{ "cells": [ { "cell_type": "markdown", "id": "5d7d4d30-998a-4af6-8c06-20452639ea23", "metadata": {}, "source": [ "# Calculating solar spectrum from the NOAA database" ] }, { "cell_type": "markdown", "id": "8f375d5b-fc7c-4056-b632-e4186aa4fd77", "metadata": {}, "source": [ "Here, we create a NEMESIS solar file using the solar spectral irradiance from the [National Oceanic and Atmospheric Administration](https://www.ncei.noaa.gov/products/climate-data-records/solar-spectral-irradiance). This product covers a wide range of wavelengths and is widely used in climate models (0 to 200 $\\mu$m). It is based on Version 1 of the NASA NOAA LASP (NNL) solar variability models. These models estimate changes in solar irradiance due to faculae and sunspots, as well as the F10.7 cm solar radio flux.\n", "\n", "Here, we convert the solar irradiance from a given year into a solar file with the NEMESIS format." ] }, { "cell_type": "code", "execution_count": 1, "id": "3aa24fbd-b739-4d50-996c-be35f63927d8", "metadata": {}, "outputs": [], "source": [ "import netCDF4 as nc\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import archnemesis as ans" ] }, { "cell_type": "code", "execution_count": 2, "id": "487717ad-6db8-465a-a7a8-0655ef6368dc", "metadata": {}, "outputs": [], "source": [ "year = 2024 #From 1960 to 2373" ] }, { "cell_type": "markdown", "id": "b54daf45-0b0e-4c49-9dc3-54a89191b27e", "metadata": {}, "source": [ "## Reading the file" ] }, { "cell_type": "code", "execution_count": 3, "id": "452bdbae-1539-4e29-8897-51c51f3d3cc5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "dict_keys(['SSI', 'wavelength', 'Wavelength_Band_Width', 'TSI', 'time', 'TSI_UNC', 'time_bnds', 'SSI_UNC'])\n" ] } ], "source": [ "# Open the file\n", "dataset = nc.Dataset('ssi_v03r00_yearly_s1610_e2023_c20240831.nc', \"r\")\n", "\n", "# Check variables\n", "print(dataset.variables.keys())\n", "\n", "# Access a specific variable\n", "wavelength = dataset.variables[\"wavelength\"][:] #nm\n", "time = np.array(dataset.variables[\"time\"][:]/365. + 1960.,dtype='int32') #years since 1610-01-01\n", "solar_irradiance = dataset.variables[\"SSI\"][:] #(ntime,nwave) W m-2 nm-1\n", "\n", "# Close the dataset\n", "dataset.close()" ] }, { "cell_type": "markdown", "id": "93a0a324-71ba-45be-ae03-4b5eae97b57b", "metadata": {}, "source": [ "## Defining the Stellar class" ] }, { "cell_type": "code", "execution_count": 4, "id": "7564bcbd-468f-4c10-bf72-8376a85fc512", "metadata": {}, "outputs": [], "source": [ "Stellar = ans.Stellar_0()\n", "\n", "Stellar.ISPACE = 1 #Wavelength space\n", "Stellar.NWAVE = len(wavelength) #Number of spectral points\n", "Stellar.WAVE = wavelength /1.0e3 #Wavelength array\n", "\n", "Stellar.DIST = 1.0 #Earth-Sun distance (since this is spectral irradiance at the Earth\n", "Stellar.RADIUS = 6.955e5 #Radius of the Sun (km)\n", "\n", "itime = np.where(time==year)[0][0]\n", "Stellar.SOLFLUX = solar_irradiance[itime,:] * 1.0e3 * 1.0e-4 #Spectral irradiance at the Earth distance in W cm-2 um-1\n", "Stellar.calc_solar_power() #Calculate the solar power in W um-1" ] }, { "cell_type": "code", "execution_count": 5, "id": "a9e3af7b-9d88-4a44-8095-a2582d60d290", "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAxYAAAGGCAYAAADmRxfNAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8g+/7EAAAACXBIWXMAAA9hAAAPYQGoP6dpAABnR0lEQVR4nO3dd3hUZfo38O85U9N7QgIhhF5CFxBBmggWEOzromJ3XSzIT1dY14INK1hfVNa+dqy7KkgLIE1agICGFpIAKaQnM8m0c94/hgyZZNLmTDInyfdzXbmY88yZ59yTZ4bMPU8TZFmWQUREREREpIDo7wCIiIiIiKj9Y2JBRERERESKMbEgIiIiIiLFmFgQEREREZFiTCyIiIiIiEgxJhZERERERKQYEwsiIiIiIlKMiQURERERESnGxIKIiIiIiBRjYkFERERERIp1isRi06ZNmDlzJhISEiAIAr7//vsWPT41NRWzZs1CfHw8goKCMGzYMHz66af1zistLcW8efMQHx8Pg8GAvn374ueff/bRsyAiIiIiUi+tvwNoCyaTCUOHDsVtt92Gq666qsWP37p1K4YMGYJHHnkEcXFx+N///oebb74ZYWFhmDFjBgDAarXi4osvRmxsLFauXImuXbsiKysL4eHhPn42RERERETqI8iyLPs7iLYkCAK+++47zJ4921VmsVjw6KOP4vPPP0dpaSlSUlLwwgsvYNKkSQ3Wc/nllyMuLg7vv/8+AODtt9/GSy+9hD///BM6na6VnwURERERkbp0iqFQTbn33nuxbds2fPHFF9i/fz+uvfZaXHLJJThy5EiDjykrK0NkZKTr+Mcff8TYsWMxb948xMXFISUlBc899xwcDkdbPAUiIiIiIr/qFEOhGpOdnY0PPvgA2dnZSEhIAAA89NBDWLVqFT744AM899xz9R7z1VdfYefOnXjnnXdcZcePH8f69esxZ84c/Pzzzzh69Cj+/ve/w2az4Yknnmiz50NERERE5A+dPrE4cOAAHA4H+vbt61ZusVgQFRVV7/wNGzbg1ltvxYoVKzBo0CBXuSRJiI2NxbvvvguNRoORI0fi1KlTeOmll5hYEBEREVGH1+kTi8rKSmg0GuzevRsajcbtvuDgYLfjjRs3YubMmVi2bBluvvlmt/vi4+Oh0+nc6hgwYADy8vJgtVqh1+tb70kQEREREflZp08shg8fDofDgYKCAlx44YUNnpeamooZM2bghRdewF133VXv/nHjxuGzzz6DJEkQRefUlcOHDyM+Pp5JBRERERF1eJ1i8nZlZSXS0tKQlpYGAMjMzERaWhqys7PRt29fzJkzBzfffDO+/fZbZGZm4vfff8eSJUvw008/AXAOf7r88stx//334+qrr0ZeXh7y8vJQXFzsusY999yD4uJiPPDAAzh8+DB++uknPPfcc5g3b54/njIRERERUZvqFMvNpqamYvLkyfXK586diw8//BA2mw3PPPMMPv74Y5w6dQrR0dE4//zzsXjxYgwePBi33HILPvroo3qPnzhxIlJTU13H27Ztw4MPPoi0tDR07doVt99+Ox555JF6Q6yIiIiIiDqaTpFYEBERERFR6+oUQ6GIiIiIiKh1MbEgIiIiIiLFOvSqUJIk4fTp0wgJCYEgCP4Oh4iIiIjI72RZRkVFBRISElyrmfpCh04sTp8+jcTERH+HQURERESkOjk5OejWrZvP6uvQiUVISAgA4Ndff3XdJv+TJAlZWVlISkryaZZMyrBd1Idtok5sF3Viu6gT20WdKioqMG3aNJ9/Pu7QiUXN8KegoKB6u2iT/0iShMDAQAQHB/M/GRVhu6gP20Sd2C7qxHZRJ7aLOkmSBAA+nyrAFiYiIiIiIsWYWBARERERkWJMLIiIiIiISDEmFkREREREpBgTCyIiIiIiUoyJBRERERERKcbEgoiIiIiIFGNiQUREREREijGxICIiIiIixZhYEBERERGRYqpOLE6dOoUbb7wRUVFRCAgIwODBg7Fr1y5/h0UeHC+x4sGfc7HndJVbuckqobTa4aeoiIiIiKitqDaxKCkpwbhx46DT6fDLL7/g0KFDeOWVVxAREeHv0MiDFzadwZFiKx5fX+BWfv1XObhx5UmYrJKfIiMiIiKitqD1dwANeeGFF5CYmIgPPvjAVZacnOzHiKgxJtu5xKHQbEd0oPtLK6vUioGxxrYOi4iIiIjaiGoTix9//BHTp0/Htddei40bN6Jr1674+9//jjvvvLPBx1gsFlgsFtdxeXk5AECSJEgSvzFvTQaN4Lp9y7encFHPQDxwfpSrzOY41wZ1/yV1YLuoD9tEndgu6sR2USe2izq1VnuoNrE4fvw4li9fjgULFuCf//wndu7cifvvvx96vR5z5871+JglS5Zg8eLF9cpzcnIQGBjY2iF3aoKkAXAuuVh33Iz8kkrUjLbbcSQPwWbZ7TFZWVltGCE1F9tFfdgm6sR2USe2izqxXdTFbDa3Sr2CLMty06e1Pb1ej/POOw9bt251ld1///3YuXMntm3b5vExnnosEhMTsXnzZoSGhrZ6zJ3Zg7/k4ViJrdFzfvxrIgBnlpyVlYWkpCSIomqn+XQ6bBf1YZuoE9tFndgu6sR2Uafy8nJceOGFKCsr8+lnZNX2WMTHx2PgwIFuZQMGDMA333zT4GMMBgMMBkO9clEU+WJuZaIoNHmO2Q4E68+1A9tFndgu6sM2USe2izqxXdSJ7aIurdUWqm3hcePGISMjw63s8OHDSEpK8lNE1Jhm5BUot3DZWSIiIqKOSrWJxYMPPojt27fjueeew9GjR/HZZ5/h3Xffxbx58/wdGnkgoOnMwuZQ5ag7IiIiIvIB1SYWo0aNwnfffYfPP/8cKSkpePrpp/Hqq69izpw5/g6NPGhOj4VdAiRZhkqn9RARERGRAqqdYwEAM2bMwIwZM/wdBjVBlmUcOmNp8rwTJVa89NsZxAZpMbdH68dFRERERG1HtT0W1H6crrA367xl24pwstyOPbnVcHA5ayIiIqIOhYkFKebNyKZqzuMmIiIi6lCYWJBiGi9eRVVMLIiIiIg6FCYWpJgoNGPmdh3ssSAiIiLqWJhYkF9U24FqOydaEBEREXUUTCxIMW+Wj33jkBZ/XXkKEpeeJSIiIuoQmFiQYt7ue2eXgOxSm2+DISIiIiK/YGJBiqVmmrx+7L0/5fowEiIiIiLyFyYWpEh+pR2fHyjzSV2yLMMucWgUERERUXvExIIUKW3G8k5TewU1en+lxVnHP37Nx90/nILN27FVREREROQ3TCyo1ek1jS9H65ABhyTjjzMW5JscOFFqbaPIiIiIiMhXmFhQq9OJjScWNknG6qOVruMVu0paOyQiIiIi8jEmFqRIQylDv2i967auiR6Lr9PL8f9+L3YdHzpj8UVoRERERNSGmFiQIp5mQ9w6PBy1t6fQNtFjsSXb+1WliIiIiEgdmFiQIg4PqzjpNIJbwtHUUChPuHEeERERUfvCxIIUsUv1y4bEGev0WLS8Xq4MRURERNS+MLEgRRx1ehbenBGPHhF6GLTneimammPhiZWJBREREVG7wsSCFKnbY9Ej3Dlp+94xUUgI0eLBsVFNDoUqra7f7fHZft9sukdEREREbYOJBXmt2i7hje1FHu9LDNPh3VldcVGvYGi96LH4b0YF1h6rbPpEIiIiIlIFrb8DoPbrq/QyFFc1vfO2N5O3AeDVbUUIN2qg1wgY0sXoVR1ERERE1DaYWJDXcivszTpP8C6vAAA8uaEAAPDDX7tD42WCQkREREStj0OhyGvN/Zjvi3SgZjK3zGVoiYiIiFSJiQV5rbk9Eb7oaKi2y1h1pAJzVp5Een618gqJiIiIyKeYWFC78ElaKd7cUYxyi4R/rs33dzhEREREVAcTC2o2SZZxIL8aZptzeVixTpfFnedFeHyckjkWNX6ttUKUh82+iYiIiMjPmFhQs/03owKL1uTjUQ89BiPijZjVP9Tj4wSfzLJwx7kWREREROrCxIKabc1RZ6/BkSIrAPeeCF/0SrTEzE+zkZZb1bYXJSIiIqIGMbEgrwlutxvOLFprldh/rStonYqJiIiIqMWYWFCz5JTZcKLU5lbW3B4LJXlFsL7xl6idEy6IiIiIVMEniYXNZkNOTg4yMjJQXFzsiypJZd7ZWb9daycMjfZK1LrvsYkxLbpu/2hDo/d/uLekRfURERERUevwOrGoqKjA8uXLMXHiRISGhqJHjx4YMGAAYmJikJSUhDvvvBM7d+70ZazkR446k6X351VjzTGT67i5PRbRQVo8PzUWDw1uetfuqwaGwqBtvL/j+z8qmqyHiIiIiFqfV4nF0qVL0aNHD3zwwQeYOnUqvv/+e6SlpeHw4cPYtm0bnnjiCdjtdkybNg2XXHIJjhw54uu4qY2FGDRux3X3khAbGfDkNhdDAAbGGpAY3PQ1bx0ejoAmEgsAKKhsOkkhIiIiotal9eZBO3fuxKZNmzBo0CCP948ePRq33XYb3n77bXzwwQfYvHkz+vTpoyhQ8g+HJOOTfaXYmm1u9Ly9eQ2v0CTU6s6oncleOSAE39Xpcbh7VAQsdhkxgVoIgoAAXdO5723fn8L/bkxq8jwiIiIiaj1eJRaff/55s84zGAz429/+5s0lSCXWHKvEyoPlTZ5XZWt4EnVDk7yv6BdcL7EAgGsGhbluN3dFqZIqByICNE2fSEREREStwmerQu3YscNXVZGK5Fb4dphR7d266+7c7YmmmRtkvLuLiwYQERER+ZPPEotrr73WV1UBAJ588kkIguD2079/f59eg5rmiw2uhYZuNyNniAtuXqdaZom1RTERERERkW+1aCjUdddd57FcluVWWWZ20KBBWLt2retYq/Vq5BYpUHc1KG+IDQyFak5WO613MLLKrMgqteFggaXB806W27H6SAWm9wnxPlAiIiIi8lqLPqmvXbsWn3zyCYKD3Zf0kWUZmzZt8mlggDOR6NKli8/rpebz9f5ztZMM0dMEijrX02kE/H10FABgxn+yGq37jR3FGNU1AJGBTECJiIiI2lqLPoFNmjQJISEhmDBhQr37hgwZ4rOgahw5cgQJCQkwGo0YO3YslixZgu7duzd4vsVigcVy7lvt8nLnpGNJkiBJks/j6wwcLcgsGvody7V6PWRZdp0nezi/ytZwW90zKgI/H6lEpFGDLiEa/HLEVO+cx9cX4PXLmIx6o+b3zveKerBN1Intok5sF3Viu6hTa7VHixKLb7/9tsH71qxZoziY2saMGYMPP/wQ/fr1Q25uLhYvXowLL7wQ6enpCAnxPNxlyZIlWLx4cb3ynJwcBAYG+jS+zqKsXERzp+JkZmZ6LM8vEwA4V2w6dTIHVWc30z55Mgd1X4KnzpQgM7PIYz39tUD/Ac7b+4vP1VnbiVJbg3FQ82RlNd4zRG2PbaJObBd1YruoE9tFXczmxrcR8JaiMSN5eXmtNlTp0ksvdd0eMmQIxowZg6SkJHz11Ve4/fbbPT5m0aJFWLBggeu4vLwciYmJSExMRGhoaKvE2dEFnykG8uv3DHiSnJzssbwyvxo4dAYA0D0xEVEBIrKyspDUPRH4Pdft3EGJUUhObnr3vHxdFZBR2KI4qHGSJDnbJSkJouizdR1IAbaJOrFd1Intok5sF3WqGdXja4oSi2nTpmH//v2+iqVR4eHh6Nu3L44ePdrgOQaDAQaDoV65KIp8MXupJXMsGvoda2qVazTn2qJ2ed8oPSYlB+GiXiGe517Uq7Phc9jWyvD9oj5sE3Viu6gT20Wd2C7q0lptoahW2RdrkTZTZWUljh07hvj4+Da7JvlmuVk0sBJU7X0skiP0uKJ/aKMJQwNV1lNl4zhOIiIioramKLEQmrl5mTceeughbNy4ESdOnMDWrVtx5ZVXQqPR4IYbbmi1a1J9Dl/vY1HrNaOt9epraQLT2Cvvw72lLauMiIiIiBRT7bqcJ0+exA033ICioiLExMRg/Pjx2L59O2JiYvwdWqci+bhXyn1Pi3MHUt11ZhXYk1vls7qIiIiIqHlUm1h88cUX/g6B4Jt9LGpX0VAnly/3y6i2td0QPSIiIiJyUjQUSqOpv9wndSzNHQp1Se+mV3ICGn7BKekYufu8CLfjkmoHXt9eBJsvxnERERERUbMoSiz27t3rqzhIpZo7FGpk14CG76xVRUPzcpQMuZrSMxhfXpfoVvbr0UqsOVbpdZ1ERERE1DKqHQpF6tDcjRkbywuaMxRKSY+FIACBuvo5ckmVw/tKiYiIiKhFfJJYVFdXY//+/SgoKKi3RfgVV1zhi0uQnzh8MHm7dhUNrSar13q/wlhDde4+XYVZ/UMQbOCQPSIiIqLWpjixWLVqFW6++WYUFtbfBVkQBDgc/Na4PfPlpGqg4WViA7QtG5XnKazIAA2Ka/VSHC6y4rF1BVh2Gfc+ISIiImptirfdu++++3DttdciNzcXkiS5/TCpaP98nViIDYyF6hGuU1znxb3qTyA/Umz1ul4iIiIiaj7FPRb5+flYsGAB4uLifBEPqYwv8gq5Vi1184rnpsbhQH41pnpICpqrpspgvec82WKXYGhhjwgRERERtYziT1vXXHMNUlNTfRAKqZGCqQ8utedY1K1uSBcj5gwNh6ahiRLNUJOsXNrXc3KyfGcxLPZmzkInIiIiIq8o7rF48803ce2112Lz5s0YPHgwdDr3IS3333+/0kuQH9l9PhRK2QpQntSkJMYGeiXWHjNh7TET/ndjkm8vTEREREQuihOLzz//HL/++iuMRiNSU1Pd9ikQBIGJRTtn9/Emc4IgQPZxZtHQErZERERE1HYUJxaPPvooFi9ejIULF0IUOY69o7H7YPZ2a+9/zbyCiIiIyP8UZwJWqxXXX389k4oOyieJRStnFg3t5l2X2cZ5FkREREStRXE2MHfuXHz55Ze+iIVUqO6c5wijBhHGlm041xp5RUN13n9+JIL1Ii5MCqx3X1k1lz8mIiIiai2Kh0I5HA68+OKLWL16NYYMGVJv8vbSpUuVXoL8yFanx0IQgHljIvF06hk/RdS4ab1DcHGvYAiCgHHdTXh+87mNG7dkm3HNoDA/RkdERETUcSlOLA4cOIDhw4cDANLT093ua+4QFVKvupO3Zdnz0KYuwYpfSj5T87obnxQE1EosPtxbim8PleOTq7spWt6WiIiIiOpT/Glww4YNvoiDVMriYVUoT9Muekbq2yCalntqSiweX1/gOi63SPgorRS3jYjwY1REREREHY/iORY5OTm+iINUyuJhIwu5zgyH0V0DGq0jOrBlczJ8aURC/di+PVTuh0iIiIiIOjbFPRZJSUmIjIzE0KFDMWzYMNeP1WrF66+/jo8++sgXcZIfyLJcr8dChoxeEe69E0H6xvPTpHA9FlwQhSg/Jhh1SbIMkUP1iIiIiHxGcWKRmZmJvXv3Ii0tDXv37sVXX32F06dPAwBCQ0MVB0j+Y21gc7wuIe4T9JszrGhKz2CfxOSNawaFYuVB914Kk1VCiEE9iQ4RERFRe+eTHoukpCTMnj3bVbZt2zbMnTsXTz31lNLqyY8aSizqighQ9wf0W4ZHwGKX8d+MClfZmzuKcWFSoHOCNxEREREp1iq72o0dOxavvfYaXn755daontqID/bGU426vSpbss14fnMhdp2q8lNERERERB2LT3be9qRPnz44ePCg0upJZYxadeywPrSLEeFGEcPjjc06X9NA2E9uKPB8BxERERG1iOKhUMHBwRg4cCCGDx+OYcOGYfjw4UhISMAbb7yBqVOn+iJG8pPaHRb/nBCDT/aV4uFx0X6LpzajVsRHV3VDc7ejaGyidoXFwfkWRERERAopTizWr1+Pffv2Yd++ffj000+xaNEiVFdXAwAuueQSPP744xg8eDAGDx6M/v37Kw6Y/OOC7oG4oHugv8Nw46tN7vIq7UwsiIiIiBRSnFiMHz8e48ePdx1LkoSMjAykpaUhLS0Nv//+O1asWIGCggI4HA6ll6M25GmH7Y7o20PleOTCGH+HQURERNSuKU4s6hJFEQMGDMCAAQNwww03uMrz8/N9fSkin9icZcbfRjkQZmSvBREREZG32mwmblxcXFtdisijMd3cd+FOiTW4bn/3B3fjJiIiIlJCHUv8kCrJZ8dCdZT9qf81MQYGzblnU2mVXLdXHiyHrZn7dhARERFRfUwsqEmNLKjUrgiCAEetiSNjurlPRn9mI5eeJSIiIvKW14lFZmamL+MgFero399flxKKvw4Jcx0fLLC4emmIiIiIqGW8Tix69eqF5ORk3Hbbbfjkk09w8uRJX8ZF1OoMWhF/HRKOT6/pBgCotsuY+Wk2HB1py3EiIiKiNuJ1YrF+/XrMnTsXx48fx1133YWkpCT06dMHd999N7744guuAtUB1Hy87iAjoRpUdzWonw9X+CkSIiIiovbL6+VmJ02ahEmTJgEAqqursXXrVqSmpiI1NRUfffQRbDYb+vfvj4MHD/oqVmprnfSL+/351ZjZP9TfYRARERG1Kz7Zx8JoNGLKlCkYP348Jk+ejF9++QXvvPMO/vzzT19UT37WUSZvN9e2nCp/h0BERETU7ihaFcpqtWLTpk1YvHgxJk+ejPDwcPztb39DSUkJ3nzzTU7wbuc6YodFc+dm7zxpbt1AiIiIiDoYrxOLKVOmICIiAn//+99RUFCAu+++G8eOHUNGRgZWrFiBm266Cd27d/dZoM8//zwEQcD8+fN9VidRDW2dd8LLWwr9EwgRERFRO+V1YrF582ZERUVhypQpuOiii3DxxRcjPj7el7G57Ny5E++88w6GDBnSKvWTZ51l8jYAvHtFV/xzQgzGJjp35zbZZKTnV/s5KiIiIqL2w+vEorS0FO+++y4CAwPxwgsvICEhAYMHD8a9996LlStX4syZMz4JsLKyEnPmzMGKFSsQERHhkzqpmTriWKgGxAZrcUH3QNw+4txr7Ps/y/0YEREREVH74vXk7aCgIFxyySW45JJLAAAVFRX47bffsGHDBrz44ouYM2cO+vTpg/T0dEUBzps3D5dffjmmTp2KZ555ptFzLRYLLBaL67i83PnBUJIkSJKkKI7OZl9eNR5b70wOBUFo9PfX0t9tzfn+bhNP148wnsu1KywSHA4HhE4ye10t7ULnsE3Uie2iTmwXdWK7qFNrtYdPVoUCnIlGZGQkIiMjERERAa1Wiz/++ENRnV988QX27NmDnTt3Nuv8JUuWYPHixfXKc3JyEBgYqCiWzsJsB/Qi8NiOcy8NWZY8TMQ/d7+3k/SzsrK8epwSMjSoGdzVcNzO53awwILPdmThgrhO1HUD/7QLNY5tok5sF3Viu6gT20VdzObWWaTG68RCkiTs2rULqamp2LBhA7Zs2QKTyYSuXbti8uTJeOuttzB58mSvA8vJycEDDzyANWvWwGg0NusxixYtwoIFC1zH5eXlSExMRGJiIkJDuS9BU8otDjzwzWmEG0UA5zJZQRCRnFxnIv62HNfN5OTkFl1HkiRkZWUhKSkJoqhoYbIWE7Y3HffYk4WuJWe/PK7BxYPjERvksxxctfzZLuQZ20Sd2C7qxHZRJ7aLOtWM6vE1rz8thYeHw2QyoUuXLpg8eTKWLVuGSZMmoVevXj4JbPfu3SgoKMCIESNcZQ6HA5s2bcKbb74Ji8UCjcZ9x2SDwQCDwVCvLlEU+WJuhoxC52Tl0mr37jEBaPT35+3v1t/t0tC1rQ73HorH1p3Bitld2yIkVfB3u1B9bBN1YruoE9tFndgu6tJabeF1YvHSSy9h8uTJ6Nu3ry/jcbnoootw4MABt7Jbb70V/fv3xyOPPFIvqSDlOteAn4ZFBbi/LXIr7X6KhIiIiKj98CqxyM7Oxt13393s80+dOoWuXVv2jW9ISAhSUlLcyoKCghAVFVWvnHxDaiCz6CRzl11uGxEOUQBWHa10lZVWOxBuZDJLRERE1BCv+kFGjRqFu+++u9FJ1WVlZVixYgVSUlLwzTffeB0g+V9DCUdHFWzQ4N7zo/DE5FhX2Y0rT0Jq7rbdRERERJ2QVz0Whw4dwrPPPouLL74YRqMRI0eOREJCAoxGI0pKSnDo0CEcPHgQI0aMwIsvvojLLrvMJ8Gmpqb6pB7yrKEPznXnHLRnLXkmg+Pc5+tY7DICdJ2s+4aIiIiombzqsYiKisLSpUuRm5uLN998E3369EFhYSGOHDkCAJgzZw52796Nbdu2+SypIGprRq2IgTHnkouOlGARERER+ZqiNTQDAgJwzTXX4JprrvFVPORHnW3IU3P0iNDh0Bnnpos3rjyJH+d07zQb5hERERG1BNf9IhfmFfX1jjzXYyED+OfafP8FQ0RERKRiTCzIhXOT67uoZ5Db8YF8C0xWqYGziYiIiDovJhYEwLnr9q9HK/wdhupoxPrDnn4/ZYbMLIyIiIjIDRMLAgA8nXoG+/Mt/g5Dlf5vXJTb8StbirA1x+ynaIiIiIjUiYkFAQD+OMOkoiGTk4Px3znd3cp+OVzZwNlEREREnZPixGLu3LnYtGmTL2IhUq26K0Gl5VVzwzwiIiKiWhQnFmVlZZg6dSr69OmD5557DqdOnfJFXESqd8bk8HcIRERERKqhOLH4/vvvcerUKdxzzz348ssv0aNHD1x66aVYuXIlbDabL2IkUqXbvz+FXw5zwjsRERER4KM5FjExMViwYAH27duHHTt2oHfv3rjpppuQkJCABx980LUjN6nT8RKrv0NoF+YOC69X9tbvxW0fCBEREZEK+XTydm5uLtasWYM1a9ZAo9Hgsssuw4EDBzBw4EAsW7bMl5ciH1rwS66/Q2gXrk0Jw1fXJdYrTy+o9kM0REREROqiOLGw2Wz45ptvMGPGDCQlJeHrr7/G/Pnzcfr0aXz00UdYu3YtvvrqKzz11FO+iJdagZ37vTVboF7E1QND3cpOl3PIHxEREZFWaQXx8fGQJAk33HADfv/9dwwbNqzeOZMnT0Z4eLjSSxGpwuA4I745VO46/l9GBS7uFVxv5SgiIiKizkRxj8UDDzyAkydP4q233nJLKmRZRnZ2NgAgPDwcmZmZSi9FpAp2yX2Z2eMlNmzJ5oZ5RERE1LkpTiyefPJJVFbW3yysuLgYycnJSqsnUh2tWL9n4r09JSi3cPlZIiIi6rwUJxZyA5uEVVZWwmg0Kq2eSHWGxxtxQWIgZvUPwc3DwhGgE3DG5MBjawtgc3DTPCIiIuqcvJ5jsWDBAgDOHYkff/xxBAYGuu5zOBzYsWOHx/kWRO2dRhTwz4kxruPzuwXgkV/zcazEirS8aozqGuDH6IiIiIj8w+vEYu/evQCcPRYHDhyAXq933afX6zF06FA89NBDyiMk8qHL+4bgvxkVPv3w3z1cj/MTA7DmmAnp+UwsiIiIqHPyOrHYsGEDAODWW2/Fa6+9htDQ0CYeQeR/t42IwHldAzAo1uDTelPijM7EgntaEBERUSeleLnZDz74wBdxELUJnUbAyATf9ygMjnXOJzpSZEWlVUKw3qd7TxIRERGpnleJxYIFC/D0008jKCjINdeiIUuXLvUqMKL2JDZYi64hWpyqsOOJ9fl45qI4BOiYXBAREVHn4VVisXfvXthsNtfthnDDMOpMFoyLxpPrC5BRaMW/d5fgvvOj/B0SERERUZvxKrGomV9R9zZRZ9Yv2oBFE2Lw6Np8rD5aid6RelzaN8TfYRERERG1CY7VIPKhIV2M+MvgMADA//u9GJtOmPwcEREREVHbUJxYVFVVwWw2u46zsrLw6quvYvXq1UqrJmqX/jokDJf2CYYM4JUthThZZvN3SEREREStTnFiMWvWLHz88ccAgNLSUowZMwavvPIKZs+ejeXLlysOkKi9EQQBfxsViYExBjhkYNfpKn+HRERERNTqFCcWe/bswYUXXggAWLlyJeLi4pCVlYWPP/4Yr7/+uuIAqXWUVjvw4M+5eHN7kb9D6ZA0ouDaKO/QGYufoyEiIiJqfYr3sTCbzQgJcU5Q/fXXX3HVVVdBFEWcf/75yMrKUhwgtY4bV54EABwptvo5ko5rwNlN+LZmm7El24QLEgO5UhoRERF1WIp7LHr37o3vv/8eOTk5WL16NaZNmwYAKCgo4G7c1Kn1idS7bi/ZVIgt2eZGziYiIiJq3xQnFo8//jgeeugh9OjRA6NHj8bYsWMBOHsvhg8frjhAovbKoBWRcrbXAgDWH+cKUURERNRxKR4Kdc0112D8+PHIzc3FsGHDXOUXXXQRrrzySqXVk8rpNRza05gF46Kx7lglPt1fhj25VaiwOBBi0Pg7LCIiIiKfU5xYAIDRaMT69evx1ltvAQAGDRqE2267DWFhYb6onnzAbJOgEwXofJQIvDS9C97fU4I7R0b4pL6OKjZIixuGhGNrjhmZJTb8N6MCfx0S7u+wiIiIiHxO8VCoXbt2oVevXli2bBmKi4tRXFyMpUuXolevXtizZ48vYiSFTFYJ132Zgzt/OOWzOgfEGPDS9C7oG21o+mTCdSnOJHvlwXKk51f7ORoiIiIi31OcWDz44IO44oorcOLECXz77bf49ttvkZmZiRkzZmD+/Pk+CJGUyih0LndaaHb4OZLOa3z3QAzpYoTVIWPRmnzsz2NyQURERB2LT3osHnnkEWi150ZVabVa/OMf/8CuXbu8rnf58uUYMmQIQkNDERoairFjx+KXX35RGm6nJHIahN8JgoB/TojBqK4BkAH8fLjC3yERERER+ZTixCI0NBTZ2dn1ynNyclz7W3ijW7dueP7557F7927s2rULU6ZMwaxZs3Dw4EEl4XZKIvdOUIVgvYgbh4YDAHacNMNklfwbEBEREZEPKU4srr/+etx+++348ssvkZOTg5ycHHzxxRe44447cMMNN3hd78yZM3HZZZehT58+6Nu3L5599lkEBwdj+/btSkPudGr3WEiy7L9ACD0jdOgepoNNAjae4PKzRERE1HEoXhXq5ZdfhiAIuPnmm2G32wEAOp0O99xzD55//nnFAQKAw+HA119/DZPJ5NonwxOLxQKLxeI6Li8vBwBIkgRJ6sTfDtdKJmx2yauVoXz5+6upq7O2yfTeQVixuxQfp5ViTFcjIgLUsfxsZ28XNWKbqBPbRZ3YLurEdlGn1moPQZZ98xW22WzGsWPHAAC9evVCYGCg4joPHDiAsWPHorq6GsHBwfjss89w2WWXNXj+k08+icWLF9cr/+yzz3wST3uVWQG8mu7MIV8abYdeAzywrWU55Wtj7a0RWqdkdQCL92pQaXMmeH8b4MCAcPYkERERUdswm83461//irKyMoSGhvqsXp/sYwEAgYGBGDx4sK+qAwD069cPaWlpKCsrw8qVKzF37lxs3LgRAwcO9Hj+okWLsGDBAtdxeXk5EhMTkZiY6NNfWntjLbQA6QUAgMSkpLNj+3NbVEdycrLP4pEkCVlZWUhKSoIoKh6N1y7drTXhla3FAICD5hBcNjzKzxGxXdSIbaJObBd1YruoE9tFnWpG9fiaTxKLdevWYd26dSgoKKjXtfL+++97Xa9er0fv3r0BACNHjsTOnTvx2muv4Z133vF4vsFggMFQf18FURQ79YtZqzn33NdlmrFiV0mL62iN319nbpfJPUMQH6LHQ6vzsOd0FRyy7zYvVKozt4tasU3Uie2iTmwXdWK7qEtrtYXiWhcvXoxp06Zh3bp1KCwsRElJiduPL0mS5DaHgpqn9sdVb5IKah19o/UIN4ow2WQ8lVrAVaKIiIioXVPcY/H222/jww8/xE033eSLeFwWLVqESy+9FN27d0dFRQU+++wzpKamYvXq1T69TmfA0fvqJAoCLugeiJ8PV2JvbjXe2lGEf1wY4++wiIiIiLyiOLGwWq244IILfBGLm4KCAtx8883Izc1FWFgYhgwZgtWrV+Piiy/2+bU6utwKTrxWq9tGRCAqQItP9pViU5YZM/tbMCCm/nA+IiIiIrVTPBTqjjvuwGeffeaLWNy89957OHHiBCwWCwoKCrB27VomFV568bdCf4dADTBqRVw/OAxTewUBAF7bVohqO4dEERERUfujuMeiuroa7777LtauXYshQ4ZAp9O53b906VKllyDq8G4fEYE9p6txstyOVUcqMXtA513FjIiIiNonxYnF/v37MWzYMABAenq6232CoI5VbojULsSgwcW9gvFlehlOV9j8HQ4RERFRiylOLDZs2OCLOIg6vTCjc2RiWTWHQhEREVH747MN8ohImTCDBgBwosSKFbuKodMIuKJfCCID+TYlIiIi9fPqE8uCBQvw9NNPIygoyG2na084x4KoeWp6LE5V2HHqzwoAgM0h487zIv0ZFhEREVGzeJVY7N27FzabzXW7IZxjQdR8oUZNvbK8Si4VTERERO2DV4lF7XkVnGNB5BthhvqrPxeaHH6IhIiIiKjlfDJ4u7q6Gvv370dBQQEk6dzEU0EQMHPmTF9cgqjDCzV46LEw2bHjpBlDuxhh1CredoaIiIio1ShOLFatWoWbbroJRUVF9e4TBAEOB79xJWoOnUaAQSPA4pBdZSarhKdTz6BvlB4vX9IFIocXEhERkUop/gr0vvvuw3XXXYfc3FxIkuT2w6SCqGXs0rmkQq85l0QcLrLi6/Ryf4RERERE1CyKE4v8/HwsWLAAcXFxvoiHqFOr1VmBmED3oVH/2VeKzVmmNo6IiIiIqHkUJxbXXHMNUlNTfRAKEdWmq9VjMTk5CDKAFzcX4oc/2XNBRERE6qN4jsWbb76Ja6+9Fps3b8bgwYOh0+nc7r///vuVXoKoUyqtPjeUcP7YKAToBPx8uBIrdpVgX2417hkdiZggbp5HRERE6qD4U8nnn3+OX3/9FUajEampqW57VwiCwMSinZjaKwhrj3GYjb/dNiIC7+8pwa3Dw5FRZMXWbDMiAzTQiALuGRWJ2CAtPtxbit9PVcGxowiLp3AIIhEREamD4sTi0UcfxeLFi7Fw4UKIIpfDbK+GdwlgYqECVw4IwbjugYgN0qC4yoGYQA0u6xsCwJmoXzMoDN1CdXhm4xmk51tgc8huQ6aIiIiI/EVxJmC1WnH99dczqWjv+NlUFQRBQFywFoIgICpQizvPi0TXUPfhhWO6BSDMIMLikHG4yOKnSImIiIjcKc4G5s6diy+//NIXsRBRMwiCgMFxRgDAyoPlOF5ihSTLTTyKiIiIqHUpHgrlcDjw4osvYvXq1RgyZEi9ydtLly5VeglqA4NjDf4OgVpgSBcjfss2Y+epKuw8VYXBcQY8NSWOw6KIiIjIbxQnFgcOHMDw4cMBAOnp6W73Cdwl2O/kZn6THRmoxSdXd8PGEyb8e3dJK0dFSk1ODkJWqRV7Tlcjt9KOA/kWfLKvFLeNiPB3aERERNRJKU4sNmzY4Is4qBVkFFrwn32lzT4/IkDjttszqVeATsQ9o6MAAJuzTHhhcyFSM024dXg4E3oiIiLyCy6C34H936o8f4dAbWB01wBoRaC4yoH8Sju6hOiafhARERGRjylOLJ566qlG73/88ceVXoKIGmHQiugVqUdGoRUrD5YjOkiDwXFGDIo1+js0IiIi6kQUJxbfffed27HNZkNmZia0Wi169erFxIKoDQyMMSKj0IpVRysBAAG6ciyfkYBo7sxNREREbUTxp469e/fWKysvL8ctt9yCK6+8Umn1RNQMKXEGfPfHueMqm4wVu0uwaEKM/4IiIiKiTqVVdrULDQ3F4sWL8dhjj7VG9URUx6iuAbjrvAi8MC0Or18WDwDYnmOG2Sr5OTIiIiLqLFptu+yysjKUlZW1VvVEVIsoCLiifygGxRrRM1KPhBAtHDJw3Vc5ePm3Qn+HR0RERJ2A4qFQr7/+utuxLMvIzc3FJ598gksvvVRp9UTkhZEJATidUQEASD1hwg1DwtA1lKtFERERUetRnFgsW7bM7VgURcTExGDu3LlYtGiR0uqpFU1ODsKGTJO/w6BWMLpbAP57NrEAgHXHK3HzMG6eR0RERK1HcWKRmZnpizjID5q7F94TkzgBuL0Z1sWIW4eHI7vMhnXHTfjmYDlMVglzh0UgUN9qIyCJiIioE+NalJ2Y2MwdmruGcQhNeyMIAq4eFAabQ4bZJmFbThV+OlyJfXnVeH5aF4QbNf4OkYiIiDoYrxKLBQsWNPvcpUuXenMJagNiM3ssmnkaqZBOI+DRibHYl1eFZVuLcLLcjn+tzceTk2O5xwURERH5lFefLDztXeGJ0MxvxKltvHZZPL48UIatOWYAgOhhRIynZIOt2P4N7RKAZ6fG4ZFf83Ci1IYFq/Lwr4kx6Btt8HdoRERE1EF4lVhs2LDB13GQj20/mzzU1itSj5uGhbsSC8FDyuCxF4OZRYfQNVSHVy6Jx+INBcgus+H/VuXh0r7BuGdUJL8EICIiIsU4i7ODembjmSbP8ZREeJp34SkBofYpLliLl6d3wfjugZAB/Hy4Ev87XNHk44iIiIiawsSiE/OcWNQvY1rRsQTqRSycEIO7znMuP7tiVwne210CSZb9HBkRERG1Z6pNLJYsWYJRo0YhJCQEsbGxmD17NjIyMvwdVoei8ZBFeFwpiplFhzSjXwim9Q6GJAPf/VGO5TtLwNyCiIiIvKXaxGLjxo2YN28etm/fjjVr1sBms2HatGkwmbihm6+wx6JzEwUB958fhYfHRUMUgNVHTThaztYmIiIi76h2vclVq1a5HX/44YeIjY3F7t27MWHCBD9F1f5FBZ7bv6C5iQV1bBOTg3DojAU/Ha7ALzkiLh7KbgsiIiJquXazj0VZWRkAIDIy0if1dVaBOhH/npUArUbAL4cr693vefI2dXTXpoRi9dEKHKsQ8PmBckQFajG1VzB0zd2enYiIiDq9drGPhSRJmD9/PsaNG4eUlJQGz7NYLLBYLK7j8vJy1+MlSfJJLO1Zze8gNqim10Kud1/tshqy7NvfX01dbBP1iDSKmNQjEGuPm/FFuvN9s/poBZ6cHINQA3fp9he+V9SJ7aJObBd1YruoU2u1R7vYx2LevHlIT0/Hb7/91uh5S5YsweLFi+uV5+TkIDAwsLXCU6n6TZuZmel2XFYqomaaTc19hSUCAPcPkjk5OSjX+z7CrKws31dKXhsZAqyt9bo5WmzDo6tP4a7+DgTr/BgY8b2iUmwXdWK7qBPbRV3M5vr7nfmCaudY1Lj33nvxv//9D5s2bUK3bt0aPXfRokVuw7TKy8uRmJiIxMREhIaGtnao6rItp15RcnKy23FEZRlwstztvmJDFfBnodt53bt3R2SA7761liQJWVlZSEpKguhp+2/yiyRJwuXF2bDqQnBZ3xA8tv4MsiolLDtkwMvT43z6GqDm4XtFndgu6sR2USe2izrVjOrxNZ8lFocOHUJ2djasVqtb+RVXXOFVfbIs47777sN3332H1NTUeh+KPTEYDDAYDPXKRVHkixmo9zuoPZ+i5j6tpv7vSdNKvz+2i/pM6yYjOTkKoijihWlxeGbjGeRW2PHurlIsmhDNHbr9hO8VdWK7qBPbRZ3YLurSWm2hOLE4fvw4rrzyShw4cACCIEA+uxB+zQcQh8PhVb3z5s3DZ599hh9++AEhISHIy8sDAISFhSEgIEBp2NSAPlH1EzPqnJLC9Vg0IQYP/pyLrTlmvLG9GHOHhyPMyJ4LIiIiqk9xuvLAAw8gOTkZBQUFCAwMxMGDB7Fp0yacd955SE1N9bre5cuXo6ysDJMmTUJ8fLzr58svv1QaMp3laQWoYL2IL65LxKuXdnGV8UvqzqtnhB53j4qEAODXY5W464dTOFFibfJxRERE1Pko7rHYtm0b1q9fj+joaFc31/jx47FkyRLcf//9zV5Bqi6ZWwB7ray6eb1EDSUMwXqRy4ySy2V9QxAfosWKXSXILrNh2dYiPDE5BpGBqp+iRURERG1IcY+Fw+FASEgIACA6OhqnT58GACQlJSEjI0Np9eSFpVsL65Vd0L3+qljNTR2YYtDw+AA8OzUOIXoRx0qsuPOH0zhUUO3vsIiIiEhFFCcWKSkp2LdvHwBgzJgxePHFF7FlyxY89dRT6Nmzp+IAqeV2n67/gW/hhdH1yhob4sT+IqorIkCDJ6fEok+kHhaHjBd+K0RBpd3fYREREZFKKE4s/vWvf7mGLT311FPIzMzEhRdeiJ9//hmvv/664gDJNzzNp0iJNTbrsZxjQTX6RRvw3MVx6BaqRZHZgQWrclFgYnJBREREChMLm82GF1980bUbdu/evfHnn3+isLAQBQUFmDJlik+CpNbRP8aAF6bF4cOrujZ6HvMKqi1AJ+Lpi+LQPUyH0moJP/zROmthExERUfuiKLHQ6XTYv39/vfLIyEiud9/Gdp6qwoH8amQUWlr0uEGxRkR7moRbaywUW5LqignS4tYREQCAH/6swN//exqZXC2KiIioU1M8FOrGG2/Ee++954tYyEul1Q4s3lCARWvysczDxG3FmCSSByPijYgNcu5pkV1mw3ObzsBslfwcFREREfmL4vUi7XY73n//faxduxYjR45EUFCQ2/1Lly5VeglqQqXl3Ie5smoffbATPN4kctGIAhaMi8b//qzAb9lm5FbY8WFaCf4+OsrfoREREZEfKE4s0tPTMWLECADA4cOH3e7jcKi2UXvPiSq7e2IxqmsAHvGwIlSTuCwUNUNKrBEpsUbsz6vGP9fm4+fDlegSrMPsASEeFwwgIiKijktxYrFhwwZfxEEK1P78VievwL8mxkAjKvuAx4+H1JQhXYy4rG8wfj5ciff3lMBkdeCmYRH+DouIiIjakOLEIjs7G4mJiR57J7Kzs9G9e3ell6AmSLV2KR/VNQA7T1W5jhXmFE7MLKgZ/jYqEl1DdFixuwRfHyyHzQFoROcqUtN7ByPMqPF3iERERNSKFCcWycnJyM3NRWxsrFt5UVERkpOT4XA4lF6CmlArr4Be454FeDscrfZIKOYV1ByiIGDWgFAcK7Fi/XETvq21DO2GTBOeuSgWUZ5WICMiIqIOQfGqULIse/zwWllZCaOxeRuwkTJSrSxgS7bZ5/VzqDy1xP3nR+HOkREY0sWIqb2CEKQXkVNmw/0/5eKnjArYJU7gISIi6oi8/vpwwYIFAJzfiD/22GMIDAx03edwOLBjxw4MGzZMcYDUNH5OIzXRis6ei1kDQgEA16c4l6LNLLFh+c5i7M+vxiMXRnNyNxERUQfjdWKxd+9eAM4eiwMHDkCv17vu0+v1GDp0KB566CHlEVKTas+x8BUOhSJfiQ/R4ZVL4rHqSAXe31OCLdlm3PPjadwzOhLD4gP8HR4RERH5iNeJRc1qULfeeitef/11hISE+CwoapnW7rHgssGklF4j4Ir+oQjRi3htexFOVdixeEMBHp0Yi/O6MrkgIiLqCBTPsejTpw++/vrreuXvv/8+XnjhBaXVUzO0QocFeymoVUzuGYyPruqG87sFwCYBT24owP0/ncan+0ph4q7dRERE7ZrixOLdd99F//7965UPGjQIb7/9ttLqqRk4FIrakzCjBgsnxOCC7s55WcdLbPj8QBkWrslDuYWryBEREbVXihOLvLw8xMfH1yuPiYlBbm6u0uqpGTh5m9obrSjgkfHReOaiWNw7JhLhRhGZJTY8k3oGNgdf0ERERO2R4kXlExMTsWXLFiQnJ7uVb9myBQkJCUqrp2Zo/TkWrVs/dU4aUXBN3h4QY8DDq/Nw6IwFd/xwClpRwKV9gnHNoDA/R0lERETNpTixuPPOOzF//nzYbDZMmTIFALBu3Tr84x//wP/93/8pDpCaJqMVMotaVTKvoNaWFK7Hw+OisWRzIYrMzuFQn6SVYky3QCSG6fwcHRERETWH4sTi4YcfRlFREf7+97/DarUCAIxGIx555BEsWrRIcYDUNI4coY5gVLdAfHBlVxzIr8a7u0pQXOXAy1sK8bdRkUjPr8bgOCP6xxj8HSYRERE1QHFiIQgCXnjhBTz22GP4448/EBAQgD59+sBg4AeAtuJp7vagWAPuGxPlk/o5FIraSphRg/FJQegVqcf8X/JwrNiKh1fnAQDCjSI+uLIbdBq+IImIiNRI8eTtGsHBwRg1ahRSUlKYVLQxT6tChehFdPPREBJ+jKO2Fh+iw5OTYxEXpIHu7P9SpdUS/r27GCdKrZBbY41lIiIiUsQnicXmzZtx44034oILLsCpU6cAAJ988gl+++03X1RPTfD0GSs5Ql+/kKgdGRBjwL9nd8V3f03CXwY7J3H/dLgS9/4vF/f+lIvP9pdib24VkwwiIiKVUJxYfPPNN5g+fToCAgKwZ88eWCwWAEBZWRmee+45xQFS0zzNsRiZ4LvdjLnzNvlLzWvvsj7BiA/RIjJAA4NGQFapDZ/tL8Nj6wrw6Np8bq5HRESkAooTi2eeeQZvv/02VqxYAZ3u3NCbcePGYc+ePUqrp2bw9IWtRmHL8jtgUpPIQC1WzOqKj6/uho+u6oq5w8IxsUcgDBoB+/MtmLMyB89vOoO8Cpu/QyUiIuq0FE/ezsjIwIQJE+qVh4WFobS0VGn11Aye5liICnsZIow+m35D5FPBBg2uTXEOjTpebMXi1AIUmR34LduM3aercMOQcIzuGuCzOUZERETUPIoTiy5duuDo0aPo0aOHW/lvv/2Gnj17Kq2emsFTj4WocPRSZKAWi6fEIkDLYVCkXj0j9fj3rK44WmzFh3tLcLDAgvf3lOD9PSWYnByEe0ZHIlDHJJmIiKgtKP6Le+edd+KBBx7Ajh07IAgCTp8+jU8//RQPPfQQ7rnnHl/ESE3wNMfCFytyjkwIwMBYo/KKiFqRTiNgQIwBz06Nw83DwjEo1rkq3YZMEx78ORc7T5rhaO3t6YmIiEh5j8XChQshSRIuuugimM1mTJgwAQaDAQ899BDuu+8+X8RITWiNoVBE7Y1WFHBdShiuSwnDH2csWLLpDE5V2LE49QwMGgEpcc69XaKDFP+3R0RERB4o7rEQBAGPPvooiouLkZ6eju3bt+PMmTN4+umnfREfNYOn72JFjv6gTmxAjAH/b0Y8Zg8IQahBhMUhY/fpavzf6jyYuYIUERFRq/DZV3d6vR4DBgwAwOVJ25rk4XOS0jkWRO1dsEGDO0ZG4tbhEThabMWSTWdQaHbguq9yEKIXMa57IAbFGXBhUhC0fMMQEREp5pPvtd977z2kpKTAaDTCaDQiJSUF//73v31RNTWD5KHPQsPkjggAoBEF9Is2YEJSkKuswiph1dFKvLKlCPf89zQ+318Km6fJSkRERNRsihOLxx9/HA888ABmzpyJr7/+Gl9//TVmzpyJBx98EI8//rgvYqQmeJqXyi9gidyd1/XcppEBWgGz+juHSeVW2PHp/jIs3VqIkioH98IgIiLykuKhUMuXL8eKFStwww03uMquuOIKDBkyBPfddx+eeuoppZegJnhebpaZBVFtA8+uFgUAj06MwbD4AMwZEo71mSb8e3cxNmeZsTnLDAC4eVg4rh4YCg0zdCIiomZT3GNhs9lw3nnn1SsfOXIk7Ha7oro3bdqEmTNnIiEhAYIg4Pvvv1dUX0dVsypUfMi5PJF5BZE7rSjgpeld8MiF0RgW7+y9CNSLmNEvBP+aGIuYQI3r3I/TSnHjypN4ZUshtmSbUGXjhG8iIqKmKE4sbrrpJixfvrxe+bvvvos5c+YoqttkMmHo0KF46623FNXT0dUMhQo1nGtO5hVE9Q2IcU7Wruu8rgFYMbsrPrm6G+46LwKhBhEVVgkbMk1YsqkQN648iU/SSlBucfghaiIiovbBJ6tCvffee/j1119x/vnnAwB27NiB7Oxs3HzzzViwYIHrvKVLl7ao3ksvvRSXXnqpL0Ls0ExcPpNIMa0oICJAgyv6h+LyviH4o9CC7Tlm7MipQm6lHV+ml+PbQ+UY1z0Il/QNxqAYA1fAIyIiqkVxYpGeno4RI0YAAI4dOwYAiI6ORnR0NNLT013n8Q9w6/lgbykAIKPQ6irT+WLrbaJOSiMKSIk1IiXWiNtHyNiWU4UvD5ThWIkVqSdMSD1hQo9wHS7oHojh8QHoH63n/3FERNTpKU4sNmzY4Is4fMJiscBisbiOy8vLAQCSJEHytNlDB3T3eeEQBAFGDVT7nGviUmt8nRXbpWHndzNiTFcDjhbbsPpoJTaeMONEqQ0nSsvw2f4y9IvS48oBITivawD0Pkzq2SbqxHZRJ7aLOrFd1Km12sPrxGLbtm0oKirCjBkzXGUff/wxnnjiCZhMJsyePRtvvPEGDAZDI7X41pIlS7B48eJ65Tk5OQgMDGyzONreuWYcqCsEAGRmnvFXMM2WlZXl7xDIA7ZLw7QALo8FJkcCaUUCMkoFHCoVkFFkxfO/FSFAI+O8GBnj4yR08eF/OWwTdWK7qBPbRZ3YLupiNptbpV6vE4unnnoKkyZNciUWBw4cwO23345bbrkFAwYMwEsvvYSEhAQ8+eSTvoq1SYsWLXKb01FeXo7ExEQkJiYiNDS0zeJoc9tyXDeTk5P9GEjzSJKErKwsJCUlQRR9skcj+QDbpWUG9XH+W2R24L8ZFdiUZUah2YHNeQI254kYHGfAgGgDJvUIRLcwnVfXYJuoE9tFndgu6sR2UaeaUT2+5nVikZaWhqefftp1/MUXX2DMmDFYsWIFACAxMRFPPPFEmyYWBoPBYw+JKIod9sVcUuW+Sk17ep4duV3aM7ZLy8QEi7htZCRuGRGBtNxq/Hy4Ar+fqsKBfAsO5Fvw/Z8VuKJ/CJLD9egdpUfX0JYnGWwTdWK7qBPbRZ3YLurSWm3hdWJRUlKCuLg41/HGjRvdVnAaNWoUcnJyPD202SorK3H06FHXcWZmJtLS0hAZGYnu3bsrqrujeH6z+oc8EXUGoiBgREIARiQEoKDSjs1ZJvx+qgoHCyxYefDcN0Mz+4Xgop5BiA/RIUjPP7JERNRxeJ1YxMXFITMzE4mJibBardizZ4/b/IaKigrodN51/9fYtWsXJk+e7DquGeY0d+5cfPjhh4rq7igOFliaPomI2lRssBZXDwrDlQNDsTXbjNRME0qqHcgotOK/GRX4b0YFYgI1uHFoOIw6AX0iDYgN9snq30RERH7j9V+yyy67DAsXLsQLL7yA77//HoGBgbjwwgtd9+/fvx+9evVSFNykSZMgn91VmoiovREFAeOTgjD+7KZ8n+8vxaf7ywAAZ8wOLNtWBMC5oeWQLkZMSArExOQgGLXsySAiovbH68Ti6aefxlVXXYWJEyciODgYH330EfR6vev+999/H9OmTfNJkEREHcH1g8PQI0KPcKOIdcdNyK+0o8Ii4WixFfvyqrEvrxrLdxbj0j4hGNc9ELIsI4DfrRARUTvhdWIRHR2NTZs2oaysDMHBwdBoNG73f/311wgODlYcIDXfs1Nj/R0CETVCFASMTXSuQzsgxugqz62wYUu2GauPVCK30u4aLgUAA8NFPJcso9hkh12S0SVE2RBTIiKi1qJ4UG9YWJjH8sjISKVVUyPWHausNyY7NohjtInao/gQHa4ZFIarB4bi47RSfF1rsvehUhGzPz/pOu4TqcftIyMQFahBRICGw6aIiEg1+Em0HTpaZHGNza7Nd/v9EpE/CIKAOUPDYXHIiDBqUGl14JtDFW7nHCm2YuGafACAQSMgJc6AbqE6TOgRhH7RbbchKRERUV1MLNqhfJPdY7kgMLUgau+0ooC7znP2+BabbfgloxyiRoPFU2IRG6TF8p3F+KPAArNNgsUhY/fpauw+XY0f/qzAhUmBmN47GIPjjNCI/P+AiIjaFhOLdkhooG+CeQVRxxJu1OCfwx3okdQV4QHOuRX/nBADAJBlGYeLrDhWbMWhAgs2njBhc5YZm7PMiA7U4NI+IegWpsUFiYH80oGIiNoEE4t2psom4blNnjfF40hroo4nRAeEGjT1ygVBQL9oA/pFG3BZ3xDMHhCCX45UYmu2GYVmBz7ZVwoAuKJ/CFJijRjTLQCiwJ5NIiJqPUws2pldp6savI+fF4g6r95RBtwXZcDdoyLx7aEy/PBHBSqsEn78swI//umcp6ETgW5hOvSM0CM2SIuBsQYMiTNCFIByi4QwY/0EhoiIqLmYWLQz1faGF7UXmVkQdXp6jYC/DA7HdSlh+Ne6AuzPq3bdZ5OAzBIbMktsrrLYIA1EQUBepR3nJwbgvjFRTDCIiMgrTCzaGZuj4cSCeQUR1RAFAYsnx6LC4kC+yY49p6txfmIgCkx2ZJfacLrChp2nqlBgcrgesz2nCnkV+bjrvEiUVDuQFKaDKAARARqEeBiORUREVBsTi3bGITeSWLRhHESkfjqNgMhALSIDta4N+XpF6jE20Xl/tV3CrlNVyK+0o3uYDq9tL8KJUhv+uTa/Xl3Tewfj2pRQxAVpOU+DiIg8YmLRzjikhu/j6pJE1BJGrYjxSUGu4yUX67BiVzHSCyyICNCg0GSHQSvAbJOx+mglVh+txKiuAXhgbBTskoycMhviQ7ToEszdwImIiIlFu2OXGhsKxcyCiLyXGKbDUxfFuY5lWYYgCNiSbcL7e0qRX2nHzlNVuHHlSbfH9YvWY1CsEeO7B6IvN+kjIuq0mFi0M43kFVxuloh8qubLinHdgzCuexCOFVvx5o4iHCmyQhSAmEANzpgdyCi0IqPQim8PlQMAUmINuHpQGIZ2MUKv4RceRESdBROLdqbxHos2DISIOp1ekXosuzQeRWY7gvQijFoRJVUObDphwu7TVdiT61yBKr3AgvSCAiSF6/DCxXEwaEVIsgyDll9/EBF1ZEws2hkHEwsi8rOowHN/OiICNJg1IBRX9A9BeoEFVoeMLVlmbDxhQlapDbd+dwp2SYZNAoJ0AiICNOgfbUBSuB5dQrRnN+7jf15ERB0BE4t2ppHVZvnHmYj8RhAEDI5zrjw1MiEAV/QPwb/W5aO0+tyKEyabDJPNjpPldgAmAEBckAaJYXrEh2jRN1qP8d2DoOPwKSKidomJRTvT6FCoNoyDiKgxPSL0+PfsrkjPtyDUICIhVIeSKgfyKmxYe9yEMyY7TpTakG9yIN9U5XxQBvD2zhIMjjVgcBcjRsQHIDGMK04REbUXTCzamcaWm2WHBRGpiVEr4ryuAa7jYL2IxDAdRnULBABUWBw4XmJFboUdJ8tt2HTCjOIqB7afrML2k1UASjAywYgJSUHIKbehyiajS7AWF/cORrCe8zWIiNSGiUU7wx4LIuooQgwaDO0SgKFdnMe3Do/A0WIrDuRXY39eNdLyqrH7tPOnts8PlGJMt0BEGDUoqXYgMUwHo1ZASqwRPSP1fngmREQEMLFod2yNJBbcII+I2jONKKBftAH9og24ZlAYTpbZ8NJvhThZbsOFPZyJxI6TVcgus2FDpsljHVf0D8G0XsH49Vgl+kYZ0CNCh9ggLTQCuCoVEVErY2LRztgamb3NDfKIqCPpFqbDssu6wCHBNaH7pmHhOFRgwZ7cKpRWS4gwalBotqO02oHdp6vx458V+PHPirM1VLjVFxmgQWKYDt3P/nQL06FXpB6BOiYcRES+wMSiHTlaZMHGE2Z/h0FE1GZEQYCocT9OiTMi5ewKVLWlZprw8pZC13H3MB2KqhwwWZ2T04qrHCiucmBfXnWt+oCkcB2uHRSGCT2CUGiy41iJFeFGDQK0AuJDdFylioiomZhYtCPzf8lz3RaFxnfhJiLqbCYlB8HqkPDLkUr8bVQk+kUbIMsyqu0y7JKM0xV2ZJXacLLMhuwyG7LKrDhjciCzxIYXfyvER3tLkG9yuNUZbhQxtIsRNgnoGqJFnygDgvWAqQpIsEsI4CRyIiIXJhbt1O0jI7BiV4nr+K7zIvwYDRGROkzrHYJpvUNcx4IgIEDn7HHoZ9CgX7TB7fxisx3/zajA1wfLkW9yQACQGKZDpVVCpVVCabXUQE+xFkg7hTCDiOggLWKCNIgJ1CI6UIOYWscRARpoOAGOiDoJJhbtVFyQFnOGhOHT/WUAgJn9Qpp4BBER1RUZqMXc4RGY1jsYh85Y0CdSj+7hzpWl7JKM309W4XSFDaIg4GiRBQUmB8otDhSabLBKAsosEsosVhwr9ly/KABRgRp0C9WhW6jOteRugFZAUrgeQXoRQez1IKIOgolFOyHL7uOejFr3b8A4cZuIyHvxITrEh7hvxqcVBVzQPbDeuZIk4fjxTMR2S0JhlYRCkx1nTA6cMdtxxmRHodmBMyY7iswOOGQ47zM5sDe3ul5dABAdqEGwXkRMkBaDYg0QBaBrqA7hRg3CjCLCjRoYuaIVEbUDTCzaCbPNPbEI1ovcEI+IyE8Ewfn/cKhRi54RnvfOcEgySqqdScXRYguKzA4UVDoTj7JqB/JNdtgloNDsQKHZgROlNuw8VeWxLoNGQKhRRJjBmWxEBGgwOM6IMd0CcbzYCoNWQESABhFGDSebE5HfMLFoJyos7hMKg/Qiqu2cvU1EpFYaUUB0oBbRgVoMiDF4PKfc4kBuhR0mq4Q/Cy04XmKFRhCQV2FHmcWZgNgkwOKQXT0fNdYeMwEoqn9dATBoBYToRfSKcl7XoBEQahARZtQg/GyCElrTI2LQIEAnsOebiBRjYtEOyLKMcovkOg41OL+tCuG4XCKidi3UoEGowbme7oiEgHr3y7KMKruM8moHSquls8mGhNwKG1IzTThjdiDMIEKvEVBS7YBdAhyys5fbbHMg39S8Jcq1IhBm1CDsbPIRrBcRF6xFmEEDjQhEB2oRZhQRoBMRqBMQotcgkMkIEdXBxEJlKi0OnKqwu1YueX1bEXadrsLc4eEAgAijBq9e1gVGrYjL+4WgwOTABd3r/zEiIqL2TxAEBOoEBOpEdKmzRscNQ8JxuNCCvtEG6DUCZFmGySqh2i7D4pBRZHbgYEE1AnUi7JKMMovklqCUVztQZpHOLscLFJkdKDI7ANiaFZtOBCICnImRUSvAqBVh1AoIM4roGqpDkF5EgFZ0xR+gExFiEBFqEGGxyzBoBYhMTIg6FCYWKvP69mJszTFjWq9gjO4WgF+PVQIAlm11dnd3D9chKtDZbEatiHtGR/otViIi8h+9RnDbKFAQBAQbNAg+O+qqa6gOQ7rU30iwrmq7hPKzyUZptTP5qLRKyCyxwuqQ4ZCBQrMd5RYJVTYJVTZn4mKTgAKTAwV19v5oigCgZiBvgFZw9YI4/z2XiATpRQTpRAQbRATrRQTrRATVuh1sEGHQsNeESE2YWKiI2SZha46z2/rXY5WupKK2MAOHPxERke8YtSKMwSJig5v/kcBid+7xUVLlQIXFgWqHcyPCaruEQpMDeZV2VNmks0OyJFTZz962Sqg9O7DKLqPK7kCx5znrTdKKQKBOhADnEDBR1iA4PRcBOtGVtNT8azy7k3qQXoAkOyffh+idw8gk2TknpiapCdSJnARP5AUmFipRVu3AnJUnmzyvpreCiIjIXwxaEXHBznkYLWFzyCi3OBCoE2FxOJMOs1VClf3s7bM9Imab5Nqk0FTn35rbDhmwS3CbgwgIKLfZffIctSKgEwXoNAJEwZmAxQRpEB+sQ4BOwBmTAzqNs+dIr3H2nui1AvQaAQaNAI0oQCs6ly2uqUenEaATAZ3GeZ57+dmys+ewJ4baI35KVYnmJBWAc6MlIiKi9kinEVxfkAXogHCjd3/TZNnZQ2KySqi0ORMLQZZxIuckImMTUO3A2WFbzjkk5rO9J5klVtglGTqN4ExSLBLskgwIgN0BVNkl14qLdsm5SWKVawVGCXmVdhzItyj+PTSHtiYBEc8lHu5JCNyO3c51lcFjAqPTCGcTHmfio6l1W1srIdJq3I81AhMeapzqE4u33noLL730EvLy8jB06FC88cYbGD16tL/D8qmjRY3/JzWzXwhKz455nd47uI2iIiIiUidBEBBwdl5G9NkySZJgLwaSYw0QRe+HDTsk2ZWQ2CQZNocMSQZMNgkFJjtyymwot0hICtNBkp1LAVsdMqxnJ81bHRKsDueEeId0tg4JsDucdVnP1mlznKvfenbOSm2uxAbqWlpeWycB0Yn1e2dqjnUaZzJiqRIRdqoQOo1Y5/GC27FGBDSC81+t6Owp0pxNaGrKRcH5mJpyUXB/XN3zNYIAsVZiVHNcuz7yHVUnFl9++SUWLFiAt99+G2PGjMGrr76K6dOnIyMjA7Gxsf4Oz2dq78baK0KPW0aEo1+UAVllViSG6RHMZWWJiIjahEZ0nwRf26BWvK4sO5ORmoTDWutfe+0yB9zKrXUSFLskw3r2HPcy2a1ux9nExfnT8O26au5HixIeESjxciJNKxMA98SkbgJT69jTeXXvF4WahKf2bWeSJIrnbgs4l+SItc9xu32uLqHO/bWvUb+O2ufWL9cIQJXJ2iq/T1UnFkuXLsWdd96JW2+9FQDw9ttv46effsL777+PhQsX+jk65artEnbkVOHbQ+UAgLvPi8DM/qGu+wfENL2aBxEREbV/guAcuqSmSeOyLJ+dy+JMYuyys+fFfrYXxiGdu22X5LM9NLUTExk2u4S8M4UIj4iCQxbc76tTh3Q2mXGcva4kOf91NPKvdPZfu6fzZWcCVXPs8TnibLIEGXDUlHR8kqV5e9y0lGoTC6vVit27d2PRokWuMlEUMXXqVGzbtq1Fde06XY2gMven2tDLpsFyD3fsOlWFX49VYkrPIJzfLbDe/ZJc8y2C801WbZdRWu1AsdmBTVkmSLXqDNAJOD+xfh1ERERE/iAIArSCcxiRt58YJUlCpngGyckhioaoKSXLziREqpVw2GslJm6JSJ2ExCHLkM6W26VaCYyH82vql2olPs4f2fWvQ3Z+rvRU7lYm1bqNs7el+o+r/bxqbtd+vp7qtgkiclrh96zaxKKwsBAOhwNxcXFu5XFxcfjzzz89PsZiscBiOTdfobzc2RPw8pYiiIbW64Jbf9yE9cdNXj1WKwJjEwNxfUooogJESJKHfscOpuY5dobn2p6wXdSHbaJObBd1Yruok5raxTn8yPkDsaak9r+dR3l5OS583vf1qjax8MaSJUuwePHieuWJQTK0xnPdA819+TQ1n6fKDuRVCYg1ygjUup8voGbcnnw223fuUhqsA8J0MsL0QIRBRs8QQBDK4SguR2ZxMwPrILKysvwdAnnAdlEftok6sV3Uie2iTmwXdTGbO9lQqOjoaGg0GuTn57uV5+fno0uXLh4fs2jRIixYsMB1XF5ejsTERLxwSQJCQ0M9PobaniRJyMrKQlJSkl+7Rckd20V92CbqxHZRJ7aLOrFd1KlmVI+vqTax0Ov1GDlyJNatW4fZs2cDcL44161bh3vvvdfjYwwGAwyG+ss4iKLIF7MKsV3Uie2iPmwTdWK7qBPbRZ3YLurSWm2h2sQCABYsWIC5c+fivPPOw+jRo/Hqq6/CZDK5VokiIiIiIiJ1UHVicf311+PMmTN4/PHHkZeXh2HDhmHVqlX1JnQTEREREZF/qTqxAIB77723waFPRERERESkDhzsRkREREREijGxICIiIiIixZhYEBERERGRYkwsiIiIiIhIMSYWRERERESkGBMLIiIiIiJSjIkFEREREREppvp9LJSQZRkAYDKZuI28ikiSBLPZjMrKSraLirBd1Idtok5sF3Viu6gT20WdTCYTgHOflX2lQycWRUVFAIBp06b5ORIiIiIiInUpKipCWFiYz+rr0IlFZGQkACA7O9unvzRSpry8HImJicjJyUFoaKi/w6Gz2C7qwzZRJ7aLOrFd1Intok5lZWXo3r2767Oyr3ToxKKmyy0sLIwvZhUKDQ1lu6gQ20V92CbqxHZRJ7aLOrFd1MnXw9M42I2IiIiIiBRjYkFERERERIp16MTCYDDgiSeegMFg8HcoVAvbRZ3YLurDNlEntos6sV3Uie2iTq3VLoLs63WmiIiIiIio0+nQPRZERERERNQ2mFgQEREREZFiTCyIiIiIiEixdp9YvPXWW+jRoweMRiPGjBmD33//vdHzv/76a/Tv3x9GoxGDBw/Gzz//3EaRdi4taZcPP/wQgiC4/RiNxjaMtuPbtGkTZs6ciYSEBAiCgO+//77Jx6SmpmLEiBEwGAzo3bs3Pvzww1aPs7NpabukpqbWe68IgoC8vLy2CbgTWLJkCUaNGoWQkBDExsZi9uzZyMjIaPJx/NvSurxpF/5taX3Lly/HkCFDXHtUjB07Fr/88kujj+F7pfW1tF18+V5p14nFl19+iQULFuCJJ57Anj17MHToUEyfPh0FBQUez9+6dStuuOEG3H777di7dy9mz56N2bNnIz09vY0j79ha2i6Ac+Oc3Nxc109WVlYbRtzxmUwmDB06FG+99Vazzs/MzMTll1+OyZMnIy0tDfPnz8cdd9yB1atXt3KknUtL26VGRkaG2/slNja2lSLsfDZu3Ih58+Zh+/btWLNmDWw2G6ZNmwaTydTgY/i3pfV50y4A/7a0tm7duuH555/H7t27sWvXLkyZMgWzZs3CwYMHPZ7P90rbaGm7AD58r8jt2OjRo+V58+a5jh0Oh5yQkCAvWbLE4/nXXXedfPnll7uVjRkzRr777rtbNc7OpqXt8sEHH8hhYWFtFB0BkL/77rtGz/nHP/4hDxo0yK3s+uuvl6dPn96KkXVuzWmXDRs2yADkkpKSNomJZLmgoEAGIG/cuLHBc/i3pe01p134t8U/IiIi5H//+98e7+N7xX8aaxdfvlfabY+F1WrF7t27MXXqVFeZKIqYOnUqtm3b5vEx27ZtczsfAKZPn97g+dRy3rQLAFRWViIpKQmJiYlNZtXU+vheUbdhw4YhPj4eF198MbZs2eLvcDq0srIyAEBkZGSD5/D90vaa0y4A/7a0JYfDgS+++AImkwljx471eA7fK22vOe0C+O690m4Ti8LCQjgcDsTFxbmVx8XFNTjeOC8vr0XnU8t50y79+vXD+++/jx9++AH/+c9/IEkSLrjgApw8ebItQiYPGnqvlJeXo6qqyk9RUXx8PN5++2188803+Oabb5CYmIhJkyZhz549/g6tQ5IkCfPnz8e4ceOQkpLS4Hn829K2mtsu/NvSNg4cOIDg4GAYDAb87W9/w3fffYeBAwd6PJfvlbbTknbx5XtFqzRwIqXGjh3rlkVfcMEFGDBgAN555x08/fTTfoyMSF369euHfv36uY4vuOACHDt2DMuWLcMnn3zix8g6pnnz5iE9PR2//fabv0OhWprbLvzb0jb69euHtLQ0lJWVYeXKlZg7dy42btzY4IdYahstaRdfvlfabWIRHR0NjUaD/Px8t/L8/Hx06dLF42O6dOnSovOp5bxpl7p0Oh2GDx+Oo0ePtkaI1AwNvVdCQ0MREBDgp6jIk9GjR/ODbyu499578b///Q+bNm1Ct27dGj2Xf1vaTkvapS7+bWkder0evXv3BgCMHDkSO3fuxGuvvYZ33nmn3rl8r7SdlrRLXUreK+12KJRer8fIkSOxbt06V5kkSVi3bl2DY8jGjh3rdj4ArFmzptExZ9Qy3rRLXQ6HAwcOHEB8fHxrhUlN4Hul/UhLS+N7xYdkWca9996L7777DuvXr0dycnKTj+H7pfV50y518W9L25AkCRaLxeN9fK/4T2PtUpei94pPpoD7yRdffCEbDAb5ww8/lA8dOiTfddddcnh4uJyXlyfLsizfdNNN8sKFC13nb9myRdZqtfLLL78s//HHH/ITTzwh63Q6+cCBA/56Ch1SS9tl8eLF8urVq+Vjx47Ju3fvlv/yl7/IRqNRPnjwoL+eQodTUVEh7927V967d68MQF66dKm8d+9eOSsrS5ZlWV64cKF80003uc4/fvy4HBgYKD/88MPyH3/8Ib/11luyRqORV61a5a+n0CG1tF2WLVsmf//99/KRI0fkAwcOyA888IAsiqK8du1afz2FDueee+6Rw8LC5NTUVDk3N9f1YzabXefwb0vb86Zd+Lel9S1cuFDeuHGjnJmZKe/fv19euHChLAiC/Ouvv8qyzPeKv7S0XXz5XmnXiYUsy/Ibb7whd+/eXdbr9fLo0aPl7du3u+6bOHGiPHfuXLfzv/rqK7lv376yXq+XBw0aJP/0009tHHHn0JJ2mT9/vuvcuLg4+bLLLpP37Nnjh6g7rpplSuv+1LTD3Llz5YkTJ9Z7zLBhw2S9Xi/37NlT/uCDD9o87o6upe3ywgsvyL169ZKNRqMcGRkpT5o0SV6/fr1/gu+gPLUHALfXP/+2tD1v2oV/W1rfbbfdJiclJcl6vV6OiYmRL7roIteHV1nme8VfWtouvnyvCLIsyy3v5yAiIiIiIjqn3c6xICIiIiIi9WBiQUREREREijGxICIiIiIixZhYEBERERGRYkwsiIiIiIhIMSYWRERERESkGBMLIiIiIiJSjIkFEREREREpxsSCiIiIiIgUY2JBRERERESKMbEgIiKPJk2ahPnz5/s7DBdv4ykqKkJsbCxOnDjh85jq+stf/oJXXnml1a9DRKRGTCyIiPzo7bffRkhICOx2u6ussrISOp0OkyZNcjs3NTUVgiDg2LFjbRxl2/J1QvPss89i1qxZ6NGjh8/qbMi//vUvPPvssygrK2v1axERqQ0TCyIiP5o8eTIqKyuxa9cuV9nmzZvRpUsX7NixA9XV1a7yDRs2oHv37ujVq5c/Qm2XzGYz3nvvPdx+++1tcr2UlBT06tUL//nPf9rkekREasLEgojIj/r164f4+Hikpqa6ylJTUzFr1iwkJydj+/btbuWTJ08GAKxatQrjx49HeHg4oqKiMGPGDLeejHfffRcJCQmQJMnterNmzcJtt90GAJAkCUuWLEFycjICAgIwdOhQrFy5ssFYm3P+pEmTcP/99+Mf//gHIiMj0aVLFzz55JNu51RUVGDOnDkICgpCfHw8li1b5uqluOWWW7Bx40a89tprEAQBgiC4DWGSJKnRuuv6+eefYTAYcP7557uV//bbb9DpdG6J24kTJyAIArKysjBp0iTcd999mD9/PiIiIhAXF4cVK1bAZDLh1ltvRUhICHr37o1ffvml3jVnzpyJL774otG4iIg6IiYWRER+NnnyZGzYsMF1vGHDBkyaNAkTJ050lVdVVWHHjh2uxMJkMmHBggXYtWsX1q1bB1EUceWVV7oSiWuvvRZFRUVu9RYXF2PVqlWYM2cOAGDJkiX4+OOP8fbbb+PgwYN48MEHceONN2Ljxo0e42zu+R999BGCgoKwY8cOvPjii3jqqaewZs0a1/0LFizAli1b8OOPP2LNmjXYvHkz9uzZAwB47bXXMHbsWNx5553Izc1Fbm4uEhMTm113XZs3b8bIkSPrlaelpWHAgAEwGo2usr179yIiIgJJSUmua0VHR+P333/Hfffdh3vuuQfXXnstLrjgAuzZswfTpk3DTTfdBLPZ7Fb36NGj8fvvv8NisTQYFxFRhyQTEZFfrVixQg4KCpJtNptcXl4ua7VauaCgQP7ss8/kCRMmyLIsy+vWrZMByFlZWR7rOHPmjAxAPnDggKts1qxZ8m233eY6fuedd+SEhATZ4XDI1dXVcmBgoLx161a3em6//Xb5hhtukGVZlidOnCg/8MADsizLzTq/5jHjx493O2fUqFHyI488IsuyLJeXl8s6nU7++uuvXfeXlpbKgYGBrmvVvm5tTdXtSd3fQY077rhDvvnmm93KHn/8cXnSpEker2W32+WgoCD5pptucpXl5ubKAORt27a51bNv3z4ZgHzixIkG4yIi6ojYY0FE5GeTJk2CyWTCzp07sXnzZvTt2xcxMTGYOHGia55Famoqevbsie7duwMAjhw5ghtuuAE9e/ZEaGioa2Jydna2q945c+bgm2++cX1z/umnn+Ivf/kLRFHE0aNHYTabcfHFFyM4ONj18/HHH3ucHN6S84cMGeJ2HB8fj4KCAgDA8ePHYbPZMHr0aNf9YWFh6NevX7N+V43V7UlVVZVbr0SNtLQ0DBs2zK1s7969bmW1r6XRaBAVFYXBgwe7yuLi4gCg3vUDAgIAoF5PBhFRR6f1dwBERJ1d79690a1bN2zYsAElJSWYOHEiACAhIQGJiYnYunUrNmzYgClTprgeM3PmTCQlJWHFihWuuRQpKSmwWq1u58iyjJ9++gmjRo3C5s2bsWzZMgDOlacA4KeffkLXrl3d4jEYDPVibMn5Op3O7VgQhHpzPbzV0rqjo6NRUlLiVuZwOJCeno7hw4e7le/ZswdXX311o9eqXSYIAgDUu35xcTEAICYmpqmnQ0TUoTCxICJSgcmTJyM1NRUlJSV4+OGHXeUTJkzAL7/8gt9//x333HMPAOe+DBkZGVixYgUuvPBCAM7JyHUZjUZcddVV+PTTT3H06FH069cPI0aMAAAMHDgQBoMB2dnZrkSmMS09vyE9e/aETqfDzp07Xb0vZWVlOHz4MCZMmAAA0Ov1cDgcXl+jtuHDh9dboSkjIwPV1dVISEhwlW3btg2nTp2q14vhjfT0dHTr1g3R0dGK6yIiak+YWBARqcDkyZMxb9482Gw2tw/uEydOxL333gur1eqauB0REYGoqCi8++67iI+PR3Z2NhYuXOix3jlz5mDGjBk4ePAgbrzxRld5SEgIHnroITz44IOQJAnjx49HWVkZtmzZgtDQUMydO9etnpae35CQkBDMnTsXDz/8MCIjIxEbG4snnngCoii6egB69OiBHTt24MSJEwgODkZkZCRE0buRu9OnT8eiRYtQUlKCiIgIAM5hUADwxhtv4P7778fRo0dx//33A4Bbj4+3Nm/ejGnTpimuh4ioveEcCyIiFZg8eTKqqqrQu3dv19h9wJlYVFRUuJalBQBRFPHFF19g9+7dSElJwYMPPoiXXnrJY71TpkxBZGQkMjIy8Ne//tXtvqeffhqPPfYYlixZggEDBuCSSy7BTz/9hOTkZI91tfT8hixduhRjx47FjBkzMHXqVIwbN85thaaHHnoIGo0GAwcORExMjNu8kZYaPHgwRowYga+++spVlpaWhunTp+P48eMYPHgwHn30USxevBihoaF4/fXXvb4WAFRXV+P777/HnXfeqageIqL2SJBlWfZ3EERE1HmZTCZ07doVr7zySqtsZPfTTz/h4YcfRnp6OkRRxPTp0zFq1Cg888wzPr/W8uXL8d133+HXX3/1ed1ERGrHoVBERNSm9u7diz///BOjR49GWVkZnnrqKQDOzftaw+WXX44jR47g1KlTSExMxL59+1ybBPqaTqfDG2+80Sp1ExGpHXssiIioTe3duxd33HEHMjIyoNfrMXLkSCxdutRtKdfWkpeXh/j4eBw8eBADBw5s9esREXUmTCyIiIiIiEgxTt4mIiIiIiLFmFgQEREREZFiTCyIiIiIiEgxJhZERERERKQYEwsiIiIiIlKMiQURERERESnGxIKIiIiIiBRjYkFERERERIoxsSAiIiIiIsWYWBARERERkWJMLIiIiIiISLH/D0BfgJocClc5AAAAAElFTkSuQmCC", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig,ax1 = plt.subplots(1,1,figsize=(8,4))\n", "ax1.plot(Stellar.WAVE,Stellar.SOLSPEC)\n", "ax1.grid()\n", "if Stellar.ISPACE==0:\n", " ax1.set_xlabel('Wavenumber (cm$^{-1}$)')\n", " ax1.set_ylabel('Spectral luminosity (W (cm$^{-1}$)$^{-1}$)')\n", "elif Stellar.ISPACE==1:\n", " ax1.set_xlabel('Wavelength ($\\mu$m)')\n", " ax1.set_ylabel('Spectral luminosity (W $\\mu$m$^{-1}$)')\n", "ax1.set_facecolor('lightgray')\n", "ax1.set_xlim(0.,3.5)\n", "plt.tight_layout()" ] }, { "cell_type": "markdown", "id": "624c18d4-1c59-42bb-bfc8-0330f6305e06", "metadata": {}, "source": [ "## Writing NEMESIS solar file" ] }, { "cell_type": "code", "execution_count": 6, "id": "cd26bafe-ba67-4177-940d-3e0465dc37f3", "metadata": {}, "outputs": [], "source": [ "#Writing the new stellar file\n", "Stellar.write_solar_file('solar_noaa_wl_'+str(year)+'.txt')" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.10" } }, "nbformat": 4, "nbformat_minor": 5 }