{ "cells": [ { "cell_type": "raw", "metadata": {}, "source": [ "%This notebook demonstrates the use of the workpackage template, replace with your own.\n", "\n", "\\documentclass[english]{workpackage}[1996/06/02]\n", "\n", "% input the common preamble content (required by the ipnb2latex converter)\n", "\\input{header.tex}\n", "\n", "% the following three lines are required to support the tikz examples\n", "\\usepackage{tikz}\n", "\\usepackage{sansmath}\n", "\\usetikzlibrary{shadings,intersections}\n", "\n", "% then follows the rest of the preamble to be placed before the begin document\n", "% this preamble content is special to the documentclass you defined above.\n", "\\WPproject{Computational Radiometry} % project name\n", "\\WPequipment{} % equipment name\n", "\\WPsubject{04-IntroductionToComputationalRadiometryWithPyradi} % main heading \n", "\\WPconclusions{} \n", "\\WPclassification{} \n", "\\WPdocauthor{CJ Willers}\n", "\\WPcurrentpackdate{\\today}\n", "\\WPcurrentpacknumber{} % work package number\n", "\\WPdocnumber{} % this doc number hosts all the work packages\n", "\\WPprevpackdate{} % work package which this one supersedes\n", "\\WPprevpacknumber{} % work package which this one supersedes\n", "\\WPsuperpackdate{} % work package which comes after this one\n", "\\WPsuperpacknumber{} % work package which comes after this one\n", "\\WPdocontractdetails{false}\n", "\\WPcontractname{} % contract name \n", "\\WPorderno{} % contract order number\n", "\\WPmilestonenumber{} % contract milestone number\n", "\\WPmilestonetitle{} % contract milestone title\n", "\\WPcontractline{} % contract milestone line number \n", "\\WPdocECPnumber{} % ecp/ecr number\n", "\\WPdistribution{}\n", "\n", "% bibfile added in this notebook\n", "%\\addbibresource{./analyseRio.bib} \n", "\n", "% this is entered just before the end{document}\n", "\\newcommand{\\atendofdoc}{\n", "\\bibliographystyle{IEEEtran}\n", "\\bibliography{references}\n", "}\n", "\n", "%and finally the document begin.\n", "\\begin{document}\n", "\\WPlayout\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# 4 Introduction to computational radiometry with pyradi" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook forms part of a series on computational optical radiometry. The notebooks can be downloaded from \\cite{Willers2014github}. These notebooks are constantly revised and updated, please revisit from time to time. \n", "\n", "This notebook was last tested with Python 3.8.3. Consider moving to Python 3.8 if you are not already using it.\n", "\n", "NOTE: The functions used in this notebook are mostly part of pyradi, available here \\cite{pyradiPythontoolkit2012}.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The date of this document and module versions used in this document are given at the end of the file. \n", "Feedback is appreciated: neliswillers at gmail dot com." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Overview" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook provides a description of the basics of radiometric spectral variables and conversions between spectral densities, generic filter functions, generic detector functions, and reading and plotting spectral data. \n", "It then moves on to how to calculate spectral integrals, calculate spectral effective values, spectral convolution, colour coordinate calculations, and spatial integrals." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "tags": [] }, "outputs": [], "source": [ "from IPython.display import display\n", "from IPython.display import Image\n", "from IPython.display import HTML" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Spectral variables" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Consider the mathematical sine function $s(t) = A \\sin(2\\pi f t)$. Here $f$ is the frequency, $t$ is time and $A$ is the amplitude. As a mathematical function all three these parameters determine the value of the function. A sine wave generator on an engineer's workbench creates a temporal sine wave, i.e., a wave shape of sinusoidal characteristics, that varies with time. The engineer can adjust the properties of the signal by changing the frequency $f$ or amplitude $A$ by turning a knob on the instrument. The engineer cannot adjust the time $t$, because time is not a free variable in the sine wave generator, time flows as part of the human reality. We can say that the sine wave _depends_ only on $f$ and $A$, but it _varies_ with time $t$.\n", "\n", "Imagine a pipe with water flowing through it. One can measure the volume of water flowing past a fixed point in a given time period; the longer the time period, the larger the water volume. It makes sense to define a temporal _flow rate_ expressed e.g., in cubic metres per second (at given time $t$). Now generalise this notion to some form of _density_ with units of [something/s], [something/m$^3$], or [something/$\\mu$m].\n", "These variables can be integrated over time/volume/spectral density to arrive at a cumulative quantity. The key observation here is that a quantity can be expressed as a density over time or volume, or in the radiometry case a quantity over a spectral band.\n", "\n", "The spectral domain is similar to the time domain: it is not a free variable that can be adjusted, but rather provides a domain of observation against which an object's properties can be calculated or measured. These properties are said to _vary_ with the spectral variable. Some spectral properties _depend_ on free variables, e.g., Planck radiance _depends_ on the temperature of the object, but _varies_ with spectral variable.\n", "\n", "Spectral domains (Sec 2.3.3) are commonly expressed in wavelength $\\lambda$, wavenumber $\\tilde{\\nu}$ (the number of waves that will fit into a 1-cm length, written as one word) or frequency $f$. In the optical domain wavelength and wavenumber are more commonly used than frequency. Wavelength is commonly given in units of nanometres (nm) or micrometres ($\\mu$m), wavenumber in (cm$^{-1}$) and frequency in [Hz].\n", "\n", "Spectral variables come in two varieties: variable without density (equivalent to the sine wave) and density variables (equivalent to the water in the pipe). Variables without density include spectral transmittance of a filter, the atmosphere or emissivity. Variables with density include Planck radiation. Spectral density values have units of \n", "[something/$\\mu$m], \n", "[something/cm$^{-1}$] or \n", "[something/Hz].\n", "\n", "The total quantity of a spectral variable over a spectral range is determined by integrating the spectral variable over the spectral range, similar to the water example above.\n", "\n", "Wavelength and wavenumber are related by $\\lambda = 10^4/\\tilde{\\nu}$ (Sec 2.3.3). The conversion of spectral densities requires the derivative of the previous relation $d \\tilde{\\nu} = -d\\lambda \\,10^4/\\lambda^2=-d\\lambda\\, \\tilde{\\nu}^2 /10^4$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "The sample grid spacing in wavelength and/or wavenumber is not critical, just so long that all the spectral data are on the same grid values. This common spacing is important when we multiply different spectral curves, e.g., sensor response, atmospheric transmittance and source radiance together as in \n", "$S\\;\\tau_\\textrm{atm}\\;L_\\textrm{source}$, as is shown in the following picture.\n", "\n", "![](pic/spectralmult.png)\n", "\n", "The $\\lambda$ sampling for all the elements must be on the same grid to obtain a meaningful result. \n", "If the various data curves are not sampled at the same spacing and we multiply the incorrectly shifted or scaled spectral scales, the result has no meaning.\n", "Doing spectral calculations with incorrect spectral grid spacing is like adding a number in base-2 to a number in base-10; it has no arithmetic meaning.\n", "\n", "Hence it is important for this and all other problems that we spectrally sample the source, the atmosphere and the sensor with exactly the same spectral grid. If the raw data from the files do not share a common spectral grid, we must interpolate all of them to the required common grid.\n", "\n", "Note that the Modtran data is provided on regular spacing in wavenumbers; but this means varying spacing in wavelength domain (recall from the relationship between wavenumber and wavelength given above) and from my book:\n", "\n", "![](pic/wnwlrelation.png)\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Spectral variables in pyradi" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Spectral variables are represented in Python as Numpy arrays (Sec D.3). These arrays are rank-one (N,) or rank-two (N,1), but always represent the spectral variable as a vector of values. The conversion between rank one and rank two is done by reshaping the vector." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Wavelength vector as rank one, has shape (101,)\n", "Wavelength vector as rank two, has shape (101, 1)\n", "Wavelength vector as rank two, has shape (1, 101)\n", "Wavelength vector as rank one, has shape (101,)\n" ] } ], "source": [ "%matplotlib inline\n", "import numpy as np\n", "\n", "#create a micrometre wavelength spectral range with 101 samples\n", "#from 400 nm to 800 nm\n", "wl1 = np.linspace(0.4, 0.8, 101) #rank (N,)\n", "wl2 = wl1.reshape(-1,1) #convert to rank (N,1)\n", "wl3 = wl2.reshape(1,-1) #convert to rank (1,N)\n", "wl4 = wl2.reshape(-1,) #convert back to rank (N,)\n", "print('Wavelength vector as rank one, has shape {}'.format(wl1.shape))\n", "print('Wavelength vector as rank two, has shape {}'.format(wl2.shape))\n", "print('Wavelength vector as rank two, has shape {}'.format(wl3.shape))\n", "print('Wavelength vector as rank one, has shape {}'.format(wl4.shape))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It appears that in Numpy a rank-one array (N,) behaves like a row vector (1,N) in some instances. In pyradi it is more convenient and natural to consider spectral variables as column vectors (N,1), therefore this rehaping from (N,) to (N,1) takes place quite frequently. Why consider spectral variables as (N,1) arrays? When saving spectral data to file, it seems more natural (and easier to view/edit) if the spectral range varies along the rows in the file: each spectral value is on a new line in the file. This approach also lends itself to saving more than one spectral variable in a file where the first column represents the spectral domain and all remaining columns represent spectral variables. A case in point is the Modtran tape7 file. So as a general rule: pyradi always expect spectral variables of one of the these shapes:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "tags": [] }, "outputs": [], "source": [ "wl1 = np.linspace(0.4, 0.8, 101) #rank (N,)\n", "wl2 = wl1.reshape(-1,1) #convert to rank (N,1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The pyradi library provides several conversion functions to convert between different spectral domains and also to convert between spectral densities. The units must consistently be in micrometres ($\\mu$m), wavenumber in (cm$^{-1}$) or frequency in [Hz] - any other units will provide incorrect results.\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import pyradi.ryutils as ryutils\n", "import pyradi.ryplot as ryplot\n", "\n", "wl = np.linspace(1, 14, 101).reshape(-1,1) # wavelength \n", "wn = ryutils.convertSpectralDomain(wl, type='ln') # wavenumber\n", "f = ryutils.convertSpectralDomain(wn, type='nf') # frequency\n", "\n", "p = ryplot.Plotter(1,1,3,figsize=(12,4));\n", "p.plot(1,wl,wn,'','Wavelength $\\mu$m', 'Wavenumber cm$^{-1}$',maxNX=5);\n", "p.plot(2,wl,f,'','Wavelength $\\mu$m', 'Frequency Hz',maxNX=5);\n", "p.plot(3,wn,f,'','Wavenumber cm$^{-1}$', 'Frequency Hz',maxNX=4);\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Converting spectral density values are similar to converting between spectral domains. In this example the `pyradi.ryplanck.planck` function\n", "is used to calculate the spectral density of Planck radiance (Sec 3.1, Sec D.4.1) for a temperature of 1000 K as a wavelength spectral density. This value is then converted to a wavenumber spectral density. Finally, the Planck radiance is calculated in the wavenumber domain, which should give the same result as the converted spectral radiance." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import pyradi.ryplanck as ryplanck\n", "\n", "wl = np.linspace(1, 14, 101)#.reshape(-1,1) # wavelength \n", "wn = ryutils.convertSpectralDomain(wl, type='ln') # wavenumber\n", "\n", "radiancewl = ryplanck.planck(wl,1000.0, 'el') / np.pi # W/(m2.sr.um)\n", "_,radiancewn1 = ryutils.convertSpectralDensity(wl,radiancewl, 'ln')\n", "radiancewn2 = ryplanck.planck(wn,1000, 'en') / np.pi\n", "\n", "p = ryplot.Plotter(2,1,3,figsize=(12,4))\n", "p.plot(1,wl, radiancewl,'Planck radiance','Wavelength $\\mu$m', \n", " 'Radiance W/(m$^2$.sr.$\\mu$m)',maxNX=4)\n", "p.plot(2,wn, radiancewn1,'Planck radiance','Wavenumber cm$^{-1}$', \n", " 'Radiance W/(m$^2$.sr.cm$^{-1}$)',maxNX=4)\n", "p.plot(3,wn, radiancewn2,'Planck radiance','Wavenumber cm$^{-1}$', \n", " 'Radiance W/(m$^2$.sr.cm$^{-1}$)',maxNX=4);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "See the section 'Performing-spectral-integrals' below." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Interpolation of Spectral Variables" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "SciPy has a number of interpolation options in `scipy.interpolate`. \n", "\n", "The one-dimensional interpolation scheme enables the definition of the lookup table as a function by using `scipy.interpolate.interp1d`. The user can define the interpolation scheme to be used - the default is `kind='linear'`, to do cubic interpolation use `kind='cubic'`. In the example below observe the difference between the two schemes. \n", "\n", "The example below is an ill-posed problem: normally one would have a much denser input data set. The purpose with using this poor data set is to illustrate the dangers of interpolation. Do not use a potentially unstable interpolation scheme such as cubic interpolation on a poor data set such as the one shown below.\n", "\n", "The input data set has only four samples. The ordinate (y) data has a slight oscillation. The abscissa (x) data are defined in the wavelength space. Equivalently, the abscissa (x) data are also defined in the wavenumber space, because $\\tilde{\\nu}=10^4/\\lambda$. This is the only information available, there is no requirement on the values between the stated abscissa.\n", "\n", "Important: *by selecting the interpolation scheme (linear, cubic, etc.), you are implicitly making a modelling assumption*. Linear interpolation in the wavelength space means a non-linear interpolation in wavenumber space and vice versa (because wavelength and wavenumber are nonlinearly related). Stated differently: if your input data set was compiled to be interpolated linearly in wavelength space (blue lines), then linear interpolation in wavenumber space will give the wrong results (red lines).\n", "\n", "Also, by *selecting between the linear and cubic (or any other scheme) you are also making a modelling assumption*. Compare the difference between the results for the linear interpolation (red/blue) and the cubic interpolation (green/cyan) lines.\n", "\n", "It is evident in the cubic interpolation graphs (green/cyan) that cubic/high-order interpolation schemes do not take kindly to large variations in abscissa increments. For example, the large increment from 10 to 20 in the wavelength space (green line) resulted in a huge variation in the spline curve. Likewise, the large wavenumber increment from 5000 to 10000 (or 1 to 2 $\\mu$m) (cyan line) causes a large variation.\n", "\n", "From this experiment we can draw the following conclusions:\n", "\n", "1. Clearly state the space (wavelength/wavenumber) where the input data set applies. Do interpolation *only* in the prescribed space.\n", "\n", "2. Ensure that the input data set samples at similar/even density throughput the abscissa domain. If no input data is available in some subranges in the abscissa domain, construct synthetic data by some modelling assumptions, to ensure even density. Such an even spread in abscissa values will limit wide swings in the high-order interpolation schemes.\n", "\n", "Thanks to Riana Willers for pointing out the subtle matter of interpolation in wavelength or wavenumber space." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from scipy import interpolate\n", "import pyradi.ryplot as ryplot\n", "import numpy as np\n", "%matplotlib inline\n", "\n", "# create input data in wavelength and wavenumber domain\n", "maxx = 24\n", "wl = np.asarray([1, 2, 5, 10, maxx])\n", "wn = 1e4 / wl # wl and wn values precisely align\n", "fn = np.asarray([2,3,1, 2, -1])\n", "\n", "# create the plotting samples - much tighter than input data\n", "wli = np.linspace(1,maxx,400)\n", "wni = 1e4 / wli\n", "\n", "#create the lookup functions\n", "fwll = interpolate.interp1d(wl,fn)\n", "fwlc = interpolate.interp1d(wl,fn, kind='cubic')\n", "fwnl = interpolate.interp1d(wn,fn)\n", "fwnc = interpolate.interp1d(wn,fn, kind='cubic')\n", "\n", "p = ryplot.Plotter(1,2,2,figsize=(12,8))\n", "p.plot(1,wli,fwll(wli),label=['wl scale interpolation - linear'],plotCol=['b'])\n", "p.plot(1,wli,fwnl(wni),'','Wavelength $\\mu$m',label=['wn scale interpolation - linear'],plotCol=['r'], maxNX=5)\n", "p.resetPlotCol()\n", "p.plot(2,wli,fwll(wli),label=['wl scale interpolation - linear'],plotCol=['b'])\n", "p.plot(2,wli,fwlc(wli),label=['wl scale interpolation - cubic'],plotCol=['g'])\n", "p.plot(2,wli,fwnc(wni),'','Wavelength $\\mu$m',label=['wn scale interpolation - cubic'],plotCol=['c'], maxNX=5)\n", "p.resetPlotCol()\n", "p.plot(3,wni,fwll(wli),label=['wl scale interpolation - linear'],plotCol=['b'])\n", "p.plot(3,wni,fwnl(wni),'','Wavenumber cm$^{-1}$',label=['wn scale interpolation - linear'],plotCol=['r'], maxNX=5)\n", "p.resetPlotCol()\n", "p.plot(4,wni,fwll(wli),label=['wl scale interpolation - linear'],plotCol=['b'])\n", "p.plot(4,wni,fwlc(wli),label=['wl scale interpolation - cubic'],plotCol=['g'])\n", "p.plot(4,wni,fwnc(wni),'','Wavenumber cm$^{-1}$',label=['wn scale interpolation - cubic'],plotCol=['c'], maxNX=5);\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Generic spectral filter response" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In most real-world system analyses, filter spectral responses will be measured and used in tabular formats. However, in some instances it is convenient to create spectral filter shapes according to a parameter set. The pyradi library has a function `pyradi.ryutils.sfilter` to assist in calculating a variety of spectral filter shapes. This function has the form (Sec D.4.2):\n", "\n", "$$\\tau_\\lambda =\\tau_s + \\tau_p\n", "\\exp\\left[ -\\left(\\frac{2(\\lambda-\\lambda_c)}{\\Delta\\lambda}\\right)^s\\right].\n", "$$\n", "\n", "This function takes a spectral variable $\\lambda$, the centre wavelength $\\lambda_c$, the spectral width $\\Delta\\lambda$, the sharpness of cutoff $s$ (if $s=2$, the\n", "curve has a Gaussian shape, and if $s=\\infty$, the curve has a square top-hat shape), transmittance in the pass band $\\tau_p$ and stop band $\\tau_s$ and the type of filter. The use of the function is best demonstrated by graphical means." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [] }, "outputs": [], "source": [ "wavelength = np.linspace(0.1, 1.3, 350).reshape(-1, 1)\n", "\n", "#demonstrate the different filter types\n", "width = 0.4\n", "center = 0.9\n", "filterExp=[2, 2, 4, 6, 8, 12, 500] # shaprness\n", "filterPass=[0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 0.99] # tau pass\n", "filterSupp = np.asarray(filterPass) * 0.1 # tau stop\n", "filterType=['bandpass', 'lowpass', 'highpass', 'bandpass', 'lowpass', \n", " 'highpass', 'bandpass']\n", "filterTxt = [r's={0}, $\\tau_p$={2}, {1}'.format(s,y,z) for s,y,\n", " z in zip(filterExp, filterType, filterPass) ]\n", "filters = ryutils.sfilter(wavelength,center, width, filterExp[0], \n", " filterPass[0], filterSupp[0], filterType[0])\n", "\n", "for i,exponent in enumerate(filterExp[1:]):\n", " tau=ryutils.sfilter(wavelength,center, width, filterExp[i+1],filterPass[i+1], \n", " filterSupp[i+1], filterType[i+1])\n", " filters = np.hstack((filters,tau))\n", "\n", "#plot sample filters \n", "smpleplt = ryplot.Plotter(1, 1, 1, figsize=(10, 4));\n", "smpleplt.plot(1, wavelength, filters,\n", " r\"Optical filter for $\\lambda_c$={0}, $\\Delta\\lambda$={1}\".format(center,width),\n", " r'Wavelength $\\mu$m', r'Transmittance', \\\n", " ['r', 'g', 'y','g', 'b', 'm','c'],label=filterTxt,maxNX=5,xAxisFmt=\"%.2f\");" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#all passband, different shapes\n", "width = 0.5\n", "center = 0.7\n", "filterExp=[2, 4, 6, 8, 12, 500] # sharpness\n", "\n", "filterTxt = ['s={0}'.format(s) for s in filterExp ]\n", "filters = ryutils.sfilter(wavelength,center, width, filterExp[0], 0.8, 0.1)\n", "for exponent in filterExp[1:]:\n", " filters = np.hstack((filters, ryutils.sfilter(wavelength,center, width, \n", " exponent, 0.8, 0.1)))\n", "smpleplt = ryplot.Plotter(1, 1, 1, figsize=(10, 4));\n", "smpleplt.plot(1, wavelength, filters,\n", " r\"Optical filter for $\\lambda_c$=0.7,$\\Delta\\lambda$=0.5,$\\tau_{s}$=0.1, $\\tau_{p}$=0.8\",\n", " r'Wavelength $\\mu$m', r'Transmittance', \\\n", " ['r', 'g', 'y','b', 'k', 'm'],label=filterTxt,maxNX=5,xAxisFmt=\"%.2f\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Detector spectral response" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Detector spectral responsivity values are also normally measured or taken from detector data sheets. In the absence of such information the shape can be calculated from a detailed bulk detector model, such as provided in `pyradi.rydetector`, but sometimes a simplified shape is required. Such a simple photon detector responsivity can be calculated with the `pyradi.ryutils.responsivity` function. The function takes the form (Sec D.4.3):\n", "\n", "$${\\cal R}_\\lambda= k\\left[\n", "\\left(\\frac{\\lambda}{\\lambda_c} \\right)^a -\n", "\\left(\\frac{\\lambda}{\\lambda_c} \\right)^n\n", "\\right]\\;\\;\\;{\\rm for}\\;\\;\\; {\\cal R}_\\lambda>0, \\;\\;\\; 0 \\;\\;\\;{\\rm otherwise}.$$\n", "\n", "This function takes a wavelength spectral variable $\\lambda$, the peak wavelength value $\\lambda_c$, the sharpness of cuton (lower wavelength range) $a$, the sharpness of cutoff (longer wavelength range) $n$, and an amplitude scaling factor $k$. Best results are obtained for $0\\leq a \\leq 5$ and $5\\leq n \\leq 50$. \n", "The use of the function is best demonstrated by graphical means." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "lwavepeak = 1.2\n", "params = [(0.5, 5), (1, 10), (1, 20), (1, 30), (1, 1000), (2, 20)] #cut-on and cut-off\n", "parameterTxt = ['a={0}, n={1}'.format(s[0], s[1]) for s in params ]\n", "responsivities = ryutils.responsivity(wavelength,lwavepeak, params[0][0], params[0][1], 1.0)\n", "for param in params[1:]:\n", " responsivities = np.hstack((responsivities, ryutils.responsivity(wavelength,lwavepeak, param[0], param[1], 1.0)))\n", "\n", "smpleplt = ryplot.Plotter(1, 1, 1, figsize=(10, 4))\n", "smpleplt.plot(1, wavelength, responsivities, \"Detector Responsivity for $\\lambda_c$=1.2 $\\mu$m, k=1\", r'Wavelength $\\mu$m',\\\n", " r'Responsivity', \\\n", " ['r', 'g', 'y','b', 'k', 'm'],label=parameterTxt,maxNX=5,xAxisFmt=\"%.2f\");" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# here we simply multiply the responsivity and spectral filter spectral curves.\n", "# this is a silly example, but demonstrates the spectral integral.\n", "filtreps = responsivities * filters\n", "parameterTxt = [str(s)+' & '+str(f) for (s, f) in zip(params, filterExp) ]\n", "\n", "smpleplt = ryplot.Plotter(1, 1, 1, figsize=(10, 4))\n", "smpleplt.plot(1, wavelength, filtreps, \"Filtered Detector Responsivity\",\n", " r'Wavelength $\\mu$m',\\\n", " r'Responsivity', \\\n", " ['r', 'g', 'y','b', 'k', 'm'],label=parameterTxt,legendAlpha=0.5,maxNX=5,xAxisFmt=\"%.2f\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Plotting of spectral variables" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The title appears trivial, but there is a hidden subtlety when working with and plotting radiometric variables. In the section above ``spectral variables in pyradi'', the data was created in the wavelength domain (using the `linspace` function), but plotted in both wavelength and wavenumber domains. Note that the data was not resampled to wavenumber domain before plotting: the wavenumber plots are not at constant intervals. The wavelength domain was merely recalculated to wavenumber domain. This is illustrated in the graph below." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "wlc = np.linspace(0.5, 8.5, 17).reshape(-1,1) # wavelength \n", "wnc = ryutils.convertSpectralDomain(wlc, type='ln') # wavenumber\n", "p = ryplot.Plotter(2,1,3,figsize=(18,2))\n", "for i in range(wlc.shape[0]):\n", " p.plot(1,np.array([wlc[i],wlc[i]]), np.array([0,1.]), 'Constant wavelength intervals',\n", " 'Wavelength $\\mu$m', plotCol=['r'], markers=['o'], maxNY=1)\n", " p.plot(2,np.array([wnc[i],wnc[i]]), np.array([0,1.]), 'Non-constant wavenumber intervals',\n", " 'Wavenumber cm$^{-1}$',plotCol=['r'], markers=['o'], maxNX=5, maxNY=1, pltaxis=[0, 10000, 0, 1]);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data and the plot are equally 'valid' or true in either domain, because the domain merely samples the data at different spectral intercepts. So we can load and process data in either domain and plot in either domain, without losing any truth value. Plot in whatever domain illustrates your argument the best.\n", "\n", "You should however take care when dealing with spectral densities: it is possible and mathematically allowable to plot a wavenumber density with units of W/(m$^2$.sr.cm$^{-1}$) against a wavelength domain with units of $\\mu$m, but it does not make much practical sense to do so." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Consider the intervals in both cases, here calculated with `numpy.diff`. Note that the intervals are constant and positive for the wavelength scale, but negative and non-constant for the wavenumber scale as converted from the wavelength scale. Recall from Section `Spectral-variables' above, that $d \\tilde{\\nu} = -d\\lambda \\,10^4/\\lambda^2=-d\\lambda\\, \\tilde{\\nu}^2 /10^4$. In other words the spectral intervals change in the opposite sense: the wavelength domain scale increases (positive intervals), but when converted to wavenumber domain the scale decreases (negative intervals)." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "p = ryplot.Plotter(3,1,3,figsize=(18,2))\n", "p.plot(1,(wlc[1:]+wlc[:-1])/2, np.diff(wlc,axis=0), 'Constant wavelength intervals',\n", " 'Wavelength $\\mu$m',maxNX=5,xAxisFmt=\"%.2f\");\n", "p.plot(2,(wnc[1:]+wnc[:-1])/2, np.diff(wnc,axis=0), 'Non-constant wavenumber intervals',\n", " 'Wavenumber cm$^{-1}$',maxNX=5,xAxisFmt=\"%.0f\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Mixing spectral data from different sources" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "When working with mixed domains, e.g., Modtran transmittance data in wavenumber domain and sensor spectral response in wavelength domain, you have to resample from the one to the other, to at least get samples at the same spectral intercepts. So, work in either domain, but be sure that the sampled data all relate to the same fundamental spectral baseline. The pyradi library provides functions to resample data when reading in the data from file, with minimal coding overhead (see `ryfiles.loadColumnTextFile`)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Performing spectral integrals" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A repeating pattern in computational radiometry is the spectral integral: integrating the sum of a spectral variable between an upper and a lower limit. For example, this calculation is required to determine the total inband radiance over a wide spectral range. We use the mathematical integral notation to indicate such integrals, but in practice, these are calculated using numerical summation.\n", "$$\n", "L = \\int_{\\lambda_0}^{\\lambda_1} L_\\lambda d\\lambda = \\sum_{i=0}^{N}L(i)\\Delta\\lambda(i)\n", "$$\n", "where the sample $i=0$ corresponds with the sample at $\\lambda_0$ and the sample $i=N$ corresponds with the sample at $\\lambda_N$.\n", "The sum above is a general statement and does not make any assumption about the spectral domain sampling interval. \n", "If the spectral domain sampling interval has fixed increments $\\Delta\\lambda(i)=\\Delta\\lambda$ then\n", "$$\n", "L = \\int_{\\lambda_0}^{\\lambda_1} L_\\lambda d\\lambda = \\Delta\\lambda\\sum_{i=0}^{N}L(i).\n", "$$\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "The spectral interval (constant interval on wavelength or wavenumber) is not of major significance when performing spectral multiplications or when plotting the data. It is however necessary to allow for the (potentially varying) spectral intervals when doing spectral integrals.\n", "\n", "![](pic/TrapezoidRule1.png)\n", "\n", "The picture above shows non-constant intervals on the $x$ axis. When using the trapezoidal rule the integral is calculated as the summation of areas where the area is given by the $\\Delta x$sampling along the $x$ axis and the mean height along the $y$ axis\n", "\\begin{equation}\n", "\\int_a^b f(x) dx \\approx \\sum_{n=0}^{N-1}\\frac{1}{2}(f_n+f_{n+1})(x_n-x_{n+1}).\n", "\\end{equation}\n", "If the intervals along the $x$ axis is constant, the integral reduces to\n", "\\begin{equation}\n", "\\int_a^b f(x) dx \\approx \\Delta x\\sum_{n=0}^{N-1}\\frac{1}{2}(f_n+f_{n+1}).\n", "\\end{equation}\n", "Both Matlab and Python have a trapezium integration function `trapz` where the user supply values for the $x$ sampling points and the $y$ function values as two matched vectors. The function then performs the integral as defined in the first equation above, accounting for nonconstant intervals in $x$.\n", "\n", "So in summary, spectral multiplication and integration \n", "\n", "1. requires all spectral variables to be on the same spectral sampling grid and \n", "1. allows numeric integration by the trapezium rule provided the spectral sampling vector is given as the $x$ vector." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "In pyradi the spectral integrals are typically (and naively) calculated using the `numpy.trapz` trapezoidal integration function. This function has the signature \n", " `numpy.trapz(y, x=None, dx=1.0, axis=-1)` \n", "where `y` is the value to be integrated, `x` is the sampling points $(x_0, x_1, x_2,\\cdots,x_N)$ corresponding to each of the samples in $y$, `dx` a scalar for the *constant* $\\Delta x$, and `axis` is the axis along which integration is done.\n", "If the spectral domain $x$ is sampled at regular intervals the `x` array is not required and unless `dx` is specified, it is assumed that `dx`=1. \n", "\n", "If the spectral variable is not on constant intervals, such as wavenumber values converted to wavelength values by $\\lambda = \\num{1e4}/\\tilde{\\nu}$,\n", "the $x$ vector must be supplied.\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "wl = np.linspace(1, 14, 1001)#.reshape(-1,1) # wavelength \n", "temperature = 1000.0 # K\n", "radiancewl = ryplanck.planck(wl,temperature, 'el') / np.pi\n", "print('Integral(1) = {} W/(m^2.sr)'.format( (wl[1]-wl[0]) * np.trapz(radiancewl)) )\n", "print('Integral(2) = {} W/(m^2.sr)'.format( np.trapz(radiancewl, dx=(wl[1]-wl[0]))) )\n", "print('Integral(3) = {} W/(m^2.sr)'.format( np.trapz(radiancewl,wl)) )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If the spectral interval is not constant, i.e, wavelength domain converted to wavenumber domain, the `dx` or pre-multiplication approach is no longer valid. The only possibility to calculate the integral is to give the value of `x`, with its non-constant intervals. Continuing from the previous example, convert the wavelength domain to the wavenumber domain, calculate the spectral density in wavenumber units W/(m$^2$.sr.cm$^{-1}$) and calculate the integral using the (non-constant-interval) wavenumber domain as `x`:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "wn = ryutils.convertSpectralDomain(wl, type='ln') # wavenumber\n", "radiancewn = ryplanck.planck(wn, temperature, 'en') / np.pi\n", "print('Integral(wn) = {} W/(m^2.sr)'.format( np.trapz(radiancewn, wn )))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What happened here? The integral appears to have (practically) the same absolute values, but the sign is wrong!\n", "\n", "Recall from Section Spectral-variables above, that $d \\tilde{\\nu} = -d\\lambda \\,10^4/\\lambda^2=-d\\lambda\\, \\tilde{\\nu}^2 /10^4$. We can see this by taking the first few elements of the `numpy.diff` along the spectral domains. Notice also that the wavelength interval is fixed, but the wavenumber interval varies." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print('First 5 intervals in wl: {}'.format(np.diff(wl)[:5]))\n", "print('First 5 intervals in wn: {}'.format(np.diff(wn)[:5]))\n", "#now calculate the intervals using the equations above:\n", "print('First 5 intervals in wn: {}'.format( - np.diff(wl)[:5] * 1.0e4 / ((wl[:5] + wl[1:6])/2. )**2 ))\n", "print('First 5 intervals in wn: {}'.format( - np.diff(wl)[:5] * ((wn[:5] + wn[1:6])/2. )**2 / 1.0e4))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The intervals are correct in absolute magnitude (corresponding to the spectral samples), just opposite in sign. To fix this, just take the negative or the absolute value as in" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print('Integral(wn) = {} W/(m^2.sr)'.format( - np.trapz(radiancewn, wn )))\n", "print('Integral(wn) = {} W/(m^2.sr)'.format( np.abs( np.trapz(radiancewn, wn ))))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The other alternative is to flip the spectral domain around (to obtain positive increments) and then do the integral. But there is a catch here: the intervals are not constant, so you must flip (`numpy.flipud`) both the spectral density and spectral domain variables, to ensure matching elements." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#flip only wavenumber but not the wavenumber spectral density \n", "print('Integral(wn) = {} W/(m^2.sr) - wrong because of a mismatch between x and y ordering'.\\\n", " format( np.trapz(radiancewn, np.flipud(wn) )))\n", "#flip both wavenumber and wavenumber spectral density \n", "print('Integral(wn) = {} W/(m^2.sr)'.format( np.trapz(np.flipud(radiancewn), np.flipud(wn) )))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Converting wideband values between radiant and photon rate units" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The relationship between the photon rate radiometric units and radiant units are well defined for a single wavelength. It is best to calculate the spectral photon rate units from first principles and then integrate over the spectral band of interest. However on occasion the information may only be available in wideband radiant units, but the quantity must be expressed in photon rate units. For wideband data the question then arises which wavelength should be used in the conversion? This section determines the appropriate wavelength to be used for the conversion for a given spectral band and source spectrum.\n", "\n", "The appropriate conversion wavelength is determined at the wavelength where an accurate spectral calculation gives the same answer as an approximate wideband calculation. The experimentation below indicates that the conversion wavelength is slightly longer than the center of the spectral band - photons at longer wavelengths have lower energy than at shorter wavelengths.\n", "\n", "Responsivity is given by\n", "\\begin{equation}\n", "R_e = \\frac{\\eta q \\lambda}{hc},\n", "\\end{equation}\n", "from which quantum efficiency can be determined as\n", "\\begin{equation}\n", "\\eta = \\frac{R_e hc}{q \\lambda}.\n", "\\end{equation}\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# to investigate the conversion for broadband data between photon rate units and radiant units\n", "import scipy.constants as const\n", "\n", "spec = np.loadtxt('data/InSb.txt')\n", "wl = spec[:,0].reshape(-1)\n", "respW = 2. * spec[:,2].reshape(-1)\n", "respQ = respW * const.h * const.c / (wl * 1e-6 * const.e)\n", "\n", "wlNan = np.where(respW==0,np.nan,wl)\n", "wlcent = np.mean([np.nanmax(wlNan), np.nanmin(wlNan)])\n", "print('wl min = {}'.format(np.nanmin(wlNan)))\n", "print('wl mid = {}'.format(wlcent))\n", "print('wl max = {}'.format(np.nanmax(wlNan)))\n", "\n", "p = ryplot.Plotter(1,2,2,figsize=(10,6));\n", "p.plot(1, wl,respW, 'Radiant domain','Wavelength $\\mu$m','Responsivity A/W',maxNX=5,xAxisFmt=\"%.2f\");\n", "p.plot(2, wl,respQ,'Quantum domain ','Wavelength $\\mu$m','Quantum efficiency',maxNX=5,xAxisFmt=\"%.2f\");\n", "\n", "q = ryplot.Plotter(2,1,1,figsize=(8,4))\n", "for temp in [250.,300.,350.]:\n", " Ve = respW * ryplanck.planck(wl,temp,'el') / np.pi\n", " Vq = respQ * ryplanck.planck(wl,temp,'ql') / np.pi\n", " Vei = np.trapz(Ve,-wl,axis=0)\n", " Vqi = np.trapz(Vq,-wl,axis=0)\n", " \n", " # convert from W to q/s\n", " qW = const.h * const.c / (wl * 1e-6)\n", " ratio = ((Vei/qW) / Vqi ) / (np.max(respW)/np.max(respQ))\n", " wlu = np.interp(1.,ratio[::-1],wl[::-1])\n", " q.plot(1, wl,ratio, 'Ratio (normalised responses) as function of conversion wavelength',\n", " 'Wavelength $\\mu$m', 'Ratio',\n", " label=['{} K, crossover at {:.3f} $\\mu$m'.format(temp,wlu)],maxNX=5,xAxisFmt=\"%.2f\");\n", " \n", " p.plot(3, wl,Ve, 'Radiant domain',\n", " 'Wavelength $\\mu$m', 'A/(m$^2$.sr.$\\mu$m)',\n", " label=['{} K, {:.3e} A/(m$^2$.sr)'.format(temp,Vei)],maxNX=5,xAxisFmt=\"%.2f\");\n", " p.plot(4, wl,Vq, 'Quantum domain ',\n", " 'Wavelength $\\mu$m', 'q/(s.m$^2$.sr.$\\mu$m)',\n", " label=['{} K, {:.3e} q/(s.m$^2$.sr)'.format(temp,Vqi)],maxNX=5,xAxisFmt=\"%.2f\");\n", "# p.plot(4, wl,Ve/const.e);\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Effective value normalisation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The effective value of a spectral variable is given by (Sec 7.2.2)\n", "\n", "$$\n", "{F}_{\\rm eff} = \\frac\n", "{\\int_{0}^{\\infty}{F} {G}\n", "d\\lambda}\n", "{\\int_{0}^{\\infty}{G} \\lambda},\n", "$$\n", "\n", "where ${F}$ is the variable in question, and ${G}$ is a weighting function. Note that the effective value\n", "of $F$ depends on the shapes of both $F$ and $G$; the effective value of $F$ thus calculated therefore applies only to the specific weighting function $G$ - it is incorrect for any other shapes. \n", "\n", "To demonstrate the sensitivity of the effective value normalisation to the spectral variability of the input spectra, consider the effective detector responsivity calculated at different blackbody source temperatures from 500 K to 2000 K. The InSb detector is modelled using the simple detector model in `ryutils.responsivity`. The source radiance is the weighting function $G$, calculated by using `ryplanck.planck`. The following graphs show the spectral detector responsivity ($F$ in the above equation) and the effective responsivity as calculated for the range of temperatures. The calculation requires the calculation of a separate quotient and integral for each temperature, yet there are no loops! This magic is achieved by constructing two-dimensional arrays with wavelengths along the row (0'th) axis and temperature along the column (1'st) axis. The first of these arrays is returned by the `ryplanck.planck` function (because a vector of wavelengths and a vector of temperatures are passed to the function). The second array is obtained by using the `numpy.meshgrid` array (google to see how this function works). The two arrays are used to calculate the numerator of the quotient. The integrals are implemented using the `numpy.trapz` function, integrating along the wavelength axis=0 direction. This integration returns a vector of values corresponding to the temperature values along the columns axis=1.\n", "\n", "Note the very wide variation in effective responsivity when calculated with different source temperatures. This stems from the fact that the responsivity is weighted differently by the different Planck radiance curves resulting from the different source temperatures. The highest effective responsivity occurs near the wavelength where the peak of the Planck radiance matches the peak of the detector responsivity." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "wavelength = np.linspace(0.1, 20, 305).reshape(-1, 1)\n", "detector = ryutils.responsivity(wavelength, 6.1, 1, 15, 1.0)\n", "temperatures = np.linspace(500, 2000, 41)\n", "spectralBaseline = ryplanck.planck(wavelength,temperatures,'el')\n", "_, detVar = np.meshgrid(temperatures, detector)\n", "spectralWeighted = spectralBaseline * detVar\n", "effResp = np.trapz(spectralWeighted, wavelength, axis=0 ) / np.trapz(spectralBaseline, wavelength, axis=0)\n", "\n", "p = ryplot.Plotter(2,1,3,figsize=(18,6))\n", "p.plot(1,wavelength,detector,'Spectral responsivity','Wavelength $\\mu$m', 'Responsivity A/W',pltaxis=[0.5,7,0,0.8],maxNX=5,xAxisFmt=\"%.2f\");\n", "p.plot(2,temperatures,effResp,'Effective responsivity','Temperature K', 'Responsivity A/W',maxNX=5,xAxisFmt=\"%.0f\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## File loading and saving" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Data are easily read in from files. The format most easy to read/write is ASCII coding in a tabular format (also known as a flat file). ASCII tabular files can use commas (csv format) or whitespace (tabs, spaces) to delimit the columns from each other. Python provides specialist CSV readers or just ASCII format readers. The data processing package Pandas also has very powerful data reading and manipulation facilities, especially for data in complex structural formats. In the pyradi context we are more interested in opening files with numpy and this analysis will focus on reading and writing files for Numpy applications.\n", "\n", "Numpy (in versions later than 1.6) has powerful functions to read and write data files to and from Numpy arrays. The file formats include ASCII, binary format and compressed binary formats. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "ASCII flat files are convenient data stores because these files can be read/written by a text editor and with a little effort with Excel (import data from txt, save as txt). In this example an array is created, written to file and read back from the file. When writing the text file, the string format is set to truncate the number of decimal values - on purpose, because we want to compare the array in memory with the array read in from file. The `numpy.loadtxt` and `numpy.savetxt` functions does the work. These functions take as a parameter the filename or file handle (if the file is opened elsewhere). If the filename has the extension `.gz`, the file is handled as a gzip compressed file.\n", "\n", "When reading and writing files, the `with` context manager is used. The motivation for using `with` is that if something goes wrong in the opening, reading or writing, the file is closed in an orderly manner. Also, it is more concise and requires less typing, because the `with` context manager for the file closes the file automatically when leaving the block. Note that the `with` context manager provides a file handle: the `gz` extension is lost and the file is not compressed.\n", "\n", "In this example the file is written with a two-line header, starting with the comment symbol. When the file is read again later, the lines with the comment symbol are ignored. The last few lines read only selected columns - useful if you do not need all the data in the file." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "arr = np.random.randn(3,4)\n", "print('original data:\\n{}'.format(arr))\n", "\n", "#write/read uncompressed file\n", "filename = 'arrfile.txt'\n", "with open(filename, 'wb' ) as filehandle:\n", " np.savetxt(filehandle, arr, fmt='%12.5e', \n", " header='# this is a header\\n#Line two of header', comments='#')\n", "with open(filename, 'rb' ) as filehandle:\n", " arr2 = np.loadtxt(filehandle, comments='#')\n", "print('read from text file {} data:\\n{}'.format(filename, arr2))\n", "\n", "#write/read gzip compressed file - does not work with `with`\n", "filename = 'arrfile.gz'\n", "np.savetxt(filename, arr, fmt='%12.5e', \n", " header='# this is a header', comments='#')\n", "arrz = np.loadtxt(filename, comments='#')\n", "print('read from text file {} data:\\n{}'.format(filename, arrz))\n", "usecols=[0,3]\n", "arrz = np.loadtxt(filename, usecols=usecols, comments='#')\n", "print('read columns {} from text file {} data:\\n{}'.format(usecols, \n", " filename, arrz))\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Data can also be written in binary format or compressed binary format. These files can only be read by the appropriate binary reading functions, and not with a text editor. As a rule, these files are smaller than text files. The binary file format does not support headers and is written and read as a single block of data.\n", "\n", "In this example the compressed file is not much smaller than the uncompressed file, because the data are random numbers - compression does not help much for this type of data." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "arr = np.random.randn(3,4)\n", "print('original data:\\n{}'.format(arr))\n", "\n", "#write/read uncompressed binary file\n", "filename = 'arrfile.npy'\n", "np.save(filename, arr)\n", "arr2 = np.load(filename)\n", "print('read from binary file {} data:\\n{}'.format(filename, arr2))\n", "\n", "#write/read binary file\n", "filename = 'arrfile.npz'\n", "np.savez(filename, arr=arr)\n", "arrz = np.load(filename)\n", "print('read from text file {} data:\\n{}'.format(filename, arrz['arr']))\n", "\n", "#write/read compressed binary file\n", "filename = 'arrfilez.npz'\n", "np.savez_compressed(filename, arr=arr)\n", "arrz = np.load(filename)\n", "print('read from text file {} data:\\n{}'.format(filename, arrz['arr']))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`pyradi.ryfiles` provides specialist functionality to read files. The use of these files is demonstrated below in the colour example.\n", "\n", "1. The function `ryfiles.loadColumnTextFile` was written to load spectral files in pyradi. The first column contains the spectral domain (e.g., wavelength or wavenumber), and the remaining columns contain the spectral variables (e.g.. transmittance). The spectral domain can be scaled; from nanometre to micormetre. The spectral variables can be interpolated to a new spectral domain. This is often required because the spectral domain values used in a calculation is not the same as the spectral domain used in the data file. In short using `pyradi.ryfiles.loadColumnTextFile` can shorten the code significantly when reading in spectral data files. \n", "\n", "2. It is common practice to document the data in a file with a one-line header containing the names of the columns in the file. The function `ryfiles.loadHeaderTextFile` reads the column headers from the first line of a text file. The column names in this header file must be comma separated, because some column headings may contain spaces.\n", "\n", "3. A function is provided to take an arbitrary string and turn it into a legal filename by removing characters not allowed in filenames. A default set is provided but you may provide your own. See \n", "`ryfiles.cleanFilename`.\n", "\n", "4. Two functions are provided to unzip gzip files\n", "`ryfiles.unzipGZipfile` and untar tar files \n", "`ryfiles.untarTarfile`.\n", "Finally, a function is provided to download a file from the internet, given the URL\n", "`ryfiles.downloadFileUrl`." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Spectral convolution" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "(Sec 6.6) describes how to calculate the signal that a given sensor with response $S$ would receive from a source $L$, through some medium with transmittance $\\tau_{01\\lambda}$. Suppose that this sensor has a spectral filter $\\tau_f$ with a narrow (but nonzero) spectral width. This filter is very narrow compared with its central wavelength, say $\\Delta \\lambda = 0.01 \\lambda_c$. Such radiometers are used to determine the spectral radiance of sources or to measure the spectral transmittance of the atmosphere. The apparent irradiance measured by such a system can be written [from (Eq 6.13)]\n", "$$\n", "E_{\\lambda_c}=\n", "k\\int_{0}^{\\infty}\n", " \\epsilon_{0\\lambda} L_{0\\lambda}\n", "\\,\\tau_{a\\lambda} \\,\\tau_{f\\lambda} {S}_\\lambda\n", " \\lambda,\n", "$$\n", "where $k$ accounts for the geometrical factors such as source area, orientation, and distance. This equation can be written as\n", "$$\n", "E_{\\lambda_c}=\n", "k\\int_{\\lambda_c -\n", "\\frac{\\Delta\\lambda}{2}}^{\\lambda_c+\\frac{\\Delta\\lambda}{2}}\n", " \\epsilon_{0\\lambda} L_{0\\lambda}\n", "\\,\\tau_{a\\lambda} \\,\\tau_{f\\lambda} { S}_\\lambda\n", " \\lambda.\n", "$$\n", "By change of variable $\\lambda = \\lambda_c-x$,\n", "$$\n", "E_{\\lambda_c}=\n", "k\\int_{-\\frac{\\Delta\\lambda}{2}}^{+\\frac{\\Delta\\lambda}{2}}\n", " \\epsilon_{0x} L_{0x}\n", "\\,\\tau_{ax} \\,\\tau_{f(\\lambda_c-x)} { S}_x\n", " x.\n", "$$\n", "These equations show very clearly that the irradiance measured with the\n", "filter centred around wavelength $\\lambda_c$ includes source energy from\n", "$\\lambda_c - \\frac{\\Delta\\lambda}{2}$ to\n", "$\\lambda_c+\\frac{\\Delta\\lambda}{2}$.\n", "Apart from the spectral selection, the filter has an additional effect by smoothing the spectrum being observed because the filter has a nonzero spectral width.\n", "\n", "The equation above is called a convolution integral because it\n", "describes the convolution between\n", "the product\n", "$(\\epsilon_{0\\lambda_c}L_{0\\lambda_c} \\,\\tau_{a\\lambda_c} \\, { S}_{\\lambda_c})$ and $\\tau_{f}$.\n", "In linear systems terminology, the observed spectral source radiance is being convolved with the\n", "filter spectral transmittance.\n", "To investigate the effects of this convolution consider the two\n", "cases: (1) the observed source has little variation over the filter\n", "passband, and (2) the observed source varies significantly over the filter\n", "passband.\n", "\n", "If the product\n", "$(\\epsilon_{0\\lambda_c} L_{0\\lambda_c} \\,\\tau_{a\\lambda_c} \\, { S}_{\\lambda_c})$\n", "is more or less constant over the filter passband $\\Delta\\lambda$,\n", "the equation can be written to show that the convolution has little effect other than some insignificant\n", "amount of smoothing:\n", "$$\n", "E_{\\lambda_c}\n", "=\n", "k\\,(\\epsilon_{0\\lambda_c} L_{0\\lambda_c} \\,\\tau_{a\\lambda_c} \\, { S}_{\\lambda_c})\n", "\\int_{-\\frac{\\Delta\\lambda}{2}}^{+\\frac{\\Delta\\lambda}{2}}\n", " \\tau_{f(\\lambda_c-x)}\n", " x \\approx \\,\n", "k\\,\\epsilon_{0\\lambda_c} L_{0\\lambda_c} \\,\\tau_{a\\lambda_c} \\, { S}_{\\lambda_c}\\, \\tau_{f}\\,\\Delta x.\n", "$$\n", "If the product\n", "$(\\epsilon_\\lambda L_{\\lambda}\\;\\tau_{a\\lambda}\\;{ S}_\\lambda)$\n", "varies significantly over the filter passband $\\Delta\\lambda$,\n", "the convolution equation cannot be simplified. In this case, the convolution attenuates and smears out the finer detail in the spectral information. If the actual spectral line is very narrow the measured line will approximate the filter resolution and will be totally erroneous unless the filter spectral smear effect is compensated by deconvolution." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This theory may be intellectually satisfying, but it is much nicer to see the convolution principle in graphical form with real-world information. First investigate the principle of convolution by creating a synthetic signal by placing a number of impulses at varying distances from each other. Then convolve this signal by a wider top-hat (square) function. Note how the top-hat function 'smears out' the signal. The `pyradi.ryutils.convolve` function is used to do the convolution." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "samplingresolution=0.5\n", "wavenum=np.linspace(0, 100, int(100/samplingresolution))\n", "inspectral=np.zeros(wavenum.shape)\n", "inspectral[int(10/samplingresolution)] = 1\n", "inspectral[int(11/samplingresolution)] = 1\n", "inspectral[int(30/samplingresolution)] = 1\n", "inspectral[int(45/samplingresolution)] = 1\n", "inspectral[int(55/samplingresolution)] = 1\n", "inspectral[int(70/samplingresolution)] = 1\n", "inspectral[int(75/samplingresolution)] = 1\n", "inwinwidth=1\n", "outwinwidth=5\n", "outspectral, windowfn = ryutils.convolve(inspectral, samplingresolution, inwinwidth, outwinwidth)\n", "convplot = ryplot.Plotter(1, 1, 1, figsize=(8,4))\n", "convplot.plot(1, wavenum, inspectral, \"Convolution Test\", r'Wavenumber cm$^{-1}$',\\\n", " r'Signal', ['r'],label=['Input'],legendAlpha=0.5,maxNX=5,xAxisFmt=\"%.0f\",pltaxis=[0,100,0,1]);\n", "convplot.plot(1, wavenum, outspectral, \"Convolution Test\", r'Wavenumber cm$^{-1}$',\\\n", " r'Signal', ['g'],label=['Output'],legendAlpha=0.5,maxNX=5,xAxisFmt=\"%.0f\",pltaxis=[0,100,0,1]);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Savitzky-Golay filter" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The Savitzky-Golay filter smooths signals by by fitting successive sub-sets of adjacent data points with a low-degree polynomial by the method of linear least squares.\n", "\n", "A Python implementation of this filter is available in the scipy library. A one-dimensional version of the filter is also included in `pyradi.ryutils.SavitzkyGolay`. \n", "\n", "The example below shows a considerable ringing on the spiky input signal. Clearly this filter is not appropriate for this particular input signal. Another example (atmospheric transmittance) is shown below which better demonstrates the Savitzky-Golay filter performance." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "outspectral = ryutils.savitzkyGolay1D(inspectral, window_size=21, order=3, deriv=0, rate=1)\n", "\n", "convplot = ryplot.Plotter(1, 1, 1, figsize=(8,4))\n", "convplot.plot(1, wavenum, inspectral, \"Convolution Test\", r'Wavenumber cm$^{-1}$',\\\n", " r'Signal', ['r'],label=['Input'],legendAlpha=0.5,maxNX=5,xAxisFmt=\"%.0f\",pltaxis=[0,100,0,1]);\n", "convplot.plot(1, wavenum, outspectral, \"Convolution Test\", r'Wavenumber cm$^{-1}$',\\\n", " r'Signal', ['g'],label=['Output'],legendAlpha=0.5,maxNX=5,xAxisFmt=\"%.0f\",pltaxis=[0,100,0,1]);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The next example uses spectral Bunsen flame measurement data. The data is read in from the pyradi Google Code site, so you must be online to run this cell. The data is read using the urllib2 library, given the URL, the urllib2 returns a file handle that is used by Numpy to read the data. The spectral width for the Bunsen flame measurement was 4 cm$^{-1}$ and the signal was sampled at 2 cm$^{-1}$. The Bunsen data file format is: first column contains the wavenumber and the second column contains the raw signal (proportional to radiance). Modtran transmittance data were calculated for a 5 m path length and a spectral width of 1 cm$^{-1}$ and sampling of 1 cm$^{-1}$. The transmittance file format is: first column contains the wavenumber and the second column contains the transmittance. The atmospheric transmittance is convolved to resolutions of 4 cm$^{-1}$ and 40 cm$^{-1}$. The spectral baselines for the Bunsen data and Modtran data are not the same, so the Bunsen data is re-sampled at the Modtran spectral values. All the data is then plotted for visual inspection. The convolution smoothing effect is clearly visible in the graphs." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from scipy.interpolate import interp1d\n", "import pyradi.ryfiles as ryfiles\n", "\n", "bunsenfile = ryfiles.downloadFileUrl(url = 'https://raw.githubusercontent.com/NelisW/pyradi/master/pyradi/data/bunsenspec.txt')\n", "specRad = np.loadtxt(bunsenfile, comments='%', delimiter=' ') \n", "\n", "atmofile = ryfiles.downloadFileUrl(url = 'https://raw.githubusercontent.com/NelisW/pyradi/master/pyradi/data/atmotrans5m.txt')\n", "tauAtmo = np.loadtxt(atmofile, comments='%', delimiter=' ' ) \n", "wavenum = tauAtmo[:, 0]\n", "tauA = tauAtmo[:, 1]\n", "\n", "# convolve transmittance from 1cm-1 to 4 cm-1\n", "tauAtmo4, windowfn = ryutils.convolve(tauA, 1, 1, 4)\n", "# convolve transmittance from 1cm-1 to 40 cm-1\n", "tauAtmo40, windowfn = ryutils.convolve(tauA, 1, 1, 40)\n", "\n", "#interpolate bunsen spectrum to atmo sampling\n", "#first construct the interpolating function, using bunsen\n", "bunInterp1 = interp1d(specRad[:,0], specRad[:,1])\n", "#then call the function on atmo intervals\n", "bunsen = bunInterp1(wavenum)\n", "\n", "atmoplot = tauA.copy()\n", "atmoplot = np.vstack((atmoplot, tauAtmo4, tauAtmo40))\n", "convplot02 = ryplot.Plotter(1, 1, 2,figsize=(20,5))\n", "convplot02.plot(1, wavenum, atmoplot.T, \"Atmospheric Transmittance\", r'Wavenumber cm$^{-1}$',\n", " r'Transmittance', ['r', 'g','b'],label=['1 cm-1', '4 cm-1', '40 cm-1' ],legendAlpha=0.5,\n", " maxNX=5,xAxisFmt=\"%.0f\",pltaxis=[1750,4000,0,1]);\n", "convplot02.plot(2, wavenum, atmoplot.T, \"Atmospheric Transmittance\", r'Wavenumber cm$^{-1}$',\n", " r'Transmittance', ['r', 'g','b'],label=['1 cm-1', '4 cm-1', '40 cm-1' ],legendAlpha=0.5,\n", " pltaxis=[3700, 3900, 0, 1],maxNX=5,xAxisFmt=\"%.0f\");\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The next step is to attempt to correct for the atmospheric transmittance present during the measurement. In this particular case the simple approach of dividing the radiance signal by the transmittance is attempted. The case on the left side is for the Bunsen data at 4 cm$^{-1}$ resolution and the atmospheric transmittance (mismatched at) at 1 cm$^{-1}$. The case on the right side is for the Bunsen data at 4 cm$^{-1}$ resolution and the atmospheric transmittance (well matched at) at 4 cm$^{-1}$. The results from the mismatched calculation is clearly much more noisy than the results for the well-matched calculation. The results also show that it is impossible to reconstruct the signal in spectral regions where there is zero signal - a more sophisticated model-based method must be followed, such as explained in (Sec 8.4)." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "bunsenPlt = ryplot.Plotter(1,3, 2, figsize=(15,7))\n", "bunsenPlt.plot(1, wavenum, bunsen, \"Bunsen Flame Measurement 4 cm-1\", r'',\n", " r'Signal', ['r'], pltaxis =[2000, 4000, 0,1.5],maxNX=5,xAxisFmt=\"%.0f\");\n", "bunsenPlt.plot(2, wavenum, bunsen, \"Bunsen Flame Measurement 4 cm-1\", r'',\n", " r'Signal', ['r'], pltaxis =[2000, 4000, 0,1.5],maxNX=5,xAxisFmt=\"%.0f\");\n", "bunsenPlt.plot(3, wavenum, tauA, \"Atmospheric Transmittance 1 cm-1\", r'',\n", " r'Transmittance', ['r'])\n", "bunsenPlt.plot(4, wavenum, tauAtmo4, \"Atmospheric Transmittance 4 cm-1\", r'',\n", " r'Transmittance', ['r'])\n", "bunsenPlt.plot(5, wavenum, bunsen/tauA, \"Atmospheric-corrected Bunsen Flame Measurement 1 cm-1\", r'Wavenumber cm$^{-1}$',\n", " r'Signal', ['r'], pltaxis =[2000, 4000, 0,1.5],maxNX=5,xAxisFmt=\"%.0f\");\n", "bunsenPlt.plot(6, wavenum, bunsen/tauAtmo4, \"Atmospheric-corrected Bunsen Flame Measurement 4 cm-1\", r'Wavenumber cm$^{-1}$',\n", " r'Signal', ['r'], pltaxis =[2000, 4000, 0,1.5],maxNX=5,xAxisFmt=\"%.0f\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The atmospheric transmittance model is next Savitzky-Golay filtered. This filter is poular in the spectroscopy community, so it should work well for the atmospheric transmittance data used here. It indeed does provide nicely filtered spectra, as seen below. More work is required to accurately translate the SG filter parameters to spectral widths." ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from scipy.interpolate import interp1d\n", "import pyradi.ryfiles as ryfiles\n", "\n", "bunsenfile = ryfiles.downloadFileUrl(url = 'https://raw.githubusercontent.com/NelisW/pyradi/master/pyradi/data/bunsenspec.txt')\n", "specRad = np.loadtxt(bunsenfile, comments='%', delimiter=' ') \n", "\n", "atmofile = ryfiles.downloadFileUrl(url = 'https://raw.githubusercontent.com/NelisW/pyradi/master/pyradi/data/atmotrans5m.txt')\n", "tauAtmo = np.loadtxt(atmofile, comments='%', delimiter=' ' ) \n", "wavenum = tauAtmo[:, 0]\n", "tauA = tauAtmo[:, 1]\n", "\n", "# convolve transmittance from 1cm-1 to 4 cm-1\n", "tauAtmo4 = ryutils.savitzkyGolay1D(tauA, window_size=9, order=3, deriv=0, rate=1)\n", "\n", "# convolve transmittance from 1cm-1 to 40 cm-1\n", "tauAtmo40 = ryutils.savitzkyGolay1D(tauA, window_size=81, order=3, deriv=0, rate=1)\n", "\n", "#interpolate bunsen spectrum to atmo sampling\n", "#first construct the interpolating function, using bunsen\n", "bunInterp1 = interp1d(specRad[:,0], specRad[:,1])\n", "#then call the function on atmo intervals\n", "bunsen = bunInterp1(wavenum)\n", "\n", "atmoplot = tauA.copy()\n", "atmoplot = np.vstack((atmoplot, tauAtmo4, tauAtmo40))\n", "convplot02 = ryplot.Plotter(1, 1, 2,figsize=(20,5))\n", "convplot02.plot(1, wavenum, atmoplot.T, \"Atmospheric Transmittance: Savitzky Golay Filter\", r'Wavenumber cm$^{-1}$',\n", " r'Transmittance', ['r', 'g','b'],label=['1 cm-1', '4 cm-1', '40 cm-1' ],legendAlpha=0.5, \n", " pltaxis=[2900, 4000, 0, 1.1],maxNX=5,xAxisFmt=\"%.0f\");\n", "convplot02.plot(2, wavenum, atmoplot.T, \"Atmospheric Transmittance: Savitzky Golay Filter\", r'Wavenumber cm$^{-1}$',\n", " r'Transmittance', ['r', 'g','b'],label=['1 cm-1', '4 cm-1', '40 cm-1' ],legendAlpha=0.5,\n", " pltaxis=[3700, 3900, 0, 1.1],maxNX=5,xAxisFmt=\"%.0f\");\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Colour calculations" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is a very high-level introduction to colour theory. For more detail see the numerous resources on the internet. \n", "\n", "(Sec 2.10.5) Colour is an elusive property - different people perceive colour differently, and the apparent colour of an object depends on the illuminance spectrum. The colour tristimulus have been standardised by the CIE. It is interesting to note that the red colour stimilus has a significant component towards the blue part of the spectrum. The description in this section is very brief, for more details see (Sec 2.10). The example given here investigates the human perception of colour, relative to the CIE 1931 standard.\n", "\n", "This section explores the subtleties of colour as an application of 1) normalising, 2) radiometric concepts and 3) colour coordinates. Four sources are considered: the first light source is a 'daylight' fluorescent light source, the second source is the sun modelled as a thermal radiator at 5900~K, the third source is an incandescent light globe at a temperature of 2850~K, and the fourth source is a low-pressure sodium lamp. \n", "\n", "The samples illuminated by these sources are a red tomato, lettuce, a yellow prune, a dark-green leaf, a blue Nitrile (latex-like) surgical glove, and standard white printing paper. The samples' diffuse reflection spectra were measured with a spectroradiometer, illuminating the sample with a bright light at short distance. The fruit samples all demonstrated considerable light propagation deeper into the fruit. The blue glove was located on a Spectralon white reference (note the considerable 'white' reflectance beyond 0.55 $\\mu$m).\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use a local copy of the data file, if the tgz file is available in the same directory where the notebook is located. Otherwise download the 28 KB file from the internet. Once availabe, unzip and untar the data files to support rest of the calculation." ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "filesAvailable is ['ciexyz31_1.txt', 'fluorescent.txt', 'LowPressureSodiumLamp.txt', 'sampleReflectance.txt', 'samplesVis.txt']\n" ] } ], "source": [ "import pyradi.ryfiles as ryfiles\n", "import os\n", " \n", "tgzFilename = 'colourcoordinates.tgz'\n", "destinationDir = '.'\n", "tarFilename = 'colourcoordinates.tar'\n", "url = 'https://raw.githubusercontent.com/NelisW/pyradi/master/pyradi/data/colourcoordinates/'\n", "dlNames = ryfiles.downloadUntar(tgzFilename, url, destinationDir, tarFilename)\n", "\n", "print('filesAvailable is {}'.format(dlNames))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data is read with `ryfiles.loadColumnTextFile`. \n", "This function loads column data from a text file, scaling and interpolating the read-in data, according to user specification.\n", "The first 0'th column has special significance: it is considered the abscissa (x-values) of the data set, while the remaining columns are any number of ordinate (y-value) vectors. The user passes a list of columns to be read (default is [1]) - only these columns are read, processed and returned when the function exits.\n", "The user also passes an abscissa vector to which the input data is interpolated and then subsequently amplitude scaled or normalised. " ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "if dlNames:\n", " \n", " wavelength = np.linspace(0.38, 0.72, 350).reshape(-1, 1)\n", " \n", " bar = ryfiles.loadColumnTextFile('ciexyz31_1.txt', abscissaOut=wavelength,\n", " loadCol=[1, 2, 3], comment='%', delimiter=',', abscissaScale=1e-3)\n", " \n", " cietriplt = ryplot.Plotter(1, 1, 1, figsize=(8,4))\n", " cietriplt.plot(1, wavelength, bar, \"CIE tristimulus values\",\n", " r'Wavelength $\\mu$m', r'Response', plotCol = ['r','g','b'],\n", " label=['$\\\\bar{x}$', '$\\\\bar{y}$', '$\\\\bar{z}$'],pltaxis=[0.38,0.72,0,2],legendAlpha=0.5,maxNX=5,xAxisFmt=\"%.2f\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next the source spectra are loaded and/or calculated. \n", "The following code builds a 2-D array with the source radiance values, \n", "where each column represents a different source. Wavelength extends along rows.\n", "Spectral interval for all source spectra is the same, which is the `wavelength`\n", "array calculated in the previous cell.\n", "Blackbody radiance spectra are calculated at the required wavelength intervals \n", "for the required temperatures.\n", "All data read from files are interpolated to the required wavelength intervals\n", "\n", "The spectra from the four sources are stacked horizontally by using \n", "`numpy.hstack`. The resulting array varies with wavelength along the rows (axis=0),\n", "with the four source spectra are given in the four columns." ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "if dlNames:\n", " \n", " sources = ryfiles.loadColumnTextFile('fluorescent.txt',\n", " abscissaOut=wavelength,comment='%', normalize=1).reshape(-1,1)\n", " sources = np.hstack((sources, ryplanck.planck(wavelength,5900,'el').reshape(-1,1)))\n", " sources = np.hstack((sources, ryplanck.planck(wavelength,2850,'el').reshape(-1,1)))\n", " sources = np.hstack((sources, ryfiles.loadColumnTextFile('LowPressureSodiumLamp.txt', \n", " abscissaOut=wavelength,comment='%', \n", " normalize=1).reshape(-1,1) ))\n", " #label sources in order of appearance\n", " sourcesTxt=['Fluorescent', 'Planck 5900 K', 'Planck 2850 K', 'Sodium']\n", " \n", " #normalise the source data (along axis-0, which is along columns)\n", " #this is not really necessary for CIE xy calc, which normalises itself.\n", " #It is however useful for plotting the curves.\n", " sources /= np.max(sources,axis=0)\n", " \n", " srceplt = ryplot.Plotter(2, 1, 1, figsize=(8,4))\n", " srceplt.plot(1, wavelength, sources, \"Normalized source radiance\",\n", " r'Wavelength $\\mu$m', r'Normalized Radiance',label=sourcesTxt,legendAlpha=0.5,pltaxis=[0.38,0.72,0,1],maxNX=5,xAxisFmt=\"%.2f\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Next load the sample reflectance data. The data file for this data \n", "has the wavelength ($\\mu$m) values along the first column, with many columns\n", "following to represent the different samples. Only a few of the samples (`samplesSelect = [1,2,3,8,10,11]`) are loaded here.\n", "\n", "After reading in the numeric values, the headers in the first row is read in.\n", "These headers are used in labels in the graphs." ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "if dlNames:\n", " \n", " samplesSelect = [1,2,3,8,10,11]\n", " samples = ryfiles.loadColumnTextFile('samplesVis.txt', abscissaOut=wavelength, \n", " loadCol=samplesSelect, comment='%')\n", " samplesTxt=ryfiles.loadHeaderTextFile('samplesVis.txt',\n", " loadCol=samplesSelect, comment='%')\n", " smpleplt = ryplot.Plotter(1, 1, 1, figsize=(8,4))\n", " smpleplt.plot(1, wavelength, samples, \"Sample reflectance\", r'Wavelength $\\mu$m',\n", " r'Reflectance', ['r', 'g', 'y','g', 'b', 'm'],label=samplesTxt,legendAlpha=0.5,pltaxis=[0.38,0.72,0,1],maxNX=5,xAxisFmt=\"%.2f\");" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now calculate the CIE x,y coordinates for each combination of source and sample. The x,y coordinates indicate the colour of the sample under the specific source illumination. This cell uses the `rychroma.chromaticityforSpectralL` function to do the coordinate calculation from the spectra. For equations and more details see (Sec 2.10).\n", "\n", "We have a number of samples and a number of sources, essentially these two are orthogonal to each other. The following calculation is therefore done in two loops and the results written to two-dimensional arrays for storage and subsequent plotting. The two arrays are pre-allocated and filled with zeros before the calculation." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "if dlNames:\n", " import pyradi.rychroma as rychroma\n", " \n", " xs = np.zeros((samples.shape[1],sources.shape[1]))\n", " ys = np.zeros((samples.shape[1],sources.shape[1]))\n", " for iSmpl in range(samples.shape[1]):\n", " for iSrc in range(sources.shape[1]):\n", " [ xs[iSmpl,iSrc], ys[iSmpl,iSrc], Y]=\\\n", " rychroma.chromaticityforSpectralL(wavelength,\n", " (samples[:,iSmpl]*sources[:,iSrc]).reshape(-1, 1),\n", " bar[:,0], bar[:,1], bar[:,2])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This cell calculates the horseshoe-shape locus of monochromatic light. The concept is really quite simple: create a monochromatic spectrum (only one wavelength) and then use `rychroma.chromaticityforSpectralL` to calculate the x,y coordinates for that wavelength." ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "if dlNames:\n", " xm = np.zeros(wavelength.shape)\n", " ym = np.zeros(wavelength.shape)\n", " #create a series of data points with unity at specific wavelength\n", " for iWavel in range(wavelength.shape[0]):\n", " monospectrum = np.zeros(wavelength.shape)\n", " monospectrum[iWavel] = 1\n", " #calc xy for single mono wavelength point\n", " [xm[iWavel],ym[iWavel],Y] = rychroma.chromaticityforSpectralL(wavelength,\n", " monospectrum, bar[:,0], bar[:,1], bar[:,2])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally plot the colour coordinates for each sample-source combination on the diagram, together with the monochromatic horseshoe. The graph is plotted trice; once to get the big picture and then two zoomed in on the detail." ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA/YAAAG8CAYAAAB0RD53AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOzdd1zV1f/A8ddhowjujeLCyVQUcCtX0xxZbnOUIytNrSyzLM2W1a+caZortdI0R7YEw1w4AfdWUMG9EGVzfn9c5AvI5nIX5/l43Ifcz/18zuf9+XA5nvM5S0gpURRFURRFURRFURTFNFkYOgBFURRFURRFURRFUQpPVewVRVEURVEURVEUxYSpir2iKIqiKIqiKIqimDBVsVcURVEURVEURVEUE6Yq9oqiKIqiKIqiKIpiwlTFXlEURVEURVEURVFMmKrYK7kSQrgIIaQQwsrQseSHEGKqEOKHfOy3SAgxrZhi6CCEuJrh/QkhRIfiOJeiKKZB5aWFikHlpYqiZKLy0kLFoPLSEkJV7E2MEGKwEOKQECJWCHFNCPGXEKJN2mfThRCrM+wrhRCP0vZ98nrHcNHrVtaMCkBK+ZmUclRex0opx0opZ+aUji5JKZtKKXcUV/qKohScykv/R+WliqIUlspL/0flpYqhmcTTLkVLCPEmMAUYC/wDJALPAL2B3Tkc5iGlPK+fCEEIYSWlTNbX+Uoyda8VpXBUXqpkpO61ohSOykuVjNS9NjzVYm8ihBBOwMfA61LK36SUj6SUSVLK36WUk3WQvr0Q4v+EEJFCiAdCiN1CCPsMuwwRQlwWQtwWQryf4bjpQoj1QojVQogYYIQQoroQYosQ4q4Q4rwQYnSW/X9N2/+hEOKYEMJVCPGeEOKmEOKKEKJLhv1fEkKcStv3ohDilbTtpYG/gOoZnvpWz+bpcBshxF4hxP20tEekbV8hhPgkl3QeCyEqZEinuRDilhDCOod7t0IIcU8IcRLwyfJ5hBAiIO3nlkKIkLR4rgkh5gshbDLs20UIcSbtd/CdEOI/IcSotM9GCCH2CCG+FULcBaYLIeoJIf4VQtxJ+92sEUKUzXLuyUKIo2lPyZcKIaqkPVF/KIQIEkKUy9+3RFFMn8pLVV6q8lJFKTqVl6q8VOWlxkdV7E2HH2AHbCym9L8GmgP+QHngHSA1w+dtgIZAZ+BDIUTjDJ/1BtYDZYE1wM/AVaA60Bf4TAjROcP+PYFVQDkgDO1TXgugBtr/JL7PsO9NoAfgCLwEfCuE8JZSPgK6AdFSSoe0V3TGCxJC1EKbOc4DKgGeQHjGfXJJZwfQP8OuLwK/SCmTsrl3HwH10l5dgeHZ7PNECjAJqIj2d9oZeC0t3opo7+N7QAXgDNrfR0atgItAZeBTQACfo73XjQFnYHqWY14ANIAr2nv/FzA1LQYL4I1c4lUUc6PyUpWXgspLFaWoVF6q8lJQealRURV701EBuF2ILi6haU/hnry6Zt1BCGEBvAxMkFJGSSlTpJR7pZQJGXabIaWMk1IeAY4AHhk+C5FSbpJSpqL9o2wDvCuljJdShgM/AEMz7L9LSvlP2rX8ijZz+yItc/oFcHnydE9K+YeU8oLU+g/YBrTN57UPAYKklD+nPUW+kxZPfqxEm2kihLAEBqHN9LPTH/hUSnlXSnkFmJtTolLKw1LKfVLKZCllBNr/LNqnfdwdOJH25Ds5LZ3rWZKIllLOSzs+Tkp5XkoZKKVMkFLeAr7JkN4T86SUN6SUUcAuYL+UMizt97sR8MrXHVEU86DyUpWXgspLFaWoVF6q8lJQealRUWPsTccdoKIo+PgVb5n3WKaKaJ+6Xshln4x/yI8Bhwzvr2T4uTpwV0r5MMO2SKBFhvc3Mvwch/Y/hpQM70lL/74QohvaJ4+uaB9ElQKO5Xo1/+NM7teUm83AIiFE3bRzP5BSHshh3+pkvgeROSUqhHBFm8m1QHstVsDh7NKRUkrx9OQpGc+DEKIy2oy2LVAG7T26l+WYrPc763sHFKXkUHmpyktB5aWKUlQqL1V5Kai81KioFnvTEQLEA88VQ9q309KuV8jjZYafo4HyQogyGbbVAqIKmqgQwhbYgLY7VhUpZVngT7TdfLKeNztXyN81PZWOlDIeWIf26epQcn4qCnANbWb9RK1c9l0InAYaSCkd0XY9enI914CaT3YUQoiM73OI9fO0be5p6b2YIT1FUZ6m8lKVl2YXq8pLFaVgVF6q8tLsYlV5qQGpir2JkFI+AD4EFgghnhNClBJCWAshugkhvixi2qnAMuCbtAk6LIUQfmkZWEHTugLsBT4XQtgJIdyBkWjHOBWUDWAL3AKS056Sdsnw+Q2ggtBO4JKdNUCAEKK/EMJKCFFBCOGZzX45pfMjMALoBazOelAG64D3hBDlhBA1gfG57FsGiAFihRCNgFczfPYH4Jb2+7UCXgeq5pLWk/Ri0T5FrgEUecIaRTFnKi9VeWku6am8VFHySeWlKi/NJT2VlxqIqtibECnlN8CbwAdoM5UrwDhgUy6HHRGZ1wudncN+b6PtSnQQuAvMovDfj0GAC9qnpBuBj6SUgQVNJK3b1BtoM6h7wGBgS4bPT6OdEOVi2jit6lmOv4x2fNBbaK8pnMxjsHJNR0q5B+1ELaFp445yMgNtN6dLaMda5fYU9e2063gILAHWZojjNtAP+BJtF7cmwCEg4elkMp3bG3iANgP+LZd9FUVB5aWovDSnc6u8VFEKQOWlKi/N4dwqLzUQIWVevUYUpeQSQvwL/CSl/MEA57ZAO4vrECllsL7PryiKoisqL1UURSk6lZcquVEt9oqSAyGED9qnjmvz2leH5+wqhCib1t3syTinffo6v6Ioiq6pvFRRFKXoVF6q5EVvFXshxDNCiDNCiPNCiCnZfF5OCLFRCHFUCHFACNFMX7EpSlZCiJVAEDAxy0yqxc0P7Yypt9Gu7fmclDIu90MUc5OP/LKDEOKBECI87fVhfo9VFH1SeamiD/nN94QQPkKIFCFE3wzbygoh1gshTgshTgkh/NK2lxdCBAohzqX9W04f16Io2VF5qZIfeumKL7TrLZ4FNGi7cBwEBkkpT2bY5ysgVko5I23yhgVSys7FHpyiKIoRyWd+2QF4W0rZo6DHKoqimJP85ntp+wWinW19mZRyfdr2lWjXMf9BCGEDlJJS3k+bAO6ulPKLtIcF5aSU7+rvyhRFUQpGXy32LYHzUsqLUspE4Begd5Z9mgDbIX3SCBchRBU9xacoimIs8pNfFsexiqIopii/+d54tEuV3XyyQQjhCLQDlgJIKROllPfTPu4NrEz7eSXFs6yboiiKzljp6Tw10M6U+cRVoFWWfY4AzwO7hRAtgdpo10q8kXEnIcQYYAyAnZ1d81q1clua0TSlpqZiYWGe0x+Y67Wp6zItZ8+evS2lrGToOHKQn/wSwE8IcQTtLL9vSylPFOBYk89LTfG7aYoxQ/7ivnv3Lrdv36ZevXpYWlrqKbKcmeK9NsWYjSQvzTPfS1t2qw/QCfDJ8FFdtLO5LxdCeACHgQlSykdo1ym/BiClvCaEqJzdyU09L9Wl8+fP4+DgQNWq2hXRTPE7XVzUvchM3Y/MdJWX6qtiL7LZlnUMwBfAHCFEONrlLcKA5KcOknIxsBigYcOG8syZM7qN1Ajs2LGDDh06GDqMYmGu16auy7QIISINHUMu8pNfhgK1pZSxQojuaJcWapDPY7UbTTwvNcXvpinGDPmLe+fOnbRv357Zs2fTo0ePXPfVB1O816YYs5HkpfnJ92YD70opU4TItLsV2snIxksp9wsh5gBTgGn5Pbmp56W6NGDAAHbt2sXp06cRQpjkd7q4qHuRmbofmekqL9XXo5KrgHOG9zXRtjKlk1LGSClfklJ6AsOASmjXX1QURSlJ8ptfxqb9/CdgLYSomJ9jFaU4tGjRAisrK0JCQgwdilLy5CffawH8IoSIAPoC3wkhnks79qqUcn/afuvRVvQBbgghqgGk/XsTJVcajYZr165x8qSa1kVRDEFfFfuDQAMhRJ20iUkGAlsy7pA2K6lN2ttRwE4pZYye4lMURTEW+ckvq4q0Zqe0oUsWwJ38HKsoxaFUqVJ4eHioir1iCHnme1LKOlJKFymlC9rK+2tSyk1SyuvAFSFEw7RdOwNPaqVbgOFpPw8HNhfzdZg8jUYDQFBQkIEjUZSSSS8VeyllMjAO+Ac4BayTUp4QQowVQoxN260xcEIIcRroBkzQR2yKoijGJJ/5ZV/geNoY+7nAQKmV7bH6vwqlJPL39+fAgQMkJz81ik5Rik0+88zcjAfWCCGOAp7AZ2nbvwA0QohzaGfc/0LnwZuZ2rVrU79+fQIDAw0diqKUSPoaY/+ku+ifWbYtyvBzCNoxoopS7FJSUrh79y5JSUk6Sc/R0ZHoaPPr8Wzq12VtbU358uWNYjKvgshHfjkfmJ/fYxVFH/z8/Jg3bx7Hjh3Dy8vL0OEoJUheeWaW7SOyvA9H21U/63530LbgKwWg0Wj48ccfSUxMNHQoJkPXZVJTYOrly8Iq7nKp3ir2imJM7t69i52dHRUrViTLRDqFkpiYSPXq1XUQmXEx5euSUhIbG8vdu3epVMnQkzYrivnz8/MDICQkRFXsFaWE0mg0LFy4kH379hk6FJOh6zKpKTDl8mVh6aNcqtYZUEqkpKQkHBwcSkwGWhIJIXBwcChRT8AVxZBq165N1apV1Th7RSnBOnbsiIWFhRpnXwCqTFoy6KNcqir2SomlMlDzp37HiqI/Qgj8/PxUxV5RSrCyZcvi4+OjxtkXkCqvlAzF/XtWFXtFURRFUXTC39+fCxcucPOmWhlMUUoqjUbDgQMHiI2NNXQoilKiqIq9ohjAnTt38PT0xNPTk6pVq1KjRo3097qccOb+/ft89913OktPURQlNxnH2SuKUjJpNBpSU1MJCwszdChKPqgyqflQFXtFMYAKFSoQHh5OeHg4Y8eOZdKkSenvbWxsdHYelYkqiqJPzZs3x9raWlXsFaUE8/X1pXTp0hw+fNjQoSj5oMqk5kNV7BXFSGzfvh0vLy/c3Nx4+eWXSUhIAMDFxYWpU6fi5+dHixYtCA0NpWvXrtSrV49Fi7Sr+cTGxtK5c2e8vb1xc3Nj8+bNAEyZMoULFy7g6enJ5MmTkVIyefJkmjVrhpubG2vXrjXY9SqKYn7s7Ozw8vJSFXtFKcFsbGxo3769qtibsOIuk3722WeqTFoM1HJ3Sok3cSKEhxctjfj4qtjZ/e+9pyfMnl2Q4+MZMWIE27dvx9XVlWHDhrFw4UImTpwIgLOzMyEhIUyaNIkRI0awZ88e4uPjadq0KWPHjsXOzo6NGzfi6OjI7du38fX1pVevXnzxxRccP36c8LQL3LBhA+Hh4Rw5coTbt2/j4+NDu3btqFatWtFugKIoShp/f3++//57kpKSsLa2NnQ4iqIYgEaj4c8//yQyMpLatWsbOhyToYsyaVbGWCaNiIjgt99+U2VSHVMt9opiBFJSUqhTpw6urq4ADB8+nJ07d6Z/3qtXLwDc3Nxo1aoVZcqUoVKlStjZ2XH//n2klEydOhV3d3cCAgKIiorixo0bT51n9+7dDBo0CEtLS6pUqUL79u05ePCgfi5SUZQSwc/Pj7i4OI4cOWLoUBRFMRCNRgOgZsc3QapMarpUi71S4hXkKWZOIiKu4+LiUujjS5cunevntra2AFhYWKT//OR9cnIya9as4datWxw+fBhra2tcXFyIj49/Kh0pZaFjVBRFyY+ME+i1aNHCwNEoimIITZo0oUKFCgQFBTFq1ChDh2MydFEmLSpVJjVdqsVeUYxAfHw8ERERnD9/HoBVq1bRvn37fB//4MEDKleujLW1NcHBwURGRgJQpkwZHj58mL5fu3btWLt2LSkpKdy6dYudO3fSsmVL3V6MoiglmrOzMzVq1FDj7BWlBBNC4O3tzfbt20lNTTV0OEoBqDKp6VIt9opiBOzs7Fi+fDn9+vUjOTkZHx8fxo4dm+/jhwwZQs+ePWnRogWenp40atQI0M502rp1a5o1a0a3bt348ssvCQkJwcPDAyEEX375JVWrVi2uy1IUpYTy8/NTFXtFKeFatGhBYGAg4eHheHt7GzocJZ/0USZ9MheLKpPqlqrYK4qBTZ8+Pf3n7NZ8jYiISP95xIgRjBgxItvPcipE//TTT5nef/XVV3z11VeFilVRFCU//P39Wb9+PdeuXVMTISlKCdW8eXNAO85eVexNg77KpBEREQghVJlUx1RXfEVRFEVRdCrjOHtFUUqmChUq0KxZM4KCggwdiqKUCKpiryiKoiiKTnl5eWFjY6Mq9opSwgUEBLBr1y7i4uIMHYqimD1VsVcURVEURadsbW1p3ry5qtgrSgmn0WhISEhg9+7dhg5FUcyeqtgriqIoiqJz/v7+HDp0iMTEREOHoiiKgbRv3x5ra2u1nr2i6IGq2CuKoiiKonN+fn4kJCRkOwGToiglQ+nSpfH391fj7BVFD1TFXlEURVEUnVMT6CmKAtpx9mFhYdy6dcvQoSiKWVMVe0UxEAcHh3zvu2nTJk6ePJn+fsWKFURHRxdHWIqiKDpRvXp1atWqpSr2ilLCaTQaALZv327gSJScqDKpeVAVe0UxASoTVRTFFPn5+amKvaKUcC1atKBs2bJqnL2ZUGVS46Uq9kBycjKhoaHMnTuXDz74gA8++IA5c+awZ88etTyHolcXLlzgmWeeoXnz5rRt25bTp0+zd+9etmzZwuTJk/H09GTWrFkcOnSIIUOG4OnpSVxcHC4uLty+fRuAQ4cO0aFDBwBiY2N56aWXcHNzw93dnQ0bNgCwbds2/Pz88Pb2pl+/fsTGxhrqkhVFMWP+/v5cuXKFq1evGjoURVEMxNLSkk6dOhEYGIiU0tDhKPlUnGXSZ555RpVJi4GVoQMwpISEBJYtW8Znn32WXuiwsNA+60hNTQW0k3706dOHl156iY4dOyKEMFi8SvGY+PdEwq+HFymN+Ph47Ozs0t97VvVk9jOzC5zOmDFjWLRoEQ0aNGD//v289tpr/Pvvv/Tq1YsePXrQt29fAP766y++/vprWrRokWt6M2fOxMnJiWPHjgFw7949bt++zSeffEJQUBClS5dm1qxZfPPNN3z44YcFjldRFCU3GcfZ9+vXz8DRKIpiKAEBAfz222+cO3cOV1dXQ4djtHRRJs3KGMukERERODk5qTKpjpXYiv25c+d47rnnOHnyJP7+/syaNYu2bdvi7OwMQHR0NIcOHWLr1q2sW7eO1atX07JlS6ZNm8azzz6rKviKzsXGxrJ3795Mhd+EhIQipRkUFMQvv/yS/r5cuXJs3bqVkydP0rp1awASExPTC9+Koii65OHhgZ2dnarYK0oJ92ScfWBgoKrYmwBVJjVNJbJi/++///LCCy9gaWnJ77//nm1FvXr16vTq1YtevXoxd+5cVq1axeeff07Pnj3p1KkTc+bMoVmzZga6AkWXCvMUM6uIiAhcXFyKlEZqaiply5YlPDy8wMdaWVml9zKJj49P3y6lfOq7LaVEo9Hw888/FyleRVGUvNjY2NCiRQs1zl5RSrh69erh4uJCYGAgr7/+uqHDMVq6KJPqgiqTmqYSN8Y+NDSUnj17UrNmTQ4ePEiPHj3ybH23s7Nj9OjRnDlzhvnz5xMWFoanpydTp04t8tMrRXnC0dGROnXq8OuvvwLazO7IkSMAlClThocPH6bvm/W9i4sLhw8fBkgfswTQpUsX5s+fn/7+3r17+Pr6smfPHs6fPw/A48ePOXv2bPFdmKIoJZq/vz+hoaGZCniKopQsQgg0Gg3BwcEkJycbOhwlD6pMappKVMX+6tWr9OzZkwoVKrBt2zbq1KlToOOtra15/fXXOXfuHMOGDePzzz/H29u7UE+zFOXx48fUrFkz/fXNN9+wZs0ali5dioeHB02bNmXz5s0ADBw4kK+++govLy8uXLjAiBEjGDt2bPpEJR999BETJkygbdu2WFpapp/jgw8+4N69ezRr1gwPDw+Cg4OpVKkSK1asYNCgQbi7u+Pr68vp06cNdRsURTFzfn5+JCYmEhoaauhQFEUxoICAAGJiYjh48KChQ1Gy0HeZtFu3bqpMWgxKTFd8KSUjRowgJiaGvXv3Uq1atUKnVaFCBZYtW0a/fv0YNWoUfn5+LFiwgJdfflmHESvm7kk3paz+/vvvp7a1bt0609Ii9erV44UXXkh/37Zt22yfcDo4OLBy5cqntnfq1En9x6ooil5knEDP39/fwNEoimIonTt3RghBYGCgGkdtZPRdJs04hFWVSXWnxLTYr1q1iu3bt/Pll1/i5uamkzS7detGWFgYrVu3ZuTIkYwcOVItj6coiqIoGVSpUoU6deqocfaKUsJVqFABb29vtZ69ohSTElGxv337Nm+++Sb+/v688sorOk27cuXK/PPPP3zwwQcsW7YMPz8/Lly4oNNzKIqiKIop8/PzIyQkRK1hrSglnEajYd++fZnGZCuKohslomL/zTffcPfuXRYtWpS+Tr0uWVpaMnPmTP744w8uX75My5Yt2bNnj87PoyiKoiimyN/fn+joaK5cuWLoUBRFMaCAgACSk5P577//DB2Kopgds6/Y379/nwULFtC3b1+ddcHPSffu3Tl48CAVKlSgc+fOrF27tljPpyiKoiim4Ml42r179xo4EkVRDKl169bY2dmp7viKUgzMvmK/YMECYmJimDp1ql7OV69ePUJCQmjRogUDBw5k1qxZquuhoiiKUqK5u7tTqlQpNc5eUUo4Ozs72rVrpyr2ilIM9FaxF0I8I4Q4I4Q4L4SYks3nTkKI34UQR4QQJ4QQLxX1nImJicyZM4du3brh6elZ1OTyrUKFCgQFBTFgwACmTJnCa6+9RkpKit7OryiKoijGxMrKCh8fH1WxVxQFjUbDqVOniIqKMnQoimJW9FKxF0JYAguAbkATYJAQokmW3V4HTkopPYAOwP8JIWyKct6//vqLW7du8dprrxUlmUKxs7Pjp59+4p133mHRokUMGTKExMREvcehGCcpJW3atOGvv/5K37Zu3TqeeeaZp/bdsWMHPXr0AGDFihWMGzdOZ3Hs2LEDJycnvLy8aNy4MTNmzNBZ2oqiKBn5+/sTFhamVo9RlBIuICAAgKCgIANHooAqk5oTfbXYtwTOSykvSikTgV+A3ln2kUAZIYQAHIC7QHJRTvrjjz9SuXJlunbtWpRkCs3CwoJZs2bx5ZdfsnbtWvr06cPjx48NEotiXIQQLFq0iDfffJP4+HgePXrE+++/z4IFC/QeS9u2bQkLC+PQoUOsXr2aw4cPZ/o8OblIf4aKoiiAdpx9cnIyhw4dMnQoiqIYkLu7O5UqVVLd8Y2EKpOaD31V7GsAGafCvZq2LaP5QGMgGjgGTJBSphb2hHfv3uX3339n8ODBWFtbFzYZnZg8eTLff/89f/31F926dSMmJsag8SjGoVmzZvTs2ZNZs2YxY8YMXnzxRT799FN8fHzw8vJi8+bNuR4fGRlJ586dcXd3p3Pnzly+fJmUlBTq1q2LlJL79+9jYWHBzp07AW1mef78+RzTK126NM2bN+fChQtMnz6dMWPGMHToUIYNG/bUU9kePXqwY8cOABwcHHj//ffx8PDA19eXGzduAHDr1i1eeOEFfHx88PHxUStFKEoJ5+vrC6C64ytKCWdhYUFAQABBQUFqHiojoe8yab9+/QpcJu3SpYsqk+bBSk/nEdlsy/qX3BUIBzoB9YBAIcQuKWWmWrAQYgwwBqBSpUrpv8istmzZQlJSEk2aNMlxH31ydXXlgw8+4LPPPqNly5Z89dVXlClTJtt9Y2NjjSLm4mAs1+bo6Jg+NKL8xx9jc/JkkdKrLCXx4n9f88QmTbj74Yd5HjdixAh69OiBjY0NnTp1ws3NjQ8//JCYmBh69+5NgwYNuH79OnFxcURERHD79m1iYmKIiIhg5MiRdO/enRdeeIF169YxatQoFi9ejLOzM4GBgVy5cgU3Nze2bNlClSpViIiIwMrKioiIiPTzZ0z73r177N69m5dffpn79+8TEhLCmjVrcHR0ZP369ennBYiLi+P69etERETw6NEj6tSpw+bNm/n888/58ssvGT9+PBMmTODFF1/Ex8eHqKgohg8fbpBud3fv3uXs2bN6P6+iKJlVqlSJ+vXrq4q9oihoNBp+/vlnjh8/XuyrVpmUiRMhPFy3aXp6wuzZee720Ucf4e3tjY2NDT169KBTp04sW7aM+/fv07Jly/QhFNkZN24cw4YNY/jw4Sxbtow33niDTZs24erqysmTJ7l06RLNmzdn165dtGrViuvXr1O/fv0c07tz5w779u1j2rRpnDx5ksOHD7N7927s7e1ZsWJFjsc9evQIX19fPv30U9555x2WLFnCBx98wIQJE5g0aRJt2rTh8uXLdO3alVOnTuV5T0yNvir2VwHnDO9rom2Zz+gl4AupfXR3XghxCWgEHMi4k5RyMbAYoGHDhrJDhw7ZnvDrr7+mXr16jBo1CiGye66gfx06dKBly5a88MILzJgxg6CgIMqWLfvUfjt27CCn6zJ1xnJt0dHRVK9eXfvG0RHs7IqUXnx8PHYZ0rBzdMTRxSVfx7744os4ODiwbt06du7cycqVKwFISUlBCEHVqlWxt7fHxcWFihUr4ujoiIuLC0eOHOHvv//G2tqaSZMm8eWXX+Li4kKXLl24cOECly5d4qOPPmLJkiXcunULPz8/XLLEFBERwaFDh+jTpw8WFhZ88MEHdOnShb1799K3b9/0c2U8L4C9vT1Vq1bFxcUFGxsbRo4ciRCCTp06ERgYiIuLCyEhIURGRqafKy4ujgoVKuT4QKu42NjY4O3trddzKoqSPT8/P7Zt24aU0mj+b1YURf+eVBIDAwNVxd5IlC5dmgEDBqSXSX///Xe+/vprQFvOvXz5co7HhoSE8NtvvwEwdOhQ3nnnHUDbW3Tnzp1cunSJ9957jyVLltC+fXvc3d2zTWfXrl14eXlhYWHBlClTaNq0Kb/++iu9evXC3t4+z2t48lACoHnz5unDPYKCgjiZoREvJiaGhw8f6r1MWtz0VbE/CDQQQtQBooCBwOAs+1wGOgO7hBBVgIbAxcKcLC4ujn///deoKvVP9OjRg40bN9KnTx+6dOnCtm3bsq3cK3qUj6eYebkeEfFUpTm/LCwssLCwQErJhg0baNiwYabPn3QjysuT73rbtm1ZtGgR0dHRfPzxx3z11Vfs2LGDdu3aZXtc27Zt2bp161PbS5cunf6zlZUVqan/GxkTHx+f/rO1tXX6uS0tLdPHP6WmphISEpKvjFhRlJLB39+fVatWERERQZ06dQwdjqIoBuLs7EzDhg0JDAzkzTffNHQ4xkMHZdKi0FeZtGXLltkep8qkRaOXMfZSymRgHPAPcApYJ6U8IYQYK4QYm7bbTMBfCHEM2A68K6W8XZjz/ffff8TFxdG9e3ddhK9z3bt3Z8OGDYSHh9O1a1cePHhg6JAUI9C1a1fmzZuXPt4sLCws1/39/f355ZdfAFizZg1t2rQBoFWrVuzduxcLCwvs7Ozw9PTk+++/p23btoWOzcXFhfDwcFJTU7ly5QoHDhzI85guXbowf/789Pfhuu5apiiKyfHz8wNg7969Bo5EURRD02g0/PfffyQkJBg6FCWL4i6T+vj4FDo2VSbNmd7WsZdS/imldJVS1pNSfpq2bZGUclHaz9FSyi5SSjcpZTMp5erCnuvPP//E3t7eKLp856RHjx5s2LCBsLAwunbtysOHDw0dkmJg06ZNIykpCXd3d5o1a8a0adNy3X/u3LksX74cd3d3Vq1axZw5cwCwtbXF2dk5faKqtm3b8vDhwyJ1dWvdujV16tTBzc2Nt99+O19d2+fOncuhQ4dwd3enSZMmLFq0qNDnVxTFPDRr1gwHBwc1zl5RFDQaDXFxcSo/MELFXSZt1KhRoWNTZdJcSClN9uXq6iqz4+rqKp999tlsPzM2GzdulJaWlrJTp04yLi5OSillcHCwYYMqRsZybVFRUTpN79KlSzpNz1iYw3Vl97sGDkkjyMNyegHPAGeA88CUXPbzAVKAvhm2TQJOAMeBnwG7vM6XU15qzIwlLykIU4xZSt3H3alTJ+nt7a3TNLMyxXttijEbS15axDwzAu1qTOFZrwcYn5buCeDLvOIwxby0OOX1nb5//760tLSUU6dO1U9ABpTbvdB1mdQUmEP5srCKs1yqtxZ7fblx4wZnz56lffv2hg4lX5577jmWL1/Ov//+y6BBg9T6jIpSwgkhLIEFQDegCTBICNEkh/1moR3i9GRbDeANoIWUshlgiXZOE0UxGv7+/hw5coRHjx4ZOhTFDBQlz8ygo5TSU0rZIsP+HYHegLuUsinwdXHEX5I5OTnRqlUrtZ69ouiI2VXsn4zba926tYEjyb+hQ4cyZ84cNm3axOjRozNNCKEoSonTEjgvpbwopUwEfkFbuMxqPLABuJlluxVgL4SwAkrx9AokimJQfn5+pKSkcPDgQUOHopiHouaZOXkV7WpNCQBSyvwepxSARqPh0KFD3L1719ChKIrJ09es+HqzZ88ebG1tad68uaFDKZA33niDe/fuMX36dGJjY+nYsaPRzeivKIpe1ACuZHh/FWiVcYe0lvk+QCe0XUsBkFJGCSG+RrvKSBywTUq5LbuTCCHGAGNAu774jh07dHgJxS82NlbFrCe6jvtJz7Q1a9boLM2sTPFem2LMRqLQeWYaCWwTQkjge6ldVhnAFWgrhPgUiAfellI+9TTK1PPS4pSf73SFChWQUjJv3jyT6W1bGLndC0dHRxITE/UbkIElJiYSERFh6DAM4u7du5w9e7ZY0jbLin2LFi2wtbU1dCgF9uGHH3L37l3mzp3Lt99+q5b/UJSSKbsnejLL+9loVw5JyfgAUAhRDm1LVR3gPvCrEOJFmc1kpGmF18UADRs2lMY82Wh2duzYYdQTpGbHFGOG4om7YcOG3Lhxo9juhynea1OM2UgUOs9M01pKGS2EqAwECiFOSyl3oi0jlwN80T4MWCeEqJs2HvZ/JzLxvLQ45ec73bp1a95//32uXbtm1t//3O5FdHQ01atX129ABhZRhGWiTZ2NjU2+JvwrDLPqih8fH8/hw4dNqht+RkIIvv32W9q1a8dbb73Fr7/+auiQFEXRv6uAc4b3NXm6O30L4BchRATQF/hOCPEcEABcklLeklImAb8B/sUesaIUkJ+fHyEhIWSpIylKYRQlz0RKGZ32701gI9qu/U/S/S1tbqsDQCpQsZiuocSytramQ4cOapy9ouiAWVXsjx07RlJSEi1btsx7ZyNlYWHB1KlT8ff3Z+jQoezevdvQISmKol8HgQZCiDpCCBu0k99tybiDlLKOlNJFSukCrAdek1JuQtsF31cIUUpom6U6A6f0Gr2i5IO/vz+3b9/mwoULhg5FMX2FzjOFEKWFEGUAhBClgS5oVxQB2IS26z5CCFfABrith+spcTQaDRcvXuTixYuGDkVRTJpZVeyPHDkCgKenp2EDKSJbW1u2bNlCrVq16N27N2fOnDF0SEoxsLS0xNPTk6ZNm+Lh4cE333xT4IkTIyIiaNasWZ77nTt3jh49elCvXj2aN29Ox44d2blzZ2FDL5QOHTpw6NChIqczefJkmjZtyuTJk3UQlfGRUiYD49DO3HwKWCelPCGEGCuEGJvHsfvRFlpD0S7fZEFaF1FFMSZ+fn7A/ya8VZTCKkqeCVQBdgshjgAHgD+klH+nfbYMqCuEOI52Qr7hWbvhK7oREBAAQFBQkIEjKbn0XSYdOXKkKpMWA7MaY3/kyBEcHByoU6eOoUMpsgoVKvDXX3/h5+dH9+7dOXDgABUqVDB0WIoO2dvbEx4eDsDNmzcZPHgwDx48YMaMGfk6PiUlJV/7xcfH8+yzz/L111/Tq1cvAI4fP86hQ4do165dpn2Tk5OxsjLubOH777/n1q1bJjmPRn5JKf8E/syybVEO+47I8v4j4KNiC05RdKBJkyY4OjoSEhLCsGHDDB2OYuIKm2dKKS8CHjnslwi8qLsolZw0atSIGjVqEBgYyJgxYwwdTomk7zLp5MmTGT16NKDKpLpkdi327u7uWFiYx2XVq1ePLVu2EBUVRd++fUlKSjJ0SEoxqVy5MosXL2b+/PlIKYmIiKBt27Z4e3vj7e2d3qq1Y8cOOnbsyODBg3Fzc8uUxsWLF/Hy8npqCak1a9bg5+eXXqkHaNasGSNGjABg+vTpjBkzhi5dujBs2DBu3brFCy+8gI+PD71792bPnj0APHr0iJdffhkfHx+8vLzYvHkzACtWrOD555/nmWeeoUGDBrzzzjv5vu6c0szp+nv16sWjR49o1aoVa9euLcAdVhTFmFhYWNCqVStCQkIMHYqiKAYmhECj0bB9+/Z8VxCV4qOPMqlGo0nflt8yqY+PjyqT5sG4H4MUgJSSo0ePMnjwYEOHolO+vr4sWbKEYcOGMWHCBL777jtDh2R2Jp47R3hsbJHSiI+Px+7evfT3ng4OzG7QoEBp1K1bl9TUVG7evEnlypUJDAzEzs6Oc+fOMWjQoPQuQwcOHOD48ePUqVMnfamQM2fOMHDgQJYvX/7UUJQTJ07kOfvm4cOH2b17N/b29gwePJhJkybRpk0b9uzZw6hRozh16hSffvopnTp1YtmyZdy/f5+WLVumd58LDw8nLCwMW1tbGjZsyPjx43F2ds71nECOaeZ0/Vu2bMHBwSH9qbKiKKbL39+fmTNn8vDhQ8qUKWPocBRFMSCNRsOKFSsICwujRYsWhg7HYHRRJs3KXMqkly9fpmvXrqpMmguzqdhHRkby4MEDPDyy7VFl0oYOHcqxY8f46quvaNasGa+99pqhQ1KKyZPhe0lJSYwbN47w8HAsLS0zrXfZsmXLTMNNbt26Re/evdmwYQNNmzbN8xx9+vTh3LlzuLq68ttvvwHap4729vaAdozbyZMnAe06ozExMTx8+JBt27axZcsWvv76a0D7MOPy5csAdO7cGScnJ0DbxTYyMjJfmWhOaVavXj3H61cUxTz4+fmRmprKgQMH6Ny5s6HDURTFgJ7kAYGBgSW6Ym9MjK1MCqgyaR7MpmL/5Jeeny+RKfr88885efIkb7zxBo0aNaJTp06GDslsFPQpZnZ0sR7nxYsXsbS0pHLlysyYMYMqVapw5MgRUlNTsbOzS9+vdOnSmY5zcnLC2dmZPXv2ZPv9b9q0aaZJSTZu3MihQ4d4++23s00zNTWVkJAQ7O3tM12XlJINGzbQsGHDTOnv378/09giS0tLkpOT83XNOaU5ffr0HK9fURTz0KpVKwBCQkJUxV5RSrgqVarg7u5OYGAg7733nqHDMRhdlEl1objLpL179wYKVibNSJVJs2ceg9HRzrAI4OrqauBIioelpSU//fQTDRs2pF+/fmqJIDNz69Ytxo4dy7hx4xBC8ODBA6pVq4aFhQWrVq3KdcyZjY0NmzZt4scff+Snn3566vPBgwezZ88etmz53+o/jx8/zjG9Ll26MH/+/PT3T7oYde3alXnz5qU/wQ0LCyvoZT4lpzQLcv2KopimsmXL0qRJEzXOXlEUQNsdf8+ePbmWUZTip48yaWBgYPo2VSbVHbOq2Ds6OlKpUiVDh1JsHB0d0ytnPXv2JCYmxsARKUURFxeXvrRIQEAAXbp04aOPtJOZv/baa6xcuRJfX1/Onj371BPRrEqXLs3WrVv59ttv0yf7eMLe3p6tW7eyaNEi6tati5+fH5988gkffPBBtmnNnTuXQ4cO4e7ujkajYdEi7cTC06ZNIykpCXd3d5o1a8a0adMKfM3PPvssNWvWpGbNmvTr1y/HNAt6/YqimCY/Pz/27duHWkVMMQe3gBT1XS40jUZDYmIiu3btMnQoJY6+y6Q//fRTgcukTZo0UWXSvEgpTfbl6uoqn+jSpYts3ry5NAfBwcG5fr59+3ZpaWkpe/bsKVNSUvQTlI7kdW36EhUVpdP0Ll26pNP0jIU5XFd2v2vgkDSCPMxYXhnzUlNhLHlJQRRHzNHR0bJdu3by2rVrOk/7ieK810uXLpWAPH36tE7TVd8P/VB5aeYXrq7yuWPH5KPk5CLeWfNQ0O/0o0ePpI2NjXzrrbeKJyADyu1e6LpMagrMoXxZWMVZLjWrFvsGRjIupbh16tSJb775ht9//51Zs2YZOhxFURTFQGbOnMnu3buZOXOmoUMpFD8/P4D05YMUxZRVAjbfvk2H8HBuJCYaOhyTU6pUKVq3bp2pm7aiKPlnFhX7xMREIiMjS0zFHmD8+PEMHDiQDz74gO3btxs6HEVRFEXPrl27xtLly0lNTWX58uVcv37d0CEVWMOGDSlbtqwaZ6+YhXLAxmbNOP7oEb6hoZx89MjQIZkcjUbD0aNHuXHjhqFDURSTYxYV+0uXLpGamlqiKvZCCJYsWUKjRo0YNGgQV69eNXRIiqIoih5NnT6dxLRJfJJTUkyy1d7CwgJfX19VsVfMRu+KFfnP05O4lBT8Q0MJvnfP0CGZFI1GA6AarRSlEMyiYv9k3cLatWsbOBL9cnBwYMOGDcTFxdGvXz8SVbcvRVGUEuHatWusXrkSkpIASEpMZOmyZSbZau/n58eJEyd48OCBoUNRFJ3wcXRkn7c3NWxt6Xr0KD+a4N+loXh5eVGuXDnVHV9RCsEsKvZXrlwBwNnZ2cCR6F+jRo1Yvnw5+/bt46233jJ0OIqiKIoeTJ0+neTU1EzbElJSeOvDDw0UUeH5+/sjpeTAgQOGDkVRdMbF3p49Xl60dXJi+OnTTL90STvBnpIrS0tLOnfuTGBgoLpfilJAZlGxf9INvXr16gaOxDD69u3Lm2++yfz587NdM1JRFEUxL3/t2pXeWp8uKYlfd+zgUlycYYIqpJYtWyKEUBPoKWanrLU1f7m7M6JqVWZERjL89GkSszyQU56m0WiIiori9OnThg5FUUyKWVTsr1y5QpUqVbC1tTV0KAbzxRdf0KZNG0aPHs2JEycMHY6SD5aWlnh6euLh4YG3t3d6oTYiIoJmzZrp5BwjRoygRo0aJCQkAHD79m1cXFwAiI6Opm/fvgCEh4fz559/5pjOoUOHeOONNwBYsWIF48aNK1AcBw4coEOHDjRo0ABvb2+effZZjh07BsD06dP5+uuvC3ppilJi3U1K4vH339P/+PFMy9wcefgQh2XL6HTkCFfj4w0dZr45OjrSrFkzNc5eMUs2FhYsa9iQmS4urLpxg65Hj3Iv60M5JZMn4+yDgoIMHEnJocqk5lEmNYuK/dWrV6lZs6ahwzAoa2tr1q1bR5kyZejfvz+PHz82dEhKHuzt7QkPD+fIkSN8/vnnvPfee8VyHktLS5YtW/bU9urVq7N+/Xog90w0OTmZFi1aMHfu3EKd/8aNG/Tv35/PPvuMc+fOERoaynvvvceFCxcKlZ6ilHSzr17lYUoK07LMK+Pu4MA2d3fuJiXR+cgRrqcVnkyBn58f+/btI1W1ZipmSAjBBy4urG7cmL0PHuAfFmZyPWv0qU6dOtStW1eNs9cjVSY1jzKpWVTsr1y5UiLH12dVrVo1Vq9ezalTp9KfZCmmISYmhnLlyj21PeuTyB49erBjxw4Atm3bhp+fH97e3vTr14/Y2Nhs0544cSLffvstycnJmbY/eQqbmJjIhx9+yNq1a/H09GTt2rVMnz6dMWPGMHToUIYNG8aOHTvo0aPHU2nfunWLF154AR8fH3x8fNizZ89T+8yfP5/hw4fj7++fvq1NmzY899xzT+0bHh6Or68v7u7u9OnTh3v37nHq1ClatmyZKW53d3cADh8+TPv27WnevDldu3bl2rVr2d4DRTEX95KSmHP1Ki9UrEgzB4enPm/h6Mhf7u5EJSQQcOQIt01kUlV/f38ePHigut4qZm1IlSps8/DgRmIivqGh7I+JMXRIRkuj0bBjxw6SVO8GvTPWMmmXLl1UmTQPVno/YzG4evUqHTt2NHQYRiEgIID33nuPzz77jE6dOjF48GBDh2T0zk08R2x49hlQfsXHx3PP7n9L2jh4OtBgdu7LL8bFxeHp6Ul8fDzXrl3j33//zff5bt++zSeffEJQUBClS5dm1qxZfPPNN3yYzcRZtWrVok2bNqxatYqePXs+9bmNjQ0ff/wxhw4dYv78+YC2K9Lhw4dZs2YNjRo1Ss+4s5owYQKTJk2iTZs2XL58ma5du3Lq1KlM+5w4cYLhw4fn67qGDRvGvHnzaN++PR9++CEzZsxg9uzZJCYmcvHiRerWrcvatWvp378/SUlJjB8/ns2bN1OpUiXWrl3L+++/n+2TYEUxF3OjoohJSWFaWvfF7Pg7OfG7mxvdjx1Dc/Qo/3p4UM7aWn9BFoKfnx8Ae/fupUmTJgaORlGKT/uyZQnx9qb70aN0CA9nTePGPF+pkqHDMjoajYbvv/+e/fv306ZNG0OHoze6KJNmZYxl0o0bN/LSSy899XluZdLdu3djb2+vyqS5MPmKfUJCAg8ePKBq1aqGDsVozJgxg//++49XXnkFHx8fGjTI/Y9ZMYwn3Z4AQkJCGDZsGMePH8/Xsfv27ePkyZO0bt0agMTExPSCcXamTp1Kr169ePbZZ/MdX69evbCzs8t1n6CgIE6ePJn+PiYmhocPH1KmTJkcj2nVqhUxMTF06dKFOXPmpG9/8OAB9+/fp3379gAMHz6cfv36AdC/f3/WrVvHlClTWLt2LWvXruXMmTMcP348fSxeSkoK1apVy/f1KYqpeZCczOyrV3muYkU8smmtz6hjuXJsbNqU3seP0+3oUQI9PChjZbz/5Tdo0IAKFSoQEhLCqFGjDB2OohSrhqVKEeLtTa9jx+h74gRf16vHpJo1EUIYOjSj0alTJ4QQBAUFlaiKvaHou0zarVu3fFewQVsmtbe3z3UfVSY1g4r9rVu3AKiknnams7Ky4ueff8bT05MBAwYQEhJSoicWzEteTzHzIyIiIn0CkMLw8/Pj9u3b6d/nJ6ysrDKNOY1PmxBLSolGo+Hnn3/OV/r169fH09OTdevW5Tum0qVL57lPamoqISEhuWa2TZs2JTQ0lN69ewOwf/9+1q9fz9atW/Mdy4ABA+jXrx/PP/88QggaNGjAsWPHaNq0qZpwSykx5l29yv3kZD7MMrY+J89UqMC6pk154fhxnj12jL/d3SllaVnMURaOEAJfX1/196yUGJVtbAj29GToqVO8deECF+LimFO/PlYWZjFKtsjKlStHixYtCAwMZPr06YYOR290USYtKn2USZs0aaLKpMXA5HMPVbHPnrOzM8uXLycsLIzJkycbOhwlD6dPnyYlJYUKFSpk2u7i4kJ4eDipqalcuXIlfZ1nX19f9uzZw/nz5wF4/PgxZ8+ezfUc77//fo4zfZYpU4aHDx8WOO4uXbqkd5UC0p/2ZvT666+zYsWKTEtZZTe5o5OTE+XKlWPXrl0ArFq1Kv1Jab169bC0tGTmzJkMGDAAgIYNG3Lr1q30TDQpKUmtCKGYrZjkZL65epWeFSrglUvrQ1a9K1ZkTZMm7HnwgN7HjxOfklKMURaNn58fp06d4t69e3nvrChmwN7SknVNm/K2szPfRUfz3PHjxGYZe1ySaTQa9u/fz4MHDwwdSomijzLp66+/rsqkxcBsKvYVK1Y0cCTGp1evXkycOJF58+axadMmQ4ejZPFkPNOTnhUrV67EMktrWuvWralTpw5ubm68/fbbeHt7A9oHWStWrGDQoEG4u7vj6+ub56RTTZs2TT8+q44dO3Ly5Mn0iUrya+7cuRw6dAh3d3eaNGnCokWLntqnatWqrF27lvfee4/69evj7+/P+vXrs12eZOXKlUyePBl3d3fCw8Mzjc8aMGAAq1evpn///oB2HNb69et599138fDwwNPTU62DrZitBVFR3CtAa31GAypXZlmjRgTdu0ffEyeMdh3tJ5MZ7d+/38CRKIr+WAjBV/Xq8V2DBvx19y7twsOJNqEVLYqTRqMhJSUlxzHViu7ou0zq6uqqyqTFIeMauKb2cnV1latXr5aAPHXqlDQXwcHBOksrPj5eNm/eXJYtW1ZevnxZZ+kWli6vrSiioqJ0mt6lS5d0mp6xMIfryu53DRySRpCHGcvL1dW1oLfV4IwlLymIwsb8MClJVti1S3Y/cqRI51949aokOFi+cOyYTEpJyfdx+rrXDx8+lBYWFnLatGlFTqskfT8MSeWlus1L/7h9W5b+7z/pvHevPPrwYZHSMgZF/U7Hx8fLUqVKyXHjxukmIAPK7V7oukxqCsyhfFlYxVkuNZsWe9UVP3u2trb88ssvJCUlMWzYMFKMuBumoiiK8rTvoqO5k5zMh0WYxwNgbI0afFuvHhtu32bE6dOkSKmbAHXEwcEBd3d3g49RVBRD6V6hAru8vEiRktZhYWy7e9fQIRmUra0t7dq1U+vZK0o+mUXF3tLSMtv1FhWt+vXrM2/ePHbs2MH//d//GTocRVEUJZ8epaTw9ZUrdC1XjlaOjkVOb6KzM5/WqcOamzcZe/YsqUZWuffz82P//v3qIbRSYnmVKcN+b2/q2NnR/ehRfoiONnRIBqXRaDhz5gxXrlwxdCiKYvRMvmJ/+/Ztypcvj4WaRTRXI0aM4IUXXuCDDz4gNDTU0OEoiqIo+bAwKopbSUl8VMTW+oym1q7NB7Vr88O1a0w4fx5pRJV7f39/Hj58mGnJIkUpaWra2bHLy4uAcuUYffYsUy9eNLqHcPryZPkw1WqvKHnTW21YCPGMEOKMEOK8EGJKNp9PFkKEp72OCyFShBDl80r3wYMHlC1btlhiNidCCBYvXkzlypUZPHhwtjNAKoqiKMbjcUoKX125QkC5cvg5Oek07Y9dXHirZk3mR0Xx7sWLRlO5f7L2sZoIUynpHK2s+N3NjTHVqvH55csMPnnSqFe1KC7NmjWjSpUqBAUFGToURTF6eqnYCyEsgQVAN6AJMEgI0STjPlLKr6SUnlJKT+A94D8pZZ6Dix48eICjDronlgTly5dn5cqVnDlzhrfeesvQ4SiKoii5+D46mptJSXxUiJnw8yLSZuJ+rXp1vrpyhRkRETo/R2HUrVuXSpUqqXH2igJYW1iwyNWVWXXrsvbWLQKOHOF2YqKhw9IrIQQBAQEEBQVlWkNdUZSn6avFviVwXkp5UUqZCPwC9M5l/0HAz/lJOCYmBicdt2SYs86dO/P222+zaNEifv/9d0OHoyiKomQjLiWFL69coWPZsrQppl5pQgjmNWjAS1WrMiMyklmXLxfLeQoak5+fn6rYK0oaIQTv1KrFL02acOjhQ/zCwjhXwnpdajQabt26xdGjRw0diqIYNSs9nacGkHHWi6tAq+x2FEKUAp4Bnl5QUPv5GGAMaGfCT0xMxNnZ2azWuIyNjS3W69FoNGzatIlhw4axdOlSypfPc8SDzhT3teWXo6MjiTp86p2YmEhEAVq8Zs6cSY0aNXj55ZcBGDZsGNWqVWPWrFkAfPLJJ1StWpVmzZqxZMkSli5d+lQa7777LqNGjaJBgwYsWLCA119/vUAxDxw4kJs3b2Jra0vp0qWZNWsW9erVK9J1GaO7d+9y9uxZQ4ehKAWy5No1ricm8kuTJnnvXAQWQrCkYUPiU1OZcvEi9hYWvFGzZrGeMy9+fn5s2bKFO3fuUKFCBYPGoijGYkDlytS0taX3sWP4hYay2c2N1iWkYSsgIADQjrP39PQ0bDBmaNKkSdSuXZuJEycC0LVrV5ydnfnhhx8AeOutt6hRowbe3t58/fXXbN269ak0Ro0axZtvvkmTJk347LPPmDp1aoFi6NChA9euXcPOzg4HBweWLVtGw4YNi3xtJY2+KvYim205DejrCezJqRu+lHIxsBigYcOG8vHjx9SrV48OHTroJFBjsGPHjmK/ns2bN9O8eXOWLFnCn3/+iRDZ/Yp0Tx/Xlh/R0dFUr15dZ+lFRETgUoDJrZ555hl+/fVXXFxcSE1N5dGjR1y+fDk9jRMnTjB69Gji4uKwt7fPNu21a9em/7xw4UK++uqrAsVsZ2fHunXraNGiBYsXL2bOnDls2bKlSNeVk5SUFCwtLYucTmHY2Njg7e1tkHMrSmHEp6Qw6/Jl2jk50V4Pc8hYCsHKRo2IT01lwvnz2FlYMEaH+WNB+fv7A7Bv3z6effZZg8WhKMamtZMT+7y96X7sGJ3Dw/mxcWP6V65s6LCKXY0aNWjSpAlBQUFMnjzZ0OGYHX9/f3799VcmTpxIamoqt2/fJiYmJv3zvXv3Mnv2bOLi4nJM48lDAKBQFXuANWvWpJdJJ0+e/FSZVFcMWSYtbvrqin8VcM7wviaQ0/odA8lnN3zQdsVXY+wLrkmTJnz99df8/fffLFiwwNDhlDitW7dOnxzqxIkTNGvWjDJlynDv3j0SEhI4deoUXl5egLaXQ9++fWnUqBFDhgxJn+SqQ4cOHDp0iClTphAXF4enpydDhgwBYPXq1bRs2RJPT09eeeWVPJeOateuHefPnyciIoK2bdvi7e2Nt7c3hw8fBrQPZNq1a0efPn1o0qQJY8eOTR/rtm3bNvz8/PD29qZfv37ExsYC4OLiwscff0ybNm349ddfdX8TFcVMLb1+nejERJ3OhJ8XawsLfm7ShG7lyzP27FlWXb+ut3Nn1aJFC6ysrNQEeoqSjfqlShHi7Y2PoyMDTp5k1uXLRjP5ZXEKCAhg586dxMfHGzoUs2MqZdInMaoyac701WJ/EGgghKgDRKGtvA/OupMQwgloD7yY34QfPnyoxtgX0muvvcaff/7J5MmT6dixI02bNjV0SAZx7txEYmPDi5RGfHw89+7Zpb93cPCkQYPZOe5fvXp1rKysuHz5Mnv37sXPz4+oqChCQkJwcnLC3d0dGxsbAMLCwjhx4gTVq1endevW7NmzhzZt2qSn9cUXXzB//nzCw7XXcOrUKdauXcuePXuwtrbmtddeY82aNQwbNizHeH7//Xfc3NyoXLkygYGB2NnZce7cOV544QVeeOEFAA4cOMDJkyepXbs2zzzzDL/99hsdOnTgk08+ISgoKL07/zfffMOHH34IaHsF7N69u7C3VVFKnITUVL64fJk2Tk501POKL7YWFmxo2pQex44x4vRp7Cws6GeA1sBSpUrh4eGhxtkrSg4qWFsT6O7OS2fOMOXiRS7ExbGgQQOszXjpZ41Gw9y5c9mzZw+dO3c2dDjFRhdl0qyMsUzarl27HOPJqUw6aNAgDh06BKgyaU70UrGXUiYLIcYB/wCWwDIp5QkhxNi0zxel7doH2CalfJSfdFNTU5FSqhb7QhJCsGzZMtzd3XnxxRfZv39/+h+uUvyePCHdu3cvb775JlFRUezduxcnJ6f0rqgALVu2pGbamFdPT08iIiIyZaJZbd++ncOHD+Pj4wNAXFwclXMonA8ZMiS9q/+8efNISkpi3LhxhIeHY2lpyblz5zLFUbduXQAGDRrE7t27sbOz4+TJk7Ru3RrQjsl/slwVwIABAwp5dxSlZFp+7RpXExJY1rCh3oZIZWRvackWNzeeOXqUwadOYWthgSH+h/Xz82P58uUkJydjZaWvNghFMR12lpasadyYunZ2fHb5Mpfj41nXtCmOZvr30r59e6ysrAgMDDTrir2h6LtMml3FPq8yacb5klSZNHt6++uXUv4J/Jll26Is71cAKwqQJgClS5cucnwlVZUqVVi8eDHPPfccM2fOZObMmYYOSe9ye4qZX4UZi+7v78/evXs5duwYzZo1w9nZmf/7v//D0dExfVI9AFtb2/SfLS0tSU5OzjVdKSXDhw/n888/zzOGJ+OZnpg+fTpVqlThyJEjpKamYmf3v14IWSsZQgiklGg0Gn7+OfvRM+pvU1HyLzE1lc8vX8bP0ZGAcuUMFkdpS0v+cHMj4MgR+p04wSdABz3H4O/vz/z58zl+/LiaLEtRcmAhBJ/WrUtde3teOXOGNmFh/OHmhnOG/7vNRZkyZfDz8zP79ex1USYtDH2XSbObmFmVSYvOpPvsPBlPYW9vb+BITFvv3r3T/+gOHDhg6HBKjNatW7N161bKly+PpaUl5cuX5/79+4SEhGR6wpgf1tbWJCUlAdolDdevX8/NmzcB7azwkZGR+UrnwYMHVKtWDQsLC1atWpVpHNSBAwe4dOkSqamprF27ljZt2uDr68uePXs4f/48AI8fP1Yz0CtKIa28fp3LCQl8WLu2QVrrM3K0suJvd3calyrFNOC/+/f1ev4neaAaZ68oeRtZrRp/ubsTGR+Pb2goYQ8fGjqkYhEQEEBoaCh37twxdChmR5VJzYNJV+yftNirin3RzZkzh+rVqzNs2LBcZ71UdMfNzY3bt2/j6+ubaZuTkxMVK1YsUFpjxozB3d2dIUOG0KRJEz755BO6dOmCu7s7Go2Ga9eu5Sud1157jZUrV+Lr68vZs2cpVapU+md+fn5MmTKFZs2aUadOHfr06UOlSpVYsWIFgwYNwt3dHV9fX06fPl2g2BVFgaTUVD67fJmWZcrQVY9LkOamvLU1gR4eVAWePXqUkAcP9Hbu2rVrU7VqVTXOXlHySVO+PLu9vLAUgrZhYfxphpVfjUaDlJLt27cbOhSzYwpl0owt7qpMmgMppcm+atWqJQG5ZcsWaU6Cg4MNct6goCAJyAkTJhTbOQx1bVlFRUXpNL1Lly7pND1j8eS6goOD5bPPPmvYYAopu981cEgaQR5mLC9XV9eC3laDM5a8pCByi3lpdLQkOFhuvX1bfwHl0/rgYFl/3z7ptHOnPBwTo7fz9unTR9arV69Qx5rb98NYqbzU+PLSqPh46XXwoLQIDpYLrl41aCy6/k4nJSVJJycnOWrUKJ2mqw+53Qtdl0lNQVHKzaZcJpWyeMulqsVeSde5c2fGjRvHnDlzCA4ONnQ4iqIoJUJyaiqfRkbS3MGB7kbSWp9RBWC7hwdlrazQHDnC8bTlg4qbn58fFy5cSO/CqShK3qrb2rLT05Nu5cvz+rlzTL5wgVRpHsvhWVlZ0bFjRwIDA9PrAIqi/I9JV+zVGHvdmzVrFg0aNOCll14iJibG0OEoRqJDhw5s3brV0GEoillac/MmF+Pj+dDFxeBj63NSy86O7Z6e2FlY0PnIEc48flzs53wyE/O+ffuK/VyKYk4crKzY1KwZr1evztdXrtD/xAni8lg73FQEBAQQGRnJhQsXDB2KYiCqTJozk67YP3lal3EcsFI0pUqVYuXKlVy5coVJkyYZOhxFURSzlpyayieRkXg6ONCzQgVDh5Orevb2bPfwAKBzeDgXi3k+lubNm2Ntba0m0FOUQrCysGBegwZ8U68ev92+TacjR7iZmGjosIpMo9EAEBgYaOBIFMX4mEXFXrXY65afnx/vvPMOy5YtU0/EFEVRitEvN29yPi7OKGbCz49GpUsT5OFBXGoqncLDuRIfX2znsrOzw8vLS02gpyiFJIRgkrMzG5o25UhsLL6hoZx+9MjQYRVJgwYNqFWrlqrYK0o2zKJin3FNRUU3pk+fjru7O6NHj1bLiiiKohSDFCn5JDIS99Kl6V3AWYcNyc3BgW0eHtxLTqbTkSNcS0gotnP5+flx8ODB9KWTFEUpuD6VKrHD05NHKSn4h4XpfflKXRJCoNFo+PfffzMtf6YoiplU7K2trQ0cifmxtbXlxx9/5M6dO7z22muGDkdRShQhxDNCiDNCiPNCiCm57OcjhEgRQvTNsK2sEGK9EOK0EOKUEKJgC9AqerPu5k3OxMUxrXZtLEygtT6j5mXK8Je7O9cSEgg4coRbxdTF19/fn7i4OI4ePVos6SvmoYh5ZoQQ4pgQIlwIcSjD9q/S8tGjQoiNQoiyxXwZxaqloyP7vL2pYmOD5sgRVl+/buiQCi0gIIAHDx5w6NChvHdWlBLELCr2VlZWBo7EPHl4eDB9+nTWrVvHL7/8YuhwzI6lpSWenp7pr4iICHbs2EGPHj0MHVqRzJ49m8d6mFjLXAkhLIEFQDegCTBICNEkh/1mAf9k+WgO8LeUshHgAZwq3oiVwkiRkpmRkTQtVYrnK1UydDiF4u/kxFY3Ny7Gx9Pl6FHuFUOrup+f9rmUGmev5EQHeSZARymlp5SyRYZtgUAzKaU7cBZ4T+fB61kde3v2ennR2smJoadPMzMiwiRnl+/cuTOgxtnrkiqTmgezqNirFvvi884779CqVStee+01oqOjDR2OQV27do327dtzXUdPue3t7QkPD09/ubi46CRd0P5tPFk1Qt9KWiZaDFoC56WUF6WUicAvQO9s9hsPbADS1wITQjgC7YClAFLKRCnl/WKPWCmwDbducerxY6a5uJhca31GHcqVY1OzZpx89Ihnjh4lJjlZp+k7OztTo0YNNc5eyU2h88zcSCm3SSmffKH3ATV1EayhlbO25h93d4ZWqcKHERG8fOYMiQYqLxRWpUqV8PLyKtEVe1UmzZ+SViY1i6ZuVbEvPlZWVqxcuRIvLy9GjRrFH3/8YRITPBWHmTNnsnv3bj7++GO+++67Yj/f9OnTcXBw4O233wagWbNmbN26FRcXF7755huWLVsGwKhRo5g4cSIRERF069aNjh07EhISwqZNm1i3bh3r1q0jISGBPn36MGPGDB49ekT//v25evUqKSkpTJs2jQEDBnDw4EEmTJjAo0ePsLW1Zfv27aSkpDB58mR27NhBQkICr7/+Oq+88go7duxg+vTpVKxYkePHj9O8eXNWr17NvHnziI6OpmPHjlSsWJHg4OBiv09mqAZwJcP7q0CrjDsIIWoAfYBOgE+Gj+oCt4DlQggP4DAwQUr51GxJQogxwBjQFpJ27Nihw0sofrGxsSYbcyrwLlAbqHjyJDtOnjRwZLnL617bAh8CHz18SJvdu5kF6HJK2/r16xMcHFyg37cpfz+UAitKngkggW1CCAl8L6VcnM05XgbWZndyU81LX0Lburfi+nWOXL/Ox4CDjs9RnN/phg0bsn79ev766y+TmEQ7t3vh6OhIYgGHM02bNo1du3YxefJkZs6cWeT4pJRERERk2nb9+nXi4uKIiIhg9uzZlCpVijFjxgDQtWtXli5dSs2aNfnhhx/49ddfARgwYAAvv/wyV69eZcSIEfj5+REaGsr333/PH3/8wZ9//klCQgIBAQG8/fbbPH78mHHjxnHt2jVSU1MZP348PXr04MiRI3z88cc8fvwYGxsb1qxZg729PbNmzWL//v0kJCQwbNgwBg8ezL59+5g9ezblypXj7NmzuLm58e2337JixQqio6Np06YN5cqV4+effy7yfdKFu3fvcvbs2WJJ26Qr9qrFXj8aNmzIF198wYQJE1ixYgUvvfSSoUPSqYkTJxIeHp7j57t27cr0pHHhwoUsXLgQCwsL2rZtC0B8fDx2dnbp+3h6ejJ79uxczxsXF4enpycAderUYePGjfmK9/Dhwyxfvpz9+/cjpaRVq1a0b9+ecuXKcebMGZYvX853333Htm3bOHfuHAcOHEBKSa9evdi5cye3bt2ievXq/PHHHwA8ePCAxMREBgwYwNq1a/Hx8SEmJgZ7e3vWrl2Lk5MTBw8eJCEhgdatW9OlSxcAwsLCOHHiBNWrV6d169bs2bOHN954g2+++Ybg4GAqmtBkYEYmuydnWftKzgbelVKmZHnQZgV4A+OllPuFEHOAKcC0pxLUFl4XAzRs2FB26NCh6JHr0Y4dOzDVmDfcukXEiRP81LgxnatUMXRYecrPve4ANLh5k0EnT/J/Zcvyu5sb9paWOjl/r169eOutt2jUqBFVq1bN1zGm/P1QCqwoeSZAaylltBCiMhAohDgtpdyZnrgQ7wPJwJrsTm7KeWlHoOP164w+c4Z37e35w80NFx1WkovzO52UlMQvv/yClNIk/m5yuxfR0dFUr14dKHiZdPXq1axevTpTmTSr/JRJ4+Pjee6554D/lUkjIiKwt7fHxcWFsmXL4uDgkN6Sb21tTc2aNblz5w6bN28mNDQ0vUzap08fatasycWLF1m9ejW+vr5s27aNO3fuEB4ejpQSjUbD5cuXuXXrFvXq1ePff/8FtGVSe3t7OnXqlKlMWqpUKZYtW0atWrVYvHhxepl00KBBVK1alVOnTmUqk0ZFRTFjxgxWrlzJ7t27japMamNjg7e3d7GkrbriK/kybtw42rVrx6RJk7h69aqhw9Grli1bUrlyZSwstH8uFhYWVK5cmVatWuVxZO4ydnvKb6UeYPfu3fTp04fSpUvj4ODA888/z65duwCoXbs2vr6+AGzbto1t27bh5eWFt7c3p0+f5ty5c7i5uREUFMS7777Lrl27cHJy4syZM1SrVg0fH21DhqOjI1ZWVuzatYsff/wRT09PWrVqxZ07dzh37lz6falZsyYWFhbp47EUnbgKOGd4XxPIOg6mBfCLECIC6At8J4R4Lu3Yq1LK/Wn7rUdb0VeMRKqUfBwRQUN7e/pXrmzocHSqf+XKLG/UiH/v36fviRM6697r7+8PoLrjKzkpSp6JlDI67d+bwEa0XfsBEEIMB3oAQ6QpDkbPh+FVq/KPuztRCQn4hoZyKCbG0CHlS5s2bbC1tS1x3fHNpUx64cKFApdJt23bpsqkeTDpFvsnLHXUKqDkzMLCgmXLluHm5sYrr7zC1q1bzaZLfl5PMQFeffVVFi9ejJ2dHYmJibzwwguZuuNHRETodDwSaIdBZHwqG5+2XnRuZYvSpUun/yyl5L333uOVV155ar/Dhw/z559/8t5779GlSxeee+65HH+f8+bNo2vXrpm27dixI9Myk5aWliTreGxtCXYQaCCEqANEAQOBwRl3kFLWefKzEGIFsFVKuSnt/RUhREMp5RmgM2Dc/bxLmC23b3P00SNWNWqEpZnkoRkNq1qV+NRUXjl7lkEnT7K2SROsLIrWhuDl5YWNjQ179+6lT58+OopUMSOFzjOFEKUBCynlw7SfuwAfp+33DNpRM+2llGY9SLdjuXKEeHvT/dgx2oeH81OTJka/BKe9vT1t27Y1u4q9LsqkxUHXZdKM5eb8lkmllKpMmgeTb7G3srIymwqmsatXrx5ffPEFf/75Jz/++KOhw9GrGzduMHbsWPbt28fYsWN1NllJblxcXAgNDQUgNDSUS5cuAdCuXTs2bdrE48ePefToERs3bsy2+1XXrl1ZtmwZsbGxAERFRXHz5k2io6MpVaoUL774Im+//TahoaE0atSI6OhoDh48CMDDhw9JTk6mbdu2LFy4MH0N6bNnz/Lo0VPDtTMpU6YMDx8+1Nl9KGnSJmsah3bm5lPAOinlCSHEWCHE2HwkMR5YI4Q4CngCnxVbsEqBSODjyEjq29sz0Mxa6zMaU706s+vX57fbtxl++jQpRWzotLW1pXnz5qrFXslWEfPMKsBuIcQR4ADwh5Ty77TP5gNl0HbPDxdCLCqmSzAKjUuXZp+3N01Ll6bP8ePMMYHemRqNhhMnTnDt2jVDh6JX5lAmvX79eoHLpF27dlVl0jyYfIu9RRFbApSCGTduHOvXr2fChAkEBARQo0YNQ4ekF7/99lv6zwsWLNDLOV944YX0Lkc+Pj64uroC4O3tzYgRI2jZUttbcNSoUXh5eT3V7ahLly6cOnUqfbkoBwcHVq9ezfnz55k8eTIWFhZYW1uzcOFCbGxsWLt2LePHjycuLg57e3uCgoIYOHAgsbGxeHt7I6WkUqVKbNq0Kde4x4wZQ7du3ahWrZqaPK+QpJR/An9m2ZZtoVJKOSLL+3C03U4VIxMChMXGsqJRoyK3Yhu7CTVrEpeSwnuXLmFnYcGShg2LNPu/n58fCxYsIDExERsbGx1GqpiDwuaZUsqLaJcFzW6/+joM0SRUsbFhh6cnL546xcTz57kYF8c39esbbe+igIAAAIKCghg6dKiBo9EfcyiTWltb8+uvvxaoTDpq1CgiIiJUmTQ3UkqTfZUvX17a2NhIcxMcHGzoEHJ19uxZaW9vL5999lmZmppaoGON5dqioqJ0mt6lS5d0mp6xMIfryu53DRySRpCHGcvL1dW1oLfV4IwlL8mv1NRU6RocLOuGhMiklBRDh1MgRbnX0y5elAQHy9fOnCnw/xcZrV+/XgJy//79+drf1L4fUppmzCovNf28NDvJqaly0rlzkuBg2evoURmbnFyodIr7O52SkiIrVqwohw4dWqzn0YXc7oWuy6SmwBzKl4VVnOVSk28yUN3w9a9BgwZ89tln/PHHH6xatcrQ4SiKohi9P+/e5Szwfu3aZt9an9EMFxfednbmu+hoJl+4gLb8UnBPWnn27t2ry/AURcmGpRB8U78+8xs0YOudO7QPC+N6QoKhw3qKhYUFnTt3JigoqNB5i6KYk5JTulB0avz48bRu3ZoJEyYQHZ118llFURTlCSm1M+FXBYaawPJ2uiSE4Mu6dXm9enX+7+pVPirkTMXVq1enVq1aapy9oujR6zVqsLlZM049fkyr0FBO5DGe2RACAgK4du0aJ0+qeWIVxaQr9urpnOFYWlqybNky4uPjeeWVV9TvQlEUJQf/3L3LgYcPGQJYl6DW+ieEEMxt0ICRVasyMzKSzyMjC5WOn5+fqtgrip71qFiRnV5eJEqJf2goQXfvGjqkTDQaDYDZzY6vKIVh8iUM1RXfcFxdXfn000/ZunUra9asMXQ4iqIoRkdKyYzISGrZ2tI1790N5tq1a7Rv377YZle2EILvGzZkcOXKTL10idlXrhQ4DT8/P65cuUJUVFQxRKgoSk6alynDfm9vnG1t6XbsGMuNaBb62rVr06BBA1WxVxTMoGKvGNaECRPw8/PjjTfeKHHLjSiKouQl6N499sXE8F6tWlgbOphczJw5k927dzNz5sxiO4elEKxs1IjnK1Zk0oULfF/AYVz+/v4AqtVeUQyglp0de7y96VC2LC+fOcO0S5eMpremRqPhv//+IzEx0dChKIpBmXzFXrXYG5alpSXLly/n8ePHjB071mgyeUVRFEOTUjIjIoKatra8VK2aocPJ0bVr11i+fDmpqaksW7asWNdEtrKw4OcmTehevjxjz55lZQHO5eHhgZ2dnZpAT1EMxMnKij/d3BhZtSqfREYy9NQpElJTDR0WAQEBPHr0iH379hk6FEUxKJOv2CuG17BhQz755BO2bNnCzz//bOhwTIalpSWenp40a9aMfv368fjxY0C73rwu7dixgx49euS6T0REBPb29nh6euLp6cnYsWPTP1u7di3u7u40bdqUd955J317QkICAwYMoH79+rRq1SrTmqUrV66kQYMGNGjQgJUrV2Z7zhEjRrB+/XoA7t69i5eXF8uXLy/ClSqKcQm+f589MTFMqVULWyMeW//RjI9ISNLOeB2fFE+Hlzpw5vaZYjufjYUFG5o2pXPZsrx8+jRrb97M33E2NrRo0UK12CuKAVlbWLCkYUM+rVOHNTdv0uXIEe4mJRk0po4dO2JhYaG64xeBKpOaR5nUeEsa+SCEINUInhQqMGnSJHx9fRk/fnyxtvYYypo1a3BxccHCwgIXFxedzClgb29PeHg4x48fx8bGhkWLFukg0sKrV68e4eHhhIeHp8dy7949Jk+ezPbt2zlx4gQ3btxg+/btACxdupRy5cpx/vx5Jk2axLvvvgtoM8QZM2awf/9+Dhw4wIwZM7h3716O533w4AFdu3ZlzJgxvPTSS8V/oYqiJx9HRFDdxoaRVasaOpQcXY26ytJlS5Epab2tUuBM0BkafdGIfr/2I/RaaLGc187Sks1ubvg7OfHiqVNsvn07X8f5+fkRGhpKghEuvaUoJYUQgqm1a/NT48bsi4nBPzSUC3FxBounbNmytGzZssRU7EtqmfTOnTuqTJoHk67YAyQnJxs6BIX/zZL/6NEjXn31VbPqkr9mzRrGjBlDZGQkUkoiIyMZM2aMTicMbNu2LefPn8+0LTY2ls6dO+Pt7Y2bmxubN28GtE8yGzduzOjRo2natCldunQhLu0/1PPnzxMQEICHhwfe3t5cuHAhU5oHDx7Ey8uLixcv5iuuy5cv4+rqSqVKlQBtd7cNGzYAsHnzZoYPHw5A37592b59O1JK/vnnHzQaDeXLl6dcuXJoNBr+/vvvbNOPjY2lW7duDB48mFdffTWfd0tRjN9/9+/z34MHvFurFnaWloYOJ1tSSrqO7vrUA3IbCxu8z3kTeCGQ5oub887Rd/gv4j+d5+ulLS35w80NbwcH+p84wT/5mG3b39+fxMREQkOL54GDoij5N6hKFYI8PLiVlIRvaCghDx4YLBaNRsPBgwe5f/++wWLQh5JcJr148aIqk+bBytABFIUQgpSUFKSUaqy9EWjcuDEff/wx7777LmvXrmXgwIGGDilfJk6cSHh4eI6f79u376nWocePHzNy5EiWLFkCQHx8PHZ2dumfe3p6Mnv27HydPzk5mb/++otnnnkm03Y7Ozs2btyIo6Mjt2/fxtfXl169egFw7tw5fv75Z5YsWUL//v3ZsGEDL774IkOGDGHKlCn06dOH+Ph4UlNTuZI2+/TevXsZP348mzdvplatWk/FcenSJby8vHB0dOSTTz6hbdu2uLi4cPr0aSIiIqhZsyabNm1Kn5wmKioKZ2dnAKysrHBycuLOnTuZtgPUrFkzx1ms33zzTUaNGsWkSZPyda8UxVR8HBFBVRsbRhvx2PpPdn7CybCTkJJ5e2JiIqmXU4lcG8nCQwv5cueXdFjZAb+afkxtO5VnGzyrs/9zHa2s+NvdnU5HjvDc8eP86eZGx3Llctzfz88P0OZnT35WFMVw2pYtS4i3N92PHqXTkSOsatSIvpUr6z2OgIAAZs6cSXBwMH369NH7+XVFF2XSrIyxTHr48GE+++yzApVJ69evr8qkeTD5FntAdcc3Im+99RatWrVi3Lhx3Lhxw9Dh6EROXT6L2hU0Li4OT09PWrRoQa1atRg5cmSmz6WUTJ06FXd3dwICAoiKikq/p3Xq1MHT0xOA5s2bExERwcOHD4mKikr/D83Ozo5SpUoBcOrUKcaMGcPvv/+ebQZarVo1Ll++TFhYGN988w2DBw8mJiYGJycnFi5cyIABA9Ir+lZWVunxZSWEyHF7djp16sTmzZu5mc8xtopiCnbfv8+/9+/zjrMz9kbaWr/k8BI+3PEhwxYOIzU1FSllpldYWBhOdk5MaTOFn1v9zILuC4h+GE3Pn3visciDn479RHKqbnrMlbO2Zpu7O3Xt7Oh57Bh7c2n1q1KlCnXq1FHj7BXFiLiWKkWItzdeDg70O3mSry5f1nvPTV9fX0qXLm323fHNpUw6derUApdJy5Urp8qkeTD5FnuAlJQULI208FTSPJkl39PTk/Hjx7Nu3TpDh5SnvJ5iuri4EBkZ+dT22rVrs2PHDkDbFcnFxaVA530ynikna9as4datWxw+fBhra2tcXFyIj48HwNbWNn0/S0tL4uLicv1PtFq1asTHxxMWFkb16tWf+tzW1jY9zebNm1OvXj3Onj1LxYoV6dmzJz179gRg8eLF6X9rNWvW5MqVK9SsWZPk5GQePHhA+fLlqVmzZvp9Abh69SodOnTINq6BAwfSpk0bunfvTnBwMGXKlMnxGhTFVHwcGUlla2teyeZvzRhsPr2ZsX+MpVv9bvzQ84c8W99tLW15zec1RnuP5pfjv/DFni8Y8tsQpgVP4x3/dxjuORw7K7tc08hLJRsbgjw8aBceTrejR9nu4UELR8ds9/Xz82PHjh2qt56iGJFKNjZs9/Bg+OnTvHPxIhfj4+mrx/Pb2NjQoUMHk6/Y66JMWhj6LpPGxMQUuEzaokULVSbNg1m02Ktx9salcePGfPTRR/z6669s3LjR0OEU2aeffpr+lPGJUqVK8emnnxbreR88eEDlypWxtrYmODg424w8I0dHx/SuSaB9evtkVtOyZcvyxx9/MHXq1Gwz/lu3bpGSou2Pe/HiRc6dO0fdunUB0p9c3rt3j++++45Ro0YB0KtXr/TZRdevX0+nTp0QQtC1a1e2bdvGvXv3uHfvHtu2baNr1645xj1x4kQ6d+5Mnz591Bq0iskLefCAwHv3mOzsTCkjfOC85/IeBm4YSIvqLfi1369YW1rn+1hrS2uGegzl2KvH2DRgExVLVWTsH2OpM6cOX+/9mocJD4sUWzVbW/718KCclRVdjh7laGxstvv5+fkRHR2d3qVTURTjYG9pyS9NmvCuszOLoqN5H3ioxzK6RqPh/PnzmWZENzfmUiZdunSpKpMWA5Ou2GdssVeMy+TJk/H09OS1117LdfZJUzBkyBAWL15M7dq1EUJQu3ZtFi9ezJAhQ4r9vIcOHaJFixasWbOGRo0a5XnMqlWrmDt3Lu7u7vj7+2daoaBKlSr8/vvvvP766+zfvz/TcTt37sTd3R0PDw/69u3LokWLKF++PAATJkygSZMmtG7dmilTpuDq6grAyJEjuXPnDvXr1+ebb77hiy++AKB8+fJMmzYNHx8ffHx8+PDDD9PTysmsWbNwdnZm6NChamiNYtI+joykorU1r9aoYehQnnLi5gl6/NyDWk61+GPwH5S2KV2odCyEBb0b9WbfyH1sH7adppWaMjlwMrVn1+bD4A+5/Th/M9xnx9nOjn89PSllYUHAkSOcfvToqX38/f0BVHd8RTFCFkLwRb16fO/qykGgbVgYUXpaxSIgIACAoKAgvZzPEMylTFqpUiVVJi0OWcfVmdKrUqVKEpB3796V5iQ4ONjQIehEaGiotLS0lCNGjEjfZizXFhUVpdP0Ll26pNP0jIU5XFd2v2vgkDSCPMxYXq6urgW9rQZnLHlJRvsfPJAEB8svIiOz/dyQMV++f1nW/KamrPp1VXnp3qUCHZufuA9cPSD7/NJHMh1Z6tNScuJfE+WVB1cKF6yU8vSjR7Ly7t2y+p498vzjx5k+S0pKkqVKlZJvvPFGkWI2NqYYs8pLTT8vLU6zgoOlw86dssaePTL84cNiP19qaqqsXr267N+/f7Gfq6By+/vWdZnUFJhD+bKwirNcqrcWeyHEM0KIM0KI80KIKTns00EIES6EOCGE+C8faQKqK76x8vLy4t1332XFihX8888/hg5HURSlWM2IiKCClRWvG9nY+rtxd+m6uisxCTH8PeRvXMq66PwcPjV8+G3Ab5x47QR9m/Rl3oF51J1Tl5GbR3L2ztkCp9ewVCmCPDyIT02lU3g4l9PGcoJ2xmMfHx/VYq8oRq4lsNvLC4A2YWH8fedOsZ5PCEFAQADbt283vZZWRdEBvVTshRCWwAKgG9AEGCSEaJJln7LAd0AvKWVToF9+009KStJdsIpOTZs2jUaNGjFmzBgePiza+EtFURRjdSgmhj/v3uVNZ2ccrIxnXtq4pDh6/tyTC/cusHngZjyqehTr+ZpUasLK51Zy4Y0LvNL8FX46/hON5jei/6/9CbsWVqC03BwcCPTw4EFyMp3Cw4nO0J3Xz8+PsLCw9PWSFUUxTh4ODuxv3pz69vb0OHaMxdHRxXo+jUbDnTt3cp0ITlHMlb5a7FsC56WUF6WUicAvQO8s+wwGfpNSXgaQUua51sCTFvuiLvGgFB87OzuWLl3KlStXeO+99wwdjqIoSrH4ODKSclZWjDOisfXJqckM3DCQkCshrHl+DR1cOujt3LXL1mZe93lETIhgSpsp/HPhH7wXe9NtTTd2Ru5E2/Mwb95lyvC3uzs3kpLofOQIN9MmM/L39yc5OZnDhw8X52UoiqIDNWxt2enpSZfy5Xnl7FnevXCB1HzmAQXVuXNnAJOfHV9RCkNfzQo1gIzT114FWmXZxxWwFkLsAMoAc6SUP2ZNSAgxBhgDpC9DsGvXrjxnZzQlsbGxRVqywhj16dOHBQsW4OzsbOhQAO1snbqc7TIxMdEsZ2E1h+u6e/cuZ88WvCuwouRX2MOH/H7nDh+7uOBoJK31Ukpe3foqW85sYX63+fRtos+Fp/6nikMVPuv8Ge+2fpfvDn7Ht/u+pf2K9vg7+zO1zVS6N+ie55J1vk5ObHVzo9vRo2iOHCHY0xNfX18A9u7dS5s2bfRxKYqiFEEZKyu2NGvG+PPn+fLKFS7Fx7OyUSPsdbx6SLVq1WjWrBmBgYG8++67Ok1bUYydvkog2f2vnfVRnRXQHOgM2AMhQoh9UspMJXIp5WJgMUD16tXlw4cP8fDwwMOjeLsX6tOOHTtyXGPRVLVo0YLQ0FDmz5/PG2+8gb29vUHjiY6OznbtzMIqzDr2psAcrsvGxgZvb29Dh6GYsY8jI3GytOSNmjUNHUq6j3Z8xA9hP/B+2/d5veXrhg4HJzsn3mv7HhN9J7IsbBlf7v2SHj/3wL2KO1NaT6Ff035YWeRcJGlftiybmjWj57FjdD16lCAPD+rXr6/G2SuKCbGysOC7Bg2oZ2fH5IsXuZqQwOZmzahkY6PT82g0Gr777jvi4uIMXt5UFH3SV1f8q0DGptqaQNZBNleBv6WUj6SUt4GdQK61dQsLbfiqK77xc3BwYMmSJVy9epUZM2YYOhxFURSdOBIby6bbt5lYsyZORtJav/DgQmbunMnLni8zs+NMQ4eTib21Pa+3fJ3z48+z8rmVJKUkMfi3wTSa34jFhxeTkJzz/+ddypdnfdOmhMfG8uzRo7Ro25aQkJB8d+tXFMXwhBC8XasWvzZpQlhsLH6hoZxNW99cVzQaDQkJCezevVun6SqKsdNXxf4g0EAIUUcIYQMMBLZk2Wcz0FYIYSWEKIW2q/6p3BJVY+xNS0BAAN27d+frr79W4yIBS0tLPD09adasGf369eNx2n9sDg4OOj3Pjh076NGjR677BAYG0rx5c9zc3GjevDn//vtv+mc///wzbm5uuLu788wzz3D7tnaN6hUrVlCpUiU8PT3x9PTkhx9+SD9m5cqVNGjQgAYNGrBy5cpszzlixAjWr18PaLvLe3l5sXz58qJerqLo1cyICBwtLZlgJK31G05u4PU/X6eHaw++7/l9nt3cDcXa0pphHsM4/tpxfuv/G+Xty/PK1leoM6cOX+/9mocJ2U+22rNiRX5q3Jg9Awbwy/Ll3LhxAwsLC4QQCCHwSpuBW1EU49a3cmX+9fDgQUoKfqGh7Lp/X2dpt2vXDmtrazXOvgBUmdQ8yqR6qdhLKZOBccA/aCvr66SUJ4QQY4UQY9P2OQX8DRwFDgA/SCmP55auqtibnldffZUqVarw8ssv63SMuz5cu3aN9u3bc/36dZ2kZ29vT3h4OMePH8fGxoZFixbpJN3CqFixIr///jvHjh1j5cqVDB06FNAuJTlhwgSCg4M5evQo7u7uzJ8/P/24AQMGEB4eTnh4OKNGjQK0GeKMGTPYv38/Bw4cYMaMGdy7dy/Hcz948ICuXbsyZswYXnrppeK9UEXRoeOxsWy4fZs3ataknLW1ocPhv4j/GPzbYHxr+rK279pcu7YbCwthQZ/Gfdg/aj9BQ4NoXKkxkwMnU3t2bT4K/og7j59eHqtf5cp0at0asvSQsLGxwd/fX1+hK4pSRH5OTuzz9qaitTUBR47w840bOkm3dOnS+Pv7m3XFXpVJVZk0O3pbx15K+aeU0lVKWU9K+WnatkVSykUZ9vlKStlEStlMSjk7rzRVxd70ODg4sHDhQo4ePcqsWbMMHU6BzJw5k927dzNzpu67trZt25bz589n2hYbG0vnzp3x9vbGzc2NzZs3A9px740bN2b06NE0bdqULl26pC/5dP78eQICAvDw8MDb25sLFy5kSvPgwYN4eXlx8eLFTNu9vLzS5xxo2rQp8fHxJCQkIKVESsmjR4+QUhITE5Pn3AT//PMPGo2G8uXLU65cOTQaDX///Xe2+8bGxtKtWzcGDx7Mq6++mv8bpihGYGZkJGUsLZlkwNb6J4W74GPB9P6lN/XK1eP3Qb9TyrqUwWIqDCEEnet2Zvuw7ewftZ/2Lu35eOfH1J5dmzf/eZOomKhM+6/+/HOss0y6ZWlpybRp0/QZtqJk8ij5ESmpKYYOw6TUs7cnxNubVo6ODD51is8iI3UyvEaj0RAeHs7Nm3kusmWSVJlUlUmzY/yP83OhKvamqVevXgwcOJCZM2fy/PPP07RpU4PGM3HixDzXO01ISODAgQOkpqayaNEiwsLCsMkw2Ut8fDx2dnbp7z09PZk9e3a+zp+cnMxff/3FM888k2m7nZ0dGzduxNHRkdu3b+Pr60uvXr0AOHfuHD///DNLliyhf//+bNiwgRdffJEhQ4YwZcoU+vTpQ3x8PKmpqVy5ol2QYu/evYwfP57NmzdTq1atHOPZsGEDXl5e2NraYm1tzcKFC3Fzc6N06dI0aNCABQsWZNp3586duLq68u233+Ls7ExUVFSm1Q9q1qxJVFRUdqfizTffZNSoUUyaNClf90pRjMXJR4/49dYt3qtVi/KGaq2XkpmTJrFr1y56jO1BuRfK8feLf1OhVAXDxKMjLWu0ZOOAjZy4eYJZe2Yxd/9c5h+Yz3CP4bzT+h0aVGhAtWrVGPXyyyxcvBhSUrCxseGll16iatWqhg5fKcGi4qKoM6cOL3u9zMteL1PLKef/a5X/KW9tTaCHBy+fPs37ly5xMS6Oha6uWFsUvv1Ro9HwwQcf8O+//zJw4EAdRlu8dFEmzcoYy6SHDx/ms88+K1CZFFBl0jzorcW+OKiKvemaO3cuTk5OjBw5kpQU43+6HZnhCbKUUifLK8bFxeHp6UmLFi2oVasWI0eOzPS5lJKpU6fi7u5OQEAAUVFR3EjrplanTh08PT0BaN68ORERETx8+JCoqCj69OkDaDPhUqW0rXanTp1izJgx/P7777lmoCdOnODdd9/l+++/ByApKYmFCxcSFhZGdHQ07u7ufP755wD07NmTiIgIjh49SkBAAMOHD0+PO6ucxvl26tSJzZs3m+0TdcV8fRIZSSkLC4O11tvb2yMsLFi4di1SSh7vfUzUW1E0rNrQIPEUh6aVm/Jjnx85/8Z5RnuPZtXRVTRa0IgB6wcQfj2cnTt3Qtr/H4mJiXz33XdqnL1iUNXsq9G4UmM+/u9jXGa70H1Ndzae2khSSpKhQzN6thYWrG7cmGm1a7P0+nWePXaMB8nJhU6vefPmlC1b1iy745tDmXTq1KmqTFoMzKLF/kmXD8V0VKpUiblz5zJ48GDmzJnDm2++abBY8nqKee3aNerWrZspE7137x6//PJLeutQYZaFezKeKSdr1qzh1q1bHD58GGtra1xcXIiPjwdIf3IJ2u6ncXFxuXZdq1atGvHx8YSFheXYbenq1av06dOHH3/8kXr16gFw8uRJgPT3/fv354svvgCgQoX/tQqOHj06fb3YmjVrsmPHjkzp5rR848CBA2nTpg3du3cnODiYMmXK5HgNimIsTj96xC83b/KOszMVdbxMU35dvHiRiW9OZPO6dSSkgq2dLX1f6MvXX39tkHiKk0tZFxY8u4AP23/I7H2z+e7Qd6w7sQ7ryOx7Sly9elXPESqKVhmrMvzz4j9E3I9gaehSloUv4/l1z1PVoSoveb7ESK+R1Ctfz9BhGi0hBB/XqUMdOzvGnD1Lm7Aw/nBzo1aGHpH5ZWlpSadOnQgMDERKabQTiWalizJpYei7TBoTE1PgMumT+FSZNGcm3WL/ZLm7xzpeJkPRj4EDB9KzZ08++OCDp8byGJOZM2eSmpqaaVtKSkqxjGvK6MGDB1SuXBlra2uCg4PzfCLr6OhIzZo12bRpE6DtyfLkb6Ns2bL88ccfTJ06NVMG98T9+/d59tln+fzzz2ndunX69qpVq3Ly5Elu3boFaGcqbdy4MaD9z+WJLVu2pG/v2rUr27Zt4969e9y7d49t27bRtWvXHOOeOHEinTt3pk+fPiY3oaJSMn16+TL2Fha85eyc987FpGLliuy7tY+EVLADkhIScXR0NOuu6FUcqvB5wOdETozk006fkpySfWueKfQCU8ybS1kXZnaaSeTESLYM3IJPdR9m7ZlF/Xn1CfgxgLXH1+a6tGNJ91K1avzt7s7l+HhahYZy+GH2q2TkRaPRcOXKFc6ePavjCA3HXMqkS5cuLXCZtEaNGqpMmgeTrtg/efqmKvamSQjBwoULsba2ZvTo0U9lVMYiJCTkqT/uxMRE9u7dW6znHTJkCIcOHaJFixasWbOGRo0a5XnMqlWrmDt3Lu7u7vj7+2eaLbVKlSr8/vvvvP766+zfvz/TcfPnz+f8+fPMnDkzfamQmzdvUqVKFT766CPatWuHu7s74eHhTJ06FdAOp2jatCkeHh7MnTuXFStWAFC+fHmmTZuGj48PPj4+fPjhh5QvXz7XuGfNmoWzszNDhw412u+BogCce/yYn27c4LUaNahkoNZ6KSVjto7hctRlOvZuzT4rK8Z6eOhsdmRjV9auLFPbTsXJzsnQoShKrqwsrOjZsCdbBm3h8sTLzOw4k/N3zzNww0BqfluTt/55i9O3Txs6TKPUuVw59np7YyME7cLC+D1tWbOC0Gg0AAQFBek6PIMxlzJppUqVClwmrV69uiqT5uXJDIOm+HJ1dZWA/Oijj6Q5CQ4ONnQIxSa7a1u8eLEE5KJFi/QWR1RUlE7Tu3Tpkk7TMxbmcF3Z/a6BQ9II8jBjebm6uhb0thqcofLJ4SdPSvv//pPXExIKfKyuYn4v6D3JdORHwR9pNwQESNmokU7Szo6x/p80bNgwCTz1GjFihNHGnBtTjFnlpQXPS1NSU+Tf5/6WL6x9QVp9bCWZjmyzrI1cGb5SPk58nOfxpkQX3+no+HjZ/OBBaREcLOdduVKgY1NTU6WLi4vs3bt3keMoqtzuha7LpKbAHMqXhVWc5VKTbrEH7ZiQR48eGToMpQhGjRpFp06dmDx5shobqSiK0boQF8fqGzcYW706VQzUWj9v/zw+3/05Y7zH8FH7j7Qbe/aE06fBiIc0FYcvvvgCiyzFGEtLy/TJlBTFGFkIC7rW78r6/uu5OukqswJmcT32OsM3Dafa/1Vj/J/jOXrjqKHDNBrVbG35z8uLZytUYPz580w6f54Umb/l8IQQaDQagoODSS7CRHyKYipMvmJfqlQp1RXfxAkhWLJkCSkpKYwdOxaZzwxbURRFnz6LjMTawoLJBhpbv+7EOib8PYHnGj3Hd89+97/JoHr00P67datB4jKUivYVCajZJNO2oUOHmvU8A4p5qeJQhXdav8PZcWcJHh7Ms67PsiR0CR6LPGj1Qyt+CP2B2MRYQ4dpcKUtLdnYrBlv1KjB7KtX6XviBI/zOZeGRqMhJiaGAwcOFHOUimJ4qmKvGIW6devy6aef8scff/DTTz8ZOhxFUZRMLsXF8eONG4ypVo1qGWYA1pd/L/3L0I1DaVOrDT89/xOWFpb/+7BuXWjSBH7/Xe9xGdKVeRcZ8/41LDJMdq1a6xVTJISgg0sH1jy/hqg3o5jddTaPEh8x+vfRVPu/aoz5fQwHow6W6IYPSyGY06ABs+vXZ/Pt23QMD+dGPiY369SpE0IIsxpnryg5MfmKfenSpVXF3kyMHz8ePz8/JkyYYNJrSCqKYn4+v3wZC+CdXNbcLS5h18J47pfnaFC+AZsHbsbe2v7pnXr2hJ074cEDvcdnCMkxyVw9+y0VGt2hv4f2d1KuXDnVWq+YvAqlKjDBdwLHXj3Gnpf30LdJX1YfXU3LH1ri9b0XCw4s4H78fUOHaTATatZkY7NmHHv0CN/QUE7lMRy3QoUKeHt7m+V69oqSlclX7EuVKqXG2JsJS0tLli5dysOHD3njjTcMHY6iKAoAkfHxLL9+ndHVqlFDz631F+9dpNuabpS1K8vfL/5NOfty2e/YsyckJ8M//+g1PkO5PPM/Uvv9hOPJanyzeRe1atXi/v37PCzksliKYmyEEPg7+7O893KuvXWN77p/h4WwYNxf46j+f9UZvmk4ey7vKZGt+L0rVuQ/T0/iUlLwDwsj+N69XPfXaDTs27dP5Q+K2VMVe8WoNG7cmA8++IC1a9fyewnrVqooinH64vJlBPCunlvrbz66SdfVXUlMSeSfF/+hpmPNnHf29YUKFUpEd/yUa/e4GrsAHGJx7baKarVq8f333yOl5ODBg4YOT1F0zsnOiVd9XiX0lVAOjT7EMI9hbDy1kTbL29D0u6Z8G/Itdx7fMXSYeuXj6Mg+b2+q29jQ9ehRfsxluU+NRkNycnK2a6Yrijkx+Yp9mTJliI1VE4uYk3fffZdmzZrx6quv8sCMu5V++umnNG3aFHd3dzw9PZ9axzMnO3bsoEfaZFlbtmzhiy++KM4wFaVEuxIfz9Jr1xhZrRrOdnZ6O29sYiw9fupBVEwUWwdvpXGlxrkfYGkJ3bvDn39CPieVMklScnnAZ6T22Ur5mC441OkMgK+vL6Bd41lRzFnz6s1Z1GMR0W9Fs7TXUpzsnHhz25tU/6Y6gzYM4t9L/5IqTWzt7UJysbdnj5cXbZ2cGH76NNMvXcq2B4O/vz/29vZqnH0eVLnU9Jl8xd7R0ZGYmBhDh6HokI2NDUuXLuXatWu89957hg4HLy8vhBBPvby8vAqdZkhICFu3biU0NJSjR48SFBSEcyFm2u7VqxdTpkwpdByKouRu1uXLAEzRY2t9Ykoifdf1JfRaKGv7rsXf2T9/B/bsCXfvghlXblO+nM1lv8MgwPWZxenby5YtS5MmTdi7d68Bo1MU/XGwceBlr5cJGRnC0bFHeaX5K/x9/m86/9gZ13mufLH7C67H5tyKbS7KWlvzl7s7I6pWZUZkJMNPnyYxNfODDTs7O9q2bWsW4+yLo0wKqlxqLky+Yu/k5GTWrbolVcuWLZkwYQILFy5k165dBo3Fz88PmyxrVtvY2ODvn8/CdjauXbtGxYoVsU0br1uxYkWqV6/O9u3b8fLyws3NjZdffpmEhAQA/v77bxo1akSbNm347bff0tNZsWIF48aNA2DEiBGsX78+/TMHBwdA+yS1ffv29O/fH1dXV6ZMmcKaNWto2bIlbm5uXLhwodDXoSjmLCohgSXXrjGialVq66m1PlWmMnLLSP658A/f9/ieng175v/gLl3Aysp8u+Pv2kXE4j+RXXdQyfoV7OwyP2zx8/Nj3759JXLMsVKyuVVxY263uUS/Gc2qPquo4ViD97a/h/O3zjy/9nn+Pv83Kanm25PHxsKCZQ0b8rGLC6tu3KDr0aPcS0rKtI9Go+HUqVNcvXrVQFHqRnGUSUH/5dIBAwaocmkxsDJ0AEWlWuzN18yZM9m0aROjRo3iyJEj2BVTwXrixImEh4fn+HlCQgLJycmZtiUnJxMWFkaHDh0AiI+PzxSfp6cns2fPzjHNLl268PHHH+Pq6kpAQAADBgygVatWjBgxgu3bt+Pq6sqwYcNYuHAhY8eOZfTo0fz777/Ur1+fAQMGFPgajxw5wqlTpyhfvjx169Zl1KhRHDhwgDlz5jBv3rxcY1WUkurLy5dJBabqsbX+3cB3WX10NZ90/ISR3iMLdrCTE7Rvr13Pftas4gnQUK5dI6XfEK5OrAwJDrgGzHhqFz8/P5YuXcrZs2cNEKCiGJ69tT0vur/Ii+4vcub2GX4I/YEVR1aw8fRGajnVYqTXSF72ejn3+TpMlBCCaS4u1LGz4+UzZ/APC+NPNzfq2GtXEdFoNAAEBQUxYsQIA0aaO12USbPKq0wK+i+Xnjp1ik2bNqlyqY6ZfIu9o6MjcXFxJGV5MqeYvtKlS7N48WLOnj3LzJkzDRaHra0tVapUQQjtYslCCKpWrfrUE9OCcHBw4PDhwyxevJhKlSoxYMAAvv/+e+rUqYOrqysAw4cPZ+fOnZw+fZo6derQoEEDhBC8+OKLBT6fj48P1apVw9bWlnr16tGlSxcA3NzciIiIKPR1KMVDCPGMEOKMEOK8ECLHPm1CCB8hRIoQom+W7ZZCiDAhxNbij9Y8XUtIYPG1awyrUgUX+2yWlysG34R8w9chX/O6z+tMbTu1cIn07AknT8LFi7oNzpCSkmDAAC7WqIv0PUw127ewti7/1G5PWqzUOPuSpzjyTCGEpxBinxAiXAhxSAjRsjivQdcaVmzIV12+IurNKNb1XUfDCg35aMdH1J5dmx4/9WDz6c0kpybnnZCJebFqVQI9PLiRmIhvaCgH0hr/3NzcqFy5ssmPsy+OMinov1zq7u6uyqXFwCxa7AEePnxI+fJP/0evmLaAgABGjBjBl19+Sf/+/fHw8ND5OfLzVPDatWvUrVs3vWX+8OHDmdZLjoiIwMXFpUDntbS0pEOHDnTo0AE3NzdWrlyZ475PMvDcWFlZkZo2rkxKSWJiYvpnthmW6LKwsEh/b2Fh8dSTX8WwhBCWwAJAA1wFDgohtkgpT2az3ywgu/XNJgCnAMdiDtdsfXXlCkmpqUytXVsv5/vp2E+8te0t+jbpy5xn5uTrbz47a1JTeR+4XK8etWrX5tNPP2XIkCG6DVbfpk4lZddeor9vgLhfhXo9Jme7W8OGDSlbtix79+4tcH6smK5izDO/BGZIKf8SQnRPe99B91dQvGwsbejXtB/9mvbj4r2LLA1dyvLw5Ty39jmqOVTjZa+XGek1kjrl6hg6VJ1pX7Yse7286H7sGB3Cw1nTuDF9KlWic+fOBAUFIaUsdB5b3HRRJi0sVS41fSbfYu/k5ASgxtmbsf/7v/+jfPnyjBw50mB/7NWqVeOll17CwsKCl156qcgZ6JkzZzh37lz6+/DwcKpUqUJERATnz58HYNWqVbRv355GjRpx6dKl9DFHP//8c7Zpuri4cPjwYQA2b96serGYrpbAeSnlRSllIvAL0Dub/cYDG4CbGTcKIWoCzwI/FHeg5upGYiKLoqN5sUoV6umhtT7wQiAjNo2gfe32rOqzCksLy0Kls2bNGsZ88AGRgAQiIyMZM2YMa9as0Wm8erVhA3z9NedfG4x0PU31Uu9jZVUq210tLCzw9fVVLfYlT3HlmZL/VfSdgGhdBm0IdcvV5dPOn3J50mU2DdiEdzVvPt/9OXXn1qXLqi78euJXElMS807IBDQqXZp93t64ly7NCydO8O2VKwRoNNy4cYNjx44ZOrwi0XWZFFS51FyYTYu9GmdvvsqXL8+8efMYMGAAs2fP5u233zZIHNOmTePEiRNMmzatyGnFxsYyfvx47t+/j5WVFfXr12fx4sUMGjSIfv36kZycjI+PD2PHjsXW1pbFixfz7LPPUrFiRdq0acPx48efSnP06NH07t2bli1b0rlzZ0qXLl3kOBWDqAFcyfD+KtAq4w5CiBpAH6AT4JPl+NnAO0CZ3E4ihBgDjAGoVKmSya3vGxsbW2wxLwQSgIAbN9hx44bO0s0u5jMPzzDpyCSc7Z15u+bb7Nu9r9Dpv/XWWzx+/DjTtsePHzP59depLyVx1auDRcGf5xfnvc6N/eXLNH/1VWKbNOFam2CIciGqehOicomlatWq/PPPP9y4cUN9p0uO4sozJwL/CCG+RtsQlu3sZKaalzrhxNvV32ZY+WH8df0v/or6i/4X+1PWuixdq3Sle7Xu1CpVtPlFjOE7PQP4DHizUydIq6Bm7P1Zv359lixZUuxx5HYvHB0dM7Vm58eIESM4fPgwI0aM0EnX9bNnzzJ9+nRiYmKwtLTExcWFzz77jI4dO9K7d29SUlJwd3fnmWee4fr168ycOZMuXbpQvnx5WrRowc2bN4mIiOD27dvExMQQERFB165dGTNmDH///TetW7emVKlSREREcP36dVJTU9Pjjo+PJzo6Ov2zuLg4s+6Of/fu3eKbC0ZKabIvV1dXGRgYKAG5c+dOaS6Cg4MNHUKxKey1paamyl69ekl7e3t5/vz5IscRFRVV5DQyunTpkk7TMxbmcF3Z/a6BQ9II8rDsXkA/4IcM74cC87Ls8yvgm/bzCuD/2bvzsKiqN4Dj3zPDvoqCssmq4i4uqbhvaItptvy0bLFcMsuyXLLMNM02zazcl7TFSksrKyu1tDQ1V9xzQ0Q2BUVkH5g5vz8GCBUVZJiB4Xyehwfmzr3nvjPi5b5zznnPgwU/9wXmF/zcDfipNOds0KBBed5ii6io6+T53Fzp9Oef8tGjR03e9rUxn7x4Unq95yUDPwiU8VfKf00SQkiMvYxXfQmQEqR0dpayfXspR46UcsECKbdvlzI9vcxxm0VGhpRNmkjp6SmPfvqa3LwZefrnlbc8bMOGDRKQM2fONEOQplUV//ZXhmtpRV0zgY+ABwp+/h+w6VaxVMVraaF8fb5cf2K9HPD1AGkzzUYyFdlleRf5+YHPZZYu67barCy/03qDQbZ45BGJjc1V10Y7Ozs5atQos8Rws/fC1PekVYE13F/eroq8L63yQ/FVj331IIRg/vz52NraMmLEiMI/uopijeKA4ovH+nP9ENA2wNdCiBjgQWC+EOI+oCPQr2D710APIcQXFR2wNXn/3DmyDQZeq+C59UkZSfT5og8GaeC3R3/D19W33G0G3KB6f4C3NyxbBk89BXZ28NVX8Mwz0KEDuLlBgwbw0EPw5pvGivrnzhk/CrAUKWHECDh6lPwvPuG8+3w0p1oSdOegWx7arl07hBAcOXLEDIEqlURFXTOfAArX8foG45B/q6XVaLmr/l2sHbiWcy+e4+2ebxN/JZ7HvnsMv9l+PP/L8xw6XzWHsGuE4JdZs7DVXj3NSavVmmQUpqJUFlU+sVdz7KsPPz8/3nvvPf744w+WL19u6XAUpaLsBuoLIYKFEHbAIGBd8R2klMFSyiApZRDwLTBKSvm9lPIVKaV/wfZBwB9SyrKXq62mUnQ65sXHM6h2bcKcSp7HbQpXcq9w98q7ScpI4udHfibMM8wk7c6YMQOna+J2cnJixqxZxqT+o4/gzz8hNRXOnIHvv4epU6FZM9i3DyZPNlbVDwiAWrWgRw948UW8f/0V9u+HgvWLK9z8+fDllzB9Ov/mbgX3SwR6zUBzi2kELVu2xN3dHSklK1asQAiBEIKWLVuaJ27FUirqmpkAdC34uQdwkmrC28WbiZ0mcmL0CX5//Hf61OvDor2LaL6wORHLIvhk/ydk6jItHWaZ+Pj4MOypp9DaGGch29jYmGx+uqJUFlU+sVc99tXL8OHD6dKlC2PHjiUxMbFcbalef+tXFf+NpZT5wHMYKzcfA1ZLKY8IIUYKIUZaNjrrNjsujqwK7q3X6XXcv+p+Dp4/yLcPfUs7/3a3PqiUBg8ezOLFiwkMDEQIQWBgIIsXL76+Kr4QEBQE/fvD668bC9SdPg1pabBtG8ydCw8+CJmZsGgRDd99F1q1AhcXaN4cHnsM3n8fNm2C5GSTxQ/Azp3w4otwzz3kvvgUKXbz0O7vTsC9d97y0IiIiOuWfLKzsytaBk+xThV4zRwOvC+EOIBxmvaI8kdbtWiEhh7BPfjqga+Ifyme2b1nk5aTxtB1Q/F534eRP41kb8JeS4dZapMnT8bWxuaqx5VFVbxfUcquov+dVfE8pUrRaDQsWbKE5s2bM3r0aL799tvbasfW1paMjAxcXFwq7ZInSvlIKcnIyMDW1tbSoZSZlHI9sP6abQtvsO+QG2zfAmwxcWhW61JeHh/Hx/OQlxeNK6jwpEEaGPL9EH4/8zsr+q/grvp3mfwcgwcPvv3l7dzcoGNH41chvZ5dK1fS1t4eDhyAqCj44w/4otgMD19faNHC+BUebvxevz5oy1jdPznZOCXA3x8+/5x//xwHdjkE+k9HaG59nZ48efJ1o7nUUNvqoSKumVLKbUBrU8VY1Xk6efJixIuMaT+Gv8/9zZJ9S/jswGcs2ruIlt4tGd5qOI80ewR3B3dLh3pDhdXkFyxYgIeHR6XprVf3pNWDOe5Lq3xi7+TkhFarVYl9NdKgQQOmTp3KK6+8wnfffceAAQPK3EbNmjW5dOkS6enpJonp0qVL1/UUWYOq/rpsbW2pWbOmpcNQLCwxMZFBgwaxatWqG97IfRAXR4Zez+QK6q2XUrLg9AK+jf+Wd3q+wxPhT1TIeUxOqyUrIAC6dYOBA//bnpxsTPSLf23cCIVLkjo6QtOm/yX6LVoYe/vd3K47RWJiIoMGDmSVlHgnJ8OOHWTZpZBq9ynabf2p+1rpetwLb9qXLFlKfn4eGo0aaqsopiaEoFNAJzoFdOLDOz9k5cGVLNm3hFHrRzFu4zj+1+R/jGg1gvb+7S0daokmT57M+vXrOXv2LJcuXaoU9wimvietCqr6/eXtquj70iqf2AshcHNzU3Psq5mxY8eyatUqnn32Wbp3706NGjXKdLxWq8XLy8tk8Zw4cYJWrVqZrL3Kwlpfl1K9TJ8+nW3btjFt2jTmz59/3fOpeXl8FBfHA56eNHVxqZAYZm6fybfx3/JCuxeY0HFChZzDrLy8oFcv41eh3Fw4duy/nv0DB4zD/IsvJRUScnXPfosWTH/3XbZt28Z0KZm3bBm0bMnxDQNAb0twvSkIbel7sAp77fPz85BSo3rrFaUC1XCowbNtn2XUHaPYk7CHJfuW8NXhr1gRtYImXk3o5taN5tnNqelo+eS5kI+PDytXrqRTp0788ccfPPjgg5YOyeT3pFWBur+sGFV+jj0Yh+OrHvvqxdbWlqVLl3L+/HnGjx9v6XAURamEHB0dEUKwYMECDAYDCxYsQAiBo6PjVft9GBfHFb2eyUFBN2wrMTGRrl27kpSUVOY4PjvwGS9vepkeXj2Y3We29Q61tLc3JuxPPAEffGAcsp+SYqyy/+OPxqr7rVvD4cPGon333UdicDDLFy7EICXLtVqS7r6btLRdpNl9j3bTw/gObFamEAp77UGDrW0X1VuvKGYghOAOvztYfO9iEl5KYMm9S3C2c2be6Xn4vu/L4LWD2RKzpdLMI2/bti2urq5s3LjR0qEoikmpxF6pslq3bs3YsWNZunQpmzdvtnQ4iqJUMtHR0TzyyCPYODgAxkR/8ODBnDlzpmiftPx85sTFcZ+nJy1u0ltfvNe/LH45+QtP/fAUPYN78nLDl9EIq/izW3pCGOfM9+0LkybB6tVw4gRcuQI7djC9SxcMBdXu9Vot06ZN48SesZBag+CmE9HYlP39mjx5MjY2bdDpniQ1NdXUr0hRlJtwtXdlWKth/DPsH5a0XsKwVsP4+cTPdP+0O2Fzw3jv7/e4kHnBojHa2trSvXt3Nm3aZNE4FMXUrOIOw93dXSX21dTUqVMJDQ1l+PDhZGdnWzocRVEqER8fH9zc3NDrdGBnR05uLm5ublf14n4UF0eaXs/rN5hbX9pe/5L8E/cPD37zIM3rNGftwLXYaarffMIbcnEhMTCQ5bt2oTMYANDpdCxfvoxzaduw+flJfB+td1tN+/j40KTJZ0Ab/vnnHxMGrShKWdRzqcfcu+eSMDaBT+/7lDoudXh508v4zfbjwdUPsuH0BgzSYJHYevXqRXR0NNHR0RY5v6JUBKtI7NUc++rLycmJJUuWcPr0aaZOnWrpcBRFqWTOnz/P0BEjsJk/n/CHH75qKP2V/Hw+iIvj3lq1aOnqWuLxhb3+Gjvjn0snJ6frev1LcuLiCe758h7qONdh/eD1uNlfXzSuups+fToGw9U39fp8HZ/NdyKozWg0trd/i9KggQ0QxN9/7yxnlIqilJeTrROPt3icrU9u5eioozzf9nm2xGyhzxd9CP0olDf/epP4K/FmjSkyMhJADcdXrIrVJPaqx7766t69O8OGDeP9999n3759lg5HUZRKZO3atSxZsIAOrVohxoxh7dq1Rc/NjY8nNT+fKTeZW1/Y6y/zJNhATk7Odb3+10pMT6TPF33QCA0bHtuAt4ua512SHTt2oNPprtqWlw9H9rjh+2T5VicIDMwH7Ni8+WS52lEUxbQaeTXi/T7vE/9SPF8/8DWhHqFM3jyZgDkB9PuqHz8e/5F8Q36FxxEWFoa/v78ajq9YFatI7GvUqMHly5ctHYZiQTNnzqR27doMHTqUvLw8S4ejKEol08vDg/0ZGaQUJJLp+fm8f+4c99SsSesb9NYXOn/+PAMeGwDDoOdDPW9aQC8tJ427Vt5FcmYy6wevp17N2xtOXh3s378fKSVSSvLzs9m22Z/NCxvwx/R/0NiX7/bEx8c4NWvfvsvo9XpThKsoignZ29gzsOlANj2+iVOjT/Fyx5fZnbCbfl/3I3BOIJP/mEzM5ZgKO78Qgl69evH777+ra4RiNcyW2Ash7hRCHBdCnBJCTCzh+W5CiDQhRFTB1+ulbbtw/cfKUm1TMb8aNWowb948oqKieP/99y0djqIolUykhwcS2FzwIfD8hAQu5efz+k166wutXbuW1ctX4xHkgd/Dflf1+heXk5/Dfavu40jyEdYOXEsb3zamewFWLiFhPnnEYfPNs/gO8yt3e76+OQBkZ/tw9OjRcrenKErFCa0Zyls93yJ2TCxr/7eWFnVaMGPrDEI+DKHPF31Yc3QNOr3u1g2VUWRkJKmpqWq0p2I1zJLYCyG0wDzgLqAx8LAQonEJu26VUoYXfJW69HCtWrXQ6/Vqnn01N2DAAB544AGmTp3KiRMnLB2OoiiVSBtXV9y0WjalppKRn8+sc+e4s2ZN2rqVbu67VqOld2hvfj31a4kfIusNeh777jG2xGxhRf8V9A7tbeqXYLXy8i4Tc/pN2HUHgXcPQOuoLXebXl452NhIIIQdO3aUP0hFUSqcrdaWAY0GsH7wemLGxPB619c5mnyUB795kLof1OXljS9z8qLpptf06tULUPPsFethrh77tsApKWW0lFIHfA30N1XjtWrVAuDixYumalKpoubOnYujoyPDhw+/riiToijVl41GQ/caNdiUmsrChARS8vJuWAn/RvqE9iEpI4mD5w9etV1KyQu/vsC3R79lVuQsBjcfbMrQrd65c++il5exWT0K36d9TdKmVgtBQWBv34jt27ebpE1FUcwnwD2Aqd2mEvNCDD8/8jMd6nbg/R3v02BuA7p/2p0vD31JTn5Ouc5Ru3ZtWrRooebZK1bDxkzn8QPOFXscB7QrYb8IIcQBIAEYJ6U8cu0OQogRwAgALy8vtmzZQkJCAgAbNmygUaNGpo7d7DIyMtiyZYulw6gQ5nhtw4YNY9asWYwbN45+/fpV6LkKWeu/mbW+LqV6ct+yhegZMxh/4QIO3t5Ez5xJxODSJ+F96vUB4LfTv9HCu0XR9re3vc283fMYGzGWsR3Gmjxua5aTE8e52DmwsRcBD/VA61z+3vpCISGClJSm7Nhx3ew/RVGqCK1Gy9317+bu+neTmJ7IiqgVLN2/lMFrB1PTsSaPNX+M4a2G06R2k9tqv1evXnz88cdkZWXh5ORk4ugVxbzMldiLErZdO5ZxHxAopcwQQtwNfA/Uv+4gKRcDiwHCwsJkt27dsLe3ByAoKIhu3bqZMGzL2LJli1W8jpKY47V17dqVffv2sWzZMsaOHYufX/nna96Ktf6bWevrUqqflStXsvrllyHbWFQtJzGRESNGADC4lMm9r6svzes059dTvzKh4wQAPtn/CZP+mMTgZoN5L/K9igneisXETEHm69GuHY7vbtP01hcKDYWtW/05ceIEFy9eLBrdpyhK1eTj6sMrnV/h5U4vs/nMZhbvW8z83fP58J8PifCPYHir4fyvyf9wtnMudZuRkZG8//77/PXXX9x5550VGL2iVDxzDcWPA+oWe+yPsVe+iJTyipQyo+Dn9YCtEMKzNI17ehp3U0PxFTBWOl28eDF5eXk8++yzqqiioihMmjSJnIKkvlBWVhaTJk0qUzt1Y+qy+YXNaDQaavvVZtibw+gd2ptP+n+CRljFQjNmk5l5hKSkFfBdf+o+egc2rqbtawgJgexsR8CdnTvVevaKYi00QkPPkJ6senAV8S/FMytyFpeyL/HUuqfwne3LqJ9HsT9xf6na6ty5M3Z2dmqevWIVzHUXshuoL4QIFkLYAYOAdcV3EEJ4CyFEwc9tC2IrVaZe+Cl8SkqKKWNWqrDQ0FCmTZvGDz/8wLfffmvpcBRFsbDY2NgybS/JypUr2fTRJkgzzqtPTkhG/CQYqB+IndbOVKFWG9HRryByndCsewL/0f4mbz801Phdo6mvCugpipXycvZibIexHHv2GH8N+Yv+Yf1ZHrWcVotb0WZxGxbtWcSV3Cs3PN7JyYlOnTqpefaKVTBLYi+lzAeeA34DjgGrpZRHhBAjhRAjC3Z7EDhcMMf+I2CQLGVXa40aNdBoNKrHXrnKmDFjaN26Nc899xyXLl2ydDiKolhQQEBAmbaXZNKkSeRm5161zaAzMG1KqRdxUQpcvryVixd/RH42iLpPNcHG3fQzA0NCjN+DgnqoAnqKYuWEEHQO7MxnAz4j4aUEPrrzI3R6HSN/Honv+74M/WEoO+N2ljiKs1evXhw8eJDz589bIHJFMR2zjRuUUq6XUjaQUoZKKWcUbFsopVxY8PNcKWUTKWULKWV7KWWp/wprNBo8PDxUYq9cxcbGhmXLlnHp0iXGjlUFrRSlOpsxY8Z1hZGcnJyYMWNGqdswRa+/YhztEB09AU1GHTS//Q//F0zfWw//JfZ16nRg165d5OfnV8h5FEWpXDwcPRjdbjQHRh5g59CdDGo6iFVHVhGxLILmC5vz0T8fkZqdWrR/ZGQkgOq1V6o8q5kQWKtWLZXYK9dp0aIFEyZMYMWKFWr+lKJUY4MHD2bx4sUEBgYihCAwMJDFixeXunAemKbXX4GUlO+5cmUnhgWP4T88FNuathVyHldX8PICR8fGZGZmcvjw4Qo5j6IolZMQgnb+7VjabymJYxNZ1HcRDjYOvPDrC/jO9uWx7x6jfpP63HHHHQA8+uijCCEQQtCyZUsLR68oZacSe8XqTZ48mbCwMEaMGEFmZqalw1EUxUIGDx5MTEwMBoOBmJiYMiX1YJpe/+rOYMgnOvoVtKkhiL/uwv+liumtLxQSArm5xnOoefaKUn252rsyovUIdg/fzf6n9/NU+FOsO76OU06n4JpVNu3s7OjQoYNlAlWUclCJvVLpJCYm0rVrV5KSkkzSnoODA0uWLCEmJobJkyebpE1FUaofU/T6V3dJScvIzj6O/v2n8Hs6ADuvii06GBICCQkOeHt7q3n2iqIAEO4dzrx75pHwUgIfvPUBQnP1qtxarVbdLypVkkrslUpn+vTpbNu2jenTp5uszc6dOzNy5Eg+/PBDdu3aZbJ2FUWpXsrb61+d6fWZxMRMxfZCK8TeTtQdV/fWB5VTaCjExgrateukeuwVRbmKs50zYyLHMHLYSGxsjQU8tVotTz75JN7e3haOTlHKTiX2SqWSmJjIJ8uXYzAYWL58ucl67QHeffddfHx8GDZsGDqdzmTtKoqiKLd27twH6HRJ5M14Ct8Rvth721f4OUNCQK+Hhg0jOX36NBcuXKjwcyqKUrX89ddf5OcZi2vq9Xrmz5+v5tkrVZJVJfZZWVlkZ2dbOhTlNuUbDPSfMIHcgsrF2fn59B8/nhgT/Zu6ubmxYMECDh06xHvvvWeSNhVFUZRb0+mSOXfuPezP9UL825SACeYpOFi8Mj7Azp07zXJeRVGqji5duqDRXJ0SqXn2SlVkVYk9oHrtq6jT2dm037iR3atXQ+GSRHl57PrmG4J/+YUu+/ezOCGB1Ly8cp3n3nvvZeDAgUyfPp1jx46ZIHJFURTlVs6efRO9PovcqY/hM9QHe7+K760H41B8ABubBtja2qrh+IqiXGfy5MnY2l69OoeaZ69URSqxVyxKSsnyxETC9+zh0IIF2FzzvK2UtPvuO5Lz8nj6xAm8t2/n/sOH+S45mVyD4bbO+dFHH+Hi4sLw4cMx3GYbiqIoSulkZ0eTkLAAp+gHEbGBBLxsvuUBfX3Bzg7i4uxo2bKlKqCnKMp1fHx8eHLIk9hiTO7VPHulqrKaxN7T0xNQiX1VkqLT8eCRIzx1/DitXVyod+YM+dfMfc/T6cg9fJijd9zB3tatedbPj+1padx/5Aje27fz9PHjbL18GYOUpT5v7dq1+eCDD/j7779ZsGCBqV+WoiiKUsyZM68hsCHrtYfwHuKNQ6CD2c6t0UBwMJw+DREREezevZu8co78UhTF+owIHYHAWB1fSql665UqyWoSe9VjX7X8dukSzffs4ceLF3kvJITfw8M5cuAAUsrrvvbv348QglaursyuV4+4iAh+bd6cvrVq8cX583SJiiL0n394LTqaf0u5Tv1jjz1G7969mThxIrGxsRX8ahVFUaqn9PS9XLjwFc7Hh8CFWgS8Yr7e+kKhoRAdbUzss7OzOXjwoNljUBSl8spLzSPrvSycbJwAMBgM+Pj4IIRQRfSUKkUl9opZ5QLPnzzJnQcP4mFjw65WrRgfEIBWiFseW8hGo6FPzZp83qgR5zt04POGDQlzdOTt2Fga7d7NHXv38mFcHOdvUvleCMGiRYuQUvLMM88gy9DjryiKopROdPREbLS1yHi1L3UG18ExxNHsMYSEFPbYGwthqXn2iqIUFzMlhrxLedx9193XPaeK6ClVidUk9oVD8dVSNpXX/vR0ngY+jo/nBT8/9rRuTbir6221lZiYSNeuXclISeFRb29+bdGC+IgIZoeGYpCSMadO4bd9O3cfPMiX58+Tqddf10ZQUBAzZsxg/fr1fP311+V8dYqiKEpxly5tIDV1Ey6HnkGmOhH4aqBF4ggJgStXwNm5Ln5+fmqevaIoRTIOZRA/Px7fkb7MWjQLB4erpwqpInpKVWI1ib2dnR0eHh6cP3/e0qEo19BLyXuxsbTbt48M4LfmzZlTvz6OWu1tt/nK5FfYum0r06ZNK9rmbW/Pi3XrsrdNG47ccQcvBwRwJDOTwceOUefvv3n82DE2XLqEvljv/HPPPUe7du14/vnnSUlJKc/LVBRFUQpIaSA6+mXsbQNJe7UrtQfWxinMySKxFFbGLxyOr3rsFUUB41z6U8+fwsbdhuDpwfj4+PDAA02wKajkbGdnp4roKVWK1ST2AN7e3iqxr2TO5uTQMyqKl6Oj6VerFsuA3jVr3lZbufm5fHPkG7rP7c6nn36KNEgWLFnAHR/cwfB1w/lgxwdsOL2BuCtxNHJyYkZICGfat+fP8HAeqVOHdSkp9Dl4kLo7djD21Cn2p6ej0WhYunQpKSkpeHl5Fc2nUvOqFEVRbt+FC1+RkRGFy74xyCs2BE6yTG89/LeWfWEBvZiYGJKSkiwWj6IolUPyN8lc3nKZ4BnB2Na0JSPjIPffH4VGY5weqtFoVG+9UqVcu7rYDQkhZgOfSSmjKi6c8vH29lZ/rCuRlefPM+rECQzAioYNebxOHf78889bHpeYmMigQYNYtWoV3t7eHDp/iGX7l/HFwS+4mH0R5w3OaNGiR48GDfE/xXOmzxmW7l9a1IarnSuNvRoXfd3n1ZixTRpxMN+JLy8k83F8PLPj4mji5MSjdeoghChxnv2hQ4dM+ZYo1URVuF4qSkUxGHI5c+Y1nB3DSX2tJV4PeOLcxNli8RQm9tHR0L17BGCcZz9gwACLxaT8R10vFUvQZ+o5Pe40LuEu+A73xWDI5/jxoUycCDqd8X4wJycHHx8fAMLDw9m/f78lQ1aUWyp1Yg/YAr8JIZKBz4GVUsq4ignr9tSpU4c9e/ZYOoxqLzUvj1EnT/L1hQt0cHPj80aNCHEsfcGk6a+/zrZtWxn43ECy+2SzO2E3thpb7mt4H/f53cfQd4aizzfOmTfkG7i84zLRK6PRumo5mnyUI8lHOJp8lKPJR1l/cj3Lo5YXte1s60wjr0bcXzscnUcH/s2ryytnsuAGxfPUOvfKbar010tFqSjx8QvIyYmhzsHPyLwiCXzNcr31AE5O4O1tTOzHjm2FnZ2dSuwrF3W9VMwu9p1Ycs/l0ujLRgit4FzsB6Sn76Fjx97ExGy+allMVUBPqSpKndhLKUcLIcYAdwGDgdeEEP8AnwFrpZQZFRNi6akee8vbnJrK4//+S5JOx5vBwbxcty42mtLN+HB0dCQnJ6fo8V9r/oI1YGNnQ0JqAp5OnowaNeq6ZFuv1zN9+nTmzZtHV+eudA3qetXzF7MucizlWFGyfyT5CFtPrychvaCH38EHvFwg+fpf4ZDCrh5FKYOqcL1UlIqQn5/G2bNvUsO1FxenBFOrvzsuLVwsHVZRZXx7e3tat26tCuhVIup6qZhbdnQ2sTNjqT24NjU61SAr6yQxMa/j6XkfM2bM4+uvQ69K7FUBPaWqKNMceymlXkr5k5TyYaA94AWsAJKEEEuFEH4VEGOp1alTh4yMDDJLuZa5Yjq5BgPjT5+m54EDOGk0bG/ZkkmBgaVK6uOuxDHjrxnUfrU2NAWbgpp6tkLg5OSEPk9Pm8ZtWLlyJTt27EB3zTJ2Op3upjdptZxq0SmgEyNaj2DOnXPY+NhG4l+KJ/XlVLY/tZ2lkdN5dEr/Eo9du3Zt6d8ERSmmsl8vFaUixMa+R37+RZy2jSH/cj5Bk4MsHRLw31r2YJxnv2fPnuv+liiWo66XijmdeukUwkYQ+m4oUho4fnw4QthTv/48fH19ebJ1a+wK9rW1tVUF9JQqo0yJvRDCTQgxVAixGfgL+AfoDDQCMoBfTB9i6RX+p1MF9CpG4RJz146KOJyRQdu9e5l17hxP+/qyr00b7nBzu2lbOr2Ob49+y90r7yZwTiCvbX6N0IBQejTqgUFqsBGCPCnJyspCSsnZs2cZMWIE48aNQ0p53VdZ5j0Vvo6cyzlEeLfh0X2C0afOUTCN6iotWrRQRfSU21LZr5eKYmq5ufHExX2AV81BXJjuTs27a+La+vaWNDW1kBA4dw50OmNin5ubS1RUlKXDUgqo66ViLpd+u8TFHy4SNDkIez97EhIWk5b2J/XqvY+9vS98+imT//4bTbGOKdVbr1QVZSme9y3QB+MFdyHwvZQyt9jzLwFpJo+wDAoT+6SkJDWEugJMnz6dbdu2MW3aNObPn49BSj6Ki2NidDTuNjZ85uXF0uHDSV+1CucbfLJ5JvMM635bx+cHPyclKwU/Vz9e7fQqQ8KHEFozlPt/uJ+RI0fy3dq1JF7zAUJWVhaThg9n8ObNUKMGeHiU/L3w52vWIr32dUwfMICJjllED01C9r/ALNt2DJ75z3X7q7lVSllVheulophaTMwbSJmPw+Znyb+YT+Bky86tLy4kxFhKJSbGmNiDsYBe27ZtLRuYoq6XitkYdAZOvnASx/qO+I/xJyfnHNHRE6hRoyfe3k/B99/D0KH49OrFkyEhLFi8mDp16qjeeqXKKEvxvJ3Ac1LKEiexSykNQog6pgnr9tSpYzy9mmdvWtfOfV+wYAELFiwArRY2beLeWrVYGhbGPT06sufvPfj4+BAYGMiMGTMYPHgwaTlpfH34az6J+oRd8buw1djSv2F/ngp/it6hvdFq/lvPvnDo+4IFC0qMJTY7G375BVJTITv75oHb21+X7Cfa27P8xx8xGAws2/MPPVdJauX6UU+zjm7v3curq4M4e/bsVc2ouVXKbaj010tFMaXMzGMkJi7Dt85zJL0l8Ij0wL29u6XDKlJ8Lfs77/QjICCAHTt28MILL1g2MAXU9VIxk/iP48k+nk2zn5sh7AQnDj2DlHrCwhYjNm+GgQOhTRv47jsmp6ez7uefSU5OJicnB4cbdBYpSmVSluJ5s0qxT1b5wikfNRS/YkRHR3Pv/fezd+fOq5+wseGpw4f5cvx46hRL/AHOnj3Lo48+yoI9C9jnuY/s/Gya1m7Ks6HPMmXAFLycvW56zoCAgOsSbICAwEBjlwtAbi6kpRmT/MuX//te/Ofi25KTmXbiBAaDsaK+HsmXsxux8qd/sK9hHC76/fff07ZtWwwGiV6fD2h54okn1Ke1SplUheulophSdPQraLXO2P/+FHkXUitVbz1cveQdGHvtVQG9ykFdLxVzyE3MJeaNGGreU5Nad9fi/PkvuXTpZ0JDP8Dx8EXo3x8aNID168HFBR8XFxYtWkTfvn35+++/6dmzp6VfgqLcUll67Cs9Ly8vhBCqx97EfHx8OH748PVP5Oby+6xZREdHU69ePbKyrv+7u33FdkZ8PoKhLYfSxrcNf/755y2TeoAZM2YwYsSIq9p0cnJixowZ/+1kbw+1axu/SuHMmT0sb9iOguVJyc+H9ftiSM3JxBtjYh8eHs7Zs2cJCQkpSOxt8fFRNXsURVFuJC3tby5e/IHAutOIH5iJe1d3anSuYemwruLtDY6Oxsr4YEzsV61aRXx8PH5+6hqvKNYu+pVoDLkG6s2ph053gZMnn8fNrT3+V3rCXd3Bywt++w1q1iw6pkuXLtjY2LBx40aV2CtVQpmK51V2NjY2eHp6qh77CpCRUfJqM7Gxsfj4+JSY1AOQBgv7LuQOvzsQQpT6fIMHD2bx4sUEBgYihCAwMJDFixczePDgMscupYHYEx8z5vkI9DdYKq84Hx8fnnzySYTQAE/x9ts7Sxw9oCiKUt1JKTl9egJ2dj7YbBiELlFH0OtBlg7rOkIYe+2L99iDcZ69oijWLW1HGuc/PU/dl+riVM+JU6deQK9PJ8xlGqLPXWBrCxs3gq/vVce5uroSERHBxo0bLRS5opSNVSX2oNayryiBgSUPqwwICACM8/Bv9vztGDx4MDExMRgMBmJiYm4rqc/MPMbuLR2ITnieo/tsyc+/+vkbLZU3efJkOnbshIvLJPLzH+fpp59GSnm7L0VRFMUqXby4jitXthPo/zpxb6fg1sGNGt1rWDqsEhWuZQ/G0VkODg4qsVcUKycNkpOjT2Lna0fApABSUtZx4cLXBNYag/M9oyAzEzZs+K8QxzUiIyPZv38/KSkpZo5cUcrO6hL7OnXqqMS+AsyYMQMnJ6erthUfGr9kyZKbPm9uBoOOM6ensXtnC7LSj2K7fDJ7f0gq9VJ5Pj4+bN36J0884Qvcz2+//cPKlSvN/0KUakkIcacQ4rgQ4pQQYuJN9rtDCKEXQjxY8LiuEGKzEOKYEOKIEEJVBlMqjMGQT3T0RBwdw+C3u8k9l0vQ60FlGp1lToU99lIaVztp06aNmmdvJW73mllsu1YIsV8I8VMJx4wTQkghhGdFxK5UrMRPEsnYm0HozFCkfQYnTjyDs0NjAp74BRISjHPqmzW74fGRkZFIKfnjjz/MGLWi3B6rS+y9vb3VUPwKcKuh8aYcOl9eaWk72f13OGfPTYE/O1H7919oP38Kbm3cytzW0KGQn29DUNBrjBkzhuTk5AqIWFH+I4TQAvOAu4DGwMNCiMY32O9d4Ldim/OBsVLKRkB74NmSjlUUU0hKWkFW1r8EB87g3NsJuN7hikdvD0uHdUOhocbOucLLeEREBPv27SM3N/fmByqVWjmvmYVeAI6VcExdIBKINWXMinnkXc7jzCtncO/kTu2HaxMdPQGdLomw2TZoDv0L330HBdNybqRNmza4u7ur4fhKlWCViX1SUpIaNl0BbjU03hRD58sjPz+DkydfYP++DmQnpaB95x2atllN4w87onXW3rqBErRsafxycBhFenq6WhpJMYe2wCkpZbSUUgd8DfQvYb/RwBrgQuEGKWWilHJfwc/pGG9UVWUwxeT0+ixiYqbg5hZB/q8R5JzJIXByYKXtrYf/KuMXL6Cn0+nYt2+f5YJSTOG2r5kAQgh/4B5gaQnHfABMANRNZRUUMyWGvEt51Pu4HpcvbyYxcQl1/wnEbc1h+PJL6N37lm3Y2NjQvXt3Nm7cqHILpdKzqqr4YByKn5OTQ3p6Om5uZe+hVaqmixd/5fi/T6PLi4Xv76PGmXE0WtEGe2/7crc9dCg895wjTz/9MYsWPc3gwYO55557TBC1opTIDzhX7HEc0K74DkIIP2AA0AO4o6RGhBBBQEvgnxs8PwIYAcYVRbZs2VLOsM0rIyNDxWwmJcf9BZCALnsiVyafgHpw2OUwXLubhZQUc0qKE9CWn346Sm7uhaKb9M8//7xS9NpX1d+PSqC818w5GJN312uO6QfESykP3OwDq6p+La1IFv2dPgPMBfrC3st/Q+pT2F1yJGjKGY6/NI5ET08oZWyBgYF8//33rFy5En9//9sKR/3/vpp6PyqG1SX2heuNJyUlqcS+GtDpUjh1agwXLqyE+EB4/2PqDbkPvw/8EBrT9Bw98giMHQswlKZNP2bkyJEcPXoUV1fXWx2qKLejpF/ca7sJ5gAvSyn1Jd1wCiFcMPZMjZFSXinpJFLKxcBigLCwMNmtW7dyhGx+W7ZsQcVsHtfGrdOl8M8/31CjRj9qH/wfx+KO0WRNE7y633opU3Mp6b3OyYEhQ8DBoTHduhlHagcHB5OcnFwp/l2q6u9HJXDb10whRF/ggpRyrxCiW7HtTsAk4JZdulX9WlqRLPU7LaXkwLQDZLhn0O6TdpxNfZm4uEQaTwft9PcIGz+esDK05+fnx4cffkh6evptvx71//tq6v2oGFY5FB9QBfSsnJSS8+dXsmtXIy4krYZPH8fp/ZW0+WwI/s/7myypB/DwgAcegK+/1jJ37jLi4+N55ZVXTNa+olwjDqhb7LE/kHDNPm2Ar4UQMcCDwHwhxH0AQghbjEn9Sinl2gqPVql2YmNnoNdnEBz4FmdnnMW5qTOe91X+umIODuDn999QfDAOx9++fbsaYlu1leea2RHoV7D9a6CHEOILIBQIBg4UPOcP7BNCeFfcy1BMJXlNMpc3Xyb4zWCybfcRd24Ovj9AjbsmwvjxZW6vXr16BAQEqHn2SqVndYl9nTp1AJXYW7OcnLMcOnQ3x449iuFkHRi6CH+PybTe3h6Xpi4Vcs6hQyEtDeLi2vL8888zf/58/v777wo5l1Lt7QbqCyGChRB2wCBgXfEdpJTBUsogKWUQ8C0wSkr5vTB2RS0DjkkpZ5s7cMX6ZWefIT5+Ht7eT5L1qxdZx7IIfC3QpB+mVqTQ0P/WsgdjYp+QkMC5c+dufJBS2d32NVNK+YqU0r9g+yDgDynlo1LKQ1LK2sWOiQNaSSnVzWUlp8/Sc3rsaZxbOOM93JN//+6PfbIkRDcE3nrrttoUQhAZGckff/xB/rXrJitKJWJ1ib2fn7FOVELCtR/WKlWdlHri4j5i164mpCb/BfNHo31tAc0X9afe7HpoHW6vQF5pdOsGwcGwbBm8+eabBAQEMGzYMHJycirsnEr1JKXMB57DWLn5GLBaSnlECDFSCDHyFod3BB7D2OsUVfB1dwWHrFQjZ85MRggtQYFTOfvmWRzDHPF6sPIMwb+VwiXvCkUUVMRW69lXXeW8ZipWJvbdWHJjc6n/UX1if3yILMfzNNjdCZuPlkI5intGRkaSlpbGnj17TBitopiW1c2x9/DwwMHBgbi4OEuHophQRsZhjh8fRnr6P9ic6kD+a6Px7NCUBgcaYOdpV+Hn12jgqadg8mQ4f96FxYsX06dPH2bMmMH06dMr/PxK9SKlXA+sv2bbwhvsO6TYz9soeb6popRbevp+LlxYSUDARNJ/syfzUCYNP2+I0FadX7mQEIiPh+xscHSE5s2b4+TkxI4dOxg4cKClw1Nu0+1eM6/ZvoUblH8s6LVXKrnsM9nEvhtL7YdrY5O6nFjXH6l9xIdaM34Hbfk6f3r27AnApk2baN++vSnCVRSTM1uPvRDiTiHEcSHEKSHExJvsd4cQQi+EePA2z4O/v79K7K1AYmIiXbp0Zteul9i7txVZaSfRzJmM/oW3aPBmF5qsaWKWpL7QkCHGBH/5cujduzePP/4477zzDocOHTJbDIqiKJYSHT0RG5ua1K07gbPTzuIQ6kDtQbUtHVaZhIYav8fEGL/b2tpyxx13sH37dovFpCiKaZweexqhFQTfe47jSWOx0dlQb/AOsCv/vaKnpyctW7ZU8+yVSs0sib0QQgvMA+4CGgMPCyEa32C/dzEOp7pt/v7+xMfHl6cJpRJ47bVRbNu2jbfe+gD703eiv38ZzvH9uWP/HfgO8zX7esn+/tCnD6xYAXo9zJ49Gw8PD4YNG4ZerzdrLIqiKOZ06dImUlM3EBg4iSsbDGTszyBwUiAam6o1o69wLftrh+Pv37+f7OxsywSlKEq5Xdp4iZTvUgh8QkPKz/1ID5PUa7QAuxqBJjtHZGQkO3bsICMjw2RtKoopmesvclvglJQyWkqpw1h5tH8J+43GWM35QnlOpnrsq76DB+fxxRffIyX8+qMtCUOHEPBcc1pub4lTAyeLxfXUU8ZhnL/9BrVq1eKjjz5i165drF2rio8rimKtDERHv4y9fSC+vqOImRaDQ5ADdR6tY+nAyqwwsb+2Mn5+fj579+61TFCKopSLIc/AqedP4VBXg+fm/px5LI9aLn2oHTzUpOeJjIwkLy+PP//806TtKoqpmGuOvR9QvORsHNCu+A5CCD9gANADuONGDQkhRgAjALy8vNiyZct1++j1euLi4vjjjz/QaKpWbwJARkZGia/LGpTutf3KBx+8i8FgfKQ3SD7r+Bk1e9Uk9u/Yig7xptzdBe7uEbzzThpOTkeoU6cOERERLFu2jE6dOuHj42PR+EzNmn8XFUUprc1kZOyjYcPPSfs9i/Rd6TRY1ACNbdX7++rlBS4uV/fYF86X3bFjB506dbJQZIqi3K74j+PJ+jeLJh7vcXJiBsLBmQbNlpl8ZGenTp1wcHBg06ZN3HPPPSZtW1FMwVyJfUn/s65dNHYO8LKUUn+z/4hSysXAYoCwsDDZrVu36/Y5fPgwX331FU2aNCla/q4q2bJlCyW9Lmtwq9eWmLiM7dvf5ddfBPn5xl+RfPLZsG8DCxsuxNvb8kvIPvUUfPyxF40bd6N2bVi9ejVhYWF88sknbNiwwexTBCqSNf8uKopyawaDDliGs3MLatd+mKhpB7D3t8f7Cctfi2+HEMZe++I99rVr16ZevXqqMr6iVEG5SbnETDlDTceD5PX6k8uNdTSoPxd7ez+Tn8vBwYFOnTqpefZKpWWuj9vjgLrFHvsD165H1wb4WggRAzwIzBdC3Hc7J/P39wdQ8+yrmPj4BRw/PozP3q+NzLu6eqlery9X9fnExES6du1KUlL5l6AdOhTy8+Hzz42P/f39GTFiBJs2beKzzz4rd/uKoiiVRULCQiCR0NB3SfvzClf+vkLdl+uisa96vfWFrl3yDozD8bdv346U1/Y5KIpSmZ156V8MmToCan3A6VGCGjW64+MzrMLOFxkZyZEjR9Sy2kqlZK6/zLuB+kKIYCGEHTAIWFd8ByllsJQyqGBJkW+BUVLK72/nZIVr2at59lXH2ZNzOHlyFGyP4N+D7uSRf9XzOp2uXFWLp0+fzrZt25g2bVp5Q6VJE2jXzrimfeE94L333kunTp148cUXOX/+fLnPoSiKYmn5+Vc4e3Y60BIPj96cnX4WOx87fIZV7SlHoaHGxL54Dh8REcH58+eJKSyXryhKpXdly3mSvkrFT6zh3GfeSI2BsLAlFTpyMjIyEjAue6colY1ZEnspZT7wHMZq98eA1VLKI0KIkUKIkaY+X2GPvUrsq4YTW2ZwJv5F2NaJIPEp/6YdR0p53df+/fvL3LajoyNCCBYsWIDBYGDBggUIIXB0dCxXzEOHwrFjsHOn8bFGo2HJkiVkZmby/PPPl6ttRVGUyuDcuZnk5aUAT5P2dxqXN1+m7vi6aB3Ktx60pYWEQE4OJCb+ty0iIgJADcdXlCpCZudwsv/v2JGC8zeOXBQ7CQ5+E0fH0Ao9b4sWLfD09FSJvVIpmW0snZRyvZSygZQyVEo5o2DbQinlwhL2HSKl/PZ2z1W7dm1sbGxUYl/JGXQGoha/TAKvodnbg5a9vyfolfoIrek+aY2OjuaRRx7B1tZYSd/GxolHHhnMmTNnytXuwIHg5GTstS/UsGFDXn/9dVavXs26detufLCiKEoll5ubyLlzs/HyGgiEcXb6WWxr2+L7tK+lQyu3kpa8a9q0KS4uLiqxV5SqQK8nqctbpF/xJeDZy0TX+RxX17b4+79Q4afWaDT07NmTTZs2qak7SqVTdSfJ3YRWq8XX11fNsa/Eso5nsXPys1xu8B4OMfcQMeJn3NvWMvl5fHx8cHNzQ6/PQat1ID8/hz//TKJdu/ZoNBqCgoJYuXJlmdt1c4P//Q9WrYLiy5lOmDCBZs2a8cwzz5CWlmbCV6IoimI+MTFvIGUeISEz4Cikbkil7ti6aJ2qdm89GIfiw9WJvY2NDW3bti3XlC9FUcxASvKeep7oPS1xC8rgyqjN5OenERa2DCHMc32KjIwkMTGRI0eOmOV8ilJaVpnYg3Geveqxr4QkxC+KZ9esUejuWoh77kO0e+IHbF0dKuyU58+fZ+TIkezZs5O6dXsQH7+F2NizSCk5e/YsI0aMuK3kfuhQY1K/evV/22xtbVm2bBlJSUlMnDjRhK9CURTFPLKyjpOYuBRf35HGYa2fg01NG3yfqfq99QCBgcbq+MUr44NxOP6BAwfIzMy0TGCKotzaK69w9jPIowZeX2dx4cKXBAZOwsWlqdlCUPPslcrKahN7f39/ldhXMrpkHbwmOblnAgz+FC+3xwnv/VWFf8K6du1a5s2bR3h4C4Q4Ceivej4rK4uRIyfxwQfw889w8iTk5d263Y4dISwMFixI5IUXXiiquH/HHXcwZswYFi5cyF9//VUBr0hRFKXiREe/ilbrSGDga6TvS4edUPeluti4mmuF3IplZwd165ZcGV+v17Nnzx7LBKYoys29+y6Z764iTjxAnVFunNO/hLNzUwICXjFrGAEBAdSvX18te6dUOlaf2Kv5L5XDxV8vsrv5bghfBIO/xMd7OI1bLjfbsKlC587Flrg9IyOWl16Cvn2hQQPj/PmwMOjXD8aNg8WLYcsWSEj4r5KyEMY17ffsmc6hQ4euWo5v2rRpBAcHM3z4cHJycszwyhRFUcovLW0HKSlrqVt3AnZ2tTk7/Sy4gN9zpl8T2pIKK+MX1759e0AV0FOUSmnJEuTEiZysMx2bGnYwYiE6XSJhYcvQaOzMHk5kZCR//vknOp3O7OdWlBux6sQ+KyuLy5cvWzqUak2frefkCyc5dNdB5IiP4aFV+Po+S4OwRQhh/l+/gICAErcHBgaQkgJ//w3Ll8P48dCsGcTEwLx58PTT0L07+PmBqyu0agWDBsGhQ4nAcqSULF++vKjX3tnZmcWLF3PixAmTLLGnKIpS0aSUREdPwNa2Dv7+L5JxMIOU71PgAbBxt47e+kIhIdcPxa9VqxZhYWEqsVeUymb1anj6aVJajuHyeX/qvJ/I+dSl+Pu/iJtbW4uEFBkZSWZmprpeKJWKdf2lLqZwLfv4+Hg8PDwsHE31lHEwg6OPHCXraAbOy5aRGbIKeJD69T+u0DVGb2bGjBmMGDGCrKysom1OTk7MmDGDWrWgQwfjV3EGA8TFwYkTV3/t2QOnT08HDADo9XqmT5/OvHnzAOjVqxdPPvkk7733HgMHDqRFixbmepmKUm56vZ5Lly6RV5p5KRbg5uZGQkKCpcMok8oYs62tLTVr1kSr1XLx4k+kpW2jfv0F2Ni4cPbNI2hdtegf0N+6oSomNBTOn4fMTHB2/m97REQEP/30E1JKi/2dUhSlmN9+g0cfRd++G6fiHsKplZ6LjV7FgRCCgy3XcdK9e3c0Gg2bNm2ia9euFotDUYqz2sS++Fr2TZuar6CGAtIgifswjuiJ0WhravDYsIJUmy+pW3c8587dZdGbpcGDBwMwadIkYmNjCQgIYMaMGUXbS6LRQECA8atXr/+2JyYmEhKynJwc4zAsnU7H8uXLmTx5Mt7e3gDMmjWL9evXM3ToUHbu3ImNjdX+l1OszKVLl3BwcMDT07NSJjg6nQ5f36pVzK2yxSylJCMjg0uXLlGrlgfR0RNxdGyAj89QMo9lkvxtMgETA4h1LXkKU1VWuOTdmTNQ/BYhIiKCFStWcPr0aerVq2eZ4BRFMdq+He6/H5o0IbbLPHLfPU/tz9ZyIecULVr8gVbrZLHQ3N3dadu2LRs3brxqKqaiWJJVD8UHVAE9M8tNyOXgnQc5/dJpPO5yx+OXpaTafE5AwCRCQt4FLJ8gDB48mJiYGAwGAzExMTdN6m9m+vTpGAyGq7YV9toXqlmzJh9//DF79+5lzpw55QlbUcwqLy8PFxeXSpnUK6YhhMDFxYW8vDzOn/+MrKyjhIS8hUZjy9kZZ9E4afB/yd/SYVaIwsS+pMr4oObZK4rFHTwI99wDfn5kL17HuQ+TqfFcEheYh4/PCDw8uls6QiIjI9m9ezepqamWDkVRACtO7H18fBBCqMTejJK/S2Z3892kbUuj/sIQbN56n+TLnxEUNJXg4OlWlyDs2LHjuqIpOp3uunWQH3zwQfr378/rr7/O6WvvIhWlErO2/7PK9YQQGAz5nDnzOq6u7fD0vJ+sk1lc+OoCfs/4Yedp/qJU5lDSWvYAjRs3xs3NTSX2imJJp05B797GeTIbN3L63TSkXR66h2dgZ+dNaOh7lo4QMCb2BoOBzZs3WzoURQGsOLG3s7PD29ub2FjrG0JY2eRn5HN8+HGO3H8Eh0AHWu1tQVrnl7lw4QuCg98kKGiKVSYI+/fvR0qJlJLNmzcX/bx///6r9hNCMG/ePGxtbRkxYoRaqUFRlEolK+sYOl08oaHvIYQg9q1YNHYa6o6ra+nQKoyHB7i7X99jr9Vqadeu3XUf0CqKYibx8RAZCfn5sHEjqafcSFmTgvtH68nSHaZBg4XY2LhbOkrAuJKGi4uLWs9eqTSsNrEHCAoK4uzZs5YOw6pd2X2FvS33krgskYCJAYT/3YwY/VAuXPiakJB3CQycZOkQKwU/Pz/ee+89/vjjD5YvX27pcBSl0rt48SLh4eGEh4fj7e2Nn59f0WNTLi90+fJl5s+fb7L2qhq9PovMzEPUqtWXGjW6kB2dTdLnSfg87YNdHevsrQfjcqUhIdf32INxOP6hQ4dIT083f2CKUp1dvGjsqU9JgV9/xVAvjJPPn8SuUwJpQR9Tu/bDeHrea+koi9ja2tK1a1e1nr1SaVh1Yh8YGEhMTIylw7A6iYmJdO3Sld0Td7O/w34MuQZa/NGCoBl+HDs5kJSUNYSGziYgYIKlQ61Uhg8fTpcuXRg7diyJiYmWDkdRKrVatWoRFRVFVFQUI0eO5MUXXyx6bGdnuoSzuif2aWlbkTKP4OC3AYh9JxZhIwiYUPLSoNakpLXswZjYGwwGdu/ebf6gFKW6ysiAu+82DqNZtw7atCF+XjxZ/6ajnTIbrdaNevU+tHSU14mMjOTUqVMq31AqBatO7IOCgoiNjUWvt76leixpyoQpbN26lRnvzsDzAU/aHGiDW2dHDh9+gIsXf6BevY+pW/dFS4dZ6Wg0GpYsWUJ2djajR4+2dDiKUmpjxkC3bqb9GjOm7HH8/vvvtGzZkmbNmjFhwgRyc3MB47X+1VdfJSIigjZt2rBv3z769OlDaGgoCxcuBCAjI4OePXvSqlUrmjVrxg8//ADAxIkTOX36NOHh4YwfPx4pJePHj6dp06Y0a9aMVatW3cY7VjXk51/mypVdODrWw8WlKTmxOSStSMJnqA/2vvaWDq/ChYQYq+Jfe4vQrl07QBXQUxSzyc2F++6DvXth1Sro3h3dBR0xU2JwevU3sm32Ur/+R9jZeVk60utERkYCqF57pVKw+sQ+Pz9f9Y6aUPQ/0Xz6xadIJL/Z/kbND2qiccvn8OH7uHTpZxo0WIi//3OWDrPSatCgAVOnTmXNmjV89913lg5HUaqMnJwchgwZwqpVqzh06BD5+fksWLCg6Pm6deuyY8cOOnfuzJAhQ/j222/ZuXMnr7/+OgAODg5899137Nu3j82bNzN27FiklLzzzjuEhoYSFRXFzJkzWbt2LVFRURw4cIBNmzYxfvx4q/0bkpq6uaAyfjgAse8aa9IEvGz9vfVgTOx1OkhIuHq7h4cHjRs3Vom9ophDfj488gj8/jt88gn07w9A9CvR6N3jyOk1j5o176F27YctHGjJGjVqhK+vr5pnr1QKVr2odmBgIAAxMTFFy98pt08aJBPvn4jEWPzNIAxMmzaFp5+O5vLlPwgLW4aPz1MWjrLyGzt2LKtWreLZZ5+le/fu1KhRw9IhKcpNVYaVGvV6PcHBwTRo0ACABx54gDVr1jCmoOu/X79+ADRr1oyMjAxcXV1xdXXFwcGBy5cv4+zszKuvvspff/2FRqMhPj6e8+fPX3eebdu28fDDD6PVaqlTpw5du3Zl9+7dRe1bC50uiczMg7i5dSAnx5nc+FwSlybiPcQbhwAHS4dnFsUr49e9pk5gREQE3333HVJKqyz+qiiVgpQwYgSsXWv8Q/P44wBc2XWFpE8Ssf9mLvkaLQ0aLKy0/w+FEPTq1Yuff/4Zg8GARmPVfaZKJWfVv31BQUEAat6LieyfuZ8fEn4gjzzAuLTb8uXLiI7+g4YNV6ikvpRsbW1ZunQp58+fZ8IEVYdAUUrD2dn5ps/b2xuHjms0mqKfCx/n5+ezcuVKkpOT2bt3L1FRUdSpU4ecnJzr2qkuq1akpm5Co3HA3b0TALEzY5F6ScDE6tFbDzdeyx6Mif2lS5c4ceKEeYNSlOpCShg3DpYvhylT4IUXjJsNkpOjT6IdtIFcz+2Ehs7EwaFyd85FRkZy8eLF61ZFUhRzs+rEvrDHXlXGL7/smGymvTYNKa6+6dXrDfz4Y0+8vR+3UGRVU+vWrRk7dixLlixhy5Ytlg5HUSq9nJwcYmJiOHXqFADfffcdXbt2LfXxaWlp1K5dG1tbWzZv3lz0d8HV1fWq6uddunRh1apV6PV6kpOT+euvv2jbtq1pX4yFZWefITv7FO7undFqHdFn60lclIj3Y944hjhaOjyzqVsXtNobF9ADNc9eUSrM22/D7NkwerQxsS+Q9FkS6afPIIfPx929Kz4+wy0YZOn06tULUPPsFcuz6sTe0dGR2rVrqx77cpJScnzocY4YjpAn8656Lj8foqJSLBRZ1TZ16lRCQ0MZPnw42dnZlg5HUSo1BwcHli9fzkMPPUSzZs3QaDSMHDmy1McPHjyYPXv20KZNG1auXEnDhg0BY/X9jh070rRpU8aPH8+AAQNo3rw5LVq0oEePHrz33nt4e3tX1MsyOyklqakb0WrdcXU1fmCReSQTg85AwKvVp7cewNYWAgNLTuwbNmxIjRo1VGKvKBVhwQKYNAkefdQ4BL9gmH1+Wj6nXz6NzbS5YKMjLGwpQlT+VMXb25tmzZqpefaKxVn1HHtQa9mbQuLiRC7/cZk/F/2J15OOHDzYm4yMAzRuvAovrwGWDq/KcnJyYsmSJfTo0YOpU6fy7rvvWjokRamUpk6dWvRz4VDHmJiYoiH3xT+8HTJkCEOGDCl6XPy5GyVpX3755VWPZ86cycyZM8sXdCWVlXUEnS4BT8/70Ghs0GfpyTqeRe1BtXGq72Tp8MwuJKTkofgajYb27duzfft28welKNbsq6/g2Wfh3nuNxfKKzUmPmRZDfuON0PhPQoJm4uRUz4KBlk2vXr2YP38+2dnZODpWn5FPSuVS+T8GKye1ln355JzN4fS403j08sBziB0HDvQkI+MgTZqsUUm9CXTv3p2hQ4fy/vvvs2/fPkuHoyiKFZNST2rqH9ja1sHZuTkAV3ZcgXwInBRo4egsIySk5B57MA7HP3LkCGlpaeYNSlGs1fr1xgJ5XboYl7WztS16KvNYJnHLj6J5eS6urm3w9x9juThvQ2RkJLm5uWzdutXSoSjVmNUn9oU99gaDwdKhVDlSSo4POw5AyKKaHDjQk8zMozRt+j2envdaODrrMXPmTLy8vBg2bBj5+fmWDkdRFCuVnr6X/PxLeHj0QggN+mw9V3ZdwT7QHufGNy9OaK1CQyElBa5cuf65iIgIpJTs2rXL/IEpirXZuhUeeACaN4d166BYr7aUklPPn0KMno90uEJY2DI0mqo1qLhLly7Y2dmpefaKRVWLxF6n05W4rJFyc4lLEkndlErgB24cS7mL7OwTNGv2I7Vq3WXp0KyKh4cH8+bNY//+/bz//vuWDkdRFCtkMORy+fKfODgE4ehoHN565Z8ryFyJS3MXC0dnOYWV8UvqtW/Xrh1CCDXPXlHKa/9+6NvXWNTi11/Bze2qp1O+TyE1/Rdk998ICHwVF5fmFgr09jk7O9OhQwc1z16xKKtP7IuvZa+UXs7ZHE6PPY1bvzySmg8iJ+cMzZqtp2bNSEuHZpXuv/9+7r//fqZOncrJkyctHY6iKFYmLW07BkMmHh6RCCEw5Bi4svMKTg2dsK1pe+sGrNTNEns3NzeaNm2qEntFKY8TJ6BPH3B3h40bwcvrqqf12XpOvXoQMWEOTk6NCQx81UKBll+vXr2IioriwoULlg5FqaasPrFXa9mXnZSS48OPI2tdQDd+FLm5cTRv/iseHt0tHZpVmzt3Lvb29gwfPlxNHVEUxWTy8zO4cmUHTk5NsLf3A+DKrivIHIl7F3cLR2dZoaHG7yUV0APjcPwdO3aoa7Ki3Ab75GSILOgQ2rjRuMbkNc7NPEdun4+RNS8UDMG3N3OUphNZ8Fp///13C0eiVFdWn9irtexLb+XKlQQFBaHVaOnzey9+H/Q0efI8zZv/Ro0anS0dntXz8fFh1qxZ/PnnnyxbtszS4SiKYiXS0v5Eynw8PHoAYMg1cGXHFRwbOGLvW3Vvok3B3R1q1rx5Ab20tDT+/fdf8wamKFVdSgrNx42Dy5eNw+/Dwq7bJedsDmd//BHu+wF//zG4u7c3f5wm1Lp1azw8PNQ8e8VirD6xd3FxoVatWqrH/hbmzZvH448/ztmzZ5FIzhtSeHfORY4fH4e7ewdLh1dtDB06lO7duzN+/HgSEhIsHY6iWJSLS+nnfn///fccPXq06PGKFSvU/yEgL+8i6el7cXVtja1tLQDS96RjyDZQo0sNywZXSYSG3jyxhxsvlagoSgnS0+Guu3BISoIff4RWrUrc7dTLR5Bj3sPeJojg4OlmDtL0tFotPXr0YNOmTUgpLR2OUg1ZfWIPxuH4KrG/uYkTJ1431DA3F9588xMLRVQ9CSFYvHgxubm5PPvss+oPg6KUkkrsS5aa+jtC2FCjRlcADHkG0ran4RDqgL1/9e6tL3SjtewBGjRoQM2aNVViryillZMD/fvD/v0cnTrVuLRdCVL/SCXF7X3wi6Nhk6VotdaxMkevXr04d+4cJ06csHQoSjVUtdaSuE1BQUEcOXLE0mFUSo6OjuTk5Nzw+djYWDNGowDUq1ePadOmMWHCBNasWcODDz5o6ZCUam7Mr2OISooyaZvh3uHMuXNOmY87ffo0zz77LPHx8dSoUYMlS5Zw6dIl1q1bx59//smbb77Jww8/zJ49exg8eDCOjo7s2LGDRo0asWfPHjw9PdmzZw/jxo1jy5YtZGRkMHr0aPbs2YMQgilTpvDAAw+wYcMGpkyZQm5uLqGhoSxfvrxMIwgqg9zcOLKyjuLu3g2t1hh7+p50DJkGanStYdngKpGQEFizBvLzweaauyIhBBEREWzfvt0ywSlKVZKfD4MGwebN8MUXXPTzK3E3Q56B4zPXwbjV1PF6Cg+PnmYOtOIUzrPfuHEjYSVMP1CUilRteuzPnDmjit+UIDo6mkceeeSGzwcEBJgxGqXQiy++SKtWrXjuuedITU21dDiKUmmMGDGCjz/+mB9//JFZs2YxatQoOnToQL9+/Zg5cyZRUVG8/PLLtGnThpUrVxIVFYVjsfWSrzV9+nTc3d05dOgQBw8epEePHqSkpPDmm2+yadMm9u3bR5s2bZg9e7YZX2X5SSm5dGkjGo0z7u7G4eSGfANXtl/BIcgBhwAHC0dYeYSGGvORuLiSn4+IiODYsWPqWqwoN2MwwLBh8MMP8PHHMHjwDXeNX3CWnAemYyM8qdfAupb5DQ0NJTg4WM2zVyyiWvTYh4aGkpubS0JCAv7+/pYOp1Lx8fHB1dW1xOecnJyYMWOGmSNSAGxsbFi2bBlt2rRh3LhxqpieYlG307NeETIyMti+fTsPPfQQOp0OOzs7cnNzy9Xmpk2b+Prrr4see3h48NNPP3H06FE6duwIgE6nK5prXVVkZ58kN/csNWveXVRlOmNfBvp0PZ73e1o4usqlcMm706ehYCGdqxT+2//zzz/ceeed5gtMUaoKKeGll+DTT2HaNHjuuRvuqrugI/rgW/DoacKafIetbQ3zxWkmkZGRfPXVV+Tn52Nz7TAgRalA1aLHvl69eoBxCKdyvdhdsfSnPy/3e7loqGlgYCCLFy9m8E0+cVUqVnh4OOPHj+eTTz5RS6coCmAwGKhRowZRUVGsX7+eqKgojh07VqpjbWxsikZtFZ9+JKVECHHVvlJKIiMjiYqKIioqiqNHj1apD9ekNJCaugkbm5q4urY2bsuXpG1Lwz7AHocg1Vtf3M3Wsgdo27YtGo1GzbNXlBt580348EMYMwZee+2mu554dxPyf5/i4XA/Xl73mSU8c+vVqxfp6ens2rXL0qEo1Uy1SOxDCxaqVYn99XLO5fDK6VeY2m0qb3/3Nunp6UgpiYmJUUl9JfD6669Tv359RowYQVZWlqXDURSLcnNzIzg4mG+++QYwJuAHDhwAwNXVlfT09KJ9r30cFBTE3r17AVizZk3R9t69ezN37tyix6mpqbRv356///6bU6dOAZCVlVWlCiFlZBwkL+8CHh49EUJr3HYgA/0VPTW61rjug4zqzt8fbG1vnNi7uLjQvHlzldgrSknmzoXXX4cnnoD334ebXF/SdqeSEjIBDc40arXAjEGaV48ePRBCqOH4itlVi8Q+ICAAGxubops0xUhKyfHhx5F6SdiyMIRG3exVNo6OjixZsoTo6Ghef/11S4ejKGaVlZWFv79/0dfs2bNZuXIly5Yt46677qJJkyb88MMPAAwaNIiZM2fSsmVLTp8+zZAhQxg5ciTh4eFkZ2czZcoUXnjhBTp37oxWqy06x2uvvUZqaipNmzalRYsWbN68GS8vL1asWMHDDz9M8+bNad++fZVYxzw9PZ3lyz8hMfF37Oz8cHJqDIDUS9K2pmHnZ4dDiOqtv5ZWaxyCf7PP/iMiIti5cyd6vd5scSlKpbdyJYwebayCv3QpaG6cVkiD5OjXb0GTI9SrPwc7u9pmDNS8atWqRevWrVVir5id2SZ+CCHuBD4EtMBSKeU71zzfH5gOGIB8YIyUcpspzm1jY0NgYKDqsb9G0vIkUn9Lpf7c+jiG3Li4lGJZXbt2ZcSIEXzwwQcMGjSINm3aWDokpYLd6npZbL87gJ3AQCnlt2U5tiq4UcHTX3/9lZiYGIKKTYju2LHjVcvdhYaG8sADDxQ97ty5c4m97i4uLnz66afXbe/Rowe7d+8uR/Tm99dffxEbew5HR0n//g8U9cxnHMwg/3I+te+urXrrbyAk5MY99mBM7BcsWMDRo0dp1qyZ+QJTSqU818yC7VpgDxAvpexbsK0msAoIAmKA/0kpVQXFQj/+aOyl794dvv76+iUlrnHuyz3k9pqLc3YPfIIeN1OQlhMZGcl7773HlStXcHNzs3Q4SjVhlh77ggvmPOAuoDHwsBCi8TW7/Q60kFKGA08BS00ZQ7169VRiX0xOXA6nXjyFe1d3fJ/xtXQ4yi289957eHt7M3ToUPLy8iwdjlKBSnm9LNzvXeC3sh6rWJ/09HT279+PlJJTpwR6vbFAnjQU9Nb72OFYX32AeyOhobfusQfUcPxKqDzXzGJeAK4t2DER+F1KWR/jPepEU8Zdpf35J/zvf9CqlbEKvsPNRwLlpeVx5tKzoNHQtOsn1eIDxl69eqHX6/nzzz8tHYpSjZhrKH5b4JSUMlpKqQO+BvoX30FKmSGllAUPnQGJCYWGhnLq1Cn+O0X1JaXkxIgTyHxJw08aqiH4VYC7uzvz58/n4MGDzJw509LhKBXrltfLAqOBNcCF2zhWsTJ//fUXUhpHOEipKbqZzDycSf6lfNy7uFeLm+nbFRICly/DjVa0Cw0NxcvLSyX2lVN5rpkIIfyBe7i+Q6k/UDic51PgPhPGXHXt2wf33gvBwbB+PdxgZaXiji5/H9l8N3XdpuPoFGiGIC2vY8eOODo6quH4ilmZayi+H3Cu2OM4oN21OwkhBgBvA7UxXmSvI4QYAYwA8PLyYsuWLaUKQEpJWloa69atw93dvUzBm1tGRkapX9dt+aXg63n4J/YfiK24U12rwl+bhZjjdbm7u9O1a1emTp2Kv78/AQEBFXo+sN5/r0rultdLIYQfMADoAdxRlmOLtXHTa6mbmxs6ne62XoA56HQ6YmJiLB1GmVRUzFlZWezbtw+93pjY6/V69u/fT0hQCI6/O4IHJDskkxyTXOLxly5dumlxwKp4HShrzFlZnkBTVq/eQ1hYRon71K9fn99//73C3ouq+D5XEuW5ZgLMASYA12aodaSUiQBSykQhRImTwm/3vrQqcoqNJfz55zE4ObH/jTfIPXz4pvtnZGSw5Ys1EDoDzjXnXN1wzlnx+3Otpk2b8sMPP3D//fer/9/XUO9HxTBXYl9SN8F1XedSyu+A74QQXTDOt+9Vwj6LgcUAYWFhslu3bqUK4MqVKyxYsAAfHx/atm1bhtDNb8uWLZT2dZVVTlwOuxftxqWLC+EfhJu9t74iX5slmet1ff311zRu3JilS5eyZcsWNDcpVGMK1vrvVcmV5no5B3hZSqm/phe2VNdauPW1NCEhAV/fyjtN59o59lVBRcX8888/X7dNSsnxfccJTwvH6yEvnIOdb3i8nZ0drVq1uuHzVfE6UNaYa9Y0Fvb28GjDjQ679957eeWVV2jWrBm1atUySZzFVcX3uZK47WumEKIvcEFKuVcI0e12Tn6796VVTmwsPP442NvD1q1E1K9/y0O2bN6Cbdwc8rx0tOy2Eve6Tc0QaOUxcOBAxo0bR7169Th16pT6/12Mut5VDHMNxY8D6hZ77A8k3GhnKeVfQKgQwtNUAagl7wqG4D99ApmnhuBXVd7e3rz//vts3bqVxYsXWzocpWKU5nrZBvhaCBEDPAjMF0LcV8pjFStz7ty566q16/V6zp09h62XLU6NnCwUWdURHGz8fqsCegA7d+40Q0RKGZTnmtkR6Few/WughxDii4JjzgshfAAKvl+gurpwASIj4coV+O03KEVSD8C/f5LX8HdqXRpX7ZJ6MM6zB9i0aZOFI1GqC3P12O8G6gshgoF4YBDwSPEdhBD1gNNSSimEaAXYARdNFUBISAhAtV7yLunTJC6tv0S9j+rhGKqKKFVVQ4YM4csvv2TChAn07dsXf39/S4ekmNYtr5dSyuDCn4UQK4CfpJTfCyFsbnWsYn2efvpp4uPnYmPjirf3EAAyj2WSvCoZ987u6kPcUnB1BS+vmyf2bdq0QavVsmPHDu65p8TZgopl3PY1E/geeKVgezdgnJTy0YJd1wFPAO8UfP+h4l5CJZaWBnfeCefOwYYNEB5eqsNy0pPB90NEbBiNB02p2BgrqWbNmlG7dm02btzI8OHDLR2OUg2YpcdeSpkPPIexEukxYLWU8ogQYqQQYmTBbg8Ah4UQURirmw6UJqx05+joiJ+fX7Xtsc+Nz+XUmFO4d3bH71k/S4ejlIMQgkWLFqHX6xk1apQqCGllSnm9LNOxFR1zRZBS0qlTJ3755ZeibatXr+bOO++8bt8tW7bQt29fAFasWMFzzz1nsji2bNmCu7s7LVu2pFGjRrzxxhsma9tUdLpE8vMv4uzcHCioKfNXGjY1bXBueuMh+MrVblUZ39nZmfDwcFVAr5IpzzXzFt4BIoUQJ4HIgsfVS3Y29OsHhw7BmjXQqVOpDz20/hlwvkJ9/yVo7ewqMMjKS6PR0KtXLzZt2nTD5VsVxZTMto69lHI9sP6abQuL/fwuxmVIKkxoaGi1TOyllBx/+jhSJwn7JEz13liBkJAQpk+fztixY1m9ejUDBw60dEiKCd3qennN9iG3OrYqEkKwcOFCHnroIbp3745er2fSpEn8+uuvZo+lc+fO/PTTT2RmZhIeHk7fvn1p3bp10fP5+fnY3GIN54qUmXkQ0OLk1AiA7JPZ6BJ11Lqvlrrel0FICGzffvN9IiIiWL58ucX/zZWrleeaWWz7FmBLsccXgZ6mirHKycszLmm3dSt8+SXcdVepD036dx2ZddbAX4/i+3rnCgyy8ouMjOTLL7/kzJkzlg5FqQaq1V+l0NDQq3p/qovzn53n0s+XqDenHk711FxLa/H888/z1VdfMXr0aHr16lUhxZwUBYAxYyAqyrRthofDnDk33aVp06bce++9vPvuu2RmZvLoo48yY8YMDh06RFZWFm+99Rb9+994Nb+zZ8/y1FNPkZycjJeXF8uXL8fPz4/69etz+vRp0tLSqFmzJlu2bKFLly507tyZ5cuXU69evRLbc3Z2pnXr1pw+fZoff/yRhIQEYmJi8PT0pHfv3uzZs4e5c+cC0LdvX8aNG0e3bt1wcXHhhRdeYO3atbi7u/PDDz9Qp04dkpOTGTlyJLGxxqVJ5syZQ8eOHcv0NkppIDPzME5O9dFqHZFScvnPy9jUsMGlmUuZ2qruQkPh66+N+Yytbcn7REREMHfuXA4fPkx4KYckK0qVYzDAk0/CTz/BggUwaFCpD83PT+fEyZGQGgANHqvAIKuGwnn2e/fuZejQoRaORrF25iqeVymEhoaSlJREZmampUMxm9z4XE6+cNI4BH+0GoJvTWxsbFi2bBmpqamMHTvW0uEoSoWYMmUKX375Jb/88gs5OTn06NGD3bt389VXXzF+/PibXs+fe+45Hn/8cQ4ePMjgwYN5/vnn0Wq1NGjQgKNHj7Jt2zZat27N1q1byc3NJS4u7oZJPcDFixfZuXMnTZo0AYw3aj/88ANffvnlTV9DZmYm7du355dffqFLly4sWbIEgBdeeIEXX3yR3bt3s2bNGoYNG1bm9ycnJwa9PqNoGH7O6Rx08Trj3Hqt6q0vi5AQYz5z9uyN9yksoKeG4ytWS0p44QVYuRLeegtGlm02w7GtYzE4J+F9aTZ4V88h+MX5+/vTsGFD9uzZY+lQlGqgWvXYF96wRUdH06xZMwtHU/GuGoK/TA3Bt0bNmzfn5ZdfZsaMGTzyyCP07t3b0iEp1ugWPesVydnZmYEDB+Li4sLq1av58ccfmTVrFjqdjpycnKLe7pLs2LGDtWvXAvDYY48xYcIEwDi0/q+//uLMmTO88sorLFmyhK5du3LHHdcub220detWWrZsiUajYeLEiTRp0oRvvvmGfv364eh460KkdnZ29O3bl7Nnz9K6dWs2btwIGCslHz16tGi/K1eukJ6ejqvrtctp31hm5kGEsMfRsUFRb73WXYtLuOqtL6uCGrtER8ONPt8JCgqiTp067Nixg2eeecZ8wSmKuUydCnPnwrhxMHFimQ5NvfgXF+VStL8/RP3X7iPpn60VE2MVExkZyeLFi8nJycHBwcHS4ShWrNr12EP1qYx//nPjEPzgt4Jxqq+G4Fur1157jbCwMJ5++mkyMjIsHY6imJxGo0Gj0SClZM2aNURFRbF+/XpiY2Np1KhRqdspXL+6c+fObN26lV27dnH33Xdz+fLlouH4JencuTP79+9n7969jCzWe+Xs/F9hOhsbm6uKI+Xk5BT9bGtrW3RurVZLfn4+AAaDgR07dhAVFUVUVBTx8fFlSuoNhjwyM4/h7NwYjcaGnJgccs/l4t5R9dbfjoJbhJtWxhdC0KFDB9Vjr1inOXNg2jQYOhTeew9E6a8jen0OR3c/BefrUL/NO2gdtRUXZxUTGRlJbm6uum4oFa5aJfb1C9bdPHnypIUjqXi5CbmceuEU7p3c8X9eLYdmzRwcHFiyZAkxMTG8/vrrlg5HUSpMnz59+Pjjj4tWgti/f/9N9+/QoQNff/01ACtXrqRTQUXndu3asX37djQaDQ4ODoSHh7No0SI6d779Ik9BQUFERUVhMBg4d+4cu3btuuUxvXv3LpqTDxBVxjoG2dknkTIXZ2fjCLS0P9PQumpxaaV662+Hjw/Y29+8Mj4Yh+OfOnWKCxeq77LmihX69FN48UV44AFYtKhMST1A9LEp5DmcxmXzFOrcF1QxMVZRXbt2RaPRFI3WUpSKUq0Se3d3d+rUqcPx48ctHUqFklJy4ukTGHIMqgp+NdG5c2eeeeYZPvzww1IlFIpSFU2ePJm8vDyaN29Onz59mDx58k33/+ijj1i+fDnNmzfn888/58MPPwTA3t6eunXr0r59e8D4/yc9Pb1cU7Q6duxIcHAwzZo1Y9y4cbRq1eqWx3z00Ufs2bOH5s2b07hxYxYuLLGI9w1lZh5Eq3XFwSGInLM55MTk4NbRDY1NtfrTbjIaDQQH37zHHv6bZ79z504zRKUoZvD998Ze+l69jHPrtWXrbU9P30/8hffh17to9OJjRSOUFCM3NzcaN26sEnulwlWrOfYAYWFhVp/Yn195nos/XSR0dqgagl+NvPPOO/z4448MHTqUvXv3YldN141VrM/UqVOLfl60aBEAMTExBAUFAdCtWze6desGwJAhQxgyZAhg7EX/448/Smxz69b/5n4+8sgjPPLIIyXuV7ztG8UExiHaK1euLLGN4lNkHnzwQR588EEAPD09WbVqVYnH3Ipen01W1knc3NoihIbLf11G46zBtXXph/Ir17vVWvYArVu3xsbGhh07dtCvXz/zBKYoFeWPP2DgQGjTBr77zjhspQwMhjyO7h8Cqe74Mh3nRs63PKY6atOmDZ9++ikXL15UqxgpFabafaxv7Yl9bmIup54/hVtHNzUEv5pxc3NjwYIFHD58+IZJiqIo1iEr6xigx9m5GTlxOeSczsG9gzsa22r3Z92kQkKMPfYFsz1K5OjoSKtWrdR8WaXq270b+veHBg1g/XpwKfs0nnOxM8k2HES7Yiwhr7SogCCtQ+vWrZFSsnnzZkuHolixancHEBYWRkpKCpcuXbJ0KCZXNAQ/20DDTxqq4knVUN++fQFYs2aNhSNRFKUiZWYexMamFnZ2PqT9mYbGSYPrHaq3vrxCQiA9HS5evPl+ERER7Nq1i7y8PPMEpiimdvQo3HUXeHnBb79BzZplbiIz819izkyDLV2p98CT2LhXu4HApdawYUNcXV3VcHylQlXLxB6wyl77C19e4OKPFwmeEYxTAzUEv7rKzMzkn3/+sXQYiqJUkPz8K+TknMXFpTm6RB3ZJ7Nxi3BDY1ft/qSbXGFl/NIU0MvOzubgwYMVH5SimFpMDPTuDba2sHEj+PqWuQkpDRw/OhSZaYfztlfwftzb9HFaERsbG7p3764Se6VCVbu7AGtN7HMTczk5+iRuHdzwf0ENwa/OnJycaNu2raXDUBSlgmRmHgIkzs7NjHPrHTS4tXWzdFhWofha9jdTWEBPDcdXqpzz5yEyEjIzYcOG/z7NKqP4+PlcydwOHz9L2NsRqlBzKURGRnLmzBlO3+qTQ0W5TdUusQ8ODsbW1taqEnspJSdGqiH4iqIo1UFm5iHs7PyQF13I/jcbt/ZuaOyr3Z/zChEcbPx+q8S+bt26+Pr6qsReqVouX4Y+fSAhwTin/jZXAsnJOUv06Ymw+w7q+D+O2x3qg8XSiIyMBGDTpk0WjkSxVtXuTsDGxobQ0FCrSuwvfHWBi+suEvxmME5hagi+oiiKtdLpktHpknBxac7lvy4j7AWu7dTcelNxcjKuZ3+rDjUhBB06dFCJvVJ1ZGVB377GufXffQcFo07KSkrJ8eNPY8g1oFk0ntC3b6/Hvzpq0KAB/v7+aji+UmGqXWIP1lUZPzepYAh+hBv+Y9QQfEVRrIdWqyU8PJwmTZrQokULZs+ejcFgKFMbMTExNG3a9Jb7nTx5kr59+xIaGkrr1q3p3r07f/311+2Gflu6devGnj17brpPZuZBQGCX04CsY1m4tXND63j1mtPjx4+nSZMmjB8/vgKjtV6FlfFvJSIigjNnzpCUlFTxQSlKeeh08OCDsH27cZ363r1vu6nz5z8jNfU3WDCc4OfaY1dbLa1bWkIIIiMj+eOPP9Dr9ZYOR7FC1TaxP3XqVJX/T1U4BF+fqafhcjUEX1EU6+Lo6EhUVBRHjhxh48aNrF+/njfeeKPUx5f2Gp+Tk8M999zDiBEjOH36NHv37uXjjz8muoTsLj8/v9TnNzUpJZmZh3BwCCF9az7CVuDW/vohsIsWLWLfvn3MnDnTAlFWfWVJ7EHNs1cqOb0eHn8cfvkFFi2Chx667aZyc5M4dfJFxMnmOJ58GL9n/UwYaPUQGRlJamoq+/bts3QoihWqlutShIWFodPpiImJIfQ2i4ZUBhe+vsDFHy4SMjNEDcFXFKXCjDl5kqiMDJO2Ge7iwpz69Uu9f+3atVm8eDF33HEHU6dOJS4ujscee4zMzEwA5s6dS4cOHdiyZQtvvPEGPj4+REVFsX79+qI2oqOjeeCBB4raKbRy5UoiIiLo169f0bamTZsW9fRPnTqVhIQEYmJi8PT05MMPP2TkyJHExsYCMGfOHDp27EhmZiajR4/m0KFD5OfnM3XqVPr378+KFStYt24dFy9eJCEhgQEDBvDee++V6nUXbzMvL5tRo5oysN94Dm09zvjfx5P7be5Vr79fv35kZmbSrl07XnnlFQYOHFjq91gxCg2FL76A3Fywt7/xfq1atcLOzo4dO3YwYMAA8wWoKKUlJTz3HKxaBe++C8OHl6u5U6dGo8/LRE4fS4PlYWhsq2X/YLn07NkTgI0bN171d0hRTKHaJvZgrIxfVRP73KRcTj53Erf2btR9sa6lw1EURalwISEhGAwGLly4QK1atdi4cSMODg6cPHmShx9+uGgY+65duzh8+DDBwcHExMQAxuv9oEGDWL58OeHh4Ve1e+TIEVq1anXTc+/du5dt27bh6OjII488wosvvkinTp2IjY2lT58+HDt2jBkzZtCjRw8++eQTLl++TNu2benVqxcAUVFRfP/99zRo0ICwsDBGjx5N3bq3vnYXbzM6ehW9ej1LZI038XR3ZtPmTTh7Ol/1+tetW4eLiwtRUVFlfn8Vo5AQYz4UEwMFtwslsre3p3Xr1qrHXqm8XnsNFi6El1+GCRPK1VRy8lqSk79FfDYcz7at8OjpYaIgq5fatWvTokULNm7cyKuvvmrpcBQrU+0T+7vvvtvC0ZTNypUrefXVVzkXe47a1Oat+9+ilfbmN6SKoijlUZae9YompQQgLy+P4cOHExUVhVar5cSJE0X7tG3bluDC8uZAcnIy/fv3Z82aNTRp0uSW5xgwYAAnT56kQYMGrF27FoB+/frh6OgIGCsaHz16tGj/K1eukJ6ezoYNG1i3bh2zZs0CjEP8C3v1e/bsiZubGw4ODjRu3JizZ8+WKrEv3mZe3gV0uXB6awz1utVj5IsjS3z9SvkUft4fHX3zxB6Mw/HnzZuHTqfDzk7NNVYqkVmz4K23jL30b79drqby8lI5efJZbJIbof92EKGHq2anWGURGRnJhx9+SGZmJs7OzpYOR7Ei1TKx9/T0pGbNmlWugN7KlSsZMWIEWVlZAJznPKOnjsbe157BgwdbODpFUZSKFR0djVarpXbt2rz99tvUqVOHAwcOYDAYcHBwKNrv2hsld3d36taty99//11iYt+kSZOrCuV999137Nmzh3HjxpXYpsFgYMeOHUWJfiEpJWvWrCn68LjQP//8g32xMd1arbbUc/UL26xbV8OFCytxiLmHnG1efLLnkxu+fqV8CteyL81S0xEREcyePZuoqCjatm1bsYEpSmktWwbjxxvn0y9YAKJ8NZhOnx6LTpcMr04jaHwIjkGOtz5IKVHLli2LRlS5uLgUbQ8PD2f//v0WikqxFtV2ckxVrIw/adKkoqS+UFZWFpMmTbJQRIqiKOaRnJzMyJEjee655xBCkJ6ejo+PDxqNhs8///ymhfLs7Oz4/vvv+eyzz/jyyy+ve/6RRx7h77//Zt26dUXbrr3WFte7d2/mzp1b9LjwJq1Pnz58/PHHRaMKTHGTVthmRsYBNMKRvauTcG3lSnpO6V+/UjZ16hiXvVMF9JQqae1aGDHCWPn+iy9Aq731MTdx6dJGkpKWY7vhMezzmlJ3gpr+WR4RERHXje6xs7OjQ4cOFopIsSbVNrFv1KjRVUMpq4LCIZ2l3a4oilKVZWdnFy1316tXL3r37s2UKVMAePTRR/n0009p3749J06cuOVwRmdnZ3766Sc++OADfvjhh6uec3R05KeffmLhwoWEhIQQERHBm2++yWuvvVZiWx999BF79uyhefPmNG7cmIULFwIwefJk8vLyaN68OU2bNmXy5Mllfs333HMP/v7++Pv789BDDzF58mR0uhy6dHmO3j3nMfv3Obh3dGfUqFFlev1K6Qlh7LUvTY+9n58fdevWVYm9Ujls2gQPPwzt2hkT/HJOD8nPz+D48eHY5oaSN+th6s2ud93ymkrZTJ48GY3m6vRLq9Xe1t8LRblWtRyKD8aKx5988gkXLlygdu3alg7nlhwdHYt6ga4VEBBg5mgURVEq3s16oYODgzl48GDR47cL5pB269aNbt26FW0PCgri8OHDANSoUYPdu3eX2F7Dhg2vqqBf3NSpU6967OnpyapVq67bz9HRkUWLFl23fciQIQwZMqSokN9PP/1U4nm2bNlS4vbZs18gJcUffrsLF99QbNxtqO9ev8TXD5Bh4hUMqqPSLnkH0KFDB5XYK5b3zz9w333GwhA//wwm+LDvzJlJ5ObGon1jLjW61MZzgGf546zmfHx8ePLJJ1m4cClS5mFnZ8eTTz6Jt7e3pUNTrEC17bEvXMboyJEjFo6kdKKjo4uG/BXn6OjIjBkzLBCRoiiKYg6ZmQcRea5wvjbundwtHU61UJjY3+Dz9KtEREQQGxtLfHx8xQemKCU5fBjuugu8veG338Cj/BXr09K2Ex//MU4nHkG/qzH1P6qPKOdcfcVo8uTJaLXGFExKVG+9YjLVPrEv7Mmp7Hx8fGjRosVV21xcXFiyZIkqnKcoimKl9PpMsrNPI08E4dLCFVsPW0uHVC2EhkJWFpw/f+t91Tx7xaLOnDHOp3dwgI0bwcen3E3q9TkcPz4UO+FP1ouP4D/aH+fGarqPqfj4+NC37xBAg5fXHaq3XjGZapvYe3t7U7NmzSqT2AOcP3+eUaNGERUVxahRo4iMjFRJvaIoihXLzDwCGOB0CO6dVW+9uRRWxi/NcPzw8HAcHBxUYq+YX2Ii9OoFubnGpL7YMp/lcfbsm2Rl/YvNJxOwdXEnaGqQSdpV/vPOO1OATqSldbrhVFtFKatqO8deCEHTpk2rVGJfuJ4ywLx58ywYiaIoimIOGVcOwWUPnP39sa1Z9XvrExMTGTRoEKtWrarUvVTFE/tbFau2s7OjTZs2KrFXzCs1Ffr0MQ4r+f13KGEpz9uRnh7FuXPv4pb5P6581pSwZSHYuFfbdKHChIX5UKPGei5f/oZjx47RuHFjS4ekWIFq22MP0KxZMw4fPqw+KVMURVEqnby8VHT554y99V2so7d++vTpbNu2jWnTplk6lJsKCjJWxy9NZXwwDsffu3cvubm5FRqXogCQmQn33APHj8P33xur4JuAwZDP8eNDsdHWJHvMk7je4Yr3kMr7AVxV16SJBmjEpk2bLB2KYiWqdWLftGlTrly5QlxcnKVDURRFUZSrZFw2Vr13tGmMnWf5lq2yNEdHR4QQLFiwAIPBwIIFCxBC4OjoaOnQSuTgAH5+pa+MHxERgU6nY9++fRUbmKLk5sL99xur4H/1lXEovonExb1PRsY+3HZPJu+UA/U/ro/QqIJ5FaVlS0eEaMKGDRstHYpiJap9Yg9w6NAhC0eiKIqiXEur1RIeHk6LFi1o1aoV27dvByAmJoY+ffqY5BxDhgzBz8+vqKc1JSWFoKAgABISEnjwwQcBiIqKuuFyeAB79uzh+eefB2DFihU899xzZYpj165ddOvWjfr169OqVSvuuecedu/8BZLqMHfrCmbNmnUbr67yiI6O5pFHHsHe3gkAOzsnBg8ezJkzZywc2Y2VZck7VUBPMQu9Hh57DDZsgCVLjAm+iWRlneDMmSl4OPTn0svN8H7SG7d2biZrX7leo0YgpQubN58gLy/P0uEoVqBaJ/ZNCuYjVaV59oqiKNWFo6MjUVFRHDhwgLfffptXXnmlQs6j1Wr55JNPrtvu6+vLt99+C9w8sc/Pz6dNmzZ89NFHt3X+8+fP87///Y+33nqLkydPsm/fPl56YTgxiTHYZjdE66K9rXYrEx8fH9zc3MjLywEc0OlycHNzq9Tz7ENDSz8U39vbm6CgIJXYKxVHSnjmGfjmG3j/fXjqKRM2beD48WFotY7I90ejcdQQ8naIydpXStaokfF7VlYAO3futGwwilWo1tUwPDw88PPzU4m9oijKTZwcc5KMqAyTtukS7kL9OfVLvf+VK1fwKGFt5hUrVrBnzx7mzp0LQN++fRk3bhzdunVjw4YNTJkyhdzcXEJDQ1m+fDkuLi7XtTFmzBg++OADhg8fftX2mJgY+vbty759+3j99dfJzs5m27ZtvPLKKxw7doyEhARiYmLw9PRkxIgRzJo1i59++umqNpKTkxk5ciSxsbHodDrmz59Px44dr9pn7ty5PPHEE3QoVqWtsbeW0HqNqenQEv78s2h7VFQUI0eOJCsri9DQUD755BOSkpJ44okn2LVrV1Hc/fr14+DBg+zdu5eXXnqJjIwMPD09WbFiBT4mWA7rdpw/f56RI0eSmTmCzz5bzNmziRaJo7RCQoxFx7OywMnp1vt36NCBLVu2IKVU630rpvfKK8Ze+kmT4KWXTNp0QsIi0tK24pfzIfHfagmdHYRdnao9/acqKKyXJ0RjNm3aROfOnS0bkFLlVesee6DKVcZXFEWpLrKzswkPD6dhw4YMGzaMyZMnl/rYlJQU3nzzTTZt2sS+ffto06YNs2fPLnHfgIAAOnXqxOeff17i83Z2dkybNo2BAwcSFRXFwIEDAdi7dy8//PADX3755Q3jeOGFF3jxxRfZvXs38+fPZ9iwYdftc+TIEVq1alX0WJ+bT67Nv2guB+DoW+OqfR9//HHeffddDh48SLNmzXjjjTdo1KgROp2O6IJx46tWreJ///sfeXl5jB49mm+//Za9e/fy1FNPMWnSpJu+bxVp7dq1zJs3j7FjWyDlPO66a+2tD7Kgwsr4pZ0tEBERQUJCAufOnau4oJTq6d13jV/PPAPTp5u06ZycWKKjJ1DDvRcpz92BUyMn/J7zM+k5lJLVrg0eHuDp2ZWNG9U8e6X8qnWPPRgT+7lz56LX69Fqq/5wR0VRFFMrS8+6KRUOxQfj3OXHH3+81B/E7ty5k6NHjxb1jut0uqJ50CV59dVX6devH/fcc0+p4+vXr98ti79t2rSJo0ePFsVw5coV0tPTcXV1veExbVu3Ii0nkV5dIln4yZCi7WlpaVy+fJmuXbsC8MQTT/DQQw8B8L///Y/Vq1czceJEVq1axapVqzh+/DiHDx8mMjISAL1eb7He+uKaNYMWLeDzz6GMpQjMKjTU+D06unQriRWfZx8QEFCBkSmVlTY7Gy5ehFq1TNfokiUwcSI8/DDMnWtcrsFEpJScODESKSUum6dw+XQuzTc0R2Nb7fv9zEII43D8uLiW7Nq1i7S0NNzdrWMFFMUyzPY/VwhxpxDiuBDilBBiYgnPDxZCHCz42i6EaGGOuJo2bUpubi6nSzuRTlEURTG7iIgIUlJSSE5Ovmq7jY0NBoOh6HFOTg5gvGGNjIwkKiqKqKgojh49yrJly27Yfr169QgPD2f16tWljsnZ2fmW+xgMBnbs2FE0Rz8+Pv66pL5JkyZF1dQNOgNrPnqFl17oRba+9J+9Dxw4kNWrV3PixAmEENSvXx8pJU2aNCl6Dw4dOsSGDRtK3WZFeuwx2LXLuFpXZVV8LfvSaN68OY6OjmqefTXmdO4ceHqClxd06gTDhsHMmfDjj3DiBJSyQFpiYiJdu3YlafFiePppuPtu+PRT0Jj2tv38+ZVcuvQLdWu+QcJkA54DPKkZWdOk51BurlEjuHLFD71ez+bNmy0djlLFmSWxF0JogXnAXUBj4GEhRONrdjsDdJVSNgemA4vNEVthZfyDBw+a43SKoijKbfj333/R6/XUuqYnLCgoiKioKAwGA+fOnSuaZ96+fXv+/vtvTp06BUBWVhYnTpy46TkmTZp0w+rzrq6upKenlznu3r17F83/B4pGIBT37LPPsmLFCrZv30763svgd4Z8nSdCXP0n2t3dHQ8PD7Zu3QrA559/XtR7HxoailarZfr06UVTBcLCwkhOTi5KNPPy8jhy5EiZX0NFePhhY47yxReWjuTGPD3B1bX0BfRsbW1p27atSuyrsWw/P5g1CwYMMP6C//gjTJgA/fpBWJixWEOjRnDffcZe+OXLYccOuHTpqnamT5/Otq1bmT5yJHTsaCyYZ2tr0lh1uvOcOvUCbm4RZL3dGwwQOjvUpOdQbq1xY7h82Q5HR3+1nr1SbuYait8WOCWljAYQQnwN9AeOFu4gpdxebP+dgL85AmvatCk2Njbs27evaFkjRVEUxfIK59iDsQf+008/vW7KVMeOHQkODqZZs2Y0bdq0aK66l5cXK1as4OGHHy5ayu7NN9+kQYMGNzxfkyZNaNWqVYlrkXfv3p133nmH8PDwMlXn/+ijj3j22Wdp3rw52dnZ9OzZk4ULF161j7e3N6tWreLlCS9z9sRpavkJvL0b8MYb717X3qefflpUPC8kJITly5cXPTdw4EDGjx9ftIScnZ0d3377Lc8//zxpaWnk5+czZsyYohVhLMnXF3r2NCb206aZdHSxyQhRtiXvwDiyZNasWWRnZ99ymoZiffKdnWHs2Ks3pqYah6YcPw7//vvf9/Xrr+7B9/SEhg1JrFuX5d98g0FKlgvB5KVL8S5N9cYyOnnyefT6DHzTP+DfLy8S+HogjkHqd9bcCivjN28+kI0bf7RsMEqVJ6SUFX8SIR4E7pRSDit4/BjQTkpZ4uw6IcQ4oGHh/tc8NwIYAeDl5dW6LMMmb2TYsGHUrFmT9957r9xtmUJGRkaJlZutgbW+NvW6qpbu3bvvlVK2sXQclUVYWJg8fs2Y6ISEBHx9fS0U0a3FxMQUrTdfVdwq5iv/XOFS9lo0QcnUDRx7XY99RbnVv/WWLVvo1q2byc/7+efw+OOwdatx1LIpmSrm++835mBHj956X4B169bRv39/tm7dSqcyvqiKep8rkhBCXUuLKelaekP5+RATc3Wyf/w4o3bvZllODjqMH84NGzaMefPmmTTO5OTvOXJkAEGB00m+rw/5l/Npe6wtWifT1pqqir/TFeVG70VMDAQHw0MPbeKbbyI5e/ZstajRoX43rmaqa6m5euxL+iy+xE8UhBDdgaFAiX8RpZSLKRimHxYWJk3xS9GlSxd++uknunbtWimWqLHmX3ZrfW3qdSmKUh4yX3L5n2S45xzOrq3NltRb0oABxpHJn39u+sTeVEJDjR2rBkPppje3b98eMBbQK2tir1QzNjZQr57xq29fwDi3fnlICLqCXXQ6HcuXL2fy5Ml4e3ub5LR5eZc5eXIUzs4tsPnlUTIPxtD4m8YmT+qV55LqyQAATxtJREFU0gkIMF4H7e3DAdi4cSNDhw61bFBKlWWuO4c4oG6xx/5AwrU7CSGaA0uB/lLKi2aKjVatWpGcnEx8fLy5TqkoiqIoRTKiMjDUjAatHheX5pYOxyxcXIw94qtXQ0HNw0onJARyc43r2ZdG7dq1CQ0NVfPsldsyffr0q4qBgnE1i+kmXOLu9Olx6HQXqOezmJjX4qjRowZeD3iZrH2lbDQaY/mF5ORaeHt7q3n2SrmYK7HfDdQXQgQLIeyAQcC64jsIIQKAtcBjUsqbVzgysdatWwOUOK9SURRFUSqS1Esub7uMaBSDjU1N7OyqzxrSjz0Gly/Dzz9bOpKSlbUyPkCHDh3YsWMH5pjqqFiXHTt2oNPprtqm0+nYvn37DY4om9TU30lKWkbduuNInlGD/Cv51P+ofqUYrVqdNW4Mx44JevXqxaZNm677cEdRSsssib2UMh94DvgNOAasllIeEUKMFEKMLNjtdaAWMF8IESWE2GOO2MC4RI1Go1GJvaIoimJ2GQcz0OemI2sm4OzcrFrdZPfsCd7elbc6fuFa9mVZETciIoKkpCRiYmIqJCbFeu3fvx8p5XVf+/fvL3fben0mx48Px9GxPp5pL5GwKAG/5/xwbnLrZTuVitWoEcTGQufOd5GSksKBAwcsHZJSRZlrjj1SyvXA+mu2LSz28zDgumJ55uDs7EzDhg3Zu3evJU6vKIqiVFPSIEn7Kw1ti3PohcTFpZmlQzIrrRYeeQQ+/hguXoRrVjO0uIAA41DZslbGB2Pva3BwcAVFpihlc+bMa+TknKFFiy1E94vH1tOWoKlBlg5L4b/K+HXrRgLGefYtW7a0YERKVWX91XlK6UZLHCmKopibEOJOIcRxIcQpIcTEEp7vL4Q4WDi6SQjRqdhzLwohjgghDgshvhJCOJg3eqUsMg9lkp+aj2hwBjs7X2xtPS0dktk99phx1S8TLHJjcnZ2ULdu2RL7pk2b4uzsrObZm9GtrpnF9rtDCKEvWK0JIYSDEGKXEOJAwXXzjWv2H13Q7hEhROVYOuk2pKXtJC7uQ3x9R6H7pSFp29IIeTsE2xq2lg5N4b/EPiXFiyZNmqh59sptU4l9gVatWpGQkEBSUpKlQ1EUpRoTQmiBecBdQGPgYSFE42t2+x1oIaUMB57CWHQUIYQf8DzQRkrZFNBirGlS5bz44ovMmTOn6HGfPn0YNuy/QV1vvvkms2fPZsuWLfQtqCh9rWHDhnG0YJ2yt956q8wxdOvWjbCwMFq0aEHHjh0p9TJWpSQNkstbL2MTkkW+Jgln5+rVW1+oRQto2tRYHb8yCg0t21B8Gxsb2rVrpxJ7MynlNbNwv3cxTgstlAv0kFK2AMKBO4UQ7Qv27w70B5pLKZsAsyrydVQUgyGX48eHYm/vT0Cd6ZwefxrXNq54P2maKvtK+dWrZ1wk4dgx6NWrF1u3biWnslYUVSo1ldgXKCygZ4p5TIqiKOXQFjglpYyWUuqArzHeXBaRUmbI/ypzOXP18qE2gKMQwgZwooQVSKqCDh06FBWMMhgMpKSkcOTIkaLn9+3bR8eOHW/axtKlS2nc2Hh/fzuJPcDKlSs5cOAATzzxBOPHj7+tNm4k82gm+Sn52LWPQ6+XODs3NWn7VYUQxl77HTvg1ClLR3O9kJCy9diDcTh+VFQUmZmZFROUUtwtr5kFRgNrgAuFG6RRRsFD24KvwuvpM8A7Usrcgn0vUAWdPfsWWVlHadBgEQnvXEaXoKPex/UQmupTy6Oys7WF+vWNiX1kZCQ5OTls27bN0mEpVZDZ5thXduHh4YDxZvGuu+6ybDCKolRnfsC5Yo/jgHbX7iSEGAC8DdQG7gGQUsYLIWYBsUA2sEFKuaGkkwghRgAjALy8vNiyZctVz7u5uRVVZ754cRo63dFyvahr2dk1plat12/4fEBAAFu3biUmJoZ///2XoKAgLly4wIEDB3BwcODUqVN4eHhw5swZUlJSuOuuuzhx4gTNmjXjgw8+QAjBoEGDePXVV/nll1/Izs6mcePGNGjQgDlz5vDdd9+xYsUK8vLyCA8PZ/r06Wi1V6/jnJOTQ0JCAjExMYSGhnLs2DG2bdvGiy++SHZ2NgBvvPEGrVu3ZufOncyePRsPDw+io6Np27Yt06dPR6PR8NdffzFnzhxyc3MJDAxk5syZODs506lLJ/7X7iG2/vQ9jz/Rk3vvvQiYbaXXIpcuXeLEiRsvRpORkXHd74epxcVtAZZTv/456tSpzbBhw+jVq9dtt2famAO4cCGE9eu34uSkL9URzs7O6PV6lixZUnR/cSvmeJ+t1C2vmQWjmQYAPYA7rnlOC+wF6gHzpJT/FDzVAOgshJgB5ADjpJS7rz35ra6llnUamAFEcugXR5gVC31gf85+2FLxZ1e/0/+51Xvh6dmEvXudGTFCg42NDcuWLcPGxnrTNPW7UTGs9zemjNzc3Khfv74qoKcoiqWV1I1y3bpZUsrvgO+EEF2A6UAvIYQHxp6qYOAy8I0Q4lEp5XU1x6WUi4HFAGFhYbJbt25XPZ+QkICvry8AeXluZGSYdqq+i4sbQUFBN3w+KCgIe3t7NBoNZ8+eJTIykvj4eOLj43F3d6dhw4Y0aNCAhIQEjh07xpEjR/D19aVjx47Ex8fTqVMnHBwc8PX1ZcGCBXz++edFw/KPHTvGH3/8wZ49e7C1tWXUqFH8/fffPP7441fFUHh8UFAQ33zzDa1ataJVq1Zs3boVBwcHTp48ycMPP8yePXuIiYnh4MGDHD16lMDAQO6880727dtHt27dWLp0KVu3biU5OZlVq1axZs0axj44Fgzg3tiWb0Y/Qa1a/XF1vfH7UZHs7Oxo1arVDZ/fsmUL1/5+mNLKlStZtmwmkAXA+fPn+eCDD2jUqBGDBw++rTZNGfOFC7B0Kfj7d6Z589Id06xZM1599VVycnJKHUdFv89WrDTXzDnAy1JK/bWrTkgp9UC4EKIGxmtqUynlYYz3yB5Ae4wfBqwWQoQUGy1VePxNr6WWYjDks3//eHJyatK27VccGxBPmmMabVe0xd7b3iwxqN/p/9zqvejSBbZvh54976JDhw6cOHHCqt879btRMVRiX0zr1q3V0BdFUSwtDqhb7LE/NxlOL6X8SwgR+v/27js8qjJt/Pj3mUlPSEKAQCBAQkgg1ABSEkGpAjbEsoCsK4iwWFB0dW2vhUUs77r76qLADwuyytpgQWQtgFI3oROqlEACJEQ6gfT2/P6YSUhIm7Q5M8n9ua5czJw29zmcec655ylHKdUcGAIkaq3PASil/g3EALV6mFh4+Lu1Wb3GbrzxRmJjY4mNjeXpp58mJSWF2NhY/Pz8irtPAfTr14/g4GDA0voqKSmJgQMHVrRZfv75Z3bu3EnfvpaKu6ysLAIDA8tdduLEiXh6ehISEsLcuXPJy8vj8ccfJz4+HrPZXKqmu1+/fnSwPvh8woQJbN68GQ8PDw4ePMiNN95Y3AJiwIABpG1MQ5kVYx7oAiTj7R1Zq2PlzF566SUyMzNLTcvMzOSFF16qcWJfl0o+y97WxL5Zs2ZERERIP3v7sKXMvAH40prUNwduVUrla61XFC2gtb6slFoPjAL2W7f7b2siv00pVWhd91w97UedSk5+l6tXd9Cly1dcWQ0X/3ORsHfC7JbUi+qJjISCAjh61NLP/tVXX+X8+fM0b974BlQVNSd97EsYMGAAycnJpKSkGB2KEKLx2g6EK6VClVJuWAa/W1lyAaVUR2W9Q1VK9QbcsLThPgkMUEp5WecPA361a/R1qKif/b59++jWrRsDBgwgLi6O2NjYUom9u/u1G1Wz2Ux+fn6l29Va8+CDDxIfH098fDyHDx/mtddeK3fZJUuWEB8fz4oVK2jbti3/93//R8uWLdmzZw87duwoTtaBMs+fV0qhtWbEiBHEx8fz/fffc/DgQd5/7n1yf8vF5G4CkvDyisBkarwPLzh58mS500+dOsnMmcb3uy9K7KszgB5Yzt+4uDiuq+AVda/KMlNrHaq1DtFahwBLgUe11iuUUi2sNfUopTyB4cAh62orsDTdRykVgaWcPV//u1N7mZlHSUp6mWbNxtDM9x4SZibg1dmLNjPaGB2aqIB1OJjifvZaa37++WdjgxJORxL7EgYMGADA1q1bq1hSCCHqh9Y6H3gcy8jNvwJfa60PKKWmK6WmWxe7B9ivlIrHMhr0OOsgUFux3LTuAvZhKeMX2nsf6sqNN97IqlWrCAgIwGw2ExAQwOXLl4mLi6u06Xh5XF1dycvLA2DYsGEsXbqUs2ctY2FdvHiREydO2LSdtLQ0goKCMJlMfPbZZxQUXOtzvW3bNhITEyksLOSrr75i4MCBDBgwgP/+978kWLPTjIwMdn69E5emLuBaQGFhZqMdDb9Iu3btyp3u5dWOefMgIgJuuw1++gkKC+0cHBAQAP7+NRtA79y5cxyr7i8ColpsLDMrEgSsU0rtxfIDwRqt9SrrvE+ADkqp/VgG5Hvw+mb4jkjrQg4fnopS7kREzCP53WSyErLo+F5HTG5y2++oOnWyDCR68CDccMMN+Pn5sWbNGqPDEk5GvuElREVF4ebmJom9EMJQWuvvtdYRWuswrfUc67QFWusF1tdva627aq2jtNbRWuvNJdZ9VWvdWWvdTWv9QNGIzs6oe/funD9/vvhH16Jpfn5+BAQEVGtb06ZNo0ePHkycOJEuXbrw+uuvc8stt9CjRw9GjBhBamqqTdt59NFHWbx4MQMGDODIkSN4e3sXz4uOjub555+nW7duhIaGMnbsWFq0aMGnn37KhAkTGDVqFP379OfQwUP4DfJD61yUcsfTM7xa+9LQzJkzBy8vr1LTvLy8WLhwDidPwquvws6dMGqUpVbr/ffh6lX7xljTkfEBaY5vB1WVmdctO0lrvdT6eq/WupfWuoe1zPxLieVytda/t07vrbX+xX57VHOpqR+SlraBjh3/BuebceL1EzS/qzkBt1SvzBT25eUF7dtbauxdXFwYOnQoa9askRY/olqkj30J7u7u9OrViy1bthgdihBCNHpms5krV66Umvbpp58CkJSUBFieNV9yAJ7333+/+HXJEXfffvtt3n777eL348aNY9y4cZV+fnkj9oaHh7N3797i92+++Wbxay8vL7766qsy6wwdOpTt27eTlJiE+y/u5F/Jx6u7O5s2zcTbuxsmU+O+FBf1o3/ppZc4efIk7dq1Y86cOcXTX30VXngBvvkG5s6FGTPgxRdh8mR4/HHLY6LqW1gYxMdXb50uXbrQpEkT4uLieOCBB+olLiFKys5O5tixZ/H3H0arVg/x6+9/Redrwv4WZnRowgaRkZbEHiz97JcvX05CQgLh9ijkRIMgNfbXGTBgADt27Kiyj6YQQghRLamQcyoHv4F+ZOceQevcRt8Mv8jEiRNJSkqisLCQpKSkMoPmubnBxImwZYvl7847Yf58+zXT79ABkpIsg1vZymw2F48LIUR901pz5Mh0tC6gU6eFpP03jbP/Oku7P7fDs4On0eEJG3TpAocPW8qZESNGAEhzfFEtkthfp3///mRmZrJ//36jQxFCCOEkBg8ezKpVqypfaA+Ym5jx6eVDevo+zGZfPDza2yfABqR/f/j8czh5El577Voz/cjI+mum36ED5OVBdcfWjY6OZu/evVy1d98B0eicPfsFFy/+h9DQOXi4hZIwIwH3tu60e778MSyE44mMhOxsOHECOnbsSPv27SWxF9Uiif11ivpySnN8IYQQdSX7RDacAb8b/dAqh6ysBLy9u6GUXIZrqlUrSzP9kyctiX7TppZm+m3awNy5HTl6tO4+K8zakrm64+BFR0dTWFjI9u3b6y4YIa6Tm3uOo0efoEmT/gQHz+D0h6dJj08n7G9hmL3MRocnbBRpferpwYOWp6qMGDGCdevWSStiYTO5o7hOSEgIgYGBktgLIYSoM5c3XAZP8OnjQ2bmAaBAmuHXkfKa6a9c2bq4mf6PP9a+mX7JZ9lXR//+/QEZQE/Ur4SEJygouELnzh+Tf7GQxJcS8R/iT4t7WxgdmqiGosS+ZD/7tLQ0duzYYVxQwqlIYn8dpRT9+/eXkfGFEELUiexT2WQfz4auYHI1kZ6+D1fXFri5tTI6tAanqJn+V19t4bXXYNcuGD269s3027YFF5fqJ/ZNmzYlMjJSEntRb86fX8nZs1/Svv3LeHt3JfGVRPLT8un4XkeUUkaHJ6qhaVNo2fJaYj9s2DCUUtIcX9hMEvtyDBgwgEOHDnHp0iWjQxFCCOHk0jamYfIyQSfIz08jJ+cE3t7d5aa7HgUE5PLqq5a+qkuWlG6m/+STVLuZvouL5VFUNXkkfUxMDHFxcfLYKlHn8vPTOHLkEby9u9Ou3XOk70nn9ILTtHm0DT7dfYwOT9RAly7XEvvmzZvTq1cvSeyFzSSxL0fRs2elOb4QQtguNTWVm2++md9++61Otmc2m4mKiir+S0pKYv369dx+++11sn17yEnJIetoFr7RvuAKGRn7+OSTLSglj5+yBzc3uP9+SxP9rVthzJhro+nfemv1munX5Fn2YLmnuHjxIkeOHKn+ykJU4tixP5Ob+xudOn2MUq4cnXEU1wBXQmaFGB2aqKHISEsf+6LfAUeMGEFcXBzp6enGBiacgiT25ejfvz8uLi5s2rTJ6FCEEMJpzJ49m82bN/OXv/ylTrbn6elJfHx88V9ISEidbBcsj4YqrM/no1ld3ngZk6cJ336+AKSn72PRoh3k5bnX+2eL0vr1g88+uzaa/u7d15rpz50LV65Uvn6HDjWrsS+qLJDm+KIuXbq0jtTUhbRt+yd8ffty9suzpG1KI/SNUFybuhodnqihyEhLWZSaank/fPhw8vPz2bBhg7GBCacgiX05vLy86NOnD5s3bzY6FCGEMNzMmTMZPHhwhX9msxmlFPPnz6ewsJD58+ejlMJsNle4zsyZM2sd12uvvcY777xT/L5bt24kJSUB8Pe//51u3brRrVs33n33XQCSkpKIjIzk0UcfpXfv3pw6dYq//vWv9O3blx49evDqq68CkJGRwW233UbPnj3p1q0bX331FQDbt28nJiaGnj170q9fP65evUpBQQHPPvts8Tb+3//7fwCsX7+em2JuYtLsSQz/YDgPPPQAWl9k4cKVnDmTxpAhQxgyZEitj4GovqLR9Es203/iCQgOrryZflgYXLwIly9X7/M6d+6Mv7+/JPaizhQUZHL48MN4enYkJOQ18tPzOfbsMXz6+BD0UJDR4YlauH4AvYEDB+Lh4SHN8YVNJLGvwMCBA9m2bRs5OTlGhyKEEA6tX79+BAYGYjJZLikmk4nAwMDiEcFrKisrq7gZ/tixY21eb+fOnSxatIitW7eyZcsWPvzwQ3bv3g3A4cOH+cMf/sDu3bs5fPgwR48eZdu2bcTHx7Nz5042btzIjz/+SOvWrdmzZw/79+9n1KhR5ObmMm7cON577z327NnD2rVr8fT05OOPP8bPz4/t27ezfft2PvzwQxITEwGIj4/n1Ttf5cChAxw/fpwdO75n8uRoWrduzbp161i3bl2tjo+oneo20y8aGd/632szk8lE//79JbEXdSYx8RWys48TEfEhZrMXJ984SW5KLuFzw1FmGbvDmXXpYvm3KLH38PBg0KBBktgLm7gYHYCjGjRoEH/729/YsWMHN954o9HhCCGEYYpqvCvzyCOPsHDhQjw8PMjNzeWee+5h3rx5tfrcoqb41bV582bGjh2Lt7c3AHfffTebNm3izjvvpH379gwYMACA1atXs3r1anr16gVAeno6R48eZdCgQTzzzDM899xz3H777QwaNIh9+/YRFBRE3759AfD19S3ext69e1m6dCkAaWlpHD16FJWh6BHUg063dMLVy5WePXuSnHyAm266HZAbb0dT1Ez/r3+FhQstCf7o0ZYk//HH4cEHixL7VCZOHM8vv3xFq1a2P9UgJiaG1157jStXrhSfO0LUxJUr20hO/j+Cgv5I06aDyUzI5NTfTtHyDy3xi/YzOjxRS61agZ/ftcQeLP3s//znP3P69Glat25tXHDC4UmNfQViYmIApJ+9EELY4MyZM0yfPp0tW7Ywffr0OhtArzIuLi6l+slnZ2cDVDr6eFGyX7TcCy+8UNyHPyEhgSlTphAREcHOnTvp3r07L7zwAn/5y1/QWpc7ir3Wmrlz5xZvIzExkVtuuYWMvRm4u7rjO6AoicuioCBLnl3v4Fq1gldeudZMPyDgWjP9uXMBZnPo0GZmz55dre1GR0ejtZZH6YpaKSzM5dChh3B3b01Y2P8CcOypY5jcTXR4q4PB0Ym6oNS1AfSKDB8+HIC1a9caFJVwFpLYV6BFixZ07txZ+tkLIYQN/v3vf/PBBx/Qs2dPPvjgA/7973/X+2eGhISwa9cuAHbt2lXcBP6mm25ixYoVZGZmkpGRwfLlyxk0aFCZ9UeOHMknn3xSPNpwSkoKZ8+e5fTp03h5efH73/+eZ555hl27dtG5c2dOnz7N9u3bAbh69Sr5+fmMHDmS+fPnk5eXB8CRI0e4fOIy2YnZuPi7YPYyA5CffwEw4eXVmSZNmnC1pg9UF3ZR1Ew/Lu5aM/3PPksFFqF1IYsWLarWj1f9+/dHKSXN8UWtnDz5JpmZB4iIWICLiy8Xvr/AhVUXaP9Ke9yDZEDOhiIysnSNfc+ePWnRooU0xxdVkqb4lRg0aBDffPMNhYWFxX1HhRBCOIZ77rmHf/7zn0RFRdG3b18iIiIA6N27N5MmTaJfv34APPzww/Tq1at4YL0it9xyC7/++mvxqOU+Pj58/vnnJCQk8Oyzz2IymXB1dWX+/Pm4ubnx1VdfMWPGDLKysvD09GTt2rU8/PDDJCUl0bt3b7TWtGjRgo+mfARmcGlqucRqXUBe3kWgCyaTG9OmTWP06NEEBQVJP3snUNRM32yezeefF1JQAAUFBcyePZsPPvjApm34+vrStWtXSexFjaWn7+fEiTkEBt5Ps2a3UZhTSMLMBDw7eRL8RLDR4Yk6FBkJixbBpUuWwT1NJhPDhg1j7dq1FbYeEwIksa/UwIED+fDDDzlw4ADdu0vzSSGEsKfynttbNKp+UlISnp6erF69utx1n376aZ5++ulS00JCQti/f3+paU8++SRPPvlkqWlhYWGMHDmyzDb79u3Lli1bykx/4403eOONNwDIu5hHyvsp3PK7Wxg/cjwAWVkJzJp1CzAMgBkzZjBjxowK9lo4otTUVL76ahEFBbkA5ObmsmjRIl5++WWb+9rHxMTw9ddfS2WBqDatCzh8eAouLn507PgeAMnvJZN1NIvuP3TH5CbnU0NScgA9a89gRowYwZdffsmBAwfo1q2bccEJhyYlQSWKmm5KP3shhBC2SNucBibwjbk2QFpGxj5MJi+gjXGBiVqZPXt2qfEc4Fqtva2io6O5fPkyhw4dquvwRAOXnPweV69uo2PHubi5NSfndA4nZp+g2Z3NaDaqmdHhiTpW9Mi78vrZS3N8URlJ7CsREhJC69atpZ+9EEKIKuVdziM9Pp0mvZvg0sTSIK6wMIfMzMN4e3dFLrnOKy4ujtzc3FLTcnNziY2NtXkbRV0+pDm+qI6srGMkJv4PzZrdQWDgOACOP3ecwrxCOv5fR4OjE/WhfXvw8Cjdz75du3ZERERIYi8qJXcZlVBKMWjQIDZt2lTpKMtCCCHElc1XQIHfwGuPnMrMPITWeTIavpPbvXs3Wusyf7t377Z5GxEREQQEBEhiL2ymtebw4ako5UpExHyUUqT9N40zn5+h7TNt8ezgaXSIoh6YzdCpU+nEHizN8Tds2FDmR0YhikhiX4WBAweSnJzMyZMnjQ5FCCGEg8q/ks/V3Vfx6eWDi++14WvS0/fh4uKPu3tbA6MTjkApxYABAySxFzZLTf2Iy5fXERb2Du7ubdAFmqMzjuIe7E77F9obHZ6oR9ePjA+W5viZmZlShogKSWJfhaJ+9hs3bjQ4EiGEEI4q7b9poEvX1hcUpJOdfRxv7+4yirEALAPoHTx4kMuXLxsdinBwOTkpHDv2DP7+QwgKehiA1I9SSd+dTtg7YZi9zQZHKOpTly5w4gRkZFybNmTIEMxmszTHFxWSxL4K3bp1o2nTpqxfv97oUIQQQjig/Kv5pO9Mx6enD67+rsXTMzIOAIXSDF8UK+pnX97TFYQoorXmyJFH0DqPTp0+RClF3sU8jr90HL+b/WjxuxZGhyjqWWQkaA2HD1+b5ufnR79+/SSxFxWSxL4KZrOZwYMH88svvxgdihBCOKwlS5YQEhKCyWQiJCSEJUuW1HqbZrOZqKgounXrxn333UdmZiZged58XVq/fj233357pcsUPV4vKiqKqKgopk+fXjxv8ZuLGTl3JDc9dxN//vOfi6dfuLCLJ55YRZcuMfTv35/k5ORr6yxeTHh4OOHh4SxevLjcz5w0aRJLly4F4OLFi/Tq1YtFixbVZleFwfr164fJZJKmtKJSZ89+xYUL3xEa+jqenmEAJL6SSP6lfML/ES4tgBqBopHxy+tnv2PHDi5dumT/oITDk8TeBkOHDiUpKYnExESjQxFCCIezZMkSpk2bxokTJ9Bac+LECaZNm1br5N7T05P4+Hj279+Pm5sbCxYsqKOIayYsLIz4+Hji4+OLYzl78iyvzHuF5W8v5+Chg5w5c4aff/6ZvLyLfP75Kpo3DyYhIYGnnnqKt956C7Ak6bNmzWLr1q1s27aNWbNmVXqTlpaWxsiRI5k2bRqTJ0+2y76K+uHj40P37t0lsRcVys09T0LCDJo06Udw8JMApO9N5/T807R5tA0+Per2h03hmMLDLYPoldfPvrCwkHXr1hkTmHBoLlUvUjeUUqOA9wAz8JHW+q3r5ncGFgG9gZe01u/YK7aqDBkyBIB169YRGhpqcDRCCGFfM2fOJD4+vsL5W7ZsIScnp9S0zMxMpkyZwocffljuOlFRUbz77rs2xzBo0CD27t1balp6ejpjxozh0qVL5OXl8frrrzNmzBiSkpIYPXo0AwcOJDY2ljZt2vDtt9/i6elJQkIC06dP59y5c5jNZr755ptS29y+fTvTpk1j2bJldOjQocq49n63l9CAUMJut9SqDR8+nGXLltGnjwtr1hxmzpz5ANx77708+uijaK356aefGDFiBAEBAYClBubHH39kwoQJZbafnp7O6NGjuf/++3nkkUdsPl7CccXExLBkyRIKCgowm6WftCgtIWEm+flpdOr0MUqZ0doyYJ5LUxdCZoUYHZ6wEzc36NixbGI/YMAAfHx8WLNmDXfffbcxwQmHZZcae6WUGfgAGA10ASYopbpct9hF4AnAYRL6Il26dCEwMFCa4wshRDmuT+qrml5d+fn5/PDDD3TvXrqvuoeHB8uXL2fXrl2sW7eOP/3pT8WPJj169CiPPfYYBw4cwN/fn2XLlgEwceJEHnvsMfbs2UNsbCxBQUHF24uNjWX69Ol8++235Sb1iYmJ9OrVi5tvvplNmzZRkFlA4G+BHE87zun00+Tn57NixQpOnTpFevo+zp7NJjTU0p7SxcWFJk2acOHCBVJSUmjb9too+cHBwaSkpJS7708//TQDBw7kqaeeqt1BFA4jOjqaK1eucPDgQaNDEQ7mwoX/cPbsEtq1exEfn24AnPv6HGkb0+jwRgdcA1yr2IJoSCIj4fpiwtXVlcGDB0s/e1Eue9XY9wMStNbHAZRSXwJjgOLTVWt9FjirlLrNTjHZTCnF0KFD+eWXX9BaS98mIUSjUlXNekhICCdOnCgzvX379rUaeDQrK4uoqCjAUmM/ZcqUUvO11rz44ots3LgRk8lESkoKZ86cASA0NLR43T59+pCUlMTVq1dJSUlh7NixgOWHgSK//vor06ZNY/Xq1bRu3bpMLEFBQZw8eZJmzZqxc+dO7rrrLjbP34yv2Zf3332fcePGYTKZiImJISHhIPn551HKvcx2lFLFPz5cP708Q4cO5dtvv+WZZ54hMDCw6oMmHF7RAHpxcXFlfqwSjVd+/hUOH/4j3t7daN/+RQAKMgo49swxfHr7EDQlqIotiIYmMhJWrYK8PHAt8ZvOiBEjWLVqFYmJidKSWJRirz72bYBTJd4nW6c5jaFDh5KamsrhksNTCiGEYM6cOXh5eZWa5uXlxZw5c2q13aI+9vHx8cydOxc3N7dS85csWcK5c+fYuXMn8fHxtGzZkuzsbADc3a8l1Wazmfz8/HIT6iJBQUF4eHiwe/fucue7u7vTrFkzwPJDQYfQDuz9YS9ekV7c/cDdbN26lbi4ODp16kT79j6AmbZtO3DqlOXSl5+fz9WrVwkICCA4OLh4OkBycnK5PyYAjB8/nkceeYRbb72Vq1evVn3QhMMLCwujefPm0s9elHL8+HPk5qbSqdPHmEyWsu7EmyfISc6xDJhnlkqlxiYyEvLzISGh9PThw4cDsHbtWgOiEo7MXjX25ZVGFd9hVbYhpaYB0wBatGhht8fQFd20zp8/v7i2p76kp6c32MfrNdR9k/0SjdnEiRMBeOmllzh58iTt2rVjzpw5xdPrS1paGoGBgbi6urJu3bpyWw2U5OvrS3BwMCtWrOCuu+4iJyeHgoICAPz9/fn444+55ZZb8Pb2ZvDgwaXWPXfuHAEBAZjNZo4fP87RX4/SNrotfjf7cfbsWQIDA7l06RLz5s3jvfdG4ekZzpgxASxevJjo6GiWLl1KdHQ0SilGjhzJiy++WDxg3urVq3nzzTcrjHvmzJmkpqYyduxYvv/++zI/cAjnopQiOjpaEntR7NKl9Zw+vYDg4Kfx9e0HQNaxLE799RQtf98Svxv9DI5QGKHkyPhFry3TI2ndujVr1qxh6tSpxgQnHJK9EvtkoG2J98HA6ZpsSGu9EFgI0KlTJ339zVd9evXVVzl+/HiZG766tn79+nr/DKM01H2T/RKN3cSJE+s9kS/vM++44w5uuOEGoqKi6Ny5c5XrfPbZZ/zxj3/klVdewdXVtdTgeS1btuS7775j9OjRfPLJJ/Tv37943saNG3nllVdwcXHBbDLz+q2vExQVhHsrd56c8CR79uwB4Pnn/0j79pfw8enOlClhPPDAA3Ts2JGAgADeeccyhExAQAAvv/wyffv2BeCVV14pHkivIm+//TaTJ0/mgQce4IsvvsBkkofaOLOYmBi+++47Lly4UNwSRDROBQWZHDkyFQ+PDoSGzi6envB0AiY3Ex3ernoQT9EwFV3Srh9ATynFiBEj+O6772QQTlGKvRL77UC4UioUSAHGA/fb6bPrzKhRo1i0aBE5OTmlmnkKIYSoe+np6RVOT0pKqrQ58/79+4tfP/PMM8Wvw8PDywyE2qFDh+IfsNq1a8eBAwfKbO+ee+7hnnvuAeDy5stcXnsZ/5v8Afjiiy+Klzt//lsyMjLx9IzAZCr9w0FSUlLx64ceeoiHHnqo3NiLfPrpp6XeyzPsG46ifvZbtmzhttscbmghYUdJSa+RlZVAz56/YDZbWode+PECF1ZeoMPbHXBvLfebjZWPD7RrV3YAPbD0s1+8eDHx8fH06dPH/sEJh2SXn/y11vnA48BPwK/A11rrA0qp6Uqp6QBKqVZKqWTgaeB/lFLJSilfe8Rnq5EjR5KZmcl///tfo0MRQghhgMLcQq7EXsGzoyfubUrfcBcW5pORcRAvr0hMJhm9WlTshhtuwGw2S3P8Ru7KlR2cOvU3goKm0rSp5dHKhbmFJDyZgGeEJ8Ezgw2OUBgtMrJsjT3AsGHDAGR0fFGK3dryaa2/11pHaK3DtNZzrNMWaK0XWF//prUO1lr7aq39ra+v2Cs+WwwZMgRXV1d+/PFHo0MRQghhgKs7rlKYWYjfzWX7vGZlHUHrHHx8ZKRzUTlvb2969uwpiX0jVliYy+HDD+Hm1oqwsL8WT09+L5msI1l0fLcjJjfpctPYRUbCoUNQWFh6eqtWrejevbsk9qIUKTGqwcfHh4EDB/LTTz8ZHYoQQgg7K8wrJC02DY8OHni09SgzPyNjH2azDx4e8vghUbWYmBi2bdtGfn6+0aEIA5w8+TYZGfuIiFiAi4vlh8Kc1BxO/OUEze5oRrPRMvaCgC5dICsLTp4sO2/EiBFs3ryZzMxM+wcmHJIk9tU0atQo9u7dS3JystGhCCGEsKP0XekUphcW960vqaAgm8zMI3h7d0MpubSKqkVHR5Oenl5qPAjROGRkHOTEidkEBo6nefM7iqcff+44hbmFhP09zMDohCMpGg2/on72ubm5bN682b5BCYcldx/VdPvttwOwatUqgyMRQghhL4X5haRtTsO9vTseIWVr6zMzDwIFeHtLM3xhm6IB9KQ5fuOidQGHDj2E2exLx47/KJ6eFpvGmc/O0PaZtnh19DIwQuFISj7y7nqDBg3Czc1NmuOLYpLYV1NkZCQdO3bk22+/NToUIYQQdpK+O52CqwX43+xf7vyMjH24uDTDza21fQMTTiskJISWLVtKYt/IJCfP5erVrYSH/wM3txYA6ALN0RlHcWvjRrsX2hkcoXAkzZpBixblJ/be3t7ExMRIYi+KSWJfTUopxowZwy+//MLVq1eNDkcIIRxGamoqN998M7/99ludbM9sNhMVFUW3bt247777ivsR+vj41Mn2i6xfv764NVZ5dIHmu4+/485Fd9JvTD/69OlT6pF5n3/+CYMH/5mRI99l9OjRnD9/HrA8rq5FixZERUURFRXFl19+WbzO4sWLCQ8PJzw8nMWLF5f7uZMmTWLp0qUAXLx4kV69eskj7xoQpRTR0dGS2DciWVnHSUx8iYCA2wgMnFA8PfWTVNJ3pRP2ThguPvZ6ErVwFhWNjA+W5vh79uzhzJkz9g1KOCRJ7GvgzjvvJDc3VwbRE0KIEmbPns3mzZuZPXt2nWzP09OT+Ph49u/fj5ubGwsWLKiT7VZX+p50/LU/y5csZ9++fSxevJgHHngAgPz8fJ566k/8618PEh+/jR49evD+++8Xrztu3Dji4+OJj49n/PjxgCVJnzVrFlu3bmXbtm3MmjWLS5cuVfj5aWlpjBw5kmnTpjF58uT63VlhVzExMSQkJHDu3DmjQxH1TGvN4cPTUMpMRMR8lFIA5F3KI/HFRPxu8iNwXKDBUQpH1KWLJbHXuuy8ESNGAJT6sVk0XvKzYA3ExMTQrFkzVqxYwb333mt0OEIIUa9mzpxJfHx8pcvk5OSwbds2CgsLWbBgAbt378bNza3C5aOionj33XdtjmHQoEHs3bu31LT09HTGjBnDpUuXyMvL4/XXX2fMmDEkJSUxevRoBg4cSGxsLG3atOHbb7/F09OThIQEpk+fzrlz5zCbzXzzzTeltrl9+3amTZvGsmXL6NChA7pQk7YpjV59ehF0YxAAXbt2JTs7m5ycHEwmE4WF+eTnB+DiEsCVK1fo2LFjpfvy008/MWLECAICAgDLjdmPP/7IhAkTyiybnp7O6NGjuf/++3nkkUdsPl7COZTsZ+/r62twNKI+/fbbJ1y+/DPh4fPx8GhbPD3p1STyLuYR/o/w4mRfiJIiI+HSJThzBlq1Kj2vd+/eNG3alDVr1pR7DRGNi9TY14CLiwt33XUXK1euJCsry+hwhBDCcCdOnEBbqxO01pw4caLOtp2fn88PP/xA9+6lB6bz8PBg+fLl7Nq1i3Xr1vGnP/2pOIajR4/y2GOPceDAAfz9/Vm2bBkAEydO5LHHHmPPnj3ExsYSFBRUvL3Y2FimT5/Ot99+S4cOHQDI2JdB/qV8/G/2L77pXrZsGb169cLd3R2tLzN79miGD59N69atOXjwIFOmTCne5rJly+jRowf33nsvp0+fBiAlJYW2ba/d2AcHB5OSklLuvj/99NMMHDiQp556qraHUTigPn364OLiIs3xG7icnNMkJPwJP7+bad16WvH09H3ppMxLofX01vj0rNsuRqLhqGwAPbPZzNChQ1mzZk3x9U80XlJjX0Pjx4/n448/5ocffuDuu+82OhwhRAOilBoFvAeYgY+01m9dN38MMBsoBPKBmVrrzdZ5/sBHQDdAAw9prWuVNVRVs56ammqp3S6R2F+6dIkvv/ySVtdXL1RDVlYWUVFRgKXGvmTCXPQ5L774Ihs3bsRkMpGSklLczzA0NLR43T59+pCUlMTVq1dJSUlh7NixgOWHgSK//vor06ZNY/Xq1bRubRkATxdqLm+8jGsrVzwjPAE4cOAAzz33HKtXrwbg8uXdLFmyg+3b44iI6M6MGTN48803+Z//+R/uuOMOJkyYgLu7OwsWLOCZZ54hNja23Juvimrqhg4dyrfffsszzzxDYKA0021oPD096dWrF3FxcYwcOdLocJxWVWVmieX6AluAcVrrpUopD2Aj4I7lnnip1vpV67J/Be4AcoFjwGSt9eXqxqa15siRR9E6h06dPix+HKbWmoQnEnDxcyF0dmh1NysakZKJ/ZAhZeePGDGCZcuWcfjwYTp37mzf4IRDkRr7Gho8eDCBgYGlBkMSQojaUkqZgQ+A0UAXYIJSqst1i/0M9NRaRwEPYUnki7wH/Ki17gz0BCoYcqfuzJ49m8LCwlLTCgoKat3XvqiPfXx8PHPnzi3TtH/JkiWcO3eOnTt3Eh8fT8uWLcnOzgbA3d29eDmz2Ux+fn6ltRlBQUF4eHiwe/fu4mkZBzLIv5CP/02W2vrk5GTGjh3LP//5T8LCwtBas23bT5hMnnTq1AOlFL/73e+IjY0FoFmzZsVxTJ06tfh55cHBwZw6dar4c5KTk4t/TLje+PHjeeSRR7j11ltlwNYGKiYmhu3bt5Ofn290KE7JxjKzaLm3gZIDJOUAQ7XWPYEoYJRSaoB13hqgm9a6B3AEeKEm8Z079w0XLnxLSMhf8PIKvzb9m3NcXn+Z0DmhuAa41mTTopFo0waaNKl8AD2AtWvX2jEq4Ygksa8hFxcX7rvvPlatWiU3W0KIutQPSNBaH9da5wJfAmNKLqC1TtfXslRvLDXzKKV8gZuAj63L5dakhqm64uLiyM3NLTUtNze3OMGtL2lpaQQGBuLq6sq6deuqbP7v6+tLcHAwK1asACzjAhSNtO/v789//vMfXnzxRdavX4/WmrSNabi2cMUr0ovLly9z22238eabb3LjjTda10+mRQs4evRs8eBna9asIdJavZKamlr82StXriQsLAyAkSNHsnr1ai5dusSlS5dYvXp1pbW1M2fOZNiwYYwdO7bMcRbOLzo6mszMTI4dO2Z0KM6qyjLTagawDDhbNEFbpFvfulr/tHXeaq110a8tW4Dg6gaWl3eBo0cfp0mTGwgOvtadpiCjgGPPHMMnyofWU+URmaJySllq7Q8eLH9+hw4dCA0NlcfeCWmKXxvjx4/ngw8+YOXKlUycONHocIQQDUMb4FSJ98lA/+sXUkqNBd4EAoHbrJM7AOeARUqpnsBO4EmtdUY5608DpgG0aNGC9evXl5rv6+trcxK5fPnyCuclJSXZtI3yaK3LXV9rTW5uLoMGDWLx4sX06NGDyMhIwsLCSE5OBiAvL6943YsXL5KZmUlSUhJvvvkmL730Es8//zyurq588MEH/Pbbb2RlZZGVlcW8efOYPHkyb898m17nesFNlvED5s6dy9GjR3n55Zd5+eWXAfjnP5+kZUt/Zsx4nOjoaFxcXGjTpg3vvPMOSUlJ/O///i9r167FbDbj7+/PG2+8URzTI488Qq9evQB47LHHuHLlCleuXCm1n+np6Zw9e5akpCQeeeQRnn32We6++27+8Y9/YDLV3e/yFy9e5MiRIxXOT09PL3N+ODpnjHn37t1OF7ODqLLMVEq1AcYCQ4G+180zYykrOwIfaK23lvMZDwFflffhlZelbwAXyct7k40bN1+b/Ikl4pxnc9iwaUPVe+iknPF7WF9qeyyaNu3Mjh1NWb++/J51Xbt2Ze3ataxduxYXF8dP7+TcqCdaa6f9i4iI0EYqKCjQbdu21bfddludbnfdunV1uj1H0lD3TfbLuQA7tAOUYeX9Afdh6SNa9P4BYG4ly98ErLW+vgFLn/v+1vfvAbOr+szyytKUlJRaHOH6l5iYWG/bLiws1MnzkvWpf5zShQWFFSyTr0+c+F995szXNm+3PmOujar+r52xHHCmmAsLC3Xr1q31sGHDjA6l2hyhLLWlzAS+AQZYX38K3FvOdvyBdVia35ec/hKwHFBVxVKyLD1//nu9bh36+PGXSx2zzGOZer37en1g4oFaHHnn4Ezfw/pW22Px1ltag9aXL5c//5tvvtGA3rx5c60+x17k3CitrspSaYpfCyaTifvvv58ff/yxVJNLIYSohWSgbYn3wcDpihbWWm8EwpRSza3rJutrNU5Lgd71FWhDlXU4i7wzeZa+9abyB7XLyjpOYWEGPj7dy50vhK2UUkRHR3Owona2oiq2lJk3AF8qpZKAe4F5Sqm7Si6gLd2W1gOjiqYppR4EbgcmWm++bZKff4UjR/6Il1cX2rd/qdS8hKcTUC6KsLfDbN2cEJWOjA+WgVaVUtLPvpGTxL6WpkyZQkFBAYsWLTI6FCFEw7AdCFdKhSql3IDxwMqSCyilOirrMOpKqd6AG3BBa/0bcEop1cm66DBAsoVq0NoyEr5LUxe8u3tXuFxGxj5MJk88PcMrXEYIW8XExJCamspvv/1mdCjOqMoyU2sdqrUO0VqHYPnB81Gt9QqlVAvrk0RQSnkCw4FD1vejgOeAO7XWmdUJ6PjxF8jJSaZTp48xma4N5Hnxp4tc+PYCIS+H4N7GvZItCFFaF+twkBUl9gEBAfTp00f62TdyktjXUnh4OIMHD+ajjz4qMyq0EEJUl7YM1vQ4lpGbfwW+1lofUEpNV0pNty52D7BfKRWPZTTocSVqk2YAS5RSe7GM8vyGPeN3dlkJWeSezsVvkF+FtfWFhblkZh7Cy6sLlu65QtROdHQ0gDzPvgZsLDMrEgSss5aX24E1WutV1nnvA02ANUqpeKXUAlviuXx5E6dPzyM4+En8/AYUTy/MLeTok0fxDPckeGa1x+ETjVxoKLi7VzyAHlhGx9+yZUuZ8VpE4+H4oys4gWnTpnH//ffzyy+/MHz4cKPDEUI4Oa3198D3101bUOL121ge21TeuvFYmp2KatJak7YhDbOfGZ+ePhUul5l5GK1zpRm+qDO9e/fG1dWVuLg4xo4da3Q4TqeqMvO66ZNKvN4L9KpguY41iITDh6fg4RFKaOjrpeakzE0h63AW3f/THZO71KuJ6jGbISKi4hp7sCT2b775JuvXr+fOO++0X3DCYUjJUgfGjh1LQEAACxbY9GOuEEIIB5SdmE1Oco6ltt5cfm09WJrhm81+uLu3t2N0oiFzd3cnPDxcauyd3gWyso7SqdOHmM3XuvLkpOaQNCuJgNsCaHZrMwPjE84sMrLyxD4mJgZPT0/pZ9+ISWJfBzw8PJg6dSrLly/n+PHjRocjhBCiBi5vuIzZ10yTqCYVLlNQkElWVgLe3t2wDnMgRJ3o2rUrO3bssPkxk8IRXaRVqyk0bTqs1NTjLxynMKeQju/WoBGAEFZdukBiImRllT/f3d2dm266SfrZN2KS2NeRJ554ArPZzN///nejQxFCCLvq1asXSqkyf0XPaa+NOXPm0LVrV3r06EFUVBRbt5b3iOmy1q9fz+233w7AypUreeuttypdPjspm5wTOfjd6Idyqay2/gBQiI9PD5v3QQhbdO3alezsbOLj440ORdSYmbCwd0pNSYtL48ziM7R9ui1eHb0Miks0BJGRoDUcPlzxMiNGjODQoUMkJyfbLzDhMCSxryOtW7fmgQce4JNPPuHcuXNGhyOEEHYTHR2Nm5tbqWlubm7ExMTUartxcXGsWrWKXbt2sXfvXtauXUvbtm2rXvE6d955J88//3yly1zecBmTjwmf3hX3rQdLM3xX10BcXQOrHYcQleliHfZamuM7s5a4uvoXv9OFmqMzjuLW2o12L7UzLizRIFT1yDuwJPaA1No3UjJ4Xh169tln+fTTT5kzZw7vvvuu0eEIIUSdmDlzZqW1iDk5OeTn55ealp+fz+7duxk8eHC560RFRVVZTqamptK8eXPc3S2PhWrevDkAP//8M0888QQmk4m+ffsyf/583N3d+fHHH5k5cybNmzend+/exdv59NNP2bFjB++//z6TJk3i9ttv59577wXAx8eH87+eZ/269czdM5c229oQHx/P3XffTffu3XnvvffIyspixYoVtGvXjJyck/j7D5Nm+KLOtWjRgrZt2xIXF8eTTz5pdDiiRkr/MJj6SSrpO9OJXBKJi4/ccovaiYgAk6nyxL579+4EBgaydu1aJk+ebL/ghEOQGvs61LlzZ6ZMmcK8efNISEgwOhwhhLALd3d3WrZsWZzsKqVo1apVmVr86rrllls4deoUERERPProo2zYsIHs7GwmTZrE3Llz2bdvH/n5+cyfP5/s7GymTp3Kd999x6ZNm6r1PPC0DWkod8WBxAO899577Nu3j88++4wjR46wbds2Hn74YebOnUtGxj4AvL1lNHxRP6Kjo6XGvoHIu5xH4guJ+A30I3CCtPARtefuDh06VJ7YK6UYPnw4a9eulcdwN0Ly82EdmzVrFv/61794/vnnWbp0qdHhCCFErdnSAik1NZUOHTqQnZ2Nh4cHO3fupFWrVrX6XB8fH3bu3MmmTZtYt24d48aN44UXXiA0NJQOHToA8OCDD/LBBx8wePBgQkNDCQ8PB+D3v/89CxcurPpDtOXZ9d7dvOl7vC9BQUEAhIWFccsttwCWGpB169aRkbEPd/d2pZraClGXYmJi+Prrr0lJSaFNmzZGhyNqIenVJPIu5tFxbkdp4SPqTJculSf2YGmO/69//Yt9+/bRs2dP+wQmHILU2NexoKAgnnvuOZYtW8bKlSuNDkcIIewiKCiIyZMnYzKZmDx5cq2T+iJms5nBgwcza9Ys3n///Uof42PLzbOLi0txLYbWmtycXEyeJrw6eRU3+QcwmUzF700mE7m5GeTlnZXaelGvoqOjAeln7+zS96eT8kEKrf/YutKnbAhRXZGRcOQIXNf7rRTpZ994SWJfD5577jmioqJ4+OGHOXPmjNHhCCGEXbz88ssMHDiQl19+uU62d/jwYY4ePVr8Pj4+npYtW5KUlERSUhIAn332GTfffDOdO3cmMTGRY8eOAfDFF1+Uu82QkBB27twJwNJFS8kryMN3gC8mt8ovhwUFVwET3t5da79jQlQgKioKDw8PSeydmNaahCcScPFzIXR2qNHhiAYmMhLy8sB6qStXmzZtiIyMlOfZN0KS2NcDNzc3Pv/8c65cucLUqVPRWhsdkhBC1LugoCA2bNhQZ7X16enpPPjgg3Tp0oUePXpw8OBB3nrrLRYtWsRjjz1G9+7dMZlMTJ8+HQ8PDxYuXMhtt93GwIEDad++fbnbnDp1Khs2bKBfv35sWrkJLzcvmvSvvEZNa01+/hU8PTtiNsvjqkT9cXNzo0+fPpLYO7Fzy85xed1lQl8PxbWZq9HhiAbGlpHxAYYPH87GjRvJzs6u/6CEw5A+9vWka9euvPXWWzz11FN89NFHTJ061eiQhBDCqfTp04fY2Ngy04cNG8Z//vMfQkJCSk0fNWoUhw4dKrP8pEmTmDRpEgAtW7ZkzZo1fPPFN0SfjmbWk7Mwe1ia+5ccwX/9+vXFr6OjQ/n4499JM3xhFzExMbz33nvk5OSU6h4inICGY386hndPb1pPa210NKIBKpnY33VXxcuNGDGCuXPnEhsby9ChQ+0SmzCe1NjXoyeeeIJhw4bx1FNPySj5QgjhIDZu3Mip06fYY9qD7wDfKpdPT9+HUm54eXWyQ3SisYuOjiY3N5ddu3YZHYqorouQczKH8LnhKLMMmCfqXpMmEBwMBw9WvtzgwYNxcXGRfvaNjCT29chkMvHpp5/i6urKH/7whzLPeRZCCGFfV69eZffu3Wg0CSSQVZBV6fJa55OZeRAvr86YTLV7fJ8QtpAB9JzYRQicEIj/IH+jIxENWGRk1U3xmzRpwoABA6SffSMjiX09Cw4OZt68ecTFxfHWW28ZHY4QQtisIY4PsnHjRnShZb+00mzYsKHS5bOyEigszGqwzfAb4v+xs2vVqhUhISGS2DupsL+GGR2CaOAiI+HQIajqMfXDhw9n586dXLhwwT6BCcNJYm8HEyZMYPz48cyaNYsdO3YYHY4QQlTJ1dWV9PT0BpX4FdXWFxQWAFBQUEB8fDzp6ekVrpOevg+TyRtPz4Z3s661Jj09HVdXGeDL0URHR0ti74yagXsbGRdB1K/ISMjIgOTkypcbMWIEWmt++eUX+wQmDCeD59nJvHnz2Lx5M/fffz+7du3Cx8fH6JCEEKJCAQEBXLx4katXrxodSrkuXryIm1v1msZv2bIFV1dXTKZrv2mbzWZWr17NgAEDyixfWJjL2bPH8fKKIDX1N0Nirm+urq4EBAQYHYa4TkxMDF988QWnTp2ibdu2RocjbNXU6ABEY9Cli+XfX3+Fdu0qXq5fv374+vqyZs0a7rvvPvsEJwwlib2dNG3alM8//5yhQ4fy0EMP8fHHH9OkSeWPWBJCCKOYzWZatGhhdBgVOnLkCL17967WOrNnzyY+Pr7M9KioKHbv3l1m+m+/LebKlecJC4vDz6/2I1zXJGbROBX1s4+NjWXcuHEGRyNsJuPlCTsoGhn/4EEYObLi5VxcXBgyZIj0s29E7NYUXyk1Sil1WCmVoJR6vpz5Sin1D+v8vUqpBnf3c/PNNzN79my++eYbfH19OVjVkJZCCCHqzO7duznx9gnWsY6cMzlordFal5vUA5w5swQPjw74+va3c6SisevRoweenp7SHF8IUUaLFtCsWdUD6IGln31iYiLHjh2r/8CE4exSY6+UMgMfACOAZGC7Umql1rpkZjsaCLf+9QfmW/9tUF544QWioqLYs2cP7du3NzocIYRoVNL+m4ZnuCdugZU3ic/J+Y1Ll36mffsXUUqq4YR9ubq60rdvX0nshRDlsmVkfLD0swdYs2YNYWENb6wYUZq9auz7AQla6+Na61zgS2DMdcuMAf6pLbYA/kqpIDvFZzdKKW699VZeeOEFvL29jQ5HCCEaDa01V2Kv4HejX5XLnjv3FVBIYOD99R+YEOWIiYlh9+7dZGVV/khGIUTj06WLpSl+VePbRkRE0LZtW3mefSNhrz72bYBTJd4nU7Y2vrxl2gCpJRdSSk0Dplnf5iil9tdtqA6hOXDe6CDqSUPdN9kv59LJ6AAcyZEjR9KVUoeNjqOaan5ufmr9s0mXGn1EBZz1++SMcTeYmL28vAwIxWZSlpbgpGVpfXLG72F9qZdjYbKxivbUqVOO1vpMzo3S6qQstVdiX96ZdP1vTLYsg9Z6IbAQQCm1Q2t9Q+3DcywNdb+g4e6b7JdzUUrJcydLO+xs/8/OeG46Y8zgnHFLzPYhZWkZTleW1idnPKfrixyL0uR4lFZXZam9muInAyWf1xIMnK7BMkIIIYQQQgghhCjBXon9diBcKRWqlHIDxgMrr1tmJfAH6+j4A4A0rXXq9RsSQgghhBBCCCHENXZpiq+1zldKPQ78BJiBT7TWB5RS063zFwDfA7cCCUAmMNmGTS+sp5CN1lD3Cxruvsl+OZeGul815YzHQ2K2H2eMW2K2D2eMuT7J8ShNjsc1cixKk+NRWp0cD6WrGk5RCCGEEEIIIYQQDsteTfGFEEIIIYQQQghRDySxF0IIIYQQQgghnJjDJvZKqVFKqcNKqQSl1PPlzFdKqX9Y5+9VSvW2dV0j2bBfE637s1cpFauU6mnrukayNTalVF+lVIFS6t7qrmsEW2JTSg1WSsUrpQ4opTZUZ12j2HAe+imlvlNK7bHu12Rb1zWSUuoTpdRZpdT+CuY7ZblRU7Upb6zzzUqp3UqpVfaL2qa4x1hjjldK7VBKDbROb6uUWqeU+tV63j7pKDGXWM5hysBaxvyU9RjvV0p9oZTycISYreVxmvXciFdKvVJinr9SaqlS6pD1HIl2hJhLxF3mOmKdZ/fvoQ3H+dkSx3i/9fwIMPI7WJ9qet7J8Sj7PbTON+TaUl+csVyqL7U8FoZcV+pTbcr/Gt0baK0d7g/LAHvHgA6AG7AH6HLdMrcCPwAKGABstXVdB9+vGKCp9fXohrJfJZb7BctAifc2hP0C/IGDQDvr+8AGsl8vAm9bX7cALlqXddj9ssZ6E9Ab2F/BfKcrN+r5/7nc8qbE/KeBfwGrHCxuH66NEdMDOGR9HQT0tr5uAhyxx/+jM5aBtYy5DZAIeFrffw1McoSYgcEVna/AYuBh62s3wN9BYvannOtIifl2/R5W95wE7gB+sb425Dto9PGo6LyT41HhNux+bXHU42FEueSIx8Ko64oDHI9yy//qlsNFf45aY98PSNBaH9da5wJfAmOuW2YM8E9tsQXwV0oF2biuUaqMTWsdq7W+ZH27BQi2dV0D2RrbDGAZcLYG6xrBltjuB/6ttT4JoLU+W411jWJLbBpoopRSWJKoi0C+jesaRmu9EUusFXHGcqOmalPeoJQKBm4DPrJTvEVsiTtdW698gDeW8xWtdarWepf19VXgVyw3C4bHbOVIZWBtYgbLU3U8lVIugBdwuj6DtarxsVJK+WL54e9jAK11rtb6cn0FWkJtriNGfQ+re5wnAF+Aod/B+lTj806OR1kGXlvqizOWS/WlttczI64r9cnueYSjJvZtgFMl3idTtiCsaBlb1jVKdWObgqV2sSbr2lOVsSml2gBjgQXVXddAtsQWATRVSq1XSu1USv2hGusaxZbY3gcisRSq+4AntdaFNq7ryJyx3Kip2pQ3AO8CfwYK6zyyytkUt1JqrFLqEPAf4KFy5ocAvYCt9RNmKc5YBtY4Zq11CvAOcBJIBdK01qvrNVoLW49VtLJ0I/pBKdXVOq0DcA5YZG0C/JFSyrue44XaXUfAmO+hzeekUsoLGIXlx5/r54Vgv+9gfarNeVdMjkexdzHm2lJfnLFcqi81PhYGXlfqk93zCEdN7FU5065/Ll9Fy9iyrlFsjk0pNQTLjfZz1V3XALbE9i7wnNa6oAbrGsWW2FyAPlh+fR4JvKyUirBxXaPYEttIIB5oDUQB71t/WXbk/bKFM5YbNVXj8kYpdTtwVmu9s/7Cq5BNcWutl2utOwN3AbNLbUApHyyJxkyt9ZX6CPI6zlgG1jhmpVRTLDUHoVjKCG+l1O/rI8jr2BLzLqC91ronMBdYYZ3ugqWbznytdS8gA7DHeAY1vo4Y+D2szjl5B/BfrXWpllIGfAfrU23OO8sG5HisAMOvLfXFGcul+lKbc8Oo60p9snse4VLdCO0kGWhb4n0wZZtjVLSMmw3rGsWW/UIp1QNLE6XRWusL1VnXILbEdgPwpaVlN82BW5VS+TauaxRbz8PzWusMIEMptRHoaeO6RrEltsnAW9bmzglKqUSgs43rOjJnLDdqqjblzY3AnUqpWwEPwFcp9bnW2h4X2WqdY1rrjUqpMKVUc631eaWUK5Yb6CVa63/Xc6xFnLEMrE3MrkCi1vocgFLq31jGa/jc6JhLJk1a6++VUvOUUs2t6yZrrYtqS5dinxvo2lxHemPM97A65+R4rM3wixj0HaxPNT7vDCyT6lNtvodGXlvqizOWS/WlNsdiCMZcV+qT/fMI7QCDC1z/h+UHh+NYfrUpGjCg63XL3EbpQbC22bqug+9XOyABiKnuuo68X9ct/ynXBmFy6v3C0lz9Z+uyXsB+oFsD2K/5wGvW1y2BFCw39g67XyViD6HiwfOcrtyo5//ncsub65YZjH0Hz7Ml7o5cGzyvt/X8VNa/fwLvOtqxvm55w8vAWsbcHzhgLfMUlsGfZjhCzECrEudGPyzNOovebwI6WV+/BvzVQWIu9zpy3TJ2+x7aem4AfljGNPEuMc2Q76DRx6Oi806OR9nvYYll7HZOO/LxMKJccsRjgUHXFQc4HnWaRzhkjb3WOl8p9TjwE5ZRAT/RWh9QSk23zl+AZYTeW7HclGZiqWGscF0DdqMMG/frFaAZMM9aS5Kvtb6hAexXtda1R9xVsWW/tNa/KqV+BPZi6S/2kdZ6P4Az7xeWps2fKqX2YSlgn9NanwfH3S8ApdQXWG4WmiulkoFXsdQuOm25UVO1KW+Mitkaly1x3wP8QSmVB2QB47TWWlkee/cAsE8pFW/d5Ita6+8dIOZqrVuf8dZBzFuVUkuxNKnMB3YDCx0k5nuBR6wtC7KA8dp694RlIMAlSik3LDdMkx0h5squI0aoxrkxFlitLTVNRW7EgO9gfarNeWdUmVSf6uB72KA4Y7lUX2p5LAy5rtQnI/II1UC/Z0IIIYQQQgghRKPgqIPnCSGEEEIIIYQQwgaS2AshhBBCCCGEEE5MEnshhBBCCCGEEMKJSWIvhBBCCCGEEEI4MUnshRBCCCGEEEIIJyaJvRBCCCGEEEII4cQksRdCCCGEEEIIIZyYJPZCCCGEEEIIIYQTk8ReNBhKqTCl1EWlVG/r+9ZKqfNKqcHGRiaEEM5DylIhhKg9KUuFvSmttdExCFFnlFJTgaeBPsByYJ/W+hljoxJCCOciZakQQtSelKXCniSxFw2OUmolEApooK/WOsfgkIQQwulIWSqEELUnZamwF2mKLxqiD4FuwFwpPIUQosakLBVCiNqTslTYhdTYiwZFKeUD7AHWAaOB7lrri8ZGJYQQzkXKUiGEqD0pS4U9SWIvGhSl1MdAE63175RSCwF/rfXvjI5LCCGciZSlQghRe1KWCnuSpviiwVBKjQFGAdOtk54GeiulJhoXlRBCOBcpS4UQovakLBX2JjX2QgghhBBCCCGEE5MaeyGEEEIIIYQQwolJYi+EEEIIIYQQQjgxSeyFEEIIIYQQQggnJom9EEIIIYQQQgjhxCSxF0IIIYQQQgghnJgk9kIIIYQQQgghhBOTxF4IIYQQQgghhHBiktgLIYQQQgghhBBO7P8Dgju1vWzNdE8AAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "if dlNames:\n", " ciexyplt = ryplot.Plotter(4, 1, 3, figsize=(17,7))\n", " for i,pltaxis in enumerate([[0, 0.9, 0, 0.9],[0.3, 0.65, 0.35, 0.5],[0.52, 0.6, 0.43, 0.46]]):\n", " ciexyplt.resetPlotCol()\n", " #plot monochromatic horseshoe\n", " ciexyplt.plot(i+1, xm, ym, plotCol=['k'],pltaxis=pltaxis)\n", " #plot chromaticity loci for samples\n", " styleSample=['r--', 'g-.', 'y', 'g', 'b-', 'k']\n", " for iSmpl in range(samples.shape[1]):\n", " ciexyplt.plot(i+1,xs[iSmpl],ys[iSmpl], [styleSample[iSmpl]],\n", " label=[samplesTxt[iSmpl]], legendAlpha=0.5,\n", " pltaxis=pltaxis)\n", " \n", " #plot source markers\n", " styleSource=['*', 'o', '^', 'v']\n", " for iSmpl in range(samples.shape[1]):\n", " for iSrc in range(sources.shape[1]):\n", " if iSmpl==0:\n", " legend=[sourcesTxt[iSrc]]\n", " else:\n", " legend=''\n", " ciexyplt.plot(i+1,xs[iSmpl,iSrc],ys[iSmpl,iSrc],\n", " \"CIE chromaticity diagram\", r'x',r'y',\\\n", " ['k'],label=legend,legendAlpha=0.5,\n", " pltaxis=pltaxis, markers=[styleSource[iSrc]],maxNX=5,xAxisFmt=\"%.2f\");\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "It is quite evident that for the two 'daylight' sources (the sun 5900 K and the fluorescent source) the sample colour coordinates are widely scattered over the coordinate space. When the same samples are viewed under 2850 K source illumination (incandescent lamp) the colours tend to cluster towards the yellow - this matches the human experience that incandescent lamps produce yellow colour photographs. Finally, when viewed under sodium illumination the sample colour coordinates converge on the colour of the lamp, meaning that the samples all appear yellow in colour (589 nm) and only differ in shade." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The CIE 1931 chromaticity diagram in colour is shown below." ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "HTML('')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Solid Angles and Spatial Integrals" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Computational radiometry has a strong element of geometry: sources and receivers have size, shape and orientation and are related to each over in some geometrical relationship. The calculation of solid angle is an essential task in most radiometric analyses.\n", "The calculation of a solid angle requires integration across a spatial extent as described in (Sec 2.5.4). Array processing in Python condenses and simplifies most two-dimensional calculations significantly. " ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [ { "data": { "image/svg+xml": [ "\n", " \n", " \n", " \n", " \n", " \n", " image/svg+xml\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " D\n", " \n", " \n", " W\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " R\n", " dw\n", " dd\n", " \n", " \n", " θ\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " H\n", " \n", " \n", " Reference point\n", " \n", "" ], "text/plain": [ "" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from IPython.display import SVG\n", "SVG(filename='images/solidangleflatplate.svg')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The solid angle of a rectangular flat surface, with dimensions $W$ and $D$, as seen from a reference point centered above the surface, is determined by the integral of the projected area of a small elemental area $\\cos\\theta\\,dd\\,dw$ across the full size of the surface:\n", "$$\n", "\\omega_{\\rm s}=\\int_W\\int_D\\frac{dw\\,dd\\,\\cos^{n-2}\\theta}{R^2}\n", "$$\n", "$$\n", "\\omega_{\\rm s}=\\int_W\\int_D\\frac{dw\\,dd\\,\\cos^n\\theta}{H^2}\n", "$$\n", "$$\n", "\\omega_{\\rm s}=\\int_W\\int_D\\frac{dw\\,dd\\,}{H^2}\\left(\\frac{H}{R}\\right)^n\n", "$$\n", "$$\\omega_{\\rm s}=\\int_W\\int_D\\frac{dw\\,dd\\,}{H^2}\\left(\\frac{H}{\\sqrt{w^2+d^2+H^2}}\\right)^n, \n", "$$\n", "where $H$ is the reference point height above the surface, and $n=3$ for the geometrical solid angle and $n=4$ for the projected solid angle. The integral is performed along the $W$ and $D$ dimensions with increments of $dw$ and $dd$. The slant range between the reference point and the elemental area $dd\\times dw$ is $R=H/\\cos\\theta$." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This example calculates the geometric and projected solid angles of a 5 m $\\times$ 5 m floor from a sensor centered above the floor at a height of 3.5 m. The solid angles thus calculated are compared to the (incorrect) $W\\times D/R^2$ approximation of (5 m $\\times$ 5 m)/(3.5 m $\\times$ 3.5 m). We investigate the accuracy of the answer for a variable number of samples. It seems you need at least `500**2` samples." ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Approximated solid aAngle is 2.0408163265306123 sr\n", "\n", "Geometric solid aAngle is 1.3776190916848792 sr [error is -48.14%] with 1001x1001 samples\n", "Projected solid aAngle is 1.2231417346316624 sr [error is -66.85%] with 1001x1001 samples\n", " \n", "Geometric solid aAngle is 1.3767628046966296 sr [error is -48.23%] with 501x501 samples\n", "Projected solid aAngle is 1.2221732303536663 sr [error is -66.98%] with 501x501 samples\n", " \n", "Geometric solid aAngle is 1.3698950234892486 sr [error is -48.98%] with 101x101 samples\n", "Projected solid aAngle is 1.2144328695069617 sr [error is -68.05%] with 101x101 samples\n", " \n", "Geometric solid aAngle is 1.361269842026548 sr [error is -49.92%] with 51x51 samples\n", "Projected solid aAngle is 1.2047779728077308 sr [error is -69.39%] with 51x51 samples\n", " \n", "Geometric solid aAngle is 1.335175107784089 sr [error is -52.85%] with 21x21 samples\n", "Projected solid aAngle is 1.1759711205782946 sr [error is -73.54%] with 21x21 samples\n", " \n" ] } ], "source": [ "import numpy as np\n", "h = 3.5\n", "d = 5.\n", "w = 5.\n", "\n", "wdh2 = w * d / (h * h)\n", "print('Approximated solid aAngle is {} sr\\n'.format(wdh2))\n", "for samples in [1001, 501, 101, 51, 21]:\n", " varx = np.linspace(-d/2, d/2, samples)\n", " vary = np.linspace(-w/2, w/2, samples)\n", " x, y = np.meshgrid(varx, vary)\n", " for n,stext in zip([3., 4.], ['Geometric','Projected'] ):\n", " gv = (1. / ( (x / h) ** 2 + (y / h) ** 2 + 1 ) ) ** (n / 2)\n", " solidAngle = np.trapz(np.ravel(gv), dx=w*d/(samples**2))/(h*h)\n", " error = 100 * (solidAngle - wdh2) / solidAngle\n", " print('{0} solid aAngle is {1} sr [error is {2:.2f}%] with {3}x{3} samples'.\\\n", " format(stext, solidAngle,error, samples))\n", " print(' ')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Experiment a little with the meshgrid and its results. What do these variables look like graphically? Calculate and plot, for each tile: (1) the distance from the reference point, (2) the solid angle of the angle to the reference point, (3) the geometric solid angle of each tile, and (4) the projected solid angle of each tile. Along the way plot the values of x and y as well." ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "distFromRef = np.sqrt(x ** 2 + y ** 2 + h * h)\n", "cosAngle = h / distFromRef\n", "geoSolid = w * d / (samples ** 2) * cosAngle / distFromRef ** 2\n", "prjsolid = geoSolid * cosAngle\n", "\n", "p = ryplot.Plotter(1,2, 3, figsize=(15,10))\n", "p.mesh3D(1, x, y, x, ptitle='Distance from centre\\nalong x-axis', \n", " xlabel='x', ylabel='y', zlabel='Distance', \n", " maxNX=3, maxNY=3, maxNZ=4, alpha=0.5, xInvert=True, yInvert=True);\n", "p.mesh3D(2, x, y, y, ptitle='Distance from centre\\nalong y-axis', \n", " xlabel='x', ylabel='y', zlabel='Distance', \n", " maxNX=3, maxNY=3, maxNZ=4, alpha=0.5, xInvert=True, yInvert=True);\n", "p.mesh3D(3, x, y, distFromRef, ptitle='Distance from reference\\npoint to tile', \n", " xlabel='x', ylabel='y', zlabel='Distance', \n", " maxNX=3, maxNY=3, maxNZ=4, alpha=0.5, xInvert=True, yInvert=True);\n", "p.mesh3D(4, x, y, cosAngle, ptitle='Cosine of angle to tile', \n", " xlabel='x', ylabel='y', zlabel='Cosine', \n", " maxNX=3, maxNY=3, maxNZ=4, alpha=0.5, xInvert=True, yInvert=True);\n", "p.mesh3D(5, x, y, geoSolid, ptitle='Geometric solid angle per tile', \n", " xlabel='x', ylabel='y', zlabel='Solid angle sr', \n", " maxNX=3, maxNY=3, maxNZ=4, alpha=0.5, xInvert=True, yInvert=True);\n", "p.mesh3D(6, x, y, prjsolid, ptitle='Projected solid angle per tile', \n", " xlabel='x', ylabel='y', zlabel='Solid angle sr', \n", " maxNX=3, maxNY=3, maxNZ=4, alpha=0.5, xInvert=True, yInvert=True);\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Compare the projected and geometric solid angles. Note that directly under the reference point the geometric and projected solid angles are equal (because $\\cos(0)=1$), but at the corners the cosine weighting function starts to weigh the projected solid angle down." ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "p = ryplot.Plotter(1,1,1,figsize=(5,5))\n", "p.mesh3D(1, x, y, 100 * (prjsolid - geoSolid) / prjsolid , \n", " ptitle='Normalised difference between\\nprojected and geometric solid angle', \n", " xlabel='x', ylabel='y', zlabel='% Difference', \n", " maxNX=3, maxNY=3, maxNZ=4, alpha=0.5, xInvert=True, yInvert=True);\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Another approach, provided by a student, is to do the integral as two separate summations. The first summation is in `sigmaGSD = sigmaGSD + ....` and the second summation is in `GeoSA = sum(sigmaGSD)`. This approach is perhaps more intuitive to some, but requires a `for` loop [which is perfectly legal, but superfluous in my personal programming mindset]." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1.3776189454252532\n", "1.2231412650040754\n" ] } ], "source": [ "#Credit to Wynand Lambrechts\n", "sampleSize = 1000\n", "D_ = 5.\n", "H_ = 3.5\n", "smallDimension = D_/sampleSize\n", "all_d = np.linspace(-D_/2,D_/2,sampleSize)\n", "all_w = np.linspace(-D_/2,D_/2,sampleSize)\n", "sigmaGSD = 0.\n", "sigmaPSD = 0.\n", "\n", "#THIS EQUATION DETERMINES THE GEOMETRICAL SUMMATION OF EQUATION 2.13 ON PAGE 32\n", "for x in all_w:\n", " sigmaGSD = sigmaGSD + (H_/np.sqrt(np.power((x**2 + all_d**2 + H_**2),(3))))*smallDimension**2\n", " \n", "#THIS EQUATION DETERMINES THE PROJECTED SUMMATION OF EQUATION 2.14 ON PAGE 33\n", "for y in all_w:\n", " sigmaPSD = sigmaPSD + (H_*H_/np.sqrt(np.power((y**2 + all_d**2 + H_**2),(4))))*smallDimension**2\n", "\n", "GeoSA = sum(sigmaGSD) \n", "ProSA = sum(sigmaPSD) \n", "print(GeoSA)\n", "print(ProSA)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Python and module versions, and dates\n" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Software versions\n", "Python: 3.8.3 64bit [MSC v.1916 64 bit (AMD64)]\n", "IPython: 7.26.0\n", "OS: Windows 10 10.0.19041 SP0\n", "matplotlib: 3.4.3\n", "numpy: 1.20.3\n", "pyradi: 1.1.4\n", "scipy: 1.7.1\n", "pandas: 1.3.2\n", "Mon Sep 06 20:49:40 2021 South Africa Standard Time\n" ] } ], "source": [ "try:\n", " import pyradi.ryutils as ryutils\n", " print(ryutils.VersionInformation('matplotlib,numpy,pyradi,scipy,pandas'))\n", "except:\n", " print(\"pyradi.ryutils not found\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "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": "3.8.3" } }, "nbformat": 4, "nbformat_minor": 4 }