{ "metadata": { "name": "", "signature": "sha256:488d7f3f3cc7d1237130861ec064a810d3ee9609cebf9aa0061baae09f9dd7bd" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "This notebook compares the surges at Neah Bay and Tofino to determine if the timing of the surge event at these two location is in sync. Also look at Toke Point.\n", "\n", "Also does a quick check of the contribution to SSH due to the inverse barometer effect." ] }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Neah Bay" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Tidal predictions and water level observations are taken from the NOAA website. \n", "http://tidesandcurrents.noaa.gov/waterlevels.html?id=9443090&units=metric&bdate=20060201&edate=20060207&timezone=GMT&datum=MLLW&interval=h&action=data\n", "\n", "The surge is calculated as the difference between observations and predictions.\n", "\n", "This data was downloaded by visiting the website. We would need something more automated if we decided to use Neah Bay conditions in forcing. \n", "\n", "Note: It was not completely obvious how to collect historical surge data from the National Weather Service website.\n", "http://www.nws.noaa.gov/mdl/etsurge/index.php?page=stn®ion=wc&datum=msl&list=&map=0-48&type=both&stn=waneah\n", "\n", "stormtools.get_NOAA_wlev() and stormtools.get_NOAA_predictions() automate retrieving the NOAA data. " ] }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Toke Point" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " Toke Point data also grabbed from NOAA" ] }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Tofino" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Water level observations are taken from DFO. Tidal predictions are calculated using t_tide with tidal harmonics from a 2005 time series. The 2005 mean sea level from observations is added to the tidal predictions. \n", "\n", "The surge is calculated as the difference between observations and predictions." ] }, { "cell_type": "code", "collapsed": false, "input": [ "\n", "%matplotlib inline\n", "from matplotlib import pylab\n", "import matplotlib.pyplot as plt\n", "import netCDF4 as NC\n", "import numpy as np\n", "\n", "import arrow\n", "import datetime\n", "import pandas as pd\n", "import pytz\n", "import requests\n", "from salishsea_tools import tidetools\n", "from salishsea_tools import stormtools" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 1 }, { "cell_type": "code", "collapsed": false, "input": [ "stns ={'NeahBay': 9443090, 'TokePoint': 9440910}\n", "\n", "st='01-JAN-2006';\n", "ed = '31-DEC-2006';\n", "\n", "for key in stns:\n", " stormtools.get_NOAA_predictions(stns[key],st,ed)\n", " stormtools.get_NOAA_wlev(stns[key],st,ed)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 2 }, { "cell_type": "code", "collapsed": false, "input": [ "def dateParserMeasured(s):\n", " #convert the string to a datetime object\n", " unaware = datetime.datetime.strptime(s, \"%Y-%m-%d %H:%M\")\n", " #add in the local time zone \n", " aware = unaware.replace(tzinfo=pytz.timezone('UTC'))\n", " return aware\n", " " ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 3 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Make a function so that the plots are easy and we minimize copying and pasting. Function will compare Tofino and Neah Bay surges in a plot." ] }, { "cell_type": "code", "collapsed": false, "input": [ "def get_surges(start,end):\n", " #loads data from files an calculates that surges. returns anomaly and time\n", " meas={}; pred={}; anom={}; time={}\n", " \n", " for key in stns:\n", " filename_wl = 'wlev_' + str(stns[key]) + '_'+start +'_' +end +'.csv';\n", " filename_pr = 'predictions_' + str(stns[key]) + '_'+start +'_' +end +'.csv';\n", " meas[key] = pd.read_csv(filename_wl,skiprows=0,parse_dates=[0],date_parser=dateParserMeasured)\n", " meas[key] = meas[key].rename(columns={'Date Time': 'time', ' Water Level': 'slev', \n", " ' Sigma': 'sigma', 'I': 'I', 'L': 'L'})\n", " pred[key] = pd.read_csv(filename_pr,skiprows=0,parse_dates=[0],date_parser=dateParserMeasured)\n", " pred[key] = pred[key].rename(columns={'Date Time': 'time', ' Prediction': 'pred'})\n", " \n", " #anomaly\n", " anom[key] = np.zeros(len(meas[key].time))\n", " for i in np.arange(0,len(meas[key].time)):\n", " #check that there is a corresponding time \n", " #if any(wlev_pred.time == wlev_meas.time[i]):\n", " anom[key][i] =(meas[key].slev[i] - pred[key].pred[pred[key].time==meas[key].time[i]])\n", " if not(anom[key][i]):\n", " anom[key][i]=float('Nan')\n", " \n", " time[key]=meas[key].time\n", " \n", " return anom,time" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 4 }, { "cell_type": "code", "collapsed": false, "input": [ "anom,time=get_surges(st,ed)" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 5 }, { "cell_type": "code", "collapsed": false, "input": [ "def compare_surge(date_start, date_end):\n", " #compare Tofino surges with NOAA surges during the time frame indicated\n", " #Loading Tofino surge from forcing files\n", " ssh_Tofino = '/data/nsoontie/MEOPAR/NEMO-forcing/open_boundaries/west/ssh/ssh'\n", " arr_start =arrow.Arrow.strptime(date_start,'%d-%b-%Y')\n", " arr_end =arrow.Arrow.strptime(date_end,'%d-%b-%Y')\n", " yr=arr_start.year\n", " m=arr_start.month\n", " m= \"%02d\" % (m,)\n", " string = '_y'+ str(yr) + 'm' + str(m) +'.nc'\n", " #get the data\n", " fT = NC.Dataset(ssh_Tofino + string);\n", " Tof_anom=fT.variables['sossheig'];\n", " tss= fT.variables['time_counter'][:];\n", " l = tss.shape[0]; t=np.linspace(0,l-1,l) #time array\n", " Tof_time=stormtools.convert_date_hours(t,start);\n", " \n", " #Plotting\n", " plt.figure(figsize=(18,5))\n", " ax1=pylab.subplot(1,1,1)\n", " ax1.plot(Tof_time[:],Tof_anom[:,0,0],'r',label='Tofino')\n", " for key in stns:\n", " ax1.plot(time[key],anom[key],label=key)\n", " ax1.set_ylim([-1.5,1.5])\n", " ax1.set_xlim([datetime.datetime(arr_start.year,arr_start.month,arr_start.day), \n", " datetime.datetime(arr_end.year,arr_end.month,arr_end.day)])\n", " pylab.xlabel('Time')\n", " pylab.ylabel('SSH anomaly (m)')\n", " pylab.grid()\n", " pylab.legend(loc=0)\n", " pylab.title('SSH Anomaly for ' +start)\n", " \n", " \n", " return Tof_time,Tof_anom" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "def get_statistics(ssh1,ssh2,t1,t2,sdt,edt):\n", " \"\"\"\n", " Calculates several statisitcs, such as mean error, maximum value, etc for two sshs in a given time period.\n", "\n", " :returns: max1, max2, tmax1, tmax2, mean_diff, mean_abs_diff, rms_diff, correlation\n", " \"\"\"\n", " #truncate ssh1\n", " trun1, trun_t1 = stormtools.truncate(ssh1, t1, sdt, edt)\n", " #truncate ssh2\n", " trun2,trun_t2=stormtools.truncate(ssh2,t2,sdt,edt)\n", " #rebase observations\n", " diff = trun1-trun2\n", " #calculate statisitcs\n", " mean_diff = np.nanmean(diff)\n", " mean_abs_diff = np.nanmean(np.abs(diff))\n", " rms_diff= stormtools._rmse(diff)\n", " corr=np.corrcoef(trun1,trun2)\n", " max1,tmax1=stormtools._find_max(trun1,trun_t1)\n", " max2,tmax2=stormtools._find_max(trun2,trun_t2)\n", "\n", " return max1,max2,tmax1,tmax2,mean_diff,mean_abs_diff,rms_diff,corr" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 7 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Feb 2006 surge" ] }, { "cell_type": "code", "collapsed": false, "input": [ "start='01-Feb-2006'\n", "end = '28-Feb-2006'\n", "\n", "[Tof_time, Tof_anom]=compare_surge(start,end)\n", "\n", "start='02-Feb-2006'\n", "end = '05-Feb-2006'\n", "sd =datetime.datetime.strptime(start,'%d-%b-%Y')\n", "sd = sd.replace(tzinfo=pytz.timezone('UTC'))\n", "ed =datetime.datetime.strptime(end,'%d-%b-%Y')\n", "ed = ed.replace(tzinfo=pytz.timezone('UTC'))\n", "[maxTof,maxNB,tmaxTof,tmaxNB,mean_diff, mean_abs_diff, rms_diff,corr] = get_statistics(\n", "np.array(Tof_anom[:,0,0]),np.array(anom['NeahBay']),np.array(Tof_time),np.array(time['NeahBay']),sd,ed)\n", "\n", "print 'From', start, 'to', end\n", "print 'Tofino Max/Time', maxTof, tmaxTof\n", "print 'Neah Bay Max/Time', maxNB, tmaxNB\n", "print 'Mean (Tofino -Neah Bay)', mean_diff" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "From 02-Feb-2006 to 05-Feb-2006\n", "Tofino Max/Time 0.882743 2006-02-04 14:00:00+00:00\n", "Neah Bay Max/Time 0.636 2006-02-04 16:00:00+00:00\n", "Mean (Tofino -Neah Bay) 0.10972174032\n" ] }, { "metadata": {}, "output_type": "display_data", "png": 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88gjR0dF5Og4zUDJE8tXt1v6FhYG3NxQpcnvPLVsWYmNv71q5TrWb5qb4mZdi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vj+sy/v3skk4d69yd/3le8r6lnq0TvIm2ERYayypgozzczE627XGRgoL8yR2VYmHFpC3cHVaDzf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\nQmCC\n", "text": [ "<matplotlib.figure.Figure at 0x7faabbc9f050>" ] } ], "prompt_number": 8 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Tofino surge is significantly higher than Neah Bay (about 25 cm) on Feb 4. Neah Bay is about 2 hours later\n", "\n", "Toke Point anomaly is much larger. Timing is about the same." ] }, { "cell_type": "code", "collapsed": false, "input": [ "start='01-Feb-2006'\n", "end = '28-Feb-2006'\n", "sd =datetime.datetime.strptime(start,'%d-%b-%Y')\n", "sd = sd.replace(tzinfo=pytz.timezone('UTC'))\n", "ed =datetime.datetime.strptime(end,'%d-%b-%Y')\n", "ed = ed.replace(tzinfo=pytz.timezone('UTC'))\n", "[maxTof,maxNB,tmaxTof,tmaxNB,mean_diff, mean_abs_diff, rms_diff,corr] = get_statistics(\n", "np.array(Tof_anom[:,0,0]),np.array(anom['NeahBay']),np.array(Tof_time),np.array(time['NeahBay']),sd,ed)\n", "\n", "print 'From', start, 'to', end\n", "print 'Mean (Tofino -Neah Bay)', mean_diff" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "From 01-Feb-2006 to 28-Feb-2006\n", "Mean (Tofino -Neah Bay) 0.0812378998059\n" ] } ], "prompt_number": 9 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Another Surge: Dec 2006" ] }, { "cell_type": "code", "collapsed": false, "input": [ "start='01-Dec-2006'\n", "end = '31-Dec-2006'\n", "\n", "[Tof_time, Tof_anom]=compare_surge(start,end)\n", "\n", "start='14-Dec-2006'\n", "end = '18-Dec-2006'\n", "sd =datetime.datetime.strptime(start,'%d-%b-%Y')\n", "sd = sd.replace(tzinfo=pytz.timezone('UTC'))\n", "ed =datetime.datetime.strptime(end,'%d-%b-%Y')\n", "ed = ed.replace(tzinfo=pytz.timezone('UTC'))\n", "[maxTof,maxNB,tmaxTof,tmaxNB,mean_diff, mean_abs_diff, rms_diff,corr] = get_statistics(\n", "np.array(Tof_anom[:,0,0]),np.array(anom['NeahBay']),np.array(Tof_time),np.array(time['NeahBay']),sd,ed)\n", "\n", "print 'From', start, 'to', end\n", "print 'Tofino Max/Time', maxTof, tmaxTof\n", "print 'Neah Bay Max/Time', maxNB, tmaxNB\n", "print 'Mean (Tofino -Neah Bay)', mean_diff" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "From 14-Dec-2006 to 18-Dec-2006\n", "Tofino Max/Time 0.554225 2006-12-15 06:00:00+00:00\n", "Neah Bay Max/Time 0.65 2006-12-15 06:00:00+00:00\n", "Mean (Tofino -Neah Bay) -0.0902090209924\n" ] }, { "metadata": {}, "output_type": "display_data", "png": 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FHBQTc1E8zEXxyNrJk1C+vP37OzIZopiYi+JhPoqJuSgekpXQ0FD8/f25cOGC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\nw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hU4exbxsnjkmpFLnRqXFi1aALVq+X3yeuwXs3Ilj9kLFuSBsrW17kj3ixf5R6OD/ff3\no+7auqhenSvj+NzzgfFsY1jPKI+KdiFw85+GIYeHYOChgbCcZ4kN1zcgKj4K+WflR/6ZhjAp+hzj\nxvHPX4ugIHbe373LUSJLl/LCZ8+eHLFiaJixqmmPHrHT1cBA43FRKrnfmTOHU/Z1zJOkOl9Pt1Vv\n377FoEGDULlyZVSuXBlDhgxBZMoc2R+MVB/u74qfnx/g6sqlolTLL8k1P9Li7Fl2hmRkABgbyz/m\nJ0/4PgUKaAZfN25wKHNcHB9nbQ3MmgU7O/YJVK7M/ZCaESM44kJX2NfevUCbNnjxAkjYsovf/h+5\ndImzTQBwhEUGRYY9PdnXERSkXZ1WzdOn7NZt3ZqfZXqeWl1s3qwWPPLLn59TX3bt4tqByaJBlizh\nfjCFzAgA3tbf/TSyTMyH97Ga0WWbNhzwkhGuv7yOBFkCOuzqoBUODQChUaEwn2uuFkj1C/H79O/5\nEyIGTdJC2EN6/JI28fbmcuUfiUmMgbFbYZiP/h9uv07t5E6QJaDBxgbYemtrhi4/9eh4ZJ6aGSWX\nlERw5EexvPnz+T0gl+Mvz/rYtMsV3rd3wX6YIWQDh6Joh3kwGFgKJVo6oNRgA8jLl+N38PHjwMmT\naLezHZy2OeHE4EFApkwY7XQPmbMoYdxpOEqMYm9Cs2acHapUAoULK3HjBthpb2PDG1+9wvora2A3\n0gTz3J3wz/LmvDqZxns+OBjIkUOJJjn9EHFUt3j+p+Djw6/4ixf5lV6gAEeL/8yk+Rvx9eX03f37\neSX34UMeL4WGIuBFgDpCs+0yO+QeWwj5phbADPcEWFlxdvOFx4HINMoS2Uflw+3QqxzykawilELB\noumZMmme47t3PD/avTtt7fVvwoULvFINsBemWjVeBS9U6JMjiD+XX7LPkgoDBqjrdNdYXQO77uzC\nhWcXMOb4GI02TAqSkoCWLf1Qtuy3LdaihULBaWr+/tyAJUu4MMEn0md/H0w8tAAFCmi6SblCjmFH\nhsOy50AUm1Ebxx9zJYjrL6/DxsMGztud0XZnWxQZ3BsOk9yRkMAR3LqCvwFwSTMDA44cK1eOD9ZR\ndcbTk2WiUsmFJiayuKqZGU8W7t7luZZSqbsKJaQ7X5dmqz4RqT7cn57ERE7L0DOthk8AACAASURB\nVJPPpkVKMdNixVhbA2Ch0eHDU5+jQqnkyIht29hDMHt2xts4ZAg7DEaOZCeFsTEPAoyNeaWgQgUW\nXStXDihZEgUsFQi1bYieObywossZzf0LF2anzfnzqe/RuDHCs1ohV3YZchrEYUonTahbq1YclXn2\nbMabDHBktYcH95s6BO4ZXd6Jz8XPT2+0TYcO3HfXq5d6bNq7N1Cy+zzQFEK7iZyz/fAhD3j0pcgk\nFzmNl8Uj78y86L2vNwzdDfH6w2utY5VKJcznmuPZ+2cwmW2CsOiwz/6KAoFAIGni47nDTzZQfBaW\niOyNpsN+nYPWoXKFHN32doPVfCt02p2+yFV40A0Yj8uExx0bY+GFhbBdYovVl1ZgaSNDbN8/E8GR\nwcg3Kx+iE6KRIEuAibsxBjh1RdZ/jXG5ZXvkzytHtRXVcXC7m1oU9szTMyi0oBDs1tuh3c526LW2\nHbK37w5bj8owcyuBp2+4P/f1Zf/J2rU8QVYqwf9TqhQ7gIyMICtsg4qDs8J0til239nFuarJ9Oh0\n8Wi1L+RVa3ziQ9bP/v0csVC+vH5Jsl+af//lkBgVT54gzjgvFjUaBsoVgUaNtDNjaw2yQbdpDqmv\n85GVK1PLk0yYwHOjv//+ym3/VIKCeHBz9Oi3q+8r+H5s3arWoFhwYQGKLSqGUktLoYt3F5ReWhpR\n8bqjwpVKltArWfI7VYvat09T/OEzUSqVKLSgEBZvvYu//tLeFxYdhnwzDGEwLh9OndPohVwNu4pc\nM3Jh0sZjsK5zFraLS0GpVMLZmYPeIyN1NOnpU2DdOv7369c6U+sVCtZMHTxYI3mS6jpNm/J1Zs/m\nEt9pINX5erqtun//Pnr37o2GDRvC3t4e9vb2qF+//vdoW4aR6sP96fHx4dwvHcrkWly6xEsuKoHP\n8HAup6T6xTx9igW5xiH0bgqHSWIie0wrVeKRVMOGPFJJFqJ16xansJUrx36SxET2cm7e/LFji47m\nkMicOTmto1MnDs/avJnvP2UKR1g8eoToElWQM1M8FN26Y8k/t9HXeBffJCCAe8rx41Orqb16BeTP\nj3kdLuNv2oTXXYajaFFg0yb1Lqxfz2O+5KW508PBgTNeAM5a0aVj9L2oWVMTkHP6tGZ7fDw7PVps\nao+aK+she9e2mD+fo6cXL1biWti1VC+gh28fwmKuBULehQAA9t3fh+qe1VF0YVHUW1dP5/2bbmmK\nTrs7wdrD+stLiAkEAoGUadBAk1fwkSbNk2A6rShOP+EO+GXMSzTY2AD2G+wR+DoQlvMs1X2jUqlE\ncLASI0cmG5TKZBjdwRj9p1TjTjs0FAvHN0DPdtnwz5BiaObVDNmnZUfH3R3V9/znYH/QZANM9twG\nKJVo2hTovWwt/tr6l/o+NVbXgMeJzejQ4w2MWk9ElX+WoErPdTj++LiW01up5DKqdna8yKhm4kR+\n/06ZApw7h7NH1yCrW1auILZiBZ+kVPJLPTRU+znJ5fysVIP1r0Ri4le93M9FWBj/fYSH83O3twfG\nj4cinyFu+b/lZ60K83jwADFWppDF6q/ap1Cknj9FRfG60mcshgsE+kkeCZ6CPvv7pCuqWrz4J2jY\njB3LzoHP4a+/OIX/C7gXcQ82HjaY4KrUFaiBnj49UXOhE6ystPuzgNtvYWYGnDunhI2HDe6E34Gn\nJ//ks2ThQjZ6Ajb0cuoUay4plRzgb2vLZci1+O8/FjLOnZsXXtNAqvP1dFtVvnx5LF++HBcvXkRA\nQAACAgJw5XMqhHxDpPpwf3qcndnTZ2SUdg7ZqFFcr/Zj3onf/PkcZpCMUvmeY17jFEsxixZxQtvx\n4xqXbbJEX1W1OHd3ltJo2JAlMDp35pdt48bJgidU4Zu3b3N7kk+qP77crw7ZgAqZAoHXr3HGX44a\nWa/y6sHo0ewIuXyZvRop2qjs0hW2tkqcHsBhooGBLMxkZ6cpAlOqlCYQJjmRkcDhw6m3FyigGfsN\nHKhdWWvtWu5Pv2YIb1rhmxYWHEK4aBEvpKjw9uZqhkUWFsH50PPIMz0fmjq/h3O7WJRZVgaW8yxR\nd21dyBQahaq2O9ui+OLi+HsPLwt18e6CpZeW4n7EfQS8CNB5/8l+k2HjYYP7Efd17v8VEeG00kLY\nQ3r8sjaZPp3TMpNx6RKQz24tyi6pgAMPDuCPRX9gwskJkCvkSEjgVcI7r++hTh2gRF9XZOtrh/xm\n0bhw4eP5G2bAbHwWPHv/jEOfq1blyItkseHBkcF4FfNK/Xnptvuwar1Q/arctg1o0PgDjGcb4+Hb\nh9gWuA2VV1ZB2XIKjBkDeHj4wcGB25phHjzgnMpk4hGqUuqIj2fP+ujRnMNeoQI7QEJCeDW/fXt+\nAf2sdW+/A5/1G+nZkwVHz5/nGaJczmEcdetyyLxKlXbwYA7z+AzOnNFI5/xO/LJ9llQYPBhqtd5k\nXH95HSWXpK6gBGhs0rMny2Po5fRpnueEhvJ8ZvJknpf4+2dMQwPgcOm8eT/d45CChRcWove+3mjW\njFP6UhKdEI2XMS9Ruza09KZq1dJ8x8GHB2P6qemIiWF91HfvuCiYpSWwalXGA1d69NB2bPr4ADVq\n6Dj/8WOd+Tjx8XxOcDCfI9X5erqtqlKlyvdoxxch1Yf7U6OK7oiO5lSU2rW11cdUqARzHBx49QeA\n38CBnN+XjHx55GiU1VfjbY2NZY/A9et6mxAYyOFZqh/d/fuc0lakCK8+2NlplMszwraNiWjbiCMZ\noqOBXFkSIOvcjbU0goIAhQKyUuV4AKBQsHejYEGcXXRFE/r7kSdP2DkT8HF+36+fJl1VxZEj/Ahz\n5dLONIqM5P5Sdb2tWzndRoWdHRfTKVFCvwDZs2c8VkweyZEW+l7ScXEcSKNQcGdpaKgRoW/bFpi/\n8jUM3Q2hUCrQdmdbzDk7BysCVqDF1hZQKBVovLkx/j3K9ct8g31h42GDVzGvYDHXAp5XPGHoboiX\nMWm/SD4kflCX8ftdEIMmaSHsIT1+WZucO8fRkCkYOEiBP4cvQ4nFJbDsMqvwR0d/zPac5IIB65eh\ndO1g5HHNA4fh1WE6uTQsXGug9fbWsBmTFXs3jOUL3bvHqwV37uhtQlwcv0eTp4rExbHG5jifxfhj\n0R8ovKAwuk32RYsW/K76JvYIDWVvvLs7a6kMGcKNcHDgiE/hCEmTz7JJQAAb38VFk5J85gzb4eBB\n/v/r13kV/vnzr9ncX55fts+SCoGBPG9IkZYvV8hh5G6kM81aZZONG1k6SS+VKnH/4+nJ4dLm5hwp\nbmPDA+P+/dMPK1uzhtP2vxDHzY7YdWcXLC1112pQMXcud5MAd6UmJpoI9ZPBJ1HNs1qqc65d40iP\nmTPTb8ebN9qFqQC+frFiHAF4+HDaqUdKJXczZcuyE8bcXLrz9XRbNXnyZCxduhRhYWF4+/at+j8p\nQUS8tJ4RbQtBxpg9WyO1LpPxj9zQUEtACwDHnRUpwtEdKtniXr04BPYjMTE84c6TNR6xdRtxr9Sl\ni7YHQAceHoDD0G1aEQVLl3LYFsARFG3bZvwrTZ0KVrn/SPGCsbhDpdVVZLy9gXx5FbhV6W/2uuTP\nD+zahdGjdZfwS46XV+qv4+zMKTQDBvBYT8XZs9zXqggN5Vw8pZI7n3z5eGBarx6we48Ma6+tRZ/9\nfXD9JTuO7t3j4+3tvzwv9949drqo6NmThaDfvuWvv/XKATTaxGWO74bfhekcUxRfXFwtdBr+IRxl\nlpWBy14XmM0xw9FHRwEA/z38D212tEHf/X2/rIECgUDwK5GUxN7wjRu1hMUjI7nPVUUEyt7FoIXl\nJbRvFo3cdTYg5/CKKDG4KKb0KAZFndpY0bUtTCr6Y+OkVtjRyEp7VJpOPcnRo3VPDKZP58Grx3kP\nOK/vAVPT7zAfVrX12jVOk9W1FCr4ulStyulLyVMBVHZwdOQVnC8M9RcIvgk9e3I6fIrQhBZbW2B7\n4HY9J3HAmYWFnoiId+841d7UlNWgN23i8Gxraw5xev+eP6tCwVWkzI13cOAiBV/A7de3YTHXAo9C\nY2FiknYEx6NH7GCQyznao3Nnzb4keRKMZxsjNCo01XlhYbyGPXw4dwG3b+u+z8SJQJ8+qbcvXcpz\nOgsLvq8+1q5liYMPHzRpNj+tM6Rw4cIoUqRIqv+kBBGxoISZGXfgO3dybM+niDgINMhkrMCdMh2q\nSRMOYwA0vxxXV/5FxcfzAO/tWw59TaYo+uABR2P+WUeOI4MPsdfA1TVdeWfHpgnI6ZYXNh426OLd\nBYlyba+synEQm36FLQD8J5K8ilW7tkpsmcB1wI8d41J93boBLt2U/D0+hrpVrMiLeWkRGsr9qOqx\nxMRw296+VWLuLj/UrKXpaTw9P/55KuTou78vPM57wLr4Ozx4wH2wqnL18rXvYTSyLv63/n9w83dj\nIb1dXVG63j3MWvoC/+z5F/mKB6rLg+/fz1VySpbU7cBWKpUcRp2MI0c4CkXFYp/TKFPxAxYsYH+V\n60lXjD8xXr2/175eqLSykpa2x5vYN3Da5oTDQTrygQQCgUCgzfz5QMuW7IlWddbh4ehcIRCLmx+B\nLDwSHasGoXGuU0iyKozxg4KQq8EMzHa2Rmx8NIeM/PMPyme6Df+qI9TLh25uHKWoD6WSiwWULKm9\n2qciMpIDAvbuZQ3A1au/wXdPi68pGi7Qz/bt+v9QLl/WWswSCCRFXByHyyUvzb14MeYNqIT++7X/\nplPqGtnY8HwkFQcOsCOjfn1OFXv9mgf1yatgvn7N3mpVuPadO9xZ+vnxXHPECC5h/YV9WBfvLph1\nZhYOHtQem+ujYkWukNmyJbBli/a+nj49MfO07hCQiAhOi8+Zk9e5U5777p12IdDwD+GY4sfR/0ol\nT/lu3eJ5T0hI6uvL5RzZr0rlVPHTOkN+BtQP9949ntEWL85v8uRCDIKMs3s354+mZPNmrt0+fTqH\ntMbFsWtQFY7bti3g7g6/HDk4j+Ujfn58+LRpaReVSU58PJCjzAlUX1kL8bJ4OG93RtMtTbX0KQBO\nVfH2ztg1a9TQdmrMnMlFaAB2Bm/YwINBIyPNalhYGHcU6Sy0AeAf/l32rWDHDtY08bnnA5pCyFfs\nrnrwOWwYh7c9ePMA5nPN0cyrGYoO74a1a9kRsm4dIFPIUMuzDrK16o9nz7lDj0mMwZ9TxiLnuMLI\nMT0HKq2sBOvuo7F/P5vC2pqfRd26qZ/Jtr0+aLqpBbJPy67lKV6xQuP5XX99PQymGMCwyUKYmnIK\nTpVVVeAfolF3/ZD4IZVDRfDpiHBaaSHsIT1+C5s0acL5lc+eAWXK4EQjd5TN+wRNLa+ice7TiD96\nCti6FUnmBfHI2i6VANWc2Qr06MH/fvSIx+bFi+tPHz14kPenpeewdy/w559Qp8eo+C3s8ZMhbCIt\nhD2+E0uWcAQ6wOnsZmYIaFUDRcfnhpvfVLTb2Q62S2yR1S0rBi8brD6tSxc9Dt5//+XQ8W3b1HOf\nJZeWYKr/VO3jqlbVhKaPHs2DfFNTnjQ4OOgvsZgBkuRJWHVlFUznmOJ9wnvMmqWZn6TFrl2srair\nhK5KfDsuSeOgiUuKw7Wwa+rPSiXrQFlaapq/cydf899/NdcacHAAaArhxssbWvdYtIh9RIMGab8v\nDh3ix5Uy4uSndoYEBgZix44d2Lhxo/o/KUFEePyYq/uEXovgZfngYP4jPX5c/4lKJR5dOoI+C+oj\n6XEQ/0V8FAH9aVEoNDP3oCAOhfD2znhNKaWSIzuSe11VqMIdChbk/LomTdSlrgCwqEeePPAzN9c6\nzcsL6NiRdYhUmTTJiY5Ovc3HByjYfRQm+00GwM6BBhsbYMbpGVrHbdwI1KmT/tdTKtmpkbyz2LD3\nKf5wmYmQEPaAqhy6I0Zwe5VKdpC0aPcOq6+uxuyzszHuxDjcfHVT5z169GBnj0zGj2W5ZwKKLSqG\nyisro/Jgd0yfzsc5OHBH4X3XGy22tkB0QjTyuVnCsPRVlCqbiMhI4MjDI6i6qir69lOo1aRfveJ2\nhoRwVMnZp2dhPa0S6tXjanmqVMUNG9hnpSIiNgK5uxRBvvbD0G3LSPT06aneN2YMlx278fIGLOZa\nYPHFxSgwqTrKlAGevHsK0zmmqRxQgi9HDJqkhbCH9PgtbHL7Ni/N5ckDzJwJhQIoWUKBISabkVS2\nkmYkuW8fV3VLMbJ8+ZIHou/fs/NixgyeG5iaQh0xqEImY03VAwc+r6m/hT1+MoRNpIWwx3fi6lWO\nwgB4vrJ5M2SxMejR1xxjJteB1y0v3Hp1Cw/fPoTlQEu039Uek3wnYfHKGHTtquN61atrSjomJODh\n24cwmW2CQgsKYcftZKVTxo/nXHuFgudBgYEcQZJRgdU06LqnK+qtq4erYVyJwcWF1QkywsqV3P/r\nosXWFlh+eTkAYN21dTCebYzcM3Lj0nNtJewhQzgS5dAhTr1JHtFxL+IeTOeYYvDhwTqr9kRGcpUZ\nVYVMgBeYkxcCS5JzRM1P6wyZPHky7O3tYWZmhu7du8PCwgJt2rT5Hm3LMESEYsX44VeqlEzWwt+f\nIxe2J8sjS0hgV1qvXrhfzhIFR2VG4XE5MaJ2VbwsUY9nm4GBP+R7fDFKJed5VKzITiBzc3aFVq/O\nIhVRuutwa7F9O1Clin7vgocHO4wuXmTF5WMpKsSMGMHxWsmYM4c3R0dzKmpyUdCkJA5d0yrHB3YY\nFJpZAedDz6u3PY3iyXnga419FAp2sHh6pv21wsPZeasaSwa9CYL1vEIg1xwoXv0xhg3THDvmqCss\nu45F797s2azs3hoNNzXEyKMj0f9gf1RcUVEdfvfw7UP43PMBwP1h+fJA4cKcdut6bBpabG2B/x7+\nhyrLasPUlPvRokU5BG2K3xSMO8EiJrOOrUKWyTmRxS0LDj44iK57umLRxUV48IAHtjExrD0ydGiy\nZydPQv5Z+TFy8iuUKwfMObIFq66swocPmuiWyLhIlF9WCdmbjseiRUqYF3oH0zmm6sotHTqws6rP\n/j6YdmoaZAoZLOZa4tjVB1h8cTG6+3RP+8EKBAKB4POJitJ638rlYI93GuLiyXFy0rziVXqjdeum\nfqeuWsWVakX1coFA8FMjk7ED+epVjWgGwCuG1tY8sB07FnB3R1hYENZeW4vO3p1RYkE5WJVOVppX\nqeTU/7x5sSlgLS48u4B4WTzs1tth3rl5uBp2FcazjSFXfLz+qVM8Pzp0SKcI9udy89VNWMy1QEyi\nRhi2Zk3WNf5SLj+/DNM5phh2ZBgKzCuAu+F3seXmFlRcUVFroVMmYwdMpkxczCs5vff1xvRT0xEa\nFQrj2caITUqtTbBrFz8ShYLbbWWlWWA+9ugYTGabYPed3T+vM6Rs2bKQy+WoUKECAODVq1dwcHD4\n5g37FIgIy5fz33XXruzhUnP+PM9O5XLA15dVY+rXBxYuRPcNrTDhqBtqtT8Ng2FF4dIjiV1xFSuy\nq+tHERvLDpnw8E87b+lSzqVzdeW8N5UTSKFg8Z9169hTNHaspvN4/pw9rO7unCtatChw8mTG7nfj\nRuqRlVzOM/1kDBvGKdIAr0wlH+Pt3s06Xl268IS/bVsW3TEr/hRG7kapohKmn5qOfw78o7Xt1i2O\n+nB25nPv3weO37ql9kQCLGFSowb/O0mehMorK2PxxcXotqsPnGbNU5e59Q32hdV8K5RcWAZVR02A\ns7sHbBeXQryMR5lKpRI1V9fElptbIFPIUM2zGvLNyof55/kLRkZy3xr46g5MZpvgadRTJMgSkH9W\nfsxf9QomJtw+AGizow223tqqvu6z989wKOgQii8ujvyz8qvLILZty/1viRKp/ySctztjy80tSJAl\nwGq+FYzcjfD8/XMMGgQM+Tca1T2ro+Hc4WjVmu1UtCjQe/sYjDk+BgB3uEf9o7Sqvgw7Mgztd7VH\ndc/qakePQCAQCKTHf//xKzz5u2HBAtYZVCGTcd+fTMpLIBAIfl5UZRdTKnw+fcrh0dOnc4j2x0IQ\nSqUSs864I/Pgcrj98GM4+vDhQMWKuP3fJpjMNoHZHDPUXF0TbXe2Vc89bJfYalJDkpJ4pdHERHuR\n/RN4Ef0Cu+5oi6y23NYSCy5oylEqlRzxp6NS7WcR+DoQjTY1wuXnlz9eX4nmXs1hv8FevTAK8FRR\nleqvQqaQwXSOKULehQAAmns1h+eV1KvPSiWnV3btyu8jlY7sxWcXYT7XHG7+bii+uPjP6wypVo1L\n81SpUgVRUVFQKpUoWVJ3PecfBRGh8srKWHVlFZae2QSjws9x+zbP7WUy8IxvxQoWWD14EACQIEuA\nkbsRajR8jn/+Aep61kfumtsREqzk2bu5OaeYfMoySkaVPHWdt2EDewmionjUYmvLTpyMFmv38uKS\nUw8f8uewMCxfnqz06rZtnEe0ahVHdHh58X2rVePEsAYN2FGk8lp8ASlDBdu31+Qwd+mWCLs5/ZEg\n4xjej34pGBqycnGtWoCZ1QcUnFI9db4egCfvnsBktkkqMdWICBYfbdcOKFLqHcg1ByrObYz3CSyC\num4d1OFxM0/PhONmRyiVShx5eAR11tYBwAJBhRcUxsEHB/E06ina7WwHh40OqcLJ/EP8YTLbBE22\nNIHDRgc8jXqKAvMKqPPwohOiUWVVFXV5RADouLsjWm5riX13jmDXnV1IkCXAdomtVpSLiuZezdFk\niyb9KDCQB7YpfEwAgOWXl8NxsyMWXFiAxpsbY/yJ8eji3QUvXgA5mo9H83WdUKGiEjNnsk1cXICJ\nSwJh7WENmVwBExNg+rElaL+rvfqaL6JfYNChQWixtYVOD7DgyxHhtNJC2EN6CJtknJTDlKdPebyu\nisLcupWrk30Jwh7SQ9hEWgh7fEfGjuW5zJEj+o/58AF+1tYc0S6TQalUotiQfqg4uxmSjhwCbGyg\nePsGddfWxYqAFTgfeh6TfCdpIkHARQOWXlqquWZkZJp5+aFRoYiITe3FWHttLSb5ToLlPEvkmpEL\n4R/Ye/0+4T1yzcilpevx8iX3398SmUIGN3839fxHHycen0DVVVXVn08Gn0SppaW0xGlVfPjA2Zwd\nOmjeSc29mqvTdBpuavjzOkP69++PyMhIrFixAsWLF0fFihXRvbu0QueJCIeDDqPDrg5w2uYEU7c/\nkNUoDLlzc4oGvLz4RzNeUxVj3/19KDK1Hpyd+e96RcAKlJ34N/5RBR1cvcpRFh06pN8ApZLFWrNm\nZUGdWbNYVSY9R4pCwc4Jc3P2cJqbs9iDqnD05MnsHUirKs727XxMgQKcf5yMZs24OQA4RyVfPpaR\nHzuWwwzq1+fZcRrtfBP7Jt2vn5KUL4S6dYENh28jNikWf8/bBJpCOBl8EkFBnMWUmMi+mCxZWAO3\n556+6OrdTatiSXL+XPcn9t3fp/f+yy4vg92KVsjRuTP6eHP+y9ixrLQf/iEcRu5Gai9nojwRRu5G\nOProKOqtq6dVOSUt7kfch+tJVzx5xyF3c87OQWfvzohNikX9DfXRZ38frfZHxUdh5umZ+N/6/6H0\n0tKY6j8VOabnSOXUATi15fn7jNUzjIqPQtc9XWEwxQB+IX6ISYxBsUXFsDJgJXJMNkZmkycYMAA4\nccIPAEfOdO4MVFhRAfN2+6FCRSVKLy2tLpUr+D6IQZO0EPaQHsImX0aNGhzurFRy+HLKtJlPRdhD\negibSAthj+/Ivn08p9FVOjEZfuvXcwWH0qWBiAgs7BOAQp0roVO7TJAdPwrPK56otaaWzsk9wIUF\nOu7umOY9Qt6FYKLvREzynYS8M/PCfoO91vj/YOApZBtTCEN8JuDs07Po4t0FCy8sBACceXoGNVbX\n0G6zn+4aFl+bmMQY5JqRS704rYv+B/tj1plZ6s9KpRJVVlXBgQfpi09dC7sGq/lW6sj6R28f/bzO\nkOQEBwfjxo0b6R/4nUn5cN38p6PofFscvHwLJibA04eJwIQJWopiHXd3RKm/l2Lfxzl1cGQwzGZb\nwNhEoSm9lJDAIjkp44aS8/YtK9fUqMGCpStXAv/+i6iilTRKZUlJrPSZXCwDYKng6tU1eSPbtvGo\nRaUoqlSyo2P3bt33lss5P273bp0qpNWqcf5XUNDHDc7OHHGiVLIoR9++eh0tF67EoezwEcg0NRMe\nRz7WeUxGKVoUKLOoMis8e1RBrqE1MPrYaMydq6nu5u3NASrhH8Jh6G6o07OqYmXASrTe0Vrv/qqr\nquK/h/+h15TzyDG0EnbuZAX9PXuAib4T0e+Advktj/MeqL2mNvod6Ke3Q0yPqPgoGM82RpVVVdBt\nbzctz3JK7obfRfZp2VFuebnPupcukjutrry4gmzTsqHHnr6pqiMHBfGftPuZ2bAZ2RqD5vmh9NLS\neh1PAoFAIPj5WLyYHd+XL3PQp+jiBQLBL0N8PHsNMsrIkYCDA24a2+OPwm/huKkRHDY6wGyOGW69\nuqU+LDycq07WqwcMHsy6gAXnF8Sjt49w8MFBnZce8d8INNrUCAMPDcSd8DuouqoqNlzfoN5faIIj\nctZdgxEj+POxR8dQZVUVAMDii4tTzUlWrNAUy/nWVFhRQR39fvPVTRRfXBwP3vAkOC4pDuZzzRH0\nJkjrHO+73iixuARef3it97qvYl6hwooK2lE1+IkFVH8GdD3cjTc2wnSOKfpOuQxnZ812mUKGYUeG\nodjCYshtHqFVCanE4hIYMvM6WrVKdqHBg7kmrC6USi5lMmiQ2juZkMApbIZ5kvChaDkuhWdvzwlg\nySJTcPgwOzLeaCaxD98+RL8D/bQnpnv3ssNE10jm+HEWk9BD4cKcoqIuZ3v1KuumAGmGeT2NegrL\nSVWRo1tb5BlYH5uv7dB7bHoolUD27IDpHDPYLrFFicUlkaPkaZRdUhH29hp/0fWX17EyYCXc/N20\nqp3oIjohGgXnF8S5UE2dXKVSiZ4+PbncrIc15Ao5EmSJyD41N8pWicKGDpcXoQAAIABJREFUDUBU\nXDRM55ji4duHn/190mLeuXlw83fLkGPh7z1/o7N352/SDoC1T1RheMlRKrmE1sZt0cj8T3WYzjbD\n4ouLv1k7BAKBQPD9efOGhx0dOkBdyUwgEAh+S5KSgLp1oZjiBiMjIPS5DGOPj4X7GXf1Id7eQO7c\nHESyaBEH61+/roTFXAvkmWKBHJNM8CHxg9Zl5Qo5CswrgHsR99Tbrry4Aou5FoiKj8K2s+eRaaQN\nAq4lwsiInS1yhRwF5xdE4OtA9PDpgZUBK7WuOXQoMHfut30cKvru74tFFxdBqVSi4aaGaLKlCYot\nKoaw6DDMPz8fztuddZ432W8yKq2spDOqRKaQofTS0pjiNyXVfEg4Q74h+h7uxhsbUXVlNRQvKVdP\nuhdeWIhaa2rh2Jm3KF9e+/hBhwZh2OF/YdbYEyNGJ3Agh7+/tmrwy5caR4KvL6edJIuuGDOGNXsa\nNQLWOO7gsiIzZgBhYZzK4ubGJUVMTDSlnD7Sansr5JieA9sDkwnzKBR8j5TyvgCrji5apPO7K5Vc\nse/CBY6KyCgKpQIVVlRA4S4zcfSoEkVcpqL1srEZvwC0QwXfvgXymyQgq1tWvIx5icDXgejTT4Zs\nkwyR2+KlWmal/ob6KLqwKGgK4frL9FX0t97aqqWG7HHeA9U9q+PCswu4G66J5LHfYI/DQYchU8jQ\nekdr9PDp8Unf5VsRkxijFkj9HiS3ybJlHHDUb/gbdNvbDVHxGagyJPiqiHBaaSHsIT2ETb6c9u05\nOvTZsy+/lrCH9BA2kRbCHtJDyyYf525OTsAOHWu8tWtzBLmKFSt4/mTSbjxKdliHLF1bwuO0tuPi\n+OPj6iiP5PTw6YGhR4bCbHIZNB/rBYAXpv/4gwWuRx0di3+P/ovKKyvj4rOLWuc2bvz5JdA/lXXX\n1qGzd2ccfHAQtktskSRPgvsZdxRZWATmc8116hoCvABtv8Fee776kaOPjqKaZzWd50nVGZKFfmH+\nrvA3eV71pPJj3WngoPFUvkYUzTgzg3xdfOm/Tcb0v/9pH9/CtgW12tGK8jjkI78bJtSiRWvat+dP\nyv7yJdHEiURnzhAFBBCZmxO5uBD5+hKNHUuUObP6Gj4+RF5eRK9fE02e3J56BbTX3GDfPt6ZlER0\n/TqRjY1615mnZ+jay2u0ufkeGn1yIDmXcqbsWbITZcpEtGgRUbduRP7+RKVK8QkPHhAdOkS0YIHO\n7x4bS2RgQFS9Orfl7VsiE5P0n9nOOzspm0EOivAZS3VXGVCTO5Vp35NlGX3kqQgJIbIs/pJi81iQ\nZR5LssxjSRPGEa0Z24BsGx+hXLl60LnQc/Qk6gndH3Sfbry6QZUsK6V73Y7lOpJXoBf1OdCH7Avb\nk/s5d7rY6yIVNSqqdVy9QvXo9NPTtPPuTvqQ9IG2tt762d/la5InWx7Kky3PD7n3gAH8H5EJEW38\nIW0QCAQCwbdl2DAiU1Mia+sf3RKBQCD4wWTKRERE//sf0alTRO2TTc8CAojCwohatNBs69OH+08b\nmxlUrRqRXffCNO/MIGpcqh4Z5zSmlzEvacaZGdS1fNdUt5pWfxqVXFqScrxuRsPadCIiovnz+Z6T\nJhE939uN3v7VgGKS3lN5i/Lq8wCia9eIKlT4No8gJTWta9K4k+PoZPBJ2tpmK2XNnJXG/DmGrPNZ\n0/0396mceTmd5xkYGNCAagNo+ZXl1KFcB619225vo87lOn+P5n81DABA147IyMg0TzQ2Nv4mDfoc\nDAwMSM/XoMeRj6ndrnYUFpqTkhSJ1KZuFVrZzJOaNiXq3Vv7x0BEJFfKyfOqJ50LvUBxWzZTjhxE\n2xqsJrp3j6huXSInJ6LAQKING/j/jx4lypaNiIgePSKqV4/oxQuid/FRZDW2IfWv15EWtv833e/Q\nYXcHKpDQgNb270e1F7SlcjaFyKOxh+aAjRv5F3TuHFGuXES1axONHk3Uq5fO6wUHEzVoQPTkCf//\nqFFETZum3Qa5Uk5ll5elnpZL6cDCRnT2LFFA0HOqubYKxbu9puzZDdL9Hinx9CTyuXqeIquPoIu9\nL6q3t5u0h+7kXUh3R52mJluaUOvSralv1b6fdO3YpFhy3OJIL6Jf0OEuh6mMWZlUxxx/fJz+2vYX\nVbOqRse6HqPc2XJ/8ncQCAQCgUAgEAgEPzcBAUQ9e/IUTkXXruyAGD1a/3nbtoFGne1NuUqdofeJ\n7ylvtrzUuXxnGlN3jM65xaHbp6mDfXl689yIcuTQbAf4/scK1yBD81i6M+COet/jx0R2dkTPn3+N\nb5o+SijJbK4Zudm70cAaAz/p3CRFEhVeWJj8XPzI1sSWtt/eTjb5bajFthZ0Z8AdssprleqctObr\nPxK9zpAiRYqQgQFPfsPCwsjKSvOlDAwMKDg4+Pu0MAOk93BlChntvr2fJozLQrlfNaL46FxkZkZ0\n+DCRkVHq48Niwqjc8nL0ZNArKmKTjW7fJrJKbdNULFpEdCUwmtqN8qd55+dR3LMS9EDmS0vaTKbu\nlbrrPU8JJZnPNad6d6/T+1AbCo2IJFnPKrSk2WJysnXSHDh3LtGqVUQxMeyynD5d7zUvXSIaPJjo\nwkUFDZnwksyyW9OUKWm3f/fd3eRxwYPqh5wjAzKg6dOJAFA2V3PaWOsGdW5RMP2HkII+fYiUpXdR\nlPV28m7vrd4uU8io8MLCNLL2SFp1dRXdHnCbsmXO9snXj5fFk0wpo3zZ8+ncH5sUSyOOjqDZjWaT\nYQ7DT76+QCAQCAQCgUAg+PmRy4mMjYmCgogsLdkBUbMm/3/+/PrP+/CBqGBBXvg2M0v/Pt7eRGvW\nEB05knrfrVtEdsPXUpshl2hyFU91osDmzUT79xPt2vV53+1ziEqI+uz50dxzc2nV1VVUt1Bduvzi\nMr1PeE+lTEuRr4uvzuOl6gzJpG/HkydPKCQkhEJCQqhMmTLqf4eEhEjKEZIRsmbOSp0qtqE73i1p\n3apctG0b0fnzuh0hRERWea2olGkpuvDSjxwciI4fz9h9Dh4kelq+P806O4saFmtI+/usJtq1kyb7\nTVUb/33Ce5p3fp7WeTde3SDjHKbk52ND27cT1alsTNXfLKHZ52Zr32DUKCJXV25QGo4QIqLwcM7m\ncfV1pdU5i5N38Pp027/g4gIaUXsEXThvQH/+ydsMDAyoZN4qNGTvZGrh5UxhYSCFIu3rHD52mP7a\n+hdFxEZQQABRvoIvqGBebUdK1sxZqVflXvTv8X/Jo7HHZzlCiIhyZs2p1xFCRJQ7W25a1WLVb+8I\n8ff3/9FNECRD2ENaCHtID2ETaSHsIT2ETaSFsIf00GWTLFk4MmPCBP48ezZR//5pO0KIiPLk4eQA\nL6+M3fv4cSJHR937KlQgKpPQi0KXeVKhQkRXr/L2Cxc48P978iXzo1F1R5FHYw+SK+V0vud5ejTk\nEe1uv/srtu77oNcZ8iuSMydraFSvznoaadG2TFvyCvQiR0eiY8fSv3ZYGNHlO+EUGH+YDnc+TJPs\nJpFVgUzUpEI1ev82G/097jL16EG06NBRGnV8FAW/0ziUTgSfoELyRvS//7EDY9YsIt/VjhT46g6F\nx4Zr36h79wwlk4WHE8lt/GnjzY20vflRumsyg5ZcWqr3+MsvLtOL6BfU0taZbt4kqpRMtqNdrTqk\ntAygIzevkHW1W+l2BF6BXuT/xJ9mnZ5LQUFElC+1M4SIaED1ATTFbgo1L9E83e8jEAgEAoFAIBAI\nBF+CmxvP7Tp1Itq7l2jo0Iyd17Mn0dq1nOqSFklJfN2//tJ/zOjRRHnzsgLCzJm87cIFojp1MtYW\nqeBk60Rerb3IKKcR5cqai4xzSkdGI6P8Vs6QT8GlogsdCDpAVeqF0/HjREpl2sevXk1UuvMGci7t\nTEY5NSEnY0YbkHVUR3qSewcVLky0cJ8vGeYwpK2BGiHP48HHKfFeQ2rdmj8XLEg0sF92Mn3vSAeD\nDn5W+yMiiO6YTaSFTRZS66p2ZHH0OE3zn0mHgg4REXcCT5/ysTKFjIYcGUJj/xxLr19moSxZOHRM\nxSS7iRQ26QY5FuxATYfvpb17dd+zs3dnarm9Jf2n+I98XXxpzbU1VLxiOL2Oe6Ezd6xA3gI02X6y\nOh1L8O2wt7f/0U0QJEPYQ1oIe0gPYRNpIewhPYRNpIWwh/TQZ5N8+Yg2bSIqX57o5k0WSs0IdnZE\ncXFEV66kfdz+/USlSxOVKKH/mJYtOZVm9GiWg1y3jlN3KlfOWFsEXw+9zpD58+eTh4cHzZ8/nyIi\nItT/Vm3/1THJZUJtS7elI+GeZGxMdOOG/mM/xCfSgtOr6ZGpB/1T9R+tfdWqEe2c3IGe5N5JrhMV\nFG/pS23zu5NXoBcBoOfRz+lK2BV6cc6eqlfXnNenD1HEWSfyub//s9ofHBFGbzPfoZa2LYmIqHHN\notQ+6yYacWwExXxQUOfOXKBGqSSa4j+FjHIaUb+q/ejmTaKKFbWvlckgE+XIYUDjW7Wipzn3kq8v\ndwbJuRtxl/ye+FHrUq1prdNaqlGwBlXI3IGy1V1BL2JeUMF8n643IhAIBAKBQCAQCARfk/r1icaP\nz5gmpIpMmXh+tnhx2setXk3UN4M1IXLnJlq2jAuO/vMPUfbsGW+P4Oug1xkSExNDMTEx9OHDB+rd\nu7f636rtvwODaw6mxZcWU4nmB+joUe19CqWCAl4EUII8gRxWtSOU20pb222imtY1U12njFkZKmFS\ngsaeHEPZ87+jc0v6kEwhoz339tAE3wnUq/xAiniWX101l4ioUCGiEtSMTj72pdik2E9u+/UEb6qS\npwWX5yWixo2Jnvg5kGkuUxrmuZtq1yaKS5CT44KhtPPuTlrfcj0ZGBjodIaoqG1dmyISXlHZP4NT\n6agsD1hOfar0IZdKLmT4ivPP8j7uTs+NttKLaN1pMoLvh8hllRbCHtJC2EN6CJtIC2EP6SFsIi2E\nPaTHt7BJ//5E//3HURy6CAvjyBFVtH9GaNOGnSHz53+dNgo+jSz6dkxJr/TIb0AFiwrk1dqLXHb1\npweBz2mYrDu13dWWKlpUpPPPztPDyIf0PuE9mcfZ0yiLY+T4R1a91/L8y5MqrKxALUq2oAdZMlFf\nKy8adMSZiIhWlw+iS5WIMmfWPqdjS2Na8q4O7X+wnzqV76TzuudCz9EE3wn0PvE9Xe17lTIZsH/r\nUY6dNMxqjPq4Ro2I+vY1oA0zXanT2tF0fHQ7Ohy+mjxOXKFn7gFkkYcdGDdv6s9xy5wpMzmVdKI3\nyr3k4zOSajR4SQnyBLodfpu2Bm6lW/1vaR0fcrYGZS0pp8fvgkVkiEAgEAgEAoFAIPhpyZ+fNUam\nT+dUm5RcvMgiqMnL6Qqkjd7SuqtXryY7OzsqWbIkAaCePXuSt7c3FSlShDZs2EBVqlT53m3Vy7cu\n1RPw5A7VWGFPLjWd6U3CS7I1saUCeQvQ8FrD6en7p9TKwZpWLsuWrgKw1y0vssxjSc9OO9C2bUSr\ndjyh1x9e06mtNenlS6IFC7SPf/yYqHKPjfRnH286/LfudJmqnlWpR6UetOHGBpr4v4kkV8pp3Mlx\n9DQUdKr9bapVXRNvVaMGkUIJCmlQhxZ2GUAzzkwnw9OrqY/j/6h3bz6mdGmiHTv0a7QefniYJh2f\nSaHzvCmpry0Z5jCkQvkLUb+q/ahLhS7q46KjOfRsiI8rLbuyhN6PfZ/ucxYIBAKBQCAQCAQCqRIV\nRWRjw1EgefNq75swgSvWTJ36Y9omZaRaWldvZMjChQupe/fuRES0bds2unnzJoWEhND169dp6NCh\ndObMme/Vxh9O9SJlyeatC+25u54eDrtLFnks1PsMUYxCHrE2SHqonAWJBYnGjSMKDypCNWsUoflX\nWEgnJX/8QeRs24q2PRxCb2IjyTS3tkJv8Ltgeh79nP6p9g9Z5rGkUcdHUVRCFO1uv5s61vmTrIdq\nZ0E5OREdOmRA23q5Uxvv5mRrakuzB9Sjvn2JunZl0dWnT0krXSclDkUdqHN0Z0KtqdSoQAfa7bJK\n53HXrrFDxaXS33TnTWD6D0cgEAgEAoFAIBAIJIyhIVGtWkQnThC1aqW97+pVogEDfky7BJ+HXs2Q\nrFmzUtasnPZx8OBB6tatG5mYmFDDhg3pw4cP362BUqHvHzOoZfhlLUcIEdGZMxwOlVV/hkwqsmcn\nWrKEqG1bolOniM6f1+9MWb00H+WPcKT+qzam2rfrzi5qXao1ZcmUhVqVakVWea1oXct1VK/Q/+hN\nRCYyM9M+fuxYorNniRrb2pFzKWdyredKdnYGVLMmKyrXrEk0YwZRtmxptD1LdmpSvAlF266gwi+H\npdq/ZQtR27b+FBDAJYxtTW1pX8d9GX84gm+CyGWVFsIe0kLYQ3oIm0gLYQ/pIWwiLYQ9pMe3tEnz\n5kSHDmlvA9gZUrXqN7ut4BugNzIkU6ZMFBYWRsbGxnTy5EkaP368el98fPx3aZyU6NQ+O9Ws+QeF\nuxKZmxO9f0+0cCE7Fxo0+PTrtW3LaTC9ehG5uOgvv5Q9O9FMRzcaGPA/ehrVmgobFqaohCi69PwS\nbQncQouaLCIi1vPw7+5PRHxdM7PUisRZkll7S+st6n9v3kx0/Djnt9Wrl37bXSq60MuwzHTdpzS9\n60eUJw87gy5eJBoxgjuDmzeJJk/+lCciEAgEAoFAIBAIBNLmr7+I5szhOY+BAW979oznWp9SoUbw\n49GrGXLw4EHq168fyeVycnJyotWrVxMRe9nmzp1Lh1K6w34g3ysHacQIog8fiJYuJWrWjOtUFyjA\n2//449vdVy4nMnKaSUWa7qV/6w2iqaemkk1+GypiWITWOq2lLJm0fVorVrBjYmPqYJKvRkwMkYUF\ndwK1axNt2EBUpw7RypVEMhmrKN+7l3bKjUAgEAgEAoFAIBD8bNjaEm3dqokE2bOHaN06ooMHf2y7\npIpUNUP0OkOIiGQyGcXExJCxsUarIjY2lgBQnjx5vksDM8L3erhRUayDERbGGh87d6auAPOtGDpc\nTsH5NlBC8R3Uu3Jv6lCug95jW7XiyJMuXfQe8lW4fZuocGG+16VLRKNHc81ugOjwYXYYqbylAoFA\nIBAIBAKBQPArMHEiLw4vXMhzn65d2UEyadKPbpk0kaozRK9myOXLl+nNmzdqR8jGjRvJycmJxo0b\nR0lJSd+tgVLC0JAoJIQoLo5o9+7v5wghInL5Owvd2dybjnU9nqYjRCYj8vMjatjw27epXDlWUd66\nlcjNjUVhiYhOnfKn5s2FI0RKiFxWaSHsIS2EPaSHsIm0EPaQHsIm0kLYQ3p8a5v06EHk5UWUmEg0\ncyZHxA8f/k1vKfgG6HWG9OvXj7J/FJ04ffo0jR07llxcXChfvnzUt2/f79ZAqZE5MwuMfu+JfuXK\nrOlx/nzax12+TFS0KKewfC9MTIiGDBHOD4FAIBAIBAKBQPDrU6wYF6BwdiZav54FVVOW2hVIH71p\nMhUrVqSbN28SEdHAgQPJzMyMpkyZkmqfFJBq2M3XZtYsLn27cqX+Y1xdWWPE3f37tUsgEAgEAoFA\nIBAIfif27OH52YEDRJaWP7o10kaq83W9kSEKhYJkMhkREZ04cYLq16+v3ieXy7/oppGRkdSoUSMq\nWbIkOTo6UlRUlM7jihQpQhUqVKDKlStTjRo1vuievwKdOxPt2sXhWPrw8WE9E4FAIBAIBAKBQCAQ\nfBtatyYKCBCOkJ8Zvc6QTp06kZ2dHTk5OVGuXLmo3seaqw8fPiRDQ8Mvuqm7uzs1atSIgoKCyMHB\ngdz1hDEYGBiQv78/Xb9+nS5fvvxF9/wVKFyYqFo1ok2bdO9/+JDozRuimjW/b7tSIvImpYewibQQ\n9pAWwh7SQ9hEWgh7SA9hE2kh7CE9hE0EGSGLvh0TJkygBg0a0KtXr8jR0ZEyZWK/CQBasmTJF910\n//79dOrUKSIicnFxIXt7e70OESmG0/xIpk1jL2SXLkS5cvG2uDiis2eJrl/nqJBMel1cAoFAIBAI\nBAKBQCAQCNIsrfutMDIyonfv3hEROzuMjY3Vn5NTrFgxyp8/P2XOnJn69etHffr00Xk9qeYgfSva\ntiWytiaaN48FXV1ciI4eJYqIYPGepk1/dAsFAoFAIBAIBAKBQCCQ7nxdb2TIl9KoUSN69epVqu0z\nZszQ+mxgYEAGesqQnDt3jgoUKEARERHUqFEjKlWqlDpd53dm8WKiv//mlJlSpYgCA4mCg/m/smV/\ndOsEAoFAIBAIBAKBQCCQNt/MGXL8+HG9+ywsLOjVq1dkaWlJL1++JHNzc53HFShQgIiIzMzMqFWr\nVnT58mW9zpDu3btTkSJFiIjI0NCQKlWqRPb29kSkyRn7VT4HBfmTqytRUpI9PXhA1LKlPwUESKd9\nCxcu/KWf/8/4+caNGzRs2DDJtOd3/yzsIa3Pwh7S+6zaJpX2/O6fVduk0h7xWWMLqbTnd/8s7CG9\nz2I+8mM/L1y4kG7cuKGen0uVH5ImM3r0aDIxMaExY8aQu7s7RUVFpdIMiYuLI4VCQXnz5qXY2Fhy\ndHSkyZMnk6OjY6rrSTXs5nfF399f/UMQSANhE2kh7CEthD2kh7CJtBD2kB7CJtJC2EN6CJtIC6nO\n13+IMyQyMpLat29PoaGhVKRIEdq5cycZGhpSWFgY9enThw4dOkTBwcHUunVrIuJSvl26dKFx48bp\nvJ5UH65AIBAIBAKBQCAQCAS/M1Kdr/8QZ8jXRqoPVyAQCAQCgUAgEAgEgt8Zqc7XM/3oBgh+PZLn\nTQqkgbCJtBD2kBbCHtJD2ERaCHtID2ETaSHsIT2ETQQZQThDBAKBQCAQCAQCgUAgEPxWiDQZgUAg\nEAgEAoFAIBAIBN8Eqc7XRWSIQCAQCAQCgUAgEAgEgt8K4QwRfHVEjp70EDaRFsIe0kLYQ3oIm0gL\nYQ/pIWwiLYQ9pIewiSAjCGeIQCAQCAQCgUAgEAgEgt8KoRkiEAgEAoFAIBAIBAKB4Jsg1fm6iAwR\nCAQCgUAgEAgEAoFA8FshnCGCr47I0ZMewibSQthDWgh7SA9hE2kh7CE9hE2khbCH9BA2EWQE4QwR\nCAQCgUAgEAgEAoFA8FshNEMEAoFAIBAIBAKBQCAQfBOkOl8XkSECgUAgEAgEAoFAIBAIfiuEM0Tw\n1RE5etJD2ERaCHtIC2EP6SFsIi2EPaSHsIm0EPaQHsImgowgnCECgUAgEAgEAoFAIBAIfiuEZohA\nIBAIBAKBQCAQCASCb4JU5+siMkQgEAgEAoHg/+3df2zU9R3H8VdbSoRBrDqIpe2stPyw12vvAEEY\nIJZesfyYRLMwdQEl+8MZUCOYbviH8IfoksFcgmzBjOB+BAUc0rlZq6QMo9YqCDhhQmcRKBCYII4K\n/XF97w/Sk3oHVLkfH/k+H4mx37v7Xj+9Z9ry/fT7/RwAAPAUJkMQd1yj5x6auIUebqGHe2jiFnq4\nhyZuoYd7aIKeYDIEAAAAAAB4CmuGAAAAAACAhHD1eJ0zQwAAAAAAgKcwGYK44xo999DELfRwCz3c\nQxO30MM9NHELPdxDE/QEkyEAAAAAAMBTWDMEAAAAAAAkhKvH65wZAgAAAAAAPIXJEMQd1+i5hyZu\noYdb6OEemriFHu6hiVvo4R6aoCeYDAEAAAAAAJ7CmiEAAAAAACAhXD1e58wQAAAAAADgKUyGIO64\nRs89NHELPdxCD/fQxC30cA9N3EIP99AEPcFkCAAAAAAA8BTWDAEAAAAAAAnh6vE6Z4YAAAAAAABP\nYTIEccc1eu6hiVvo4RZ6uIcmbqGHe2jiFnq4hyboCSZDAAAAAACAp7BmCAAAAAAASAhXj9c5MwQA\nAAAAAHgKkyGIO67Rcw9N3EIPt9DDPTRxCz3cQxO30MM9NEFPMBkCAAAAAAA8JSVrhqxfv16LFy/W\nv//9b7333nsaMWJEzMfV1NTokUceUTgc1s9+9jNVVVXFfJyr1yABAAAAAOBlrh6vp+TMEL/fr40b\nN2rixIkXfEw4HNa8efNUU1Oj3bt3a+3atdqzZ08SRwkAAAAAAK5EKZkMGT58uIYOHXrRxzQ0NKiw\nsFD5+fnKzMzUT37yE23atClJI8Tl4Bo999DELfRwCz3cQxO30MM9NHELPdxDE/SEs2uGNDc3Ky8v\nL7Kdm5ur5ubmFI4IAAAAAABcCXol6olDoZCOHj0adfvSpUs1Y8aMS+6flpb2jT7ffffdp/z8fElS\nVlaWAoGAJk2aJOmrmUG2k7PddZsr42H73HYXV8bj9e0urozH69tdXBkP22yzzfbFtidNmuTUeLy+\nTQ/3trtuc2U8Xtt+5plntGPHjsjxuatSsoBql9tuu03Lli2LuYBqfX29Fi9erJqaGknSU089pfT0\n9JiLqLq6IAsAAAAAAF7m6vF6eqoHcKEXZdSoUdq3b5/279+vtrY2vfjii/rRj36U5NHh2+iaGYQ7\naOIWeriFHu6hiVvo4R6auIUe7qEJeiIlkyEbN25UXl6e6uvrNW3aNFVWVkqSDh8+rGnTpkmSevXq\npRUrVmjKlCkqKirSrFmzdNNNN6ViuAAAAAAA4AqS0stk4sXV024AAAAAAPAyV4/XU36ZDAAAAAAA\nQDIxGYK44xo999DELfRwCz3cQxO30MM9NHELPdxDE/QEkyEAAAAAAMBTWDMEAAAAAAAkhKvH65wZ\nAgAAAAAAPIXJEMQd1+i5hyZuoYdb6OEemriFHu6hiVvo4R6aoCeYDAEAAAAAAJ7CmiEAAAAAACAh\nXD1e58wQAAAAAADgKUyGIO64Rs89NHELPdxCD/fQxC30cA9N3EIP99AEPcFkCAAAAAAA8BTWDAEA\nAAAAAAnh6vE6Z4YAAAAAAABPYTIEccc1eu6hiVvo4RZ6uIcmbqGHe2jiFnq4hyboCSZDAAAAAACA\np7BmCAAAAAAASAhXj9c5MwQAAAAAAHgKkyGIO67Rcw9N3EIPt9AUcMNsAAARK0lEQVTDPTRxCz3c\nQxO30MM9NEFPMBkCAAAAAAA8hTVDAAAAAABAQrh6vM6ZIQAAAAAAwFOYDEHccY2ee2jiFnq4hR7u\noYlb6OEemriFHu6hCXqCyRAAAAAAAOAprBkCAAAAAAASwtXjdc4MAQAAAAAAnsJkCOKOa/TcQxO3\n0MMt9HAPTdxCD/fQxC30cA9N0BNMhgAAAAAAAE9hzRAAAAAAAJAQrh6vc2YIAAAAAADwFCZDEHdc\no+cemriFHm6hh3to4hZ6uIcmbqGHe2iCnmAyBAAAAAAAeAprhgAAAAAAgIRw9XidM0MAAAAAAICn\nMBmCuOMaPffQxC30cAs93EMTt9DDPTRxCz3cQxP0BJMhAAAAAADAU1gzBAAAAAAAJISrx+ucGQIA\nAAAAADwlJZMh69evl8/nU0ZGhrZv337Bx+Xn56ukpETBYFCjR49O4ghxObhGzz00cQs93EIP99DE\nLfRwD03cQg/30AQ9kZLJEL/fr40bN2rixIkXfVxaWpq2bNmiDz74QA0NDUkaHS7Xjh07Uj0EfA1N\n3EIPt9DDPTRxCz3cQxO30MM9NEFP9ErFJx0+fHiPH+vitUW4uM8//zzVQ8DX0MQt9HALPdxDE7fQ\nwz00cQs93EMT9ITTa4akpaWpvLxco0aN0nPPPZfq4QAAAAAAgCtAws4MCYVCOnr0aNTtS5cu1YwZ\nM3r0HG+99Zays7N1/PhxhUIhDR8+XBMmTIj3UBFn+/fvT/UQ8DU0cQs93EIP99DELfRwD03cQg/3\n0AQ9kdK31r3tttu0bNkyjRgx4pKPXbJkifr166cFCxZE3VdYWKj//Oc/iRgiAAAAAAD4lgoKCtTY\n2JjqYURJyZoh57vQXMyXX36pcDis/v37q6WlRbW1tXriiSdiPtbFFxYAAAAAALgpJWuGbNy4UXl5\neaqvr9e0adNUWVkpSTp8+LCmTZsmSTp69KgmTJigQCCgMWPGaPr06aqoqEjFcAEAAAAAwBUkpZfJ\nAAAAAAAAJFvczgzJyMhQMBhUcXGxAoGAli9fHpe3xW1tbdWsWbM0ZMgQ3XLLLfr0008j991+++26\n5pprLrog62OPPaabbrpJpaWluvPOO3Xq1KnIfU899ZSGDBmi4cOHq7a2NnL7tm3b5Pf7NWTIED38\n8MPdnm/dunXy+XwqLi7Wvffee9lfXyKlookkffHFF8rNzdX8+fNj7u/VJsnuUVdXp2AwGPmvT58+\nqq6ujtqfHvHtsXXrVo0YMUKZmZl66aWXut33/PPPa+jQoRo6dKj++Mc/xtzfqz2k5Df59NNPNXLk\nSAWDQfl8Pv32t7+Nub9Xm6Tie+TAgQOqqKhQUVGRfD5f1O8Xybs9pNQ0qaqqkt/vl9/v17p162Lu\n79UmieqxfPly+Xw+lZaWqry8XAcOHJAk7dixQ+PGjVNxcbFKS0vpEUOym5z/OYPBoGbOnBlzf682\nSXYPM9NDDz0kn8+noqKiqNetCz3i2+P3v/+9SkpKFAwGNXbsWO3cuTNyn/PH6xYn/fr1i3x87Ngx\nKy8vtyeeeOKyn/fZZ5+1n//852Zm9sILL9isWbMi923evNn+9re/2fTp0y+4f21trYXDYTMzq6qq\nsqqqKjMz++ijj6y0tNTa2tqsqanJCgoKrLOz08zMbr75Znv33XfNzKyystJeffVVMzPbu3evBYNB\n+/zzz83M7Pjx45f99SVSKpqYmT300EN2zz332Lx582Lu79UmqephZnbixAm79tpr7cyZM1H30SO+\nPfbv32+7du2y2bNn24YNGyK3f/bZZzZ48GA7efKknTx5MvLx13m1h1nym7S1tVlbW5uZmZ0+fdpu\nuOEGO3jwYNT+Xm2S7B5mZrfeequ98cYbZmbW0tJiX375ZdT+Xu1hlvwmr7zyioVCIQuHw9bS0mI3\n33yzffHFF1H7e7VJonrU1dVFfl//7ne/i/xe37t3rzU2NpqZ2eHDhy07O9tOnToVtb9Xe5glv8nX\nP+eFeLVJsnvU1dXZD3/4Q+vs7LRwOGxjx461LVu2RO1Pj/j2OP/3QnV1tU2ePDmy7frxekLWDBkw\nYIBWrVqlFStWSJLC4bAee+wxjR49WqWlpVq1alXksb/61a9UUlKiQCCgX/7yl1HPVV1drTlz5kiS\n7rrrLm3evDlyX1lZmfr163fRsYRCIaWnn/syx4wZo0OHDkmSNm3apLvvvluZmZnKz89XYWGh3n33\nXR05ckT/+9//NHr0aEnS7Nmz9fLLL0uSnnvuOc2bN09XX321JOn73//+t3p9UiFZTbZt26Zjx45d\ndH0XmiSvR5f169dr6tSpuuqqq6Luo0d8e9xwww3y+/2R17TLa6+9poqKCmVlZSkrK0uhUEg1NTVR\n+9PjnGQ0yczMVGZmpiTpzJkzyszMVN++faP2p0lyeuzevVvhcFiTJ0+WJPXt21d9+vSJ2p8e5ySj\nyZ49ezRx4kSlp6erb9++Kikp4efWBcSzx6RJkyK/r89/PYcMGaKCggJJUnZ2tgYOHKjjx49H7U+P\nc5LRpKdokpweAwcOVFtbm1pbW3XmzBm1t7fr+uuvj9qfHvHt0b9//8jHp0+f7vYauH68nrB3k7nx\nxhsVDod17Ngxvfzyy8rKylJDQ4NaW1s1fvx4VVRUaM+ePaqurlZDQ4OuuuoqnTx5Mup5mpublZeX\nd26wvXrp6quv1okTJ3Tttdd+4zGtXr1ad999t6Rzi7Xecsstkftyc3PV3NyszMxM5ebmRm7PyclR\nc3OzJGnfvn1KS0vT+PHjFQ6HtXjxYk2ZMuUbjyNVEt0kKytLCxcu1F/+8he9/vrrPRqTl5sk83vk\nhRde0MKFCy85Jnpcfo8LOXz4cLfXrev1vBgv95AS30SSDh06pKlTp6qxsVG//vWvL/m7xctNEt1j\n7969ysrK0l133aWmpiaVl5fr6aefjjpAP5+Xe0iJb1JaWqolS5ZowYIFamlpUV1dnXw+30X38XKT\nRPT4wx/+oKlTp0bd3tDQoPb29sjkyIV4uYeUnCZnz57VyJEj1bt3b/3iF7/QHXfccdH9vdwk0T2K\niopUUVGh7OxsmZnmz5+vYcOGXXR/esSnx8qVK7V8+XK1tLTo7bff/tZjSnaPpLy1bm1trT788ENt\n2LBB0rk1Jfbt26fNmzdr7ty5kZm9a665JmFjePLJJ9W7d2/dc8893/o52tvb1djYqH/+8586ePCg\nJk6cqA8//DAy8/RdEu8mZqaVK1dq6tSpGjRoUI+uP6PJVxL5PXLkyBH961//uuQPZnp8hZ9Z7klU\nk9zcXO3atUtHjhzRrbfeqoqKChUWFsZ8LE2+kogeHR0devPNN7Vjxw7l5eVp1qxZWrNmjebOnRvz\n8fToLhFNQqGQ3nvvPY0bN04DBgzQ2LFjLzo5RZOvxKPHn//8Z23fvl2/+c1vut1+5MgRzZ49+4Jr\nT3WhR3eJanLgwAFlZ2erqalJZWVl8vv9Gjx4cMz9afKVRPTYunWr6urq1NzcLDNTKBTSlClTNH78\n+Jj70+Mrl9vjwQcf1IMPPqi1a9dq7ty5qqur+8ZjSEWPhE2GfPLJJ8rIyNDAgQMlSStWrFAoFOr2\nmNdee+2SB805OTk6cOCABg0apI6ODp06darbX+7S0tIuOZY1a9boH//4R7fLB3JycnTw4MHI9qFD\nh5Sbm6ucnJxup7513S5JeXl5GjNmjDIyMpSfn6+hQ4eqsbFRI0eOvOQYXJDIJtddd53q6+v15ptv\nauXKlTp9+rTa2trUv39/LV26NOo5aJK875F169bpzjvvVEZGxgWfgx7x63G+838+5eTkaMuWLZHt\ngwcPqqysLOZ+9Dgn0U3Ol52drQkTJmjHjh0xJ0NokvgeeXl5CgQCys/PlyTNnDlT9fX1MSdD6HFO\nMr5HFi1apEWLFkmS7r333gv+lZUm8e3xxhtvaOnSpdq6dWvkcj7p3AHK9OnTtXTp0sgp4rHQ45xk\nNMnOzpZ07q/skyZN0gcffBBzMoQmie9RX1+vysrKyCWvlZWVeuedd2JOhtAjMb9DZs2apQceeKDb\nbU4fr19yRZQe+vqCLKFQyBYvXmxmZqtWrbKZM2dae3u7mZl9/PHH1tLSYjU1NTZu3LjIAmknTpyI\net5nn33WHnjgATMzW7t2bdTikHV1dRddkOXVV1+1oqKiqMVTuhZkaW1ttU8++cQGDx4cWZBl9OjR\nVl9fb52dnd0WZKmpqbE5c+aY2bnFWPLy8mKO2RWpamJmtmbNmgsuoOrVJqnqMWbMmJiLR3WhR3x7\ndJkzZ063hQhPnDhhN954o508ebLbx1/n1R5myW9y6NChbvsNGzbMPv7446j9vNok2T06OjqstLQ0\n8jrfd999tnLlyqj9vNrDLPlNwuGw/fe//zUzs507d1pxcXFkkbvzebVJonps377dCgoKIouldmlt\nbbWysjJ75plnLjour/YwS36TkydP2tmzZ83s3OszZMgQ27NnT9T+Xm2S7B6bNm2y8vJy6+josLa2\nNps8ebK98sorUfvTI7499u3bF/m4urraxo8f3+1+l4/X4zYZkpGRYYFAwHw+n5WWltqyZcsig+3s\n7LRFixaZ3++34uJiKysri6w6+/TTT1tRUZEFAgF7/PHHo5737Nmz9uMf/9gKCwttzJgx1tTUFLlv\n/PjxNmDAAOvTp4/l5uZabW1t1P6FhYX2gx/8wAKBgAUCgci7bpiZPfnkk1ZQUGDDhg2zmpqayO3v\nv/++FRcXW0FBgc2fP7/b8z366KNWVFRkfr/fXnzxxct6zRItFU26rFmzJuq16+LVJqno0dTUZLm5\nuRcdFz3i26OhocFyc3Pte9/7nl133XVWXFwcuW/16tVWWFhohYWFtmbNmpjj8moPs+Q3qa2ttZKS\nEistLbVAIGDPP/98zHF5tUkqvkdef/11KykpMb/fb/fff3/kH2Xn82oPs+Q3OXPmjBUVFVlRUZGN\nHTvWdu7cGXNcXm2SqB7l5eV2/fXXR17PO+64w8zM/vSnP1lmZmbk9kAgELOJV3uYJb/JW2+9ZX6/\n30pLS83v99vq1atjjsurTZLdw8zskUceMZ/PZ0VFRbZgwYKY46JHfHs8/PDD5vP5LBAIWCgU6jY5\n4vrxeppZHN5cGAAAAAAA4DsiIW+tCwAAAAAA4ComQwAAAAAAgKcwGQIAAAAAADyFyRAAAAAAAOAp\nTIYAAAAAAABPYTIEAAAAAAB4CpMhAAAgoT777DMFg0EFg0FlZ2crNzdXwWBQ/fv317x581I9PAAA\n4EFpZmapHgQAAPCGJUuWqH///nr00UdTPRQAAOBhnBkCAACSquvvMFu2bNGMGTMkSYsXL9acOXM0\nceJE5efn669//asWLlyokpISVVZWqqOjQ5K0bds2TZo0SaNGjdLtt9+uo0ePpuzrAAAA311MhgAA\nACc0NTWprq5O1dXV+ulPf6pQKKRdu3apT58++vvf/6729nbNnz9fL730kt5//33df//9evzxx1M9\nbAAA8B3UK9UDAAAASEtLU2VlpTIyMlRcXKzOzk5NmTJFkuT3+7V//37t3btXH330kcrLyyVJ4XBY\ngwYNSuWwAQDAdxSTIQAAwAm9e/eWJKWnpyszMzNye3p6ujo6OmRm8vl8evvtt1M1RAAAcIXgMhkA\nAJByPVnPfdiwYTp+/Ljq6+slSe3t7dq9e3eihwYAAK5ATIYAAICkSktLi/w/1sfnP+b87czMTG3Y\nsEFVVVUKBAIKBoN65513kjdwAABwxeCtdQEAAAAAgKdwZggAAAAAAPAUJkMAAAAAAICnMBkCAAAA\nAAA8hckQAAAAAADgKUyGAAAAAAAAT2EyBAAAAAAAeAqTIQAAAAAAwFOYDAEAAAAAAJ7yf4y4A2bg\n5NerAAAAAElFTkSuQmCC\n", "text": [ "<matplotlib.figure.Figure at 0x7faa96b2fe10>" ] } ], "prompt_number": 12 }, { "cell_type": "markdown", "metadata": {}, "source": [ "On Dec 15, the Neah Bay surge is slightly higher (10cm) than Tofino. But the timing of the maximum is a good match" ] }, { "cell_type": "code", "collapsed": false, "input": [ "start='01-Dec-2006'\n", "end = '30-Dec-2006'\n", "sd =datetime.datetime.strptime(start,'%d-%b-%Y')\n", "sd = sd.replace(tzinfo=pytz.timezone('UTC'))\n", "ed =datetime.datetime.strptime(end,'%d-%b-%Y')\n", "ed = ed.replace(tzinfo=pytz.timezone('UTC'))\n", "[maxTof,maxNB,tmaxTof,tmaxNB,mean_diff, mean_abs_diff, rms_diff,corr] = get_statistics(\n", "np.array(Tof_anom[:,0,0]),np.array(anom['NeahBay']),np.array(Tof_time),np.array(time['NeahBay']),sd,ed)\n", "\n", "print 'From', start, 'to', end\n", "print 'Mean (Tofino -Neah Bay)', mean_diff" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "From 01-Dec-2006 to 30-Dec-2006\n", "Mean (Tofino -Neah Bay) 0.0410648408411\n" ] } ], "prompt_number": 13 }, { "cell_type": "heading", "level": 3, "metadata": {}, "source": [ "Another Surge: Nov 2006" ] }, { "cell_type": "code", "collapsed": false, "input": [ "start='01-Nov-2006'\n", "end = '30-Nov-2006'\n", "\n", "[Tof_time, Tof_anom]=compare_surge(start,end)\n", "\n", "start='14-Nov-2006'\n", "end = '18-Nov-2006'\n", "sd =datetime.datetime.strptime(start,'%d-%b-%Y')\n", "sd = sd.replace(tzinfo=pytz.timezone('UTC'))\n", "ed =datetime.datetime.strptime(end,'%d-%b-%Y')\n", "ed = ed.replace(tzinfo=pytz.timezone('UTC'))\n", "[maxTof,maxNB,tmaxTof,tmaxNB,mean_diff, mean_abs_diff, rms_diff,corr] = get_statistics(\n", "np.array(Tof_anom[:,0,0]),np.array(anom['NeahBay']),np.array(Tof_time),np.array(time['NeahBay']),sd,ed)\n", "\n", "print 'From', start, 'to', end\n", "print 'Tofino Max/Time', maxTof, tmaxTof\n", "print 'Neah Bay Max/Time', maxNB, tmaxNB\n", "print 'Mean (Tofino -Neah Bay)', mean_diff" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "From 14-Nov-2006 to 18-Nov-2006\n", "Tofino Max/Time 0.725153 2006-11-15 19:00:00+00:00\n", "Neah Bay Max/Time 0.63 2006-11-16 01:00:00+00:00\n", "Mean (Tofino -Neah Bay) -0.0594614228353\n" ] }, { "metadata": {}, "output_type": "display_data", "png": 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ERERERMUk64SEUqlU/d/Hxwfjx49HfHy8WrVtAHB1dcX169f13TwiIiIiIiIiyoeXlxfO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qBmVRfDXIxgfkiYJ1/EKYJ3jDcGHhiII9d9BcatBBwdyRgsjorPPzUfc3xHAIWFeHjlCFoukkPA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\n1hQvL68YxzOflMsmICBA/v77b+nSpYusXbs22n179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"text": [ "<matplotlib.figure.Figure at 0x7faa95ae56d0>" ] } ], "prompt_number": 14 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Neah Bay Surge is several hours later later and 9 cm lower on Nov 15/16." ] }, { "cell_type": "code", "collapsed": false, "input": [ "start='01-Nov-2006'\n", "end = '30-Nov-2006'\n", "sd =datetime.datetime.strptime(start,'%d-%b-%Y')\n", "sd = sd.replace(tzinfo=pytz.timezone('UTC'))\n", "ed =datetime.datetime.strptime(end,'%d-%b-%Y')\n", "ed = ed.replace(tzinfo=pytz.timezone('UTC'))\n", "[maxTof,maxNB,tmaxTof,tmaxNB,mean_diff, mean_abs_diff, rms_diff,corr] = get_statistics(\n", "np.array(Tof_anom[:,0,0]),np.array(anom['NeahBay']),np.array(Tof_time),np.array(time['NeahBay']),sd,ed)\n", "\n", "print 'From', start, 'to', end\n", "print 'Mean (Tofino -Neah Bay)', mean_diff" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "From 01-Nov-2006 to 30-Nov-2006\n", "Mean (Tofino -Neah Bay) 0.00765545827363\n" ] } ], "prompt_number": 16 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Generally, it looks like the Tofino surges are slightly higher than the Neah Bay surges. There are a few exceptions though, like on the Dec 15, 2006 storm surge and also Nov 13, 2006." ] }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "Inverse Barometer" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "NEMO can correct the sea surface height to account for the force applied the atmospheric pressure. If the atmosphere is at a low pressure then the ssh will be elevated slightly. \n", "\n", "The correction fator given by the NEMO documentation is:\n", "\n", "$ \\eta_{ib} = -\\frac{1}{g\\rho_0}\\left(P_{atm}-P_0\\right) $\n", "\n", "\n", "Questions:\n", "1. How significant is this at the mouth of Juan de Fuca?\n", "\n", "2. Are we double counting this?" ] }, { "cell_type": "code", "collapsed": false, "input": [ "#define constants (from NEMO book)\n", "rho0=1035\n", "P0=101000\n", "g=9.81\n", "NB_lat=48.37\n", "NB_lon=-124.45" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 17 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Find a CGRF point close to Neah Bay\n" ] }, { "cell_type": "code", "collapsed": false, "input": [ "CGRF_path = '/ocean/dlatorne/MEOPAR/CGRF/NEMO-atmos/'\n", "\n", "spr = NC.Dataset(CGRF_path+'slp_y2006m02d04.nc')\n", "print spr\n", "\n", "\n", "bathy_path='/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc'\n", "b=NC.Dataset(bathy_path)\n", "bathy=b.variables['Bathymetry']\n", "X=b.variables['nav_lon']\n", "Y=b.variables['nav_lat']\n", "\n", "lat=spr.variables['nav_lat']\n", "lon=spr.variables['nav_lon']\n", "\n", "#Can't use this for som reason :( \n", "#[i,j] = tidetools.find_closest_model_point(NB_lon,NB_lat,X,Y,bathy[:])\n", "\n", "i=365\n", "j=28\n", "print X[i,j], Y[i,j]\n", "\n", "plt.figure(figsize=(8,8))\n", "pylab.subplot(1,1,1)\n", "pylab.pcolormesh(X[:],Y[:],bathy[:])\n", "pylab.plot(X[i,j], Y[i,j],'or',label='Neah Bay')\n", "\n", "Ci=461\n", "Cj=523\n", "pylab.plot(lon[Ci,Cj]-360, lat[Ci,Cj],'og',label='CGRF point')\n", "pylab.legend(loc=0)\n", "\n", "press_CGRF=spr.variables['atmpres'][:,Ci,Cj]\n", "time_CGRF=spr.variables['time_counter']" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "<type 'netCDF4.Dataset'>\n", "root group (NETCDF4 data model, file format UNDEFINED):\n", " NCO: 4.0.9\n", " nco_openmp_thread_number: 1\n", " Conventions: CF-1.6\n", " title: CGRF sea-level atmospheric pressure forcing dataset for 2006-02-04\n", " institution: Dept of Earth, Ocean & Atmospheric Sciences, University of British Columbia\n", " source: https://bitbucket.org/salishsea/tools/raw/tip/SalishSeaCmd/salishsea_cmd/get_cgrf_processor.py\n", " references: /ocean/dlatorne/MEOPAR/CGRF/NEMO-atmos/slp_y2006m02d04.nc\n", " comment: Processed from goapp.ocean.dal.ca::canadian_GDPS_reforecasts_v1 files.\n", " history: Tue May 27 11:29:47 2014: ncks -4 -L4 -O -d time_counter,18,23 /ocean/dlatorne/MEOPAR/CGRF/rsync-mirror/2006-02-03/2006020300_slp.nc tmp1.nc\n", "Tue May 27 11:29:50 2014: ncrcat -O tmp1.nc tmp2.nc /ocean/dlatorne/MEOPAR/CGRF/NEMO-atmos/slp_y2006m02d04.nc\n", "Tue 27 May 2014 11:29:53 AM : Adjust time_counter values and clean up metadata.\n", " dimensions(sizes): time_counter(24), y(600), x(801)\n", " variables(dimensions): float32 \u001b[4matmpres\u001b[0m(time_counter,y,x), float32 \u001b[4mnav_lat\u001b[0m(y,x), float32 \u001b[4mnav_lon\u001b[0m(y,x), float64 \u001b[4mtime_counter\u001b[0m(time_counter)\n", " groups: \n", "\n", "-124.467224121 48.3496665955\n" ] }, { "metadata": {}, "output_type": "display_data", "png": 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K0Dmg7tTwwOUlMYUQ4p+SjmPCymwDNkAbT7AdBviYmcfuvN75tWG0JUD/BPxe\nGz5pBL3AkzjeYzRfTwgh2SELok+h/+CmARqA6GgIzgDvDJ4/PB1qmt1KgToEWit0guLQbEVD3ctU\ndQ8C0i2d14QQwgpJSVoUGqV2wYst4FvgWAxmCJXnVeecMhuBteGbDByd06juGkcIi6lKPLMZxqEJ\n/vDmLiAFiMZUpY+5yb0vUuHPTDp6bmQ4H3IMH0a1/QT2A71Ahyg2db6X9o23w4YMfL2OcHRvE2iW\nbklhG1p3LMzHIYQoh6QkLaxYFLwPHANcfADPa9ad1ro28KOZUvRPB9q4bqExf2BPJk6k8ThzCJ6y\nDh5vgalGN4OolXo/z/vVtLbj0tuVGMFMvqMLo+p/QvPNP6PDFGFzFOFd4Lj6icF/zKK5125m8RQL\n/PvBZ47ASgnQQgirJEFaFBqtn7N0uJoL6Zje1sr02L5y3WmtBwIbYCs05CD1OEobNuPLUZqyj16s\ngDmgdRBaBwGuQHWUMo3K1w3Ub8ETfE5NzsDDsKfaPWwecTcAoR/A0K3Qn8Wk4kI7tjOQpegnQOv+\nRfdQhBDiH7At6QyIsidn5jETVFtA1vf5nBUHI/fyfq/RvFNnJFVIIhtbttOKsQM+BCJRKhWtewCP\nmMlNjlwE8q6qYTqu5XT7TsE+3hM39yT0KUWbv9bzQMo60o9WISxQoROgO+YlhBClQYFK0j4+Pvj7\n+xMQEMDdd5uSSUJCAp06daJBgwZ07tyZpKSkIs2oKH1MFXIa0BrToezUFccGQj1/atY5iRdncCKd\nbGw4Q00zk5ljMABKHTbrRsYAAXaYdu4xKPUflIqzpBYNgZ4wwyx3NXz/Z6jhmq0qiPSpbuCblTsO\nWwghSpMCBWmlFJGRkezevZsdO3YAMHXqVDp16sShQ4fo0KEDU6dOLdKMitLJtEEfgEZBwD6UWn75\noDfEtq/LHB5nMf3ZQ3MeZy5haeOgF5hhXcfN1KPNgd0XgWBLb+xGmDFVcfBVMMd/8US3Vhx3r4M6\npKErMN4VZhXv9xVCiMJU4Dbpq3urrVy5kiFDzBq7Q4YM4euvvy7cnIkyJBqi38cEVsfLc3xvSodz\nYEMWPsTQiu1kY4MncfASQD2go5nbe2c6sAvICfL1gIFALfgNFjGAjEZwiIb8u89L+Cb8Dj7AuQTL\ndUIIUfoUuCTdsWNHAgMDmTXLFE3i4uLw9DTDazw9PYmLi7tREqIc0/pFoBbgbtmTYtnvCPtOsXZm\nHyIJZi9g8I/4AAAgAElEQVRNiaM6vhxhfYs2NNKV4R1MwO7qiKnzBtgFjzeCqcAwO/gaoghis9N9\nNOAgHdnI60TAeeAdd7ANQqlIlIoszq9dorw4hvLCvOqXdG6EELerQB3Htm3bRs2aNfnrr7/o1KkT\nfn5+eY4rpVBXj7WxCAsLy90ODg4mODj4tjMrSrOLpm1ZpwDPWXpoXwRqwUiYP+4pVib1IMh+B8OY\nTSouNGUv0a0DYAawDkwv72HQzhOqAONSMLOcPcLXXiF83SSEmt8fYyEDCWAPW8cEsoU2jJ/9rhlu\njRlPrbVdSTyAYqNehppvYWZg2wRcKOEMCVGGRUZGEhkZWWTp3/JkJuHh4Tg7OzNr1iwiIyOpUaMG\nsbGxtGvXjgMHDuRNXCYzEVe43JYcg6mCTsCM1QKoDvjAN0GE9RxHU/ayD3/+j+c5+2kdc8ovwB6g\nH2YI9cgYIAo4jtavoNyBXhD2+TjashlH0onibjOpiYPl1NQUIAutc0r1ZY96HsI+Mj+aQycAb8j/\ng0IUl2KfuzstLY3s7GxcXFy4cOECnTt3JjQ0lA0bNlC1alVeffVVpk6dSlJS0jWdxyRIi6spNRds\nh5og2xzYCtgA3pYTnIGl8FODALKxYTbDWJzSn/Rv3cy83ADeGTDXASaewkxLehxTnZ4ODMT5wgUm\nOUUAkEQVdhLIPpoSe8Ibgm3h2EVwtIP0gi8KUur8W7FrErRsp9E/lHRmhCg/ij1IHzt2jN69ewOQ\nlZXFwIEDGT9+PAkJCTzyyCOcOHECHx8f/vvf/1KlSpUizawo/ZT6j2WrEdADhgH3ApUAH+gRtIQ2\nbGEw89hIRxYygLVnusMgBxPMGwEeQBfgG0tSb1p6eXPapOnWCGZD7T5HyMSesye8zHlJthCJKci/\nmw7ejhALZMWgtU/Rf/niFKBgLKgKGj2gpDMjRPkhq2CJUk+p6Zj25bvBwx/Gg/3QFHzdjzKM2XTh\nO+qlHcUhHmZ4Pw3AmLjpXKqRDZyG0Y2oOf0Y2diYAPykLWxYBRwG7Ey6+EA9TzgCcAo4Ak2DTQZi\ngWwgBNMsPjsGcC1zVeCJOAHg/kQa+vMSzowQ5YQEaVEmKPUGuaXpRpaOXCFQfdIJurGGl3ibhilH\nsc2AP6tVZjH9Cc0MJ3l/DTq3WMmvl1pSs8IZPDnLQRpyqlU9+Gktl9u4YzBjt3I4YiJylmW7Nwyr\nD48D7wJLE6CrO6wtvaVqNR2uXIfkGWbwSeNRqAWaynf9SZJ9jbznq4Qy98NEiJImQVqUCSZIgxnM\n3AIcG8GzwFC4y/8XxjGNDmygRmwy2IKTQwLpvdwgCZhsrryj2wGG83+k4UQ8VZmXOZjkqTVM57K/\ngbXRwFpM6bojpjo8DjMEzA5oCu2CIMySlSPAB8BuMCuF1ELrPkX8JAqHsgOmme2cQO3DAWJ+awSD\nQY3Spkd8FczzOwKclCAtRGGTIC3KDKXCMb266wMdoTcwFKgIvp1/B2AGI+n+10Y4Ax82e5IX6syG\nk2shvCvcB9Xbn6AjG/DlKGDGS/96qSXxe2rBg0CspWQd4Gg6pVXBBPpY4MguzFzgPeETd/DDjK1+\nG9i0FxPJagE7LGO9rZPaC339F+JCKnPtnkVfzHs8p9p7pkontDkQAU177MCbk6yhdPwIEaK0kCAt\nyhxTqnYH+kMjd9NW3BDIhvsGfM8bvEbb33bA3zA86B3+b8QYE2Q7AQ9mcJ/XZlqznebsASCO6myn\nFVtoS+ykuvAlpve4L2aismpARUywrmLZroKZNSAWM1Tr3ZxItwvYAVy86ZrWJUVFAY6gNyh8xkQT\ng1++5/XnCxqroQBE6WX0ZBXPRcxBTyq+vApR1sl60qLM0XoicBZYDNEpZn6S74AjsPVMW76jCwea\n3QFV4cOoseiBik+XPEbfpxdS2SORrZ06Me2pUDbQEW9O0p019GexmV40EjiyDTZFwuzDMC7BzGD2\nN6ZaexMmWIMJ0o6YNmpiYLwddA0CXgRcUWouSi2+7lKZJUHthc5BK8lsq5g0ZgLHp/ih1N58z13M\nEDbo9fQAglRfUnEp3swKIW6ZBGlhFbQOxXT0Og07o2EpcACY7MCUmREMYiFT643iq6BeUB2eOjCf\nWTxFuH0ojAcOmnS8OINPyinqEmOqwB8A3miNaYNOBVIgcYMZ+tUOeBhTij4PfAU8FI3WoHV9mItp\nJ/8E6DgM1FDMj4mciVmswFfwXceHOJVUk7dTXsLxhcSbXtJirHl/Zf1MKUULYeWkultYFTM8yx1o\nDTXrmwlPmgAB4DvgdzqwgQD2EEQUVUjCOyWWtEr2AGyxaUMG9vT5ay0kw5/1KrOMfryc8hbpo9yg\nNiYgn8NUcd9n+XwKU+J+dy+mc1kCZohYRwCC9Y/E4Un05gCzjOa7CUAcWjcqtudyPbnzkX8XjJ6r\n4BioDzX8DbrVtef/Tj2WqqOERoDP69evGhdC3B5pkxblhlLbQLWGlsC/LDtD4N62m3Agg6rE04bN\nPMZ83PanwxpM8HUHMgBvWNi5LyvozYbMDjjZp2NPBkmZVcj82wGA9CQXmGtrgm8NYO1hTEe2GHjU\nB4bB6+0n4s1J9tHU9CD/uAaMTAei0Dq4WJ/JlZQrkBppPgQE89mugVRSi9irX2fKDxHo9pbz2mPa\n+SNBV1eEzzD7w2Zo9Ihiz7YQZZoEaVGuKDXXstUC2vib0u89UPmBP6lrH0MDDuLCeRpykGA28a9j\n+2E9pjAMcBcc61GTD3me7bTGkzgysCcdJ87gRUyCD5lbXc0CHjmdyZzhjpkHeJm3aco+fDlKNjYA\n7KE57zKayJkPwMhdaN2imJ/IZUql01WvZe3yPtzbZxMA2/u2h+HQsf23bKC7OS9nFaxeoL9ThO+D\nxroHD7OyhHIuRNklQVqUS0otB1pAPR9TBV4FqGs5eBfY35dCA/eDeBFLP5byWNp8HCzjhukG3wfd\nx1L64UYS9mSSRBVi8OEPGnN0exOYDeyznH8B6A7241Po574UezKZ89tz8DdsCrqXN5jIxgnd4c04\nwJOS+k9cKbM8rJ5Qg/Apl/ef0e8RixeOpPHfH4bAUpj8kSLLcny+3s8RmhR/hoUoByRIi3LLtFc3\nArqaAP03poo6GLgLuA8q+/xJQ/tDfEUIdafHmn5eDsDDkHiXI2mWMcOZ2LOJdpzEmzPU5BANTen4\nT8xkKOsAvRzw4S6dTT+WEbpqGtSFWXcN5ukW8yyTngBuQOJaTDv2XrR+rsieQTeWs2ZFX9r1Xkuk\n/wNU+P4Ck2o453tu6MeWjWQgCsKXQ9jrGh1RZNkTotyTIC3KNTOm2h+43zTKVsTMN1IfU8KuZ86r\nOvQ0XSp8x+tE4PfZcbOedAbghVnM41GYWO11zlGVbGyJpyrbacXZmXXMZGNHNgAxaD3M3HezSfd/\nbb2ouyIW7oOp1UbxIcM5tbmembVsU6Qll3ZAOlp3vCLfOR3iQOuh+XyvFPB2NR9yZjbNtrw3x0zM\n9id0XbOcIHYwRE3jCyC0tTklfNvltEKHwbhZYUybFsrgV2cx7/Gn6T9nLv/tNgS+55rJToQQhUeC\ntCj3zEpaTS2fmgK1wQWzOpYN8BxwD9zR6gDP8gnj9r8HPwJnMG3VycDDcKD3HUxhImk44UQaqbiw\nJqEbmQtcYRSgt6F168v3rQCdL61kZdpDOKzBBPssIBCW1+zKoJSFpN/lBic3WK7ww8xalrNCV84U\nnHaYecTtAEe07mOCdEdXGny/l0MT/Kkw8gIOjpn0dl1Bdcuwr3cnjoe5MPeMWZzTUw/luT5zTIE/\nJ4+tMOtuN8cMS/sA+Bn4CnQCQogiJkFaiCuYtupgwB0UZphVIGZK0Huga+PljGMabdfuMBf8jAnW\nyZjJSxzg2JyarKEb83iMHSvbwn7MOtdro68ZZqVUDBz04bMGAwHownfU2hZvpgOPAyoDXvBW0It8\nwjMcHdAEvowG1Qh0Ojg6WkrKMZi1sB2BBAgcRstfTHF457H7UP/V6K8VWd9BT9dlbElry3SnMTx9\nZhbay4GfCeD+hB/JcHe99pmMsOQf0Lv++TMWQhScBGkhrqJUFKatGsDVlKoDgXuAjtCy/Tae5//o\nxmpqrE82Q7XOYqq/bYCKkDjPkZHMYP6hp0x79EiTpP7jBvf1BybD3T03E/Xr/abtO8py0JLuVyG9\neDbzI5KX1oCdlmPNMRO15LZ9R0JgMABv/jKa8TPfhZFR0CgIoudaMutSpG3dQojCIUFaiHyYtmpP\nTKN0EHg7ms5kIXDHY2Y4VTCRNDl21BRgozG9uJMt72Dat1+B6Xc9z9g+H5pAGn0Rre0KlAcvjgEQ\n+0ddqJLB614RtGI7D6yKhBNAN1hStwezGUZU5t0kz60B7wG9gKFwyUPRxH0X0SoTU03eFTN3OEC0\nVS/yIYQwJEgLcQMmWNfCBOyuZudgoBc07/MzA1hEG7bgzUlqrYg3peljmKrqBMyiXI1g95ONaLHo\nDxi4C2hh5vueC/qvW8+TU0oin7s+QcjSr6EmXAiswDSHcfz7hzdy5w23D05hsPt8vDlJ2BNTYU5O\nO/ZhtO5/4+9czbzfTt6EEIVLgrQQN2GWwATT3vsAePububpD4L4G3+PPPmzIJhUX5vxgqUJO5nLA\nBlPydQBegC/qPcLQ5YvhGeBcDCZ4OmKGWw0tcL58OABAzFeNoBKkdLOn8m8ZZp7y2vDj80H4cpTa\n689Bl21AAlr3uP737INZG/pn4BTlfh7unL+7mQdeiJIhq2AJwZWB+Eb7bYFdpgd2EnDKrKq1lH7M\nyxzMPpoyvP077G7fiHO9nUkMcSRrOCagu2Oagt+BkLT/8mqfcNNDvJ0PJkAfttyv4D2zYvDj+A9+\nrA7pAJUgzcaRqs1Pm45qflCVeN5llFn3eltrsL1+gAbotfwr+Bh4MqFcB2ilLEPYhCiDpCQtSp1r\nA7TtFdtZmOpuMIOL4zFdvlubVa+GYjqV2YK9Rwre7icJIip3LepNBBOPB83ZzVvZr+AamAkzYGrb\nUQDsJJANmR1MR7CBYNqMUzBjqocWKP+BbGPn/vvMh6owsebr9GIFJ/GmT+xaVtbszEPzvjNjr4+Z\nnmhaB137HKZzuRr+sQLdusxQazDzkafmDGVLwfyK4oa1D0IUNanuFoKrA3V1Lk/WnYUJ2kPAozZ4\nY5kZ7CK0sTNBzRbTSew8ptTql8GrXlMBsCGbnQSy/oee4JdBS6+d7Jx+nxm21Q1OtK/OYvqzmP78\nurK1CfqJkZhAQZ5x1TfiyQkGsIh3Y8fD45ZsuwPDYGXnzjw04jszqQpRmJnMLmI6k7XALOzR3wSq\nfcBO0Etu8QGWYmoAMAjTTDAIqJcFsbbwDegpN75WiKImQVoICxOobTElZjCdxU5h6qnvAJf+0NBy\nKGf4Uz+gB2bubzDBcSs5q1JCVeANYBWm5P0xjGowldG8S51VZ02wzoDTI6qyiAEAJmB/2hqeiQHW\nAna5M5XdMP974Sf/AO55ao9pD0+2HKgETDDTj0YRRCTBHJ3eBMbGgJsPJEYDezEzr7kA+9C6awGf\nWumn2sObP1iGqjUH3bakcyTEZRKkhbjK5Tm9fSx7YjBFzOpAMDT1MZ3A9mAmKOuHGatc9YpEojDz\ndgP8hRmmdRGoaZJwfCmRlq476cdS+rGMWifjzTWHgc4Q0PIn9tS/B46sxYzvalSgwKn+D4KfX8em\nbV3hK0ygPgv4mY5gT7h/xBF8cSKd9f/rAV8r84PjyzhM23jOqiCnbtoLvKxQa8z7p90e4+l/zQNv\n8sy6JkRJkiAtRD7MVKHumChsh4myKUAL8Ohqdm+ynOyNqSYNxlR7g6n2rogJ1PsxNcvnMB3OKgFd\nwb5XCt3c1xDMJhrzB+1StmL7IxANF0ZWwHlhNjyZMzH2DnBsjU4rWP6dUhJJO+Fultn8ETN2+w34\nMOhJNliK+T7EUIUkDtGAlWk9Of+Ah8lnLMCqctMWq9ZAy27bSMOJ6L0B0CwOrT1LOltCABKkhbgu\nE6hz2oTTMUVdR8AT3AaaGcj+xLRR18QE339h9t+FWVHLFrO61n5MkD6HqUGvZ86r3f4IjTHTkDXk\nIEFE0ZKd+B04Dj9CxmAY7vQBn/1rOPwOpMeAo89Ng7WyzO55b8omtse2hy8xJf+NwAswdfwoVtAb\nb0xHt3iqspNANj7VHWbPxTSOz8Us7FG2ZyZTy+HuPpvZsasttExB62unRhWipEiQFuIGlFpl2aqO\nGc+8DxOoW4Nba7PmRUVMyRlMM3YjzP7agLPG0SOJ7CwbADLPO8F5W1ODngT4gmOjRHxcY/Akjqbs\nI4goemSvwvXnTDPlqCdMGjHBTFbyIJCeALibHwBZ3HD9aaXgEf0Fi/8aCv/FVAi8AQF1f2LPrnsY\n1WIqL/E2qZYvMJ6pfH0oBBpexDSkA7RAa59/+CStk1NKIunnzXKjd3tFsaNVW/T2Es6UEFeQIC3E\nDSj1PqbY64PpxJWK1qGWdmsfzPAsyzSfti1M/AbTwaw5pmTdDPDOoGqNczhXSM1NOxMHsrHBhmyy\nsSEj0x4P+3hasR0fYgBoxXaas5sanyWDA6we1IHhfMDxM3WhnwP8BNjefLlIb45wJK0+AEud+tIK\nE4nq/hprqsLrw7GaNVlBb8bO/BBGJgAXoa4nHLt2YZDSSPXEVIictuyIjsQxuRn9XRczgpm0qPYH\nnDuF1rVLMJdC5CVBWoibUGoxJiAfQeuBVx2bjik+t8AE8yPm3dYOHsWUqH2BplC53p842afjQmqe\nNLIxpewsbEjHlOpcSKUBB8nEAW9O8ipT8XvquBmTnQzrXglmKf34LGo43JMATd1hXwwM9kHPu8F3\n2QU6SUEEXNwDdo0wQ8Fer84bTGB23DAuvVHJDEeKNROs0LE+bNiQZz3r0kCZzvLoRaDqA/dimhrm\nZsHHtvA13PXHL0xkCo+OWAGzKXCbvxDFRYK0EDdhgrQ/pk069ZqFKczQLXfMWKwUTG/s45hitTtQ\nD+oFwcOYtupAqOzzJ572Z7EhGxuycCATG7LZcSYIPnCAFzK4y2sv6TiRigtnD9Xh3gamp1pvVtCK\n7bQO/dX03h4G6+4Kpusfm6BJAti6m/Wr386/A5SKAH1Mmdpsb8vO+006/e5aQOSlYOK31rKMq8ZU\nFNgC829ctW4N1HrMAiMvYX4vAVyEe5dsIhsb9iQ0ByDzJVezslgbaPTYbqJfDkC/VTJ5FuJGJEgL\ncRNKfYTpQPYjJvC2QOsWVxz/j2WrKab6ex1av3LF8Zyq8R7Qzw7aAM3BOfAcnk5xOJLGoYSGtHHf\nAsDGH7rDeaje8wQ2ZBMbVddMdJaKebcFakPNbsf4hp78a/9+OAyJvR15gs/5+uUQeDsOBnua4VWz\nQbe66jsdAv2tMn3D4gEvyPgR3nUaRRRBfB0VAgsx7eb1MLOVaTCrZ1lf1XdvvuLrRSHgQe7a10Mj\nPsaHGGzIIh0nMrDnnSdeQ38OqoI5z94vhcxIV+grHcaEdZK5u4W4Ca2fQ2t/chfYICfw5hx/xXIs\nHVOKvnjV9WPQuo9ZonLpKhi5Cu6P4/zXHqThhBPptHLfjj0ZxFMVbOGunr/QlH3Ebq8LNbNMz+yj\nmGroZ2Kg+0Vivepy91P7UDM0qqrGjwMEs4nkqQ6M0nPYOi8Q5pg8OKUkoiZckacGYDPwPNSH6DOA\nF/zh1AhH0kjDic5BK03VehIm8L2HmcmMFJRaW8hP+PapVqAmQWP+oNeAr8AZxkZMJixiHEfwJZSp\nvK7+zRTXCLKxhVRQizGl6D/B2/0kvIcEaFFuSElalGkmOD+CKVWfxszQ5Ygp5ta7Yjs+z9zbpkr8\njitSMiVyPOrDt+Ab9Du+HCXN0vPsPC44k0osXgAc/aOJWZ1qLbA0HfgIrcdYOra5AwNBAfdhfkd8\nDJyHyn/+yTr7rty7ZjesA8fJiaRPdUNPAWWpDNBtFVEzIGgKTB4/lvcujSb+pVrw7mLgLNi+CJ0w\n7bn7FmK6ptczx7AtsSFaqgUwFxr47+XQicZwxBbd/jrnToL7Ir5nR0IQmd+7ml7uH0HXi8tZ27YP\nenMxZlyIWyDV3ULcIhMYwQzLcsUsHm3aqk0p0xWzUEYtTDBOwDSQumDGZ7WGQFd4CjNuGqAf/KfB\nCHyI4ROe4Qi+eBCPI2mk40QSVTi6q4lpa96yHFNiz8p3GUWlFubp4KbUXgAck71J3+oG67B0DIuD\n01XQ+ysytwsM3Qqq5iX4W5m2cx2J+THih6klAPMDxBbTUa4W5oeKT4lN/uGQkMKr7tP4g8YsixpI\nPuuG5BpHOBk48AeNeTynigF4dOUK2AB6ZjFkWIhbJEFaiNtkSsf3Y8ZOu3N5UY6cYJyA6XUVbdnf\nCFOatgN84FG4Y9EBerKKk3gzmHl8RxfO4skZvIinKkcPNYEYuK/z98TjQbRTAKRvIGdpS/Pj4HL7\nd/75jMEUHV1hdA9Tda3joJ4nVIH//eLFGRULQGsvWH66K0PS5nF+sgfMAs5tsHynaKA+UAtcfEwH\nrflYxmvn/WFQXNTnwE9w96zN7HiiLfrzG5yr4G69maqcIxtberISgCokMeippehZxZNnIW6FBGkh\nbpOp+s7p6Z0KLMeUOF0AV3DrY6qfG2LisgemlngDZvKTQVCz8TGGMZvRvIvbkXSwgV/q3sUqegIQ\nRRDrT3SDWFu6Bi0nEwc2nugCD9hC9ELMkpk+4Ax65c3ya5mcpEcPeq38ioYc5CTezGAkHvedhwOY\nOclXQpuW69m6qJNZMMTBkufZ2zAR2RU+aQSRloQPAzsXYkrW0Zjag66Wi1wx1ePumJ7vjkDVQpty\nVH2OqYafDfrE1d/XtJ1fPef5DJ4hG1vGfvohy57uRiTteH/Ay+hFhZIlIQqVBGkhblPeVbPqYUrU\npzHByofcmcmGYcboNoeaLY6RjQ1ViQegHZvw5iQt2Umn37aa3th/AxVh95ONSMWFDOxxwoyv9j9y\nyEw+Uh361Vxg1qLuV4MKsy5wqVMlU30eu82Sw5yS/UXMj4daaB2Mmgn0yuK3Ok2wJwO/FcchFNPL\nOwOYAOvGBDOHoXyX2QUAT/uzHPrBHz4ClmFmU1vH5R7nW4E3V3G5vbqR5XmcwkR6nzzPrtCCtLJ0\n0pthB++DPgxK5Xz/nCr6FLTuY6ZKTT0FdWvT6H+7mc4YkqhCBJOIrh+APpzPDYQoYRKkhSgCSr1h\n2fIE7gYPfxOox4HjXWYaUAcyuJso/NlHMJE0OXDUBOljmLiWhQmaYFbYsrniBtmYQqoXUN8yTnrm\nJpgKxEaDdyPTrnwAOHaKy4OGg4GL8J0d+zvXo0nUUbN7CWYxjjhL2pUwvbvHwPTWz7OBDnhYfljk\nTL5SlXh8iCEbG47gSyTtOBThb9LbY8lvFHAyCnAHl/pmSvB0YHak5WbpeTrY3Q7livmtlIgZ930y\nBnr7mIK8LZC4DXq0NiX/1FPwhZlRbOxjk2nLFubw/+yde3xU5Z3/34eZTJgxEyYXExISGCSAQcgC\nokFBjYpVaKGV2mJLdWmXbW1rL/a6rf7W2tqLl2Xt2lbbta1biy1bi67UW8WKF9AoAiVoQEITmJCQ\nmMswE2YykxnO74/v88yZQABtUYM8n9drmDPnPPOcMzPhfJ7v7fP9JA9tupKsqjoDg2EDQ9IGBm8j\npIa6BJgH1RXSfGMuQoKVQEWKM8fWcylPAFBLPWdTz+g1+8WNfEA9UmrCXIS4UwgBnaKmL5c66YkH\ndxLr83Fe/nPsYgK7TjtD3vcBxN1+YwsQlPaa5wD94L22l32njCZ/bpLIFoj2i+1degp4ZwHXwJ4r\nS1jDQhLkElIKKEk8uEjjI0aAMClcdFPMLiYA4CJNmAAhKmmLlBNvLZCGJMuB5lU4SWggVn/qmPH1\nob9joADoXQvV8/A8H5Hzu9PE7yqA2xHvexg+9PDveehvS/jdaYvxE2UVS6hjHT/nM7xknYVte49y\nJgODdx6GpA0M3mY4/akB5kFZjiRMz0Z0vYMwIniAGaVbmEAT02jgUp7grL9uk6YYBxBiPqCmSGVN\nrntYa+WwEiAPmq6o4GkupIUgD3I5jZ+aIQpjXQihzYYPP7qSDkp4/rVLuGPKZ/jS3F8QeQWa+mUq\nL2Ksl4yCnNmIoNp0iMz2UO86m9eZTBQ/XRRJDbJCFD/dFNFBKQ2xafR1BSgbGwLAQ4I4Pjr/Mha+\niUQH2lsRszdHnbUDvQo5VnmXNQL4sHqRls9e9ptmruY3eEjiJ8o3tv4XX6i5jQU8ymtMIYqfaWzl\nwz94FP4E39xwE7f8q2TJm+Qxg+EGQ9IGBu8QxAU+BsmQPhum5UAtIlRWC56JESoLQ0xgF0GauY7/\n5PRXdsubG3Es6magDTFCc9X+UWRyulgMkeke8juTbC6rxkOSKH5ySdBEFdOQkqxiuvkpn2cGmwFY\ntP7PcCP0PAPdKaHMAXVKLxCchjQNuQBYAA+XvY8mqtjBJDqREqwwAbooYlekSsq9nkcEUfqBecDc\nFGVjQ4QjAeK/LZBFgxup6w4NIKVrexGiBnHPdwCFSlBGf5f1MKtWDoV0sloQvgbzb1vNpTzB7Xyd\n1lVVcKUjZ2qdBtwg27/41NXUU0sxXdyy6MZjJt4ZGLwbMCRtYPAOQyzrmQhDA8VeMbQnI89jwHNJ\nhAmFQtaVhOjDzzQaKKKbAGFmsZHx7e0kRkHufiSxfCNCeKPUiarV9n7Ear0DGA/b54zj9PbdQvz6\neA/y+hmgGwaaIa7i4R39TuOoHiQtrGYisAAYC0yFxFz4ve+jbOBcXmMK3RTTEgkSv6cAHkJc/KqZ\nmGe6LEZcpAGxvGNJcTPv3zha4uinAH9FSP451cfbqgH7MWTZEEN82I1IstpMIB/mq3rta4EbwN50\nyHd/GvAQ/KLmalyk6aSEb63+T+zFb+03NDB4p2BI2sDgXYTogucD1VA2U1zgI4E+JCG6DjG+T1V/\n98ICwnkAACAASURBVGHLKX2qgupFm7mUJ1jAI1zS9DyJcshdjSRuqVg1PUgGdpvang68T6bYWjsJ\nF2lyVYZaLwHi+IjhI0izkPktiLW+BQZ2QtN+mWbOWOATEPmuh/z7kpCA5s+UsZZ51FNLmAAAGzlT\nWmumXLDFLXFpnRQftPEEohQVduPDaUGVIJfuSJFY4y8C3wOp9Y7g+PtLgJlQneN0DJ0LbAN+N3Qz\nEOs0+I+/fZ7nOI+H2i4HwC7PffM/mIHBOwxD0gYGwwSWtQ4ybSxjQDW4a8Qd7kJirmE1RLWwZjTw\nUIplY+9hCauopZ6CN+JCyCnkWSeaoZ7LEUt1v1jAKdcIWnLHE6KSJB5i+PjYhgf59Lk/Zrzqa/1v\noTvEyn4UNv1O3OC6wGv+dEish8/7fsI9k64V7rwGmj5RwT0sZyvTSONmC9Mpp40OSmnfOl4+SxOy\nKKlAFiZVMueo4D4CnjBu0tIFbOtYIes+IKA+dxRRbYtuAnZCwRLobQQ6sO26w7/fVbBsyd0AlNLB\nLdaNw76rl4GBIWkDg2EMy7r1sIxnp+tWIVjL4WLgLNlT9oNmaqmnjqepoYEmqvjXv94nB0tgX9ko\n1nEht/M1Nj44Fx6Elvsg+DHgq/DimdOZ3b4FDkBTlZQqhajkWc5nEQ8z45eNUv68HXlOwNpumFcE\nAymxst2ADxizDLgKVlz0Ob669acSd75CLqWobi9lI9qoJISPOFuYLupq9yJZ7ZXAh2DC+a+qdp7S\n0nNbWw15gSh9DcXi7Q6qr2LzGmCh6nOy5rA6bOuLolu+IP9Rqmjilj3Xw7hXkNrxin/0ZzIweNtg\nSNrA4ASGCKrMBOZAVaEQ12wY9/HtzOMpgjQTx0c5bQRpoYUg1068Bw7AL9tExvNTxfeztlv4rQrw\njpS5UykonAosQizveiRR7VC4gQOwdzWqklqM3DFAsAi4XOZ4ZOHFXBn7PX0XFEsY+TqY++0nKaWT\nC3maEJU8waVseXa2xLG3A0EYdcc+AAKeMLkkM+Ius9hIF0U0UEPrz6rgT8BjSlWNQiQoHwMq4OdQ\n9+nHWffnyzILBSYDG3WiWkTtHEC+iSa0u+LvKQszMDheMCRtYPAegGSOFwK60UU1zFNlXx8BrgFu\nhlu//UVqqed6bub5r1zCuBXbeZzLOP2c3Wx9UchV65OhngvVAyCoCNyryDqnCLF6JyLiJ9XAfwDr\nlYU9Vh2bClwFz555NhfU18s13QDMhjNrRCFsAY9yHs/yOpPZwWQamEbDwWl0/2iMuLlnw4haqUPz\n+eP4fVEW8CiVhLiPq8QSvwO4S7cKzYHxcu66hx8nQJiHHr1S2nfuQPL27kEulnHq0+5GVNI6OVSP\n/d3q9mVwcsOQtIHBexRC3DXgXQjxASAHzkMs3y7gO/DDxdfxb813wM+R+HWbvHdgI7y0f3AJloY7\nazsFzNGlWY8Cn4e9NxXh93aztx+qpwOnqcG5SDx8PPBReOTUi7mBm9lSPxu88C81P+U6/pMwAWbF\nXqHJN4F6armPq2gmSBo34ViAdMqRXouH/dDvZtyk7cziFWaxkWaCrGERsaSXRZ41nMlG7uNqXtlT\nC/1uUSY7gGSON+F0InsR6I2jldDkk8bVp9yEbS//x34QA4O/A4akDQze47CsVdj2kqzXq9XWYmAn\nzJqI96lepuU3EKSZybzOdDaz+LePwU/JWNjZiCMEHsGxurUUSQ7i6ka9ri5HumVNRIzWZsR9fgG8\n/E9TeYlafsPVdFDCCr5CLS8xpl45zkfK2D1Voni2lnm0UU4LQaIRP/E+H/TlQl6CUcW9XOH5Iwt4\nhBCVzOMp1nIx67iQelXuFo4EiG8sgDcQL3cT4lbfDrT34FjR3YgVHUWkSw9vCWpg8E7AkLSBwUkM\nKQFbBm4vpFoQMZH58IyXUbP3scc1jvzZSQAaNzqRWxD7UpP0QNb+fISo3VnPFcCYOcDFsO+mUYxe\nv18GP4jw4SRgOTSdWsHEPc08P3Y2c37/ivCltsBnw4unTucVzqSeWh6IXCEk3e/BE5BlxKTCHQQI\n80nupYomvMTopJRf80n+uGcJtLthJWJFbwanrGsv0r3Mh8Sx9bIkjpC0iUsbvDswJG1gcJJBks1A\ntEl1HFa/ngOWyna+GLgFfjJzOVel7yP/xST8FrGEdUlYBxCSzO7V+2W2UudUg8gate0FKtxQ+Guk\nrMuNxLLHA2MhMRGivjyKQ33S9KMBR/60RI2bBneXLWMz0zN64VH8eEgSJsBkdrCEVVQSooNSNnAu\n9/VcRfLafPgdiAyp9Pm2bd1u9NDvB2NBG7zrMCRtYHCS4XCSTgFnI1RaLSneCUQYpA64LMWHx67i\nXDZQSz1znn1F85sQJgjRPgORW6Gxf7B7/FCS1shBCL1kFOScgqOUVo6QcRGihrYTsabHI+7vEiRJ\nbTZsPrWaJqoIUckuJtBBKaV0cDb1+LOuYhdV/IariONj1/lnwHNr1MQyxpCxwXCFIWkDA4MhYVkr\ns15VwTm1cAP8ZMFyXKQ5k43M6tlGqLCEDkroppjJ7GD8tna4Fga2QOd+qbZSaWuAY01rK9sH+EdC\njkuVf52CkPIpZGLSg14XIvHtcjVhiTT9aHEF6aCEMAWkceEjRohKJrCLEJXsYBIN1LC242IOXncK\n/G4d8BJOVN2QtcHwgyFpAwODNw1RRRsDsybCVfDLLy7lNap5gkvxKbK7mt9Qxzqi+Cmmi7JEG7mJ\ng7ivh567pXmH7rSZA+S7we2Wsq4cTcQu9Yza1g1EtFqabtE5Vu0bBXYltBUWESWPMAV0UkIKF2EK\naCHIa0zhNaYA0Hj/DFgKUoOlu24NhiFsg+EAQ9IGBgZvGZa1CbGR58Gr+ZRNaaZ903hJjl4LzIaK\njzfRen+VdMC6LMGt5V/n61+7E56Blo3OXIWH1F4D5GhSzsWxoovUdimSnabImVGIdT0SR2ylFHpP\n9bKF6XSpmLUm6Vc2zYGvAU+vVJ/hcILWMERt8G7jePOe+9hDDAwMTnTY9kwsqwOq8xlVtY/2EeMl\nfu1CNLlboXVpDFRbTPw1fKP0v/jGF/6Le19ewj9/9n+lLjmBZHCXyHNc9bLOOYCIpIxESB7k7jIS\niVOn1LYmZrfa1++MSZzqIYUrY0XvYDINPdOkQcnTPTi9vfSbD/2MhqAN3nswJG1gcNKgCRrvZH/u\nNVLWdCPQtAZoxX75s1iWGvb/aqj4bhM+YpTTxhoWkXtXknLaOH/7S1JDHQL2g7dTvadN2mXmlCBi\nKJqYDyBWtRvnbpNQjwOIhV0IkbEeQlTSSSltlFOEdNkKFIbpPD1fJFSbquQzDCogMzB4b8OQtIHB\nSYDBGeJReLFQmnw0OfKZtl2jxq6n9XvTYFY+r18i+/74iaV4RkeYdPoOJn9fhEAv5QkmsYPR2/dL\n/fQtEG8D7wGcWHQKsZzzEas9l4xmaeIC2OGbRM1fXyftclFMN2E6mMJrrKOOMAHCPQHxcB8AsaQN\nQRucXDAxaQODkwRC1KotR/ViaJTmFod2oBr8njtlPHVwjhc+ACxLcHZ5PVH8uEhRQwMX8xSfeuV+\nuJaMVCm5iFu8FCHmUUjiWAlQCYkZ8LSvjiK6cJMmRCUdlGbi0fXU0vmXsVLrDfDrHiRxTIufDoZx\ndxsMB5iYtIGBwT+AONAAjRFgGQCW9RgAtj3/sNGHC4fcC9dX8BIAU+HCHLbdcRb3Fy9lzZkLOfeF\nDSznHgrOiovL+4B6FCKWtbami6DDV0IaF1uYAcAuJvA0FzKNBs6mnhg+NszyE28pgAdA1Mb+MUta\nexQMoRucKDCWtIHBSQzLWoW0zkxh29WHHFuBkLoXaQTdgiN7Uogofnth4Xy4BuoWPE4UP+eygRWR\nb+C+FCHqrPpoxiIiJ9XARGguK6OBadRTy0ZmEaISHzE8JHktWc3+50cLQd8FcCtHsqI1hiLfbEWy\no40zMDgeMJa0gYHBcUN2Iw/Q7u2j4XRE2duN1F9XwDXgmR1hQ8+51BWuo5IQD+R/iCtXPwTfBLYg\nBO1GXN65ZHjWRRoPSVykcZHCR4wuiuiMZImVBgALsLNbUQ5N1NmW8lDkbGBwosGQtIGBQRYiiIVc\ni2RStwBz1LHFwGpsew6WdSswDTYCayvw1CW51PcEAcL4iBGkhb1lRYz5SLeoeY5C3N39OGTdBkWF\nXZTmSrKYizQNTMNFmr48P90vj5HGGrcB9l043bOPDWM9G7xXYEjawMAgCzmIpbwXWIiQ9jM4nafm\nYFmrse1vYFlrZWwYgr5mAoSZxlYChPETJUyAMeO7aXqhgqrPtorr242UbyWAcvAdOIg3N0aAMMV0\nUUoHHZSQ6M+VEPS9QGorjiip7hn99uJIVrgheoN3GiPe7QswMDAYPpAWj63AGOkE6c4H5iFxaTfi\nbs7HslqRnpWr4NdxttWcxQPJD/OKiivvYBIBwmyeWk1VeytcDkxDEscgU4plJSCXZOb8U3iNybxO\npS8EV6Tgy0BBDU4sWjcYeSuf6cY3Ta6WddNR3eTGhW7wTsNY0gYGBoNg28tE8zvaAd46mOiFvsUQ\nigOPISVZIK02IsBW6Kpl/75imscG8RNlArvYxQSK6CYxClyzwd2JqJJtBPrUFAdgvLud2Kk+AHYw\nCYAAYUbkJjjY54beQ69waMWxoT/L0OT895KtsaQN3mm8KUs6nU4zY8YMFi6Uesq//vWvnHPOOdTU\n1LBo0SKi0egxZjAwMDiRYNt1QJ0YsH2Ii5oOJBP8JUSdJAIMYNu10L4extXz/MRLeJhFrOVidjCZ\nboro8hXh3oKj3V2uHppn+6GILgCK6aacNsppo7I0xLhvb4cngAs/C1ygzguDJcyOjKEs47+HoN+K\nNW5gcDzxpkj6xz/+MVOmTMFSuoHLly/n1ltvZevWrVx++eXcdtttb+tFGhgYvPOwbSQe3I64vv1B\ndWQewrAXAGBZt2Lbc6BsDpwFrW2VvM5k1lFHF0XkkhD3drN66G5ZbkT4ZA+MbtpPKR0U0c1kdjCF\n15jBForpZsQ/HZCS7mm1iBWvG2fqOPWbh3FXG5xoOGaddGtrK8uWLeP6669nxYoVrFmzhkAgQDgc\nBiAUCnHZZZfx6quvHj65qZM2MDghYVn3IkRcCrhh2nxo6EGyvUvQsWkxtdcjyWYdwEfhkRzGLdjO\nLF4BYDqbqaGBIrqZntjMKesPCln3I5b1NEhMhDZfGU1MIMRY2iijk1KamEADNbQ+WyWNNkC6dj3X\nAzwJ7FY7ddb30G5wbQUfT5I2lrXBUHjH66Svu+46brvtNiKRSGbfGWecwf/93//xwQ9+kD/84Q+E\nQqHjdkEGBgbDAT2I4sh8KAAaQGqpGhBCnIiTZV2L06Hqf+D9Y9hdPZ/dt5/OhAWv0kEJjUzhTF6h\nLbec3IsS1KXXkX93Uu5A/ZDI9RDFTxo35bSRSwI3adK4yCVJ6fkd7Jg1mb4Xi4XcA4WwZQmEIsD/\nqmvq4Vjx6qPXT7/5WDcMJnxD2AZvF45K0n/6058oKSlhxowZrFu3LrP/V7/6FV/84hf53ve+x6JF\ni/B4PG/3dRoYGLwDcIjHj1jGSOJWNbCvFnp7MvKholbmAxqRWPUYpNVlBPs1sCbCrvAZtH2gnGR+\nLi7SbGE6zQTZ6JpF7efreX/zUxCC/OYkk8tfx+NLsIsqoviJ4cOliNpFGr8vSl9FMcwGRqNE0PKB\n5ZKQHgK6WpF6al0y1giksKybMkQ6mKj9iNt8QD1nQ++LZO07soiKIWqDtwNHJekNGzbw8MMP8+ij\nj9Lf308kEuHqq6/mN7/5DU888QQAr7/+Oo888sgR5/jOd76T2a6rq6Ouru64XLiBgcHbjRRSqLzM\n6fvMNCVkEldktwZh8JeAyxDhk4qMHjhLIT5+Pi9dez4vfeg8Lj7tUV7qqaWqcBchKmkbX8688Wsp\nSncTc3lpp5wOSumiiDABuinCT5QofgKESU/aQ2deKVTkCklrTt4PvAF0SN02ANuA3hU4UqaCwZa0\nPuZXjyIgpp4HEG/BGDUmzuBSsIGs/SmjC36SYt26dYOM2OONN63d/cwzz3D77bezZs0a3njjDU49\n9VQOHjzIsmXLuOiii1i2bNnhk5uYtIHBCQfL+j5CvKpj1viJogbaCjREgLvRrm4haj2+FCE6rxy3\narAPIn2qP4lYwLOgZOYewj0BygrbOJ/nALiYtZTTho84bZSziwl0UEoUP52U8BpTiOIn3BMg2ZUP\nXQgZp9RzGMlC16VdAPsQ63ptK7AGh5CzxVDcSGy9BImrZyOeNTbG4BrtATXf4cIqhqRPbryr2t06\nu/v+++/nZz/7GQAf/vCHhyRoAwODExO2fT2AspK3Q/NE0c8OAP58iJYAnTgWpmq0wSaE7OaIr9ve\niWV1KhnRVfDrxVCVQ+f0sXA57J7r4z6qqB7bgJ8olYRwkSaKnyQSo+6miF4CeEjiJUZnuBLcNoy0\nxLLvQ+5iI3H4sw/h0OnALCBYAfd8Fsk460bItQNxZavm1oPc2trtrRYbgwhak3IE0y7T4J2A6YJl\nYGBwVFhWHKq9EgfejpRksQ5HS7tRjazF0f4GyQT3AeOARmx7CZa1ErgAqivEM34eMNem5LQQ57KB\nEhUHd5Mmho8ofrGgCWSeu3uKSG7Ld6zoPsQd34djXQPkAVOztp8HXkQafrTvRPzla9X1j8Fxceus\n9RS6FlygCToF7B0yCc2QtMHx5j1D0gYGBseEZdVDQa24vccA9ajM6k1IVnUEyfjWOtvaCq1GSLpT\nvW5B4tnLhfwBLvTCZ4AZMGLUAS4tfYICwrhIEyZAF8V0UyQkHQkQD/uhz+10zkyoi9QE3Y9D1G5E\nitSLeOP3I4TdpS7lXqC3A0kya1HXC45VrV3aA+rRidOJ63AYkjYwJG1gYPCuQGqn54O7VELPH0Cs\n1wdbELdxD7AG2/5C1vhqhORUvTV7ke5aVTgWuBeohf+rxjM3gmdkkiJfF+NpwUOSJFI9EiZAG+V0\ndRRx8IAPwpYQ8z4cYs4maA0d1MsDig/Z34XE2rep5y1AdJ3IocYjOCsB7d6O4Sw4TDza4HAYkjYw\nMHhX4fScvhyWVwhh/+cAzMiBzY3YdvUh4+9CXOED4K6FVAtige9FmNKLbS9TY3dC9USJJ78I/ASm\nLngZP30k8dBBKZ09JST3qeSxfqRELM3gpLGh4EZIOk+91hnrbwC7EKJ+Azn3E+q1rYm4A+0FEMLu\nwUlEE9e4IWgDMCRtYGDwLsOJwxZC2RfgQcTD/STwby3AGGw755D33KO2ShEr2o9YpuuBCLb92SHO\ng2SFzwLPlREqC0MU0U0ML+0Hy+nePsYpv9LJYmmEfMGxoPVzABgN3qpePCMT+DxCwGnVmqtz01j5\nDM8gsfd9KGM5oh7aoi5ERF32Aj2GnA0GwZC0gYHBuw4haq96NQ78S6iINNG6JwjT3TAV7GeP9N7H\nkMB2PkLajQhx7x3CCl+pNpbCb4EAnLlgPV5iNCSnsb9ltFjSB3Bc3SkcwnbhJGvnAUHwFEcIFrYw\nnc0kEZGVctq48y9flzyyPsTtvQVlLOtyKzdiTYMQdBxx3YtSmbT5NDjZYUjawMBg2EBUx4CqJZTt\nbOZCnub+VZ+CK1uAIEf67y/lXSBJZfkI4fcAW1UW+Gqc5K0UomgGlM2Ea6D63zczhdeop1YWBgBh\nt/BmAoewtdJnBYwoPUBxaTfn8RyVhGijjFxV2lVAmPWcy/PPXgIvINb5izgWtQ2DVck0cTcirns5\npuPxBicvDEkbGBgMO1jWVrz7KzkvX8RJ/vyXRXDxVmy75pBx2lXuRkqgqhBruhRh2PUIcRciJFiP\nbk9p24vVHHcCF8DCGlgGZYubmUATrzNZksq6T3EIOi9FUUUHqZSLWs9LFNNFglwAXKTw04ePGAEl\nUxbFzxoWsusXZ4jrW4eidXlXhqxR1xdT2ymk13Yp4hEwZH2ywpC0gYHBsIb1EWAd2G8McWwQSQOU\nwsLlsrmmHiG7OSJCsvExxLouzOiFO/PcCcwDbzXcDBVfaaKKJvxESakYcznthAngU0SaxkUKF2nc\nGT3wXBJU8xpp3MTxkiCXHUzisT2L4Edup/PWPiTJzI3UiXsR4rZ7kLRw3WBEl3OZRLKTFYakDQwM\nTmgMSjyjGlEpy0e6WbllX+V8qAPuewypq16MZa1HSHAM8Liaw4v0ta6BeV64RWRHg7RQRRMeknRQ\nomg5jZ8oaVyZ5h3ltGWsaFE7yyNMAQ1M46UN50vI+Z9bkEQxnTQ2H8qQTPCUbuSxF1Ez0/VfTYak\nT1IYkjYwMHjPQGLa+TgZ02I5c46yrl+IYNv5amwLTtnWGCQNW1vk1WDVSPnUBOBj4KmLUFTYnSFh\nHzESePDTRy4J6lhHLomMqpmPGF0UE8fLa0zBRZpX/nYu3GzBrxvRmegSlz4bptWKEd0LsrFbHW9E\nl2cZoj75YEjawMDgPQWpow4C0xACzIcCr4il3AewWlnSdyIx7Fqkt3ULIuXZgpRxfQXL0gIphUAH\n+Guk9AqkRlrLh9bCqJX7uNzzEB4SdFPMHzctZdzM7YxXGdweksTwEsfHK5vmwO3A71aoyfKhbLmS\nSAWnHVcL0hFsMAxZnzx4VxtsGBgYGBxv6BppqaWeBlTDSK+IlbAanajlKJnpmmsvQo5ebHu5GpNd\nwlWqxt8p84ZmAo/BwiWQgP1dBUwv30w75ZTTzh+vhd0vuNi98DJGPbAPtzuNZ0SSIrpgdAK25CKL\niR55bueQc2lltSrET+5gqH7TRvfb4M3AWNIGBgbDBpm6aJYKX6eAxkaEiINZ476PECY4dVZViJBK\nBZbVkTVpKdiqnMvKh4vhfU8+TAtBwgQIEOb179bAQ0gt9TaUnncEnppIyUV7AOjcUw5/csOfEIO5\nsQesQnlPVDca0Rnpg3tYg0PCh5LzkcYZnJgwlrSBgcGwgiMTWohYkq3Y9jIsiyPWScv77kXi0dkt\nIheDpTpupZAs70ZRJ7NOBbrBPqjH7kWI+Wz1ugXowSo8pC+03Uq1/QbzWEsb5RTRxf2xpfSd4oFX\n8unMGwtXInfD63UiWBBYCRdDJ/OhslpIHCTuDTC6UHUF06Vj2rIfo+Y4nKiPRdDZYwxZG4CxpA0M\nDP4BCKH41at5SCesVXDFMnhA9h6dqFcj5FaINK6YR0bJzI1kUascMu5EEqjtNWp8RM0/X8RRrIWw\nDOFtgCttRlV0sP/B0QCMunwf53o24CdKmAL+bC0S2dEG4F+Rcqvf6dhyE0K4E2HGPJm3GCepXBO1\nHv5LwN6JsHaHenjJTiA7MkF71UO3x3QadxiiPvFgEscMDAyGLSyrEdzVwtWNABEoyIfeemy79pCx\nWxG1LoCZUFaj4rwtZDK+y4ArEJJ8HLgBsHWWNWDNh2uAuTgNNuYi3KilQosQBbHRMLXmZbbdcpYY\nuj8B7Hq4rlaIPQicbkPKAmDSpK28/myNtLP8EHA3MBsh9Qd64PuFktndrfZtHFCfx4tt16iEOHCs\nfg1pKiL7/TjyqnF0a0wjMXriwpC0gYHBsIdlrQHvQuk/vQ9or0eysrciNc3A2q3AbqheKGpe7ZsQ\nkosAH0U6dwyA9ysy6W9hwuJXCfVUktyXT9mUZpawilUs4SZu5OrYfWz2TecT/JauZBH7m0Y7ymNu\n4PcI0WYSvtYh7LoUduczanQXuZ4knb8YK/2t0WIqS2EhMteLCDF/Um3PUVNpnfAngNBqnBaX2suQ\n7fpWteDkcHjEMQXsxLa/8ta+cINhA0PSBgYKkjykoUUkvMYKGSaQmPNiqM4X4Y+uesRq3A3TFioe\nW4fj3p2Pk809HyHQQmTgPJiXw8In/8ASVrEwvYZHXQtYyzwAouTRSSkhKtm1Z7JM1+IW77MbsZS/\nCmxsBZ7BtpdiWWrh8CpMmPIqu759BvxwE7Y9M+sz3ERGN5yFTo4awAxgcwt4g7AUsdy3AI06+a1H\nPbwc3nv6dMRbkINjSYOWRjVu7hMXhqQNDBQcki5Ebm4p9A3PaCcPD1jWTrU1ESqBXFR10np0opeQ\nchwhrQuQ3xP1Oh9YDf7FHGyxsLYh1jDw7/d/m+9t/T7cAVwB3rm9xLcUiIEcRuqjtwAPxhGruAmH\nLMcA0+DVWs6Z8jQAL1xyIax9TMW478FxUfsHWbbW+erSLwXuWYcQ7Ry4HMdg3gGEBpBAuv4smrBB\nfOt6O5vEI8jixG+s6RMUhqQNDLIgilVFOIk3PciNTvyctr3s3bs4AyUushXOWSI/z8ZNSKerZVlj\nbkKIuQdprpGt070eqBI1sTqwv2dBM7z6iQlMvaVJqp0eXIkkai2GhUH56d9ASHovKMExJeOplcOA\nLyyH2XDxxx/hqd+8H/vq7Ou+FyHWONIwY7B3xrIUqf4/r8TCQ4jLW+d9hVEx6vVAQ1aN92p1UWPU\nTKU4f68aMaDTLDRPUBiSNjDIgiQfgZMh24NkCbcid8ucjNCFwTuPTCLZ88BTwPVr1ZGtZPdgFqIu\nQSzMFOJLbsIps0rBz+dgX2TBTrBrYcRyGx7sgPNK4bksJTCv+r3nINZ7P/AyYv2eB0yAvB93kTsy\nQfeWMfAZsF8+9Lp11jlA41GtWut8xGLPQ5pwFCHJZC1qgL1W7ejBCWJvUvMH1WfUnbW0glrckPQJ\nCkPSBgaHwLJ61JYbcT0OIFaQsuJIAS3Y9vXvzgWepLCstXCOxIy5F7yje4l/oACeW4v8Nj1ZAh/f\nR8i4ArGmtyPEtkTN1go0wbfq+MkPljOJHVSxix/xTX6x6UuSfX2FnIfeeoToFsEXvDALRl25j/03\nj4Y6mH7RiwCU0cZj5y+G524FGMJaXoNYtUVIMtdnj/A5b1LXDDATzqlxLjkEImG6FyFpXYMNklQW\nR7wA2pLWiWR7zd/rCQpD0gYGQyDjfswgjrgRWxCLrAMh8MNvxgZvHywLvPt7OS//ObYwnc6JjZr7\n9QAAIABJREFUY6FpFba95JBx38dxAU9ESO9+tW8hlOWL+/oKqP7uZs5lAwt4hBCVrONCnk7WST30\ndUC7stateWLd1gFrWuDFIHNrn+T5v1zC1IteZlvhWdg9YFm3qvP6kYWDQ47SeUt7a4KDWmY6JVad\nCLnWQcEc4fRdKJUznSfhRv4GQRaQDcjf5mLEJa41x/VCM4Jp0nFiwpC0gcERYFlD7R1Abo6dOHKN\nA8ZKeQdhPSrP71vwMDuYxG6reYj+0CsQ8goibu/dCDnmINnVJUANvArfmfJvAExmR6ZX9Ac3PQE/\nBBKIetiPgAZJ1Cqz9/E1bmcD5/IaU2hcMUMyvbkHR+0MdLjk0L8Ny8p20Reia5mF1HOca/bXOG+K\n9iDku1ONuQDp1JUjQigfQMReGiNIQ46dZCc+CrJrqw1ZnygwJG1gcBRkiNoCMn96OqGsCbFY4sjN\nMGIyaN8BWIuA2+Fzk1bwsy9+Be7cim3XDB5jrULITluUOl77DPL75aj98+A/ZvLDr1xHJSFK6MBN\nmousB5HyrfjgTGxrFdplPiqxj/GeFrZYb6ij2rKNqHPpRh6DrXyZ5zG1pRtn9CBW7xygBicnApww\nSydOQtxMpDa6UJ2nKWu+AZwMd+32jqv3OTAkfWLAkLSBwTFg5RyyIztxlh4c2cZNyM2/x9wA30ZY\nH4f33f8ws9gIwA+sT2PbFYePy2Tqb0Is5yiiy70WJ9P6n/F0e7mp8EaCtFBJiLk5Mi+poTWvLWsV\nuJfAK0CeDVdYsFnHiZsQiziozqerBLKTuaI4rvgBxMp3q2v6KIMVw9bjELDuyNWqxkxE/u40Mecg\ncXhtnXerOeIIwR8O83c6/HG8eW/EcZvJwGCYwNb3Vq266CdL2EnvyEFuvOIStawVWNb3say7smKU\nBscFAfjz5xaxg8n84OHvAqmseK4DsWAbEeKK4yQALs4alUOyKIWfKAHClNIB3wJSEY7UL8i2l8jf\nxDVAiwWbG5GVm+6claMkSxtxFMJQ5wb5OylUz0EcRZOzcQharwy92PYXVGa2zuBehpRaNSJWexVC\n2DNxys261bOWBh3qcxiCPhlhLGmD9ySssYhwhr7nunDqWEF6Fb+hX+sEs704co765is3ZFMO84/B\n+hlwJjB7J7D2iJnSkB0D1gpltTiJgGNgfi1/fvQ8KgmRxk09tfyLtRJYcczwhfVxhGfnAu8HsdI7\nkBaXder8dyIx5B7wyz6ijyGkPQdYiW0vVWNbcLK1dVb59qys9bWIBmorkggH8jdViHgN3AiZa/3S\nQW6fDAxBnzgw7m4DgzcJSxtgFYgRpEm6HxGbeAORcuxTr7sQnWkbYA1yY9U3TT+Oy1WShg7PUF6B\nk0FuSD1TGvexQiHFZrBvezPvuxVxd+vcgWrE/auTsACu4V/sX/DfPdfSUTiKDZzLh9sehIpc1cry\nWOcAvoazFvveOvVCu9YBJTkq++YhceZqRFb0C1lzRaRPtf0YstDbq7perUXXPMv7NmHb31CZ7NWI\ndT107+lsGII+sWBI2sDgLcD6FdJisAIpx+lXB1IIOXchBN3CYLJuRzyQIbI6DtYjLssUjst8L45l\n1IMRT3FgLUZEPmaDff+xRme9L9PSsQr5bvUqK6K2Vdz45/l8+dM/4jPczetM5oP3PwFLj94a8/Bz\nKYINAs31yGJAksBse07W9RQiup8647oUWIm44vfiCLE0qjm6s+aaiaisOd4Dy7oJ3DfKwtG+k0OT\nxMCQ84kKQ9IGBm8RQbYDUEonpXTQRjkxfETxE44FiEW9HEy7IeWCdrfcOMM45L0PIe4WHBWpjMXd\ngZNk9Iw6WALkY9vZsdSTD9YtwM/B/ttbfJ91K0JuSmmMQpz64ZnSkSoXPvqH/2GDUvD6PVcSJsCV\nsd/T9/ti7E+9lXPNhIJ5cDHwqjrQuBbbnpc1TvfNrsZJCFujrvMCKJ4ofyOsQSz+IE6yGUiZVQ+O\ngIn20GgFsvVDXp8h6hMPhqQNDP4OfJK7KaILP30k8RDDl3kGiOInlwQpXMTxkSCXGF768NNGOeGe\nAMl9+ULO+tGOZAyPRFznSpdakI9TlqOtb53YFDWCKkeBEKJO1tKQBC/wQkFQ4tuXQ93nHsdDkk/y\nawKEmf/s09DEMUlazqF93aqZtHum9K8OAdx1iOW7AvkNxyEWcgngQ5LHAG+p/B306vIqnb2tqwn0\nQi4f8QgU4vSU1mVnh8ejDUmfeDAkbWDwd2IFnyeXBF7iuEiRxo0/Kx6YTd6arMMEiKnnDtUKsS1Z\nxv59xdDlVtYTQtqt6llX4rwBdOlSryaySVosqsIha3INskm0BHEtVwNBIdEzgPNg6r+/zAy2cCYb\nKaWT6WzmI/wBgG2rzoJVYK8+1vyXAzngDsI5wEYgXq+yvbPH6gxE6WYlseV75JpmzRMRFYCG9Yh7\neyeiKhbhcBUz7c7Xi7hDG2w4MCR94sGQtIHB34nVLADATxQfcVykM8fSuHCRJkwg8zqBhyh+ZVnL\ndh9+uigmTIAwARJ4CFFJZ6SU+L4C4WJtaTcjRpQm73Zwssh3IjfovUZQ5SiQJKtCYAkUKMs6CkwD\nvgxMhqtq/5sz2YiPOAt4lDG/7MY6z4ZtwM3IV957KyJ0cmPW3CvBL1nalCJhjouBewa7umXsnVmv\ntEpZDrAcrEKwe+Bb6vp+BNibEMu5AU3qg+e7iTcDQ9InHgxJGxj8A9jKZECI2kMSgCh5JMklgYcX\nngyz8v4IcdvCZbm59OOnMeGS0wEyxOwnSgoXffhJ4ZLYNgHaKKeF8QB09pSQ3JYvBNEKPI3oOYeQ\ndonF1dC1EnGHxhErO2puykeACJ1UI/XFbqjMEZKeBYyGb0/6d7ooYjn3sIsqdjCZBTzCDUjP8T9P\nXARNdwG12PZMNadujFEHVUG4BLhrfSZhbPD512a92omT6FWKZH7nQ3UhjAae3op4Typ4sx2tjkTa\n5u/hxIMhaQODfxBd+HGRxpVOk3a5iOEjjpdHn4RbfvoGbTMSmbGjN3tZ/vnTOeOScRlrO4qfGF6i\n+EnjJkyAXBKZ+HY3RexgMi0Hg3RvH+P0UmhCYtib40jsOopYZVrhKopYjdIsxMStB0OkOWci39lE\n6WYJUkoVhkmf25oJX3yc+3GR4luRH/HD/H8jRCX/Yd2AuDbiyPd8D/KdjwOqoaxWSHbz4cplmQQz\nCoF1am8+UAXuOnHDlyK/czdg6ziz7m/+0jEJdyiiNiR94sGQtIHBccCBhAuAaK6fEJW4SfP5T+7h\nheCBw8aeubuAH/7qDLopJo0LLzGS5NJBCWEKCBMgqmKWaVz4iOEnShfFtCihiyYmsPvZ06UD4z6E\nsFsQl2xvC0IeOslIN3AAx8qWFpzvtcYglnXTmyIiJ5lMy3FOA4JQrRpWhJHyupuBy+QQVfC+1Q9z\nOQ/yKAtooorGvyhmXw40r8ZpvgJwo9ITuRXt2YDTEXf1ZzMkKjXQ2V276qAyKG8ZCTTqpi570QI5\nQ4U0DiXlwYuCoSVODYY/DEkbGBwnrOQKdjCZXUygg1I2L/s6PeMbDxs3rXkUd91blbGgAeL4MmSt\nSVo/J/CQxk0aWQi4SOMjhos0LQTZzHR2bz0d/gT0Ivfx37UgrJ2dDT6gnjVhD+DoPMuxE/UmPpig\n3EddfAweOxOJHwAshhmloia3C/it2h0GbkQs2suAU4BPwqfP/THdFPPHHyxF/TSiU7J2E2Id1+B8\n5xGcBhylWQpj0mbTsnRG2kJ5mpUjMe1+dT5dwtd1eFvOoT+XIeT3CgxJGxgcR5SyB4DOv1XCVy6D\nGX8+bMyE3eP53K/mi0404CFJGhceEplYtiZrkHKuDkoASOMmjhcXaTwkcaks3j78dFDKxuSZ7H9+\ntGSCJxCuaEFc5F0ghK3j1hF0tvDgWlsvDpEP/5u9WKHZ2czaU6A7kx3aKvImJMtbN+XwI3XH8h1T\ntkzc1AF1eB9ClEFETOUc4Aw455tP4ydKmADdFLHrtTPEo/HBncD/AvPgiloh17U9OLHnTUhTapAF\ngk89LwO31+nPAUL+BxCyHokI6Ty3HlivMsIdVbpsAZPh/psZvHkYkjYwOI6wHlYb+4C/PAKhL8H7\ndjkDXjqN0V/+KjMuGY2POLkkyCOKnyhu0gQIAwwi4FySeEjSSQkdlNJNUcaqTuEirUqxsq3rEJWE\neiqdZLMuhAe0RbYdUUQLdeAoquiYdguDpSVl/uHoGpeyJY1C9dBdo/RCRPdV9uO4/guz9uWocUXA\nZeDOkZhwHvKdVQCNPTj1xyrOv3ImVMD081/EQ1KI+pIzYO0aIAYsETf4AeBxxI3eouZ7Lg4FXujV\nxB1FEsY2IXXW+ZLE5kUWBgFgKvBYC6JUtzuTYzA4Ca0evWAxRP3egCFpA4PjDOsi4Dkk69qzDor/\nB3IsGMiHri9C7vvhCuRmXYzcvIthRNEBqkp3MY0GAoQJ0kwuSXzEACHuXUygjfIhXeAgtdkJcgEh\n7TABmgnSHSsWJbSWU4Qo9iMLiQZEFasR5EAjTmxUS1Lq3sRag1r3SX73S72klMmLxJRBsq3G4FiX\n63DczOAsRAqR7O4x8h5vzuCmV24kfLwdWdTYW3FCBXFRFFsmx0b88ADjS1uI4qfztbFwRgecUwof\nUHM1I9yZi5BtJWIhJ3Dq4vuRTP1dOH3Lq1GtolfBeUtgMlIv33gP0HFIrfQKnEyzHE708IWBA0PS\nBgbvEBzNZi+wXAg6gHQXPB0x5CZCYdMqzvzlbYxK9GHnHmTkF89l5vtPoZSOjOUcJkCISropUlnh\nLlK4SCqCBvCQII4vI54SxU9HRwkHE7nQ7xaSbkEsal13fQCx3LarSexWhMlBLL4enL7IKYQctf60\nqGK9E1rjjtSnHymjmgbkg4W4hUci32cO4qoGx5DeqFs81kpGdzjrPSn1OpO0pT9XE/LZx8H8Cllk\njVTzjlbjqxIiBdvvhs3I2iAE7EB5LdT4NPJ7n4IQdR+OBvyA2pcCGrOu80LEBf5ryO6aNfg7WYHj\nARkcsgBjWZ+oMCRtYPAOQiw/3dt4DGJOV4EVhKmQV/AICxq+xKpex0V+9YQxtP/440x9fyFFdFFJ\niLGE2ENlhnzdSjglip8uiuimmASeQZZ4r6rL1u7xtmQZyf5c0ikXyT4fhN1C2mGc5iD9ajuKHEuQ\npYTWihB0A45spUaPfC4GkJjrTpxSsH/MbW5Z96qtxVCVP/igvgQ3sgDKQ8jwVBxSJWu7D6c5mQ4H\n9KvL7tKLEW2JV8BViFd6KlCcAnca+nIlYc8PntER+S43ukVtrAX5rrYgnbtA3NhbkK8toM7pV+fV\nCzeQryugPlOrmiu0GhGsObxO2rJWIovAl4b62gBD1CciDEkbGLyLkKSnfISw5zOLD/Eyhyeb1V50\nMemnbmIyOwAIEMZLjGK6BwmpaBd3F8V0U0QTE0jjVlHvPLopxkWaNC7a28phey70g3duL5X5ITqS\nJexvGS1u2BBiWWdDE5obIUDdjlN3+2oBQq04RKFJuhWnLWcOuhTsrRK2LHK0tGedWMIBHE90GnEl\n+xFLOqD2PQRMUKd24xiZaWQBkkDc0V71DMLNfQgh1yEEGsRRE/sRsGa9mmwe7JZYcF5xmL4txZLp\n3YJjQa9FLP3LcDqmvaGuMYjjkBiJky0O8huEUU1Y1qJbVB7+3dzE0XpIZ8OQ9YkDQ9IGBsMElnUn\nF/Bj1rHrsGN1pRfwzLfXQR2cU/M0s9iYsZQ1AoTxEyWNCKoU0UWYAl6jmrjq0qW7dQGZ8q80bto6\nyji44xQoBm9Fr1jX/bkQFhI/e+azvPTs+ai8NoG2VnUyWp96DCAx7y04Cml96j32TiSwqmPDpQhZ\nLxv0PcjkpYM6f1nWXep9l0FVTUYsDBjcbwSEaDsQImwE6SY1h0yTDa+6djeOp8CPLDxqcSzykWrf\n6ep1hdq3DfhqKxIX2Aosh9/nw3nK5b3F7VjQLepcWxCdcBjsdNDnaMFpF53Ies7k8K0GGo+5sHGy\n1zuPOg4MWZ8IMCRtYDCMcMOll3Lznw+3pM/KuZSNVY+Lq7QOuCzB1PKtVCozza+UwEGSx7zEKCCM\nh2QmZt1NER2UDkoy66JIbUvpVxwfiaQHn0dMzTQuohG/Q9opl3pYjsGm3cNphHDcWY9eHG/xNiRW\n+0AccX9rcQ4tKBLHtpcOImlJkJLuURKHBrgcLpwosWDtZdcGpI4/HwCeR2WvdwDVkhymS6t04pb2\nAOhcs6xEvkxcWkN/tpcRcTHWAnEYvxDuhrL3NeMjJqVYOoyvc7h2AddrT0IMx/T3wseCspDRza7C\n6nAm9q9ZeuUx5UA1JD6dj2OeHx2GrIcvDEkbGAwjPPvIIzzxpS/x/V2ONf1RSnmMX9Lnf7/jpg2o\nRx1wHYybsp1KQviI4ydKEV2ZEi+ARJZICkAHJXRTTCWhTPMPELLWcqVpETvFRTqTTZ5LIjNHEd2Z\nMV7iJPFkmoro7l/hngDevBjxPh/evBj7uwqgSaxzetVn2QHcBzSthMqlENIlRTMRNizJ+oYq4MJ5\n4srWcdxT1PZIHJLbgSTC6fiudoMH1Nhsl722wF047u4chNBHIiSuFyTbEdd5fJPaMQZ+Xgp1UD1p\nM0k8Uvq2JV/Gagu9X73vOe0Dj+DIts6EKqXvrV3smducXtA8/nfJujp11D3HGmqIepjCkLSBwTDD\ns488wpN33omrv5/0yJHc8UQRffwTkog1H/BKbHM0YgEGgY+Bpy5CZaFjWQcIU04beUQpIEyC3IxV\nrYlZ97rWZOwiRVxphmvoGuBs4gap0c4lqfakM/vTmZmcGu7sfXohkEh6SPbnOt2+nkdcxNPViZ8D\nHliPo5o2AMyEWTXSvEJjJ1KuVIGQoXYTo173IyTbh2PA6qzvU9XxdUjM2q++VxAC70dIXHsLdMMx\nnSG+shbmppgwdgcpXOzeUwV3uuF2gFYoqIBrs671HqD9XpyStlIonifX34IsLAaFlFcDTUckaCcO\nDUeqj5ZEu72HTjwkDFEPPxiSNjA4gSCWEUiKMVBQI+RyKhI3nQXMTVE2NqQSyhIECOMjToBe/PSR\nxEMaFxPYRQvBDLlqso4dQtJAhrx1X+xsazubjF2k8Clz30OCPtV8ROaXGLpeKIAQPYgF376nUk7W\n5xbe0bFsHfd+EfhhBNgLldVOMtfpCEGncNRPtaRmP2KwdiALAB0b71Lz9qv92wG7HqiBq7ziaS9G\nyFzHrMNyap4EUgPwVA5FdXsJjAgTPigme/dPxsCXdAPwiExw3kIp2WrCKXd7HPgO8jm7gAdQCWYD\nOFZvE1B/WD360B2uxuCUx2nxFnDCBiCrgKMTtSHp4YfjzXvuYw8xMDD4e6Fv2LqRhGXdBRsnAvMc\nV2zQTfvy8YQ/0EtRfjdhCnCRIkkuAcIU0YWfKA1MUxZ1biaOraFlStO4cZHCTTqjLQ5krO2Y6o2d\nLawSJ4aXWCYxzUOSJB789BHHS4BwhuRlDi+5dFM0VpQ9NMknJ3kybvr2PZVC3o/kQ3++WLNp4Ep1\n8wpb6ll9AE3GILykY8tdOHXQbyB63L2IZ+JbtYfHortwQsJarvMjwO/isDaH2CwfeflRYn0+4vcU\nwFdBLk7Fk2cslPnmqTm/DMTrYUat/FZLsq7ZDaR05nsjQtLZym+HIjuT241039p+yJh8dWw3hqAN\nwFjSBgbvGqROFoRJChHzcQ58LAeuAc/UCC53Gn9+VJF1N7kkBlnCGkkVo852ZXuUD1nrh2tyByHr\nWNJLuac9ozmutch1Q5By2jLn0oSua7hj+PCQGFTH7coiFb04KKGDsYTooph1PXUie1qsBuVlkVCf\n26kt1iViI3HqonX3MI2v4YiSZNcpH8DJWt+HlGPNBk+FhBZ0KKBzw1iRAG0cQKQ9s8j18nmO+ti/\nNKqL2otYu0tFgrRfXaOttb2l9eiRiHOwNa0V13KQBUI+cIE6RyNC0MeGIenhCePuNjB4j8OyVoK1\nFO4G5or8KIC/IIrf0zeouYePGB6SxPDiJk0KV8aKBsfK1THtKP5BMeZor5+DaTfevBiekQmS/bkE\n8sN4SChqFuvZg9NjW8e19X5N7NqC19cTx4eLNDG8dFMs1nXYDYEUI3IToqSmyTmbhDUxa7d5v9o+\nHSHmYiT+rLO3wYlhaxGXMqAKvFN7cbnlWl3uFJWekLQXjQXo21gsZVZfVvPlIlZ3MeKa3w58vh6n\nJ7SSXPUqd3YQJW4mtdCS7X6jymovZHDylxenkUipOp610LJqVQ/qdWSXYpn2lSceDEkbGJxEkCSi\nGpg3Ez6LhDIrFWGmXNDqFqIJIhnUXlQdb4K8QBS/L5qxfrORHVtO4yJ90EVKlW2lUy48I5P4fLEh\nLXMgY10nD3rIGxEdMsYt4+Q8MXx09pSQDPvxFou/OL6vwCFkbQWH1esQ8EeEmHV/6DwcVbKpCae8\nDKDfUm5vpSqWcjkLgRa340IPAHkpPHkxkv25eEYmKCrspv1vQXlfu9vpX/Iq8AJSucVWxJ2t5TuD\nUDATelchFrC2xHWsGRyi1gRdgSON6s16VIjIy+bVg+rM4UjxbEPUwxmGpA0MTmJYVgSuUNKalwOj\nwTM9QrIlXwhuCxKXzUOyrouAygTevBjplAtvnhB2sj83Y2ECpBXZpVMuXO40ibiHgwd8jDhFxh9M\nu/GMdEhaExxAasCFOyc9aJ/Lnc7M6XKnCearhhY9JSS71PXrttBvIAS9D4k356ht3cxiFkKyG3Hq\nrO8A7+he4n0+6PcIwWr0ux3yfxHZzlPHipGke3B0v3V5lybyfqS2eq+ao6EHphU62ehNQGgnUlzd\noiaLKiv6TvXaj7ixdUJYj3qtxFkYp16r7lkb1yHyoUNpfA9N1GDIejjCkLSBwUkOuWkvBP9MiatO\nxSmDasVJttIyluAYc1oqU9dt6yQorcwFTlnUofACeTaMTGbc4xrxPp+jJ64TvVKIC1mLpuzDIcs+\nnFKpOBKO1wSZQoi0S13vfQgXVqKy4RG3d3/WXC6EvPXnKc76DrYgJVZx1D/dUFYhFrpuUR0G7lTH\nZ3hhNkLwupQLeRsjkVIwvd0ewdETBVFdO5xoNUSFDSQzTVnWVahuWuuw7bpDxh+ZoMGQ9HCEIWkD\nA4OsDl1VwBywlHWq9a77cEQ+BhAS1MQbzJrIj5C1jvXqTGlN2JORcjHUsVyggCxxkUTGOo83FUgT\niy1umJ4Sws7W3NaqYZqcdRy5Xx0rUOd9HqflZAohy5E4Ep0fwVlUZFvAWqpzm9qnE8rWIiqjmdiy\n+jDnVcjnq1a7bkA1IckXb0UYsfADONnn7TiKbDppbSTQqN3h8czjaGpjltUKVoVTjvfCOg61pI9F\n0BqGqIcXDEkbGBgMgtzM/epVvtquyNqn46VuxBwO4sRNvQiLV0iylSa2II5rWZN4dkw4j8GWch/i\nqs7ExBErtgnJhaol454HHFf3PhyLeB9O+0lwSLwLIW0Xov89Rn20WTjiJXmI10Crat4M9LaQMYPn\nT5Q5mnuAmBBkHlJS1aGus7FVfS8T4VtescAfV+dNIWSeaQnKYOiMdT/QvBWpu87h0D7SGpb1mBo/\nX7wgcWDjSkPS7wEYkjYwMDginHpsfYPPLtXy4pC47hjRkzUmX+3XmcczcYQ26oFqcOeL21lb25pg\ntXs5jENYm1twOlAg7/cG4Q61W59WK46lcARNBnA6eu1ESBSkPlq79ovUs5YTb+hASphakIVJHIn9\nVjjP31LXeBewELGMQWRJo/U4busiqP7/7d17fJTVve/xz0MuGiCRm0RIqEEgJQRySLjpxkvUdAu1\n6akBpcJxC5pXd71Qi0XrtfVS2dtLNxuz96Z6sFKQCl7S1ljAGiVeoCeIwCteKBAlmMQADTEmlABJ\nXOeP9cxMAiEkIZl5SL7v12temcw888ya5zXwy1rrt34rw36W97EBvbYeJkbYuXH/cQMgOsa+3Uj3\n0v4NqMt3r5nvujadPwjHmDtxHPfSTnTPvw5gI8bYkqN2x7Wme3n6LlZg6ZoCtPcoSItIhxy/hOfE\nnpovEES5xwUqZ7W0/MffG/TvdtE0SaqEQEWtps/FQniGLRPqm7uGwLaVRwj0spvukgkE9t30TWI3\nYCeHG5r8fvxkepz7WLR97+HT7cPxBJLr3seWNKUeu2XnDmAAJGUFhrOrgbnAHb7Pdxi7pacvEE+F\n/jHwf4AX3Ie+Al8d70Amt/2Lwl/kZgCBPzoagPcCQRp8Feuy4SK3IExlIYFdyRSkvUhBWkQ8xWY0\nRzd5pIpAtrOvVrUvSPsynsfhH3aPTrBzw76tKut852i6dMxXK9TXk6whMP9bz8kKiQT+EPFlziW4\nv6cRqO4Vg/0DIAJ4yT1nHDDHDnEnEBjuz9mBXRPtW/PsmzaoB7JhWASU1sDEGLuEqw7spLjvr5E4\nfEHWmPk4jjvBnRFrRxPeywcGY0xKk89QCJlTmmel/xdgbClTY6af8LkldBSkReSM07TXboP3KgI1\nqsMJLE2CQAIWxz3uC8h1BObZa4CGVnuUzUcMRmKre/ky6tyEO//PHAJTAFlwSVJgvntLy5tn2GHp\nWGCy+0iKffm92AGFlfvxzU8TngQN+UBRoDedRmCNe1/gxSJ7DnxbfZ5vfwybBT8mkID3G6BiB8b4\nMt/ECxSkRaRbsRW66gn0tn27bkBgTvbENWHtHeoNBOs47PqrBvxzyocAk4sN1vuBTMh0S5g+vx8o\nwJhZLZzTN28chd2i09fOUXDRVPjf2I7zFqCiHvpHwFd5bvszcZxlQBqEp9nhdLAj+NXAhiL3fOXu\ne0yFewcE5vwBfrYVhqRhvmzXpZAupCAtItJBdo43FtujjgHibDJcPwJLscZjfw/HVj5bthxj5h53\nnocJZMZjzwPuSbYSSO5ytyv9NbaX/GPczPBlGJON42x032gUcBjmxdtgXUFgBuHqOuzAhiR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KfQ7lnxEXCxdwO031zgr2CqwJgsG4CvymeXk8ROvg1AGI2E0QiHUIDuARSkRaRbsjtapdlfCsHM\nDmVrWuc4W2HIAFgPdplVU3FACSMp5p/YRAb5vJV2NdRuDH5DJegUpEWke7ooASiHZ8Cknd6pHOdh\n/61rxEHFVphKC2u2d8DwURzlLN7gKoZRCg8A0VNtkpl0awrSItLtOE69XQ69KgHO7ug5TgzMXbaX\n87BYeCYNXqnCcQqOe7IK9izjr9+9nDAaKGYkV2b92e51fXlE17RHPEOJYyLS7ThOPTxnA5i5qT2v\newJbWOTACc91VYB2nP1AOQxLg5Fg3j7++RzgRnrtC+Oq2DeIppY6egN2fvqPzgwgAv1X6w3aYENE\npBWOsx/ujYVzgD+DefdUxy9z74Vjg3M0zUtv1jYL0L6edWcFbcfZb3vS3wOW0mKwtXteJ8CQKfAA\njL31Ay6nAICcSXfBlpZfJ8HX2XEvvNPOJCLiBcNi4QPgQ5slfTKOsxG7ILkGiGlyq8cG6VqMmd8p\nTWp9yDwG7sEOX1MHRLk9+nBsPe9oTJPapY5Twse3ncvH/30XN9/63zAP2N4pzRQP0py0iHQbjvME\nlO6H/P2Qbmt1O84T7m0NjrPUPS7PfUUckI4NiHXusqdZGDO3xQDd3sQxx8lxA25rNsK/Yyuhub1j\nKwrbqwdnKDi/sMuo/fKhkTAm3LoRGrY2+UzSnWi4W0S6DTt/GwVkw0iguB54CRuEfd3qBuAabE+5\n/euMHec/3Ht216qWhr1tO3yZ1zHuz5pmPeLAsfnASBiUAJWFGDMFx1nlPltuP8vwAXAE2HKUIUO/\nZChf2rXSwOZHLoVf5mFMZrs/i3Q+DXeLiJyEMfPd+dtVUFyO7R3bIOo469yj3ISyDhcCiSAwZx3X\n7BnbU49pctxlwA5gL8bcfcKZbICOs+ebDqwsd5/x/UExDigj6fO9/teE0UAlAwGIphbmNsAfM3Gc\nNRgzq4OfSbxKPWkR6ZYc5+FOz8i2w91R2J2oBgBVGJPd5Pml2AA+BVtIZY17TEs96KXAKPe30dhe\nczl2+L0IG+zjSDT7AfwlQSuPDeTryv4w9iz4ShtteI160iIibdD5Ado3t1yH7f3WuLemGsBxA7LZ\njx1Sb23D6ihgpE12GxQP+9yHK9KBevgsnGiKaSSM7c4Ee37WYUyW29lWgO7uFKRFRFph56CnAoOx\n89AjsUPZA7E9X99xuUAc9MPG0to8mi/las6YW9zSpbFQWmUT3qKSYAucM3IfgyIPAvDh1qkwAcA3\n75zV6Z9RvEvZ3SIiLXCcVU16zxuBBGzPN8n9WY8vecwG8hpwsuxhtfXuMVFuElnLjEnAzlmHAzsw\nh4HkQr4uPo/D9KaW6GbLq06dKS7djYK0iEiL6rG9ZrA95/3AtCbPlx83pD4XDFAJXBNBIIEMd/nX\nY00KpzRVBOExEG57yMZMgZlQ8chwDnwx1Ab9Jfjb0nX1w8WLlDgmInIKdknUHGyvF+y8cNMCI75y\noqOADLge6AMs881Z5wCxBBLOYtxzxbmP2165MVOPe98SmJ8AOVvdR7Y2S1QT71FZUBGRIHMc39xy\nGZCPMbe0cMxjQBokTYfzwF0lZeeol9WBEwXGnbemyr2F29ewGWPmtPL+nVuKVLqOgrSISJA5znKI\nngu1hcCUk9bJDgxFpwGZtkd9HlANLAd+BuZJcJwiIAVfwRNjtJtVd9HZcU9z0iIip2DMXDdb2xYv\nsXPMy1s4MhybBV4GrLFVPgcBFwPjgbfAuRZsL7oAhkQA67u28XJG0xIsEZE2icaurarBjmU3X14V\nKBdqt7n0DYnbmtqj4a1Rdlnz/djXRk+HClUJk9ZpuFtEpA1sZvZIYAoMiYIKIAnMp7756CRsAC8n\nkNldB9wIUbHwPERN/4q6c0phegoAZm3wP4d0LQ13i4iERCx2XbQtMsI8+8NxyrAZ2/uBWdgs8MHY\nAD3YPl5XBE/Z4/v+Y6itArouP4htlzOVhrtFRE7BbtoBdtHyNtuL3ucr4+kb9s7EBvACO4cNOOfa\nZyJ31jB4QDFlF4yEvsBHBRiTEazmyxlMw90iIm1gE8WqCJQGBS6fA2OBnHXYjO7iZmudnaHAr7BJ\nY9nANoAijEkJXsMlqLQES0QkBJpW+jLmlzjORug/1faMAUp9ve2B2EIlUfjrbK8aYEfBFaC7Pc1J\ni4h4QiF8VQiHsKVAo2bBsKaZ2u4w+HMD4AWwRVAUoKV91JMWEWmjlip/2aVXadjksTr3VgL958I0\nML8PejMlhDTcLSLiQTaARwGD/Ylj0vMoSIuIiHiU5qRFRER6CAVpERERj2pTMZPGxkYmTpxIfHw8\neXl5zJo1i127dgFQXV1Nv3792LZtW5c2VEREpKdpU5BesmQJY8aMoba2FoA1a9b4n1u4cCH9+vXr\nmtaJiIj0YKcc7i4rK2Pt2rVkZ2efMBlujOGll17i+uuv77IGioiI9FSnDNILFizgySefpFevEw99\n7733iI2NZcSIEV3SOBERkZ6s1eHu119/ncGDB5OamkpBQcEJz7/44ovMnj271Td46KGH/PfT09NJ\nT0/vSDtFREQ8p6CgoMX42FlaXSd93333sXLlSsLDwzly5Ag1NTXMmDGDFStW0NDQQHx8PFu3bmXo\n0KEtn1zrpEVEpAcJWTGTd955h6eeeoq8vDwA1q9fz+OPP86GDRtOfnIFaRER6UFCWszEcRz//TVr\n1ihhTEREpAupLKiIiEgnUVlQERGRHkJBWkRExKMUpEVERDxKQVpERMSjFKRFREQ8SkFaRETEoxSk\nRUREPEpBWkRExKMUpEVERDxKQVpERMSjFKRFREQ8SkFaRETEoxSkRUREPEpBWkRExKMUpEVERDxK\nQVpERMSjFKRFREQ8SkFaRETEoxSkRUREPEpBWkRExKMUpEVERDxKQVpERMSjFKRFREQ8SkFaRETE\noxSkRUREPEpBWkRExKMUpEVERDxKQVpERMSjFKRFREQ8SkFaRETEoxSkRUREPEpBWkRExKMUpEVE\nRDxKQVpERMSjFKRFREQ8SkFaRETEoxSkRUREPEpBWkRExKMUpEVERDxKQVpERMSjFKRFREQ8SkFa\nRETEoxSkRUREPEpBWkRExKMUpEVERDxKQVpERMSjFKRFREQ8SkFaRETEoxSkRUREPEpBWkRExKMU\npEVERDxKQVpERMSjFKRFREQ8SkFaRETEoxSkRUREPEpBWkRExKMUpEVERDxKQVpERMSjFKRFREQ8\nSkFaRETEoxSkRUREPEpBWkRExKMUpEVERDxKQVpERMSjFKRFREQ8SkFaRETEo9oUpBsbG0lNTSUz\nM9P/WE5ODklJSYwdO5af//znXdbAnqCgoCDUTThj6Fq1ja5T2+g6tZ2uVWi0KUgvWbKEMWPG4DgO\nABs2bOC1116jqKiIjz/+mIULF3ZpI7s7ffnbTteqbXSd2kbXqe10rULjlEG6rKyMtWvXkp2djTEG\ngKVLl3LvvfcSEREBwLnnntu1rRQREemBThmkFyxYwJNPPkmvXoFDd+/ezbvvvsuFF15Ieno6W7Zs\n6dJGioiI9EimFXl5eebWW281xhizYcMG873vfc8YY8zYsWPNT37yE2OMMZs3bzbDhw9v8fUjRoww\ngG666aabbrr1iNuIESNaC6vtFk4rNm3axGuvvcbatWs5cuQINTU13HDDDcTHx5OVlQXApEmT6NWr\nFwcPHmTgwIHNXl9cXNza6UVERKQVrQ53L1q0iNLSUvbs2cPq1au54oorWLlyJT/4wQ94++23Adi1\naxfHjh07IUCLiIjI6Wm1J308X3b3TTfdxE033cS4ceOIjIxkxYoVXdI4ERGRnswxxk3ZFhEREU/p\nlIpjL7/8MsnJyYSFhfHhhx/6H3/zzTeZOHEiKSkpTJw4kQ0bNgBQW1tLamqq/3buueeyYMGCzmiK\np7X3OgEcO3aMH/3oR3z7298mKSmJ3NzcUDQ96DpyrdLT0xk9erT/e1VZWRmKpgdVR66Tz/e//33G\njRsXzOaGVEeu1bRp0xg/fjzJycncfPPN1NfXh6LpQdXe61RXV8fVV1/tL2517733hqrpQdeR79T9\n99/Pt771LaKjo9v2Jp2RfbZjxw6zc+dOk56ebj788EP/49u2bTMVFRXGGGM+/vhjExcX1+LrJ0yY\nYN57773OaIqndeQ6/eIXvzAPPvig//fKysrgNTiEOnKtjj+2J+jov71XX33VzJ4924wbNy6o7Q2l\njlyr2tpa//0ZM2aYlStXBq/BIdLe63T48GFTUFBgjDHm2LFj5pJLLjHr1q0LfsNDoCPfqcLCQlNR\nUWH69u3bpvdo15z0yYwePbrFx8ePH++/P2bMGOrq6qivr/cXQQGbeHbgwAEuvvjizmiKp3XkOj3/\n/PPs3LnT/3xPSdDr6HfK9LDZm45cp0OHDrF48WKeffZZrrvuumA1NeQ6cq369u0LQH19PceOHWPQ\noEFBaWsotfc6RUVFcdlllwEQERFBWloa5eXlQWlrqHXkOzV58uR2vUfQNth49dVXmTBhQrMADbB6\n9Wp++MMfBqsZntf0OlVXVwPwwAMPMGHCBK677joOHDgQ4hZ6R0vfqRtvvJHU1FR+9atfhbBl3nL8\ndXrwwQdZuHAhvXv3DnHLvKel79RVV11FbGwsUVFRTJs2LYSt846T/X9eXV1NXl4eV155ZYha5j0n\nu1Zt1eae9He+8x327dt3wuOLFi1qtvFGSz755BPuuece3nzzzROeW7NmDS+88EJbm+F5nXmdGhoa\nKCsrY+rUqfz6179m8eLFLFy4sNtk03f2d2rVqlUMHTqUQ4cOMWPGDFauXMkNN9zQ6e0Ots68Ttu3\nb+fzzz9n8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"text": [ "<matplotlib.figure.Figure at 0x7faa96b56290>" ] } ], "prompt_number": 18 }, { "cell_type": "markdown", "metadata": {}, "source": [ "Close enough...\n", "\n", "Now calculate the ssh correction." ] }, { "cell_type": "code", "collapsed": false, "input": [ "print press_CGRF.shape\n", "print 'Max CGRF pressure', max(press_CGRF)\n", "print 'Min CGRF pressure', min(press_CGRF)\n", "\n", "eta= -1/g/rho0*(press_CGRF-P0)\n", "print max(eta)\n", "pylab.plot(eta)\n", "pylab.xlabel('Hour since Feb 4, 2006 00:00')\n", "pylab.ylabel('Eta correction due to inverse barometer (m)')" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream", "stream": "stdout", "text": [ "(24,)\n", "Max CGRF pressure 98661.5\n", "Min CGRF pressure 96697.2\n", "0.423781005776\n" ] }, { "metadata": {}, "output_type": "pyout", "prompt_number": 19, "text": [ "<matplotlib.text.Text at 0x7faa95d8ae10>" ] }, { "metadata": {}, "output_type": "display_data", "png": 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Go0aN+EkSCeLi4nQSYFWoRUGqY80a4JNP+EDqgAFiR0NKMQb07w+4uAALFogdTe2mlXUU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\nyeVAWBgv50tJghCi70JCgE2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"text": [ "<matplotlib.figure.Figure at 0x7faa95b543d0>" ] } ], "prompt_number": 19 }, { "cell_type": "markdown", "metadata": {}, "source": [ "This seems like a large contribution due to the inverse barometer effect. Can this be right?\n", "\n", "Note: digging into the namelists, there is a flag for turning on/off the inverse barometer effect on OBC SSH data. This is ln_apr_obc. I am currently using true, but I am considering changing this to see if there is an effect...\n", "\n", "To do: \n", "* Run a case of all_forcing with ln_apr_obc=false\n" ] }, { "cell_type": "heading", "level": 1, "metadata": {}, "source": [ "ln_apr_obc=false" ] }, { "cell_type": "code", "collapsed": false, "input": [ "path = '/data/nsoontie/MEOPAR/SalishSea/results/storm-surges/tide_fix/feb2006/'\n", "\n", "\n", "runs = {'all_forcing','obc_false'}\n", "\n", "fUs={}; fVs={}; fTs={};\n", "\n", "for key in runs:\n", " fUs[key] = NC.Dataset(path + key +'/SalishSea_4h_20060201_20060207_grid_U.nc','r');\n", " fVs[key] = NC.Dataset(path + key +'/SalishSea_4h_20060201_20060207_grid_V.nc','r');\n", " fTs[key] = NC.Dataset(path + key +'/SalishSea_4h_20060201_20060207_grid_T.nc','r');" ], "language": "python", "metadata": {}, "outputs": [ { "ename": "RuntimeError", "evalue": "No such file or directory", "output_type": "pyerr", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mRuntimeError\u001b[0m Traceback (most recent call last)", "\u001b[1;32m<ipython-input-20-01886e1c2471>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 8\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mkey\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mruns\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 9\u001b[1;33m \u001b[0mfUs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mNC\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataset\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mkey\u001b[0m \u001b[1;33m+\u001b[0m\u001b[1;34m'/SalishSea_4h_20060201_20060207_grid_U.nc'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'r'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 10\u001b[0m \u001b[0mfVs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mNC\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataset\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mkey\u001b[0m \u001b[1;33m+\u001b[0m\u001b[1;34m'/SalishSea_4h_20060201_20060207_grid_V.nc'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'r'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 11\u001b[0m \u001b[0mfTs\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mNC\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataset\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mkey\u001b[0m \u001b[1;33m+\u001b[0m\u001b[1;34m'/SalishSea_4h_20060201_20060207_grid_T.nc'\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'r'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", "\u001b[1;32m/home/nsoontie/anaconda/lib/python2.7/site-packages/netCDF4.so\u001b[0m in \u001b[0;36mnetCDF4.Dataset.__init__ (netCDF4.c:19478)\u001b[1;34m()\u001b[0m\n", "\u001b[1;31mRuntimeError\u001b[0m: No such file or directory" ] } ], "prompt_number": 20 }, { "cell_type": "code", "collapsed": false, "input": [ "start='01-Feb-2006'\n", "stations = {'PointAtkinson': 7795, 'Victoria': 7120, 'PatriciaBay': 7277, 'CampbellRiver': 8074, \n", " 'CrescentBeach': 1, 'WhiteRock': 1, 'BoundaryBay': 1}\n", "datums = {'PointAtkinson': 3.09, 'Victoria': 1.881, 'PatriciaBay': 2.256, 'CampbellRiver': 2.916, \n", " 'CrescentBeach': 2.44, 'WhiteRock': 2.85, 'BoundaryBay': 1 }\n", "thalwegs = ['Thalweg1','Thalweg2', 'Thalweg3', 'Thalweg4', 'Thalweg5', 'Thalweg6']\n", "allstations = {'PointAtkinson': 7795, 'Victoria': 7120, 'PatriciaBay': 7277, 'CampbellRiver': 8074,\n", " 'CrescentBeach': 2.44, 'WhiteRock': 2.85 , 'BoundaryBay': 1,\n", " 'Thalweg1': [], 'Thalweg2': [], 'Thalweg3': [], 'Thalweg4': [], 'Thalweg5': [], 'Thalweg6': [],\n", " 'Plume': 1} \n", "#datums from t_xtide\n", "run_stations={}\n", "us={}; vs={}; lats={}; lons={}; tmps={}; sals={}; sshs={}; ts={};\n", "\n", "for run in runs:\n", " for key in allstations:\n", " string = path + run + '/1h_' + key + '.nc'\n", " run_stations[key] = NC.Dataset(string,'r');\n", " t=run_stations[key].variables['time_counter']\n", " ts[run]=stormtools.convert_date_seconds(t,start)\n", " [us[run], vs[run], lats[run], lons[run], tmps[run], sals[run], sshs[run]] = stormtools.combine_data(run_stations)\n", " run_stations={};" ], "language": "python", "metadata": {}, "outputs": [] }, { "cell_type": "code", "collapsed": false, "input": [ "\n", "\n", "start='01-Feb-2006'\n", "end='07-Feb-2006'\n", "emin=-3\n", "emax=3\n", "plt.figure(figsize=(20,12))\n", "\n", "wlev_pred_xtide={}\n", "wlev_meas={}\n", "\n", "i=1;\n", "for key in stations:\n", " for run in runs:\n", " ax=pylab.subplot(4,2,i)\n", " pylab.plot(ts[run],sshs[run][key][:,0,0],label=run)\n", " pylab.title(key)\n", " ax.set_ylim([emin,emax])\n", " \n", " \n", " if key == 'PointAtkinson' or key == 'Victoria' or key =='PatriciaBay' or key =='CampbellRiver':\n", " #plotting observations\n", " statID_PA = stations[key]\n", " filename = 'wlev_' +str(statID_PA) + '_' + start +'_' +end +'.csv'\n", " tidetools.get_dfo_wlev(statID_PA,start,end)\n", " def dateParserMeasured(s):\n", " #convert the string to a datetime object\n", " unaware = datetime.datetime.strptime(s, \"%Y/%m/%d %H:%M\")\n", " #add in the local time zone (Canada/Pacific)\n", " aware = unaware.replace(tzinfo=pytz.timezone('Canada/Pacific'))\n", " #convert to UTC\n", " return aware.astimezone(pytz.timezone('UTC'))\n", " wlev_meas[key] = pd.read_csv(filename,skiprows=7,parse_dates=[0],date_parser=dateParserMeasured)\n", " wlev_meas[key] = wlev_meas[key].rename(columns={'Obs_date': 'time', 'SLEV(metres)': 'slev'})\n", " #pylab.plot(wlev_meas[key].time, wlev_meas[key].slev-datums[key],'k*',label='observed') #subtracted off the datum from t_xtide\n", "\n", " \n", " if key != 'BoundaryBay':\n", " #plotting t_xtide predictions\n", " filename = '/data/nsoontie/MEOPAR/analysis/storm_surges/data/'+ key+ ' (2)_xtide_prediction_' + start+'_'+end+'.csv'\n", " def dateParserMeasured2(s):\n", " #convert the string to a datetime object\n", " unaware = datetime.datetime.strptime(s, \"%d-%b-%Y %H:%M:%S \")\n", " #add in the local time zone (Canada/Pacific)\n", " aware = unaware.replace(tzinfo=pytz.timezone('Canada/Pacific'))\n", " #convert to UTC\n", " return aware.astimezone(pytz.timezone('UTC'))\n", " wlev_pred_xtide[key] = pd.read_csv(filename,delimiter='\\t',parse_dates=[0],date_parser=dateParserMeasured2)\n", " wlev_pred_xtide[key] = wlev_pred_xtide[key].rename(columns={'Time_Local ': 'time', ' wlev_pred ': 'slev'})\n", " #pylab.plot(wlev_pred_xtide[key].time, wlev_pred_xtide[key].slev-datums[key], label='t_xtide')\n", " \n", " pylab.grid()\n", " i=i+1\n", "\n", "pylab.legend(bbox_to_anchor=(1.05, 1), loc=2)\n", "print 'Sea Surface Height'" ], "language": "python", "metadata": {}, "outputs": [] }, { "cell_type": "code", "collapsed": false, "input": [ "Us={}; Vs={}; Es ={}; Ss={}; Ts={};\n", "\n", "timestamp =25#model output time \n", "depthlevel = 0 #model level to plot\n", "for key in runs:\n", " \n", " [Us[key], Vs[key], Es[key], Ss[key], \n", " Ts[key]]= stormtools.get_variables(fUs[key],fVs[key],fTs[key],timestamp,depthlevel)\n", "# define plot parameters\n", "#time, depth, colormap etc\n", "\n", "times = fVs[key].variables['time_counter'] #array of output times\n", "time = times[timestamp] #physical time in seconds\n", "\n", "depths = fVs[key].variables['depthv'] #array of depths\n", "depth = depths[depthlevel] #physical depth in meters\n", "cmap = plt.get_cmap('jet') \n", "u_lat = fUs[key].variables['nav_lat']\n", "u_lon = fUs[key].variables['nav_lon']\n", "T_lat = fTs[key].variables['nav_lat']\n", "T_lon = fTs[key].variables['nav_lon']\n", "v_lat = fVs[key].variables['nav_lat']\n", "v_lon = fVs[key].variables['nav_lon']" ], "language": "python", "metadata": {}, "outputs": [] }, { "cell_type": "code", "collapsed": false, "input": [ "diff = Es['all_forcing']-Es['obc_false']\n", "pylab.pcolormesh(diff,vmin=-0.004,vmax=0.004)\n", "pylab.colorbar()" ], "language": "python", "metadata": {}, "outputs": [] }, { "cell_type": "code", "collapsed": false, "input": [ "print (Es['all_forcing']==Es['obc_false']).all()" ], "language": "python", "metadata": {}, "outputs": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "These are identical! I should double check that the I actually used ln_apr_obc=false" ] }, { "cell_type": "code", "collapsed": false, "input": [ "import commands\n", "\n", "str1=path+'all_forcing/namelist' \n", "str2=path+'obc_false/namelist' \n", "\n", "cmd = 'diff '+ str1 +' '+ str2\n", "print cmd\n", "\n", "\n", "out = commands.getoutput(cmd)\n", "print out\n", "\n" ], "language": "python", "metadata": {}, "outputs": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "** Conclusion**\n", "\n", "This flag ln_apr_obc does not affect our results. Note that this flag was not found in the 3.4 documentation so it may not be in use anymore.\n", "\n", "Does that mean we have to remove the inverse baromenter ourselves? This would make preparing foricng files more difficult since we would need the weather..." ] }, { "cell_type": "code", "collapsed": false, "input": [ "def get_NOAA_wlev(station_no, start_date, end_date):\n", " \"\"\"Download water level data from NOAA site for one NOAA station\n", " for specified period.\n", "\n", " :arg station_no: Station number e.g. 9443090.\n", " :type station_no: int\n", "\n", " :arg start_date: Start date; e.g. '01-JAN-2010'.\n", " :type start_date: str\n", "\n", " :arg end_date: End date; e.g. '31-JAN-2010'\n", " :type end_date: str\n", "\n", " :returns: Saves text file with water level data at one station\n", " \"\"\"\n", " # Name the output file\n", " outfile = 'wlev_'+str(station_no)+'_'+str(start_date)+'_'+str(end_date)+'.csv'\n", " # Form urls and html information\n", " \n", " st_ar=arrow.Arrow.strptime(start_date, '%d-%b-%Y')\n", " end_ar=arrow.Arrow.strptime(end_date, '%d-%b-%Y')\n", " \n", " base_url = 'http://tidesandcurrents.noaa.gov'\n", " form_handler = (\n", " '/stationhome.html?id='\n", " + str(station_no))\n", " data_provider = (\n", " '/api/datagetter?product=hourly_height&application=NOS.COOPS.TAC.WL'\n", " + '&begin_date=' +st_ar.format('YYYYMMDD') +'&end_date='+end_ar.format('YYYYMMDD')\n", " + '&datum=MLLW&station='+str(station_no)\n", " + '&time_zone=GMT&units=metric&interval=h&format=csv')\n", " # Go get the data from the DFO site\n", " with requests.Session() as s:\n", " s.post(base_url)\n", " r = s.get(base_url + data_provider)\n", " # Write the data to a text file\n", " with open(outfile, 'w') as f:\n", " f.write(r.text)\n" ], "language": "python", "metadata": {}, "outputs": [] } ], "metadata": {} } ] }