0O+K6R3A9hGxYkS8Bvgn4P5W\nFVD9dk1EdDU9vw+4C2Pblsq+L9cAX8zMC8rF9wzEe3eodsp81RgWrSyMGvYj4LyIuIUiE55OUUtx\nTkSsQDHQ2c9bVzwNkCOAH9bGNDMzIk6nuF9PUHT8eqWVhVS/fAb4XkS8AvwV+GRmPm9s29JRwBjg\n6Ig4BkjgEIr4NvTedRwKSZLUsKHa5CFJktqICYUkSWqYCYUkSWqYCYUkSWqYCYUkSWqYCYUkSWqY\nCYXUhiJio4i4MiKuj4jbI+K4AdrvuhGxyzLW+UREjIyIiRFxcbmsoXFEImL9iPh6eR1817LREXFK\nRKxZZ/1XImJmRKwXEb/p9tinyuvr6x3nXyLiTxHxyUbKK+nVTCikNlOOWncx8PnMfB+wNbDxAH1J\n7gRst4x1vkxxUyEoBsUhM/dq5KCZ+XBmfrX2ToaZ+VxmHpaZT9fZ5O+ZOaW2DH08zpnAeY2UVVJ9\nJhRS+9kNuD4zHwXIYnS6/YFzI2L3iLgxIm6IiIcj4nqAiPhmRNwcEbMj4p/LZQdHxG3lslPLG/B9\nCdg3InaJiHERcUu5v6vL2osDgTcBP6ktUEQ8GRGbRMQV5fw+EfG7cnrbiPhBRLwmIq4o71h5a0R0\nlI9/oyzDbeVts4mIrSLi1+Wyn0fESr2cj6i7MGLrmnNxX0T8sbf1JTVmqA69Laln61Dc8XGxzJxX\nTl4OXB4RY4GfAgdExBRgbGbuUH4x3xYR1wEHAAdn5l0R8aly+xOBDTLzyoi4AzgwM++LiF2BUzJz\n74j4KvBhYNuli5D3RcRby2aLKcDCiFiLIgG6FPgqMCszv1fe0+VW4O3AvkAHxZDOB5T7+wHw4cx8\nKCJmAO8G7u3hfGwYETeU0wGsDVyUmbcBO0bEa4ErgI8t+9RK6i9rKKT28xjw1toFETE2It5bTr+J\n4rbEMzLzcWATYEL5pTuT4ofEehQ3bftsRNxYznf/PFgnM7tuzHczsGHX4ej5V/41FM0m61LcYfb9\nwPbA9RRJwc0AmfkXYG5EvIHii/7bZdnGlPt5U2Y+VK57Xmb2lEwAPJCZO5V/OwL/VnNeVqdIso7O\nzN/1sg9JDTKhkNrPlcDkiHg7QFkjcAqwUdm/4jLgC5n5X+X6/w3ckJk7UXzZ/wz4I/AJ4FPll/B4\nYBuKm7d1fS48ERGblNMdFLehp1ynqw9Fl64E43KKZpPfUSQXnwMeycyFFDcd2qEs85spkodngL0z\nc9+yfDMi4q3lsd9RrvvFiNitl/PRU5PHihQ3nTsjM2/sZXtJA8AmD6nNZOZzEXEAxZ09AxgN/Gdm\n/iAizqCo8j82IkYBL2fmlIjoKO/2uj7FF+wLEXEfcGtEPAc8DtwOPAd8OSLupkg4zigOwQLgoLII\ntwBXAcfXFqv8/xvgXcCJmXl/RKwLfKt87JsU/Tz2AlYGPpGZ8yPiHxFxGzAPmJmZf46IT1PcoXYh\n8CQ1tQ71TkkPyz8PbA58MiIOLtfbs5f9SGqAdxuVhomI+AxwT9m3oK1FxJOZuXY/tz0WeDIz/32A\niyUNazZ5SMPHisB3I6J7c0U7em1EzFzejSLiX1jS8VPSALKGQpIkNcwaCkmS1DATCkmS1DATCkmS\n1DATCkmS1DATCkmS1DATCkmS1LD/Dzz2T/oTshHWAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d9e9208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ustawienie jednostek umownych dla natAzotOdHg\n",
    "myData['natAzotOdHz'] = AnalyzeCSVwrapper('natAzotOdHz')\n",
    "myData['natAzotOdHz'] = myData['natAzotOdHz']._replace(y=normalize(myData['natAzotOdHz'].y))\n",
    "myData['natAzotOdHz']._plot(title = True, fun = lambda: plt.ylim(0,1.1), loc = 1, fmt='None')\n",
    "# niepewnosc z ostatniego zostala przeniesiona na pozostale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGoCAYAAAAemnx2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIlI2FRQiIiJStv8HM3orOyeXfO0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f09c748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ustawienie jednostek umownych dla natAzotOdKv\n",
    "myData['natAzotOdKv'] = AnalyzeCSVwrapper('natAzotOdKv')\n",
    "myData['natAzotOdKv'] = myData['natAzotOdKv']._replace(y=normalize(myData['natAzotOdKv'].y))\n",
    "myData['natAzotOdKv']._plot(title = True, fun = lambda: plt.ylim(0,1.1), loc = 4, fmt='None')\n",
    "# niepewnosc z ostatniego zostala przeniesiona na pozostale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGoCAYAAAAemnx2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3Xu8XPO9//HXJ4lrJNI6pUErSjlKrqIuDRkh4hYSl1O0\n5MLhUNUQVNqSRFuU0ghSVINqqbokGiSijVH3uqVUe4hL9CD0V5rEJXLZ+fz+WGt2JrNndmbvuaxZ\n3/1+Ph7z2LMus+bzXjN77++s73fWMndHREREpBKdki5ARERE0k8NChEREamYGhQiIiJSMTUoRERE\npGJqUIiIiEjF1KAQERGRiqlB0QGY2TZmttrMxhbMH29mN5bx+PPNbHiZz7WrmT3X3lrztjPczKa0\n8TE3mtlZlT53tSRdj5n1NLNH4/sTzWxqUrXUg5kNNbOFZvaUmW3QjsdvY2YftmH9/P17ipmd29bn\nbCszm2xm32znY3c1s99Vu6Y2PP9zZtbdzEaZ2awKtlOXfS1t1yXpAqRuVgM/NbM/ufurefPLORHJ\nEOClcp7E3Z8FBrSjvsLtzALa/UdHwN0XAYOSrqOOjgGud/eLKthG2Sfmyd+/7n5dBc9ZNnefWMFj\nnwX+q4rltPX5BwCYGbRhPxfZTl32tbSdjlB0HMuAy4HfmlmLhqSZfdnM5prZY2b2hpnNMLP1zew0\nYCBwmZkdbmbrmdkVZvaMmT1vZtPNbBMz2zqefi7+ucjMlsTb7h5/Wn/azOab2eVm1iletiz+9Pyo\nmb1mZmfE85s/xbT2+FLMbKyZPWlmz8Z5/ieev4WZPRDX/4yZXVjwmGfix8w1sx3i+Tea2T1m9qKZ\nXVxqX5UoZW8ze8LM/mpmP8vLXVjfKXm5/xTXMc/M/mlmX4qXnWdmC/PqnWtmB5rZQ2Z2kZk9HG/r\nV/Hyop+4zWxc/DptbmZdzGyqmb1kZn8xs+vj1/MMM7slXr+LmS0xs9Hx9F5m9lR8f3hejkfMbI94\n/kZmdrOZvRwvv9HMpsfLdo6z/SV+rxxfpMaynj9v/bOBEcCpZvaT+D11Vd7y5iM0pfZXwfZ2MrPX\nzezwePrQuNb58eveJ3//Fj5fwfPeaGZzzOzv8XN+Pm+bj5nZny06snJhPH9wPG9GvI+eMLMd42XN\nR73iGh+w6Pfiudz+yXt//TWu9w8W/X4ONrMX4+U7WBnv4bju5+LbAjNbZWbbWSu/AxYdRZkfZ5ht\nZlvE81eb2WcLtr9HvE+eiPfBL+L525jZq/F78ykze8XMji7yWhbdh5IQd9ct8BuwDbA0vv8wcFl8\nfzwwPb5/KXBcfL8L8BdgZDz9UN7984Gf5G37h8A1Bc/XC3gTGBpP/xL4Vny/E/Ar4Ox4ejVwanx/\nAFHDZ31gFPD7Vh5/TpGcNwJnAV2Bx4DPxPN3z8v/A2BafH9j4FagG7BPvG82jJcNBV7K2+7cvOcp\nua+K1PNnYMN4vXnAKeuobxTwL6BrPH0DcFre6/A2sD3QHXgv3u5DwG/jdTYB3gIGF7zuE4GrgHOA\nR4Bu8fzJwB1Ap7x9PQ34IrAonjc4ft5fx9M/Ac6O63ghL8dXgHeAjYCL89bvBswHpgOdgVeBw+Nl\nPYH/A3Yv2HfrfP5Sr39e3ql5y5qn17W/gJ2BBUAmXmdz4N9A73h6JHBfkf07tUhNE+Nt5V7Pe4CJ\n8f0/Atvl7YeVwGfjWlYCe8XLTgGeLniPdwb+CvSL53cHXgS+CvQB/glsGS87I35NBwMvtOU9nJdj\nfSDLmt/boo8HtgYWA+vFy84EDovvN8X58n+3fwPsE9/vGtfdP963q4GD4mVHAG8UeS2L7sOk/+Z2\n1Ju6PDqebwLPmdkDBfO/Cww1s3OAHYh+OTfJW27xz0OBTc3sgHi6C9EfgWgls/8A5gAXuPuDeY/Z\nzcxOiqc3JPpjkfN7AHd/Lv6U07WgtmKPL3nI1N0/tmjMx6Fm9mWgX9425wD3mdk2wB+A89z9QzM7\nBNgOeNzMcll7mFmP+P6jeU+xrn2V7xZ3/zTeN78GDnb361qpD6I/+h/H92cCp8SfonsSNYAOAD4A\n5rj7qrjcWXH2j8zsVaI/3AsLajkS2AIY7u65IxcHAt9z99zrcRUww91PM7O3zGxgvM7FwHnxOocD\nB8XzPw/8MW+frQK+HC8/M67pQzO7Gegd768N3P2eeNkiM7sr3lbzUQd3/0cZz1+JUvtrQ6KG38Pu\nno3X/Rrworu/GD9mBjAjfg+VI5v3ej4fPxfAYUTvgW8AO8Xzcu+Dv7j74/H96cDVZvaZvG3uQPR+\nnZ637zci+me8MdF745243tyn+cF5jy/7PRxv/zfA39z9p+t4/NtEjcfnzWw2MNvd57Wyb0YDB5vZ\nBOA/4wybEL2/V7j77Hi951iz3/KV2ocftPKcUiNqUHQw7v5/ZnYqcDPRJ/2c3xJ9+v8dcC/RJ0Rr\nuQU6A99x9wcAzGxjoj/CmNlGRH+of+PuN+c9phNwtLu/HK+3KWs3KJYVPEfh83YueHx3WmlQmNlW\nwBPAdUSfxu8EDonzP2Nm2wL7E40NedrMRsTPcYu7T8jbzpbuvjj+e/1R3lOUu68g+lSWn2tla/XF\n8p/rQaKjFIcQfbJ+EDgN+CSuIyd/H3qJel4BvgX83Mx6u/tSWnZ7dgbWi+/fDRxMdLTmEOA4M/s6\n8Im7v2FmnYE/uvuxzQHNtiY6SrGqoIbcfuhUpLZOec+Zr9XnL7J+vsJ9UHg4v9T+cqKuk1vMbIS7\nz4yzrPV+M7PeREczytHiueLfm/nAXUTvgenx8+Y3zHJy+yz/vdQZ+LfH4xLimjYHlgAn59drZhsS\nfeLP15b38FSi3/Fvrevx7u5Axsx2Jfod+5mZzXP3M0ts/1GiRtaceFu75623Im+9Fu/pMvah1JnG\nUHQczb9k7n4nMBsYl7f8AOBCd78jXnd3oj9aEP1xy/3BfwA43aKxFJ2IDpFfHP9zuQP4q7v/sOC5\nHyA6TItFo+9/D5y+rjpbefysVh4P0ZiPf7r7j+OjJMPjx5qZXUx09OT37j6OaLDpl4G5wLG2pn/7\nNKLDqcUMpfS+KnSMRWNRNiT6NDa7tfoKH+zuy4m6YibGNf4J2JNoMOCcVvZBMS/En67/SHQIHKJ9\n+z8WjVPoRNRYyR1ZmgkcB3R29/fi+ZcSNYAg+iR/gK3p3z+Y6ND3BkRdAmPifb5xvB0HXgaWx404\nzGxLoiMnuefMt67nb83/A3aNn6Mr0fu7HCvc/QngROC6+J/0U8BOZrZTvL0RwC1lbq+ULxN9Ev+B\nu98HZIgaPbn3UX8z2yW+fzLwWNwAzHkZ+DT+ZI6ZfYGoC2QAUcNz/9zYBeB/iLqJ8rX2+97MzM6L\nl309bizkFP0dsGhsyV+Bv7v7T4CfAX2L7YD46N8A4Ltxw21rom60XB3rahisax9KnekIRcdR+In+\nDKJDubn53wNmmtn7RJ9+s0S/3BD9A/9p3B1xIdHgzueBrYD7icZiHE10GPoZi742avG2vw58B7jS\nogFhXVjzj6FYXcWOPJwBTCnx+GKPfQAYa2YvE33a/zPRP5jtgSnAzWb2ArCc6B/gbe6+0sx+Ajxo\nZk1Enz5HlqiptX1VWM8bRJ/CugJ3u/uv4iM5Y0rUV8wMoj7kee7+qZnNB95399wnuHL2Yb5xwItm\ndhTRGJjLiT7pdY5r+TaAu//dzJyoawii/foDok+EuPvfzOxkooG+EDU8h7v7srjhdjXRGIslROM9\nPom7aEYCU81scvyck9z94RY7bx3PX0R+7t8AB5rZK0SH4R9n7aMQpR7n8XM/bGa3EY0xyh1S/1Xc\ncF5K9L5uN3f/i5ndB7xsZv8mGlfyN6L3wArgXeDH8dG094DcwNVcfSstGjA61cx+APQAvh83hoi7\nIh6I998iYCywY14J63wPm1lP4CLg78AjcYPTgQtKPd7dbzSz24FnzeyjeNm382vP2weL4/fJ82b2\nL6KxQ4/GdbxeuH4b9+G6jmBJDdjajU6R8lg0BmAHd7886Vqk8cRdE0vdfXZ85OUu4AEP6Ct/ZtaH\nKFPPKm93MHCVu/cpc/3bgTPiozgiiVGXh7TXpkRdH4esc03piP4KfN/Mno/vv000FiQIcbfHHODa\npGsh+obH7630V5dF6kJHKERERKRiOkIhIiIiFVODQkRERCrW0N/yiEcoi4iISALcvezzejT8EYqk\nTyVai9uoUaMSr0GZOmamUHOFmCnUXMqUnltbNXyDQkRERBqfGhQJ6NWrV9IlVJ0ypUeIuULMBGHm\nUqZwqUGRgEwmk3QJVadM6RFirhAzQZi5lClcalCIiIhIxdSgEBERkYo19JkyzXJXwxUREZF6MjM8\npK+NioiISONTgyIB2Ww26RKqTpnSI8RcIWaCMHMpU7jUoBAREZGKaQyFiIiItKAxFCIiIlJ3alAk\nIMT+NmVKjxBzhZgJwsylTOFSg0JEREQqpjEUIiIi0oLGUIiIiEjdqUGRgBD725QpPULMFWImCDOX\nMoVLDQoRERGpmMZQiIiItFE2G91y93NXMM9k1txPu7aOoVCDQkREpAJmEOK/Kg3KTIEQ+9uUKT1C\nzBViJggzV4iZIJt0AQ1BDQoRERGpmLo8REREKqAuj4iOUIiIiEjF1KBIQIh9iMqUHiHmCjEThJkr\nxEwaQxFRg0JEREQqpjEUIiIiFdAYioiOUIiIiEjFatqgMLPdzeyhIvOHm9mfzewxMzupljU0ohD7\nEJUpPULMFWImCDNXiJk0hiJSswaFmZ0D/ALYoGB+F+AKYH8gA5xsZp+rVR0iIiLV0pb2UJBtp1bU\nbAyFmY0EXgBucfe98ub3Bn7i7gfH01cAj7n7XUW2oTEUIiLSMCZNim75So2hKLZumjTMGAp3nwGs\nKrKoO7Akb/pDYNNa1SEiIiK11yWB51xK1KjI6QYsLrXy6NGj6dWrFwA9evSgX79+ZOJLueX64tI2\nnZvXKPVUY7owW9L1VGN6ypQpQbzf9P5L7/T8+fMZN25cw9RTjencvEapp63T2WwGM1gzbiIDZON5\nueloed++MGlSY9W/rvfb4sXRv+OFCxfSVjX92qiZbQP81t33zJvXBXgJ2B34BHgcGO7ui4o8Psgu\nj2w22/wihkKZ0iPEXCFmgnByZbNrxhPMnJllxIgMAJlMdEuT4l0eWdwzZa2bJg11+fK4QXGbu+9l\nZscCXd39BjM7BJgIGPBLd7+2xOODbFCIiHRUaT9ng8ZQtLJ+I//DVoNCRCQsaW9QZLMtj6qUylRs\n3TRpmEGZUlp+X2IolCk9QswVYiYINVc26QIqUryBkG3DuuFSg0JEREQqpi4PERGpm7R3eRQTYiZQ\nl4eIiIgkQA2KBITYL6pM6RFirhAzQai5skkXUAPZpAtoCGpQiIiISMU0hkJEROomxPEGIWYCjaEQ\nERGRBKhBkYAQ+0WVKT1CzBViJgg1VzbpAmogm3QBDUENChERqYly20NBtps6II2hEBGRmij3uhfp\nv+aFxlBAMpcvFxERSbX8K6gOHrymQZTGK6hWi7o8EhBiv6gypUeIuULMBOnPlc1Gn97zb5BtMS+N\nMTOZNUdWJk3KNt/vqI0JUINCRERqJJOJugLyb9ByXkf+JxwSjaEQEWkg+YfS8y9/ncZD6R1lDEWo\n2jqGQg0KEZEGlfbBfvkNopximYqtJ8nTia1SIO39osUoU3qEmCvETJFs0gVUpHgjIVvmeukR7vuv\nbdSgEBERkYqpy0NEpEGlvcujmBAzhUpdHiIiIlJ3alAkIMT+NmVKjxBzhZgpkk26gBrIJl1A1YX7\n/msbNShERESkYhpDISLSoEIcbxBiplBpDIWIiIjUnRoUCQixv02Z0iPEXGnPVLr8lgtSHhWNoQiX\nGhQiIglry/8j/e+SRqUxFCIiCSt1LYtQrnsR0vVJOpK2jqHoUstiRERk3XKX+S6mcP7gwTUvp+rU\ncOgY1OWRgBD725QpPULMlfZMxS7zHR2ZyAZ3qe+0v1bFhJipPdSgEBERkYppDIWISMJKXb5bl/qW\nJLV1DIUaFCIiDUongZIk6cRWKRBif5sypUeIuULMFMkmXUDVhfhahZipPdSgEBERkYqpy0NEpEGp\ny0OSpC4PERERqTs1KBIQYn+bMqVHiLlCzBTJJl1A1YX4WoWYqT3UoBAREZGKaQyFiEiD0hgKSZLG\nUIiIiEjdqUGRgBD725QpPULMFWKmSDbpAqouxNcqxEztoauNiog0kPxLffftu+ZS5bpipzQ6jaEQ\nERGRFjSGQkREROpODYoEhNjfpkzpEWKuEDNBmLmUKVxqUIiIiEjFNIZCREREWmjrGAp9y0NEUin/\n2xDZ7JpvQOjbECLJUJdHAkLsb1Om9AglVyYTfaVy0iR4+OFs8/2QGhOhvFb5lClcalCIiIhIxTSG\nQkRST9e8EKk+nYdCRERE6k4NigSE2N+mTOkRZq5s0gXURIivlTKFSw0KERERqZjGUIhI6mkMhUj1\naQyFiIiI1J0aFAkIsb9NmdIjzFzZpAuoiRBfK2UKlxoUIpIqbfnbrb/zIvWjMRQikiq5M2LmKzWG\noti6IlIejaEQERGRuqtZg8IiPzezx81snpl9qWD5N8zsWTN7ysz+p1Z1NKIQ+9uUKT3SniubjY5I\n5N8g22KeWfq7PNL+WhWjTOGq5RGKEcAG7r4XMAG4omD5ZcAQYBAw3sw2rWEtIhKITCbq3si/Qct5\n7mFdKEyk0dVsDIWZXQ485e6/i6ffcvet85bPBk4FPgCeBXZ196UF29AYChFZi8ZQiNRHW8dQdKlh\nLd2BJXnTq8ysk7uvjqdfImpIfATcXdiYEBEppi1HHXSEQqR+atmgWAp0y5tubkyYWW/gEGAb4GPg\nN2Z2pLvfVbiR0aNH06tXLwB69OhBv379yMR/JXL9Vmmbzs1rlHqqMV2YLel6qjE9ZcqUIN5vHeH9\nB1ly8VrmbYT62jc9f/58xo0b1zD1VGM6N69R6qnGdGG2pOtp7/T8+fNZvHgxAAsXLqStatnlcQRw\nqLuPNbM9gPPd/ZB42ReBGcAe7r7SzKYAf3X3Gwq2EWSXRzabbX4RQ6FM6RFiLrMs7pmky6i6EF8r\nZUqPtnZ51LJBYcA0oE88awywK9DV3W8ws1OAscBy4DXgv919VcE2gmxQiEh16VoeItXXMA2KalCD\nQkTKoQaFSPXpxFYpkN/fFgplSo8wc2WTLqAmQnytlClcalCIiIhIxdTlISKppy4PkepTl4eIiIjU\nnRoUCQixv02Z0iPMXNmkC6iJEF8rZQpXLU9sJSJSM9lsdAPo23fNKbYzGZ0hUyQJGkMhIiIiLWgM\nhYiIiNSdGhQJCLG/TZkaWza75sqb/fplm++HEjGk1ypfiLmUKVwaQyHSAeSPK5g8GebPT7IaEQmR\nxlCIdDA6Z4OIlENjKERERKTu1KBIQIj9bcqUJtmkC6i6UF+rEHMpU7jUoBAREZGKaQyFSAejMRQi\nUg6NoRAREZG6U4MiASH2tylTmmSTLqDqQn2tQsylTOFSg0JEREQqpjEUIoHKZotfJKvYGIpS64pI\nx6UxFCICtO202jpiKyKVUoMiASH2tylTmmSTLqDqQn2tQsylTOHStTxEApXNRt0bxRTOHzy45uWI\nSOA0hkIkULkrihYqNoai1Loi0nFpDIWIiIjUnRoUCQixv02ZGk/pb21k27BuOqT9tSolxFzKFC41\nKEQC1ZZGQtobFCKSPI2hEOlgdC0PESmHxlCIiIhI3alBkYAQ+9uUKU2ySRdQdaG+ViHmUqZwqUEh\nIiIiFdMYCpEORmMoRKQcGkMhIiIidacGRQJC7G9TpjTJJl1A1YX6WoWYS5nCpWt5iHQA2eyaK4r2\n7bvmNNuZjM5BISLVoTEUIiIi0oLGUIiIiEjdqUGRgBD725QpPULMFWImCDOXMoVLDQoRERGpmMZQ\niIiISAsaQyEiIiJ1pwZFAkLsb1Om9AgxV4iZIMxcyhQuNShERESkYhpDISIiIi1oDIWIiIjUnRoU\nCQixv02Z0iPEXCFmgjBzKVO41KAQERGRimkMhYiIiLSgMRQiIiJSdyUbFGa2w7pu9Sw0JCH2tylT\neoSYK8RMEGYuZQpXl1aWPQU8D5Q63NEX+GzVKxIREZHUKTmGwsx+4e7/XfKB61heDRpDISIikoy2\njqFo86BMM9va3d9qc2XtoAaFiIhIMuoxKPPH7XiM5Amxv02Z0iPEXCFmgjBzKVO42tygcPdRtShE\nRERE0mudXR5mdkHhPHe/sGYVrf3c6vIQERFJQFu7PFr7lkfOe7ltAwPQuSskYNlsdMvdz2Si+5nM\nmvsiItJSewZlznb3g2pUT+FzBXmEIpvNkgnsv1OImcyyuGeSLqPqQnytQswEYeZSpvSo+hGKghNY\n9QS2aU9hIiIiEq5yxlA8lDe5DLjK3WfXtKo1zx3kEQpJBzPQ209EOqqan4eiDYUYMI3ojJqfAie5\n++t5y3cDLo8n3wW+6e4rCrahBoUkRg0KEenIan4eCjO7usxVRwAbuPtewATgioLl1wOj3X0fYA4d\nqCslxO8sh5gJskkXUBMhvlYhZoIwcylTuNrzjY1rylxvEFFDAXd/ChiYWxCPy3gfOMvMssBn3X1B\nO2oRERGRBtDatTy2dve3SlxVdAXwZmv9EWb2C+BOd38gnl4IfMndV5vZXsCDQH/gdeBe4BJ3zxZs\nQ10ekhh1eYhIR1bNb3mcFd+uK7JsPWAVkGnl8UuBbnnTndx9dXz/feBVd38lLnoO0RGMbOFGRo8e\nTa9evQDo0aMH/fr1a/56Tu4wk6Y1Xel0dHft5ZCNz0Wx9vqQIZNprPo1rWlNa7rS6fnz57N48WIA\nFi5cSJu5e9EbcEypZfHyl9ex/Ahgenx/D+C+vGXrAa8RHbEAuAs4qMg2PEQPPfRQ0iVUXdozTZzY\nch48VPa6aZL216qYEDO5h5lLmdIj/h9c8v984a21IxSTzax7a22RdbRVZgBDzeyxeHqMmR0LdHX3\nG8zsROC26MsgPO51+iqqiIiIVF9rYygmruvB7j656hWtXYOXqk+kmjIZePjh8tYdPBg0qFtEQle1\nMRS1biyINJJoTMTa80oNypw0qQ4FiYikTHu+NioVygb48TbETEXGCAchxNcqxEwQZi5lCpcaFCJE\nRyhqsa6ISEdRzrU8ugHfBbYkOl/EC+7+ah1q0xgKSZTOQyEiHVktTr09nejkU18muubGL9tZm4iI\niASqnAbFZu4+HVjp7o+X+RhpRYj9bSFm0hiK9AgxE4SZS5nCVVbjwMz+M/65NdEZMkVERESalTOG\nojfRlUF3Av4XOM3dn6tDbRpDIYnSGAoR6cjaOoZinQ2KJKlBIUlSg0JEOrKqDco0szvjn4vM7J34\ntsjM3qlGoR1ZiP1tIWbSGIr0CDEThJlLmcLV2pkyj4p/9qxfOSLJymbXnDGzb981Z8XMZHT+CRGR\n1pQzhqIfcDKwYW6eu4+tcV2551aXh4iISAKqdi2PPDcBVwP/196iREREJGzlfG30XXe/wd0fyN1q\nXlXgQuxvU6b0CDFXiJkgzFzKFK5yjlAsNLPzgOcBB3D3uTWtSlIhf7zBzJkwYkR0X+MNREQ6nnLG\nUNxYMMs1hkIK6SuWIiJhqcl5KMxsB2B74AXgHXdf3f4Sy6cGRXqoQSEiEpaqXxzMzE4Hfg78GDgS\nmNr+8gRC7W/LJl1A1YX5OoWZK8RMEGYuZQpXOYMyjwGGAovd/Upg99qWJCIiImlTzhiKx4GvAX90\n9yFm9qi7D6pLcerySA11eYiIhKUW56G4DfgTsI2Z3Q/MbG9xIiIiEqZ1dnm4+1VEZ8ocD5wH3FDr\nokIXZn9bNukCqi7M1ynMXCFmgjBzKVO4yhmU+Rqwvrvf4e4vAHfXvixpZOX+7uh3TESk4yg5hsLM\nDnD3uWb2F+DfwGR3f8jMHnL3fetSnMZQNKRJk9ZcNCun2BiKYuuJiEg6VHMMxUHAXOB9YCQww8w+\nB6yqrEQREREJTckuD3c/M75r7r4EOBQYDfStQ11BS3t/WzYbHZHIv0G2xbyUx0z961RKiLlCzARh\n5lKmcJVzHooJAO7+CXA4cGlNK5KGl8lE3Rv5N2g5T9fzEBHpOMo5D8XWwCXA5sAdwAvu/lQdatMY\nigalMRQiIuGr+qm3geuA6cB6ROej+EX8ROPbVaGkXrlHHnSEQkSk4yinQbGRu88jusroywBmdhPR\nQE1ph7T3txVvKGTLXC890v46lRJirhAzQZi5lClc5Zwp81MzGwZ0NrM9iK42Orq2ZYmIiEialDuG\n4qdAb+DvwNnuvrD2pWkMRZroWh4iImGpxRiKA939GHff2d2PAg5rf3kiIiISopINCjM71sxuA35k\nZrfGt98Cp9SvvDCF2d+WTbqAqgvzdQozV4iZIMxcyhSu1sZQzAEWAZsRfdMDYDXwWq2LEhERkXRZ\n5xgKADPrSfS1UQO2dPcnal1Y/LwaQ5ESGkMhIhKWto6hKGdQ5i+BPYGuwMbAa+6+R0VVlkkNisaW\nza45vXY2u+ZroplM+r8yKiLS0dViUGZfYGfgAWAn4NN21iaxUPrbMpk1Z8OcNCnbfD+UxkQor1Oh\nEHOFmAnCzKVM4SqnQfF+fJigq7v/q9YFiYiISPqU0+VxEfABsAXwBWBbd9+9DrWpy0NERCQhVR9D\nEW+0G7AMOAj4s7u/1/4Sy6cGhYiISDKqNobCzE7I3Yiu23Ec8BlgWOVldmwh9rcpU3qEmCvETBBm\nLmUKV2vnodipYNqAMcAnwK9qVpGIiIikTrldHtsBNwMvA+Pc/cNaFxY/r7o8REREEtDWLo91Xm3U\nzL4FjAPOdPd7KylOREREwtTaGIqtzGwusDfwVTUmqifE/jZlSo8Qc4WYCcLMpUzhau0IxUvAcmAe\ncI3ZmqMe7n5cjesSERGRFCk5hsLMBpd6kLs/XLOK1q5BYyhEREQSUJPzUCRFDQoREZFk1OJaHlJl\nIfa3KVN6hJgrxEwQZi5lCpcaFCIiIlIxdXmIiIhIC+ryEBERkbpTgyIBIfa3KVN6hJgrxEwQZi5l\nCpcaFCJOAu+OAAAcOUlEQVQiIlIxjaEQERGRFjSGQkREROpODYoEhNjfpkzpEWKuEDNBmLmUKVxq\nUIiIiEjFajaGwqKriU0D+gKfAie5++tF1rsOeN/dv1dkmcZQiIiIJKCRxlCMADZw972ACcAVhSuY\n2SnALjWsQUREROqglg2KQcAcAHd/ChiYv9DM9gR2A66rYQ0NKcT+NmVKjxBzhZgJwsylTOGqZYOi\nO7Akb3qVmXUCMLPPAxOB04GyD6eIiIhIY+pSw20vBbrlTXdy99Xx/aOBzYD7gZ7ARmb2v+7+q8KN\njB49ml69egHQo0cP+vXrRyaTAda0CjWd/HQmk2moeqoxnZvXKPVouvR0iO+/3HROo9Sj6ZbTobz/\n5s+fz+LFiwFYuHAhbVXLQZlHAIe6+1gz2wM4390PKbLeKGBHDcoUERFpHI00KHMGsNzMHgMuB840\ns2PN7KQaPmcqFH7yCIEypUeIuULMBGHmUqZw1azLIz60cGrB7FeKrHdzrWoQERGR+tC1PERERKSF\nRuryEBERkQ5CDYoEhNjfpkzpEWKuEDNBmLmUKVxqUIiIiEjFNIZCREREWtAYChEREak7NSgSEGJ/\nmzKlR4i5QswEYeZSpnCpQSEiIiIV0xgKERERaUFjKERERKTu1KBIQIj9bcqUHiHmCjEThJlLmcKl\nBoWIiIhUTGMoREREpAWNoRAREZG6U4MiASH2tylTeoSYK8RMEGYuZQqXGhQiIiJSMY2hEBERkRY0\nhkJERETqTg2KBITY36ZM6RFirhAzQZi5lClcalCIiIhIxTSGQkRERFrQGAoRERGpOzUoEhBif5sy\npUeIuULMBGHmUqZwdUm6gI4im41uADNnwogR0f1MJrqJiIikmcZQJMAMAowlIiIB0RgKERERqTs1\nKBKRTbqAqguxDzHETBBmrhAzQZi5lClcalCIiIhIxTSGIgEaQyEiIo1OYyhERESk7tSgSEQ26QKq\nLsQ+xBAzQZi5QswEYeZSpnCpQSEiIiIV0xiKBGgMhYiINDqNoRAREZG6U4Oihkp3q7VckPYuuBD7\nEEPMBGHmCjEThJlLmcKlBkUNteU9pvejiIikmcZQ1NCkSdGtULExFKXWFRERSUJbx1DoaqM1lM1G\njYdiCucPHlzzckRERGpGXR41lMlERyIKb5BtMS/tlzAPsQ8xxEwQZq4QM0GYuZQpXGpQiIiISMU0\nhqKGstniRx6KjaEota6IiEgS2jqGQg2KBOjEViIi0uh0YqtUyCZdQNWF2IcYYiYIM1eImSDMXMoU\nLjUoREREpGLq8kiAujxERKTRqctDRERE6k4NikRkky6g6kLsQwwxE4SZK8RMEGYuZQqXGhQiIiJS\nMY2hSIDGUIiISKPTGAoRERGpOzUo6iSbXXNF0b59s833Q+l6C7EPMcRMEGauEDNBmLmUKVy62mid\nZDJrTq2df19ERCQEGkMhIiIiLWgMhYiIiNSdGhQJCLG/TZnSI8RcIWaCMHMpU7jUoBAREZGKaQyF\niIiItKAxFCIiIlJ3alAkIMT+NmVKjxBzhZgJwsylTOGqWYPCIj83s8fNbJ6Zfalg+bFm9qSZPWJm\n02pVh4iIiNRezcZQmNlIYLi7jzWz3YEJ7j4iXrYh8CKwi7svN7NbgVvd/d6CbWgMhYiISAIaaQzF\nIGAOgLs/BQzMW7Yc2Mvdl8fTXYBPa1iLiIiI1FAtGxTdgSV506vMrBOAR/4fgJl9G+jq7n+oYS0N\nJcT+NmVKjxBzhZgJwsylTOGq5bU8lgLd8qY7ufvq3ISZGXAp8GXgiBrWISIiIjVWywbFY8ChwJ1m\ntgfRmIl81wPLcuMqShk9ejS9evUCoEePHvTr149MfGWtXKtQ08lPZzKZhqqnGtO5eY1Sj6ZLT4f4\n/stN5zRKPZpuOR3K+2/+/PksXrwYgIULF9JWtRyUacA0oE88awywK9AVeBZ4GngkXubAle5+T8E2\nNChTREQkAQ0zKDMeJ3Gqu38tvr3i7re5+w3u/ry7d3H3fePbkMLGRMgKP3mEQJnSI8RcIWaCMHMp\nU7h0YisRERGpmK7lISIiIi00TJeHiIiIdBxqUCQgxP42ZUqPEHOFmAnCzKVM4VKDQkRERCqmMRQi\nIiLSgsZQiIiISN2pQZGAEPvblCk9QswVYiYIM5cyhUsNChEREamYxlCIiIhICxpDISIiInWnBkUC\nQuxvU6b0CDFXiJkgzFzKFC41KERERKRiGkMhIiIiLWgMhYiIiNSdGhQJCLG/TZnSI8RcIWaCMHMp\nU7jUoBAREZGKaQyFiIiItKAxFCIiIlJ3alAkIMT+NmVKjxBzhZgJwsylTOFSg0JEREQqpjEUIiIi\n0oLGUIiIiEjdqUGRgBD725QpPULMFWImCDOXMoVLDQoRERGpmMZQiIiISAsaQyEiIiJ1pwZFAkLs\nb1Om9AgxV4iZIMxcyhQuNShERESkYhpDISIiIi1oDIWIiIjUnRoUCQixv02Z0iPEXCFmgjBzKVO4\n1KAQERGRimkMhYiIiLSgMRQiIiJSd2pQJCDE/jZlSo8Qc4WYCcLMpUzhUoNCREREKqYxFCIiItJC\nW8dQdKllMSIi1darVy/efPPNpMsQCcY222zDwoULK96OjlAkIJvNkslkki6jqpQpPdKeK/7UlHQZ\nIsEo9Tulb3mIiIhI3ekIhYikSrFPU9lsdMvdzx2AyWTW3F+XamxDJI2qdYRCDQoRSZV1dXmYQaV/\nNqqxDZG0UJdHioX4nWVlSo9QcyXtzTffpFOnTkyfPn2t+ZdffjljxoxZ5+N/+MMfMmvWrLKe69ln\nn2XAgAHtqjPfrFmzGDduXJseM2bMGK644oqKn7takq5n0aJFDBo0CIDJkydzxhlnJFZL0tSgEJFU\namu7qNj61dhGvk6dOnH22Wfz6quvrjXfbN0f8ubNm8fKlSvLqmPXXXflueeeK2vd1gwfPpwpU6ZU\nvJ2OrGfPnjz66KNJl9EQ1KBIQJpH2JeiTOkRSq5GbFBstNFGjB8/nmOOOYZVq1a1WL5gwQIOOOAA\nvva1r7HtttsycuRIVqxYwbRp03jmmWc455xzuOeee1i5ciVnnXUWAwcOpH///owdO5aPPvqIt956\ni/79+zNgwAD69+9Pz5492XTTTQFYunQpY8aMYbfddqNfv36MHz+e1atXN9c1efJkBg0axHbbbcfU\nqVMBuPnmmxk+fPg6H1/K9OnT2WOPPdh1113ZdtttufbaawF47733GDZsGAMHDmTgwIFccMEFaz1m\n4MCB7LrrrhxwwAG88sorQHSk4fDDD6d3795MmDCh5L4q5pFHHmHPPfdkl1124cwzz2yuu7C+6667\nrjn3Pvvsw8CBAxkyZAibb745r7/+OgCXXHIJvXr1at72AQccwJw5c9h333353ve+x+DBg9l22205\n4YQTgOjIVLdu3VrUNGXKFAYMGMA///lPVq1axRlnnMHOO+9M3759Ofnkk/noo4+YOnUqxx9/PACr\nVq1i00035aabbgLg8ccfZ/fddweiI0m5HHvvvTdPPvkkAMuWLWPUqFHsuOOO7LHHHowZM4axY8cC\n8NJLLzFkyBD69u1L//79ueWWW1p9LavC3Rv2FpUnIrJG7u/CxImllhefX2z9amwjZ+HChd6tWzd3\nd99nn3387LPPdnf3n/70pz5mzBh3dz/nnHP8N7/5jbu7r1y50vv06eN33323u7tnMpnm+xdeeKGf\ne+65zdv+wQ9+4Keddtpaz/fGG2/4F7/4RZ87d667u48dO9avvvpqd3dvamry448/3i+77DJ3dzcz\nnzZtmru7P/vss77hhhv68uXL/aabbvLhw4eXfPyll17aIufo0aP98ssv948++sj32msv/+CDD9zd\n/cknn2zO/8Mf/tBPPfVUd3f/+OOP/dhjj/WlS5f6ww8/7Pvss48vW7bM3d3nzp3rX/nKV5q3O3To\n0ObnaW1fFdaz2267+bJly3zlypW+7777+rXXXttqfTfddJNvttlm/tFHH7m7+4knnujXXHNN8+uw\n5ZZb+oIFC3zJkiW++eab+8qVKz2TyfjXv/51d3f/8MMPfauttvJsNrvW6z5p0iQ//fTT/dJLL/VB\ngwb50qVL3d39ggsu8KOOOsqbmpqa9/Wpp57qb775pn/+8593d/dsNutbbrmlf+Mb33B393PPPdcv\nu+wyX7Bggffu3bs5x0svveQ9e/b0Tz75xM8777zm9ZcuXep9+/b1MWPG+KpVq3y77bbzmTNnurv7\nO++841tvvbU/+eSTLfaf+5rfqRLzy/6frRNbJSDt5wEoRpnSI5Rc2Ww0eLKYYvMHD67NNor59a9/\nzYABAxg2bNha83/yk5/w4IMPctlll/HKK6+waNEiPvroo+blHg+Mu/fee1myZAlz584Fok+vm2++\nefN6//rXvzjwwAO58MILGTp0aPNjnn76aW644QYAPv30Uzp1WnMQ+rDDDgNgwIABrFixgo8//nit\n2oo9vrWumq5duzJr1izuvfdeFixYwPz585u3eeCBB3LIIYfw5ptvsv/++3PJJZfQrVs37rvvPl57\n7TX22muv5qyLFy9m8eLFAM1jEcrZV/mOP/54NtxwQwC++c1vcv/993PKKaeUrA+gT58+dO3aFYAR\nI0Zw3XXXccIJJ7Bo0SKOO+445s6dy2c/+1kOPPBAunSJ/lXmjuZssskmbL/99nzwwQdrHc0AuOuu\nu3jvvfeYNWtW85GLOXPmcNFFFzW/Ht/+9rcZOXIk06ZNY+utt+aZZ55hzpw5TJgwgUsuuQSAe+65\nh9mzZzNnzhzeffdd9ttvv+Z91qVLFxYsWMDs2bP52c9+BkC3bt0YNWoUL774Iq+88grLly/n8MMP\nB6JumSOPPJI5c+Y0H/WoBTUoRCSVMpniXRClvqExaVJttlHMF77wBX7+858zatSo5kPjAMcccwyr\nV6/mv/7rvzj00EP5xz/+UXR0fVNTE1deeWVzg+STTz7h008/BaLD3MOHD+cb3/gGo0aNan7M6tWr\nueOOO9hxxx0BWLJkyVoNio022mit5yh83qamprUev3Tp0lYbFG+//TZ77rknp5xyCnvvvTdHHXUU\n9913HwADBw7kjTfe4A9/+APz5s1jt912Y+bMmTQ1NXH88cdz8cUXN2/nnXfeoUePHkD0j7qt+wqg\nc+fOa+Vab731Wq2v8LmGDh3KSSedxH333ce+++7L0KFDmTZtGhtvvDHHHHNM0X1Y6psRO+ywA9dc\ncw2nnnoqL774It27d2/RddTU1NQ8XuaII47g/vvv58EHH+S+++7j1ltv5fbbb2fjjTdm2223pamp\nif3224/bbrut+fFvvfUWW265JV26dFmrhtx+WL16dYvaVq9eXfYYnfbSGIoEhPDpsJAypUeouRpB\n/h/xo446ioMOOmitQY9z587lggsu4Oijj8bdeeqpp2hqagKiT525P/jDhg3j6quvZuXKlaxevZoT\nTzyRCRMm0NTUxNFHH80uu+zC+eefv9ZzDxs2rPnbDsuXL+ewww7j6quvXmedpR4/fPjwko8HeOaZ\nZ9h88835/ve/z9ChQ5u/oeLuTJgwgQsvvJDDDjuMKVOmsPPOOzePibjtttt49913AZg2bRr77bdf\n0e0/+OCDJfdVod/+9resWLGCTz/9lJtuuomDDjqo1foKbbDBBgwePJjJkydzwAEHsM8++/DEE0/w\n6KOPcuCBB5bcB8X06dOHkSNHst9++3HaaacB0b699tprWbVqFatXr2batGnNR5ZGjBjBrbfeSlNT\nE1tssQVDhw7l3HPP5aijjgJgyJAhzJ07l5dffhmA+++/n759+7J8+XIOOeQQbrzxRtydTz75hFtv\nvRUzY8cdd2SDDTZg5syZQNRou+uuu5qfs1Z0hEJEUqmt7aJi61djG/kKP9FPnTqVxx57rHn+RRdd\nxIgRI9hss83YeOONyWQyzd8IGT58OGeffTYrVqzgggsuYPz48fTv35+3336bgw8+mMsvv5w77riD\n2bNnM3DgQAYMGIC7Y2bcfvvtXHnllXznO9+hd+/erFq1qvkfU7G6ih15mDp1KuPGjSv6+GKPHTZs\nGNOnT2fHHXdkk0024atf/Sqf+9znePXVVxk3bhyjRo2iT58+bLDBBvTt25djjz2W9dZbj+9+97sM\nHTqUzp070717d2bMmFG0ptb2VWE92267LYMGDeLjjz/miCOO4IQTTmDZsmXceOONResrZuTIkdx9\n990MGTKEDTfckH79+rHZZpux/vrrl70P802ZMoXevXtz5513cv755zN+/Hj69etHU1MTX/3qV7nq\nqqsA2GmnnTAz9t9//+b9+qMf/YgjjzwSgK985Stcf/31zUdKunTpwqxZs9hoo42YMGECp59+On36\n9GHTTTdliy22YOONN6ZLly7MmDGDM844g4kTJ9LU1MSkSZMYXG6fXTvpxFYJCKUPO58ypUfac3Wk\nE1vNmjWLV155hfHjxyddijSg22+/ne7du3PQQQfh7hx55JEMGzaMU045pU3b0YmtREQCt2TJEq6+\n+uq1+v5FcnbZZRd+/OMf079/f3bZZRe22morTjrppMTq0REKEUkVXctDpLp0LQ8R6ZB0+XKR6lKX\nR4qFeC0FZUqPUHOJSLLUoBAREZGKqctDRFJFXR4i1VWtLg+dh0JEUmWbbbYp6+qdIlKebbbZpirb\nUZdHAkLsw1am9Eh7roULF7a4KNFDDz2U+MUMa3ELMZcyNd5t4cKFVfndrFmDwiI/N7PHzWyemX2p\nYPlwM/uzmT1mZsl9cTYB8+fPT7qEqlOm9AgxV4iZIMxcyhSuWnZ5jAA2cPe9zGx34Ip4HmbWJZ7e\nFVgGPGZm97j7/6thPQ0jd2W9kChTeoSYK8RMEGYuZQpXLbs8BgFzANz9KWBg3rKdgAXuvtTdVwKP\nAvvUsBYRERGpoVo2KLoDS/KmV5lZpxLLPgQ2rWEtDaVa/VWNRJnSI8RcIWaCMHMpU7hq9rVRM7sc\neMLd74yn/+HuX4zv9wYucfdD4ukrgEfd/e6Cbei7YSIiIgnxBvna6GPAocCdZrYH8GLesr8D25tZ\nD+ATou6Oywo30JYgIiIikpxaNihmAEPN7LF4eoyZHQt0dfcbzOwsYC5gwA3uvqiGtYiIiEgNNfSZ\nMkVERCQdGu7EVma2u5k9FN/vZ2ZvxeexmGdmRyddX3sUZPqcmc00s6yZPWJm2yZdX3sV5Lotfo0e\nMrM3zOzWpOtrjyLvvyfM7E9mdkPStbVXQaYBZvaUmT1sZlcmXVt7mFkXM/tV/Lo8GZ/TZrv49+lh\nM7sm6RrbqlimvGVXmNnJSdbXXiVeq77x9Dwzm21mn0u6zrYokWmn+P33iJlNz/sCQmqs4z14nJk9\nvs6NJH2GrvwbcA7wAvB4PH0icGbSdVU5043AUfH9DHBQ0jVWI1fe/B7Ac8DmSddYhdfqbmBYfP/X\nwCFJ11iFTE8Du8f3LwSOS7rGdmQaDVwR3+8BvAncA+wdz/s5cHjSdVaQ6TNxps2A+4EFwMlJ11jF\n1+ohoHc872Tg8qTrrEKmu4GvxfNuTNv7r0iuzwBvxvf7A38o/Ftf7NZorahXgZF507sCh8SfOm4w\ns64J1VWJwkxfA7Y2sweB44BsEkVVQWGunMnAVe7+zzrXUw2FmZ4H/sOiC0d0A1YmUlVlCjNt7dF5\nYQAeJzpfTNr8Djg/vt8ZWAUMcPdH4nmzgf2TKKwC+Zk6Eb3XNgEmArckVVQVFL5WK4Gvu3tukH4X\nopMbpkmLTO5+hLs/ZmbrA59n7dMipEWL96CZfRb4EfCdcjbQUA0Kd59B9Mch5yngHHcfDLwOTEqi\nrkoUydQL+MDdhwL/B5yXRF2VKpKL+NDlEOCmJGqqVJFMC4CpwEvA5qSw8Vck02tmtnd8fziQuka6\nu3/i7h+bWTfgDuD7RIO7c1J3Xptimdz9TXd/mrWzpUqJXP8EMLO9gG8BP0uyxrYq8f7DzL4I/JXo\nyNJfEiyxXYrkOh/4JXAW8DFlvA8bqkFRxEx3fz6+PwPol2QxVfI+MCu+P4voKEwojgJu9fg4WQCu\nJDqM+RWiT4lXJFxPNYwFvhcfIXsP+FfC9bSLmX0BmAfc7O6/BVbnLe4GpO5cyAWZbk+6nmoplsvM\nvg5MAw529/eTrK89imVy93+4+w7AdaSskZSTn4vo6Ob2RF2ItwE7xeeMKqnRGxQPmFnulN37Ac8m\nWUyVPAIcHN/fh+jTb5rlt1r3JzrcHIr3iT7tArxD1F+adocQjZsYCvwH8GDC9bSZmW0BPACc6+43\nx7OfN7Pc6fsPIvo9S40SmVKvWC4z+ybRkYmMu7+ZZH3tUSLTPWa2fbzKh0BTUvW1V2Eud3/a3Xu7\n+xDgGOBv7n5Wa9uo5XkoquFU4CozWwG8SzSAJ+3OBm4ws1OJ+tmOS7ieSuUfjdiBqGsqFP8N3G5m\nK4EV8XTaLQDmmdnHwEPuPifpgtphAlHj7nwzu4DoPfgdor8V6xGdOO/OBOtrj2KZDnL35az9O5Y2\nhbk6AzsTDWScYdHZkB9298kJ1thWxV6r7wM3mdlyopM1pvEK2q29B8ui81CIiIhIxRq9y0NERERS\nQA0KERERqZgaFCIiIlIxNShERESkYmpQiIiISMXUoBAREZGKqUEh0gGY2WAzW2xmW+XNu9jMTmjH\nttp0jof46pI/KHPdbHylw53MbFHBstFmdnPBvH7xFR5/YWb/NrMd2lKbiFSPGhQiHcdyoishVsTd\nj2rj+n9x9x+VuzpwvLv/nZYndPodMMTMNsqbNxa41t3/m+hibiKSEDUoRDqOecAHZvatwgVmdpGZ\nPWBmz5jZL+N5E83sNjP7o5k9G1/MidyRAzPrbWbz4tsd8UWFMLOrzOwpM3vOzIbHR0dui5cdbWaP\nm9mfzOyiEnWudREiM/uxmV3l7p8AvweOjOevT3Sa7TuLPU5E6ksNCpGOw4lOZz/OzLbLzYwbAh+4\n+zBgN2BPM+sZL/7Y3fcDjie6mFNuOwDXA6fF5/qfDXzXzEYAm7n77sC+QO5aPG5mnyG6YvAQd98H\n2NrM9mulXjOzy4DO7v7teN4NQK6b5nDg3racGlhEaqfRr+UhIlXk7v82szOJrib4aDx7GbCFmf2G\n6DLFXYH14mXz4sf9Lb54UL6dgGlmRrz+AqLruTwRP2YJMNHMBsfrbw98DrjfogdtAmwH/LFEuVsA\nvYmuepir/3kz625mWwJjgPFt3gkiUhM6QiHSwbj7vcDLRP+QIeo2+IK7fwP4HrARa7oPdgUws12A\nt+N5uWX/C5wQH6H4LnAv0YW5vho/ZlMzy7/42BvAP4Ch7r4vcDXwZCulvuvuBwK7mNmwvPnTgW8D\nG8VjLUSkAegIhUjHNA4YEt//M/ADM8vG068DW8b3+5vZH4CNWXMFxVyXx2nALfE3R/5F1Lh41cyG\nmtkjRFeWbL6KpLv/y8x+BvzJzDoTNTBuL6PWE4HZZra7u/8buI3oapVntDW0iNSOrjYqIkWZ2URg\nkbtf38o6XYDr3X1slZ7zIeAUd3+lno8Vkcqpy0NESinn08b6wEAzO66Kz/srM/vPtjzAzH4B9K1i\nDSLSRjpCISIiIhXTEQoRERGpmBoUIiIiUjE1KERERKRialCIiIhIxdSgEBERkYqpQSEiIiIV+/+6\nEAeuYcmTjwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1f0dd7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ustawienie jednostek umownych dla natBarwnikowego w kV\n",
    "myData['natBarw'] = AnalyzeCSVwrapper('natBarw')\n",
    "myData['natBarw'] = myData['natBarw']._replace(y=normalize(myData['natBarw'].y))\n",
    "myData['natBarw']._plot(title = True, fun = lambda: plt.ylim(0,1.1), fmt='None')\n",
    "# niepewnosc z ostatniego zostala przeniesiona na pozostale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaUAAAGoCAYAAADmTPpwAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSGb8fwSRIna1oT8QAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1da26710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Labels = namedtuple('Labels', ['x', 'y', 'label_y', 'label_x', 'key'])\n",
    "# Data = namedtuple('Data', ['x', 'y', 'labels'])\n",
    "\n",
    "def joinDataByX(datax, datay, key):\n",
    "    mergedDataLabel = Labels(x=datax.labels.y, y=datay.labels.y, label_x=datax.labels.label_y, label_y=datay.labels.label_y, key=key)\n",
    "    return Data(datax.y, datay.y, mergedDataLabel)\n",
    "\n",
    "def fun_01(func=None):    \n",
    "    plt.ylim(0,1.1)\n",
    "    plt.xlim(0,1.1) \n",
    "\n",
    "def fun_01_outer(func=None):\n",
    "    def fun_01_inside():\n",
    "        fun_01()      \n",
    "        if func != None:\n",
    "            func()\n",
    "            \n",
    "    return fun_01_inside\n",
    "  \n",
    "myTitle = u'Natężenie lasera barwnikowego od natężenia lasera azotowego'\n",
    "myData['natBarwOdAzot'] = joinDataByX(myData['natAzotOdKv'], myData['natBarw'],'natBarwOdAzot')\n",
    "myData['natBarwOdAzot']._plot(title = True, show=False, fun = fun_01_outer(lambda:plt.title(myTitle)), rc =[4,4], fmt='None')\n",
    "\n",
    "myData['nat2HarmOdBarw'] = joinDataByX(myData['natBarw'], myData['nat2Harm'],'nat2HarmOdBarw')\n",
    "myData['nat2HarmOdBarw']._plot(title = True, show=False, fun = fun_01, rc =[4,4], fmt='None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.3597363459765888+/-0.07591025348321112\n",
      " 0.6444859495028196+/-0.0632363580404707] [0.9376907396871316+/-0.02635211505559262]\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAGoCAYAAAATsnHAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n5qwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1ee09780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ?curve_fit\n",
    "# def ucurve_fit(x, y, *args, **kwargs):\n",
    "#     popt, pcov = curve_fit(xdata=unv(x), ydata=unv(y), yerr=sigma(y), *args, **kwargs)\n",
    "#     return unumpy.uarray(popt, np.sqrt(np.diag(pcov)))\n",
    "fsqr = lambda x, a, b: a*x**2 + b*x\n",
    "flin = lambda x, al  : al*x\n",
    "p1    = myData['nat2HarmOdBarw']._curve_fit(p0 = (0.5, 0.5), f=fsqr)\n",
    "p1lin = myData['nat2HarmOdBarw']._curve_fit(p0 = 1,          f=flin)\n",
    "print(p1, p1lin)\n",
    "a, b= unv(p1)\n",
    "ap, bp = unv(p1)+ustd(p1)\n",
    "am, bm = unv(p1)-ustd(p1)\n",
    "alin = unv(p1lin)\n",
    "alinp = unv(p1lin)+ustd(p1lin)\n",
    "alinm = unv(p1lin)-ustd(p1lin)\n",
    "\n",
    "\n",
    "# print(unv(myData['nat2harmOdBarw'].x))\n",
    "# print(partial(fsqr, a=a, b=b)(unv(myData['nat2harmOdBarw'].x)))\n",
    "\n",
    "# @fun_01\n",
    "# def plot_fit():\n",
    "#     plt.plot(unv(myData['nat2harmOdBarw'].x), partial(fsqr, a=a, b=b)(unv(myData['nat2harmOdBarw'].x)),label ='dopasowanie')\n",
    "x = np.linspace(0,1.2,20)\n",
    "\n",
    "label_data = u'Natężenie drugiej harmonicznej \\n w funkcji lasera azotowego'\n",
    "label_dop  = u'Dopasowanie do funkcji $a_{{sqr}}  x^2 + b x$,\\n gdzie $a_{{sqr}}={:L}, b={:L}$'.format(*p1)\n",
    "label_dop_lin  = u'Dopasowanie do funkcji $a_{{lin}}x$,\\n gdzie $a_{{lin}}={:L}$'.format(*p1lin)\n",
    "uplot(x=myData['nat2HarmOdBarw'].x, y=myData['nat2HarmOdBarw'].y, fmt='None', label = label_data)\n",
    "plt.plot(x, partial(fsqr,  a=a, b=b)(x), 'g-',label = label_dop)\n",
    "plt.plot(x, partial(fsqr,  a=ap, b=bp)(x),'g--')\n",
    "plt.plot(x, partial(fsqr,  a=am, b=bm)(x),'g--')\n",
    "plt.plot(x, partial(flin,  al=alin)(x), 'r-', label = label_dop_lin)\n",
    "# plt.plot(x, partial(flin,  al=alinp)(x),'r--')\n",
    "# plt.plot(x, partial(flin,  al=alinm)(x),'r--')\n",
    "plt.ylim(0,1.1)\n",
    "plt.xlim(0,1.1)\n",
    "plt.legend(loc=2)\n",
    "plt.xlabel(u'Nateżenie [j.u.]')\n",
    "plt.ylabel(u'Nateżenie [j.u.]')\n",
    "plt.title(u'Nateżenie 2 harmonicznej od natęzenia lasera azotowego')\n",
    "plt.grid()\n",
    "plt.tight_layout() \n",
    "# plt.show()\n",
    "filepath = os.path.join('plots', 'nat2HarmOdBarwDopasowania' + '.png')\n",
    "plt.savefig(filepath, dpi = 140) \n",
    "crop_image(filepath)\n",
    "    \n",
    "# myData['nat2harmOdBarw']._plot(title = True, show=True, fun = plot_fit, rc =[6,6], fmt='None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lin\n",
      " 9.18 / 7 = 1.312\n",
      "prawd 0.988\n",
      "0.239728539021\n",
      "\n",
      "sqr\n",
      " 1.94 / 6 = 0.323\n",
      "prawd 0.999\n",
      "0.925463240327\n"
     ]
    }
   ],
   "source": [
    "# return x, (y+-yerr), xerr, popt, np.sqrt(np.diag(pcov)), lambda x : foo(x, popt[0], popt[1])\n",
    "def chi2f(fit):\n",
    "    \n",
    "    x = unv(fit[0])\n",
    "    y = unv(fit[1])\n",
    "    yerr = ustd(fit[1])\n",
    "    popt = fit[2]\n",
    "    foo = fit[3]\n",
    "#     print y\n",
    "#     print foo(x)\n",
    "#     print yerr\n",
    "    suma = np.sum(((y - foo(x)) / yerr)**2)\n",
    "    d = len(x) - len(popt)\n",
    "    print('{:>5.2f} / {} = {:.3f}'.format(suma, d, suma / d))\n",
    "    return suma / d, d\n",
    "\n",
    "fit1 =  myData['nat2HarmOdBarw'].x, myData['nat2HarmOdBarw'].y, p1lin, partial(flin,  al=alin)\n",
    "fit2 =  myData['nat2HarmOdBarw'].x, myData['nat2HarmOdBarw'].y, p1, partial(fsqr,  a=a, b=b)\n",
    "\n",
    "print('lin')\n",
    "chi1 = chi2f(fit1)\n",
    "print('prawd {:0.3f}'.format(stats.chisqprob(chi1[0],chi1[1])))\n",
    "print(1 - stats.chi2.cdf(chi1[0]*chi1[1],chi1[1]))\n",
    "\n",
    "print('\\nsqr')\n",
    "chi2 = chi2f(fit2)\n",
    "print('prawd {:0.3f}'.format(stats.chisqprob(chi2[0],chi2[1])))\n",
    "print(1 - stats.chi2.cdf(chi2[0]*chi2[1],chi2[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGoCAYAAAAemnx2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d73c160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ustawienie jednostek umownych dla nat2Harm w kV\n",
    "myData['nat2Harm'] = AnalyzeCSVwrapper('nat2Harm')\n",
    "myData['nat2Harm'] = myData['nat2Harm']._replace(y=normalize(myData['nat2Harm'].y))\n",
    "myData['nat2Harm']._plot(title = True, fun = lambda: plt.ylim(0,1.1), fmt='None')\n",
    "# niepewnosc z ostatniego zostala przeniesiona na pozostale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGoCAYAAAAemnx2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x20719978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ustawienie jednostek umownych dla nat2Harm w kV\n",
    "ramie = ufloat(62,0.05)\n",
    "\n",
    "myData['nat2HarmOdDwoj'] = AnalyzeCSVwrapper('nat2HarmOdDwoj')\n",
    "myData['nat2HarmOdDwoj'] = myData['nat2HarmOdDwoj']._replace(y=normalize(myData['nat2HarmOdDwoj'].y))\n",
    "myData['nat2HarmOdDwoj'] = myData['nat2HarmOdDwoj']._replace(x=unumpy.degrees(unumpy.arcsin(myData['nat2HarmOdDwoj'].x/ramie)))\n",
    "myData['nat2HarmOdDwoj'] = myData['nat2HarmOdDwoj']._replace(labels = myData['nat2HarmOdDwoj'].labels._replace(x=u\"Kąt [stopnie]\"))\n",
    "myData['nat2HarmOdDwoj']._plot(title = True, fun = lambda: plt.ylim(0,1.1), fmt='None')\n",
    "# niepewnosc z ostatniego zostala przeniesiona na pozostale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAhQAAAGoCAYAAAAemnx2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XmYXFWZ+PHvGxLZBMLooCiSMGoQMJhNWSUNIztBYIAB\nF0gAF3BDwfUnAjqiyKbIMiwqqAgjsgnIokIjBEUIRBDBgBpcwA2FgKxJ3t8f93an0lR3uru66nZ1\nfz/P00/XXc+pt25VvXXOufdGZiJJktSIMVVXQJIktT8TCkmS1DATCkmS1DATCkmS1DATCkmS1DAT\nCkmS1DATigZExISIWBoRB/WYf0REfKMf2x8VEbP6Wdb0iLhzsHWt2c+siPhyg/u4MiIOaLQuNfs7\nNiLesYJ1pkfEd+vMnxkR9wxVXZohIs6JiO3arbyIeENEPBgRd0TE+oPcx9KI+LcBrH9nRKw50OM0\nIg6MiCsHU8dm6O14XcE234iIjzSrTnXKmxERZ/ZjvYbrFRFPDPQYiohXldttUjOv6/gYVq+3CmOr\nrsAIsBQ4MSJ+kpkP1szvzwU+tgPu7U8hmTkPmDaI+vXcz5XAsHojZubR/VhnHrBvb4uHtkZDKzPf\n1abl7Q7ckJnvbqQ6A1o5s+sYH8xxOmyOgxUcr8PF64FXtqiswbw2uwEfy8zuz8iu4yMiBrtPNZEt\nFI17GjgJuCgiXpCgRcRrI+L6iJgbEb+LiMsi4kURcRgwAzghIt4aEeMi4uTy1+BdEfH1iHhxRKxX\nTt9Z/n8kIh4v971m+evh9oiYHxEnRcSYctnTEXF0RNwSEb+JiA+W87sz+7627/Ec1i2fwz0RcTXw\n8pplz0TE/0XEfeWvsuV+kdZOR8QnImJB+RxPiYjflfO7fwFFxEYRcV1ZpzsjYnY5v6+WiDUi4sIy\nPr+KiK36in0v9X46Io6LiLvLdfeJiO+Wy38UEauW2705In5axuvnEbFjTVwvj4hLyzjdEREbl8tu\njIi9yse7lfWcX9Zr04jYo8dr/EREnB9FC9iDEXFqRNxWxq77SyoiPlWWc2dZ7st7llez7u4RcXPN\n9P0RcUz5eL2I+FOP9d8GHAa8NSK+FT1+EfY4jr4REV+JiBsi4oEoWrBW61q1XOflZVwOK6c3i4if\nlfG+IyI6ao+XnuXVlPuy8vi4o/w7ts46e5f1eG25n59ExLyI+HG5/OBy23nl8bFhOX/1KN53v46I\nX0bE58v5dd+b5bLfRfE++0n5+PhyfvfxGhGTejsOe1OW98OIWK2M7xVl/L4UEf+IiNfUrHt9FC06\nW5XHye3lsblnufza8hi5s4zL4ijeI8cCb46Ir0XhK1Ec27+MiHsjYouaKq0WEf8efby/e9T/zWWs\n5kXEWZTfNWUdtisf7xfF+27lcvrsiHhvFJ9L3wIOBd4bEcfHss+12vIiItaPiFdGxPfLY+nuiDiy\nXDghis++c8rndH8Zp6uieF9dVLPeYN5nr46Im8oyry9frwPKZXuU688vj4039vV6jxiZ6d8g/4AJ\nwKLy8U3ACeXjI4Cvl4+/BLytfDwW+AWwZzl9Y83jo4Dja/b9OeD0HuVNBB4Cti+nvwa8r3w8Bvgm\ncGQ5vRQ4tHw8jSLxeRFwIPD9Prb/aJ3neSlwbPn41cATwAE15bytZt0lwL/1nAZ2BH4FrFHOPxf4\nbfn4G8BHgJWAXwJTyvlrUrTgvAmYCdxdp24zgeeAGeX04cAP+xH7nvVeWhOLjwGPUSROAdwB7Fc+\njz/XlLUx8LfyODgQ+AewbrnsVOAbNa/zXsA6wD+ByeX8PYGrezyf3YBfAy8t97sU2LlcthewsHx8\nAHAhMKacflfXvrrK67HfVcqy1yz3+zBwS7nsUOC0OrE9Gji1fNx93PScLl+/m8sYjwXmAQfWxPUN\n5eu6X81r8TCwU83x+Ysy1l3Hy3Ll1ZT7aeCM8vFqwHeANbrWB/YH7gZeUVPPvwOrl9PbULxXVymn\ntwfuLR+fDFxQPh5XxnEbXvje/HxXvIDfAV8qH78CeKqMb/fxSh/HYY/n9g3gSOA04HvA2Jr519es\nd3JXfSjejwvL2P0I2LecPxn4ao/9vwjoZNlnRO1ruDnwfzXrfhy4onx8Xvk8J9DL+7tHOeOAR4CO\ncnq/cr31y1h+qWa/fwLeUtb/TxTvkfOAU2rqfC1FS0V3ecBsYBGwa/mcPlTzmTGfonWo6/2za7ns\nDOA3wOrAymV5mzP499mtwLvLx68DnizX37B8/hPKZdtSHO8vXtF3Srv/2eUxdN4B3BkR1/WY/3Fg\n+4j4KDAJWBd4cc3yKP/vBqwVETuU02OBv3avFPFSijfWZzLzhzXbvDEiDimnV6F4Y3T5PkBm3ln+\nIlq9R93qbV+vGfEtFEkSmfmbiLihx/Jb6jyfnnYGLs7MJ8rp0ym6fGpNoviA/HpEdO1nFWAqcH8v\n+wX4TWbeUT6eD8wpH68o9rX1hiJxguJD557M/DMUv0IpPsQ2Ax7oKiszfxURtwAd5XbzMvOR8vGd\nFAlDra3K/d5Tbn8ZcFnXwojYHDgT+M/M/HtErA48l5nX1Oxz7fLxrsAbgXllqMYAq/YWoMx8JiJ+\nBOwAvAQ4C3h3RKwJvBU4vrdt++nazFxcPo97KOLV5Wrgj5l5UTk9GVicmdeWdbuTIulg2cveeznA\n1RExgeIL9BOZ+US53ZuAnYDDM/Phmm3uzsx/lY93pTjGbq05xsZHxNrAfwIfLuv0PMUXARFxAsu/\nN8cBf6nZ/xXlNg9HxF97PHdY8XFY6yPAv1Mk1Ytr5tceq2cCN0XEpyi+4M7NzIxizMbpEbF7GZtP\ndW1QPtcLgF9l5ok9C83Mn0Uxpuu9ZXw6gEXlL+tZwP9k5kPxwheo3gs2meK47Sz3fVHZSgHF8X4h\nRdK+NUVytAPFl/GDmfnXiNgZ2LLc9rmI+F/gQxSJWZcjKRKJG4HLKRJDMnNRRJxH8XlzW1mPq8tt\nfgPc2nUsRMTDFK/VIwzwfRYR4ymOtzeX5d5fvr+g+Fz7UWY+VC67sTwuplMksyOWCcUQycw/RMSh\nwPkUv/S7XERxEH4XuIoiS6/3JlyJIsu+DiCKJuNVyserUvQnX5CZ59dsMwbYJzN/Xa63FssnFE/3\nKKNnuSv12H5N6icUS3tsu7jH8ifrlRMR43psU7uPpbzQSsA/c1k/OhGxDkVrwRZ11u/yfM3jrCln\nRbHvWe9ne9lnlzHUj+G4cv3aeGeddXvGjYiYnJn3RMQkil+l+2fmgppVnutlnytR/Eo9q9zPOJZ9\nCPbmMmAXYC2KD+cNgT2ATVjxB13P59Ozyb6v5/4e4P9FxEcy82SKOCx3nEUx8K6vpLHYceYdEbEB\nRZK7HXB7RLy1XPxPil/DF0fEVZn5+3J+7eu8EvCtzPxkTdmvyMx/RsRy9YqI9ShaHHp9b/bjuUP/\nPwOg+JKcC5wfEZtl5pKezyEzH4iIuyleu7dRfLGRmWdHxPcpvqB3Bo4pj68nKFrMVgHeV6/QiNgV\n+DJwIsUX9P3A2yla5H7Qo7713t+1ej32M/OXUXT5zgIeoPhc+265/JJy3Z7drmMo3mNdZa9G0Yqx\nTZ11e67/XI9l9d7XPdfrz/tsSZ3n2fWZVu9zorZOI5ZjKBrXfeBk5veAayia3bvsAHw2My8u192M\n4iCF4k3UdZBdB7w/iv7aMRTdEV+IiJWAi4FfZubnepR9HcUvGqLoh/w+8P4V1bOP7a/sZftrgXeX\n661P+cutF3+lGBsC8F81868G/qtMWgAO5oXJy6+BZyLi7WVZr6JoKp/eR3l96Sv2g/EzYFJEzCjr\ntwnFL5TOfm5/G/C6iNio3H4P4FsR8TKKD+0jM/PmHtv09sVzHXBIRKxRTv8P8K0VlH81xa/wKcDP\ngR9SdK1dk5n1ErxafwNeX34ZjKX41dpfP6Voov50FONKfg1kRPwnQERMA35M/Q/i5UTEFyha6b6f\nmYdTdIlNKhc/UP4q/ipFXOvt63pg/5p+8MPKsqH4VX9gFFamSPC2oTj+P9DzvTmA5z+Q4/COzDyd\nIjl6wfiQGmcAJwC31bSkzQWmZeY3KZK4tYC1I+ITZZn/nZm177naz5+3UHR/nEXRZbUHsFJm/oHl\nE+Ge7+96P0DuKaoTO5X12p3lk93LKVrEriuT57UoEqOuhOJaysSnfB3eTfG6dXmK4ngkM5+keF92\nrb8WRbdD1/orbPJawXp132dlkjYXOKgsdwOK91YCN1C0SE0sl20HrEfx/h/RTCga1/MN9UGKPs2u\n+Z8CLo+In1N8CHQCXQOqrqQ4Q+SdwGcpxkfcBTxKke0eAexD8Wtj01g2aO/OiHgtRTPg6mUT83yK\nvtmuZsGe9ar3xv8gxWCretvXej+wSUTcC5xT1rGv539GRNxB0Yz9CBTNfhTjJm4tY7EGxQfDsh0V\nzcxvpXgD/4Lig+X/ZeZP69SpP/qKfX/is9yyzHyU4vU4rfyF+G1gdi5/dk9f2/+V4lffN6M4Bfhw\nil/Ux1I0c3+4fH3vioirVlCvcyl+7f6sfP1eT9En3nslMh+nGMdyZ/nFcj3FB933VlB/ynVvokgG\nbqIYp9BrUT0fl18cn6OI2VKKL6NjIuIuitdmz/L1X5EvA1OiHMwJ/JaiCb3W5yl+xR75goplXk/x\nZfbDiJhPEf+urqljKX7B/oLiS/WqzLyc4kvkdxTH/S/L53REnedabxr6Pg572/Zg4NAousHq7fMq\nim6T2tM+Pwp8tjy2fgwcUz6f4yi6O2+u+fzYjSLRe11EXFLup6OMyVzgQWCDOuV+iDrv7+WeRNFV\nswfwP2Vd9mD5LqLLKFrHurpufwg8nJldA4M/BLysPK5/QdFaclydunR5B/CW8j35M4qu1a5W4hW+\nr1ewXr332exy2YHAvuUx/FWKY/GpzLyPYkDzZWWdjgN2q+nuHbFi+YRVVSubAidl5klV12UoRcR0\nYMvM/Go5/WHgTZm5fz+33x34ZGb21fUhICLmAZ/qaqJvF2Xr1T+B1TLz2RWtP5pFxJbAWZk5ueq6\ntMpwOz6iGMPyvcxcUNbtFxQDO1fYdTdS2UIx/KxF0fWxa9UVGWILKE5Ru6fM2rej7G5ZkYh4H/C/\nFL8W1IuIWCkiFlA0Uc+tuj4DUXYj3UdxZkzlXxbDWRSDDi+gODtnVBimx8cC4LtlK8zNwBdGczIB\ntlBIkqQhYAuFJElqmAmFJElq2LC+DkVE2B8jSVKLZGZ/T7V9gWGdUAA4xqMas2fP5rzzzqu6GqOW\n8a+Osa+Osa9W/Uu39J9dHpIkqWEmFKpr4sSJVVdhVDP+1TH21TH27c2EQnV1dHRUXYVRzfhXx9hX\nx9i3NxMKSZLUMBMKSZLUsGF9pcyIyOFcP0mSRoqIaOi0UVsoJElSw0woVFdnZ2fVVRjVjH91jH11\njH17M6GQJEkNcwyFJElyDIUkSaqeCYXqsi+zWsa/Osa+Osa+vZlQSJKkhjmGQpIkOYZCkiRVz4RC\nddmXWS3jXx1jXx1j395MKCRJUsMcQyFJkhxDIUmSqmdCobrsy6yW8a+Osa+OsW9vY6uugKTRo7Oz\n+Ot63NFRPO7oWPZYUntyDIWkSkSAb29p+HAMhSRJqpwJheqyL7Naxr86xr46xr69mVBIkqSGOYZC\nUiUcQyENL46hkCRJlWtqQhERm0XEjXXmz4qIn0fE3Ig4pJl10ODYl1kt418dY18dY9/emnYdioj4\nKPBO4Mke88cCJwPTgaeBuRFxRWb+rVl1kSRJzdW0MRQRsSdwN/CtzNyyZv5k4PjM3KWcPhmYm5mX\n1NmHYyikNlF7oar+GMwYioGWIan/hu0Yisy8DFhcZ9GawOM1008AazWrHpJaoxWt1baIS8NXFYMy\nF1EkFV3WAB6roB7qg32Z1TL+1TH21TH27a0V9/Lo2XxyH/CaiBgPPAVsA5zQ28azZ89m4sSJAIwf\nP54pU6bQUbZ5dh18TjvtdPXTl1/eybHHAhTT0Fn+7306YmDrv+ENcMwxzX0+XaqO52icnj9//rCq\nz0ifnj9/Po89VvyeX7hwIY1q6nUoImICcGFmbhkR+wOrZ+a5EbErcDRFsvG1zPzfXrZ3DIXUJo45\npvjrr8GMoeirjM7OZV0itWMtvPGY1D+NjqFoagtFZj4EbFk+vrBm/tXA1c0sW9LgteOXc23dIhxv\nIbWaV8pUXZ2dnd1NY2q94RT//rYk1CYeQ7nfwZTRyFU4h1PsRxtjX61he5aHpNGlFd8DftdIw5ct\nFJL61Kx7bjTzXh7eJ0QaOFsoJElS5UwoVFfPU+jUWsa/Osa+Osa+vZlQSJKkhjmGQlKfqh5DMdCz\nRway70bLkUYSx1BI6rdWtSgPZTntWGdpNDKhUF32ZVarWfH3y3nFPParY+zbWyvu5SFJwPJX4Jw5\nc9lltPu6AmdnJ+U9PwZmoNvMnDnwMiQt4xgKaRTp6ICbbmp+OTNnDl0rxUDvEQJDf58QaTRwDIWk\nfuvoKL5oB/IHA9/GwY3S6GNCobrsy6yW8V+mVclJVznGvjrGvr2ZUEijSKu/nIfbvoZDOdJI5RgK\nqcna8VbgtdrxvhjtWGepao2OoTChkFqoHb/orLM0OjgoU01hX2a1jH91jH11jH17M6GQJEkNs8tD\naqF2bIq3ztLoYJeHJEmqnAmF6rIvs1rGvzrGvjrGvr15Lw9JI8Jg7hMiaeg4hkIapNprSvTXYPr2\nB1NOo9r92hntwjhrOPE6FFJFvGmVhpIDSVU1B2WqKezLrJbxr46xr46xb2+OoZAGqbOz+FU5UAPd\nZubMgZchSa1mC4Xq6rADd4WaeyvwDm8FXhGP/eoY+/ZmQiFJkhpmQqG67MtcsWb+mKqNvz/aWstj\nvzrGvr2ZUEiD1KovehMKSe3A00alFvLUwNFhJF+jRCOXp41K0jDTqpZ7ewg0nJhQqC77Mqtl/Ktj\n7Ktj7Nub16GQpCHmNUo0GjmGQmohx1CMDl6WXe3IMRSSJKlyJhSqy77Mahn/6gxF7D2leHA87tub\nYyikJqu9RfXMmcuaqL1F9chlQqHRyDEUkjQMOL5GVXMMhSRJqpwJheqyL7Naxr86xr46xr69mVBI\nkqSGOYZCkoYBx1Coao6hkCRJlTOhUF32ZVbL+FfH2FfH2Lc3r0MhSRXxGiUaSRxDIUmSHEMhSZKq\nZ0KhuuzLrJbxr46xr46xb28mFJIkqWGOoZAkSY6hkCRJ1TOhUF32ZVbL+FfH2FfH2Lc3EwpJktQw\nx1BIkiTHUEiSpOqZUKgu+zKrZfyrY+yrY+zbm/fykCT1W+39Rzo7l91zxPuPyDEUkqRBiQA/okcO\nx1BIkqTKNS2hiMKZEXFrRNwQEf/RY/nbI2JeRNwWEe9tVj00OPZlVsv4V8fYV8fYt7dmjqHYA1g5\nM7eMiM2Ak8t5XU4ANgKeAn4VERdm5uNNrI8kSWqSpo2hiIiTgNsy87vl9B8zc72a5dcAhwL/AOYB\n0zNzUY99OIZCkoYpx1CMLI2OoWhmC8WaQG2Lw+KIGJOZS8vpeykSiSeBS3smE5IkqX00M6FYBKxR\nM92dTETEZGBXYALwL+CCiPivzLyk505mz57NxIkTARg/fjxTpkyhozw3qau/zemhn67tyxwO9Rlt\n08a/uumuecOlPsN9GoZuf/Pnz+fwww8fVs9vJE/Pnz+fxx57DICFCxfSqGZ2eewF7JaZB0XE5sBR\nmblruWx94DJg88x8PiK+DPwyM8/tsQ+7PCrS2dnZfeCp9Yx/dUZr7GuvKdFfg+ny6Kuc0Rr74aLR\nLo9mJhQBnAFsWs6aA0wHVs/McyPiPcBBwLPAb4B3ZebiHvswoZCkFjjmmOJvIAaTUAymHLXGsB1D\nUWYCh/aYvaBm+VnAWc0qX5IktY4XtlJdtf3Jaj3jX53RGvvOzqLFYSB/MPBt+grvaI39SOG9PNRW\nOjuXfSDV9sV2dHgfAakRHR19f9nXM9guD41M3stDbctz4KWh4xgKeS8PSVLDWtXCZ0viyGVCobrs\ny6yW8a/OaI39cEgoRmvsRwoTCkmS1DDHUKhtOYZCqpbvwZHFMRSSJKlyJhSqq9V9ma0qrl26aO1L\nro6xr46xb28mFBoWTCgkqb15YSvV5Q16qmX8q2Ps+1Z7cbmZM5ddU2IoLi5n7NubCYWGha7L/g7U\nQLeZOXPgZUhaxqvSqjd2eaiuVvdldnQUo8UH8gcD36ZdPgjtS66Osa+OsW9vJhSSJKlhXodCw0Lt\njb76azDnwA+mHEkaDRq9DoUJhdqWF9WRpKHjha3UFPZlVsv4V8fYV8fYtzcTCkmS1DC7PNS27PKQ\npKFjl4ckSaqcCYXqsi+zWsa/Osa+Osa+vXmlTLWVZl72V5I0eI6hkCRJjqGQJEnVM6FQXfZlVsv4\nV8fYV8fYtzcTCkmS1DDHUEiSJMdQSJKk6plQqC77Mqtl/Ktj7Ktj7NubCYUkSWqYYygkSZJjKCRJ\nUvVMKFSXfZnVMv7VMfbVMfbtzXt5SJJGtNp7AHV2Lrvvj/cAGlqOoZAkjRoR4NdKfY6hkCRJlTOh\nUF32ZVbL+FfH2FfH2Lc3EwpJktQwx1BIkkYNx1D0zjEUkiSpciYUqsu+zGoZ/+oY++oMNPateqk8\nJPrHhEKS1JZMKIYXEwrV1eHVXipl/Ktj7Ktj7NubV8qUJLWlzs5ikOVADXSbmTMHXsZoZAuF6rIf\nuVrGvzrGvjoDjX1HR3HGxkD+YODb2HDSPyYUkiSpYV6HQpLUlmpv9NVfg7kOxWDKaUeNXofChEKS\nNGp4YaveNe3CVhExaUV/gy1Uw5/9yNUy/tUx9tUx9u2tr7M8bgPuAnrLVt4A/NuQ10iSJLWdXrs8\nIuKczHxXrxuuYPlQsMtDkjSU7PLoXcvHUETEepn5x8EWOMCyTCgkSUPGhKJ3Vdwc7PODLUztw77M\nahn/6hj76jQr9p2dcMwxxd/Mmcse+1IPrQFfKTMzD2xGRSRJaoaOjtFx2mfVVtjlERGf6TkvMz/b\ntBotX7ZdHpIktUCjXR79aaH4S1dZwDS8uqYkSephhclBZp5V/v1vZr4beGUL6qWK2Y9cLeNfHWNf\nHWPf3lbYQtHjAlbrAhOaVx1JktSO+jOG4saayaeBr2bmNU2t1bKyHUMhSVILDNt7eUREAGdQXFHz\nGeCQzPxtzfI3AieVk38G3pGZz/XYhwmFJEkt0PLrUETEaf1cdQ9g5czcEvgkcHKP5WcDszNzG+Ba\n7EoZVuzLrJbxr46xr46xb2+DOWPj9H6utzVFokBm3gbM6FpQjst4FPhIRHQC/5aZDwyiLpIkaRjo\n614e62XmH3u5q+hzwEN99UdExDnA9zLzunJ6IfAfmbk0IrYEfghMBX4LXAV8MTM7e+zDLg9Jklqg\nmdeh+Ej5d1adZeOAxUBHH9svAtaomR6TmUvLx48CD2bmAoCIuJaiBaOz505mz57NxIkTARg/fjxT\npkyho7zkWVfzmNNOO+200047PbDp+fPn89hjjwGwcOFCGtVXC8V+mXlRrxtG/DozN+xj+V7Abpl5\nUERsDhyVmbuWy8YB9wPbZ+ZvI+IS4NyeZ4/YQlGdzs7O7gNPrWf8q2Psq2Psq9XMFopjI2LNPpav\n6Jv+MmD7iJhbTs+JiP2B1TPz3Ig4GLiwOBmEW1t1KqokSRp6fbVQHL2ijTPz2CGv0fJ1sIVCkqQW\nGLbXoRgKJhSSJLVGK24OphGqs7P463rc1XVZ/Lcvs0r2JVfH2FfH2Lc3E4pRrKNjWRIRsSy5gOUf\nS5K0Iv25l8cawMeBV1BcL+LuzHywBXWzy6OFIsBQS9Lo1YpLb3+d4uJTr6W458bXBluYJEkamfqT\nULwkM78OPJ+Zt/ZzG7W5Tvs8KmX8q2Psq2Ps21u/koOIeF35fz2KK2RKkiR1688YiskUdwbdiOLq\nlodl5p0tqJtjKBpQe9ZGfwxmDMVAy5AkDV9NH0ORmfdk5haZOT4zN29VMqHGtKLl0NZJSVKXXhOK\niPhe+f+RiHi4/HskIh5uXfVUFfsyq2X8q2Psq2Ps21uv16HIzL3L/+u2rjoaKp2dRTfGQAx0/Zkz\nB7a+JGnk6s8YiinAu4FVuuZl5kFNrldX2Y6hGKRjjin++mswYygGWoYkafhqxaW3zwNOA/4w2EIk\nSdLI1p/TRv+cmedm5nVdf02vlRrW6NkX/enL9AyP5rEvuTrGvjrGvr31p4ViYUR8ArgLSIDMvL6p\ntVLDWvFlb0IhSerSnzEU3+gxKx1DMfJ4Lw9JGt0aHUOxwoSiLGQS8BrgbuDhzFw62AIHwoSidUwo\nJGl0a/qFrSLi/cCZwOeB/wJOHWxhah/2ZVbL+FfH2FfH2Le3/gzK3A/YHngsM78CbNbcKkmSpHbT\nnzEUtwJbAT/OzO0i4pbM3LollbPLo6k6O5ddPrv2vhwdHQ64lKTRpuljKCLiA8C+wATgl8ANmXni\nYAscCBMKSZJaoxU3B/sqxZUyjwA+AZw72MLUPuzLrJbxr46xr46xb2/9GZT5G+BFmXlxZt4NXNr8\nakmSpHbSa5dHROyQmddHxC+AfwLHZuaNEXFjZm7bksrZ5SFJUks0814eOwPXA48CewKXRcS/A4sH\nW5gkSRqZeu3yyMwPlw8jMx8HdgNmA29oQb1UMfsyq2X8q2Psq2Ps21t/7uXxSYDMfCoi3gp8qLlV\nkiRJ7aY/p42uB3wRWAe4GLg7M29rQd0cQyFJUos0/bRR4Czg68A44CfAOWXBRwy2UEmSNLL0J6FY\nNTNvoLjL6K8BIuI8ioGaGqHsy6yW8a+Osa+OsW9v/RlD8UxE7AisFBGbU9xtdHZzqyVJktpJf8dQ\nnAhMBu4DjszMhc2vmmMoJElqlVaModgpM/fLzE0yc29g98EWJkmSRqZeE4qI2D8iLgT+JyK+U/5d\nBLynddVTVezLrJbxr46xr46xb299jaG4FngEeAnFmR4AS4HfNLtSkiSpvaxwDAVARKxLcdpoAK/I\nzJ82u2JluY6hkCSpBZp5L4+uAr4GbAGsDqxG0UKx+WALlCRJI09/BmW+AdgEuA7YCHimqTXSsGBf\nZrWMf3WrzE/+AAAabklEQVSMfXWMfXvrT0LxaNnvsHpm/r3ZFZIkSe2nP9ehOA74B/Ay4FXABpm5\nWQvq5hgKSZJapNExFP0dlLkG8DSwM/DzzPzLYAscCBMKSZJao2kXtoqIA7r+KO7b8TZgbWDHwRam\n9mFfZrWMf3WMfXWMfXvr6yyPjXpMBzAHeAr4ZtNqJEmS2k5/uzxeDZwP/Bo4PDOfaHbFynLt8pAk\njTqdncVf1+OOjuJxR8eyx0Ot6WMoIuJ9wOHAhzPzqsEWNBgmFJKk0S4CWvFV2MwxFK+MiOuBNwNv\nanUyoWrZl1kt418dY18dY9/e+hpDcS/wLHADcHrEsqQlM9/W5HpJkqQ20muXR0TM7G2jzLypaTVa\nvg52eUiSRrV26fLo16DMqphQSJJGktoBlv01mIRicOU0aQyFRjf7Mqtl/Ktj7KszGmLfqqdYRShN\nKCRJUsPs8pAkqUU6OuCmFoxCnDlz4K0UdnlIktQmOjqK8RAD+YOBb9Osi1/1xYRCdY2GvszhzPhX\nx9hXx9i3NxMKSZJapFUtB1W0UDiGQpKkYaxdrkNhC4UkSWqYCYXqsi+zWsa/Osa+Osa+vZlQSJKk\nhjVtDEUUdxM7A3gD8AxwSGb+ts56ZwGPZuan6ixzDIUkadTp7Fx2HYnay2h3dDRvwGWjYyj6utto\no/YAVs7MLSNiM+Dkcl63iHgP8HqgJTcbkySpHTQzcWiWZnZ5bA1cC5CZtwEzahdGxBbAG4GzmlgH\nDZJ9mdUy/tUx9tUx9u2tmQnFmsDjNdOLI2IMQES8HDgaeD8w6OYVSZI0PDSzy2MRsEbN9JjMXFo+\n3gd4CfADYF1g1Yi4PzO/2XMns2fPZuLEiQCMHz+eKVOm0FG2A3Vls04P/XRHR8ewqs9omzb+To/W\n6S7DpT4jeXr+/Pk89thjACxcuJBGNXNQ5l7Abpl5UERsDhyVmbvWWe9AYEMHZUqSVJ3hfGGry4Bn\nI2IucBLw4YjYPyIOaWKZGiI9fy2otYx/dYx9dYx9e2tal0fZtHBoj9kL6qx3frPqIEmSWsN7eUiS\npGHd5SFJkkYJEwrVZV9mtYx/dYx9dYx9ezOhkCRJDXMMhSRJGtb38hhVOjuLv67HXddg7+hov+ux\nS5I0ULZQNEEEtGG1l9PZ2dl9RTW1nvGvjrGvjrGvlmd5SJKkytlC0QQjoYVCkjS62ELRAq04k8mz\npSRJ7cyEoh9GY0Lh+eDVMv7VMfbVMfbtzYRCkiQ1zDEU/dDRATfd1NwyZs4cfq0UkqTRwzEULdDR\nUQyy7O8fDGz9TK9VIUlqbyYUqsu+zGoZ/+oY++oY+/ZmQtEPrWg9sIVCktTOHEPRBF6HQpLUbhxD\nIUmSKmdCobrsy6yW8a+Osa+OsW9v3m10iNTebXTmTDjmmOKxdxuVJI0GjqGQJEmOoZAkSdUzoVBd\n9mVWy/hXx9hXx9i3NxMKSZLUMMdQSJIkx1BIkqTqmVCoLvsyq2X8q2Psq2Ps25sJhSRJaphjKCRJ\nkmMoJElS9UwoVJd9mdUy/tUx9tUx9u3NhEKSJDXMMRSSJMkxFJIkqXomFKrLvsxqGf/qGPvqGPv2\nZkIhSZIa5hgKSZLkGApJklQ9EwrVZV9mtYx/dYx9dYx9ezOhkCRJDXMMhSRJcgyFJEmqngmF6rIv\ns1rGvzrGvjrGvr2ZUEiSpIY5hkKSJDmGQpIkVc+EQnXZl1kt418dY18dY9/eTCgkSVLDHEMhSZIc\nQyFJkqpnQqG67MuslvGvjrGvjrFvbyYUkiSpYY6hkCRJjqGQJEnVM6FQXfZlVsv4V8fYV8fYtzcT\nCkmS1DDHUEiSJMdQSJKk6plQqC77Mqtl/Ktj7Ktj7Ntb0xKKKJwZEbdGxA0R8R89lu8fET+LiJsj\n4oxm1UOSJDVf08ZQRMSewKzMPCgiNgM+mZl7lMtWAe4BXp+Zz0bEd4DvZOZVPfbhGApJklpgOI+h\n2Bq4FiAzbwNm1Cx7FtgyM58tp8cCzzSxLpIkqYmamVCsCTxeM704IsYAZOFvABHxAWD1zPxRE+ui\nAbIvs1rGvzrGvjrGvr2NbeK+FwFr1EyPycylXRMREcCXgNcCezWxHpIkqcmamVDMBXYDvhcRm1OM\nmah1NvB017iK3syePZuJEycCMH78eKZMmUJHRwewLJt1euinOzo6hlV9Rtu08Xd6tE53GS71GcnT\n8+fP57HHHgNg4cKFNKqZgzIDOAPYtJw1B5gOrA7MA24Hbi6XJfCVzLyixz4clClJUgs0OijTK2Wq\nrs7Ozu5MVq1n/Ktj7Ktj7Ks1nM/ykCRJo4QtFJIkyRYKSZJUPRMK1dVzxLVay/hXx9hXx9i3NxMK\nSZLUMMdQSJIkx1BIkqTqmVCoLvsyq2X8q2Psq2Ps25sJhSRJaphjKCRJkmMoJElS9UwoVJd9mdUy\n/tUx9tUx9u3NhEKSJDXMMRSSJMkxFJIkqXomFKrLvsxqGf/qGPvqGPv2ZkIhSZIa5hgKSZLkGApJ\nklQ9EwrVZV9mtYx/dYx9dYx9ezOhkCRJDXMMhSRJcgyFJEmqngmF6rIvs1rGvzrGvjrGvr2ZUEiS\npIY5hkKSJDmGQpIkVc+EQnXZl1kt418dY18dY9/eTCgkSVLDHEMhSZIcQyFJkqpnQqG67MuslvGv\njrGvjrFvbyYUkiSpYY6hkCRJjqGQJEnVM6FQXfZlVsv4V8fYV8fYtzcTCkmS1DDHUEiSpIbHUIwd\nyspIUjNMnDiRhx56qOpqSCPChAkTWLhw4ZDv1xYK1dXZ2UlHR0fV1Ri1jP/yyl9OVVdDGhF6ez95\nlockSaqcLRSShr3eflF1dhZ/XY+7GnU6OpY9XpGh2IfUTprVQmFCIWnY60+XRwQ0+nExFPuQhju7\nPNRSng9eLePfPh566CHGjBnD17/+9eXmn3TSScyZM2eF23/uc5/jyiuv7FdZ8+bNY9q0aYOqZ60r\nr7ySww8/vKF9zJo1i29+85sN16XL0Ucfzbe//e0+15k3bx777rvvC+bfdNNNTJ48ecjq0gzvete7\nuOGGG0ZseWBCIanNDDTXqrf+UOyj1pgxYzjyyCN58MEHl5sfseIfezfccAPPP/98v+oxffp07rzz\nzn6t25dZs2bx5S9/ueH9DKVjjz2Wd7zjHX2uM336dL773e/WXdafWFfpnHPOYbvtthux5YEJhXrh\nGQbVMv69G44JxaqrrsoRRxzBfvvtx+LFi1+w/IEHHmCHHXZgq622YoMNNmDPPffkueee44wzzuCO\nO+7gox/9KFdccQXPP/88H/nIR5gxYwZTp07loIMO4sknn+SPf/wjU6dOZdq0aUydOpV1112XtdZa\nC4BFixYxZ84c3vjGNzJlyhSOOOIIli5d2l2vY489lq233ppXv/rVnHrqqQCcf/75zJo1a4Xb13rk\nkUfYYYcdmDx5Mrvuuit//vOfu5etssoq/Pd//zcbbbQR8+bNY8yYMfzjH//oXl47/cUvfpFJkyYx\nY8YMPvzhD7PBBhsAMGfOHE4++WQA7rvvPnbccUfe+MY3Mm3aNM477zyg75aIJ554gv3335+pU6ey\n8cYbM3fu3D5jX6/eq666Kp/61KfYdNNN2WCDDbj44ovZd9992WijjXjLW97C008/DcDNN9/MFlts\nwZQpU3jTm97Edddd1x3XPfbYg7322ovJkyczY8YMfvWrXwGw7bbbcumllwJw1VVXMXXqVKZMmcJW\nW23F3XffzeWXX77ca7zGGmtw4IEH8tBDD/Ga17yGD37wg2y22WZMmjRpuaTquOOOY8aMGUybNo29\n9tqr+3WpLa9lMnPY/hXVkzTa1X4WHH10b+vUn19v/aHYR5eFCxfmGmuskZmZ22yzTR555JGZmXni\niSfmnDlzMjPzox/9aF5wwQWZmfn888/npptumpdeemlmZnZ0dHQ//uxnP5sf+9jHuvf96U9/Og87\n7LDlyvvd736X66+/fl5//fWZmXnQQQflaaedlpmZS5YsyXe+8515wgknZGZmROQZZ5yRmZnz5s3L\nVVZZJZ999tk877zzctasWb1u/6UvfekFz3PPPffMz3zmM5mZ+eCDD+aLX/ziPP/887vL6Xp+mZlj\nxozJRx999AXT1157bW600Ua5aNGizMw8+OCDc4MNNsjMzNmzZ+dJJ52Uixcvzk022STvuuuuzMx8\n/PHHc+ONN87bbrstOzs7c/LkyS+oW2dnZ44bNy5vv/32zMw85ZRT8i1vecsKY9+z3hHRHYvjjz8+\n11prrXzkkUdy6dKlOX369Lzwwgvz0UcfzZe97GXdZd1777350pe+NBcuXJjnnXderr322vnwww9n\nZuYHPvCBnD17dmYWr/Mll1ySf/nLX3L8+PF59913Z2bmpZdemrvssstyz+fKK6/MSZMm5d/+9rdc\nuHBhRkT+4Ac/yMzMSy65JCdMmJCZmeeff37ut99+uWTJkszMPPvss7v31VVePb19t5bzB/2d7YWt\nVJfXQaiW8e9dZ2cxeLKeevNnzmzOPur59re/zbRp09hxxx2Xm3/88cfzwx/+kBNOOIEFCxbwyCOP\n8OSTT3Yvz3KA3FVXXcXjjz/O9ddfD8DixYtZZ511utf7+9//zk477cRnP/tZtt9+++5tbr/9ds49\n91wAnnnmGcaMWdb4vPvuuwMwbdo0nnvuOf71r38tV7d629frPvjRj37ESSedBMCrX/3qFzSnb731\n1i94Pj1dc8017LPPPqyxxhoAvO9973tBP/+CBQv4zW9+w0EHHdS9n2eeeYa77rqL173udXX321Wn\nGTNmADBlyhS+8Y1vACuOfW29Afbaa6/u/U2ePJmXv/zlAGywwQb84x//4LbbbuO1r31td1kbb7wx\nW2+9dfe4p+nTp7PuuusCRcwvu+yy5fY/d+5cJk+e3N3Ssueee7Lnnnt2L//Zz37GoYceyo9//GNe\n+tKX8q9//YsXvehF7Lzzzt37/Oc//wnA1Vdfze2338706dMBWLp0aXcrShVMKCS1lY6O+l0QvZ2h\nccwxzdlHPa961as488wzOfDAAznggAO65++3334sXbqUfffdl912243f//73db90lyxZwle+8pXu\nhOSpp57imWeeAeDpp59m1qxZvP3tb+fAAw/s3mbp0qVcfPHFbLjhhgA8/vjjyyUUq6666nJl9Cx3\nyZIly22/aNGiugnFmDFjltt27Njlvz5e/OIX1y2ndnzI2LFjl9tHbT1r67P22msvN1bkr3/9K+PH\nj+enP/3pC9bvMm7cuO7HtWcxrCj2Peu98sor191nl6VLl9aN4fPPP8+4ceOWi3e9syl6xg3gnnvu\nYfLkySxYsIC9996bCy+8kEmTJnUvf9GLXlR3n0uWLOHjH/8473nPe4Ai1l3JRhUcQ6G6/HVcLePf\nXmq/NPbee2923nnn5QY9Xn/99XzmM59hn332ITO57bbbWLJkCVB8wXR96e64446cdtppPP/88yxd\nupSDDz6YT37ykyxZsoR99tmH17/+9Rx11FHLlb3jjjt2jz149tln2X333TnttNNWWM/etp81a1bd\n7XfaaSfOPvtsAH7/+99z44039hqPddZZhzvuuAOASy65pHv+rrvuyiWXXMKiRYsA+NrXvvaC5GXD\nDTdklVVW4YILLgDgD3/4A69//euZN29er+X1pa/YD8bmm2/OggULup/fvffey80339zv9+xmm23G\n/fffz3333QfA5Zdfzjvf+U7+8pe/sMsuu3DiiSfy5je/ebltemvx2XHHHTn33HN54oknAPj0pz/N\nO9/5zkE+s8bZQiGprQw016q3/lDso1bPL8VTTz2VuXPnds8/7rjj2GOPPXjJS17CaqutRkdHR/cZ\nIbNmzeLII4/kueee4zOf+QxHHHEEU6dO5U9/+hO77LILJ510EhdffDHXXHNN9+C7zCQi+L//+z++\n8pWv8KEPfYjJkyezePFitt9+ez72sY/VrVe9lodTTz2Vww8/vO72tU477TTmzJnDJptswnrrrcfU\nqVP7fP6HHXYYa6+9Nttvv313F8C2227LIYccwpZbbslqq63GJptswmqrrbbctuPGjeOKK67ggx/8\nIF/60pdYvHgxn//859liiy246aab+n4h6ugr9v2JT89lL3nJS7j44ot5//vfz1NPPcVKK63Eeeed\nx2te85rugaB9bb/OOutwwQUXcMABB7BkyRLWXHNNLrroIo4++mj+9re/ccopp3D88ccD8MpXvpLT\nTz+913odcsghPPzww2y++eaMGTOG9ddfn/PPP7//wRliXthKddmHXy3jv7zRdmGrK6+8kgULFnDE\nEUdUXZUhNW/ePG699VY+8IEPAHDKKafw85//nAsvvLBf23//+9/nC1/4Qp9dHypMnz6d44477gXj\necALW0nSqPH4449z2mmncfXVV1ddlSE1adIkbr75ZiZPnsymm27KDTfc0N3dsiKnn346733veznk\nkEOaXMv2tmTJEiZNmsTYsWPZaqutWlq2LRSShj3v5SENHe/lIWnU8vbl0tCxy0Mt5b0kqmX8JbUb\nEwpJktQwuzwkDXt2eUhDp1ldHl6HQtKwN2HChGF/N0mpXUyYMKEp+7WFQnV5HYRqGf/qGPvqGPtq\nDdtBmVE4MyJujYgbIuI/eiyfFRE/j4i5EeGJxcPM/Pnzq67CqGb8q2Psq2Ps21szuzz2AFbOzC0j\nYjPg5HIeETG2nJ4OPA3MjYgrMvNvTayPBuCxxx6rugqjmvGvjrGvjrFvb808y2Nr4FqAzLwNmFGz\nbCPggcxclJnPA7cA2zSxLpIkqYmamVCsCTxeM704Isb0suwJYK0m1kUDtHDhwqqrMKoZ/+oY++oY\n+/bWtEGZEXES8NPM/F45/fvMXL98PBn4YmbuWk6fDNySmZf22IcjMiVJapHhetroXGA34HsRsTlw\nT82y+4DXRMR44CmK7o4Teu6gkScmSZJap5kJxWXA9hHRdYP4ORGxP7B6Zp4bER8BrgcCODczH2li\nXSRJUhMN6+tQSJKk9lD5vTwiYrOIuLHHvJMj4t111h0TEV+LiFsi4icRsXHrajryDCT2NcvXiYjf\nR8Sk5tdw5Bpo7CNiXnk9lxsi4mutqeXINIjYf6K8ns7tETGnNbUcuQb4mX9gRNxYHvc/jYinImLN\n1tV2ZBlg7MdGxAXltaJu6s9nfqUJRUR8FDgHWLmcfmlE/ACY1csms4DMzK2Bo4DjWlLREWgQse+6\nfsj/Uox70SANNPYRsTJAZm5X/h3cssqOMIOI/Uxgi8zcEugAXtWiqo5IA41/Zp6fmdtm5nbAPOAD\nmbmoZRUeQQbxmb8LsFJmbgV8jn5831bdQvEgsGfN9IuBo4Fv1Vs5M68AujKpicA/m1m5EW5AsS+d\nCJwJPNzEeo0GA439G4DVI+K6iPhReaE4Dc5AY78j8MuIuBz4PnBVc6s34g3mc4eImAFsnJm2zg3e\nQGO/ABgbxU101gKeW1EBlSYUmXkZsLhmemFm3k4xULO3bZZGxHnAV4ALml7JEWqgsY+I2cBfM/OH\nva2j/hnEcf8UcEJm7ggcClxQc00XDcAgYv9Siiv67k0R++80vZIj2GA+80ufBI5tZt1GukHE/klg\nA+B+4Czg1BWV0ZYfSpk5G5gEnBsRq1ZcndFiDsVZOzcCU4BvRsQ6FddptFhAmTxn5gPAo8C6ldZo\n9HgUuC4zF2fmAuCZiHhp1ZUaTSJiLWBSZt5UdV1GmQ8D12bmhhStpN+MiBf1tcFwSSj69Ys3It4R\nEZ8oJ58BlgBLm1ar0aFfsc/MmWVf5rbAfOCAzPxrc6s24vW3pecg4CSAiHgFsAbgadaN6W/sbwF2\ngu7Yr0aRZKgxA2nl3Ab4cbMqMgr1N/b/YNkVrR+juMzESn1tMFwSip7nri43HRHnR8R6wKXA1Ii4\nCbgG+FBmPtuiOo5U/Y19X9tocPob+68B4yPiZuBC4KDMNJFuTL9in5lXA3dFxM+BK4DD0nPth8JA\nPnc2BH7bklqNDv2N/ZeB6RHxE+BHwCcz8+m+dux1KCRJUsOGSwuFJElqYyYUkiSpYSYUkiSpYSYU\nkiSpYSYUkiSpYSYUkiSpYSYU0ggXETMj4sKa6b0j4u461xep3eZdEbFSj3lHR8SvI2K/XrZ5VUTs\nNoT1/l4fyz4XEY9ExA5DVZ6kxphQSKNDAkTE/sDHge0y8499rP8p6l8V76TMvKiXbbYDtmqoljUy\nc+8+lh1FcXE7ScPE2KorIKklIiLeAXwA+M+uW0BHxDYUdxwMirsPvo3iUscvBy4C9uplZ4cBB1Bc\n/v524CPAJ4BVI2Iu8EfgqxQ3I3oGeBdFgnIxxd1q1wOuycyjIuIbwLMUdxB+OTA7M+dHxCOZuW5E\nTKa4GSAUl70+KDOfwJvUScOKLRTS6PBmii/1tYFxNfM3Bt6emdsBlwH7ZObXKe4V8t997O9A4H2Z\nuRVwXznvi8B3MvMq4ByKy1RvS3HL+1PKdSaU274J2C4ippbzF2bmTsBpwLvLeV2X8T273Nd2FK0S\nHxvok5fUfLZQSKPDw8D2FEnFBZQ3vCrnfzUinqBoNbilnB/03QJwEHBkREwEfsoLf5y8IjPvKR//\nBPgCRYLwi8x8HKC8P8aG5Tp3lf//AGzZY18bAWdEBBTJ0AN9P1VJVbCFQhodHszM5zLzdODZiPh/\n5fxzKLoYDqJILrqSiKX0/fnwLuA9ZQvENGCLHtv8qeyqAOiguAV7ABtHxCrlgM/NgHvLderdVKir\nLvdT3N12O4rxH1f18zlLaiFbKKTR52Dgzoi4BfgWcEtEPAn8HdikXOdm4AcUAy3ruafc7gmK8RK3\nAU8An4qIOykSjtOiaFZ4viwT4DmKcRQvAy7OzHsiorc7FHbNPwz4VkSMpUhaDu5lfUkV8m6jkgCI\niKOACzPzwV6WHw38OTPPGuT+J5T779mlMSjlYM4LM/P6odifpMbY5SGpy6oUp4v25cO9XYeilSLi\nc8COVddD0jK2UEiSpIbZQiFJkhpmQiFJkhpmQiFJkhpmQiFJkhpmQiFJkhpmQiFJkhr2/wFWvFlC\nUOpTNgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3b7e278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ustawienie jednostek umownych dla nat2Harm w kV\n",
    "myData['nat2HarmOdDwojYellow'] = AnalyzeCSVwrapper('nat2HarmOdDwojYellow')\n",
    "myData['nat2HarmOdDwojYellow'] = myData['nat2HarmOdDwojYellow']._replace(y=normalize(myData['nat2HarmOdDwojYellow'].y))\n",
    "myData['nat2HarmOdDwojYellow'] = myData['nat2HarmOdDwojYellow']._replace(x=unumpy.degrees(unumpy.arcsin(myData['nat2HarmOdDwojYellow'].x/ramie)))\n",
    "myData['nat2HarmOdDwojYellow'] = myData['nat2HarmOdDwojYellow']._replace(labels = myData['nat2HarmOdDwojYellow'].labels._replace(x=u\"Kąt [stopnie]\"))\n",
    "myData['nat2HarmOdDwojYellow']._plot(title = True, fun = lambda: plt.ylim(0,1.1), fmt='None')\n",
    "# niepewnosc z ostatniego zostala przeniesiona na pozostale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA3sAAAGFCAYAAABEyuqjAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkyRJkqQRZLInSZIkSSPov70YZxg3JtkqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d9e9710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ustawienie jednostek umownych dla nat2Harm w kV\n",
    "myData['nat2HarmOdFresnela'] = AnalyzeCSVwrapper('nat2HarmOdFresnela')\n",
    "\n",
    "x, y = myData['nat2HarmOdFresnela'].x, myData['nat2HarmOdFresnela'].y\n",
    "do_usrednienia = [0,10,20,30,40,70]\n",
    "for i in do_usrednienia:\n",
    "    delta = 0.5\n",
    "    i_m = i - delta\n",
    "    i_p = i + delta\n",
    "    warunek = (x>=i_m) & (x<=i_p)\n",
    "    mean = y[warunek].mean()\n",
    "    val_x = x[np.where(warunek)[0][0]]\n",
    "    y = np.delete(y, np.where(warunek)[0])\n",
    "    x = np.delete(x, np.where(warunek)[0])\n",
    "    y = np.append(y, mean)\n",
    "    x = np.append(x, val_x)\n",
    "\n",
    "myData['nat2HarmOdFresnela'] = myData['nat2HarmOdFresnela']._replace(x=x, y=y)\n",
    "myData['nat2HarmOdFresnela'] = myData['nat2HarmOdFresnela']._replace(y=normalize(myData['nat2HarmOdFresnela'].y))\n",
    "myData['nat2HarmOdFresnela']._plot(title = True, fun = lambda: plt.ylim(-0.1,1.1), loc = 2,rc=[10,4], tight = False, fmt='None')\n",
    "\n",
    "\n",
    "# niepewnosc z ostatniego zostala przeniesiona na pozostale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "zielony: 10.19 \\pm 0.05\n",
      "czerwony: 13.62 \\pm 0.05\n",
      "zolty: 11.44 \\pm 0.05\n",
      "0.952 \\pm 0.011\n"
     ]
    }
   ],
   "source": [
    "kat_dopasowania = {\n",
    "    'zielony' : ufloat(10.97, 0.05),\n",
    "    'zolty' : ufloat(12.30, 0.05),\n",
    "    'czerwony' : ufloat(14.60, 0.05)\n",
    "}\n",
    "ramie2 = ufloat(62, 0.1)\n",
    "\n",
    "kat_dopasowania_wkacie = {key : degrees(asin(value/ramie2)) for key, value in kat_dopasowania.iteritems()}\n",
    "for key, value in kat_dopasowania_wkacie.iteritems():\n",
    "    print('{}: {:L}'.format(key, value))\n",
    "    \n",
    "print('{:L}'.format((degrees(asin(ufloat(14.60, 0.03)/ramie2))-degrees(asin(ufloat(10.97, 0.03)/ramie2)))/360*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11.348+/-0.013 : 0.353+/-0.021\n",
      "11.396+/-0.013 : 0.559+/-0.026\n",
      "11.443+/-0.013 : 0.754+/-0.030\n",
      "11.490+/-0.013 : 0.914+/-0.034\n",
      "11.537+/-0.013 : 0.959+/-0.035\n",
      "11.561+/-0.013 : 1.00+/-0.04\n",
      "11.584+/-0.013 : 0.962+/-0.035\n",
      "11.631+/-0.013 : 0.890+/-0.033\n",
      "11.678+/-0.013 : 0.788+/-0.031\n",
      "11.726+/-0.013 : 0.660+/-0.028\n",
      "11.773+/-0.013 : 0.436+/-0.023\n"
     ]
    }
   ],
   "source": [
    "myData[\"nat2HarmOdDwojYellow\"]._print()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}