From dab2daca396ac3be8a4e53291c4a158d29ee69f9 Mon Sep 17 00:00:00 2001 From: Riccardo Bertossa Date: Fri, 3 Aug 2018 11:51:59 +0200 Subject: [PATCH 01/19] Modified directory structure to allow correct import of package added more options in analysis.oy --- __init__.py => thermocepstrum/__init__.py | 0 analysis.py => thermocepstrum/analysis.py | 35 ++++++++++++++----- .../blockanalysis.py | 0 .../example}/Blocchi_due_componenti.ipynb | 0 .../example}/Silica.dat | 0 .../example}/Test_due_componenti.ipynb | 0 .../example_cepstrum_silica_API.ipynb | 0 .../example_cepstrum_silica_old.ipynb | 0 .../grafici_belli.mplstyle | 0 .../heatcurrent.py | 0 {i_o => thermocepstrum/i_o}/__init__.py | 0 .../i_o}/extract_lammps_thermo.sh | 0 .../i_o}/read_lammps_datafile.py | 0 .../i_o}/read_lammps_dump.py | 0 .../i_o}/read_lammps_log.py | 0 .../i_o}/read_lammps_log_old.py | 0 {i_o => thermocepstrum/i_o}/read_tablefile.py | 0 {md => thermocepstrum/md}/__init__.py | 0 {md => thermocepstrum/md}/acf.py | 0 {md => thermocepstrum/md}/aic.py | 0 {md => thermocepstrum/md}/armodel.py | 0 {md => thermocepstrum/md}/cepstral.py | 0 {md => thermocepstrum/md}/lpfilter.py | 0 {md => thermocepstrum/md}/mdsample.py | 0 {md => thermocepstrum/md}/tools.py | 0 {md => thermocepstrum/md}/units.py | 0 .../old_src}/blockanalysis.py | 0 .../old_src}/mdthermanalysis.py | 0 28 files changed, 26 insertions(+), 9 deletions(-) rename __init__.py => thermocepstrum/__init__.py (100%) rename analysis.py => thermocepstrum/analysis.py (95%) rename blockanalysis.py => thermocepstrum/blockanalysis.py (100%) rename {example => thermocepstrum/example}/Blocchi_due_componenti.ipynb (100%) rename {example => thermocepstrum/example}/Silica.dat (100%) rename {example => thermocepstrum/example}/Test_due_componenti.ipynb (100%) rename {example => thermocepstrum/example}/example_cepstrum_silica_API.ipynb (100%) rename {example => thermocepstrum/example}/example_cepstrum_silica_old.ipynb (100%) rename grafici_belli.mplstyle => thermocepstrum/grafici_belli.mplstyle (100%) rename heatcurrent.py => thermocepstrum/heatcurrent.py (100%) rename {i_o => thermocepstrum/i_o}/__init__.py (100%) rename {i_o => thermocepstrum/i_o}/extract_lammps_thermo.sh (100%) rename {i_o => thermocepstrum/i_o}/read_lammps_datafile.py (100%) rename {i_o => thermocepstrum/i_o}/read_lammps_dump.py (100%) rename {i_o => thermocepstrum/i_o}/read_lammps_log.py (100%) rename {i_o => thermocepstrum/i_o}/read_lammps_log_old.py (100%) rename {i_o => thermocepstrum/i_o}/read_tablefile.py (100%) rename {md => thermocepstrum/md}/__init__.py (100%) rename {md => thermocepstrum/md}/acf.py (100%) rename {md => thermocepstrum/md}/aic.py (100%) rename {md => thermocepstrum/md}/armodel.py (100%) rename {md => thermocepstrum/md}/cepstral.py (100%) rename {md => thermocepstrum/md}/lpfilter.py (100%) rename {md => thermocepstrum/md}/mdsample.py (100%) rename {md => thermocepstrum/md}/tools.py (100%) rename {md => thermocepstrum/md}/units.py (100%) rename {old_src => thermocepstrum/old_src}/blockanalysis.py (100%) rename {old_src => thermocepstrum/old_src}/mdthermanalysis.py (100%) diff --git a/__init__.py b/thermocepstrum/__init__.py similarity index 100% rename from __init__.py rename to thermocepstrum/__init__.py diff --git a/analysis.py b/thermocepstrum/analysis.py similarity index 95% rename from analysis.py rename to thermocepstrum/analysis.py index abdeb8f..5d1dcaa 100755 --- a/analysis.py +++ b/thermocepstrum/analysis.py @@ -1,4 +1,4 @@ -#!/usr/bin/python +#!/usr/bin/env python # Needed modules: # numpy @@ -6,23 +6,30 @@ # matplotlib # argparse + + +#add to path the application directory +from sys import path, argv +import os +abs_path = os.path.abspath(argv[0]) +tc_path = abs_path[:abs_path.rfind('/')] +path.append(tc_path[:tc_path.rfind('/')]) + import argparse import numpy as np -import scipy as sp +#import scipy as sp import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt from matplotlib.backends.backend_pdf import PdfPages plt.rcParams['figure.figsize'] = (16, 9) plt.style.reload_library() +plt.style.use(tc_path+'/grafici_belli.mplstyle') #plt.rc('text', usetex=True) c = plt.rcParams['axes.prop_cycle'].by_key()['color'] from matplotlib.ticker import MultipleLocator -from sys import path, argv -tc_path = argv[0][:argv[0].rfind('/')] -path.append(tc_path[:tc_path.rfind('/')]) import thermocepstrum as tc plt.style.use(tc_path+'/grafici_belli.mplstyle') import math @@ -107,6 +114,9 @@ def main(): parser.add_argument( '-j', '--add-currents', type=str, default=[], action='append', help='additional current for multi-component fluids' ) parser.add_argument( '-w', '--psd-filterw', type=float, help='plot - periodogram - filter window width (THz)' ) + parser.add_argument('--plot-conv-max-pstar',type=int,help='max number of P* in the kappa(P*) plot') + parser.add_argument('--plot-conv-pstar-tick-interval',type=int,help='tick interval on the x-axis for the kappa(P*) plot') + parser.add_argument('--plot-psd-max-THz',type=float, help='max frequency in THz for the psd plot') args = parser.parse_args() inputfile = args.inputfile @@ -284,7 +294,7 @@ def main(): # plot periodogram j.plot_periodogram() #PSD_FILTER_W=psd_filter_w) - pdf.attach_note('Nyquist frequency = {} THz'.format(j.Nyquist_f_THz), positionRect=[0, 0 , 5, 1]) + #pdf.attach_note('Nyquist frequency = {} THz'.format(j.Nyquist_f_THz), positionRect=[0, 0 , 5, 1]) pdf.savefig() plt.close() @@ -377,7 +387,8 @@ def main(): # plot kappa(Pstar) # ax = jf.plot_kappa_Pstar() # ax.set_xlim([0, 10*jf.dct.aic_Kmin]) - plt_cepstral_conv(jf) + + plt_cepstral_conv(jf,pstar_max=args.plot_conv_max_pstar,pstar_tick=args.plot_conv_pstar_tick_interval) pdf.savefig() plt.close() @@ -438,7 +449,7 @@ def main(): ################################# -def plt_cepstral_conv(jf,pstar_max=None, k_SI_max=None): +def plt_cepstral_conv(jf,pstar_max=None, k_SI_max=None,pstar_tick=None): if pstar_max==None: pstar_max=(jf.dct.aic_Kmin+1)*2.5 if k_SI_max==None: @@ -457,7 +468,13 @@ def plt_cepstral_conv(jf,pstar_max=None, k_SI_max=None): ax2.set_ylim([0, k_SI_max]) # ax2.grid() ax2.legend() - dx1,dx2=n_tick_in_range(0,pstar_max,5) + + if pstar_tick==None: + dx1,dx2=n_tick_in_range(0,pstar_max,5) + else: + dx1=pstar_tick + dx2=dx1/2 + dy1,dy2=n_tick_in_range(0,k_SI_max,5) ax2.xaxis.set_major_locator(MultipleLocator(dx1)) diff --git a/blockanalysis.py b/thermocepstrum/blockanalysis.py similarity index 100% rename from blockanalysis.py rename to thermocepstrum/blockanalysis.py diff --git a/example/Blocchi_due_componenti.ipynb b/thermocepstrum/example/Blocchi_due_componenti.ipynb similarity index 100% rename from example/Blocchi_due_componenti.ipynb rename to thermocepstrum/example/Blocchi_due_componenti.ipynb diff --git a/example/Silica.dat b/thermocepstrum/example/Silica.dat similarity index 100% rename from example/Silica.dat rename to thermocepstrum/example/Silica.dat diff --git a/example/Test_due_componenti.ipynb b/thermocepstrum/example/Test_due_componenti.ipynb similarity index 100% rename from example/Test_due_componenti.ipynb rename to thermocepstrum/example/Test_due_componenti.ipynb diff --git a/example/example_cepstrum_silica_API.ipynb b/thermocepstrum/example/example_cepstrum_silica_API.ipynb similarity index 100% rename from example/example_cepstrum_silica_API.ipynb rename to thermocepstrum/example/example_cepstrum_silica_API.ipynb diff --git a/example/example_cepstrum_silica_old.ipynb b/thermocepstrum/example/example_cepstrum_silica_old.ipynb similarity index 100% rename from example/example_cepstrum_silica_old.ipynb rename to thermocepstrum/example/example_cepstrum_silica_old.ipynb diff --git a/grafici_belli.mplstyle b/thermocepstrum/grafici_belli.mplstyle similarity index 100% rename from grafici_belli.mplstyle rename to thermocepstrum/grafici_belli.mplstyle diff --git a/heatcurrent.py b/thermocepstrum/heatcurrent.py similarity index 100% rename from heatcurrent.py rename to thermocepstrum/heatcurrent.py diff --git a/i_o/__init__.py b/thermocepstrum/i_o/__init__.py similarity index 100% rename from i_o/__init__.py rename to thermocepstrum/i_o/__init__.py diff --git a/i_o/extract_lammps_thermo.sh b/thermocepstrum/i_o/extract_lammps_thermo.sh similarity index 100% rename from i_o/extract_lammps_thermo.sh rename to thermocepstrum/i_o/extract_lammps_thermo.sh diff --git a/i_o/read_lammps_datafile.py b/thermocepstrum/i_o/read_lammps_datafile.py similarity index 100% rename from i_o/read_lammps_datafile.py rename to thermocepstrum/i_o/read_lammps_datafile.py diff --git a/i_o/read_lammps_dump.py b/thermocepstrum/i_o/read_lammps_dump.py similarity index 100% rename from i_o/read_lammps_dump.py rename to thermocepstrum/i_o/read_lammps_dump.py diff --git a/i_o/read_lammps_log.py b/thermocepstrum/i_o/read_lammps_log.py similarity index 100% rename from i_o/read_lammps_log.py rename to thermocepstrum/i_o/read_lammps_log.py diff --git a/i_o/read_lammps_log_old.py b/thermocepstrum/i_o/read_lammps_log_old.py similarity index 100% rename from i_o/read_lammps_log_old.py rename to thermocepstrum/i_o/read_lammps_log_old.py diff --git a/i_o/read_tablefile.py b/thermocepstrum/i_o/read_tablefile.py similarity index 100% rename from i_o/read_tablefile.py rename to thermocepstrum/i_o/read_tablefile.py diff --git a/md/__init__.py b/thermocepstrum/md/__init__.py similarity index 100% rename from md/__init__.py rename to thermocepstrum/md/__init__.py diff --git a/md/acf.py b/thermocepstrum/md/acf.py similarity index 100% rename from md/acf.py rename to thermocepstrum/md/acf.py diff --git a/md/aic.py b/thermocepstrum/md/aic.py similarity index 100% rename from md/aic.py rename to thermocepstrum/md/aic.py diff --git a/md/armodel.py b/thermocepstrum/md/armodel.py similarity index 100% rename from md/armodel.py rename to thermocepstrum/md/armodel.py diff --git a/md/cepstral.py b/thermocepstrum/md/cepstral.py similarity index 100% rename from md/cepstral.py rename to thermocepstrum/md/cepstral.py diff --git a/md/lpfilter.py b/thermocepstrum/md/lpfilter.py similarity index 100% rename from md/lpfilter.py rename to thermocepstrum/md/lpfilter.py diff --git a/md/mdsample.py b/thermocepstrum/md/mdsample.py similarity index 100% rename from md/mdsample.py rename to thermocepstrum/md/mdsample.py diff --git a/md/tools.py b/thermocepstrum/md/tools.py similarity index 100% rename from md/tools.py rename to thermocepstrum/md/tools.py diff --git a/md/units.py b/thermocepstrum/md/units.py similarity index 100% rename from md/units.py rename to thermocepstrum/md/units.py diff --git a/old_src/blockanalysis.py b/thermocepstrum/old_src/blockanalysis.py similarity index 100% rename from old_src/blockanalysis.py rename to thermocepstrum/old_src/blockanalysis.py diff --git a/old_src/mdthermanalysis.py b/thermocepstrum/old_src/mdthermanalysis.py similarity index 100% rename from old_src/mdthermanalysis.py rename to thermocepstrum/old_src/mdthermanalysis.py From 1da9d340663bc44834115bd1c68105a006b78b69 Mon Sep 17 00:00:00 2001 From: Loris Ercole Date: Mon, 15 Oct 2018 19:38:43 +0200 Subject: [PATCH 02/19] a few multi-components edits + block.py analysis.py : cospectrum in output mdsample.py : cospectrum is now self.cospectrum util/blocks.py : utility by Riccardo (needs to be checked and standarized) --- thermocepstrum/analysis.py | 9 + thermocepstrum/md/mdsample.py | 4 +- thermocepstrum/utils/blocks.py | 359 +++++++++++++++++++++++++++++++++ 3 files changed, 370 insertions(+), 2 deletions(-) create mode 100755 thermocepstrum/utils/blocks.py diff --git a/thermocepstrum/analysis.py b/thermocepstrum/analysis.py index 5d1dcaa..11edbd8 100755 --- a/thermocepstrum/analysis.py +++ b/thermocepstrum/analysis.py @@ -58,6 +58,8 @@ def main(): OUTPUT DATA files (can be text ".dat" or binary ".npy"): [output].psd freqs [THz], original periodogram, original log(periodogram) + [output].cospectrum (if any) + freqs [THz], full matrix cospectrum [output].resampled_psd freqs [THz], resampled periodogram, resampled log(periodogram) [output].cepstral @@ -307,11 +309,18 @@ def main(): binoutobj.j_logpsd = j.logpsd binoutobj.j_Nyquist_f_THz = j.Nyquist_f_THz binoutobj.j_PSD_FILTER_W_THz = psd_filter_w + if j.multicomponent: + binoutobj.j_cospectrum = j.cospectrum outfile = open(output + '.psd.dat', 'w') outarray = np.c_[j.freqs_THz, j.psd, j.fpsd, j.logpsd, j.flogpsd] outfile.write('freqs_THz psd fpsd logpsd flogpsd\n') np.savetxt(outfile, outarray) outfile.close() + if j.multicomponent: + outfile = open(output + '.cospectrum.dat', 'w') + outarray = np.c_[j.freqs_THz,j.cospectrum.transpose((2,0,1))] + np.savetxt(outfile, outarray) + outfile.close() # resample and plot if resample: diff --git a/thermocepstrum/md/mdsample.py b/thermocepstrum/md/mdsample.py index 2070802..11d67f2 100644 --- a/thermocepstrum/md/mdsample.py +++ b/thermocepstrum/md/mdsample.py @@ -262,11 +262,11 @@ def compute_kappa_multi(self, others, FILTER_WINDOW_WIDTH=None, method='trajecto ndf_chi = covarALL.shape[3]- len(other_spectrALL) # compute the sum over the last axis (x,y,z components): - cospectrum = covarALL.sum(axis=3) + self.cospectrum = covarALL.sum(axis=3) # compute the element 1/"(0,0) of the inverse" (aka the coefficient of thermal conductivity) # the diagonal elements of the inverse have very convenient statistical properties - multi_psd = (np.linalg.inv(cospectrum.transpose((2,0,1)))[:,0,0]**-1).real / ndf_chi + multi_psd = (np.linalg.inv(self.cospectrum.transpose((2,0,1)))[:,0,0]**-1).real / ndf_chi if normalize: multi_psd = multi_psd / np.trapz(multi_psd) / self.N / self.DT_FS diff --git a/thermocepstrum/utils/blocks.py b/thermocepstrum/utils/blocks.py new file mode 100755 index 0000000..fef175e --- /dev/null +++ b/thermocepstrum/utils/blocks.py @@ -0,0 +1,359 @@ +#!/usr/bin/env python + +import sys +import os +abs_path=os.path.abspath(sys.argv[0]) +tc_path = abs_path[:abs_path.rfind('/')] +tc_path = tc_path[:tc_path.rfind('/')] +sys.path.append(tc_path[:tc_path.rfind('/')]) +print tc_path + +import numpy as np +import scipy as sp +import scipy.stats +import matplotlib +matplotlib.use('Agg') +import matplotlib.pyplot as plt +from matplotlib.backends.backend_pdf import PdfPages +plt.rcParams['figure.figsize'] = (16, 9) +plt.style.reload_library() +plt.style.use(tc_path+'/grafici_belli.mplstyle') +plt.rc('text', usetex=True) +c = plt.rcParams['axes.prop_cycle'].by_key()['color'] +from matplotlib.ticker import MultipleLocator +import math +import os.path +import thermocepstrum as tc + +def main(): + usage="""usage: {} output N_currents N_processes DT_FS input1 input2 ... inputN + + N must be at least 2. + This utility computes some histograms and statistics of the outputs generated by the analysis program. + N_processes is the number of independent processes used, and N_currents is the number of currents in every random process. + DT_FS is the timestep in femtoseconds. + + Riccardo Bertossa (SISSA), 2018 + + """.format(sys.argv[0]) + + #number of elements of the periodogram used in making the big histogram + all_cut=1500 + + if len(sys.argv) < 7: + print usage + exit(-1) + + output=sys.argv[1] + M=int(sys.argv[2]) + L=int(sys.argv[3]) + dof=L-M+1 + print dof, ' degrees of freedom for the chi2 distribution' + ndata=len(sys.argv)-5 + DT_FS=float(sys.argv[4]) + ff=5 + + print "Number of inputs: {}\n reading...".format(ndata) + periodograms=[] + cospectrums=[] + cepstrals=[] + aic_Kmins=np.zeros(ndata) + kappas_Kmin=np.zeros(ndata) + kappa_scales=np.zeros(ndata) + if os.path.isfile(sys.argv[ff]+'.psd.npy'): + freqs=np.load(sys.argv[ff]+'.psd.npy')[0] + else: + freqs=np.loadtxt(sys.argv[ff]+'.psd.dat',usecols=(0,),unpack=True) + cont=0 + for fname in sys.argv[ff:]: + print fname + if os.path.isfile(fname+'.psd.npy'): + periodograms.append(np.load(fname+'.psd.npy')[3:5]) + else: + periodograms.append(np.loadtxt(fname+'.psd.dat',usecols=(3,4),unpack=True)) + if os.path.isfile(fname+'.cepstral.npy'): + cepstrals.append(np.load(fname+'.cepstral.npy')[4:6]) + else: + cepstrals.append(np.loadtxt(fname+'.cepstral.dat',usecols=(4,5),unpack=True)) + + if os.path.isfile(fname+'.cospectrum.npy'): + cospectrums.append(np.load(fname+'.cospectrum.npy')[1]/L) + + if len(cospectrums)==0: + cospectrums=None + + fka=open(fname+'.kappa_scale_aicKmin.dat') + kappa_scales[cont]=float(fka.readline()) + aic_Kmin=int(fka.readline()) + aic_Kmins[cont]=aic_Kmin + fka.close() + + kappas_Kmin[cont]=cepstrals[cont][0,aic_Kmin] + + + cont+=1 + + aic_KminM=np.mean(aic_Kmins) + aic_Kmin=int(aic_KminM) + print 'Reading done.' + + print 'Mean value of kappa_scale: {}'.format(np.mean(kappa_scales)) + print 'Mean value of minimum of AIC: {}'.format(aic_KminM) + + #resizing and creating a big numpy array. + for periodogram,cepstral in zip(periodograms,cepstrals): + periodogram.resize(periodograms[0].shape) + cepstral.resize(cepstrals[0].shape) + + cepstrals=np.array(cepstrals,copy=False) + periodograms=np.array(periodograms,copy=False) + + #calculate statistics over first axis + std_periodogram=np.std(periodograms,axis=0,ddof=1) + std_cepstral=np.std(cepstrals,axis=0,ddof=1) + mean_periodogram=np.mean(periodograms,axis=0) + mean_cospectrum=None + if cospectrums!=None: + mean_cospectrum=np.mean(cospectrums,axis=0) + mean_cepstral=np.mean(cepstrals,axis=0) + print mean_cepstral.shape + print mean_periodogram.shape + np.savetxt(output+'.mean_periodogram',np.c_[freqs,mean_periodogram[0],std_periodogram[0],mean_periodogram[1],std_periodogram[1]]) + np.savetxt(output+'.mean_cepstral',np.c_[mean_cepstral[0],std_cepstral[0],mean_cepstral[1],std_cepstral[1]]) + + + print 'Mean values and standard deviations done.' + + print 'Computing index of .40 psd power...' + psd_int=np.cumsum(mean_periodogram[0]) + psd_int=psd_int/psd_int[-1] + p95=0 + while psd_int[p95]<0.10: + p95=p95+1 + all_cut=p95 + + all_cut=100 + + #select only components that are significantly different from zero + selection_not_zero=[] + zero=mean_periodogram[0,0]/10 + for i in range(all_cut): + if mean_periodogram[0,i]>zero: + selection_not_zero.append(i) + print 'Number of components > {}: {}. Last is {}'.format(zero,len(selection_not_zero),selection_not_zero[-1]) +# print selection_not_zero + + print 'Index = {} , {} THz'.format(p95,freqs[p95]) + + print 'Some plots...' + #make some plots and histograms + + with PdfPages(output+"_all.pdf") as pdf: + plt.fill_between(freqs,mean_periodogram[0]-std_periodogram[0],mean_periodogram[0]+std_periodogram[0]) + plt.plot(freqs,mean_periodogram[0]) + plt.title('Original PSD') + pdf.savefig() + plt.close() + + class Psd: + psd=None + fpsd=None + freqs_THz=None + kappa_scale=None + cospectrum=None + DT_FS=None + def ffpsd(self,w): + WF=int(round(w/1000.*self.DT_FS*len(self.freqs_THz)*2.)) + print 'filtering: ',WF + ffpsd=tc.md.tools.runavefilter(self.fpsd, WF) + self.fpsd=ffpsd + try: + for i in range(self.cospectrum.shape[0]): + for j in range(self.cospectrum.shape[1]): + ffpsd=tc.md.tools.runavefilter(self.cospectrum[i,j], WF) + self.cospectrum[i,j]=ffpsd + except AttributeError: + pass + + + psd=Psd() + + psd.DT_FS=DT_FS + psd.kappa_scale=np.mean(kappa_scales)/DT_FS + psd.psd=periodograms[0,0,:] + psd.fpsd=mean_periodogram[0,:] + psd.freqs_THz=freqs + psd.cospectrum=mean_cospectrum + psd.ffpsd(0.2) + + plt_psd(psd,k_00=True) + pdf.savefig() + plt.close() + + #make histogram for component 0 and 1 of psd + + #compute means without i-th element + independent_mean=np.zeros((periodograms.shape[0],periodograms.shape[2])) + for i in range(periodograms.shape[0]): + all_but_ith=[x for x in range(periodograms.shape[0]) if x != i] + independent_mean[i,:]= np.mean(periodograms[all_but_ith,0,:],axis=0) + + plt.hist(kappas_Kmin) + plt.title('kappa(aic-Kmin)') + pdf.savefig() + plt.close() + + data1=periodograms[:,0,0]/independent_mean[:,0] + + ks__0=plt_hist_single_psd(data1,dof) + pdf.savefig() + plt.close() + + data2=periodograms[:,0,1]/independent_mean[:,1] + ks__1=plt_hist_single_psd(data2,dof*2) + pdf.savefig() + plt.close() + + #ks_1=sp.stats.kstest(data2*2*dof,sp.stats.chi2(2*dof).cdf) + + #make histogram for all components normalized + all_normalized=np.zeros(periodograms.shape[0]*(len(selection_not_zero))) + for i in range(periodograms.shape[0]): + #for idx,i in enumerate(selection_not_zero): + all_normalized[i*len(selection_not_zero):(i+1)*len(selection_not_zero)]=periodograms[i,0,selection_not_zero]/independent_mean[i,selection_not_zero] + + ks_all=plt_hist_single_psd(all_normalized,dof*2,nbins=100) + pdf.savefig() + plt.close() + +# np.savetxt(output+'.histogram_all',np.c_[(intervals[1:]+intervals[:-1])/2.0,histogram/np.sum(histogram)]) +# print 'Histogram bin width: {}'.format(intervals[1]-intervals[0]) + +# np.savetxt(output+'.kolmogorov_smirnov',[ks_0,ks_1,ks_all]) + print 'Statistical test results (psd(0), psd(1), psd(all but 0)): {}'.format([ks__0,ks__1,ks_all]) + + #make graphs of mean of theoretical and statistical error of the final result + plt.fill_between(np.arange(mean_cepstral.shape[1]),mean_cepstral[0]-std_cepstral[0],mean_cepstral[0]+std_cepstral[0]) + plt.plot(np.arange(mean_cepstral.shape[1]),mean_cepstral[0]-mean_cepstral[1]) + plt.plot(np.arange(mean_cepstral.shape[1]),mean_cepstral[0]+mean_cepstral[1]) + plt.plot(np.arange(mean_cepstral.shape[1]),mean_cepstral[0]) + plt.title('Convergence of cepstral result with theoretical and statistical errors') + + plt.xlim([0,10*aic_Kmin]) + max_y=np.amax((mean_cepstral[0]+std_cepstral[0])[aic_Kmin:3*aic_Kmin]) + min_y=np.amin((mean_cepstral[0]-std_cepstral[0])[aic_Kmin:3*aic_Kmin]) + plt.ylim([min_y*0.8,max_y*1.2]) + + + pdf.savefig() + plt.close() + +def plt_hist_single_psd(data1,dof,nbins=None): + + fig=plt.figure(figsize=(3.8,2.3)) + if nbins != None: + h,i,p=plt.hist(data1*dof,bins=nbins,normed=True) + else: + h,i,p=plt.hist(data1*dof,normed=True) + + xmax=i[-1] + ymax=np.max(h)*1.2 + plt.xlim([0.0,xmax]) + plt.ylim([0.0,ymax]) + + x=np.linspace(0.0,xmax,1000) + + plt.plot(x,sp.stats.chi2.pdf(x,dof),ls=':',label='$\chi^2_{{{}}}$'.format(dof)) + + plt.xlabel('Normalized values') + plt.ylabel('Probability') + plt.legend() + + dx1,dx2=n_tick_in_range(0,xmax,5) + dy1,dy2=n_tick_in_range(0,ymax,5) + + plt.axes().xaxis.set_major_locator(MultipleLocator(dx1)) + plt.axes().xaxis.set_minor_locator(MultipleLocator(dx2)) + plt.axes().yaxis.set_major_locator(MultipleLocator(dy1)) + plt.axes().yaxis.set_minor_locator(MultipleLocator(dy2)) + ks_0=sp.stats.kstest(data1*dof,sp.stats.chi2(dof).cdf) + + text='KS-value=${}$\nP=${}$'.format(as_si(ks_0[0],1),as_si(ks_0[1],1)) + plt.text(.5,.6,text,transform=fig.transFigure) + + return ks_0 + + +def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False): + + if f_THz_max==None: + idx_max=index_cumsum(jf.psd,0.95) + f_THz_max=jf.freqs_THz[idx_max] + + if k_SI_max==None: + k_SI_max=np.max(jf.fpsd[:int(jf.freqs_THz.shape[0]*f_THz_max/jf.freqs_THz[-1])]*jf.kappa_scale*.5) *1.3 + if k_00 : + try: + k_SI_max2=np.max(np.real(jf.cospectrum[0,0][:int(jf.freqs_THz.shape[0]*f_THz_max/jf.freqs_THz[-1])])*jf.kappa_scale*.5) + if k_SI_max < k_SI_max2: + k_SI_max = k_SI_max2 + except AttributeError: + pass + + + + plt.figure(figsize=(3.8,2.3)) + plt.plot(jf.freqs_THz,jf.psd*jf.kappa_scale*.5,lw=0.2,c='0.8') + plt.plot(jf.freqs_THz,jf.fpsd*jf.kappa_scale*.5,c=c[0]) + if j2 != None: + plt.axvline(x=j2.Nyquist_f_THz,ls='--', c='k', dashes=(1.4,0.6), zorder=3) + if j2pl != None: + plt.plot(j2pl.freqs_THz,j2pl.dct.psd*j2pl.kappa_scale*.5,c=c[1]) + try: + plt.plot(jf.freqs_THz,np.real(jf.cospectrum[0,0])*jf.kappa_scale*.5,c=c[2],lw=0.2,) + except AttributeError: + pass + + plt.ylim([0,k_SI_max]) + plt.xlim([0,f_THz_max]) + plt.xlabel('$\omega/2\pi$ (THz)') + plt.ylabel('${}^{\ell}\hat{\underline{S}}_{\,k}$ (W/mK)') + + dx1,dx2=n_tick_in_range(0,f_THz_max,5) + dy1,dy2=n_tick_in_range(0,k_SI_max,5) + + plt.axes().xaxis.set_major_locator(MultipleLocator(dx1)) + plt.axes().xaxis.set_minor_locator(MultipleLocator(dx2)) + plt.axes().yaxis.set_major_locator(MultipleLocator(dy1)) + plt.axes().yaxis.set_minor_locator(MultipleLocator(dy2)) + +def n_tick_in_range(beg,end,n): + size=end-beg + n_cifre=math.floor(math.log(size/n,10.0)) + delta=math.ceil((size/n)/10**n_cifre)*10**n_cifre + return delta,delta/2 + +def index_cumsum(arr,p): + if (p>1 or p<0): + raise ValueError('p must be between 0 and 1') + arr_int=np.cumsum(arr) + arr_int=arr_int/arr_int[-1] + idx=0 + while arr_int[idx] Date: Mon, 15 Oct 2018 19:47:12 +0200 Subject: [PATCH 03/19] utils/blocks.py : modified some plots --- thermocepstrum/utils/blocks.py | 28 ++++++++++++++++++++-------- 1 file changed, 20 insertions(+), 8 deletions(-) diff --git a/thermocepstrum/utils/blocks.py b/thermocepstrum/utils/blocks.py index fef175e..28b88e5 100755 --- a/thermocepstrum/utils/blocks.py +++ b/thermocepstrum/utils/blocks.py @@ -26,7 +26,7 @@ import thermocepstrum as tc def main(): - usage="""usage: {} output N_currents N_processes DT_FS input1 input2 ... inputN + usage="""usage: {} output N_currents N_processes DT_FS max_THz_psd input1 input2 ... inputN N must be at least 2. This utility computes some histograms and statistics of the outputs generated by the analysis program. @@ -40,7 +40,7 @@ def main(): #number of elements of the periodogram used in making the big histogram all_cut=1500 - if len(sys.argv) < 7: + if len(sys.argv) < 8: print usage exit(-1) @@ -49,9 +49,10 @@ def main(): L=int(sys.argv[3]) dof=L-M+1 print dof, ' degrees of freedom for the chi2 distribution' - ndata=len(sys.argv)-5 DT_FS=float(sys.argv[4]) - ff=5 + max_THz=float(sys.argv[5]) + ff=6 + ndata=len(sys.argv)-ff print "Number of inputs: {}\n reading...".format(ndata) periodograms=[] @@ -186,10 +187,21 @@ def ffpsd(self,w): psd.cospectrum=mean_cospectrum psd.ffpsd(0.2) - plt_psd(psd,k_00=True) + plt_psd(psd,k_00=True,f_THz_max=max_THz) pdf.savefig() plt.close() - + + plt.xlim([0,max_THz]) + + plt.plot(psd.freqs_THz,np.real(psd.cospectrum[1,0])) + pdf.savefig() + plt.close() + plt.xlim([0,max_THz]) + + plt.plot(psd.freqs_THz,psd.cospectrum[1,1]) + pdf.savefig() + plt.close() + #make histogram for component 0 and 1 of psd #compute means without i-th element @@ -310,14 +322,14 @@ def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False): if j2pl != None: plt.plot(j2pl.freqs_THz,j2pl.dct.psd*j2pl.kappa_scale*.5,c=c[1]) try: - plt.plot(jf.freqs_THz,np.real(jf.cospectrum[0,0])*jf.kappa_scale*.5,c=c[2],lw=0.2,) + plt.plot(jf.freqs_THz,np.real(jf.cospectrum[0,0])*jf.kappa_scale*.5,c=c[2],lw=1.0,) except AttributeError: pass plt.ylim([0,k_SI_max]) plt.xlim([0,f_THz_max]) plt.xlabel('$\omega/2\pi$ (THz)') - plt.ylabel('${}^{\ell}\hat{\underline{S}}_{\,k}$ (W/mK)') + plt.ylabel('$^{\ell M}\widehat{S}\'_{\,k}$ (W/mK)') dx1,dx2=n_tick_in_range(0,f_THz_max,5) dy1,dy2=n_tick_in_range(0,k_SI_max,5) From c90746fe82730bb4cb467917bdedf83c96b22b3c Mon Sep 17 00:00:00 2001 From: Loris Ercole Date: Mon, 15 Oct 2018 20:11:07 +0200 Subject: [PATCH 04/19] Added options in analysis.py and blocks.py to have a better control over the plots. analysis.py : cleaned plot code --- thermocepstrum/analysis.py | 154 +++++++++++++++++++++------------ thermocepstrum/utils/blocks.py | 70 +++++++++++---- 2 files changed, 153 insertions(+), 71 deletions(-) diff --git a/thermocepstrum/analysis.py b/thermocepstrum/analysis.py index 11edbd8..f16a92b 100755 --- a/thermocepstrum/analysis.py +++ b/thermocepstrum/analysis.py @@ -116,9 +116,14 @@ def main(): parser.add_argument( '-j', '--add-currents', type=str, default=[], action='append', help='additional current for multi-component fluids' ) parser.add_argument( '-w', '--psd-filterw', type=float, help='plot - periodogram - filter window width (THz)' ) - parser.add_argument('--plot-conv-max-pstar',type=int,help='max number of P* in the kappa(P*) plot') + parser.add_argument('--plot-conv-max-pstar',type=int,help='max number of P* in the kappa(P*) plot (x)') + parser.add_argument('--plot-conv-max-kappa',type=float,help='max kappa in the kappa(P*) plot (y)') parser.add_argument('--plot-conv-pstar-tick-interval',type=int,help='tick interval on the x-axis for the kappa(P*) plot') - parser.add_argument('--plot-psd-max-THz',type=float, help='max frequency in THz for the psd plot') + parser.add_argument('--plot-conv-kappa-tick-interval',type=float,help='tick interval on the y-axis for the kappa(P*) plot') + parser.add_argument('--plot-psd-max-THz',type=float, help='max frequency in THz for the psd plot (x)') + parser.add_argument('--plot-psd-max-kappa',type=float, help='max kappa in W/mK for the psd plot (y)') + parser.add_argument('--plot-psd-THz-tick-interval',type=float, help='tick interval on the x-axis for the psd plot') + parser.add_argument('--plot-psd-kappa-tick-interval',type=float, help='tick interval on the y-axis for the psd plot') args = parser.parse_args() inputfile = args.inputfile @@ -355,10 +360,18 @@ def main(): else: jf = j - plt_psd(j,jf) + plt_psd(j, jf,\ + f_THz_max=args.plot_psd_max_THz,\ + k_SI_max=args.plot_psd_max_kappa,\ + k_tick=args.plot_psd_kappa_tick_interval,\ + f_tick=args.plot_psd_THz_tick_interval) pdf.savefig() plt.close() - plt_psd(jf) + plt_psd(jf,\ + f_THz_max=args.plot_psd_max_THz,\ + k_SI_max=args.plot_psd_max_kappa,\ + k_tick=args.plot_psd_kappa_tick_interval,\ + f_tick=args.plot_psd_THz_tick_interval) pdf.savefig() plt.close() @@ -374,7 +387,11 @@ def main(): binoutobj.TEMPERATURE = temperature binoutobj.VOLUME = volume - plt_psd(jf,jf,jf) + plt_psd(jf, jf, jf,\ + f_THz_max=args.plot_psd_max_THz,\ + k_SI_max=args.plot_psd_max_kappa,\ + k_tick=args.plot_psd_kappa_tick_interval,\ + f_tick=args.plot_psd_THz_tick_interval) pdf.savefig() plt.close() @@ -397,7 +414,11 @@ def main(): # ax = jf.plot_kappa_Pstar() # ax.set_xlim([0, 10*jf.dct.aic_Kmin]) - plt_cepstral_conv(jf,pstar_max=args.plot_conv_max_pstar,pstar_tick=args.plot_conv_pstar_tick_interval) + plt_cepstral_conv(jf,\ + pstar_max=args.plot_conv_max_pstar,\ + pstar_tick=args.plot_conv_pstar_tick_interval,\ + k_SI_max=args.plot_conv_max_kappa,\ + kappa_tick=args.plot_conv_kappa_tick_interval) pdf.savefig() plt.close() @@ -458,85 +479,109 @@ def main(): ################################# -def plt_cepstral_conv(jf,pstar_max=None, k_SI_max=None,pstar_tick=None): - if pstar_max==None: - pstar_max=(jf.dct.aic_Kmin+1)*2.5 - if k_SI_max==None: - k_SI_max=jf.dct.tau[jf.dct.aic_Kmin]*jf.kappa_scale +def plt_cepstral_conv(jf, pstar_max=None, k_SI_max=None, pstar_tick=None, kappa_tick=None): + if pstar_max is None: + pstar_max = (jf.dct.aic_Kmin+1)*2.5 + if k_SI_max is None: + k_SI_max = jf.dct.tau[jf.dct.aic_Kmin]*jf.kappa_scale - f, (ax2) = plt.subplots(1,1,figsize=(3.8,2.3)) + f, (ax2) = plt.subplots(1, 1, figsize=(3.8,2.3)) ax2.axvline(x=jf.dct.aic_Kmin+1, ls='--', c='k', dashes=(1.4,0.6), zorder=-3) ax2.fill_between(np.arange(jf.dct.logtau.shape[0])+1,\ - (jf.dct.tau-jf.dct.tau_THEORY_std)*jf.kappa_scale*.5,\ - (jf.dct.tau+jf.dct.tau_THEORY_std)*jf.kappa_scale*.5,alpha=.3,color=c[4],zorder=-3)#'#3c8da8') - ax2.plot(np.arange(jf.dct.logtau.shape[0])+1, jf.dct.tau*jf.kappa_scale*.5,\ - label=r'Cepstral method',marker='o',c=c[4],zorder=-3)#'#3c8da8') + (jf.dct.tau-jf.dct.tau_THEORY_std)*jf.kappa_scale*0.5,\ + (jf.dct.tau+jf.dct.tau_THEORY_std)*jf.kappa_scale*0.5,\ + alpha=.3, color=c[4], zorder=-3) + ax2.plot(np.arange(jf.dct.logtau.shape[0])+1, jf.dct.tau*jf.kappa_scale*0.5,\ + label=r'Cepstral method', marker='o', c=c[4], zorder=-3) ax2.set_xlabel(r'$P^*$') ax2.set_ylabel(r'$\kappa$ (W/mK)') - ax2.set_xlim([0,pstar_max]) + ax2.set_xlim([0, pstar_max]) ax2.set_ylim([0, k_SI_max]) # ax2.grid() ax2.legend() - if pstar_tick==None: - dx1,dx2=n_tick_in_range(0,pstar_max,5) + if pstar_tick is None: + dx1, dx2 = n_tick_in_range(0, pstar_max, 5) else: - dx1=pstar_tick - dx2=dx1/2 - - dy1,dy2=n_tick_in_range(0,k_SI_max,5) - + dx1 = pstar_tick + dx2 = dx1/2 + if kappa_tick is None: + dy1, dy2 = n_tick_in_range(0, k_SI_max, 5) + else: + dy1 = kappa_tick + dy2 = dy1/2 ax2.xaxis.set_major_locator(MultipleLocator(dx1)) ax2.xaxis.set_minor_locator(MultipleLocator(dx2)) ax2.yaxis.set_major_locator(MultipleLocator(dy1)) ax2.yaxis.set_minor_locator(MultipleLocator(dy2)) -def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None): - if f_THz_max==None: - idx_max=index_cumsum(jf.psd,0.95) - f_THz_max=jf.freqs_THz[idx_max] - - if k_SI_max==None: - k_SI_max=np.max(jf.fpsd[:int(jf.freqs_THz.shape[0]*f_THz_max/jf.freqs_THz[-1])]*jf.kappa_scale*.5) *1.3 +def plt_psd(jf, j2=None, j2pl=None, f_THz_max=None, k_SI_max=None, k_tick=None, f_tick=None): + if f_THz_max is None: + idx_max = index_cumsum(j is psd,0.95) + f_THz_max = jf.freqs_THz[idx_max] + else: + maxT = jf.freqs_THz[-1] + if j2 is not None: + if j2.freqs_THz[-1] > maxT: + maxT=j2.freqs_THz[-1] + if j2pl is not None: + if j2pl.freqs_THz[-1] > maxT: + maxT=j2pl.freqs_THz[-1] + if maxT< f_THz_max: + f_THz_max=maxT + + if k_SI_max is None: + k_SI_max = np.max(jf.fpsd[:int(jf.freqs_THz.shape[0]*f_THz_max/jf.freqs_THz[-1])]*jf.kappa_scale*0.5) *1.3 plt.figure(figsize=(3.8,2.3)) - plt.plot(jf.freqs_THz,jf.psd*jf.kappa_scale*.5,lw=0.2,c='0.8') - plt.plot(jf.freqs_THz,jf.fpsd*jf.kappa_scale*.5,c=c[0]) - if j2 != None: - plt.axvline(x=j2.Nyquist_f_THz,ls='--', c='k', dashes=(1.4,0.6), zorder=3) - if j2pl != None: - plt.plot(j2pl.freqs_THz,j2pl.dct.psd*j2pl.kappa_scale*.5,c=c[1]) - - plt.ylim([0,k_SI_max]) - plt.xlim([0,f_THz_max]) + plt.plot(jf.freqs_THz, jf.psd*jf.kappa_scale*0.5, lw=0.2, c='0.8', zorder=0) + plt.plot(jf.freqs_THz, jf.fpsd*jf.kappa_scale*0.5, c=c[0], zorder=2) + if j2 is not None: + plt.axvline(x=j2.Nyquist_f_THz, ls='--', c='k', dashes=(1.4,0.6), zorder=3) + if j2pl is not None: + plt.plot(j2pl.freqs_THz, j2pl.dct.psd*j2pl.kappa_scale*0.5, c=c[1], zorder=1) + + plt.ylim([0, k_SI_max]) + plt.xlim([0, f_THz_max]) plt.xlabel(r'$\omega/2\pi$ (THz)') plt.ylabel(r'${}^{\ell}\hat{S}_{\,k}$ (W/mK)') - dx1,dx2=n_tick_in_range(0,f_THz_max,5) - dy1,dy2=n_tick_in_range(0,k_SI_max,5) + if f_tick is None: + dx1, dx2 = n_tick_in_range(0, f_THz_max, 5) + else: + dx1 = f_tick + dx2 = dx1/2 + if k_tick is None: + dy1, dy2 = n_tick_in_range(0, k_SI_max, 5) + else: + dy1 = k_tick + dy2 = dy1/2 plt.axes().xaxis.set_major_locator(MultipleLocator(dx1)) plt.axes().xaxis.set_minor_locator(MultipleLocator(dx2)) plt.axes().yaxis.set_major_locator(MultipleLocator(dy1)) plt.axes().yaxis.set_minor_locator(MultipleLocator(dy2)) -def n_tick_in_range(beg,end,n): - size=end-beg - n_cifre=math.floor(math.log(size/n,10.0)) - delta=math.ceil((size/n)/10**n_cifre)*10**n_cifre - return delta,delta/2 -def index_cumsum(arr,p): - if (p>1 or p<0): +def n_tick_in_range(beg, end, n): + size = end-beg + n_cifre = math.floor(math.log(size/n,10.0)) + delta = math.ceil((size/n)/10**n_cifre)*10**n_cifre + return delta, delta/2 + + +def index_cumsum(arr, p): + if (p > 1 or p < 0): raise ValueError('p must be between 0 and 1') - arr_int=np.cumsum(arr) - arr_int=arr_int/arr_int[-1] - idx=0 - while arr_int[idx] Date: Mon, 15 Oct 2018 20:49:33 +0200 Subject: [PATCH 05/19] analysis.py : added some plots when multicomponent code is used mdsample.py : fcospectrum introduced -- still needs two minor edits compute_kappa_multi and filter_psd --- thermocepstrum/analysis.py | 67 ++++++++++++++++++++++++++++++++--- thermocepstrum/md/mdsample.py | 12 ++++++- 2 files changed, 73 insertions(+), 6 deletions(-) diff --git a/thermocepstrum/analysis.py b/thermocepstrum/analysis.py index f16a92b..157de03 100755 --- a/thermocepstrum/analysis.py +++ b/thermocepstrum/analysis.py @@ -316,6 +316,7 @@ def main(): binoutobj.j_PSD_FILTER_W_THz = psd_filter_w if j.multicomponent: binoutobj.j_cospectrum = j.cospectrum + binoutobj.j_fcospectrum = j.fcospectrum outfile = open(output + '.psd.dat', 'w') outarray = np.c_[j.freqs_THz, j.psd, j.fpsd, j.logpsd, j.flogpsd] outfile.write('freqs_THz psd fpsd logpsd flogpsd\n') @@ -323,7 +324,11 @@ def main(): outfile.close() if j.multicomponent: outfile = open(output + '.cospectrum.dat', 'w') - outarray = np.c_[j.freqs_THz,j.cospectrum.transpose((2,0,1))] + outarray = np.c_[j.freqs_THz,j.cospectrum.reshape((j.cospectrum.shape[0]*j.cospectrum.shape[1],j.cospectrum.shape[2])).transpose()] + np.savetxt(outfile, outarray) + outfile.close() + outfile = open(output + '.cospectrum.filt.dat', 'w') + outarray = np.c_[j.freqs_THz,j.fcospectrum.reshape((j.fcospectrum.shape[0]*j.fcospectrum.shape[1],j.fcospectrum.shape[2])).transpose()] np.savetxt(outfile, outarray) outfile.close() @@ -394,7 +399,15 @@ def main(): f_tick=args.plot_psd_THz_tick_interval) pdf.savefig() plt.close() - + + try: + for idx1 in range(ncurrents): + for idx2 in range(idx1, ncurrents): + plt_other(j, idx1, idx2) + pdf.savefig() + plt.close() + except: + pass # plot cepstral coefficients ax = jf.plot_ck() @@ -516,9 +529,49 @@ def plt_cepstral_conv(jf, pstar_max=None, k_SI_max=None, pstar_tick=None, kappa_ ax2.yaxis.set_minor_locator(MultipleLocator(dy2)) +def plt_other(jf, idx1, idx2, f_THz_max=None, k_SI_max=None, k_SI_min=None, k_tick=None, f_tick=None): + if f_THz_max is None: + idx_max = index_cumsum(np.abs(jf.fcospectrum[idx1][idx2]), 0.95) + f_THz_max = jf.freqs_THz[idx_max] + else: + maxT = jf.freqs_THz[-1] + if (maxT < f_THz_max): + f_THz_max = maxT + + if k_SI_max is None: + k_SI_max = np.max(np.abs(jf.fcospectrum[idx1][idx2])[:int(jf.freqs_THz.shape[0]*f_THz_max/jf.freqs_THz[-1])]*jf.kappa_scale*0.5)*1.3 + if k_SI_min is None: + k_SI_min = -k_SI_max + + plt.figure(figsize=(3.8,2.3)) + plt.plot(jf.freqs_THz, np.real(jf.fcospectrum[idx1][idx2])*jf.kappa_scale*0.5, c=c[3], lw=1.0, zorder=1) + plt.plot(jf.freqs_THz, np.imag(jf.fcospectrum[idx1][idx2])*jf.kappa_scale*0.5, c=c[2], lw=1.0, zorder=1) + + plt.ylim([k_SI_min, k_SI_max]) + plt.xlim([0, f_THz_max]) + plt.xlabel(r'$\omega/2\pi$ (THz)') + plt.ylabel(r'$S^{{{}{}}}$'.format(idx1, idx2)) + + if f_tick is None: + dx1, dx2 = n_tick_in_range(0, f_THz_max, 5) + else: + dx1 = f_tick + dx2 = dx1/2 + if k_tick is None: + dy1, dy2 = n_tick_in_range(0, k_SI_max, 5) + else: + dy1 = k_tick + dy2 = dy1/2 + + plt.axes().xaxis.set_major_locator(MultipleLocator(dx1)) + plt.axes().xaxis.set_minor_locator(MultipleLocator(dx2)) + plt.axes().yaxis.set_major_locator(MultipleLocator(dy1)) + plt.axes().yaxis.set_minor_locator(MultipleLocator(dy2)) + + def plt_psd(jf, j2=None, j2pl=None, f_THz_max=None, k_SI_max=None, k_tick=None, f_tick=None): if f_THz_max is None: - idx_max = index_cumsum(j is psd,0.95) + idx_max = index_cumsum(jf.psd, 0.95) f_THz_max = jf.freqs_THz[idx_max] else: maxT = jf.freqs_THz[-1] @@ -532,7 +585,7 @@ def plt_psd(jf, j2=None, j2pl=None, f_THz_max=None, k_SI_max=None, k_tick=None, f_THz_max=maxT if k_SI_max is None: - k_SI_max = np.max(jf.fpsd[:int(jf.freqs_THz.shape[0]*f_THz_max/jf.freqs_THz[-1])]*jf.kappa_scale*0.5) *1.3 + k_SI_max = np.max(jf.fpsd[:int(jf.freqs_THz.shape[0]*f_THz_max/jf.freqs_THz[-1])]*jf.kappa_scale*0.5)*1.3 plt.figure(figsize=(3.8,2.3)) plt.plot(jf.freqs_THz, jf.psd*jf.kappa_scale*0.5, lw=0.2, c='0.8', zorder=0) @@ -541,11 +594,15 @@ def plt_psd(jf, j2=None, j2pl=None, f_THz_max=None, k_SI_max=None, k_tick=None, plt.axvline(x=j2.Nyquist_f_THz, ls='--', c='k', dashes=(1.4,0.6), zorder=3) if j2pl is not None: plt.plot(j2pl.freqs_THz, j2pl.dct.psd*j2pl.kappa_scale*0.5, c=c[1], zorder=1) + try: + plt.plot(jf.freqs_THz, np.real(jf.fcospectrum[0][0])*jf.kappa_scale*0.5, c=c[3], lw=1.0, zorder=1) + except: + pass plt.ylim([0, k_SI_max]) plt.xlim([0, f_THz_max]) plt.xlabel(r'$\omega/2\pi$ (THz)') - plt.ylabel(r'${}^{\ell}\hat{S}_{\,k}$ (W/mK)') + plt.ylabel(r'${}^{\ell}\hat{\underline{S}}_{\,k}$ (W/mK)') if f_tick is None: dx1, dx2 = n_tick_in_range(0, f_THz_max, 5) diff --git a/thermocepstrum/md/mdsample.py b/thermocepstrum/md/mdsample.py index 11d67f2..a6b225f 100644 --- a/thermocepstrum/md/mdsample.py +++ b/thermocepstrum/md/mdsample.py @@ -262,6 +262,7 @@ def compute_kappa_multi(self, others, FILTER_WINDOW_WIDTH=None, method='trajecto ndf_chi = covarALL.shape[3]- len(other_spectrALL) # compute the sum over the last axis (x,y,z components): + self.L = covarALL.shape[3] ## isn't is == to N_CURRENTS? self.cospectrum = covarALL.sum(axis=3) # compute the element 1/"(0,0) of the inverse" (aka the coefficient of thermal conductivity) @@ -281,7 +282,6 @@ def compute_kappa_multi(self, others, FILTER_WINDOW_WIDTH=None, method='trajecto #multi_mdsample.cospectrum = cospectrum #return multi_mdsample - self.ndf_chi = ndf_chi self.psd = multi_psd self.logpsd = np.log(self.psd) @@ -342,6 +342,16 @@ def filter_psd(self, FILTER_WINDOW_WIDTH=None, window_type='rectangular', logpsd raise ValueError('Filter window width not defined.') if (window_type == 'rectangular'): self.fpsd = runavefilter(self.psd, self.FILTER_WF) + try: ## THIS IS HORRIBLE -- find another method to check its definition + self.fcospectrum = [] + for i in xrange(self.cospectrum.shape[0]): + self.fcospectrum.append([]) + for j in xrange(self.cospectrum.shape[1]): + ffpsd = runavefilter(self.cospectrum[i,j], self.FILTER_WF) + self.fcospectrum[i].append(ffpsd/self.L) + self.fcospectrum = np.asarray(self.fcospectrum) + except AttributeError: + pass if logpsd_filter_type == 1: self.flogpsd = runavefilter(self.logpsd, self.FILTER_WF) else: From cddacef412eee4c8fc41edc47ef706b9cc837729 Mon Sep 17 00:00:00 2001 From: Loris Ercole Date: Mon, 15 Oct 2018 21:27:18 +0200 Subject: [PATCH 06/19] Split time series option in analysis.py analysis.py : the --split option splits the input timeseries in m parts to obtain a timeseries with more independent processes mdsample.py : compute_psd detects if multi_component and calls compute_kappa_multi instead. --- thermocepstrum/analysis.py | 28 ++++++++++++++++++++++++++-- thermocepstrum/heatcurrent.py | 2 +- thermocepstrum/md/mdsample.py | 5 +++++ 3 files changed, 32 insertions(+), 3 deletions(-) diff --git a/thermocepstrum/analysis.py b/thermocepstrum/analysis.py index 157de03..6cc96c5 100755 --- a/thermocepstrum/analysis.py +++ b/thermocepstrum/analysis.py @@ -99,6 +99,7 @@ def main(): parser.add_argument( '--cindex', nargs='*', type=int, help='Column indexes of the heatflux to read (0,1,2,...)' ) parser.add_argument( '--sindex', nargs='*', type=int, help='Column indexes of the heatflux to substract from the flux read with --cindex (3,4,5,...)' ) parser.add_argument( '--run-keyword', type=str, help='Keyword that identifies the run to be read (only for "lammps" format)' ) + parser.add_argument('--split', type=int, default=1, help='Build a time series with n*m independent processes (n is the number of processes of the original timeseries, m is the number provided with --split). The length of the new time series will be [original length]/m.') parser.add_argument( '-o', '--output', type=str, default='output', help='prefix of the output files' ) parser.add_argument( '-O', '--bin-output', action='store_true', help='save also binary files' ) @@ -135,6 +136,7 @@ def main(): jindex = args.cindex sindex = args.sindex run_keyword = args.run_keyword + NSPLIT = args.split output = args.output binout = args.bin_output @@ -172,11 +174,13 @@ def main(): else: raise ValueError('resampling: you should specify either TSKIP or FSTAR') elif (TSKIP is not None): - raise ValueError('Use flag -r to resample. TSKIP will be ignored.') + raise ValueError('Use flag -r to resample. TSKIP will be ignored') elif (FSTAR is not None): - raise ValueError('Use flag -r to resample. FSTAR will be ignored.') + raise ValueError('Use flag -r to resample. FSTAR will be ignored') if (corr_factor <= 0.): raise ValueError('the correction factor must be positive') + if (NSPLIT < 1): + raise ValueError('The number of splits must be a positive number') ncurrents = len(j2_keys) + 1 @@ -210,6 +214,26 @@ def main(): else: raise NotImplemented('input format not implemented.') +<<<<<<< a9205c6c78ad3be789f8983d335e022721ad0602 + if (NSPLIT > 1): + print 'Splitting input data time series into {:d} segments...'.format(NSPLIT) + data_size = jdata[selected_keys[0]].shape[0] + n_proc = 1 + try: ## HORRIBLE + n_proc = jdata[selected_keys[0]].shape[1] + except: + pass + rm = data_size%NSPLIT + steps_start = data_size - rm + steps_end = data_size/NSPLIT + if (steps_end%2 == 1): + steps_end = steps_end - 1 + for key, value in jdata.iteritems(): + if key != 'Temp': + newdata = value[:steps_start].reshape((NSPLIT,data_size/NSPLIT,n_proc)).transpose((1,0,2)).reshape((data_size/NSPLIT,NSPLIT*n_proc)) + jdata[key] = newdata[:steps_end] + print 'New shape of input data: ', jdata[selected_keys[0]].shape + if NSTEPS==0: NSTEPS=jdata[jdata.keys()[0]].shape[0] diff --git a/thermocepstrum/heatcurrent.py b/thermocepstrum/heatcurrent.py index 86de5cc..a68483b 100644 --- a/thermocepstrum/heatcurrent.py +++ b/thermocepstrum/heatcurrent.py @@ -41,7 +41,7 @@ def __init__(self, j, units, DT_FS, TEMPERATURE, VOLUME, PSD_FILTER_W=None, freq elif (len(j.shape) <= 2): self.multicomponent = False else: - raise ValueError("Shape of j not valid.") + raise ValueError("Shape of j {} not valid.".format(j.shape)) if self.multicomponent: print "Using multicomponent code." diff --git a/thermocepstrum/md/mdsample.py b/thermocepstrum/md/mdsample.py index a6b225f..5f419c7 100644 --- a/thermocepstrum/md/mdsample.py +++ b/thermocepstrum/md/mdsample.py @@ -296,6 +296,11 @@ def compute_psd(self, FILTER_WINDOW_WIDTH=None, method='trajectory', DT_FS=None, """Computes the periodogram from the trajectory or the spectrum. If a FILTER_WINDOW_WIDTH is known or given, the psd is also filtered. The PSD is multiplied by DT_FS at the end.""" + if self.multicomponent: + if self.otherMD is None: + raise ValueError('self.otherMD cannot be None (wrong/missing initialization?)') + self.compute_kappa_multi(self.otherMD, FILTER_WINDOW_WIDTH, method, DT_FS, average_components, normalize) + return if DT_FS is not None: self.DT_FS = DT_FS if (method == 'trajectory'): From bdfa83608fee3c67df7353673c7fd7a4617b4291 Mon Sep 17 00:00:00 2001 From: Loris Ercole Date: Tue, 16 Oct 2018 17:19:24 +0200 Subject: [PATCH 07/19] Updated units in analysis.py --- thermocepstrum/analysis.py | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/thermocepstrum/analysis.py b/thermocepstrum/analysis.py index 6cc96c5..d1be9b9 100755 --- a/thermocepstrum/analysis.py +++ b/thermocepstrum/analysis.py @@ -106,7 +106,7 @@ def main(): parser.add_argument( '-V', '--volume', type=float, help='Volume of the cell (Angstrom). If not set it will be read from structure file or inputfile.' ) parser.add_argument( '--structure', type=str, help='LAMMPS data file containing the structure. Read to get Volume.' ) - parser.add_argument( '-u', '--units', type=str, default='metal', choices=['metal', 'real'], help='LAMMPS units (default: metal)' ) + parser.add_argument( '-u', '--units', type=str, default='metal', choices=['metal', 'real', 'qepw', 'gpumd', 'dlpoly'], help='LAMMPS units (default: metal)' ) parser.add_argument( '-T', '--temperature', type=float, help='average Temperature (K). If not set it will be read from file' ) parser.add_argument( '-r', '--resample', action='store_true', help='resample the time series (you should define --TSKIP or --FSTAR' ) @@ -159,8 +159,6 @@ def main(): raise ValueError('timestep must be positive') if (NSTEPS < 0): raise ValueError('nsteps must be positive') - if ((units != 'real') and (units != 'metal')): - raise ValueError('units must be metal or real') if temperature is not None: if (temperature <= 0.): raise ValueError('temperature must be positive') @@ -214,7 +212,6 @@ def main(): else: raise NotImplemented('input format not implemented.') -<<<<<<< a9205c6c78ad3be789f8983d335e022721ad0602 if (NSPLIT > 1): print 'Splitting input data time series into {:d} segments...'.format(NSPLIT) data_size = jdata[selected_keys[0]].shape[0] @@ -626,7 +623,7 @@ def plt_psd(jf, j2=None, j2pl=None, f_THz_max=None, k_SI_max=None, k_tick=None, plt.ylim([0, k_SI_max]) plt.xlim([0, f_THz_max]) plt.xlabel(r'$\omega/2\pi$ (THz)') - plt.ylabel(r'${}^{\ell}\hat{\underline{S}}_{\,k}$ (W/mK)') + plt.ylabel(r'${}^{\ell}\hat{S}_{\,k}$ (W/mK)') if f_tick is None: dx1, dx2 = n_tick_in_range(0, f_THz_max, 5) From cddec2ae5f05078507c5aeb9826d204a71735a94 Mon Sep 17 00:00:00 2001 From: Riccardo Bertossa Date: Sat, 13 Oct 2018 12:21:36 +0200 Subject: [PATCH 08/19] Two new options to analysis.py - no-text-output - old binary output format --- thermocepstrum/analysis.py | 102 ++++++++++++++++++++++++------------- 1 file changed, 68 insertions(+), 34 deletions(-) diff --git a/thermocepstrum/analysis.py b/thermocepstrum/analysis.py index d1be9b9..9080f13 100755 --- a/thermocepstrum/analysis.py +++ b/thermocepstrum/analysis.py @@ -31,7 +31,6 @@ import thermocepstrum as tc -plt.style.use(tc_path+'/grafici_belli.mplstyle') import math def main(): @@ -99,15 +98,17 @@ def main(): parser.add_argument( '--cindex', nargs='*', type=int, help='Column indexes of the heatflux to read (0,1,2,...)' ) parser.add_argument( '--sindex', nargs='*', type=int, help='Column indexes of the heatflux to substract from the flux read with --cindex (3,4,5,...)' ) parser.add_argument( '--run-keyword', type=str, help='Keyword that identifies the run to be read (only for "lammps" format)' ) - parser.add_argument('--split', type=int, default=1, help='Build a time series with n*m independent processes (n is the number of processes of the original timeseries, m is the number provided with --split). The length of the new time series will be [original length]/m.') + parser.add_argument( '--split', type=int, default=1, help='Build a time series with n*m independent processes (n is the number of processes of the original timeseries, m is the number provided with --split). The length of the new time series will be [original length]/m.') parser.add_argument( '-o', '--output', type=str, default='output', help='prefix of the output files' ) parser.add_argument( '-O', '--bin-output', action='store_true', help='save also binary files' ) + parser.add_argument( '--no-text-output', action='store_true', help='do not save text files' ) + parser.add_argument( '--bin-output-old', action='store_true', help='use old format for binary files (compatibility)' ) + parser.add_argument( '-V', '--volume', type=float, help='Volume of the cell (Angstrom). If not set it will be read from structure file or inputfile.' ) parser.add_argument( '--structure', type=str, help='LAMMPS data file containing the structure. Read to get Volume.' ) - - parser.add_argument( '-u', '--units', type=str, default='metal', choices=['metal', 'real', 'qepw', 'gpumd', 'dlpoly'], help='LAMMPS units (default: metal)' ) parser.add_argument( '-T', '--temperature', type=float, help='average Temperature (K). If not set it will be read from file' ) + parser.add_argument( '-u', '--units', type=str, default='metal', choices=['metal', 'real', 'qepw', 'gpumd', 'dlpoly'], help='LAMMPS units (default: metal)' ) parser.add_argument( '-r', '--resample', action='store_true', help='resample the time series (you should define --TSKIP or --FSTAR' ) resamplearg = parser.add_mutually_exclusive_group() @@ -140,6 +141,8 @@ def main(): output = args.output binout = args.bin_output + binout_old = args.bin_output_old + no_text_out = args.no_text_output units = args.units temperature = args.temperature @@ -338,20 +341,22 @@ def main(): if j.multicomponent: binoutobj.j_cospectrum = j.cospectrum binoutobj.j_fcospectrum = j.fcospectrum - outfile = open(output + '.psd.dat', 'w') - outarray = np.c_[j.freqs_THz, j.psd, j.fpsd, j.logpsd, j.flogpsd] - outfile.write('freqs_THz psd fpsd logpsd flogpsd\n') - np.savetxt(outfile, outarray) - outfile.close() - if j.multicomponent: - outfile = open(output + '.cospectrum.dat', 'w') - outarray = np.c_[j.freqs_THz,j.cospectrum.reshape((j.cospectrum.shape[0]*j.cospectrum.shape[1],j.cospectrum.shape[2])).transpose()] - np.savetxt(outfile, outarray) - outfile.close() - outfile = open(output + '.cospectrum.filt.dat', 'w') - outarray = np.c_[j.freqs_THz,j.fcospectrum.reshape((j.fcospectrum.shape[0]*j.fcospectrum.shape[1],j.fcospectrum.shape[2])).transpose()] - np.savetxt(outfile, outarray) - outfile.close() + #TODO: move all output in one place? + if not no_text_out: + outfile = open(output + '.psd.dat', 'w') + outarray = np.c_[j.freqs_THz, j.psd, j.fpsd, j.logpsd, j.flogpsd] + outfile.write('freqs_THz psd fpsd logpsd flogpsd\n') + np.savetxt(outfile, outarray) + outfile.close() + if j.multicomponent: + outfile = open(output + '.cospectrum.dat', 'w') + outarray = np.c_[j.freqs_THz,j.cospectrum.reshape((j.cospectrum.shape[0]*j.cospectrum.shape[1],j.cospectrum.shape[2])).transpose()] + np.savetxt(outfile, outarray) + outfile.close() + outfile = open(output + '.cospectrum.filt.dat', 'w') + outarray = np.c_[j.freqs_THz,j.fcospectrum.reshape((j.fcospectrum.shape[0]*j.fcospectrum.shape[1],j.fcospectrum.shape[2])).transpose()] + np.savetxt(outfile, outarray) + outfile.close() # resample and plot if resample: @@ -378,11 +383,12 @@ def main(): binoutobj.jf_logpsd = jf.logpsd binoutobj.jf_Nyquist_f_THz = jf.Nyquist_f_THz binoutobj.jf_resample_log = jf.resample_log - outfile = open(output + '.resampled_psd.dat', 'w') - outarray = np.c_[jf.freqs_THz, jf.psd, jf.fpsd, jf.logpsd, jf.flogpsd] - outfile.write('freqs_THz psd fpsd logpsd flogpsd\n') - np.savetxt(outfile, outarray) - outfile.close() + if not no_text_out: + outfile = open(output + '.resampled_psd.dat', 'w') + outarray = np.c_[jf.freqs_THz, jf.psd, jf.fpsd, jf.logpsd, jf.flogpsd] + outfile.write('freqs_THz psd fpsd logpsd flogpsd\n') + np.savetxt(outfile, outarray) + outfile.close() else: jf = j @@ -465,11 +471,12 @@ def main(): binoutobj.jf_dct_kappa_THEORY_std = jf.dct.tau_THEORY_std*jf.kappa_scale*0.5 binoutobj.jf_dct_aic_Kmin = jf.dct.aic_Kmin binoutobj.jf_dct_Kmin_corrfactor = jf.dct.Kmin_corrfactor - outfile = open(output + '.cepstral.dat', 'w') - outarray = np.c_[jf.dct.logpsdK, jf.dct.logpsdK_THEORY_std, jf.dct.logtau, jf.dct.logtau_THEORY_std, jf.dct.tau*jf.kappa_scale*0.5, jf.dct.tau_THEORY_std*jf.kappa_scale*0.5] - outfile.write('ck ck_std L0(P*) L0_std(P*) kappa(P*) kappa_std(P*)\n') - np.savetxt(outfile, outarray) - outfile.close() + if not no_text_out: + outfile = open(output + '.cepstral.dat', 'w') + outarray = np.c_[jf.dct.logpsdK, jf.dct.logpsdK_THEORY_std, jf.dct.logtau, jf.dct.logtau_THEORY_std, jf.dct.tau*jf.kappa_scale*0.5, jf.dct.tau_THEORY_std*jf.kappa_scale*0.5] + outfile.write('ck ck_std L0(P*) L0_std(P*) kappa(P*) kappa_std(P*)\n') + np.savetxt(outfile, outarray) + outfile.close() # plot cepstral log-PSD #ax = j.plot_periodogram(() #PSD_FILTER_W=psd_filter_w) @@ -485,11 +492,12 @@ def main(): if binout: binoutobj.jf_dct_psd = jf.dct.psd binoutobj.jf_dct_logpsd = jf.dct.logpsd - outfile = open(output + '.cepstrumfiltered_psd.dat', 'w') - outarray = np.c_[jf.freqs_THz, jf.dct.psd, jf.dct.logpsd] - outfile.write('freqs_THz cepf_psd cepf_logpsd\n') - np.savetxt(outfile, outarray,) - outfile.close() + if not no_text_out: + outfile = open(output + '.cepstrumfiltered_psd.dat', 'w') + outarray = np.c_[jf.freqs_THz, jf.dct.psd, jf.dct.logpsd] + outfile.write('freqs_THz cepf_psd cepf_logpsd\n') + np.savetxt(outfile, outarray,) + outfile.close() #conv_fact=open(output+'.kappa_scale_aicKmin.dat','w') # @@ -507,7 +515,10 @@ def main(): # write binary output if binout: - np.save(output, binoutobj) + if binout_old: + binoutobj.write_old_binary(output) + else: + np.save(output, binoutobj) return 0 @@ -702,5 +713,28 @@ def __init__(self): self.VOLUME = None self.TSKIP = None + def write_old_binary(self,output): + """Write old binary format.""" + outarray = np.array([self.j_freqs_THz, self.j_fpsd, self.j_flogpsd, self.j_psd, self.j_logpsd]) + np.save(output + ".psd.npy", outarray) + + if self.j_cospectrum is not None: + outarray = np.array([self.j_freqs_THz, self.j_cospectrum]) + np.save(output + ".cospectrum.npy", outarray) + + if self.j_fcospectrum is not None: + outarray = np.array([self.j_freqs_THz, self.j_fcospectrum]) + np.save(output + ".cospectrum.filt.npy", outarray) + + outarray = np.array([self.jf_freqs_THz, self.jf_psd, self.jf_fpsd, self.jf_logpsd, self.jf_flogpsd]) + np.save(output + ".resampled_psd.npy", outarray) + + outarray = np.array([self.jf_dct_logpsdK, self.jf_dct_logpsdK_THEORY_std, self.jf_dct_logtau, self.jf_dct_logtau_THEORY_std, self.jf_dct_kappa, self.jf_dct_kappa_THEORY_std]) + np.save(output + '.cepstral', outarray) + + outarray = np.array([self.jf_freqs_THz, self.jf_dct_psd, self.jf_dct_logpsd]) + np.save(output + ".cepstrumfiltered_psd", outarray) + + if __name__ == "__main__": main() From 990cc89adc43e8b37ac97c7769f76a4b2cf421c0 Mon Sep 17 00:00:00 2001 From: Loris Ercole Date: Mon, 17 Dec 2018 14:33:39 +0100 Subject: [PATCH 09/19] Few additions to output. --- thermocepstrum/analysis.py | 58 ++++++++++++++++++++++---------------- 1 file changed, 34 insertions(+), 24 deletions(-) diff --git a/thermocepstrum/analysis.py b/thermocepstrum/analysis.py index 9080f13..935b305 100755 --- a/thermocepstrum/analysis.py +++ b/thermocepstrum/analysis.py @@ -191,6 +191,13 @@ def main(): selected_keys = [j1_key] selected_keys.extend(j2_keys) + # Write some parameters + print ' Input file ({}): {}'.format(input_format, inputfile) + logfile.write(' Input file ({}): {}\n'.format(input_format, inputfile)) + print ' Units: {}'.format(units) + logfile.write(' Units: {}\n'.format(units)) + print ' Time step: {} fs'.format(DT_FS) + logfile.write(' Time step: {} fs\n'.format(DT_FS)) ## Read data jdata = None @@ -217,6 +224,7 @@ def main(): if (NSPLIT > 1): print 'Splitting input data time series into {:d} segments...'.format(NSPLIT) + logfile.write('Splitting input data time series into {:d} segments...\n'.format(NSPLIT)) data_size = jdata[selected_keys[0]].shape[0] n_proc = 1 try: ## HORRIBLE @@ -232,7 +240,8 @@ def main(): if key != 'Temp': newdata = value[:steps_start].reshape((NSPLIT,data_size/NSPLIT,n_proc)).transpose((1,0,2)).reshape((data_size/NSPLIT,NSPLIT*n_proc)) jdata[key] = newdata[:steps_end] - print 'New shape of input data: ', jdata[selected_keys[0]].shape + print 'New shape of input data: {}'.format(jdata[selected_keys[0]].shape) + logfile.write('New shape of input data: {}\n'.format(jdata[selected_keys[0]].shape)) if NSTEPS==0: NSTEPS=jdata[jdata.keys()[0]].shape[0] @@ -317,10 +326,11 @@ def main(): logfile.write(' Nyquist_f = {} THz\n'.format(j.Nyquist_f_THz)) + ################################ + ## OUTPUT SECTION ## TODO: isolate output from computation if binout: binoutobj = TCOutput() - with PdfPages(output + ".plots.pdf") as pdf: # plot periodogram @@ -350,11 +360,11 @@ def main(): outfile.close() if j.multicomponent: outfile = open(output + '.cospectrum.dat', 'w') - outarray = np.c_[j.freqs_THz,j.cospectrum.reshape((j.cospectrum.shape[0]*j.cospectrum.shape[1],j.cospectrum.shape[2])).transpose()] + outarray = np.c_[j.freqs_THz, j.cospectrum.reshape((j.cospectrum.shape[0]*j.cospectrum.shape[1], j.cospectrum.shape[2])).transpose()] np.savetxt(outfile, outarray) outfile.close() outfile = open(output + '.cospectrum.filt.dat', 'w') - outarray = np.c_[j.freqs_THz,j.fcospectrum.reshape((j.fcospectrum.shape[0]*j.fcospectrum.shape[1],j.fcospectrum.shape[2])).transpose()] + outarray = np.c_[j.freqs_THz, j.fcospectrum.reshape((j.fcospectrum.shape[0]*j.fcospectrum.shape[1], j.fcospectrum.shape[2])).transpose()] np.savetxt(outfile, outarray) outfile.close() @@ -526,17 +536,17 @@ def main(): def plt_cepstral_conv(jf, pstar_max=None, k_SI_max=None, pstar_tick=None, kappa_tick=None): if pstar_max is None: - pstar_max = (jf.dct.aic_Kmin+1)*2.5 + pstar_max = (jf.dct.aic_Kmin+1) * 2.5 if k_SI_max is None: - k_SI_max = jf.dct.tau[jf.dct.aic_Kmin]*jf.kappa_scale + k_SI_max = jf.dct.tau[jf.dct.aic_Kmin] * jf.kappa_scale f, (ax2) = plt.subplots(1, 1, figsize=(3.8,2.3)) - ax2.axvline(x=jf.dct.aic_Kmin+1, ls='--', c='k', dashes=(1.4,0.6), zorder=-3) - ax2.fill_between(np.arange(jf.dct.logtau.shape[0])+1,\ - (jf.dct.tau-jf.dct.tau_THEORY_std)*jf.kappa_scale*0.5,\ - (jf.dct.tau+jf.dct.tau_THEORY_std)*jf.kappa_scale*0.5,\ + ax2.axvline(x=jf.dct.aic_Kmin + 1, ls='--', c='k', dashes=(1.4,0.6), zorder=-3) + ax2.fill_between(np.arange(jf.dct.logtau.shape[0]) + 1,\ + (jf.dct.tau - jf.dct.tau_THEORY_std) * jf.kappa_scale * 0.5,\ + (jf.dct.tau + jf.dct.tau_THEORY_std) * jf.kappa_scale * 0.5,\ alpha=.3, color=c[4], zorder=-3) - ax2.plot(np.arange(jf.dct.logtau.shape[0])+1, jf.dct.tau*jf.kappa_scale*0.5,\ + ax2.plot(np.arange(jf.dct.logtau.shape[0]) + 1, jf.dct.tau * jf.kappa_scale * 0.5,\ label=r'Cepstral method', marker='o', c=c[4], zorder=-3) ax2.set_xlabel(r'$P^*$') ax2.set_ylabel(r'$\kappa$ (W/mK)') @@ -549,12 +559,12 @@ def plt_cepstral_conv(jf, pstar_max=None, k_SI_max=None, pstar_tick=None, kappa_ dx1, dx2 = n_tick_in_range(0, pstar_max, 5) else: dx1 = pstar_tick - dx2 = dx1/2 + dx2 = dx1 / 2 if kappa_tick is None: dy1, dy2 = n_tick_in_range(0, k_SI_max, 5) else: dy1 = kappa_tick - dy2 = dy1/2 + dy2 = dy1 / 2 ax2.xaxis.set_major_locator(MultipleLocator(dx1)) ax2.xaxis.set_minor_locator(MultipleLocator(dx2)) ax2.yaxis.set_major_locator(MultipleLocator(dy1)) @@ -588,12 +598,12 @@ def plt_other(jf, idx1, idx2, f_THz_max=None, k_SI_max=None, k_SI_min=None, k_ti dx1, dx2 = n_tick_in_range(0, f_THz_max, 5) else: dx1 = f_tick - dx2 = dx1/2 + dx2 = dx1 / 2 if k_tick is None: dy1, dy2 = n_tick_in_range(0, k_SI_max, 5) else: dy1 = k_tick - dy2 = dy1/2 + dy2 = dy1 / 2 plt.axes().xaxis.set_major_locator(MultipleLocator(dx1)) plt.axes().xaxis.set_minor_locator(MultipleLocator(dx2)) @@ -609,12 +619,12 @@ def plt_psd(jf, j2=None, j2pl=None, f_THz_max=None, k_SI_max=None, k_tick=None, maxT = jf.freqs_THz[-1] if j2 is not None: if j2.freqs_THz[-1] > maxT: - maxT=j2.freqs_THz[-1] + maxT = j2.freqs_THz[-1] if j2pl is not None: if j2pl.freqs_THz[-1] > maxT: - maxT=j2pl.freqs_THz[-1] - if maxT< f_THz_max: - f_THz_max=maxT + maxT = j2pl.freqs_THz[-1] + if maxT < f_THz_max: + f_THz_max = maxT if k_SI_max is None: k_SI_max = np.max(jf.fpsd[:int(jf.freqs_THz.shape[0]*f_THz_max/jf.freqs_THz[-1])]*jf.kappa_scale*0.5)*1.3 @@ -640,12 +650,12 @@ def plt_psd(jf, j2=None, j2pl=None, f_THz_max=None, k_SI_max=None, k_tick=None, dx1, dx2 = n_tick_in_range(0, f_THz_max, 5) else: dx1 = f_tick - dx2 = dx1/2 + dx2 = dx1 / 2 if k_tick is None: dy1, dy2 = n_tick_in_range(0, k_SI_max, 5) else: dy1 = k_tick - dy2 = dy1/2 + dy2 = dy1 / 2 plt.axes().xaxis.set_major_locator(MultipleLocator(dx1)) plt.axes().xaxis.set_minor_locator(MultipleLocator(dx2)) @@ -657,17 +667,17 @@ def n_tick_in_range(beg, end, n): size = end-beg n_cifre = math.floor(math.log(size/n,10.0)) delta = math.ceil((size/n)/10**n_cifre)*10**n_cifre - return delta, delta/2 + return delta, delta / 2 def index_cumsum(arr, p): if (p > 1 or p < 0): raise ValueError('p must be between 0 and 1') arr_int = np.cumsum(arr) - arr_int = arr_int/arr_int[-1] + arr_int = arr_int / arr_int[-1] idx = 0 while (arr_int[idx] < p): - idx = idx+1 + idx = idx + 1 return idx From d4586b9f2a6ded3e930a3ac83edc6760bd83a2f8 Mon Sep 17 00:00:00 2001 From: Loris Ercole Date: Tue, 18 Dec 2018 11:24:27 +0100 Subject: [PATCH 10/19] Fix message in heatcurrent. --- thermocepstrum/heatcurrent.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/thermocepstrum/heatcurrent.py b/thermocepstrum/heatcurrent.py index a68483b..ce6e1e3 100644 --- a/thermocepstrum/heatcurrent.py +++ b/thermocepstrum/heatcurrent.py @@ -85,7 +85,7 @@ def __init__(self, j, units, DT_FS, TEMPERATURE, VOLUME, PSD_FILTER_W=None, freq def __repr__(self): msg = 'HeatCurrent:\n' + super(HeatCurrent, self).__repr__() if self.dct is not None: - msd += self.dct.__repr__() + msg += self.dct.__repr__() return msg From 4995251e9cc406827a6719d52deeb7d8fcc4b9a7 Mon Sep 17 00:00:00 2001 From: Riccardo Bertossa Date: Sun, 23 Dec 2018 14:05:00 +0100 Subject: [PATCH 11/19] Better plots in utils/blocks.py --- thermocepstrum/utils/blocks.py | 93 ++++++++++++++++++++++++---------- 1 file changed, 65 insertions(+), 28 deletions(-) diff --git a/thermocepstrum/utils/blocks.py b/thermocepstrum/utils/blocks.py index 3663e95..eaa84be 100755 --- a/thermocepstrum/utils/blocks.py +++ b/thermocepstrum/utils/blocks.py @@ -25,8 +25,13 @@ import os.path import thermocepstrum as tc +try: + from mpl_toolkits.axes_grid1.inset_locator import inset_axes +except: + print "Error: cannot import inset_axes (will not be able to plot some parts of the plots)" + def main(): - usage="""usage: {} output N_currents N_processes DT_FS nyquist k_SI_max max_THz_psd input1 input2 ... inputN + usage="""usage: {} output N_currents N_processes DT_FS max_THz nyquist k_SI_max zoom_max_THz zoom_k_SI_max input1 input2 ... inputN N must be at least 2. This utility computes some histograms and statistics of the outputs generated by the analysis program. @@ -53,7 +58,9 @@ def main(): max_THz=float(sys.argv[5]) nyq=float(sys.argv[6]) k_SI_max=float(sys.argv[7]) - ff=8 + zmax_THz=float(sys.argv[8]) + zk_SI_max=float(sys.argv[9]) + ff=10 ndata=len(sys.argv)-ff print "Number of inputs: {}\n reading...".format(ndata) @@ -219,6 +226,10 @@ def ffpsd(self,w): plt_psd(psd,k_00=True,f_THz_max=max_THz,nyq=nyq,k_SI_max=k_SI_max) pdf.savefig() plt.close() + + plt_psd_with_zoom(psd,k_00=True,f_THz_max=max_THz,nyq=nyq,k_SI_max=k_SI_max,inset_maxTHz=zmax_THz,inset_maxk=zk_SI_max) + pdf.savefig() + plt.close() plt.xlim([0,max_THz]) @@ -325,7 +336,13 @@ def plt_hist_single_psd(data1,dof,nbins=None): return ks_0 -def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=None): +def plt_psd_with_zoom(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=None,inset_maxTHz=None,inset_maxk=None): + #plt.axes([0,1,0,1]) + fig_r,ax0=plt_psd(jf,j2,j2pl,f_THz_max,k_SI_max,k_00,nyq) + ax=fig_r.add_axes([0.2,0.52,0.3,0.3]) + plt_psd(jf,j2,j2pl,inset_maxTHz,inset_maxk,k_00,nyq,False,axes=ax) + +def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=None,plt_figure=True,axes=None): if f_THz_max==None: idx_max=index_cumsum(jf.psd,0.95) @@ -341,45 +358,65 @@ def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=No except AttributeError: pass - + fig_r=None + if plt_figure: + fig_r=plt.figure(figsize=(3.8,2.3)) + if axes is None: + axes = plt.gca() - plt.figure(figsize=(3.8,2.3)) - plt.plot(jf.freqs_THz,jf.psd*jf.kappa_scale*.5,lw=0.2,c='0.8',zorder=0) - plt.plot(jf.freqs_THz,jf.fpsd*jf.kappa_scale*.5,c=c[0],zorder=2) + axes.plot(jf.freqs_THz,jf.psd*jf.kappa_scale*.5,lw=0.2,c='0.8',zorder=0) + axes.plot(jf.freqs_THz,jf.fpsd*jf.kappa_scale*.5,c=c[0],zorder=2) if j2 != None: - plt.axvline(x=j2.Nyquist_f_THz,ls='--', c='k', dashes=(1.4,0.6), zorder=3) + axes.axvline(x=j2.Nyquist_f_THz,ls='--', c='k', dashes=(1.4,0.6), zorder=3) if j2pl != None: - plt.plot(j2pl.freqs_THz,j2pl.dct.psd*j2pl.kappa_scale*.5,c=c[2]) + axes.plot(j2pl.freqs_THz,j2pl.dct.psd*j2pl.kappa_scale*.5,c=c[2]) try: - plt.plot(jf.freqs_THz,np.real(jf.cospectrum[0,0])*jf.kappa_scale*.5,c=c[3],lw=1.0,zorder=1) + axes.plot(jf.freqs_THz,np.real(jf.cospectrum[0,0])*jf.kappa_scale*.5,c=c[3],lw=1.0,zorder=1) except AttributeError: pass - plt.ylim([0,k_SI_max]) - plt.xlim([0,f_THz_max]) - plt.xlabel('$\omega/2\pi$ (THz)') - # plt.ylabel('$^{\ell M}\widehat{S}\'_{\,k}$ (W/mK)') - plt.ylabel('(W/mK)') + axes.set_ylim(0,k_SI_max) + axes.set_xlim(0,f_THz_max) + if plt_figure: + axes.set_xlabel('$\omega/2\pi$ (THz)') + # axes.set_ylabel('$^{\ell M}\widehat{S}\'_{\,k}$ (W/mK)') + axes.set_ylabel('(W/mK)') idxnyq=int(nyq/jf.freqs_THz[-1]*jf.freqs_THz.size) if nyq != None: - plt.annotate("", xy=(nyq, (k_SI_max-jf.fpsd[idxnyq]*jf.kappa_scale*.5)/7+jf.fpsd[idxnyq]*jf.kappa_scale*.5), \ + axes.annotate("", xy=(nyq, (k_SI_max-jf.fpsd[idxnyq]*jf.kappa_scale*.5)/7+jf.fpsd[idxnyq]*jf.kappa_scale*.5), \ xytext=(nyq, (k_SI_max-jf.fpsd[idxnyq]*jf.kappa_scale*.5)/7+jf.fpsd[idxnyq]*jf.kappa_scale*.5+k_SI_max/7.0), \ arrowprops={'width': 1.0, 'headwidth': 3.0, 'headlength': 7, 'color': 'k'}) dx1,dx2=n_tick_in_range(0,f_THz_max,5) dy1,dy2=n_tick_in_range(0,k_SI_max,5) - dx1=10 - dx2=5 - plt.axes().xaxis.set_major_locator(MultipleLocator(dx1)) - plt.axes().xaxis.set_minor_locator(MultipleLocator(dx2)) - plt.axes().yaxis.set_major_locator(MultipleLocator(dy1)) - plt.axes().yaxis.set_minor_locator(MultipleLocator(dy2)) - -def n_tick_in_range(beg,end,n): - size=end-beg - n_cifre=math.floor(math.log(size/n,10.0)) - delta=math.ceil((size/n)/10**n_cifre)*10**n_cifre - return delta,delta/2 + #dx1=10 + #dx2=5 + axes.xaxis.set_major_locator(MultipleLocator(dx1)) + axes.xaxis.set_minor_locator(MultipleLocator(dx2)) + axes.yaxis.set_major_locator(MultipleLocator(dy1)) + axes.yaxis.set_minor_locator(MultipleLocator(dy2)) + return fig_r, axes + + +def n_tick_in_range(beg,end,n,n_c=1,nit=0): + size=end-beg + dx0=(end-beg)/n + e=10**(math.ceil(math.log10(dx0))) + m=dx0/e + cifre0=math.ceil(m*10**(n_c)) + cifre=cifre0-cifre0%5 + if cifre==0: + cifre=1.0 + delta=cifre*e/10**(n_c) + #print "n=",n, " dx0=",dx0," e=",e," m=" ,m," cifre=",cifre + if nit<30: + if delta>=size: + return n_tick_in_range(beg,end,n+1,n_c,nit+1) + if (end-beg)/delta > n and n>1: + return n_tick_in_range(beg,end,n-1,n_c,nit+1) + + return delta,delta/2 + def index_cumsum(arr,p): if (p>1 or p<0): From eb6eded16a179aa70d9cf7afb3f81d2923a578d8 Mon Sep 17 00:00:00 2001 From: Loris Ercole Date: Mon, 24 Dec 2018 10:19:19 +0100 Subject: [PATCH 12/19] plot spectra in kappa units (EXPERIMENTAL) --- thermocepstrum/heatcurrent.py | 30 +++++++++++++++++++----------- 1 file changed, 19 insertions(+), 11 deletions(-) diff --git a/thermocepstrum/heatcurrent.py b/thermocepstrum/heatcurrent.py index ce6e1e3..3f3bb30 100644 --- a/thermocepstrum/heatcurrent.py +++ b/thermocepstrum/heatcurrent.py @@ -160,7 +160,7 @@ def cepstral_analysis(self, aic_type='aic', Kmin_corrfactor=1.0): ### PLOT METHODS ################################### - def plot_periodogram(self, PSD_FILTER_W=None, freq_units='thz', freq_scale=1.0, axes=None, FIGSIZE=None, **plot_kwargs): + def plot_periodogram(self, PSD_FILTER_W=None, freq_units='thz', freq_scale=1.0, axes=None, kappa_units=False, FIGSIZE=None, **plot_kwargs): """ Plot the periodogram. PSD_FILTER_W = width of the filtering window @@ -190,17 +190,21 @@ def plot_periodogram(self, PSD_FILTER_W=None, freq_units='thz', freq_scale=1.0, else: raise ValueError('Units not valid.') + if kappa_units: + psd_scale = 0.5 * self.kappa_scale + else: + psd_scale = 1.0 if axes is None: figure, axes = plt.subplots(2, sharex=True, figsize=FIGSIZE) plt.subplots_adjust(hspace = 0.1) if (freq_units == 'thz') or (freq_units == 'THz'): - axes[0].plot(self.freqs_THz, self.fpsd, **plot_kwargs) - axes[1].plot(self.freqs_THz, self.flogpsd, **plot_kwargs) + axes[0].plot(self.freqs_THz, psd_scale * self.fpsd, **plot_kwargs) + axes[1].plot(self.freqs_THz, psd_scale * self.flogpsd, **plot_kwargs) axes[0].set_xlim([0., self.Nyquist_f_THz]) axes[1].set_xlim([0., self.Nyquist_f_THz]) elif (freq_units == 'red'): - axes[0].plot(self.freqs/freq_scale, self.fpsd, **plot_kwargs) - axes[1].plot(self.freqs/freq_scale, self.flogpsd, **plot_kwargs) + axes[0].plot(self.freqs/freq_scale, psd_scale * self.fpsd, **plot_kwargs) + axes[1].plot(self.freqs/freq_scale, psd_scale * self.flogpsd, **plot_kwargs) axes[0].set_xlim([0., 0.5/freq_scale]) axes[1].set_xlim([0., 0.5/freq_scale]) else: @@ -263,17 +267,21 @@ def plot_kappa_Pstar(self, axes=None, label=None, FIGSIZE=None): return axes - def plot_cepstral_spectrum(self, freq_units='thz', freq_scale=1.0, axes=None, FIGSIZE=None, **plot_kwargs): + def plot_cepstral_spectrum(self, freq_units='thz', freq_scale=1.0, axes=None, kappa_units=True, FIGSIZE=None, **plot_kwargs): if axes is None: figure, axes = plt.subplots(2, sharex=True, figsize=FIGSIZE) plt.subplots_adjust(hspace = 0.1) + if kappa_units: + psd_scale = 0.5 * self.kappa_scale + else: + psd_scale = 1.0 if (freq_units == 'thz') or (freq_units == 'THz'): - axes[0].plot(self.freqs_THz, self.dct.psd, **plot_kwargs) + axes[0].plot(self.freqs_THz, self.dct.psd * psd_scale, **plot_kwargs) axes[1].plot(self.freqs_THz, self.dct.logpsd, **plot_kwargs) axes[0].set_xlim([0., self.Nyquist_f_THz]) axes[1].set_xlim([0., self.Nyquist_f_THz]) elif (freq_units == 'red'): - axes[0].plot(self.freqs/freq_scale, self.dct.psd, **plot_kwargs) + axes[0].plot(self.freqs/freq_scale, self.dct.psd * psd_scale, **plot_kwargs) axes[1].plot(self.freqs/freq_scale, self.dct.logpsd, **plot_kwargs) axes[0].set_xlim([0., 0.5/freq_scale]) axes[1].set_xlim([0., 0.5/freq_scale]) @@ -333,7 +341,7 @@ def resample_current(x, TSKIP=None, fstar_THz=None, FILTER_W=None, plot=True, PS TSKIP = int(round(x.Nyquist_f_THz/fstar_THz)) if plot: figure, axes = plt.subplots(2, sharex=True, figsize=FIGSIZE) - axes = x.plot_periodogram(PSD_FILTER_W, freq_units, 1.0, axes) + axes = x.plot_periodogram(PSD_FILTER_W, freq_units, 1.0, axes=axes) fstar_THz = x.Nyquist_f_THz / TSKIP fstar_idx = np.argmin(x.freqs_THz < fstar_THz) @@ -355,11 +363,11 @@ def resample_current(x, TSKIP=None, fstar_THz=None, FILTER_W=None, plot=True, PS xf = HeatCurrent(yf, x.units, x.DT_FS*TSKIP, x.TEMPERATURE, x.VOLUME, x.FILTER_WINDOW_WIDTH*TSKIP) if plot: if (freq_units == 'thz') or (freq_units == 'THz'): - xf.plot_periodogram(x.FILTER_WINDOW_WIDTH*1000./x.DT_FS, 'thz', TSKIP, axes) + xf.plot_periodogram(x.FILTER_WINDOW_WIDTH*1000./x.DT_FS, 'thz', TSKIP, axes=axes) elif (freq_units == 'red'): print PSD_FILTER_W print x.FILTER_WINDOW_WIDTH - xf.plot_periodogram(x.FILTER_WINDOW_WIDTH*TSKIP, 'red', TSKIP, axes) + xf.plot_periodogram(x.FILTER_WINDOW_WIDTH*TSKIP, 'red', TSKIP, axes=axes) xf.resample_log = '-----------------------------------------------------\n' +\ ' RESAMPLE TIME SERIES\n' +\ From cdb3cbbde7d3e58f408ab6f618af9af02cbe2d9b Mon Sep 17 00:00:00 2001 From: Riccardo Bertossa Date: Fri, 28 Dec 2018 00:44:52 +0100 Subject: [PATCH 13/19] bettered a plot in blocks.py --- thermocepstrum/utils/blocks.py | 20 ++++++++++++++++---- 1 file changed, 16 insertions(+), 4 deletions(-) diff --git a/thermocepstrum/utils/blocks.py b/thermocepstrum/utils/blocks.py index eaa84be..71c52b1 100755 --- a/thermocepstrum/utils/blocks.py +++ b/thermocepstrum/utils/blocks.py @@ -339,9 +339,18 @@ def plt_hist_single_psd(data1,dof,nbins=None): def plt_psd_with_zoom(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=None,inset_maxTHz=None,inset_maxk=None): #plt.axes([0,1,0,1]) fig_r,ax0=plt_psd(jf,j2,j2pl,f_THz_max,k_SI_max,k_00,nyq) - ax=fig_r.add_axes([0.2,0.52,0.3,0.3]) + coord_f=[0.2,0.55,0.3,0.3] + ax=fig_r.add_axes(coord_f) + inv=fig_r.transFigure # + ax0.transData.inverted() + f_x=0.73 + f_x2=1.3 + f_y=0.87 + f_y2=1.35 + print inv.transform((coord_f[0]*f_x,coord_f[1]*f_y)) + ax0.add_patch(matplotlib.patches.Rectangle((coord_f[0]*f_x,coord_f[1]*f_y),coord_f[2]*f_x2,coord_f[3]*f_y2,fill=True ,color='White',visible=True,transform=inv)) + #plt.box() plt_psd(jf,j2,j2pl,inset_maxTHz,inset_maxk,k_00,nyq,False,axes=ax) - + def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=None,plt_figure=True,axes=None): if f_THz_max==None: @@ -387,8 +396,11 @@ def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=No xytext=(nyq, (k_SI_max-jf.fpsd[idxnyq]*jf.kappa_scale*.5)/7+jf.fpsd[idxnyq]*jf.kappa_scale*.5+k_SI_max/7.0), \ arrowprops={'width': 1.0, 'headwidth': 3.0, 'headlength': 7, 'color': 'k'}) - dx1,dx2=n_tick_in_range(0,f_THz_max,5) - dy1,dy2=n_tick_in_range(0,k_SI_max,5) + ntick=5 + if axes is not None: + ntick=3 + dx1,dx2=n_tick_in_range(0,f_THz_max,ntick) + dy1,dy2=n_tick_in_range(0,k_SI_max, ntick) #dx1=10 #dx2=5 axes.xaxis.set_major_locator(MultipleLocator(dx1)) From a2fffa07359902ac5b5fafc95e2625867a6c6a1d Mon Sep 17 00:00:00 2001 From: Riccardo Bertossa Date: Fri, 28 Dec 2018 17:53:20 +0100 Subject: [PATCH 14/19] added more interesting plots to blocks.py --- thermocepstrum/utils/blocks.py | 117 ++++++++++++++++++++++++++------- 1 file changed, 92 insertions(+), 25 deletions(-) diff --git a/thermocepstrum/utils/blocks.py b/thermocepstrum/utils/blocks.py index 71c52b1..c5e8dca 100755 --- a/thermocepstrum/utils/blocks.py +++ b/thermocepstrum/utils/blocks.py @@ -79,11 +79,14 @@ def main(): freqs=np.loadtxt(sys.argv[ff]+'.psd.dat',usecols=(0,),unpack=True) cont=0 for fname in sys.argv[ff:]: - print fname if os.path.isfile(fname+'.psd.npy'): periodograms.append(np.load(fname+'.psd.npy')[3:5]) else: periodograms.append(np.loadtxt(fname+'.psd.dat',usecols=(3,4),unpack=True)) + if periodograms[-1].shape != periodograms[0].shape: + print fname , " not used (inconsistent shape with firts element)", periodograms[-1].shape, periodograms[0].shape + del periodograms[-1] + continue if os.path.isfile(fname+'.cepstral.npy'): cepstrals.append(np.load(fname+'.cepstral.npy')[[4,5,2,3]]) else: @@ -107,6 +110,7 @@ def main(): kappas_Kmin_std[cont]=cepstrals[cont][1,aic_Kmin] l0s[cont]=cepstrals[cont][2,aic_Kmin] l0s_std[cont]=cepstrals[cont][3,aic_Kmin] + print fname, periodograms[cont].shape, cepstrals[cont].shape cont+=1 aic_KminM=np.mean(aic_Kmins) @@ -117,9 +121,17 @@ def main(): #resizing and creating a big numpy array. - for periodogram,cepstral in zip(periodograms,cepstrals): - periodogram.resize(periodograms[0].shape) - cepstral.resize(cepstrals[0].shape) + #for periodogram,cepstral in zip(periodograms,cepstrals): + for i in range(1,len(periodograms)): + periodograms[i].resize(periodograms[0].shape) + cepstrals[i].resize(cepstrals[0].shape) + # *this does not work when using a lot of data + #import pdb; pdb.set_trace() + #print periodograms[0].shape + #for i in range(1,len(periodograms)): + # print i + # periodograms[i]=np.resize(periodograms[i],periodograms[0].shape) + # cepstrals[i]=np.resize(cepstrals[i],cepstrals[0].shape) cepstrals=np.array(cepstrals,copy=False) periodograms=np.array(periodograms,copy=False) @@ -189,26 +201,35 @@ def main(): plt.fill_between(freqs,mean_periodogram[0]-std_periodogram[0],mean_periodogram[0]+std_periodogram[0]) plt.plot(freqs,mean_periodogram[0]) plt.title('Original PSD') - pdf.savefig() + pdf.savefig(bbox_inches='tight',pad_inches=0.0) plt.close() class Psd: psd=None + mpsd=None fpsd=None freqs_THz=None kappa_scale=None cospectrum=None + mcospectrum=None + ucospectrum=None DT_FS=None - def ffpsd(self,w): + def ffpsd(self,w,single=False): WF=int(round(w/1000.*self.DT_FS*len(self.freqs_THz)*2.)) print 'filtering: ',WF - ffpsd=tc.md.tools.runavefilter(self.fpsd, WF) + if not single: + ffpsd=tc.md.tools.runavefilter(self.mpsd, WF) + else: + ffpsd=tc.md.tools.runavefilter(self.psd, WF) self.fpsd=ffpsd try: - for i in range(self.cospectrum.shape[0]): - for j in range(self.cospectrum.shape[1]): - ffpsd=tc.md.tools.runavefilter(self.cospectrum[i,j], WF) - self.cospectrum[i,j]=ffpsd + for i in range(self.ucospectrum.shape[0]): + for j in range(self.ucospectrum.shape[1]): + if not single: + ffc=tc.md.tools.runavefilter(self.mcospectrum[i,j], WF) + else: + ffc=tc.md.tools.runavefilter(self.ucospectrum[i,j], WF) + self.cospectrum[i,j]=ffc except AttributeError: pass @@ -217,31 +238,77 @@ def ffpsd(self,w): psd.DT_FS=DT_FS psd.kappa_scale=np.mean(kappa_scales)/DT_FS - psd.psd=periodograms[0,0,:] - psd.fpsd=mean_periodogram[0,:] psd.freqs_THz=freqs - psd.cospectrum=mean_cospectrum - psd.ffpsd(0.2) + plot_idx=2 + psd.psd=periodograms [plot_idx,0,:] + psd.mpsd=mean_periodogram [0,:] + psd.fpsd=np.copy(mean_periodogram [0,:]) + psd.ucospectrum=cospectrums[plot_idx] + psd.mcospectrum=mean_cospectrum + psd.cospectrum=np.copy(mean_cospectrum) plt_psd(psd,k_00=True,f_THz_max=max_THz,nyq=nyq,k_SI_max=k_SI_max) - pdf.savefig() + pdf.savefig(bbox_inches='tight',pad_inches=0.0) plt.close() plt_psd_with_zoom(psd,k_00=True,f_THz_max=max_THz,nyq=nyq,k_SI_max=k_SI_max,inset_maxTHz=zmax_THz,inset_maxk=zk_SI_max) - pdf.savefig() + pdf.savefig(bbox_inches='tight',pad_inches=0.0) plt.close() plt.xlim([0,max_THz]) plt.plot(psd.freqs_THz,np.real(psd.cospectrum[1,0])) - pdf.savefig() + pdf.savefig(bbox_inches='tight',pad_inches=0.0) plt.close() plt.xlim([0,max_THz]) plt.plot(psd.freqs_THz,psd.cospectrum[1,1]) - pdf.savefig() + pdf.savefig(bbox_inches='tight',pad_inches=0.0) plt.close() + psd.ffpsd(0.5,single=True) + + plt_psd(psd,k_00=True,f_THz_max=max_THz,nyq=nyq,k_SI_max=k_SI_max) + pdf.savefig(bbox_inches='tight',pad_inches=0.0) + plt.close() + + plt_psd_with_zoom(psd,k_00=True,f_THz_max=max_THz,nyq=nyq,k_SI_max=k_SI_max,inset_maxTHz=zmax_THz,inset_maxk=zk_SI_max) + pdf.savefig(bbox_inches='tight',pad_inches=0.0) + plt.close() + + plt.xlim([0,max_THz]) + + plt.plot(psd.freqs_THz,np.real(psd.cospectrum[1,0])) + pdf.savefig(bbox_inches='tight',pad_inches=0.0) + plt.close() + plt.xlim([0,max_THz]) + + plt.plot(psd.freqs_THz,psd.cospectrum[1,1]) + pdf.savefig(bbox_inches='tight',pad_inches=0.0) + plt.close() + + + psd.ffpsd(0.2,single=False) + + plt_psd(psd,k_00=True,f_THz_max=max_THz,nyq=nyq,k_SI_max=k_SI_max) + pdf.savefig(bbox_inches='tight',pad_inches=0.0) + plt.close() + + plt_psd_with_zoom(psd,k_00=True,f_THz_max=max_THz,nyq=nyq,k_SI_max=k_SI_max,inset_maxTHz=zmax_THz,inset_maxk=zk_SI_max) + pdf.savefig(bbox_inches='tight',pad_inches=0.0) + plt.close() + + plt.xlim([0,max_THz]) + + plt.plot(psd.freqs_THz,np.real(psd.cospectrum[1,0])) + pdf.savefig(bbox_inches='tight',pad_inches=0.0) + plt.close() + plt.xlim([0,max_THz]) + + plt.plot(psd.freqs_THz,psd.cospectrum[1,1]) + pdf.savefig(bbox_inches='tight',pad_inches=0.0) + plt.close() + #make histogram for component 0 and 1 of psd #compute means without i-th element @@ -252,18 +319,18 @@ def ffpsd(self,w): plt.hist(kappas_Kmin) plt.title('kappa(aic-Kmin)') - pdf.savefig() + pdf.savefig(bbox_inches='tight',pad_inches=0.0) plt.close() data1=periodograms[:,0,0]/independent_mean[:,0] ks__0=plt_hist_single_psd(data1,dof) - pdf.savefig() + pdf.savefig(bbox_inches='tight',pad_inches=0.0) plt.close() data2=periodograms[:,0,1]/independent_mean[:,1] ks__1=plt_hist_single_psd(data2,dof*2) - pdf.savefig() + pdf.savefig(bbox_inches='tight',pad_inches=0.0) plt.close() #ks_1=sp.stats.kstest(data2*2*dof,sp.stats.chi2(2*dof).cdf) @@ -275,7 +342,7 @@ def ffpsd(self,w): all_normalized[i*len(selection_not_zero):(i+1)*len(selection_not_zero)]=periodograms[i,0,selection_not_zero]/independent_mean[i,selection_not_zero] ks_all=plt_hist_single_psd(all_normalized,dof*2,nbins=100) - pdf.savefig() + pdf.savefig(bbox_inches='tight',pad_inches=0.0) plt.close() # np.savetxt(output+'.histogram_all',np.c_[(intervals[1:]+intervals[:-1])/2.0,histogram/np.sum(histogram)]) @@ -297,7 +364,7 @@ def ffpsd(self,w): plt.ylim([min_y*0.8,max_y*1.2]) - pdf.savefig() + pdf.savefig(bbox_inches='tight') plt.close() def plt_hist_single_psd(data1,dof,nbins=None): @@ -391,7 +458,7 @@ def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=No # axes.set_ylabel('$^{\ell M}\widehat{S}\'_{\,k}$ (W/mK)') axes.set_ylabel('(W/mK)') idxnyq=int(nyq/jf.freqs_THz[-1]*jf.freqs_THz.size) - if nyq != None: + if nyq != None and nyq < f_THz_max: axes.annotate("", xy=(nyq, (k_SI_max-jf.fpsd[idxnyq]*jf.kappa_scale*.5)/7+jf.fpsd[idxnyq]*jf.kappa_scale*.5), \ xytext=(nyq, (k_SI_max-jf.fpsd[idxnyq]*jf.kappa_scale*.5)/7+jf.fpsd[idxnyq]*jf.kappa_scale*.5+k_SI_max/7.0), \ arrowprops={'width': 1.0, 'headwidth': 3.0, 'headlength': 7, 'color': 'k'}) From 2b87179cd593750a67708b053a7a2efd58d8a104 Mon Sep 17 00:00:00 2001 From: Riccardo Bertossa Date: Mon, 11 Mar 2019 16:59:08 +0100 Subject: [PATCH 15/19] added a setup.py file to package the software --- pack.sh | 15 +++++++++++++++ thermocepstrum/setup.py | 27 +++++++++++++++++++++++++++ thermocepstrum/utils/blocks.py | 21 ++++++++++++--------- 3 files changed, 54 insertions(+), 9 deletions(-) create mode 100755 pack.sh create mode 100644 thermocepstrum/setup.py diff --git a/pack.sh b/pack.sh new file mode 100755 index 0000000..91974cf --- /dev/null +++ b/pack.sh @@ -0,0 +1,15 @@ +#!/bin/bash + +set -x + +cp -v LICENSE thermocepstrum/ +cp -v README.md thermocepstrum/ +python3 -m pip install --user --upgrade setuptools wheel + +cd thermocepstrum +python3 setup.py sdist bdist_wheel + +python3 -m pip install --user --upgrade twine +python3 -m twine upload --repository-url https://test.pypi.org/legacy/ dist/* + + diff --git a/thermocepstrum/setup.py b/thermocepstrum/setup.py new file mode 100644 index 0000000..430438d --- /dev/null +++ b/thermocepstrum/setup.py @@ -0,0 +1,27 @@ +import setuptools + +with open("README.md", "r") as fh: + long_description = fh.read() + + +setuptools.setup( + name="thermocepstrum", + version="0.1", + author="Loris Ercole, Riccardo Bertossa", + author_email="lercole@sissa.it", + description="Cepstral analysis of heat current time series in single and multicomponent substances", + long_description=long_description, + long_description_content_type="text/markdown", + url="https://github.com/lorisercole/thermocepstrum", + install_requires=['numpy','scipy','matplotlib'], + packages=setuptools.find_packages(), + classifiers=[ + "Programming Language :: Python :: 2.7", + "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", + "Operating System :: OS Independent", + "Intended Audience :: Science/Research", + "Natural Language :: English", + "Topic :: Scientific/Engineering :: Physics", + "Environment :: Console" + ] +) diff --git a/thermocepstrum/utils/blocks.py b/thermocepstrum/utils/blocks.py index c5e8dca..4dd62cf 100755 --- a/thermocepstrum/utils/blocks.py +++ b/thermocepstrum/utils/blocks.py @@ -15,10 +15,13 @@ matplotlib.use('Agg') import matplotlib.pyplot as plt from matplotlib.backends.backend_pdf import PdfPages -plt.rcParams['figure.figsize'] = (16, 9) +#plt.rcParams['figure.figsize'] = (16, 9) plt.style.reload_library() -plt.style.use(tc_path+'/grafici_belli.mplstyle') -plt.rc('text', usetex=True) +try: + plt.style.use('./grafici_belli.mplstyle') +except: + plt.style.use(tc_path+'/grafici_belli.mplstyle') +#plt.rc('text', usetex=True) c = plt.rcParams['axes.prop_cycle'].by_key()['color'] from matplotlib.ticker import MultipleLocator import math @@ -406,11 +409,11 @@ def plt_hist_single_psd(data1,dof,nbins=None): def plt_psd_with_zoom(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=None,inset_maxTHz=None,inset_maxk=None): #plt.axes([0,1,0,1]) fig_r,ax0=plt_psd(jf,j2,j2pl,f_THz_max,k_SI_max,k_00,nyq) - coord_f=[0.2,0.55,0.3,0.3] + coord_f=[0.23,0.55,0.3,0.3] ax=fig_r.add_axes(coord_f) inv=fig_r.transFigure # + ax0.transData.inverted() - f_x=0.73 - f_x2=1.3 + f_x=0.72 + f_x2=1.25 f_y=0.87 f_y2=1.35 print inv.transform((coord_f[0]*f_x,coord_f[1]*f_y)) @@ -436,7 +439,7 @@ def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=No fig_r=None if plt_figure: - fig_r=plt.figure(figsize=(3.8,2.3)) + fig_r=plt.figure(figsize=(3.4,2.0)) if axes is None: axes = plt.gca() @@ -454,9 +457,9 @@ def plt_psd(jf,j2=None,j2pl=None,f_THz_max=None, k_SI_max=None,k_00=False,nyq=No axes.set_ylim(0,k_SI_max) axes.set_xlim(0,f_THz_max) if plt_figure: - axes.set_xlabel('$\omega/2\pi$ (THz)') + axes.set_xlabel(r'$\omega/2\pi$ (THz)') # axes.set_ylabel('$^{\ell M}\widehat{S}\'_{\,k}$ (W/mK)') - axes.set_ylabel('(W/mK)') + axes.set_ylabel(r'W/(m$\,$K)') idxnyq=int(nyq/jf.freqs_THz[-1]*jf.freqs_THz.size) if nyq != None and nyq < f_THz_max: axes.annotate("", xy=(nyq, (k_SI_max-jf.fpsd[idxnyq]*jf.kappa_scale*.5)/7+jf.fpsd[idxnyq]*jf.kappa_scale*.5), \ From 85c72ee19bef9352972538efadf923cadcc7ea61 Mon Sep 17 00:00:00 2001 From: Loris Ercole Date: Fri, 15 Mar 2019 00:13:25 +0100 Subject: [PATCH 16/19] Update Example 1 single component silica. Renamed examples folder. Preparing to clean examples directory. --- .../example/example_cepstrum_silica_API.ipynb | 547 -- .../example/example_cepstrum_silica_old.ipynb | 647 -- .../{example => examples/data}/Silica.dat | 0 .../example_cepstrum_singlecomp_silica.ipynb | 7578 +++++++++++++++++ .../tobedeleted_Blocchi_due_componenti.ipynb} | 0 .../tobedeleted_Test_due_componenti.ipynb} | 0 6 files changed, 7578 insertions(+), 1194 deletions(-) delete mode 100644 thermocepstrum/example/example_cepstrum_silica_API.ipynb delete mode 100644 thermocepstrum/example/example_cepstrum_silica_old.ipynb rename thermocepstrum/{example => examples/data}/Silica.dat (100%) create mode 100644 thermocepstrum/examples/example_cepstrum_singlecomp_silica.ipynb rename thermocepstrum/{example/Blocchi_due_componenti.ipynb => examples/tobedeleted_Blocchi_due_componenti.ipynb} (100%) rename thermocepstrum/{example/Test_due_componenti.ipynb => examples/tobedeleted_Test_due_componenti.ipynb} (100%) diff --git a/thermocepstrum/example/example_cepstrum_silica_API.ipynb b/thermocepstrum/example/example_cepstrum_silica_API.ipynb deleted file mode 100644 index e4bc4f8..0000000 --- a/thermocepstrum/example/example_cepstrum_silica_API.ipynb +++ /dev/null @@ -1,547 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Example: Cepstral Analysis of solid amorphous Silica\n", - "## WITH API" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import scipy as sp\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline\n", - "from sys import path\n", - "path.append('/u/cm/lercole/software/scripts')\n", - "import thermocepstrum as tc\n", - "plt.rcParams['figure.figsize'] = (16, 9)\n", - "c = plt.rcParams['axes.prop_cycle'].by_key()['color']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Load trajectory\n", - "Read the trajectory file, selecting the desired columns." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "# Solid Silica - BKS potential, melted and quenched\n", - "# 216 atoms, T~1000K, dens~2.295g/cm^3\n", - "# NVE, dt = 1.0 fs, 50 ns, output_step = 1.0 fs\n", - "# Temperature = 1065.705630 K, Volume = 3130.431110818 A^3\n", - "# LAMMPS metal units\n", - "c_flux1[1] c_flux1[2] c_flux1[3]\n", - " #####################################\n", - " all_ckeys = {'flux1': array([0, 1, 2])}\n", - " #####################################\n", - "Data length = 100001\n" - ] - } - ], - "source": [ - "jfile = tc.io.TableFile('Silica.dat', group_vectors=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " ckey = {'flux1': array([0, 1, 2])}\n", - " step = 100000 - 100.00% completed\n", - " ( 100000 ) steps read.\n", - "DONE. Elapsed time: 1.46912622452 seconds\n" - ] - }, - { - "data": { - "text/plain": [ - "{'flux1': array([[ 91.472925, 630.61992 , 199.16002 ],\n", - " [ 71.403952, 666.80601 , 274.30247 ],\n", - " [ 47.754737, 678.10914 , 305.95706 ],\n", - " ..., \n", - " [ 466.489 , -360.14259 , -47.286976],\n", - " [ 414.3014 , -378.42595 , 166.42152 ],\n", - " [ 331.99113 , -400.35311 , 378.13009 ]])}" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jfile.read_datalines(start_step=0, NSTEPS=0, select_ckeys=['flux1'])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. Heat Current\n", - "Define a **HeatCurrent** from the trajectory, with the correct parameters." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "DT_FS = 1.0 # time step [fs]\n", - "TEMPERATURE = 1065.705630 # temperature [K]\n", - "VOLUME = 3130.431110818 # volume [A^3]\n", - "\n", - "j = tc.heatcurrent.HeatCurrent(jfile.data['flux1'], 'metal', DT_FS, TEMPERATURE, VOLUME)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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md54Pm9tB2TWTHLsKTN6lPp48A8Sus3nXQcltAS6/miDoIDl529ox7dGt9C0UK0WcHT+L\nM2NnAADXktz3m2wmtQwkbgBzb1TLHHizj2jwdEm1uzlI5hZQXbFxl/WEEAsA7gfwNIBZKaWeta8B\nmDU/PgqgsbvMbfNcp/NEBKh1x7IK+JsyySHzpZXZGPyYehG7qoJjAJg4A5SyQGbd2jGNiuwWEJxS\nH+ttwYYsk3w5ocrx7x6/G0dDR+FxeHB9+7rFoyJqsvGaOr7hn6pjnM9RooEzsmoro+aAj1tAdVcx\nuAWUlYQQIQBfAvBLUspU42NS7elxYKkjIcRHhBDnhRDnNzc3D+rbEtlbPqGOzZlk/zggHCpgspv8\ntsp21jLJp9Uxxkzhgchu1Z8Pwen6uSFyOXEZDuHAmbEzcDlcWIguMJNM9rNpduW/50fUMXHDurEQ\nHVZGtrXUGmC59W4YJFtHCOGGCpA/L6X8K/P0ullGDfOo01zLAI43/O/HzHOdzreQUv6hlPJBKeWD\n09PTB/eLENlZLqaOzUGyw6HO5WwYHOnS36j50p4wM8osVTwYuYZMsieo3gTzcWvHtEc3kzdxLHQM\nXnO91OnoaVzbZpBMNrPxGhCcAabuBrwRZpKJrGBkWztbA+r9r1oCysbgxzQM2LjLGkIIAeBPALwq\npfzthof+FoDuUP1hAH/TcP5/Mrtcvx1A0izL/hqAHxJCjJsNu37IPEdEQEOQ3KafXWDKnhnEjNlM\nTK+bjh5XWe8h3c/XdrIx9W8PqL2zA5P158mQWM2u4kiovq3ZicgJrGZXUa6WLRwVUZPN14CZ16nX\n2cQpBslEVjAy7TPJ7oA6lphNbouNuyzzLgA/BeC9QogXzf/+MYDfAPCDQogrAP6R+TkAfAXAdQBX\nAfwRgH8BAFLKOIBfA/Cs+d+vmueICFCdrYHWTDKgsol2DI7S5trjsLlu2ulS2Ri7NhkbNo2ZZMAM\nkofrsrmSWdkRJM8GZlGVVWzlbXjThw6v5G1g7KT6ePwUEGe5NdHnX/08PvTlDyFlpHb/4oPQqdza\n7VdH7mHeXsU4VPsku6wegCalPAdAdHj4fW2+XgL4aIfv9WkAnz640RGNkE7l1vrc+oXBjqcXOpMc\nmqufi8wDKQbJd8zIAaXczueDf3yoguRipYhYIYb54Hzt3FxQPVfWc+u1j4ksVSmpZoO6Od7YCeDS\nV1SXftFp+kM02qqyit94RuW/fuv8b+Hhdz7c/x/aMUjWmeRc/8cwbKRUQTLLrYloZOVigMPdfj1O\ncMqea5LT64A3CngC9XPhefvu6TxM9L93SybZhhUFHaxl1fOgMUieDaiqg/UsO6CTTaTXAEggYlY8\nBKfVpLOYtnRYRFZ6YeOF2sfPrD4zmB9qZNrPgdw+dSzlBzOOYVIx12mzcRcRjax8HAhMtM9cBKZU\n9+uKzdZxZtbqpdZaeB5Ir1gznlGiM8aNW4IFJoeqcddKRj0PmsutAWAjZ9Mtzejw0ctDakGyeWPK\njjcmiQZEB8kfvvfDuJ25jdwgsri7ZZLLLLduwSCZiEZeIQn4ou0f05M2uwVI6bX6Ps5aZF4F9Fw7\ndGeK5hqwxudEYFL9basVa8a0R6tZFXw0ZpKj3ii8Ti/Wc8wkk03ovccbM8mAPZslEg3I9e3rmAnM\n4P6Z+9XnyQE0s9t1TTLLrVvojt8styaikVVIdQ6S9bpUu03a0mv1ztaa/pzNu+5MIamOO4LkCUBW\n64/ZnM4WzwRmaueEEJgNzLLcmuwjZVa+6CDZrtdbogG6nryO09HTuGv8LgDAlcSV/v9QIwu42wTJ\nLh0ks9y6RaWojswkE9HIKqbU/pztBMySW7tlkrNb9ayLxiD5YBR0JrnhOaEn70PSvCuWjyHiicDT\n9OY9E5hhJpnsI7WiJuG+MfV5LZO8ad2YiCwkpcSN5A2cjp7GsdAxeBwe3Ej2ueO7lD1kkhkktyib\nQTIzyUQ0sgrJnQFRIz15y28Pbjy7KRXUnoWBiZ3ndfk1J5h3RmeLG2+c+M09tO12s6SDWCGGSX9r\nt/YJ3wTiheH4HegQSK8B4bl6PwiuSaZDbj23jlw5h9PR03A6nJgOTGMj3+c+EuUiAFkPiBsxSO6s\nUlJHZpKJaGR1K7f2m0FywUZBsg7UmoNkPcFkkHxn9JrkxiBZPz8KA9qz8g7F8jFM+adazo/7xrFd\ntNFzmQ637CYQqi8JgNuvOuyy3JoOqaX0EgDgROQEAGDaP42tft800uuN3YHWx7gmuTOWWxPRyOtW\nbm3HTLIu+W3e17m2ns/irYrs2A18LwopNVF3uurn9POjOBxrkmOFGCZ9rZnkcd84ksUkKkPSgIxG\nXLtlI4FJBsl0aDVv3zfln8Jmvs83vnUA7OkSJLO7dSs27iLa6Zu3volfe/LXYOjW7zTcykV18e+U\nSfZGAAh7ZpL9TZlkp1sF9VZmkjcvA//5zcBf/ARQrVo3jjvRrtu5LscfkkzyVn6rfSbZOw4JyWwy\n2UN2s/VmX3Ca1TB0aOkgeTaolk9N+aewle93JtkspW6bSTbPMZPcqrYFlNvacQwQg2Tq6hPPfAJf\nuPwF/M5zv2P1UOggFNps99PI4VCP2SqTbGaKm8utATXBtHI931f/jSpBuvoI8MqXrBvHnSgmWysL\nauXW9s8kF8oFZEvZjmuSATBIJutVq+pa1pxJ9o/b66Yk0QCtZdcQ9UbhN7tKT/mnkDJSKOrS3n6o\nlVu3WZPsdAPCyTXJ7dTKrZlJJkLGyGAzp+5wP77yuMWjoQPRbv1pM/+YvSZtncqtAbUu2apSRSMH\nLD4BfO//osZ27VFrxnGn2mWS3QE1USjaP5McK6ibKO3KrcfM5QNs3kWWK2wDstIaJPsiQ3EzapTF\n8jEuybDIem4dc4G52ufTAfX6iOX7uIyqlkluEyQD6v2PQXIrllsT1Z1fP4+KrOD+mftxK3WLJdej\nQAe/nTLJgCphtlUmuUO5NWDter5bT6ryozM/AJx8F3BzSG8kFVKt3c6FMCfv9g+SdWleu0zyuFd1\n6U4UEgMdE1ELXVIdbFoW4IsOxetsVK1n1/Hev3wv/vlX/nl/s5fU1lp2DXPBepCsl830dV2ykVXH\ndvskAyp4ZpDcio27iOqubl8FAHzwrg+iIiv937uO+q/dnrjN7JZJzsdVYylXmwuzleXWN88BDhdw\n4h3AwvcByVtAYtGasdyJTo3cvMOR4do2n6u6tLoRy63JNjoFyfp1JuXgx0T4xq1voCqruBi7iHO3\nz1k9nENnLdc+SO5rh+tdM8k+Bsnt1NYkM0gmwmpmFWPeMbxx6o0A6kEzDbFeyq3tmEkOTGAtWcDn\nnlrErVhDQ43glFrnZ0XTrM3XgMm7AE8QOPIWdW7j1cGP4061K7cG1LkhKLfWAXDU2/o7jHlZbk02\nUQuSm8uto0C1xG66Fvn6za/jRPgEXMKFV2KvWD2cQ6VQLiBZTGI2MFs7p29sJop9rP7p1rhLn2fj\nrla1cmsGyURYza5iPjiPhcgCnMKJa9vXrB4S3SmdGexWbm23THIuBsMzhh/6nX/Av/tvr+Ch//c7\nWIqbb2DBaUBW1TZMg7Z1BZi6W308cUYd49cHP4471a7cGhiaMlAdJOuAuJHb6UbYHWa5NVlPLwsJ\ntCm3BoaiamPU6Azy9x//ftw9fjde2RquIFlKiV/4xi/gi5e/aPVQ9kXfvGxcKhPxqPeiZD+3HyyZ\n5dbttoACVIaZN61asXEXUd1qdhVzwTm4nW5M+aewkduwekh0p4ppdfSGO3+NziTbpfyvkMSVlBvl\nqsRnfuatAIBf/4qZsdXrlAcdJFdKQOIGMGkGyYEJNdmND9mNpLKhslieUOtj3sjQZJJdwoWQu83v\nACDijSBtpAc8KqImtQaETcsCGCRbZj27jkKlgFPRU7hv6j5ciF2AtMv7Xg9e3HwR55bP4eEnH0ZW\nB35DRDfnamy66Hf54XK4kDL6+N6zW7m1i2uS22LjLqK6texabYP3af90/zd4p/4rZtSxXVCk+cdU\n4GSTcqNSNo4bWRc+8p7T+P6z0/gf334Sj1xcRzJfUtunAIMPkhOLQLVczyQLobLJsSELko0uzwdf\ndCgm7tvFbUS9UQgh2j4e9oQZJJP18nF146l5j9FakGz/G1Kj5kZK9VlZiCzgnvF7kDbSQzXP+fL1\nL9c+/sbiNywcyf7UdiZoyCQLIRD1RPscJOstoLpkkm0y/7EV7pNMpKSNNDKlDI6EjgAApgJTQ/Xm\nQR0YGcDlA5yuzl9jbptjl3XJRiaBlAzgn33PMQDA+++bRbkq8e1LG9YFybEr6qgzyQAweWb4MslG\nl7KzIelunSwm25ZaaxFPpL8TLqJe5BPqBmQz3R9iCG5IjZrFlGq0uBBZqCUE1rJrVg5pT57feB7v\nOvIuuIRrKBurtsskA6r6p6/l1kZObXHYqQGV2w+UWG7dguXWRMpqdhUAMBtUDRWm/dP97TZIg2Fk\numeRgfpEzibrkl2lNAKRSRwbV4HcW46PYzLowbcvbdbHmh9wY6btW+o4vlA/N3Ea2F6qlyQNA323\n3NNmKwxdbm1FU7Q90JnkTsKeMINksl4u3n4bO51J7mdQQG3dTN5EwBXAlH+q1mFZz33sriqrWEot\n4czYGRwLH8Ot9C2rh7RnOpM80fS66H8mOa+yyB2qj5hJ7qDM7tZEAOp7j874ZwCoDd4TxQRKlZKV\nw6I7VcwA3l2CZBtlktOZNLwwMDU1UzvndAi85fgYXllOWpdJTq0ADrfap1mLHAEggewQrd3vVm7t\nDQOQtp8sJAoJZpLJ/vKJ+vWqkY+ZZKsspZdwMnISQohakDwsmeTN3CYKlQJOhE/gRORELSs+TOKF\nOELuELxNmcmIN4JUP/thlHKd1yMDqtquzD2zW1QMte2l4/CEjofnN6U90XuPjpkB07RfbVuhg2ca\nUkZ2qDLJL19Vd8fnZmd3nL/vSATXNjPIO0IAxOCD5PQqEJ7Dk2tP4zu3v6POhcy9HtPDMckCUC+3\nbrc2S2eXDXs3hEkWk7XrVDuHfU3y559exIc//Qy+c/lwLJdJG2ksZ5atHkarfLy1aRfANckW2sxv\nYiagbsBGPBH4Xf6hCZJ15vh45DhORk5iKb2EqrR31U+zWD62Yz2y1vcbm6V8587WgBkks9y6RcU4\nVKXWAINk6kDvUTfuVXe+dZDMdclDzkjvHiTbKJN86eZtAMCx+fkd5+89EkFVAq9tZNUkMzfgcuv0\nKmLhGXzkkY/go49+FC9tvgSEhzFI7lJurZ8nOttsQ1LKnsqt8+U8StXDVwVTKFXwG195Df9weRO/\n983Dsc/9w08+jIe+9BAeXXzU6qHslE+0L7d2B9T6SGaSB24jt4HpgJrb6GzysATJS+klAMDJyEmc\nDJ9Evpwfuh1IYoVYy3pkQO15399McrZz0y5AdW9mkNyqXDxUeyQDDJKpg+3iNgREbc86/UaymWOQ\nPNR6Kbe2USZ5dV1NWHzhnZPL+46ooOjCSkqVMA683HoVf+6vXz4/d/FzDUHycKxpA9C93HoIMsk6\n+N2t3BrAocwmf+PVdaSLZbz11ASeXYxjIzXaE79ytYyv3fwaAODTFz5t8WgaVCvqpmO7cmshVMn1\nEGy3NkpK1RLihXhtSRkAzAfnh2ZN8q3ULbgcLswF5moNVtdz6xaPam+6ZZLTpTQq1Up/fnAp30O5\ndcE+22DaRaXITDIRoNb5Rb1ROB1OAMCETwUpOsNMQ6qXxl3eKFQJs/VBcixu3pTx7cwUHhv3w+ty\n4OZW1pogOb2K74oy7p28Fz986ofx/MbzkIEpQDiAzBBNVLp1tx6CIFmX5EU93TPJwOEMkr/12iYm\ngx48/E/ug5TAt0e85PqlzZcAALOBWVyOX0a5WrZ4RKZCEoBsX24NqGuyjV9no0h3Vp4KTNXOzQRm\nhiYRsJ5bx2xgFk6Hs9b4Sv9OwyJWiNXmlo10ZVDfrtm6cVcnLh8gq2qbR6qrlA5V0y6AQTJ1sF3c\n3pGd0Ret7aL1gRPdgV7WJDsc5vY/1v5bZ4tllNJm8NsUJAshcHwigKVETk08BxkkF1KQRgavVjK4\nd/JePDDzADZyG1jNbwDBmeHKJHfrbl0rt7bv5F0HyToQbkdfu/pavmdTLy9v483Hx3B2Ngyf24HL\na6N9o+DuBMhTAAAgAElEQVTFzRcBAD/9hp9GoVLA9eR1i0dk0tendplkwAyS7busYRTpYLgxkzzu\nG0e8GIccggziZn4TU34V4OuS5XhhwMuO7kCpWkKymGxbbq2rf5JGn5YgGLuUW7t96siS651Ybk2k\nbBe2Me6rv6H7nD54HJ5DOdEcKb2UWwNqXbLFmeQrGxlEhBmg+VozhScmArgVz5uZ5AFODtJruO1y\nIlUt4t7Je3H/zP0AgBc2XlAl10O1JtmcmLvbBcnBnV9jQzrT0C1IPqyZ5JxRxtWNDN54NAqnQ+D0\nVAhXN+37b3kQVjIriHgieMeRdwAALmxdsHhEplqQ3CmTHFTXZhqYjbxav6uXkgHAhHcC5WoZmZL9\n/y1i+VgtSNbZ2GHKJCcK6jXRrtxaX7Mz/Xrv6aXcGmCH62Zs3EWkJIo7t1URQmDMO8ZM8jCTsrfG\nXYBal2xxJvnqRgYRmJnONt2Lj4/7sRTPQXqjg216k93Eax51N/XeiXtxeuw0nMKpslbhOSA9ZOXW\nTk/7u8PDUG5t3rSLeCMdvybsVhOuVOlw3eC7uJJCVQJvOqZuMN09G8KVdftP/u/EcmYZR0NHsRBZ\ngMfhsU8mWTcW7JRJ9rLcetB0Jlk3JQVQSwzoAM7OGjPJHqcHYU94qDLJOqBvl0kOmjdt+3azYtdy\na2/966iuYgBOt9WjGCgGydRWopDYkUkGgKgvyiB5mJXyap1Nu9LaZjbIJN+K5xAROUinp17+1OD4\nRACZYhkFZ1BtnzKoErlcDLfdLgCqs6jb4caR0BHcSt0CglNAbnju5sPIdZ4sDEG5dbqkssMRd5cg\n+ZBmkl9dVTcF7j2i/jZ3z4SwvJ1Htji66+xWM6uYD87DIRz26lSsM8ld1ySP9g0Mu9nMb0JA7FgT\nq+c8dg82jYqBZDFZC5IBFWzGCsPz3qPH2i6THHKr955sqU/vPaXs7ltAAcwkNysX6zcQDgkGydRC\nSolEMVHb/kkb844hWeQ2FUNLBzvezqWpNTbIJC/Fc5jxGBAdsoQnJtSbXKLiB2Slvr6233IxrLhc\nCLtDCJmB5InICSymFlU5ZS42PF0xu61RH5Fya/1vlBvU88Mmrm1mEfQ4MRdRE74z0+rvcGPLvjc9\n7oSUEivZlVqnX3sFybtkkhkkD9x2QfVd0c1JgYYGpTbPJOsgvjFInvBNtC233s4ZKJT61CX6DnTL\nJPc/SN6t3NoMBLkmeaeKwcZdRLlyDuVquWXv0agnyiB5mOlMWi/l1r6oys5aaCmew7TH6BjUHxlT\nb3KJinnXd1Al17kYVl0uHAnW924+GT6JxdQipH9CbZMwLAGZkelcWeDyqv1bbZxJ1uXWoS7Pab9L\nPU+GYZ3hQbq2mcGp6SCEEACAo+Pq77CyPZolhNvFbeTL+Z1Bcs4uQXICgGjbWwEA1yRbIFFMYKxp\nGU+t3Nrmu3i0KxWf9E+2ZMD/+LHreMuvPoJ//YXvDnR8vdBjnWizTj/o6WO5tZTq/blrubUZQDOT\nvBODZKLO2Zmol+XWQ01Pwnopt/Zav2/nUiKHCVexY6OxmYi62xurBckDGm8ujhWXG/Pho7VTJyIn\nkCvnEPOYd6CHpeTa6FJ2JoS5VtK+k/eUkULQHYTL4er4NQ7hQNAd7F8TGJu6vpnF6an6a2c+qiZ+\nq8nRzI6sZFcAoBYkzwZmsZnb7N9eq3uRi6sAuSFruQPXJA/cdnG7pVpOf273cuut/BaANpnkhnJr\nKSU+++QiAOBrF9aQzJcGO8hdxPIx+Jw+BFyt7z99zSTrdca9rElmJnknbgFF1DlIHvOOIWkkh2J7\nBGqjtiduj2uSSzl1UbRAoVTBeqqIqKOgAvY2JoNeOASwaZhvaIMK6s1M8nxDJvlE+AQAYMlhvjZy\n9p5k1ZRy3SsLbF4GmjJSXUuttaA7iFx5SLL7B6BQqmAlmcfp6fprfTLogdspRjZI1uWbOrs2F5xD\nRVawmbfBvrf5ROf1yIB6nVWKll1vD6PmbS4BIOAOwOf02b7cut163gnfBJLFZG1v8BtbWdyK5/BP\nHziGclXikYv2aigZK8Qw6Z+sVbo08jg9cDvc/bmx2VOQrNckj2bVzb5VSoCz8w3pUcQgmVroEhfd\nFVYb846hXC3bf7JZKQOP/RawddXqkdhLaS9BshmYWlRyrUtCg8h3LLd2OgSmQl6sFc07mwMaayq7\ngYwDOBI8Ujs3F5wDAKyjqk4MTSa5Xm79N1f/Br/wjV/Ate1r9cc9QVtnuNJGuucgedCZ5KX0Ej7x\n9CdwfXvwHZYXYzlICZyert8AcTgE5qI+rCZHc+KnAxtdMqtfk7ZYl5yPd16PDDQ0ybPvDalR07zN\npTbuG7d9kKyXvTUuidN7C+vr3LmrKtv8L993F6J+N56/Za/fKZaPtV2PrIXcof6UW+ulUD2tSWa5\n9Q4stybqXm4NwP4l1xf+Gnj0V4FPvt3ydbW20ssdVE1nby1ag76WUtkun+zSWArAbMSHlYK5JcGA\nxrpWUJOPudBcfRzBWQDAetV8U83ba0LSkZEF3AFc376Of//Ev8e55XP4xW/9IqrSDPaHIEjWk8Nu\nQu4QsuXB/R5SSvz8Iz+PP3/tz/HHL//xwH6udiuuJoInJ3a+1uejfqxuj2YmWb8v6ZLZ2YB6TW7k\nNiwbU00+0XmPZKB+45LrkgdCNydtziQDGIqtLpNGEh6HBz5nfdcHvQ2enr9dXk8j4nPhxEQA98yG\ncWXdXt39Y4VY2/XIWtAd7HO5dS/7JI/mtXLfqiy3JkLKUIFlc5CsJ6O230rlyd9Tx2oJuPEP1o7F\nTgx9B7WHIFk3mBnk/sMN1s0g2V3Ode3GPRP2YilnBskDuiESNydQU776erCwOwy/y4/1ivmmPjSZ\n5BzgCeLvrv8dBAR++cFfxmJqEU+tPqUe99h7rWSv5dYBdwDZAf4ei6lF3ErfAgB8e+nbMCrGwH42\noJreAcCx8Z0TwfmoD6up0c0kuxyu2h6rtupUnNslk+y1/3ZroyRbyqJcLbfNJEc8Eds3+UsVU4h6\noztKlWv7wZvzt2sbWZyZCUEIgbtnQ7i0lrbVUrl4Id49k+zpVya5h4o6N7eAaqtSArr0/xhFDJKp\nhS7Xae4Yqz+3dZBcSAKrLwLf98vqxbz8vNUjsg9dZtRtf0DN4nLr9ZR6c3KWMt2D5IgXixnzoj2g\nNclx8427cX9NIQRmA7NYLyYBiOFZk2xuAfXEyhN40/Sb8JOv+0lEvVF8+fqX1eOeoK1LQDNGpmVZ\nSDuDziQ/ufokAOBX3vorSJfSeGHjhYH9bEA1vQt4nJgI7rzrPx/1Yy1ZQLVqn8nyQdGNmHTgoDsX\nx4s2eC32siYZsPVrbZTo7tXNO3gAKjlg6zkOVLl189h1JjlpqBvb1zYztW3f7pkLI1Uo195XrVaV\nVSQKiR3voc0CrgAzyXbDcmuizuXWfd+77iCsvqSOJ94BzN4HLD9n7XjspJc3B80GmeSoR0KUC12D\n5OmwD0s5AQkxmIC+UkJcquY6zW/ws8FZrOc31N9uGDLJUgJGBttOJy7GLuKdR94Jj9ODt869FefX\nzquvsXm5daaU6br9kxZ0BweaSX527VkcCR7BD578QQDAjeSNgf1sAFiK53F8PNDSFGcm7EWpIpEq\njF6DqHghvmNLH7fDjbAnjG2L93tHpaRu4HUtt2aQPEj6OdHc3RpQ8x6djbWrpJFsWWaiP08ZKaQL\nJWyki7XGfWdn1XvoJZuUXG8Xt1GRlR2Nx5qFPKE+Ne7qoaJOr0kuMUjeoVJmkEyULqXhcXjgdXp3\nnB+KTPLqi+p45C3AkQeAlReAatXaMdmFvrnh7nELKMCybaA2UkUshM1sV9cg2YuqdEAOasuqQgpx\npwNOiNqde202MIv13LrKGOVtkL3aTcUAZAUXZQESEg/MPAAAeHD2QaxkV7CcWbZ1kCylRLaUrZXX\ndhN0BweaSb6+fR33TNyDaf80/C4/FlOLA/vZAHA7kcPxidabYZMhNcHZytgjowQA/9ffXsD7fuvb\nd9xYqNOWPpaXW+sbjf7W9a81XJM8UDqT3LxPMjA8meTm959akFxM4fqmutbpTPLJSRUQ6mUYVtOd\n6LsFyX1bk9zLsjNmkturGOxuTdSpY6zOJNt6vc7Ki0DkGBCcAmbuVYFT1gaNW+yglAeEE3C6d/9a\ny8utCzgRNPc37RIkT5rlpBV3eDBjLWwj7nRi3BWEQ+y8fNb2ZfVFh6NhnBn8Xq+qCoMzY2cAAA/O\nPQgAeG79OVuvSS5UCqjISk9BcsgdQtbIDmRNXrlaxq30LSxEFyCEwEJkATdTN/v+czUpJW4n8jg2\n3joJnA6pG5+b6cGuke4kmSvhz564iWubWXz15dU7+l6JQmsjpnHfuPXl1nrpRbdMsr7GMZM8EDpT\n3K7pX9gTRr6cR6lq32qLZDGJqKd9uXXKSOF2Ql3TT5iN+2bCPridAsvb9uhHUNvCypLu1j1U1DnZ\n3botNu4iMtf5tQuSzUzyoLdS2ZOtS8DM69XHY8fVMXnbuvHYidmkCW32JWyh71JbVW6dLuBYQO33\n2K279VhABfyGOzSgTHISMYcDE21eH1P+KVRkBUlv2LK/256Yr+NrZdUERpePn4megc/pw2vx1+pr\nkm3U8EXTWQZ9866bgDuAsiyjWOn/pGcls4JStYRTkVMAgJORkwPNJG/nSsgUyy1NuwBg0gySY1l7\nTP6+e7teCn1+8QAyyb7WTLLl5da6032gS+MundUq2SPTN+p0prhTkAzYe56TMlIta5J9Th/cDjfS\nRrq2zduRqLoGOB0CR8b8teDZanGz0mrXINmqcmuHQwXKzCTXVatAtQw4ekiyjBAGydSiUybZ6/Sq\nDd7tmkmWEojfBCbU5BRRM0jevmXZkGyllOttPTIAOJyAJ2xJubWUEhupIub95p38Lplk3Zio6AwN\nNJM80WbrEB1kxr3+IQmS1WThupHAmeiZ2vpVp8OJu8buwuXEZRUky6otJws6SO41k9z4//STzhqf\nitaD5OXMMkqVwWSmlhLq3/X4ROskcEqXW6ftESS/uKQC2A+97QReWU6iUKrs6/tUqhUki8nWINkO\ne97qpRfdulvr63LJHkHMqNPBV7t5jt138TAqBvLlfEuQLIRAxBNBykhhNVmA3+1ExF8vjT065sdy\nwh43YWqZ5C7l1gF3AEbVQLlaPtgf3msDU5ePmeRGurKil0rEEcIgmVp0CpIB9aZi2zusuRhgpIFx\nM0iuZZKXrBuTnZRyvW3/pPkilgR7mWIZxXIV0x4dJHfeB3cioCb9OREYzD7JhSQSTkfbrpy1INnt\nHZIgWQWM1wpbOD12esdD90zcg8vxy5A6ALVhybW+WdfrmmRgMEGybtK1EFkAABwNHUVVVrGRH8yy\nj6W4CrSOtym3Hgt44BBALGuPcuuXbm/jzHQQ7zk7jVJF4rW1/QUmaSMNCdlSgqrLrS3d+kZnkruV\nWzOTPFBpIw2v0wtPm9JRPfexa5CsS8Wbn+uAKrlOFVNYSxYwH/XtaNx3bNw+meRYPgaXw9V1j3u/\nS904ypcPeMy9ZJIB1bzroH/2MNM3eVluTYddupTuWMIYcoeQLtnzzQNxs4OsziT7ooA3CmwzSAag\nshR7CpKjlgR7cXMCP+E07+J6u5Vbqwt2BsEBZZKTKpMcmGl5qBYku9xDEiRnkBYCyXIOJ8Indjx0\n9/jdSBQT2HTI2tfaTc6c7PRSbj3IIHkls4KgO1hrCqSzJZu5zb7/bKAxk9xaNeJ0CEwEvbZp3LUY\ny+HMdKi2dnJln2sm9XtS883dce84ytXywHdkuJ68jg995UP41Iufgsz1kEl2ulW/CGaSB6Lb/ur6\nvF07XCfNm8Httq+qZ5LzmB/z7Xjs6FgAG+kiiuX9VWscpFghhgnfREv3/UYBc66SO+gbR6W82h50\nt4woM8k7Vcwbq8wk02GXNbIdt1XpW8fBg5Awg2SdSQZUNpmZZMXI9rZHsjaojtFNtjLqYhx1miW+\nXcqtPS4Hwl4X0vAPZKylfBxZhwNjgemWxybMTFHcKdQdaLu/wZZyWHWpcrz54PyOh+4auwsAcL1i\nTlDsmEk2A/egZ/dMct+yEm2sZdcwF5irfT7tV88V3dG135biOYwF3Aj72k9mpkKe2mvMaqvJAo6M\n+WtrJ/cbJOvnQvMNE32jQnczHpTPX/w8Xtp8CZ/87idxOXkDEI6uFTEQQt3AZJA8EJlSpuPNNbtn\nknWQ3NzdGqhvX7WaLGAusvMm2VGzR8HqtvVLZ2L5WNf1yED9mp0r9yFI7mWHD9dorEn+7IXP4v1f\nfD9e3Hjxzr6RLntnkEyHXbacRcDVPpiydbm1ziSPn6yfix5n4y6tlO99TTJgeSY56tCZ5M5BMgCM\nBd3YrvpVJrnPZZXJ3BYAIOKfanks6onCIRyI65vjdu9wbWSx5nICAOaCczseOhlRr6FbumrEjkGy\nLrd22SxIzq3t+HtOmzdUNvODyiTn25Zaa1Mhe2SS0wXVYGw+6kPE70LQ49x39139XGi+udu4d+yg\nFMoFfPXGV/Guo++CS7jw1dRllUV27DLdcvtZbj0gaSPdsdTX7muSa5nkNuXWYXcYWSOLjXQR89Gd\nmeQj5udrKesDv1gh1nU9MoDaHPTAr9lGtrd5kHv4M8mvxl7Fb57/TaxkV/Cvvv2vUKneQRWBziSz\ncRcdZlJK5Eq5juv8bF1unboNBGd2XgDDs0Bm3box2Ukp29sdVM0XsSTQi5kT+CB0g43u5bQTAQ/i\nFR8gK32fZKbMJjzt7uI7HU6MeccQl+Ybkd1Lro0M1jpkkmcCM/A6vVgsmZ2Bi/Z7zde6W+/y/AAs\nyCQ3BMnj3nE4hGNgQfLteK5tZ+vaeIIeJLqtSR7Qa341qSbr82N+CKG67+673NoMaDoFyf0KeNaS\nBSRzOxuyvRZ/DelSGj929sfwtvm34VvFte6l1prbz0zygHTawQMYgiDZ6JxJDrgDSBsZVKoSs01B\n8pwOkpM2CJL3kknuR7l1L0Gyyzf0meRHFh+BUzjx8DsfxmZ+E0+vPb3/b1Yrt+aaZDrE8uU8JGTn\nINnTp7b8ByG1CkR2TvYRnFYNve7kDtqo2Gsm2aJya91UKCBzKqh3OLt+/XjQg1jJnBD0eYKfMss2\nO2UhJnwTiEvzzcT2QXIOqy4nXMKJqabMuEM4cDx8HLcK5npKG2aS99Ldum9ZiSZGxUC8EMdscLZ2\nzulwYsI3ga38Vl9/NgBUqxK3t/NtO1tr4wE3Erk2nbalBL78y8B/OgVsvNrHUSo6INYZLhUk729S\nqjPJYffOwKe2vrQP17G/eXEZb//Eo/jJP3oK5Uq1dv5S/BIA4PUTr8dbZt6CG7KArL8169fCHWAm\neUBSRqrjzTW/yw+ncA7lmuSgO4isWZ6s90TXdJC8anGQLKVEvBDfPZPs7tM1u9cGpi4fUBruIPnc\n8jm8efrN+JHTP4KwO4y/v/H3+/9mFZZbE+068ezbBu8HIb0KhI/sPBecVlvY5C3eBsQOjNze1iTr\ncusBd4aNZQwEPU64ytldS60BlUleN8wJQZ+Dej3ZbncXHzCD5Ir5pm71/qy7MbJYc7kwE5iBs82N\niBPhE7ilOzLbNEh2Cid8Tt+uX+tzqa/pd5C8nlNVK41rkgG1LnkQQfJmpgijXMXxLpnksYAHqUIJ\nlWrT63r1u8Czf6TWnj3xe30e6c5MMoC+ZJJ1INGPrODvffMqAODiagp/+Vx9Sc+lxCWEPWHMB+dx\n7+S9kABe9fVw3WUmeWC67eAhhEDYE7ZtJjllpOAQjrZrqkPuEIqVPIAqpsM7M34BjwsRnwtrSWuf\nYykjhVK1tGsmWd/YPPg1yT3Og4Z8TXKikMCr8Vfx7qPvhtfpxffMfQ9e2Hhh/9+QjbuIdt9WJeQJ\nIVvKWrulRieplTaZZDNDlh1MqaOt7WcLqGp54BO3eLaIiZBHlfj2ECRH/G5sGuaEoN+ZZPP10TWT\nrBvbtckkP3FtC5/46qv2eP0YGay63JhrKrXWTkZOYim3hor5tXaTKWUQcAe6dkjVBlVuvZZdA9C6\nxnvSPzmQ7tZLcTWhPLZLJllKIJlvyiYvPqGOZx8CXvlSPXPQJ6vJAoQAZsLqBtd81IdY1thX993a\nvrcdMskHHfBcWU/jykYGD/+T+3B6Ooi/f2Wt9tilxCWcHT8LIQTunbwXAHDRtftzlI27BidTyrQ8\nVxqFPWHbLitLFpOIeCJwiNbpu86+wmFgqimTDADzUb/lmeRe9kgG+rkF1F7KrYd3TfLlxGUAwH1T\n9wEA3jj1RtxM3axVIuxZlVtAEdXWf3QKksPuMKqyevB39+5UqQDk420yyeZWPSMWJJeqbcold/2f\n9hgk62zpgMuGY1kDk0GvGSTvvt406nc3ZJL7O9aU+bxvV+oG6CDZnFy1+bv9r597Dn/wD9fx7Us2\neD4aWWyameR2joaOolQtIeZ02jaT3Mv2T0AfO6U20YHwbGB2x/kp/9RAulvXtn/q0rhr3Nw2LZFr\nWpe89BQwdgK470dVd/bY1b6NEwA20wVMBr1wO9U0ZDKkxrXdrhR8F5lSBl6nF+6mLEfAFehL6ey3\nLqkKi/ffN4f33D2Np67HUChVIKXE1cRVnB0/C0D9u89UqnhN9PA7sXHXQBQrRRQrxY6ZZAD2ziQX\nUx3ff/T1UDiKbYPkuajP8sZd+jrYa7n1wa9J3kO59RBnkq8krgBA7Vr0xqk3AgAuxC7s7xvqfZLZ\nuIsOs93KrfV2K7Zbl5xeVcfwzgwOguZWPZmNwY6nj55dexbv/ot34y9e+4ve/6dKWZXL7HWfZGDg\n65LjWQMTQQ9QzPScSU7D/L36nUmuqDvLnSZYE74JpEsZlICWIDmRNZAuqOzcn5y70c9h9qaUQ8wp\nWtYja/MhlWFedblsGyT3sh4ZUOuCPQ5P3zPJuqS6eQI47h3HdnG77xUES3H1+3Vr3DUWUJOc7ZYg\n+Rng+NuAOTWZwvorfRmjFs8amAzWsxITZvAe28f2VJ229NGlswcdJF9cSWE+6sNc1IfvPzuNYrmK\n8zcT2C5uI1fO4Xj4uPrCSgmnjSIWqz1kpFhuPRA6+B3WIDlpJNt2tgbq8zafp4Sg19Xy+HzUZ59M\nco+Nuw6+u/VeguThzSRf3b6Kce947e+sM8oXYxf39w1Zbk1UD5IDHS4iukTJduuSdZDcrnEXAGT7\nvx5wUD7+xMeRK+fwyRc/2XtGWd+N3esWUMDAO1ynCiVE/W4zk9xlb1FT1O9GWprP136vSa4aCAgn\n3B3uptb2Sna5WkqUz11Vz8F7ZsO4tG79BKxQTCErRMc7+rpkeNUXtGWQnClleg6SAcDv9iPf5yAk\nVojB5XC1lONHvBEYVaPvQfpSPIfpsBc+d+dmd7VMcrbh2pFPqGvo3JuAqbOqpG7tpb6ONZ41MB6s\nv44mzIA53q3zdgcZI9OxEVPEEznwIPnV1TReP6/+jR84qTpXf/f2NlYyKwBUFQYAIJ/AyVIZN8rp\n3W+Q2Lhx11p2DR879zH85rO/aY+lInegtqd2l674EU/EvkFyMdmxJ4a+Ho6F2i9ZmIv6sGX2LbBK\nr5lkn9MHAdGnfZJ7XZM8vDetriSu4O7xu2vLkSKeCGb8M7iR3OcN+grLrYmQLZvbqnQoY9RvLFa9\ngTx2ZRMf+P3H8fevrO58IKUmJy3l1v5xQDhGptw6UUhgKb2E+2fux3ZxG0+v9tjSXwcHe23cBQy8\n3DqZKyHic6kguYftfSI+F9Iwg/9+jlVKpGQZEUdrGZs24TWDZG9YZcIb3NxSr633v2EOm+kiMsX+\nrvncTcwMHDrd0T8SVK+lNY/PlmuSs0bv5daAykz0O0jVW5s0r5Me844BwP7Xg/VoMZ7DwmT313jb\ncuvETXWcOKUyBdOvA9YGkUmuv5Z0uXUsu/fsTbqU7vhcOOisYLFcwbXNDF4/r24YR/1unJgI4MJK\nErczqoFXY5C8UCojXS0iUdyleaRNM8lSSjz85MP422t/i89e/Cy+tfQtq4d0R/RzoVNfCQB9qT44\nKMlismO5tQ6SI4H2QfJ81AcpgY20ddnkWD4Gp3DWromdCCHgd/n7VG49+muSbyRv4HT09I5zJ6Mn\nsZha3N83rAXJzCTTIZY1du9uDdQzzoOUNyr4F//f8/ju0jY+9tevIFVoyIR0yiQ7HEBgamSCZF0q\n89P3/TQEBF7efLm3/1H/e+1nTXKfJ/aNqlWJdLGsMslGb427on43svBBCkd/s96lPJIOgYizS5Cs\nM8m+QMvewkuJHGbCXrxuTv1OOmi2ypZZDdLpjn7IE0LYHcaq22PLTHK23Hu5NTCgILkQa/v31BPC\n7WJ/O54vxrI4MdH9bzIW1OXWDddPHSSPn1LHyTP1c33Smkn21s7v1SAzydc2sihXJV43Vw+y3nA0\ngleWU7VM8pGQebM2n8DJkvo77zo5tWnjrpe3Xsa55XP4pQd+CScjJ/HpVz5t9ZDuSE/l1m57l1t3\nCvD19TDk75RJVsGhlXslxwoxjPvG2zYeaxZwB/qzBdSId7dOFpNIl9I4Fj624/yJ8AncSt3a3zdl\nuTVRPZOs2+8300GyFZ0f/+6lFaSLZfwfD70OsayBRy6s1x9MrwEuP+Brc3cyOKX2Sh4BOkh+cO5B\nnBk7g5e3eg2SzTeavXa3BgZabp0xypAS9Uxyj2uSJRwoOwP9DeaMDFJOByIdXhuAWpMMAHG3TwX5\nDZbiav/ahUk1kbkZszbwjJllbN3Whs2F5rDqdNhy8p41sl1LJpsNMpPcTGd++hkk540K1lPFXTPJ\nYa8LTodon0keP6mO0eNA8jZQ7U9ZZqUqsZ0v1QJjABjzu+EQ+w+SO3UrPuhM8g3z5tZdM/Xn3n1H\norgVz+H69hIinkg9AMvFsVBSFSM3kze7f2PduMtm5cz//dp/h9fpxY/f8+N4aOEhvLz1sv16kuyB\nnniIFQsAACAASURBVLt0q0IJe8LIl/P7a5DZR5VqBRkjs2sm2e9rX6U0b4O9kjtdI9vxu/wHW25d\nrarAt5d5kNuvdvfoc5f/fljOLANoqGgxLUQWkCgm9lfRxO7WRCpD7BCOWtOEZnpSasWb5N+9tIqF\nyQA+8p7TiPhcePZmvP6g3v6p3XYw/nEgb/M9a3t0KXEJx0LHEPaEcd/kfbgQu9DbGrF9BcmDL7dO\nmtmtcU9VvUH12N0aAErOQH/LgotpZIQDYVfnTF09SPa0lFsvJXI4Nu7HwpT6N7A6kxyrqIlSt7Vh\n88F5rDlhy7WSmVKm4828dgYWJHfJJCeN/r2WbpnbP52c6p5JFkJgzO/GduMWUPEbquJG35QaOwFU\nin2rwNnOGZASmAjUsxIOh8B4wIPYfoLkLuvTI95IbX/zg1DrIN6wzZauDrmeuLVzYppPYL5chku4\nesgk+wFZrWdsbKBSreBrN7+GHzj+Awh5Qvie2e9BVVbx4uaLVg9t33pt3AXYr0FpppSBhOzYuEtf\nDz3u9sH9nBkkW5pJ7nCNbCfgOuBMsv5ePZVbmzfwKsNXct0pSD4ZUTdB91Vyze7WRKrdfsDVee9R\nq948KlWJ5xcTeOddU3A6BL53YQLP3GgIktOrreuRNf+4akwzAlazqzgaVhe++6buQ7wQx3pufZf/\nC/UM617WJLsDgHAOtLu1LqEfd5kTxR4ad0XMINlw+PscJKeQdTi6lviG3CG4He6Wxl3lShWryQKO\njwcQ8LgwFfLidsLa7GxMqr9xt7v6M4EZbAhpu0yy3obOTpnkqqwiXoi3/XvWguQ+3nDSlQknu+yR\nXBtPwL2zu3XiplqPrEXN7szJ2wc4woYfZ/7siaZtaiaCHsT30d06V8513bbwIBtNLsVzGA+4EWro\nHnx6Wj0P13MbO7f/yifgAnA8dLS3cmvAVjekXt56GYliAu87+T4AwJun3wyXcOH82nmLR7Z/eu6y\n25pkwLreK53oDGCnTLKsqteT09U+sAt7XQh6nNZmkguxjjsqNAu4AwfbbHEvyQKXz/x/hq/kejlt\nBsnhnUGy7rqvg+g94Zpkot23VfG7/BAQA+9u/dpaCuliGW9dUJm67z01getb2Xppns4kt+MfG5kg\neaNhEnYmegYAeutWWNrDHVRNCJVNHmAmOZVXpU1jTnO8PZRbBz1OOB0CBYe/v+XWxQxyDoFgl8BM\nCIEJ3wRiDseONcmryQIqVYnjE+rvPxXyYCtj7R3qLZQREe6WvWUbTfunEUcFJQt6EHSjm7nYqXFX\nqphCWZYtW5N8K6b+Jrqcv5vxgGdnd+vkbSDasH5Nf5zc5/q1XehtnvS2T9pE0LPncmsppbq522Hi\nG3AHUKwUUa4eTNnkUiK/I4sMqC23XA6BpBHHVKAhAMjHAeHEyegp3Ezd7P6N9bXZRjekHlt+DE7h\nxDvm3wFA/S3vGr8LryVes3hk+5cyUnAKZ8dqOaAeQA9bkJwrCsiqEw5H+9eQEMLcK9ma55iUcs/l\n1gd6zTb20JtFZ5KHcF3y7cxthD3hlhtBs0E1d9zI7WNLVK5JJlJBcqfJBgA4hAMhd2jgQfL5myrI\n/d5TKki+Z9Ysb9vMqDVc6TUg3ClIHleTlSFXqVawmdusBckL0QUA2H3yBTQ07lIT6M8/vYjPP724\ne6m2LzLQNclJswQ06jQDSM/uE34hBCI+F/Lw9TlITiMrHAjskt0e844h6RA7yq3XU+qNVjdOmQ57\nsbmPjNmBkRJJVDDh9HX9sin/FCSAmM22wtDXn27Xqmb9DpLjRXWN0SX3jdxONwKuQF+D5JuxLKJ+\nN6KB3ScxYwHPzjXJmXUg1LDH/JiZSd5eOuBRKrVMcrA1SE4079+8C6NqoCIrHW/u6vMH1WzydjyH\n4+M7n3dupwPHJ70oVFM7s2T5BOAfx0J0AbdSt1Cptm+opL6JziTb57X22O3H8ObpN+8Iyk5FT+HG\ntg32ed+ntJFGyBPqWC0H1DPJdutwrZdrdMqCJ/MlyKoPcHQO7OajfssyyZlSBkbV2FO59YGuSd5L\nskBnkocwSF7NrraUWgPqprLf5cdadm3v35RbQFlPCPFpIcSGEOKVhnMTQohHhBBXzOO4eV4IIX5X\nCHFVCPGSEOKBhv/nw+bXXxFCfNiK32VY5cv5Xdf5hTyhgd9hvbiSwmTQg6Nj6uJ2elpNfK5vZYFc\nXK0biXQqt55QFzobTT72I16IoyIrtSB52j+NoDu450zyE1e38LG/fgUf++tX8NkndykB9Eb6Xm5d\nqVbw28/9Np5de7ZWbh0SOkjuLVOoO1w3d5Q+SKVCEoZDILTL1hVRbxQpVHc07toyA+JJMyiYCnmx\nlbYwk1wump26uwfJM4EZAMBWxV4TBR3w2CmTvF1QAfC4d7zt42Pesb5uAbUY2337J2084K53ty5m\n1NKAcEOZsC8KeKN9K7eOm1nsxu7WgHodJ/N7a5akqwo6ZQZ1kHwQW8lUqxK3E3kcm2j9WcenqgAk\npnwNQXIuDvjHcTJyEkbVwFquy+S0lkm2R7n1Zm4Tr8Zfxfcd+74d589Ez2Alu3LwW/MMSKbUucmb\nZvVWl53slklO5Ayg6kVVdL5ez0V9lq1J1nskt7uR2M6BX7P1c3Yv5dZDuA3UZm6z9t7dSAiB2cBs\nb0v0mlVZbm0HfwbgoaZzvwLgUSnl3QAeNT8HgB8GcLf530cAfApQQTWAjwN4G4C3Avi4Dqxpd/ly\nvmsZEqAmHYPeAuq19TTOztbf2I6O+eF2CtVpVG//FJ5r/z/7zX9+m5Rclyr76xirL2y6ZEYIgVOR\nU7t3TQUAw3xz8ATxh49dx1zEh7OzIXzxuV0mwQMot3585XH86St/ip/52s9g0fxd9hokR/xuZGR/\nM8nZ/BYAINhDkJxEVQUfZqZe7/06Za7B1OXWPTVd6wcji6TDgeguN8Sm/dMAgA1pr4mCvv7sZQuo\nA28C00TvgzvWrsM+1POin5nkxXgWJ3sotQaA8caMbcacMIWarp/h2fpjB6xWMeLfZ5AsJXDhvwFf\n+bfIXvgSgM47MhxkJnkrW4RRqeLYWOt75OyYmR33tWaSdcOcrtdqm2WSzy2fAwB839GdQfLpMbX3\n6o3UcGaT00a6a9MuALUgetAVc7vZLUjezpUgqx5U0S2T7MNGuojyPuchdyJWUEFyz5lkd+Bgb8bo\n79XTFlDDm0nezG/W3rubzQb3GSTrcms27rKOlPI7AJrrYj8A4DPmx58B8MGG85+VylMAxoQQ8wDe\nD+ARKWVcSpkA8AhaA2/qoJcgOewJD7RxV7UqcWU9jXvm6m9sLqcDJyYCuLGZBbLm+orQbPtvYGGQ\nXK1K/OX5JXz0z5/HB3//cbzt17+Buz/2VbznP30LF1b2FnzqC1vjHcKF6EKP5dbqzaEAD568FsND\nb5jDj95/DC8vJ7G83WVS5ov2vdz6C5e+UPv4tdQzEALw6zf5HsqtASDkdfU/SDYzhQF/93tuEU8E\nSVlSd17Nu9C1NZgNmeRiuYqs0aX8sp+MDJIOJ6K7ZGKnA+qNdkvaaxsMPXndSybZ5/KhWCl2L3m9\nA3oC2ymTHPFE+jbpNspVLCfyONljJnks4EaxXEXeqNQD4XDT9TM4A2T2sXatB8l8CW6ngN/t3HE+\n4lfjKpR2+Td67P8B/vLDwHN/itzfq/vmwV2C5IP4268n1et5NtJagREJmdfRSsNzMp8AAhNYiCwA\n2KWrrM0yyeeWz2HGP4Oz42d3nD8dVUHy9e3rVgzrjvUSJAfN9x27dbfW5dadxr+dMyCrPhiy83v6\nXNSHSlXWqpsGSWeSLdsCak+Nu4ZzTXKlWkG8EO/YHG02MIv17H6CZHMOwHJr25mVUpqpQqwB0O/k\nRwE0Lpi6bZ7rdJ56kCvndg2SQ+7QQPdJvp3II2dUdgTJAHBqKoTrWxkgqzJ8CLa/c2ZVkCylxC//\n5Xfxb774El5YTCDodeLdd03jX773LhjlKn7uM+dRLPc+YdcXtsbuqUdDR7GeW999P0dz4vXUUg7F\nchXff880/tHrVbD9+JWtzv+fN9LXTHJVVvHM2jP4iXt+AkdDR7Gcv4iw1wWHzvr0GCQHvS6kqp6+\ndrfOmlnAYIdMoRb1RpGsFiGB2nhimSIiPhc8LnXJ1Rlly0quSzmkHA5Ed5ksTvgmIABsiGrf9szd\nj/1kkvV1rdCn0vFEoXsmuZ/LVJa386hK9J5JNhtmJXKG6ucAtN5kDM30NZMc9btb1oXqTvV62UVb\nW1eBb/068MYfAz62htyD/zMAIHDl622//CDLrXVvgXZBcsCvJuCpTMP7p5lJnvJPIegO9hgk955J\nllLileUkLq4c7I3MSrWCp1afwjuPvrPl3+hE+AQEBG6n+1OK32/pUg9BsuvgbqwcpFQxhaA7CHeH\nbN52rgRUvTAqnZ9D9b2SB1+xsOdMsitwsDc2a+XWNlqTLCXw3J+p69oBSBQTqMpq1yB5K7+1979p\nLZPs7P51I2YYguQaqWoTD6w+UQjxESHEeSHE+c3N/uwHOWx6Lbce5Hqky+tqYtlYbg0AJycDuJ3I\nQ+qJnNVBcjENfOnngBuPAQAefXUDf/XCMv63H7gLj//Ke/9/9t47WpLzvg68VV3V3dU5vhwmDzAz\nAAgQAAEQpCgQApMirWB6RUm2tOuV1l7ZtK21d/cc25KtI8uyKFs6kigfUqZthWWQQIoCJYEACBIY\nkBjkAQaTw5uXO6eq6q7qqv3jq686Veo0GAjvnsPziJ5+/fr1q/q+7/7u/d0f/ujn7sN/+vE78KlH\njuJXP34CmxUZ3zrvQFD7UJALYBkWyWBHqVqILEDTNffKoCICnIAX1ypgGeC+/WkczEYQ9vucFe1g\nfKo9yRv1DUiqhKOpo7hz5k7klHOIClwn9MpDujVAlORKO0CU5CmROdEgOGEX9TIeiEPRNUgMY/ZI\n5xstZKKdcTfpCCEpb1XCdbtZQ83HOo5BAQCO5ZDyCchxvpuqoj4OSZ6W5brcLCPgC9jPmOenR5Lp\n+KdhepIBgyTb2a0js1Obk1yVFJMQd4Par6tOlutnPg34AsCHfhVgfRBPfBwAEHrtS6QHuA/Uht1Q\nx3eZ7NTsSbLPT/62hUrXWCupBAgpMAyD1diqC0kefgTUX72+je//7Wfw/b/9bZRGmC9thzcKb6Da\nquKBhQcG/o338cgK2dHGyNwEqLVqrg4UH+tDmA/fdD3J1VbVdkYyAJQlBT49CNHhWp+LkfXprehL\nLkjGGcbGbdOPia/ZrWF6kqmSPOU9+tU/Af7iF4H//oNAffz1NieS17C1W4dm0dbbZsHCM9otoiI7\nBN79bcTbgSTvGDZqGF+p/2sDwHLX85aMx+weH4Cu63+g6/rduq7fnc3aEKx3GG7GnmR6ADyQ6T0Q\nz8WCEFtttCo75OYN2mweN4okf+2fAqe/APzp3wOadfznJy7gQCaMX3z48EA1/n2Hs0iF/Xj0Fe8H\njbJcRtwfB8t0btv5MEn03mps2X0bQUsE/CG8sVnFoZkIBL8PLMvg1vkY3nBSIYIxQvSmRDwvlC4A\nAI4kj+D27O1ooYJIqNFRhIewW1faAQA6MCUS1GhSkuz8nughpsqyPUpyJtw5PJtK8ltEkmvGRhoP\nuh9W0lwIRZa9aXolgdGDu4DpkeSSXDJHPVkh6p/svN5uXMuTz2PFs92aFGnKokKUZJYHQn1hOpEs\nKZC1Jl8QrUgKYkF7kmzbl6zIwJlHgdt+lCjdgGnHDLcawKnPDnwLDWGaxJ61U22CYUimQD8aaglo\nC1grGmRVbZH739h/VmOrzq0xIyjJf/4y2T80HXj8zORU/5ObJ8GAwX3z91n++0JkwX3PmSCePp/D\nx3/3WfzOkxfGfq16q+6qJANvTfaKGyrNim0/MkCKXn5fyPF9d5Tkt4AkywUkAgn4PKqRdHrBxNbs\nYYK76P047eLw078OpA8D1Q3g9BfHfrmcRPb2nlF0XUgJZJ0vykNOfNHUd5zVGnh7kOSvAqAJ1T8N\n4Ctdj/+UkXJ9H4CKYcv+awCPMAyTNAK7HjEe24MHSIoEwcWK8laQ5LjAI9k3LmTOWOzl8jbpn7Or\ncN0Ikqw2gTNfBbK3As0qci/8GU5vVPD33rMC3jd4m/E+Fg/dMoPnLhU8hzeVm+WBDXIhQhK9N+ub\nzt+sSAAfwhubFRxf6LzGicU4zmxV0dZs3kMwDkCfmpp8vnQeAHAoccjs2/MHS0QRZjnPi3I4wKGk\nGofu5nSISMM4jLuNHaJ/o4qvMys5X2+Z6jHQTZLfmjFQFSOELOaBJCe5CEo+303TKwl0egVvJiW5\n0qz0uDz6EfVH0VAaU+mJvlYUEfL7kI0E3J8M0pMMGCS5vksIZ//6Se3Xjcn3JVO7dT9iQc78d0tc\nfooQz+M/bD5ESXJo7k5yyOxbT6l1diIkuSIjEwmAs1jTC3IBPBMnYZJAZ78RSOFkX2wfNuubaLZt\nCmNDBnfVZAXfPJfD33/vPiynBHz99cmR1pObJ3Esfcz2ep6PzN8wJVlW2vilL72Kl9bK+PQ3Lpjz\nwEeBrutoKA1P60aUn15Ra1RUmhXEHEYQVkQFQReSnAjxCHAsNp2ySKaEglTwbLUGOmv2xPqShwru\nugFKcn0XKF0B7vopIHsLcP7rY79k3tjb7ZRkmiw+NElut8iZ7B2Gm4okMwzzJwCeA3CUYZh1hmF+\nFsCvAfg+hmEuAHjY+G8AeAzAZQAXAfxXAL8AALquFwH8CoBTxv9+2XhsDy5oa220tJY3u7UqQtNv\nTI+i3WgTSpLb1R2ietjBHwYY33RTmrdeJWOoPvAvgWAC+dOPAwA+cpvN7GYAty3GUWy0sF31Vqms\nNCsDShVVkjcbbiS5AdUnYKfaxPGFziZ7bD4GsdXGWtFmE6Ib8pRI8qXyJSxGFhHiQ2YCrC+QJyTZ\nH/Zs7YkGOVTbhgVySn3JDYNcuSrJlCSzrEnYC/VmD0mmJGXYcTeTQsWYGx636VvqRsofRcl3cynJ\noiqCZ3nwQ4yjmLqS3HRWkqnqPY2D97WCiNV02HH2azd6epLFAhCyOLhSkjyF8C47kuyqJJ/7OlmT\n9r3ffMgcAXXrDwD5c8DOGz3fMsl0652ajNmYdSEiL+UR9iVxvWhcX5QkGwr9amwVOnRcr9rMnh4y\nuOv0egWttoYPHJ3BAwcyOL0xmf2t1qrhtdxrllZrisXIInYaO1MLwevGV1/ZxE61id/88TvAMsAf\nP7828mtJqgQduieS/FaMunRDpVVxtFuXxBYEY7aw3fmMYRjsS4dxdYxiw6goyAXPoV1Ap1VCUiXo\nuo5vX8jhr98YYcYvxVB2a+M8Mc19b/0F8nX5XuDIh4FrJ8cOSqV2a7ueZFr4Gokk7ynJby10Xf+E\nruvzuq7zuq4v6br+WV3XC7quf1DX9cO6rj9MCa+Rav1/6Lp+UNf123Rdf6HrdT6n6/oh439/+Nb9\nRm8PiC0V3zy3i5JMDm9uc5InGYTiBVcL1qNN5mhfWCNv348MEKIViE43pfn6d8nXlfuB/e9DNvcd\nHJuLmnOdrUDJqtfQlXKzPHAI9/v8yApZbNVdVARFggyywN063yHJB2fI53olb3NwDxrPndJnt1Hf\nwHKUdEfMhmYB3QeNoyTZu5U27PdBBCXJ03E5iEbgE1Wm7ED7fCssC7RqaGs6ypKCVJfdOsj7EODY\nt44kGyFT8ZB7m0nCH0OJvbmUZFERXRX9ftyInmQ3uzUwHZJ8tdDAasr759FRkh1IMl1TpxDeVZWd\nSXJVsklTv/YssPoAwHUOa2Z/+pGPkQeuPN3zLbyPB8/yE7Nbz1n0IwPkcJoIpLBZlogzx1SSyaHU\nNeF6SLv160aWxG2LcRyaiSBfb5G/55h4fut5tPW2I0meD89D1VXT2jlNPHVuFwvxIH7kzkXcthjH\nqaujax7DZBlE+Mjbzm5dlhSzGOd0PtufCdvv+VPE0EqycU+Iiog/fPYqPvnZ5/EP/8eL+OqrLqKA\nHZQGyTPwYve+EXOS158n6uz8HcD+9xFL89YrY71kTsoh5o/Bb0NoaZGCBk16RnvPbr2HdyB0XcfH\nf/ckfuYPT+H3n34TADwpycCNSX6ko032ZQY3NRqewst5Yrd2wpQDqLDxIpBYAaKzaK8+iEx7Fw8t\nOhOgW+ZjYBg49wR3wcpuDRDrm6uS3BLR0AlJ29/1We5LU5Jss6HSPu8pqfCb9U3TMu5jfdCVNBRm\nl6jBHvuRAWK3bmC6SnLdsEl6VpJ9REmuSgp0vROWRJEI8aiIbxFJpvM2nYpLBpKBBGo+Fkrz5lFV\nRFV0Leb1gx64pCkpA3b3JwUlyZNWp9qajvWihNWM988jwPkQ8vuI3dpWSTbW1AmHd2majqqd3dpJ\nSa5tA4WLwOp7ex4WVREMGARTB4DkPuDqswPfOqkWoVytabZKdEPXdRTkAmZCWaiaTpKDDbdGd08y\nAPu+ZNZHDvAei1Gvb1SxmBCQCvtxaIYQo4u74699z24+ixAXwh0zd9g+x3Obz5hoazqeu1zAA4cy\nYBgG9+xL4bX1svuIMBvQa8BLge1mU5J1XUe1WXVcYyqigqjf/Xy2PxvGWlG8obOSdV1HXsojE3R3\nL1HQNX63XsWnHz+P+w+kcctcFL/9xIi96UY2iyfciHTr3TeBzFFSIJu/kzy2+fJYL1mQCrZWa4Ds\nQz7GN6KSvGe33sM7DKc3Kji7TTaCR1+9AsA7Sb4RSjIdbbJioZL4ORaZMA9BKTrbrQGiiE5TSS5e\nBjJknuQ1/2EAwINRZ1tQJMBhJRXCuW1vG7GV3RoAFsILHnqSRdQ10ovUrYSkwn7Egpx9VXmKdutm\nu4mCXDAt40pbQ7uZgqjvdOzWHhENcmjo01WSG5oCPxhXi2+P3bpVR9k48Cf6SHJc4FGW3qKeZGOE\nWzw05/LMTg9T+QaoRl4hqdLwJHmKSrKma6i1apMlyWf/EnjslywTm7uxVZHQamtmwcsrEgKPkqiQ\n17ciyTTLweXnD4t6S4Wmw5Ik8z4WIb/PmiSvPUe+9pNkw1XAMAyw+iBRm/uCBidBknVdR0lsmbPO\ne96DKkJSJSwas6avF6UuJZncPxF/BBkh4z4GyquSvFEx3UgHs4QkX8qNT5JPbp7EvfP32o4ZAoCZ\nECmgTFtJPrNZRVlU8OAhQqzu3peC0tbx2vpoRVuacO7mBgKIknwz9SSLqghVV20nEug6cSzFAt6U\nZKWtY6OvL/kLp67j7/zeyYmPFAPI6K1mu4msB/cSBV2znzh3HbWmin/7Q8fxiXtXcGG3PlpBSJEA\nrzkWN2JOcukaKewBQDhNhJYxSXJOytmGdgEwJ6QMrSRryp6SvId3Hh4/swOWAf7D37kNRYksOl5J\n8o2wIm2UyCK+lLR+TwejKjhddVeSA1NUknUdKF41F7tTIiEetzDuvVPLyRDWPQRoyKoMuS1bzmCd\nj8xju7Ht3COuiCgrPFbTIbBsp2+RYRjsz4Rx9S1QkrcbpIhAVYmqpEBTUqi3c8PbrW+AkixqCsKM\nu00r6AvCz/pRYX1As2ZaIBNC7waTEPxvmd26apDkqOAhuMuwxxWlIUdGTBGj2K27+9smjYbSgKZr\njiO1aMpy3cv1qevA1z4FPP8Z4Kv/2PGp14zewmHs1gBJuK41RKBZsSbJvABwwsQDD6l7wook08ct\n74uNF8khbe62nod7XAUr7wHkMgnD6cIkSHJVVtHWdEuSTPsA9yfJ2n+9JHaKC133mKcxUB6Kz021\njSuFBm4xWmcWkwICHDu2krzd2MZGfcM21ZqC9jvSkKBp4dlL5PUfOESuzxOL5PelYyGHBSWOb0e7\nddU4v9gV4mpNcn0mBVKMc3rvB7Pk97+c6zzn1NUifunLr+GV62X83OdPQbML8xwRbqOJrEDv65NX\nNvHu1SSOzEbxoePkHvvGmyO0gSgN70oy6yNW6GnZrXUdKK8RYkyxcOfYJDkv5V0/42QwOYKSrJAp\nCO8w7JHkdzhOXirgXcsJPHJsDmDJweRmsltvlMmmZtfbeyBkLPIRN7t1bHrBXVKJHDST+wEAr+d1\nrOsziFfPu37rYkIwCwFOKDfLAKw3yIXwAhRNcT6wKCKKis9SbdqXCXcSWfthkuTJFxio+k2V5Kqs\nQldjaGkimUk8hJIcCXCdnuRppVvrKkKM+ybBMAzigTiqnJ+QZOPAH+9XkkM8sbu+BagoIqKaDs5D\nWmXSOBCXht1Upwgvo+r6MU0lmarDTiQ5yhtKsuLhgL/2HFDfBoIJ4OI3HNVFkyRbtKQ4IRnm0W4Y\nhY/+8U8UodTkSbJxP8QE62svGuRQly16kjdfAWZP9PQjA4T4mKRn9gT5ahHeNa7zqWjMIbYiyXTt\nPZRaAMMA6yXDbs1yPbPe98X24VLlkv1EA49K8lpBhK53yI6PZbCcCnVCw0bEK7ukH/Jd2Xc5Pi8R\nSIBjuOmT5It5HJmNYCZK1vbZaBAC77Pfr1wwVE+yPwJJlaBob80a3Y9Ky2iRsQnuKjfI+0wG3bMP\nDs1EwTDEjUDxB9+6jFTYj3//wyewWZHx0tpk73vqOhhKSTZaZHbrNXz8rkUAJLB1OSXg9Chugpbo\nLbSLggtOjySLBULak6udx+ZuB0pXzakYw0LXdeTEnCtJTgVSI9qt90jyHt5B0HUd53dquHU+hmTY\nj6yxl99UduuSBJbpJFn3Y4k33oNbb2Vginbr0lXy1VCSz+/UsBE4AKbvoGaFxaSAfL3p2mNFSbKl\n3dpDf5iuyCg22Z5+ZIrVdBibFQkt1UKJNu3Wky8w0DmblCRXJAWaQn5eTq0PpSRHAhzq07ZbQ0PY\nYyU1HoijwvFAq24qZwlh0G79lgV3tSXEdI9JyIZLg16DNwNG6kmeIkmutsja4kiSh7FbX34aYFjg\nh36H2P2ufNv2qdcKDfg5FvM2gVJ2SAh+6FTttFKSAWIVnrDdumYQYKs5yYBxLzf7SLKmkQkCTSZY\njgAAIABJREFUC4PkTVTFzp6VvYV8bjuv9zwnxDuPxfECSpL7RxECQF4mZHEuksV8LIj1okgCJUOZ\nnoT+I8kjqDQr2BVtEsP9IU8k+bJBErvX8/l4EFseJyXY4dXcqwj6gjiSOuL4PJZhkRJSpjo4DchK\nG89fKeK9hzrWUZZlnIu6LhimJ5ner40p7SfDguZI2I2Aoq072TAh0U7ns7jA48hMFKeuESJ8Nd/A\nN97cwf/ynhV87PZ5+DkWj50eI0XaAuMoyQzTwsO3zpqPH5+P443NEc4kyrAkOTA9u3XZcJR0K8mz\nx8nX3TdHeslqq4qW1rJNtqZIBVMjBHft2a338A7Dbq2JmqziyCzZDFYypLJ/MynJ62UJc7Gg5axh\nAFjgyeFUD7uEQQRjUyF6ADokObXfLDzUE7cAhQuuBx6qkG9VnBdiJ5JMSSYlnVbQFQmixlumhC8l\nBOg6sG31Hjg/sVxOyW7NgMFsmGx+VUmBrpIDwG5bGjq4S5yC3boiKajJCqDrEKEh7HGTiPljqHAc\n0Kx37Nahfrv1W0eSq+0m4h6X/2SY2NuK07p/RoCoiK7z3PvBszx8jG86JNmwQtKDtRWo3doTSc6f\nAxKrwOFHSJhTX2JzN64WGlhOCj1tFF6QCPHwyS4kOZTsBFBNCDWZXPNRO5Ic5FHrJ8mlK6RdZn6Q\nJPe4CvwhIHVwQEmeRH9piSrJocE1oGC0IqSCKSylQobdugD07UtHkoR80vnwA/Bot6YkcV8fSd6u\njHFta228un0Kx9PHHfuRKbJCdqpK8ktrJTRVzexHpjgwAZJME6CdcCPPOV5ghi3a2K1LRjE2GyZ7\nqNv7fve+JF6+VkJb0/HfTl4FxzL45H2riAZ5vHsliRdvAiU5aIRnzSQYM6gVIJNBrhbEwWKaG1pD\n2K0BoiTbzTUfFyVKkruU5Jlj5Gtfkc8r6P3oRpKTwSRKzVFI8p6SvId3EGhfz+FZsmEsJMnloGvO\nRGBaPcmKpkBp95KG9ZKERZt+ZACYZcjhtMHb2AUpgnFiYbGzuY2Dcmexy9dbZLOaPQHoGpA76/it\n9Hdzs1zTPkarQzhVkjfqG/YvoMqQ4cc+iwRc+h7Wy3Z9ydNR4XNSDslg0jyQVeUOSc5preGU5CCH\nFjhoDDcxkkyS35/Fbf/mb/DMm9fRYBmEWG9qXTwQN+Ykd+zWsWCvvTQR4iG22tYK/pRR0VqIeeiv\nBoB4eBaMrqN0EyW9jqIkMwwDgROma7e2UXkAQtIFTvDWk5w7D2SPEiVj9hiwfdr2qWSO/HBWa4Bc\nfzw9KL0FSnI0aGO3DnCoy33FI0p6+/qRAZLX0FPYnT0+Hbu1aG+3LsklMGCQCCSwnDRsz43cwOdK\nFdpzpXPWP8Sj3fpKroFMJNCjxs/FBezWmlBGTCxuf/Uf40LhTRwreJtDPG2S/OzFPHwsg3v39+7t\n+zMkmXmU33MYuzVtj7hpSLKb3dq4PmcjZA1yO5/duy+FWlPFoy9v4E9PreEH71jEjEFEb52P4dx2\nlYwymxByYg4hLuTps6eQWhp0zY/FZC9VOWYE1r25NeS5RJFGUJKnRJIr6+RrYrnzWGIF8EeBnTMj\nvSS9H90KEbFADPVWfbg559oeSd7DOwznd8jiT5XkhMFJCi5nYXMOnzo5u3VeyuMH/vwH8I+e/Ec9\nj2+UJMdZwymUoeos8m0XQhWIEdI6jVCn6hYJBgtEzHTR2D5D8XCxXNPfbcOOoBqgG7XVBhPmw4j6\no/YWPq0NVlMg635Lu7X5HuyIeoD0c0uqhM+/8XlcLl92fK9ekRfzPRXPiqRAoyRZV4dTkv0cAAYt\nX2hiduuLu3VcMoJN/uKFi2gwLMLcECSZAUm3FhVEgxy4PjdE3GnczZRR0VXEPVrHOT6EmKahpN4c\nh0VgtOAugCgT07RbOynJAFk7XXuStTYZdWSk5WP2BFEWLAp8uq5jrShiJT38Z5EM+ZGA8V7sepKF\n5MR7kqmSHLEhyZZ2690zABhip+7DQH965jApXKqd5PgQFzKTjUdFycFuXZJLiAfi8LE+LCUF7NRk\n6I38gJIc88cwH57H+eKYSnKhgf19Bc/5eBC6TsZUDY3qFtbOfBkyy+LI9lkg7z5iJy2kp5pu/cxF\nkpfS7zhYTYfQ1nRPWR79aCgNMGA85RkM5fy4AXBTkuk+Mh8jbjO389mHT8xhPh7EP/viq9B04J88\nfNj8t1vno5AVDVcLkxNCclJuKBUZAF5eK0PX/EhGetc+ema9PGyauzLc1Az4pmi3ru8Ql153YZVh\nSFF0dzSSTO9HNyU55o9Bhz5cAajd2gvu2sM7C9cKDcSCnDn3MRwkVaXdqnP10O/zg2M5b4qIR/zO\ny7+DjfoGTm6exKntUwDIPM3dmox5B5Ic0yooIoaCWwBS0FiIptGXXN8GjNEfa0aIztzqLeTA40KS\naa+1m93azSY2I8zY94cZyoTKBjAbHSR58wnyWP84CBPGjOlPffNT+I0XfgP/6pl/ZR88MwRyUm/A\nRFVSAS0AwSdgh2OH2sx8LIOQ34cmK0yMJD95lhQdHjiYxukrm2iwDCIe1cu4P44qowHNGiqSMjD+\nCQDihm2z8haMgaqijbhHVRwMg6QGlCZYFBsHmq6NNAIKIK0kkyzuAQDqOVRP/38AgBjnXKzzNHu1\nfI1Y/ChJnrudWHdrg+0UuXoTYqs9kpIcF/gOSRZcgrsm6MChBNhOSY5YBXftngFS+y2tkpIqmbZM\nAEDqACmIVq6bD1EleZx1q9howc+xCPsHHRilZgnJIEmxXk6FoOswSPIgKTiROYHX8q9Z/xCPSvJ6\nUcRyX5q5173EEqe/iPMcsesfUTXglT92/ZZsKIuSXIKqDWl59YBcrYnX1st4/+HBz2/BOA9sj9B/\n3VAanXFhLqB77STPOeOg2qwi4Av0XutdKBnBXZlwGCzDuhYDg7wPv/xDJ/DgoQz+80+8q+d6unV+\nRKXWAV4Cpfrx/NUioPkRFnpdA/PxIDiWwVpxyLV8iOCuslzGj4Rk/F7LwaE3Dho5sj70X4szx8i5\ncYS1Ki8aSrLL50yzM6rDTHzZ60newzsNm2UJi8nOghH0E5K8VXK3YExipEY3Xtx5EffP348oH8Vf\nXv5LAMTeprR1zEYDtt8XUYvI63Hkai5Eg1brppFwXdsBIoQkXys2wLEM5pNhstg52CQBMhc0LvBm\nKIwd6EZtZ1XKhDLYlWyUZKMSGgpHLPsWA5wPM9GAfWU+GENVLuO5zeeQDCRxpnAGz2095/h+vSAn\n5XoqnlVZAe9jMSOkkPP5hqv4gvQly4wwcjJkP05dLeJgNowfu3sJLbmBBst6Vi/jgTgk6Gi2yAio\n/vFPQMd+faOVZF3XUYGOuM970FNKB0pTUGBHgazK0KGPpCRP3G6t68CXfxbVtZNgdR3h7/y+49Oj\n/qj7obtojC9KHyRf54zE5u3BPjUz2XpEJTnONKD5AgBvcy0IKUBvT3TdrMkq/ByLAGdt948EODRa\n7V6r586ZTr9eHwaU5NQB8rXYcbxE+Ah06GP97YuNFlIhvyXBKspFJAMGSU4K8EMB26qR4K4+3JG9\nAxv1DWursgeS3FI1bFdlLCUHlWTAJlvCDde/i/PxGfgYHw5mjndmUjsgK2ShQx8+JdcDnnhzB7oO\nPHJ8duDf5sb4PUVV9DQjGega2XYT2a2dggHLUgvRAAc/50OIC3lqL/i+Y7P4nz/3Hnzktvmexw/P\nRsAywPntyano/UVxL3h5rQS/L4i23ns+4nwsFpOCuf55hiKSe8wDfvPF38RFto3f1fJ4bnP8884A\nGjkgYvF5zB4nY+yq9kGsdshJOQic4GppN0lya1iSvKck7+EdhPWShMVE53DURhPQfbhecLdrRfjI\nxBSZolzE1epVvGf+PTiROYE3CkR9pZugXbI1AASbBeT1GAoNl/dMleRpzEqubQFREm60ViQ91JyP\nJf1z26ddK4KZiB+FujNJbqgN+Fk//DaVvBlhxqwiDsA4dEUj9irXYlJwVJKfV8to62382vt/DX7W\nj5MbJx3frxs0XUNRKvbYryqSgrjAIxtIYpfzDdWTDJBeRokJTkxJvlYQcTAbwR1LCQiQITIMwh4C\nX4COJa6q1FG2UZKpjbBqNe5mimgoDbQZID7ECKUkfChpU+rNAoDaNvDkvwOufMv1qXTdGVVJnihJ\nvvgEcOVp1PY/iAjjA/v8Zxx72KJ81F1JrhmpslHj4EotxvlBi+5VI8DIKpDPDYkQjzgaUGx6HAF0\nbNgTDO+qyupAf343qMLcaBn3hSIDxUtjkWRaUBmH8JTElqXVGiCqUypIPqulVAhJqtCHB3u978je\nAQB4dffVwRfyYLfersjQdGCpL6tjzugnHVph1XVg/QVcDiewHF1GYOV+MpNacX6dtDE/fRp9yX/0\n6jeRPPB5nK0/MfBv9PccRTGnSrIXmEqy3TVT2yEzbbUbkylRbVZtrdYAUBYVc8zguOtcgPNhPi4M\nr9TaQNd15KU8MhZFI6fveWOzijBv/buspELDvT9NI/eWh+K7qqn4q6t/hR9ABILO4Mm1J73/HK+o\n54CwxehSus45Wa7lKvC1T5H9pws5KYd0MO3qlKDZGbTP3RP2RkDt4Z2GzbJkWpcActhgEcC1ojvJ\nCPGhidmQ6GHhzpk7cSJzAhdKFyCrMnZrZBOccRhtwjdLKCKKvKuSPKV5v7pOeksi1G7dwAq1Lc2d\nIBVBGtBgg3QkgHzdmYA0Wg3H6mA2lMWutGtpJ9QNkhyL2lehFxMOJDkQw3eZJkJcCPfM3YPbs7fj\n1M4px/frhpJcgqqrvUqypCAW5JHlYyMrySImQ5I1jfR6rqZDWE6FEOZE6AyDsEfibm5CioSKpCAm\nDG4ulChYzoSdIujGGPNI+AEgwfhQ0qZoC//q/wl86z8C3/g3rk+VjOv5plCST38RCCZQTSwhFkwS\nW/S5x2yfHvF7SFmmtmqj8IZQiii6hcE+0bWiCB/LOOY22CFhKMlNzqGPWiDq6CT7kmuyYptsDRAl\nGei6L/LniX165taB5+q6DlmVey2o4SwpsHWR5EmETRYbLaTC1u+72249Ew0gzRr7jAUpOJY+hoAv\ngBd2Xhh8IQ9K8nqJEIN+khwXeHAsg4LLXjKA6gZQ38Y1jsW+2D5g5X5yIN582fHbqCo4LkluNFX8\nyy+/hp/4zHP48ovrePzNdVxmPgM18CZ+66XfGgjzDAc4xILcSEneDcV5H+0GzRewPOe8+Hng08eB\nP/gA8D9+aHrhTl1wVZLFllmMDfGhsUWMlVQI10fo+7ZCQ2lAUiXMCBak0AbbVRnFRgvxQNhyzV5N\nh4ZTkmlvsYd942zxLCRVwvvZOO7RODyz8cxEWsx60MgNZBYAID3JgHOr3hc+CbzwWeBP/m7P8/JS\n3lPf90hKsqbu2a338M5BTVZQldUBkswzQZLM6YIwFx47CIXiYvkiAOCW1C04kTmBtt7G2eJZbFfI\nxjPnQJIZqYiGL4aS6HKAn5aSLFfI4msqyWIXSb6dfHWxXGcifhTc7NZK3XFznwnNQNVUy1m25Zox\nwzVqfxheTArYKsvQrNIsgzFcYdo4lDwEnuVxz9w9OFs8O9wC2wczhbG7J1lWERV4zHBh5Hw+6EOT\nZB/qujCRcLZcvYmmqmElFQLvY7EQIwe1sMMhpRs0gbQMBQ2xaTkTlhKF2o0myTK5RuIuIVPdSDF+\nlKFC06egmrRV4Nqz5P9vvuyapnzTKMltBTj/deDoR1FTG4iGZkgyqcNM46g/6n7f1HeAYKLXFpg5\nDOQvDjz1akHEQiIIPzf8Vp40lGTJ53BN015lcZIkWbXtRwY6gV5meBdVVCyUZLlNrPc9SjLDAMn9\nHds6OiR5nITrkqggaTH+SdM1lJtlkyTzPhb7g8aB3OIQ7Pf5cffs3Xhm45nBH8IJZD9xUCevGyR5\nuc9uzTAM0h5cSQPYPg0dwHWlhuXYMrBwJ3ncZQwNLXCOOyv5X3/1DXzhhevI15v4Z198FT//6GfB\n8lV84uhPoigX8eT1QRVvLh4cSUkWFdEzSfb7/OBZfrCode0k8Be/COx/P/DwvyXul5P/Zej3Miwq\nzYqzkix1rs8QFzKLiaNiOSXg+oSUZNoKNoySfGaTrJOpUMRWSa5ICipueTQU9N73cK54cedFAMC7\n+TjeqzJYr687jtgcGppm2K0tigZCEogt2ivJGy8Cl78JPPhPScjj6S+Z/5SX8q6hXcCoPcl7SvIe\n3kGgG0w/SQ74gtip2pClLoT9YTQmZGtdr68jI2QQ4kO4NUXUgvOl89ipymAYIGvXk9xWAbkCmU+6\n93UGqZI84Z7k+g75GplDvamiJCqdAIyZYwAYV5KcDgdcq/+iIpo9UlYwDywWaaO5IvmdE3H7w/BS\nQkCrrSFn9T6CcVzjWKxGyKiCd2XfBU3XcK5oM8bEA6xGFVC79QwXgsyyqLLDLU+RAI+6HpgISaY2\nrhXDxjoTIQf2kMMhpRtUSa4zLNRmzUyy7gYlCrX+cTdTRs2Y6eqWxNyNJBtAG1NKet15nfzN7v2H\nRDG8/E3Hp49DkoO+INZLVfzY7580k+hHxvoLZD05+hFUm1XyN1++B1j7ju23RHkPPcld7Rsm0oct\nleT1UldRbkjEBR5xpoE66+AomILdmijJDiQ5QO+LLpLs83d6tLsgG+rQQFpxYrnHwTMJJblQbyJt\nYbeuNCvQdM20WwPA/pDxc2xIwYOLD+Jq9SrWa30uI9ob7pCou16SwDLWbUjpcMC99agfhUvY9fkg\nay2sRleJzd8fBXLO6zvdc8ZRktdLIh59eQM/88B+PP5Pvwe//5PvxuEDF7AUWcH/de8/R8AXwGu5\nwZCzubgwVnCXVwxkCGga8Ni/AJKrwI//d+DBfwIc/Rhw8rd70tSnAVeSLCrmPjOJgMLlZAi7tSZk\nZYgxQTagrWDDKMmUJGfC1iSZ9uRvenUU0POqh7//a7nXsBhZRJaP4rjR9jHOeWcAcplkPVgE+wHo\nhHdZ4YXPEafMg58iro/zf23+U17Me+r7NtvBhupJ3ku33sM7CNRa292TTHu7VE13VTYnqSSv19ax\nGFkEAMyGZxHwBbBWXcNOVUY6HADvs7lMDQug4k+4K8nTCu4y+wdnTfsXDVBBIEIOdts2SaYG0hE/\nSqIC1WHuY12pO5KCmRDZfKyq+sWyUZGN22+w5qxkC3uVxIewzXFYMTa4w0kyKuJ8yWaMiQcUZELU\n0sFOz15NUhALcphhSVEkN2QPbCTgQ1XzT8RuTVPKKQFJhsj1JXgkyXTGZs3HwK+KiAmDpCDk94Fl\nbrySXDcIT8Tj7wIACSPkaxohPbj+XfL1/l8gm7BLUYkqJILHAJZuyAqLhiLh1NUS/uDpMUeZbRC1\nAcvvQbVVJdX5lfsJqbOxJ0f9UbS0Fppth2u7tj1IkjOHSUGur11k3WVEnhM4H4sEK6IGB5JsKsmT\nJMmqSYStEO1XknfOkKRvCxWDHp4H1sb4kiVJHrUnWWlrqMqq7fgnAEgEEuZjS35jHbWyUwJ4/9L7\nAQCPX3u89x84d5K8WZYxGwta7ovpiB/5YZXk4iWshcl7X44tEyU+exTIO5MCv8+PeCA+1hior7yy\nCVXT8bPv2w+WZXD/YQHbzTfwyL6H4WN9OBA/YDrNujEfG01JHsZuDViMbDv/V6So973/D9nfAeCu\nnyLniitPD/1+hkG1VbWdkQwQuzVVkgWbPt5hQMfKUXv/OLBUkrW2o2PiUq6OxYSAqD9sqYoPHeBG\nlWQP+8aV6hUcShwCuAAOt0gRe5zzzgDqRsiqHUmePU6KVH2tBmirwNnHgFs+RtyRRz4E7L4B1LYh\nqzJqSs2T3TrIBeFn/UOS5D279R7eQdgxFpbZWC9JDhtVNreFJ+KPTCzder22jqXoEgCAZVgsR5ex\nViMkeTZmn2wNkRAtNZhE2c1ywwsAy03ebm28B4Szpj28+zPF3G2utrW0MYKr6ED0G0pjZCW5VCGF\ngUzSgSQnyN/dqi/5OkMqyfsMQpsRMkgGkrhQcp+laYeiQdRo+AtA0q1jAo8sQw7Du+3hNvlIkEO1\nHQSa4yvJtFhACUjYT/62zbY3FYKqtFWWRYiRLe3WDMMgEuBuuJIsypQkJ1ye2UHKUOooIZgo8ueJ\nvTi5D0is9PSSWmEcJXm9oIJhVTxwMI0nzu66OmYcsfEiEF8GorOotWqEJC/dDUAHtqwLY55mr9Z2\nOqFdFBljhmmXmiwrbeRqzYGU42GQQB0V3eH7BeMamWhPsurSk0z+zexJzp2znI8MdEjywFic+BLQ\nrJhF0XGVZLq/pCxIMi0cUbs1AMzxNahgyXVtgZXYCu7I3oGvXPxKb6+jSZLtiyjbVal3j+lCJjKa\nkrwWJ5kaK9EV8lj2FlclGQAywQwKhjNlFDx1dhe3L8XNdfZb69+Cqqv44MoHAQCHEocsSfJMjLiv\nhr1/h0m3BiymeLzwOSC2BBz/eOexg99LMk/OfGWo9zIMmu0mJFWyVZI1Te8ZNeg13doJdF3x0n7n\nhoHRRK/+KfDr+4Hfuq1TbOzDlXwD+zNh2xaZ+WFHnrW82a01XcNadY3053NBhFQZy9HlyZLkhnFO\ncyLJmgIU+q79698hrp5bPkb+e+Fd5OvOG+bZr1t4cEIsEBvBbm1f3Pzbij2S/HaBVAL+6Mc8Bdt4\nQa5GNtJuK7OkSIgEyMK45WJhCXGhiZBkpa1gW9zGUmTJfGwluoK16hq2q03HfmTTAiik3e3WDEPU\n5EkHd9HDo5A07V8973n2BFC66qhgZ4yDl1MvmVtPMl0YrUhMpUYO5JGwc7o1AMsxUGs6+b1WjIAf\nhmFwJHlkrE2jKBcR8AVMoqPresdurZPRMLkhnQrhAIey6gdUiVSpx0C+3kQyxJu9nhxH7hdJ9RZ2\nZY4PYVmEIVsGdwGkL/mGK8lGT7JX6zgAJIyQr0pzCiPUSleJfREgycRTJMm71TZYVsWP3b2EfL2J\nNzbHWA82XgQW7wKAjpKcOUr+zcIaDXiYvarrxG4d6Rt9kzZIcr7zupvl3kLO0GirCENCUXM4NLI+\n0qoyQbt1vem1J1khB9vKGlE2LUAPzwN267ixn1TIjNNxe5KpU8mqJ7nUJGtut906y9RR0qOQ2/Yk\n7ocP/TAuVS6Z0xwAdJFk+/13uyJ33Ep9SIVH6EkuXsamEAfLsJgLGw6G7BHiXHApjmRCmZGV5LLY\nwktrJXzgaMeC+41r38BMaAYnMmTs2cHEQeyKuwOKVzrsh6aTPtxhMKyS3GO3ru0Al54A7viJXrLA\nBYB9Dzq2WYwLSmbsSHJNVqHp6LFbj6sk02tsx8LWLqnSUHvBjrgDgRPI+rf2HeDRnweytwIMC3z5\nfyUqZRd0XcdlF5KcjQTAMvAe4KZ4s1tvNbbQbDexL76P3I9qc+zzzgDoehpKWf/77HHytd9VdfYv\nAV8AOEiKSMgaYYa5s5YtbE6I+WPD2633lOQ93LR47F8AF/4GeObTPT0IoyJXbyIu8D2zKkmlkmwg\nVgtjN8J8GKIijp34t9XYgqZrppIMkCr79dp17FRFx2RrquKy4ZS73Rog9pRJK8n0EBFMmJ9ZT6+Y\nGd5lryZTdcIp4bqhNMwDthUETkDQF7S0w9brhmrlYDOKBDjEBR4b5cFD5IZBSpa65uoeTh7GxfLF\nkf/+BbmAVDBljiqQFQ1KW0csyCNjqAO7ynB/q4ifQ1Uzij5jWq4Ljaap8AMAw5C/bbnpbbYwz/IQ\nWD9qLIswI9uOvIkGuRs/Asq4ByKCzQZtAZqEPU5Ymy1K14iKDBgk+Yrj2DRKdIa1WyttDYWaDp1p\n4c5lovCd2RqR9MtVoHwN59mD+Nyz59FsN4l7ILYA8OEeMtsNGphiqyRLJaIg9JPk5D6A8fW8LnV9\n9Kcce/8dyO+eV12+X0hNzG7d1nSDJLunW9dktaOkUCW9D/YkmeQnUMu1qSSP2CJE59hbKcm0MEnn\nJANAQq+goMcc99EP7fsQgr4gHr34aOdBzlhzHJTknWrTVklOR/wQW22ILY9riiIDlXVs+/3ICllw\nrLFOpYz+767wMytkhMzIPcmnrpag6cCDh4gLSlIlnNw8iYeWHwLLkKPpocQhAMDlcm/hjK7Ntntm\n8QqxpXZB0RQ0282hepJ77NZn/4JkJtz244NPXLyLFMYm6LjoBiWkdunWZam3iBPixk+3zhif8U61\n9zMWFREf+7OP4eNf+TgUzVuRYruxjfnwPBhdB77+S8Qp85NfAj78q2S825lHe55faLRQk1WTJKu6\nOvCzOB+LmegQtntq2fY7//2vVq4CAFGSfX5AlXEgfgDXa9d73sNYZ1/JCFi1cZogc5T0HXcXXnQd\nOPs1w7lgnAUjWSCUBnbfNFvtvM6iHooka20A+h5J3sNNipZIKkh3/RSZq3b6i2O/ZK7WHAjEklQJ\niWAYHMu4LjwRPgId+tjVSpoYuBBeMB9bia2gpbVQauaclWSDJHORDCqS4m69mpaSzIcAPoitioRE\niEeQ7xQeTDvMhsW4DwMJY2NzUsPdKuAMwyAVTFla3+oNoxLeb0nsw2JCsFSSd9sSgpqGqNIpRKzG\nViGp0sgqQlEu9igv9HePCRwEtYloW0NOHkzqdkIkyKEB43ccM7wrX2/1hPS0WXJQKNW9242ifJiQ\nZMiWwV0AEAvyRDG7gWi0quB0Hf4h7NYxah+fNEnWNKB8DUh0KcmtGtCwP3h7VpLLa8C5r5uE+1Ku\njnab/P1m4hwCHIuLuyNeJwZ5+08v6fiVx14CYBxgGcZIorZWHUy7tWJDkikZDfVZ5jg/IcpdCrXZ\nEjAySSb3167iUvgJpSamJNM+Y6c5yeYIqKba+RwzoyrJ1wGQwDaWYUceW+hEkq3s1hGtgqIedWxb\nivqj+ODqB/HYlcfMADKzkGmTTFyTFdSbqmVoFwBkwmRP96wmVzcA6NhmNMyHuyz+1Nl59Tr4AAAg\nAElEQVRRvub47elgeuScgpfWSuBYBrcvEXX0mY1nILdlfHD1g+ZzqLK9I+70/tyIQ2F5+3Xgv7wL\n+NNP9AgKtLjmVGzuR8Qf6QSUXvgGWaesXA2L7yZfXcZmjQq67tJAyH6UjHaARIgHFBmh6hbEMZ1+\nfo5FOuzHTq33Gv7js3+MnJTDrrSLr136mqfX2m5sk7/lpSeArVeBh/5fIBAloWexJeCNP+95/hVj\n/vv+bNi8t63OmnPxoPcANzO4y9lJcLV6FQA6SrKmYiW6hLbexlZ9C7LSxi/+6ct4368/hd0RwuMA\nmGuv2c7SDx8HLN8LrD3XeWz7NNnTqNWaIntrj5LsJd0a6Lu23dA21hN2z269h5sRF/6GhA7c9mPA\nge8BLj/tqLR4Qb7eRDYySJJDfAizMfeFh1ZjRw1CMd8HvbG7Ah0WwyTEi+XLLj3JZHMOxLLQddLT\n6ohgfPLBXVLZnCW6XbGwh0dmSFX+2nMW30xA+4jsSDKtgLvZxNLC4IFF13XIIt0cnA/TS0nrWck5\ntYFMuw2m2TnY096167Xrjq9ph36STP92cYEHWg1kNB15eTiFIhzg0NApSR5TSa43zUo6AChGf3Rh\niMs9ykdQY1mEHO3W3I23W7dqCGsamKD3dOuoPwZG1ydvt65tkQ24W0kGHC3XoiKCATPYh9oNqQR8\n9hEyR/KpXwUAvLFRha6Rv4OiNXEgG8GFEUmybpDkZnw/ji2R1wzTw3fmiK2STA/o9kqygw2vbwzU\nRkmCj2WcC4lOMNSM7ZYHJXlCChntv3eyW/tYBiG/j/Qk588TSya9Lvpg25McmSXKe5XYrRmGQZgL\nj6yuuSnJET4Cf5fKIrRKKCLmuo/+yKEfQa1VwxNrT5AHXJTkHauWni5Q8ugWvGmiugkA2FbFjtUa\n6BStSs4kORVMQVKl4Wzsz/9X4As/jSuXL+L4QswsKj9+9XEkA0ncPXu3+VQaSNmvVtO12bIY8NLn\nyTXDh4HH/7X5MG0PGym4S22SUU+Hv48UwvphtF1g4yXPrz0M6LprZ7cuG066hMABf/hhCGe+gpam\nQB3z/WSjAez2Kcmnc6exL7YP+2L78NdXvbkatxpbpAjznd8DInPAiR8l/8CywJFHgEtP9VzzdP7x\nvnTYdAxZhXfNDzMKzGNw12Z9E0FfkLSwGffjSsgY8VlbwxdeuI6vvLKJ9ZKE//vPnfNmbCGVyfrk\nkDODlQdICCQtnL7+ZfI9Rz/a+7zsESB/HnkpDx/j6ynWOSHCR7yf32mA2J6SvIebEs0a6W1dfS+w\n/3uAxi6w++ZYL2mnJAucgNlYwD24yzjsjduXbFX9mg0TqyHDVzBrUzEHQJRkPoSoMf/XNbwrGJ+O\n3dogySRozOL9rt5PKoI2SY5UZbR7/14r4KlgaoAkVyQFDFUp3JTkJFGS+21E+VYVM+12T4FhOUrs\njGvVNcfXtMMASaZKcpAHWnVkdWbo+ZvRAAcZxiI+JknO11vmgRMAxDb5DHcr3otTEX8UNZZBxCa4\nCyDq940myaLSQETTPc2LpGD9YUQ1DVWLOdxjgSpVVLmiCqBBbqwgqiIETjAtmZY49dlOb+93PwO0\nFZzfrcHHkL9ps93EoZnIyEpyae0NaDqDR973AD58O1F3ClXDQZI+RBRMZXANpYFutusmPRBZWeHT\nh4g10VhH1ksi5mJBcHbp/26QKUn2o+3kwhGSE7Nb02vdyW4NEDXZVJITq53RSH2wHQHF+kiBstZR\nIMdJ/C0ZpJMWNHv+rVkaOJjycgEFFyUZAO6ZuweLkUV85aIR+kR/D5t0axoOaackp03y6DG8q7oJ\nHcBOq9JLkoMx8ncvO6/vdA2nfdmuyJ0HHvvnwJlH8cmd/4A7V8jn1mw38fT603ho5aGO5RskMZxj\nOeyKuz0vk7H7PdsqIRPHfoiolbk3TaJP77mh7NZGQKl+7STpaT30fdZPDMbJbFub4ti4qLQMkmyT\nbk3PDgs7TwGbLyN04GEAgPSlvz9WkOVsLIjdPiX5fOk8jqaO4t65e/Fq7lW0XfI/Wu0WCnIBc74Q\ncOlJ4N0/TZwxFIc/RD7bLtWU5i3Mx4MIGm1eVvfubCxohtC6wmNwF1W9GYYxz0wrhoV5rbqGr722\nhSOzEfzCBw7iybM73u+1bshloiJbFVwoDj1Evp79GlnzX/8ycOiDg4n5iRVAriBX30Q6mHbeF7sQ\n5sMjkOS9EVB7uBlx1yeBn3+WbPwr95HHtl4Z6yX7SXJba0NuyxA4AfMeZhBOYu4kQEhywBcwR+YA\nHYsVy1UwG3VRi0Jp8+DiGuIxLbs1VZKrsnWFf+UBsijmzlq+RJD3wc+xJlE0YWw+dCFzq4Cngilz\ntBLFeklCkDGq7R7s1o1We0DRzjVLyKhaT4FhPjIPjuFGUpJ1XUdRKiIlDNqtiZJcR4bhhrZyhwMc\nRGq3trErekFL1VCRFKTDXaF2ahO83jmkekE0EDeVZDvljCjJN9ZuXVcaCOmacxW7H3wIMU1DddLp\n1kawktlDSkcf0dFqFhAV0f2g+/qfAcv3Ad//aZJyfO0k1goiUiHyfU21icMzEayXJO/9m10oXz+L\ndT2D992yiIOz5G97fst4nYTxu1gQfdd0a1NJtlADMocJeTIsxBtlaXSrNUCKrwCqemhw7elGaJJK\nMiXJzra9SJBDrakS0pE5Yvs8W7s1QAok9c51NE7ib1FsIRLgejI8KEpyH0luK2CaFdTYuOs+yjIs\nPrL/I3h++3miFppKsg1JdlOSPYRA9qC6jhLLoqm1ekkyQA7fLnZrkyR7XRde+Z8Ay6Ny/JO4H6dx\nb5r8Pic3TkJURTyy+kjP0xmGQVbIDijJCYEHy2Bw3FXuTVI8P/ox4KBBMi4/BWB0JVnTNUjn/4qo\naPvfZ//k9CHbwL5xYfYk29itqZKcPvvHQHwFwpEPAwDE6jrwxC+P/HNnY4GevvqG0sB6fR2HE4dx\n5+ydqCt1y/Txbuw0SKFqrnAVgA7c/hO9T6Bn2vVT5kNbFQmZiB9B3me21ViGd0UDqDVVb7OcPQZ3\nbTe2TaGGkvm0j9i+zxWu4tTVIj562zw+dvs8NB34mzM7Dq9mA6ls349MsXAXCWx8+Y8IQa5cB+74\nxODzjL0zV9voHbHlggg/xIQaarfeI8l7uOmR3Edmidr0vHlBo6mi0Wr3kGS53anIz8aC2K7IjsEE\n9JA6CZKcETJmgBNANrEAGwbDl20r5gDIZigkERfIQuYa3jWt4C4hAaWtIV9vWivfq/eTr2snbV8m\nLvC95PTc14FfyQC/ez/qxnv2QpKLcrHn77ZekhBAC5ovQKxNDliymZWck3LIwtdTYOBYDguRBazV\nhleSG0oDLa3VM6qA2q1jht06y/hRkApDhWOEAxwk3ahQj3Fd0uuoW0mWtBaC+hAzGUFIcp1lEWOb\nvX3q3c8x0q3HDcAbBo22jIg2LEkWENM0VCZNkuvGAYMGVQlJchitbdl+i6iKzv3I+YtkduSJjwMH\nPkDSQC/8Da4VRGSNhHe5LWPVmAO6adFi4Aa2dAnb/BKWUyHoLCFer68b92+MtItYkWQ6fsa2gu+o\nJPeOgVovSaOHdgHmWljTQ85rp5Aiz22P73igBSGnOckAcYU0pCbp/bYJ7QJcSHJ0vkdJDvGjhxmV\nGi1LqzVACGIq0PX3oqMJhbRrACYAPLzyMNp6G09df8p1TrJlOGQXzF5dr2OgqpvYDpHD+lyonySv\nerJbA0PMT7/ybWDpHpya/wRYRse7G2S28OPXHkfMH8M98/cMfEs2lB1QklmWQSpsMe6K2osX7yK9\nw7FF4PI3AXQcWUORZFrUuvIUsPqAswqZOUyu1yms5ZVmBT7G1yMmdKMsKfChDX7ju8CRRxAy3rd0\nx98Fnv8McM3+7OGEmWgQ+XrLdJrQsY9Hkkdw58ydAICXd537sGnuzPzGK8Di3UD6YO8ThAQpMGx0\nXmejLGPBSO136kmmLYN0WosjFAkA42q3piFjAMz7kWk3sRJdwZv5S9B14H2HMzg2H8NySsATb+46\nvJoNqJLsBIYB7v4HZOzTn/0cMHsbcOyHB59n7Dd5cddzaBdArm1JlaBqHtZ1bc9uvYe3C3w86c/K\njU6SadhFd89l92FjPh6E2GqTSr4NJmW3zkm5nlm5FEEmBZ+/iqSFvc2EWABCafM5FTe7dSBG1BOH\nAfZDw1CSd2tN6DqsR3Mk95M+HIe+5B6SrOvAk/+eJGnunkHj2jMA3O3WaSENVVN7wpU2yhKCaLmq\nyID1rGRREdFQGsgw/EA/93J0eSQlmR6oeu3WXYE+rQaybBByWx6q5z0a5CDBuKbHUJIt7w+thaDO\noii2oLa9XT9RfwxV1ocUb09AokEOqqZDViZ4Tbqg0ZYR0nTXw0IP+BDimjb54K76DiGxQcNGyDBE\nTXZQkiVFclaSr36bfD30MDnUztwKfecNrBVFzBmtGc12E/NxY+xZebjwFV3XEW/toB0jFXz6mVza\napPwwL7xQ93wsT5ic7MLkJKKpO8saGGrpGQxfxEtVcNOVcbSqOOfAFNJriFkBv9Ygr6XCRQYaXCX\nq906yCEkbhKyaDP+CejqSfZZrG/R2Z5iyzhKcqHRQtKBJPcoyTR0Lpz1VFQ7lj6GGWEGz24827GV\nW1j1AViHQ3Yh5OcQ8vtQ9KwkbyIXJQdr2v9rIrFC1CsH0kfdQJ5mJctV4oDb9yBO1VK4ps8iW3gR\nrXYL37z+TTy08hB4dvC6sFKSASAT8Q8qyZsvk5nFqQNkLVl8txmmRZPNhxkdR0lpvXQJOPC9zk9O\nHyJ7pEPo4KgoNUuIB+I9YkI3yqKCe4LXwbTqwOoD5u8o3vsPiLDypZ+1XI/cMBsLoK3pZjGC7vf7\n4vuwEF5AzB9zHY20LZK1fH7nHHDrD1g/aeEuYLPTP71ZlrBgrM9mT7IFSc5E3SeDmGg1iIrsYHFW\n2gpyUq7jqujKCFiMLGKrsQWWAY7Nk7/Few9m8PyVgnO7ihW8KMkA8J7/Hbj3fyM2/x/9rLXQYew3\n+VbZc2gXMOQZntqtLe7Pv+3YI8lvR2SPAPlzI387DfXoUcoMUhHiQ2aV2mmDn5TduiAVLKtfnJaE\nP1C13RQAENUllDLToT0pydAnpybrukmS6WdlaYNjGGIpWnvO9sDRQ5I3XwJ2TgMf/Q0gEEfj4jcA\nAGGXXhqrqv56SUTEp4DxQIgWLZRkc/YeFxr43Jajy7hevT60CmpFkjvp1sRunTY2+WEs1wLvg0hJ\ncmv08RfUqtirJKsIgoWuE+ulF0SNnuSYz34Dp2ShdgMTruvtJiLwOfdD9YMXEGtrqNrZhEd+MzuE\nzHS/l+h8j022H65K8tpzQDjbCXuauRX67puoN1XMx4hdUVZlLCTIvTqskrxTKCGJKgIpQpKpdbou\n8eTeiRlJ/cb4oX5E+Ii93VosEjXd6m8TzhICULiA7YoMTQeWksPPijZhOEMaCKIiOVzTlCRPIPSQ\njjtzSrcGiNKckgwV08FuLasyAr4AfKwFaYzMAWLePOCNpSSLLaQsCra6rqPYLPaSZJGsmXwkOzA+\nxwoMw+Duubvxws4L0H0udmurcMg+pCP+IYK7NpAXyD0xMF81tkjeh4PVno698qQkb7xACr+rD+DM\nZhWXA7eC3TiF72x+BzWlhu9bte73zQqDSjJAQtSK/b/n5stkogS9f+bvIHPY5cpIdmv63DrLklnI\nTuhzekwSlWYFCYdpBGWxhQd54+euPGASSxE68BN/RApi/+2jriO9+kFHcNLwLrofz4RmwDCMp/nB\nW3VSqJptq8At32/9pMW7SEGrtg1d1wlJ7lOSZYt7ImOOAvNwvSui6/inXWkXOvQBJRntJuYj86gq\nuzg8G4HgJ+vNfQfSqMoq3twa8kxpOBBdwbLAR/8jGZdlVyyMzkNhWBRV0fOMZKDr2vYiROz1JO/h\nbYXMUbLYqR43wj7QEJJUqCuYyDg8CJxgkmSn1MBJ2a1zUs6y+qWpcYBzCQkylGR64HIN7qL9PM0J\nHfQVCWg3ASFp2uDs5ldi34PEfmmT2pvoJslXnyVfb/1B4OD3opEnIW3UqmkHuol2JxBvlCQkeQ2M\nTfBNN5IhHgLv6xkD1SHJ4YFD8kpsBTWlhvKQYU60b7o/uCvk94H3sURJNqqcedF7VT7k90HSqZI8\n+nVJe9u7XQyyriLIkOvMk7ULhCSrDAOBtb+P6LV7I8O7RE1BZNhRDrQneRokuX8msJuSrErOM5LX\nngNW7u8clLO3gK1vI4YGlhJkDWi2yaxZlgG2hiTJVy6TQ2FigZDwWqsGPxsAwOHMVpUo9KE0ULUn\nybbrplS0TrYGjPFSh4D8Bawb88zH60muQuMj0MCi1HBSko11cwIkuZNu7RbcxWOm5U6SaYibJaLG\ndVUnBEvgxgnuUiyV5LpSh6qpPTOSqZIYSMxgpyq7jyYE8O7ZdyMv5bFGMyUc0q1t9xgD6XDAm7IG\nALVt5APk8+tejwEAMYMoOLQ+hPgQBE7wRpJzpLCvzx7Hmc0qyul3AfUdPHnxK4jwEdw3f5/lt82E\nZlBtVdFs9/5OiVBfi5KmkZ8xd1vnsXljBOP26ZFIMg3aq/MCIdxOSO0nX10s6qOg3Cw7kuSSqOAY\nu0YKjLH53j7euRPATz1K7t/PfdhMNPeCGaMlj4Z35aU8BE4wP8MjySO4ULoATbd3Qm2L20iBRSB9\nlKxfVsjeQr7mz6MiKRBbbbOISe9vqwIXbRn0tCe3RE9Wa6Cr9aBLSZ4Pz0Njmrh1obN23XeAuCC/\nc9mDk6Ibskcl2Qt8HPLxeegAZkOzrk+noK0Ensbi7fUk7+FthfQhQG+bAS7DomAxzqLbbk0r1U6p\ngdSqMc4IKKWtoNKsWNqtm3IMbaaGVtumENBWyaIfSoPzsYgFOcc5wwA6h71JkWRaYReSZkHBtoea\nWrWM/qh+9CjJ106Sv3F0Fpg5hrphZYu49JDS8RDdpHW9JCHBq53UVAcwDGOMgepsRjS1NBGIDZJk\nYwzUsH3JlnZrWekkQLcayPrJ32oYJTnkn4zdutKdtG1A0tsQDKuRp6o1OgcsH2f/Xmhv5o0kyXVd\nRYgZliQLxG6tNibbP13ftSDJ8+7BXXZKcj1HEnmX7+08NnMrAOAws46lZEdJ5n0sZmPBoe3WO9dJ\nUM3cMjnw1Vo1xAIxsAwISQaIBc7G3hjxR5znJFv1I1NkjgCFi6ZzxbK9wyuaVTKrFC6hhxNUkmuy\nCo5lEOSdjx7RIIcF9TopNtgVDUD2LdtRYFGD5BmuhLGCuxqtnqIyBQ2s6lWSyXodSsxC1XT3fQkw\nxx69VDKmVtiQ+a2K7Po3T4f93oK7NA1o5JH3+RAPxHtGWAEAooYjwoVUpYIpb8Fd+fNAMIFcO4pC\nowVu5V7oAL699RweWHhg8OcbSBhkoiz3FmPjgr+3MF7dIJ9buouIzd9Ovm69OlpPMh3Zlj3kThBo\nFoGNg2QclJtl2/FPALl/V/V1U2007daUWC7dDfzMX5J7/tGf9/xzaUGGOiLyYr5H1DicPAxRFbFZ\nt79GtqrXMdeUB+f7doMWwvLnO+F08V6SbFXgouGanopCSsN1RnK3Ug6AtAIBgCojxpHHZlOdNWQu\nHsT+THg4kqxpZC31oiR7xI7RMjEUSR7Fbr3Xk7yHtwXMnrfRFuOSC0mmC6NTMmfAF4CP8Y186AA6\nZK47wImi3iCLGU1GHIBcBqCbB8pEyO9utzYOhBOzW3eR5J2qDD/H2vdQpw8CsSVbkhyjJFnTSMDX\n6gPkH7JH0TAUMbfN3Yokb5QlRDnVdoRKPxb7ZiXTg0nSn7DsSQaGn5VclKzt1nQUFloNZIwgHKte\nNDsEeRYSM77dutpt/TYg6RpCxgYxjJIMALqDkmzarW9QwrWmaxChITLsZscHEdM0qLo2smXVErVt\nayW5WbUdXeKoHm6/Sr52qz7GwfEgu4nFuEGSjaDChYQwtN26vkuUolCGjK1qKA1E+DCWUyFcyhnv\nObZkO8Yq4o849CSXHEkh0oeA6gaKJbL2zIw6IxkA5CoYIQ6W6aTjWmKiJFlBNMg5t9GAFI9WtA3o\nDioyQIodttcCva6M8K5R7dZSqw1JaSMVGbxnaMGvtyc5B4BBOEkOrgPhUhZYja2S9NyK4TSyUJKV\ntoZCo+muJEf8nn4m5DKgt1FgdGSCFr2MMe8k2ZuSfB7IHsUb26RANHfoTpz3B7Cr1PC+JfvUaDr2\niI5BoiBKcqtTtKM2526SHJkhbQq7b6KhNMCxnC0Zt0LEmDDRsJnT3QM+CIRnRhYvnFCRne3WlUYT\ni8oacRnCpo939jgZi3X5m8DGi55+LrUzd9utu9vjjiTJ/elkud4pX8a86mC1Bsi1xoeB/AVzf50x\nJpvQIpgVSfZzLOIC7z24y8VuTZ1rZiHADNJroq2Q6zAo9J4f7zuQwnevFL33JbdqpO1gUkoygJ0g\nIbwDuQIOGEro0vbs1nt4O2FMklxstODnWIT8nT6ubpJMFx6n6hzDMAjz4bHs1h2VsnexqMkKZIkQ\nDBr6MACaAhuiJJn3YLemATSTV5K3KzJmYwH7wx/DkKTdK98yRzt1Iy6QlOP2zhvkMLr6XvIPM7ei\nYYQ1uAWO9Nuta7KCiqQg4vOmJANkDFS33ZoS7ngoPXBIXowuggGD69UhSbJcRNQfBd+14FYlFTGB\nIz3brTqigTgCvsBQJJlhGPj5ANqMbyy7dVVS4OfYnnAcidER5oYICUGHJGusU0/yjVWSTTWFHZJc\n8SHEjMCy6qSKTGqL2Ivp2CcKSm4a1i4Cx57kLYMkz93eeSy2CB0M9nMlpEPkYECtmwsJAZuVIV0H\n1XVoYEwSUVNqiPAR7EuHca1gXHeRGdPm248oH7U/mHSNlLOEEd7Vzl9A2O9zTYl2RLMGJhBFXLBe\nO2VVJjNQJxjcVZNVV6s1QIK7DjIbaKfsk60Bw3pva7em48SIXTjEhSApg3Pg3UAzCJyU5B6rciMP\nhFLIRsk16sV54mN9OJw8jHOl80StsXDC0HBIx4kPILOSC/WW++9p2MLzumId+BOdA8BMjiTnzwGZ\nIzizSa6jo8tZfDtN1P4HF+37fWnxt7uNCCAtSkpbh9gy9tO8MYoo3Wfpzd4C5M6hoTSGUpEBILJD\nxjbWE4veviG+OHElWdd1V7u1X9xGUJcGleR+EePOT5KpBqc+5+ln+zkW6bAfO1126+5r5VDiEBgw\njiR5Sy5gng0AC3fa/6CuVpIOSSYE3UlJBmiAm1e7tQtJlvLgWK4zaqtrJJsoksdYf+91eN+BNGrD\n9CXT86dVOOOI2PWT9zmMkkwzboayW+8Fd+3hbYHYAgBmLJKcDvt7CF3/KI1sNOBanRtqGLkFqErZ\nv/jvVJvQVPIY7REZgGFp65Bkv4c5yYaSPAFFBEAPSc7Xm+Y4Alsc+ACp3tODfBeoitq8aCTzUiU5\ndQB1nw8C47MOp+lChI+AYziT2FJFWGCUoZTkkqigYaTQlptlBHwBCEKGfG5dBD/gC2A2PDu8kiwX\nB9wDpt1alQFdAxOIICNkhp6VLPg5tBhhLLt1Ve5StQFAa0MCEOKCEHifZyWZVmoVOCnJlCTfGCXZ\nnLntIe28B1wQcSMVfmIJ15QEh/vCRuh/26TEOs5J3nqNpLl2W9l8PMq+FA74SwgY9jkaAjMbJXNA\nvRInXdcRFLcgcknzANVoNRD2h7EvHcLVvEheKzJD1iiLsUkRv0NwV7PWyU6wghEOxJcujaciA4bd\nOmbpwrlcuYwPfflDeOiLD+HFqhH2MyG7tRdin2ZqSDM1SPGDjs9zJMnhGQCMOWYsxIeg6ioUbbh7\njTqvrHqSaaF3ILgrlEE6MoQVFMDR5FGcK56DzgUtleRO7oXzPpMO+73ZvA3VLNcWLVue4OPJvVhz\nJ8k0Z8IWUpnc75nDeHOriqWkgFiQx7eFIG5tM46pvJQk9687CcO1Ze77hYuEAPYX3bJHgdw5iErD\nNdejH6H1F8DoOmpWc8st3+zSxEmypEpoaS3Tdt6PtqZjvnWV/AclyXyf3ZoiGAOOfgS4+LjnUVUz\nsSB2q9YkOcSHsBxdNkdD9aPWyKEBDXPpW1xHUCJzpIck035jnuXBsZwtSc5GPfbgKw3nEV4gv186\nmMb/z96bBsuSnuWBT+6ZlbWeU3X2u/e9t1stdWtvWkILgxBmUGATGJBFeBnHQHgIgrEYEzMYbM8Y\nE2NslhhMzBhh8AwMWGIzMC0BkkBLS63W0uq97+2++3L22rfMrNzmx5dfVmblWnVOK2hx3wjFbdWp\nJasy8/ve532e93lZxjvWAJN80OHhOjx0N7wvzd2XTEGyFD/Oa5E44DhIjoPKHNe379yey7iL9iTf\nk1vfi9dC8BJhWxaU9bRHE9RmquKzIDlPdU4V1CPJrX0mWZ4FyTpcT9qyP06QW/sgmSxQVUVIlwwC\nAbn18TPJreEkNDIoNs6+h/x743ORP1GwhFtPkOHwVdLvC07AWCqhmONWZRgGZansg+S7bW88Cia5\nmWTqlksBNu2FYgrLAFyS7ARiQ93A9nC+0RJtvR0xifHl1lRiK5VQV+pzGXcBxLxrwkpk3MOCEZJ+\nA4A5hsYyKHAy6qWcVWsAPMhvqSM5WZ3Krb+xTHIxo6IeCc+4C4gyOosfTPge9kP1krAYJtm0TZiO\nmcwk778IrL4++jDTwBbb9qV7lEleKUvQTccfTZQVhwMDNacLQ5nK2obmECWhhNN1FUPDIsyh2gDg\nTr9jIEpCKb567zgeSE5JnpbOAmBQGtzwmZaFQ+8DcjlWhfPTj/80xiYB/D/91f8dGsMeC0ge6tZ0\nrUuJNZPsbcPi6dTnpfYkc7wH8kih1TcAmnPPase0J9Hwe5JDxl0tQG347vi5+oMB3L90PwbmALui\nHOtuPStDTQoKLjIZ7NEhXACtyTAZpJY3MpnkmlxDW2+nF5q6nm9F7TSu7A9xcc/PzscAACAASURB\nVLWEntHDM+4Y7xr0U01Iqdx6VsFSUcjv6+/77WvT0U/BaNwPGD2MtHb66LiYYG8/CRUshnZO34LK\nCQKSj9G3ga63SUxyXzNxgvFUK0ukqCSyIliGjQeWp95JCketq7k+f6Uk4WBgQLM0DM1hxEH5fO18\nIpO8/fKfAgDWT7wz+4OWzwO9O2h3eyiIHNRAMS3NdK9ezCZ0AOQy7mrq4SJA0LjrRmsMzlnCwYy6\ncbUs42xdxZeuzQuSU4qhc8Y+42DFtsHk8QbwYq4JNbTYe09ufS9eM3GEimV7PIls+FEmWc7FJB9F\nbu33u0rhKu1eTwdcEUWhlMwke32t057kHHLrV9G4qzUyfOYgMYorwMrrYvuSCbviQtx+csoiezEU\nZag5+12qUtXfVCnQFVwjP5PsjV2gkuuu0SXnh/ZJamFZ3WZxEzuj/G6ZQDxI7mumP/4JACCqaCiN\nuZnkgshBh3w0JlmzwiNqTA0aw0ARFDTybsgA4HqjK5jkBPAbbdxFq8aFOWWHEBQfJB8bk6yFWyb8\n8JnkqFyZMiOxya5tAp0bsaMy7tg1rLjNKZPsJb0N37013zm93hyhwXTBlKayNirjPF0nv+nN1ojc\n64DPYgajKBYxcSZRU8LJEIA7XafiQpCB6kks6bePgUkmgLyqCOgGRkC92HoRL7RewIff8mH823f/\nW2wPt/Fn1aVjGgFl5pJbLxmk8NZVTqY+T7f09DaU0uqUSQ46/s4RlGWfLSwDBCTLnBy+HsdNQF1G\nrSCCZfIzyWcrpO/1hpQOkhsZxZHcZkajJsYMA80x4plkgBTjY67hYCzJS7AcK52R8nIVq7SJ680h\nzq+W8PTB03AAPKqNUwEblb5G5NYek9yj+373NlA7FX0Dbz0Yjg99dU+uMDVg52kUeTmfJBUgeZk5\nSh2bNW9QMiHJuKurmdhimrBZwW9VYRgm2ajutNf/ffMLuT5/tUzUNnQW9qwK7ELtAm4PbseOaLp5\n7S8AAKfO/a3sD6qfB+CCaV+LXOMKr8S+P0BAcu4RUBn7XktrJYBkHTebI6hcHbujqNv7I2eX8ZUb\nbVh2ssu3H7TYI81xLWbEvmNg1bITW3ziQuEVsAw7J5N8DyTfi9dKVLYWZpI7o2SQTBOJelF81UFy\nUk+y726oricbd80yyQURfd1MN08QVADM8Rp3sQJsTkF7NEE9xtglEmffC9z6UgTEFWUeZ5g98Nph\nFCTzItQY2WZczIJkiWfB2cYcTLI3K5kyybrXC0Udd2c2/83SJg7GBzDt/BLGltYKgWTHcTEwPGBK\nGWBRXUhuXRA56IxENsQFY5ZJdowBdJaFwhfyS7sAOBYBMWPXSmQWOJaBKnLfMJBM79eiMKfUS1BQ\nsY8ZJI/DhS4/CslM8mwxLxSdm4BjRUYGGZaNm2YNVesAPMOBZ3gYVpiVy1v4uNEcoc70IFWmks7h\nZIiiSHqSAeBmc+RJfREL9BPnU/rJU/q5cevnsW7dwepRmWRPbl0riKERUI9dewwSJ+ED5z6AR9cf\nxdnKWfx+seDPVT5KDHQrc0YyAFT0bTgugzaf3mOXKrcGyKxkryfZnx07p3kXZZKXE+TWIak14PUk\n18GxDJZUMbcb/qkyAXi3eD4RJDNMPKMdjHopp3fCqIk2R1LAyPgnGsUGcYxPCfra1L5kL1e5Y9dh\n2i7OrxTx7OGz4BkOrzcmwOGlxJcW+AJ4ho817gI8ubXrAt07QDUOJJPxQmOjO19P8t2vAY6JoljJ\n31ZGHdVT3PnnDaoMS2KSu+MJtphDGOpmSNKcyL4unyN5U07zrpWSjOZwgq5XJJsF6xdqF+C4Dq71\nroVf6Ni4fUBay07WchifeX4LSv96pHWtwBdS5dZDw4I2iXq9hGIyyjbu0uKZZNfScaM5wrK0Guvk\n/Z4LDQwMC09ez9Gb/yrIrfetEVZsG8P2Lq4e5LtWGYaByufM4Z177tb34rUW5Y2FF+JWAkjmGd43\nU2qUJIwmNsaT5OT9qCC5Z/RQFIohAyeAMMnVgoB1dTXduItX/EWvqghw3akzcWywLJG4HCeTrNTQ\n0Uw4LrLl1gD6Jx/BD61U8Z+e+NmQPK0o8Xg7S0xCfNMuL0Ysh6Jl5JJwVaTKVG7dGWOzqoCxtNxM\ncqMoQeRY3O2QRLJrdIkcnpoJjcObwIa6Acd1khn/mTAdE12jG2IuBoYF1/XcpAMguVFoYDAZROZj\npkVB5Mms5CPIrfu6GXK21j3FgyKo+aVdAPQJC9ZlMGTdaSU2Jkqy8A3rSR55jIgqzrlBcwLK3nZx\nbHLrJCZZkInJXkxPcuoYl6Yn+VsOmz3t9wzsussQHAPQOpB4yb+m5mWSt9sj1NGDUiPJsOu6GJpD\nqILqz/Xc6eoBJjkKMPzZq7PsVE4Znlk9h1PYxUrpCAmLbZFCklT23ZDpevTk7pN4y+pbUBbLYBgG\n33f++/ACD9zQ8rMUSUHdrbNCHd/FLpYwsNJ9GDRLg8ylrG2l1am7dZKZUUa0RxOwTNjt3v+b3g6D\nZNsi+4LXMkBYrnzXVl2po8AXcFtgATMGJA8NLBVEMks+7X1oL3TWNT1uoqMQwJMIktUVwow7yQwZ\nZRYzQTIv43KfXLMXVkt49vBZXKxdgAzGn6EcF7SNKGrcReXWJlkrLG3aphT6Dg1AqWE0Gc4nt779\nJQAMSmojP5NcTC6OLRpZcuvu2MQWcwjLmzZBI9HNnWFI4aCZbLYVjEZJgu242O4TYqIshten8zWy\n3r7Snnm/O1/BLXeCVaGcXsiisXQOAIPK+GYsk5wIkvP2/ptaqnGX7djELyWoqvBaOUajEcYTG5vF\nDbT0ViQnee/FBlSRw2PP5VDVBVrKjiNc18XhpIdVy8a/+t3P4n2/9Dn8yl/G94jPhiLknB1PSRD2\nCEaRr9G4B5Jfq6E2iDxvTjBg2Q4GuuVXYWnMVuT9hWeQnNwf1birY3RiF/7dno61sow1dS2FSW6H\nkmv6fXKNgTpmkEx7zpZzMMmfxhjPyRL+j5v/H55rPuc/TkDyJRjScsSdc8QAqm3nknBVperUuKuj\nYbOmkIQrp1ETyzLYqMohuXVVqgLUuCRGbg0A26N8fckdvQMXbqhaGxq55Muti/6oiXkcrhWRwxjS\nkeckB5lkzQfJRTRKEjpjE2YOWdVAtyDYPIYsm3qflmT+Gye39hJZNWXmZlIUOBkcmGOUW9N2hZgE\nXa3HMsm+3DpOYtv0EoN6+P45GOjYcb3Ep3cXEif5cmva15u38NFtHUBkbLCe3FqzNLhwURJKkHgO\n9aKE3Z6Wmiz7s1dnZyVTpjYDJPfUU1AZAyeEburzUoOy1nIZy0XSlz2e2GhqTVztXsXb16Zzpt9/\n+v0AgE8a6bLbrHBdF0Mjn7u1MrqDO+6KbyCYFLmY5NEB4NjR2bE5oz2aoFoQwbHRyQUdfYZJ1toA\nXF8NsZzXeRcEDJ4qn8ItFolMcpbUGkBA5p3dk9z1QHKic3Jxhagz9ORrbcm7f9taCkju3gEqW3jl\nYASGAc7UFbzQfAEPr7yJ9BEfJDPJACn+Jht3TaY9z3Eg2QOFI9uYj0m+9QSw8jqU5aX8ax515p9D\n9poV/oSJRLn1BJvMYeS7Uzf32KhfAA4v5yq802tuZ0DW6/LM+rRV3ILCK9G+5MuP4ZYo4lRtxm08\nKcQCUDmBhnE7cp3LvJzck+wVCw/T7jPbAmwjFSR3jA4c1wnLyb32nM6A5CVna2SyzCwpIAscvvPB\nNXz8uV30swrex8wkv3K4j4ljYtW28NaGhXecW8Yvf/oV0raYEblnx98z7roXr7nwmYr5FuO+l4xX\nlHSQXKfJY8rCc1Tjrq7ejUrVAOz1NaxXCEjuGJ34XpRxKwSS6ffJdPSUSsfrbu05WwPTXrC0+MSd\nv0LRJcnWMwfP+I8XZR6PsJexX3tzxHhkBIf0JGcYqABkI6WV57sdDVtVmVTYMwwrgkFnJduOjf6k\nnyq33iiSMThxEqS4iOtrouesLIeZZFrRPRznl1wXRA4jV1xYbu26LumPDiTympekyKLqszR5zHh6\nmgnOEdBn2Sn4j4mSzGNgfIOYZC/ZLS4wo5ERFFQY/vhGQI07xI2Wj9l41cb8cuvmFZKkzozW2O8b\nOHS9x0aHUHjFl1tXFAEix+YGyVrX60fz1l/fLdxzTd2sysQLQCwSpUvM+pzJJKf1JANoy0RSumnN\nZ5gX+1lSyZcRt4YTfG3vawAQAslr6hrexBTwFzhacXE0seG4yMUkC/3buO2spBqqOa4D3dZ9GXVs\nlNbITNJRc+r4O+fa0BlPUCvEA/uO3sGSNDP+CQBUsnYtqVK2V0YgTpZP4jbjxLpb5wXJROYtZc9K\nHjXRlsm1GLcPA5j6A6TkGdRTJNXhuncXqGzhysEAWzUFh8Y2NEvD65Zf541oupx6qGUxyiTLAgeJ\nZ0lPcpfMLo8FyQDQuIixa0HNGKPoh20Bd78KnHo0tKdmRo7fa97IAsn9fh8Npg9hOSw1V3gluSDU\nuJ/kQTmOk15ze0NSBJllkjmWw33V+8IO164L9/JjuCUpOFnNIbX2wlm+Dyec7Ugulc4kEwIgVTlB\n19qUPmDqkRNSVbAswIkYeCD5wRXyG8f1Jf+jd57GwLDwX758O/k4gOnaO6+aKyb+9NkdfN+vfwIA\nULeBDz4g41//7dfDdYFPPB89xtnIPTvevie3vhevtfB73ubr2aSAJMIkm1oo2aBMclryqAoqRtZo\n7rmTNJKY5L2ejrWK7M98i3W41tohBso38cgCyfJxyq27IZDcyJA/mo6Jpw6ewvdV7seaZeHF/af9\nvxX1XWwxTdwtR2cJDp0JVNfxe+vSoiyWYdgGutoYrdEEJyueXHGOkT90VvLQHMJxHbIpSmWAYSNy\n6zV1DRzD5Xa4polUUNJEK6+VWbn1AkxyQeQwchYHyUPDguOGi0iaBwoVqRxwjs0GVX3NBGuLGLDs\nVGIVE0Ru/Q3qSfbcL9UkeWVaCDLKDBfpDVw4Zu7hUKj1WKkyBTixssnmK5F+ZIAwyS14id2oGWKS\nGYZBoyThYJDPvdb2pLuUMaJAl7LD6xUFuz2dFLqK8UCfPjcKkr3fNYNh2OGJrLJuZCRjaWFMWetg\nQfTF1osQWRH3L98fevp3iqu4wjq43r2+8EfSloJiFkiejMGN9nHLXU0FybR4msok03FAw70jMclJ\nfcAdoxOezkDd+D0muaoI2eqmQJwsncQ2Y8GKOcbDQY4xg14QT5EsJrmJjkj2hVnzTD9yyIdz9ST3\nt4HyFq7sD3FhpYSXO0RefaF2gQC21rV0h+sEoForiKQIQZnkyonIcwDArV/EiAEKiKoBYmP/eQKs\nTj5KAHreNU+uEPYxw+xsnugZPZSEEoSEGbVOl5iiSfXTocdTpbQNb51sJsvc/afSXHBIfoNZkAyQ\n83ipfQmO6ymsDi7hoH8HXdi4r5qTSQZglE7hNLOPpUJ4jUh1t87DJPt5RTJIjh3nBgCchOFoBJFj\n8frV0wCA3WE0F3toq4p33reMX3/8eroCxuiTAip3NOnyJ1/cw4//l6exVSfr6rpQBKO3cd9KEfev\nlfDnL2a3wOVnkilIvmfcdS9eK7Egk0zHJcwyyWNrHJZb5wADqqDCcZ253UJp9IxepDpqWDaawwnW\nygrWVJLgxEqux63Q6Ji5mOTjNO4Kyq0zmOSbvZuwHAsPbL4DrzcmeOFgCpLVnScBANcKD4de47ou\nxraBopMPJFOW6mqTJOcnS94tPgeTvFUr4GBgoDXuTd+TZUlf8oykjmd5rBZWc4NkCnhDIFkjG0pZ\n4cNya2/UxDzmXQWRx9ARybiHBYKC1SDbpXnJmSKWfSY5D/PY1UwwjpQpty5+A+XWI6MP0XEhyPPL\nrSEUUHbZY2SS21MZ/2wkMMmJcmvX9UDy+chr9vsGeqwHZEaHkDgp1FNWzzETHiAGcyxdb2eZZE/G\nuVFVsNPVSOFQWYptkSh6iVrUuCtfT/KuXcXQlVEZ3cg85sTQp3LrukrVEQZear2EC7ULkYT8fepp\nMK6Lv7j5Fwt/5PTeyki0PFZwh0lnkum+k9qTHJC/0v1tbnfrkRkLkjVLg2ZpYebJZ5LJ2lUrCOhp\nJpyc0wk2ihuwARzOjBxyXReHw3xMMpCzF3rcREcQIbBCsgxZzc4zBE5ASSz547Ai4TjA8AC2uoLr\nzSHuWy3ilfYr4BgO56rnCEh2baCdXIApi+VYyXO14Dmz97eJj0GCCkNfPguHYaAaOdvTbn2J/Hvy\nUZSlMkbmKN98bYYha8Oc5EVa0DGMieHlBWx5I/RwKgCivg05xkDRa66ld8EzfGxR6uHGw+hP+rjZ\nv0keuPxxXBbJPfPA0gOZn0FjoJ5CmRljRQgfdxpI9t3c04pCgakZSUGv3whxw0vQ9RG2agrWvHU/\naTTp//T+i2gOJ/i/n7iZfixHlFqPJxZ+6o+ex4MbZfzDd5PjXRErPonxyJklvLTTz1x30n7XUDj3\nQPK9eK3FggYRFERmya2XVBEMk8Eke4PL563M0+gb/UhV8qBPPo/KrQHEm3eN2yGQXJ4LJB9vT3Jz\naIBjmchvOhu0Z+fCue/EAxZwx2j7mxh79VNouhXc4k6HXmPYBizXJnLrmJmrs+GD5BbZpDdLXuV8\nTiYZAG60Z4w6lKUIkwyQxO4ocut+8JoMgOSaVAPLsHPLrQe2AHdBJplWgIMzGrUJuV4UqTLtYc3B\nJPc0E6yrYMAyqXLr8jcSJE/6KLpOarKQGIKC8rH2JKcwycUVcr07YcfSRCZ53CJ9k8tRkHww0FEo\n1ohUbHQImZd9uTVA+pLzgOTWaIKa6/VmeiCIAl16321UZYwnNin8KLXY+8VnkmdBst+TnJ5AtUYT\nXHfXofQXZ3VDcuvi1A35UusSHliOJrWr6irephv4k2t/MmWL5oy4AlRsdG4CAA6FDQxT7guqBkjv\nSfZA8mBvYbl1nNElkDAjma7RnnFXpSASQ8mcxnwbKgE6uzMgua9bmFjOHCA5oxfacYBxCx2WRU2u\ngZmdLUyjmE+xtiwvJzPJWgdwbbSZKkzbxYWVEq50ruBM5QxETpyymimS66JQjDUJrSje6Mf+DlDZ\nTHz9qEoYZnWcs4//9hNEul3Z9Oc0DyY584biyrEyyf6EiYTghl5+RJ21vUgFQKV1ogzrZRe3VYlH\nQeTQ0/soiaXYa+XhBinuP+u5WePyY7jUOAMGDC4uRUfyJUVbJudw3QrnE2nfReRZVBQh/XrPYZZF\nZe0RJpmXYerE30XiJNSkGg7G8Xn3m0/W8L4HVvBrn7s2HU0WOZbBkUHyHz+9g9Zogv/1ex5ESz8E\ny7Coy0tE3Qjg/vUyhoaFu510AJxfbu0VIBLUDMH4wvYXcL13hL3pr1ncA8mv1fB7XxaTW1eUqLt1\nMNkQOBa1gpjek+wl2rmdHwPhuA6G5jBiArHrmQ2sVWSsFMgGHXFOdjwTq7ie5Kz+r+Nyt7YMMg/R\nY5KXVBFsjLFLMF7pvAKe5XG6dh82PTOLvdEekZld/TSeYN+C4SScgPpMFcPlAskU0N7qkOduUCw0\nh6vnpjcGir4HZb5QiGfGNoubczHJBb4QAjk0gZy6WzOAoIBjOSzLy+m9bjMxNe5aECR7YySKIZBM\nkrOCXJ2LSe5pJnhGJXLrlHukKPEYfoN6koeTAQqOkyo7SwxeQdlxj8/desZ8LxRqA4AbAZl0Q48A\nI+rUGie37htolGWPnQ7LrQHClOQ5n7s9DTVmAIfhAE9iSxP3IJMMeDPKE+4Xej9Fkm5jAIDJPDet\n0QR32E2wrWupz0sNX25d8UHyje5tDMxBLEiGXMH3DYbYHm7jSU/1Mm9QuXXmCCgPJHeljVTZIjUl\nSu1J9pnkff+amaeo67qu15OcApKDSTVlkr3iT9Xbl/L2Ja8VSWF4F+Hn552RTIMyyYmtUFoHcB10\nmRSpNUCuc5bPVKwtyUvJINkr5O9YBBicWyniSvcKzle9gtbyeSDD4booFjGcDCPfp+ox9ejdJRM/\nEmLs9aKqoxx7iesSJvkkGcVIWdz8fckrc+dladE1uqikKH9E3Ts3pbXQ4wU+BQBxPAHK/Xz7dqMk\nYWAOIvkajdOV0yiJxLEcvbvA7jO4XF7GyfLJuczSDjgCkpcn4ePKYjyXi6I/qi02AsX3pKDXb+R+\n4CWYE90fj7mqriYyyQDw4e+4gL5u4Q+/fjf+CccAkj/61dt4YL2Mt56qYW+0h7pSB19Y9pV+D6yT\n8/TSbnpB+7jl1rZj419+8V/il5/65ez3fI3EPZD8Wg1OIEzFnBXLvEwyQHpR0swQKJM8suYftzOY\nDODCjTDJuz2yEK5XZCi8gqpUjcqt9R6Ig+iUjZR4DorA5TTuOgYmzKvYQamiNTJyjX+60rmCs5Wz\nEFgBayceBQDs3XocuPopwOjjK9K3ROSF/lxbXo1lpWaDMlo7/TZ4lsGy5IHunCOggCmTvN0nn+eD\n5Bi5NUBA8uH4EJOUMUc0WnorPGIBhElmGKAoenOSxaJvXlZX6vMxyQKHsSuDcazUHrekoEl5QZyO\nntG9QoUi16CIHFSRy9WT3Bub4NmSB5LT3K0F6KYTcsxu621cal2C5RydYXYcFx/76m38h7+8gpE5\nRtFxUw1MEkMgIPl4meQkuXX8rGSfSZ6VWyc4WwOESV4pSb5jtszJIbl1oyihNZpkOpbvdDUsYQBH\nrvnzSKM9yeQ+2+1pifeLwAqQOTmmJ7lP1ic2fVtujSbYF06QsTqLurgHZjJLPIeSzOPWgFT/L9Si\nhQbIFbxvNMaKvIxffeZXF2KTc8utOzcBsQhLWsIgh9xa4VJAsiCTPtHhPniWh8RJc4Hkvm7BdtxY\nJpkm1SG59bhJzrvXb1hTA7N8c8RagYLk8PeeGySXpo7lseH1TrdhJZt2AeRaLNQzFWs1uZYMkr0c\n5bZB7pHNqoCd4Q5OV06Tv4sFwtqm9MeqggrLtSKjd6qKOGWSU0DyiLZpDLP7NNG6Sn6fU2SPnhsk\nHzeTbKQzyQX9AGOmEFnTC0IGACpvEkCbIxpFCWNrENuPDAAsw+Jtq2/DF3e+CPflP4MN4KlJGw/V\nH8r1/jS2mRXYLoOKFvZbUHgFuqUnFn3qakZ7QQ65ddfoxo4kdTgJsAxs1cies1JYSWSSAeDBjQoe\n3CjjT55JKEAcESS3hgaeu9vDBx5aB8Mw2B5uY6u45e03pHB3cbUElgEu72WA5HmMuxgOYNNH8n11\n/6s41A7xgbMfyP19/rrHPZD8Gorfe/n38Olbn54+UFydX249zg+S66V0JpmCp0UcrmmiXZpx+NsL\nMMkAMYaKyK0pozoj1awoQg7jrgpxe7aPyNzRkRhKDYfDCeo5xj/d6t/CmcoZAMD6Gz4EANh77neA\nx38RqJzEi+ojiSBZFUtzMcm7gw42qgo4ypjlmVPoxXpFBscy2Ol7Ix+EoNw6yoxtFDfgwo11fJyN\nttYOjX8CSOGmLAuEiZ8M/dnXAAHJcxl3STx0eOdigRnesXJr7/pWvGSpXpKyx6uAfC+JK0NjWZgp\nCRZlrYPS0h/99I/iBx77Afz6878+93eYjY9+9Q7+5z98Hr/4qVewO+yhcBS5tWNjMBksLLn1w7E9\n47s0JhmR9W1sjSGwQiSRQfMV0lIQY9xzMDCw6jPJh5B4KeSYv1LO51i+09VRYwah4txsTzItMO10\nNa8nuRs7Y7YoFuN7kjP6kQGgPTLQUU4CcInh0SIR6EkGCPO4q5Fe4LOVGDdauQwRwI/f9/14vvk8\nfuFrvxA/dSAlcsut2zeA2mkUZSGdSU5zOg9GcRUYkD0kN3PiRcdjp+KY5Fh55ujQN+0CpoqtvOZd\nBaGAKiNilwlfM3QfXpmDSQZSPEW84lPXNtKZZIAY0GUwo6lMsvfaq+MC2aOtXbhwcbp8evqcxv3p\nTHJCi0K1IGCkjck6Ud5KfL2/j3azmVPn5hPkPyiT7Mmt84+BorOlEwoUc0bP6KWC5JLZxECoRx5X\neAUTZ5JcaK1szcUk6/Ywkq8F470n3ou90R4uX/szvLB0El1zgHdtvSvX+9No6cCOW4cyuBV6XOEV\nuHBDCqBgkFnvaUyylwukgNPIzHP6UgiQMPHX9tXCavJoUi/+zhs38ezdHu60Y9aaI4LkL14jeeA7\n7yPn/O7wLhnFSdt7XBeKyOHEUgHXDtNzIDomLNN8157k6kf+8xt/DlVQ8Z6t9+T7Mq+BuAeSXyPR\n0lr42Sd/Fh/+7Ifx9f2vkwfV7M1rNnqaiYLIQeTDp16ztAg708gw/6CS2UXk1lRqOFuZ3OvrKEq8\nzzbELkgULBYWAMl0cTqq5Nqf8VpDa2j4Y1SSwnRM7Ax3cLJERlQ0amfAANhtXQa2nwLe+79AluRI\nUuhv7lI5H0j2kuzmuEsWddPbVOZgknmOxVpZxuGIALuw3Dq+JxlALsl1U2uG5xCCsDVlxUucKZPs\nRaPQmNO4y5NbAwuxbKNJFCSPaTLuXe/1DIUFjZ5mQhJJcjNMmXFNQQMFEV29ixdbLwIAvrj9xXm/\nQigcx8VvfOE6Htwo480nq2hqQ8IkLyK3FhSULQsu3CPNRwcQUINkgeRwgSRxLm7rKpkvPlPp1k0b\n3bHpMclTufUskwxkS+h3exqW2SG4YhQk0yS+XpQgcAx2errHkruxM2aLQjEqt9Z7uZKn1nACveiN\nuuneSn9yUhgD0l/meRXUiyI65h2sFFbiE2FP7vk9Sw/jBy/+IH77pd/Guz76LvzEZ38CN3s3c30k\nlVvnYpJrp6FKfLq7dZ6eZICAZE8uXBAKcxl3tT1wuxRTBPXlmcHEetyeqiAAf3RUZhtQINb5AnZZ\nhGbY+kxyMd86Huwzjw3vvupa47A7d1yoK5nF+CV5CV2jCzsOGHqs6uWhjNPLBd/c6VQlMLKocZGo\nQRKAJS1CzfYlVwoCKpa3L6bJrT22TB21MxVZn//0n6CDMp4akft8fiZ51UPvCgAAIABJREFUlYwd\ny7FfZ4XpmBiaw1TjrqrdwkhqRB6n+Vzi9V7ZJD3JOWclWxgnMskA8J4T7wHLsPiTzgv41MoWWIbF\nOzbekfnewWiPTNxl1sB1w6aEsrdOJZp3FUW0UnuS6dil9BFQcQUjHQIkmL7ceqWwgo7RSVXOvfsC\nOR9PXo+5Bo4Ikr90rYmSzOMNmxWYton90T42S5tkL7UNP+/ZqinY7qQXBBVegeVaEVO6L19v4Te/\ncGMKnh0r1/inl1ov4eHGw/75+maIeyD5NRIfv/5x/78/cYPMRSMuivMbd8UZTMXKrb1evaQq01Hk\n1rQqGwHJ3vgnGvFMsrfJxYDkTFmbD5KPKBkNgeRJptx6b7gHy7VwskySW4EV0FBWsHfftwH/4E+B\nN/1QrMuxL+eU402AZoMmuB29TxZ1uqnMwSQDhBFra+Q3msqtq6TX1wxXc7eKpIKfx7wrSW7tzyWe\njEIs50phBS2tlc9ZFAQka653LhZwuB4ZJElTpSnY0rwESw4Aijxy665moiCSa3RoJBvG+CDZ60t+\nav8pAMBbVt+CF5svHmkW+Uu7fVw7HOEfPnoa3//WE5jAhLpwT7KMskWO8cgO1/RazmSSo3LrxPFP\ny1GpNQUXhEkmslF5BiSvlMl5zRoDtdPVscINwQSY5NFkBIUn/fMAwLIM1iqyxyR7CVdMgaQklqJG\nRMYgc0YyQOTWdsUDyZ1FQbIn7fbaGpZVCSN3G+cq5+Kf74Fkxujjpx/5afzmd/4mvvf89+LJ3Sfx\n9//s7+NGL9tpe6BbYBhAFdMle+hvA5UtFGU+1bgrsT99NoqrgCezze3m6kXbUxcsJfQk8yyPkhBI\neGemLlQL8zHJALAmlLDLcyG10+HAgMix02JiRkwLPwmfOzqEDWBgjdOdkwFPPpzNJDuuEz8qaXQA\ncCJeajM4uaz6IDnMJF8kCb7Xjx45hCQmWRGxhmyQ7BebXWfqXxATr+z1cZ/2LL5sX8RvfJEcC81R\ncjPJxzgrmQLzJCbZsh3UnTYMeSXyt0yjuvIW+c1H2UqtRlGCw4yhCsngbklewvduvBu/o0r4f4y7\n+K4z35V9bc1Ee2RgX9iIKGSyAP+yKqEzNmEltczklFvHFYw0h4fEmL5XCx1Nmia5Pr9SRK0g4Ms3\nYnK2yXAxJZcXL2z38fBWFRzLYHdEVBm+3BrwiYzNqpLLuAsI/67P3OniBz/yJP71Yy/hhW3vms/B\nJFuOhWvda/HtOq/huAeSXyPxxO4TuK96Hx5ZewQvNF8gDy5gENGNAcmOYxOQ/NXfAJ7/A//xepH0\nNY0S+pqOJLc24uXWuz3d7+sDCEjuGb3w4ugzyWGwVVYE3yk5Maic8ZiYZI0vQzNtLGeA5FuefIgy\nyQAxadkVBeAskaYUY5gTWoBQleVclWmJkyCyIsbWgCzqCzDJAKlC9ow+FF6ZjoOhgGYm6W8UGuAZ\nPhMkm46JrtGNgORQ4cYIj0dYV9fhwk3dkIKhCDw0n0me/7ocUyZZDMitbQOMS35bIOd4FXjfywM9\naaCSMmu0QPK1/a9B5mT849f/Y1iuhWcOnpn7e9Cglez3XGzg2y6uwGItFFwAfHZVOBJCAWWTfO8j\n9yVr8YUuP6hh0CxItsbRfmTLS64TZiQDQKMskfXC0iExXEgqTPs8s5jknZ6GGqJya5rA01ivKNjt\n6tPvpiUwyeascVc/k2FwXRfd8QRiqUEKHQmgIjP0fgiQL6kCLHYfZ6sxUmvAB8kw+mAYBm9bexv+\n+SP/HB/97o/ChYuf+eLPxLOIgRjoJooSn+ykDJB1eTIESusoZTDJuYy7AGJoNDwAXHduubXPJMe5\nWxsdVKVq+PuMW7GGknmNuwCgIRTR5DggcI0eDsj4p9TfLhC0aNsaJVzT4xaGLAsXri8nTgy1QYBu\nCuO45O0N7RilEYaHcNUGtrs6Ti8XcKt/Cw2lETZ0anhzuRMk1zTXGM14O1QLAtYZ7zPLKe7WHkgu\nOG6qi/bnnnwSW0wTrZVvweNXmrBsx89R5mKSgWPpS6afmSSJ72smVpgOLHUt8rfMkWfUDXyQXdxu\nlCQwrA7OTb/Xfkw9j0c1DfeXz+KfvfWfZb7vbLTHJtriFlHfBEgB/7skqMNou1s7qRhFDUFTwGlb\nb8f+ziObh8RYWCmRHIqC5DTzLpZl8MiZZXz5RkzONhnPZaQaDMt28Mr+AA+sk2vy7oD0lBO5dTg/\no6M8DSt5XfZnxwfWxL+8NP1eH3/ea6GzJ5nO1rf7tzFxJn/zQDLDMEs5/peh17kXR40b3Rs4XzuP\n19dfj5c7LxMmpLgCTAZzMWZxTLL+4h8BABQwwB/9CNC9AyA7eaQ32CLSS5pkz1Ya93o61spTQOcv\nSEHJtZ9gh8GW73SZFscst27aZNFdzuhJvt0nRhSUSQaiUvKixEfl1l5SUFQbZOOws42cCkIRYHVi\nNGHN35MMEIfrsTWEGgQAftIfMytZXcXdYboJCE2gonLrIJMcrrLSMWC7w+x+Z2BWbj0/SB56TLIi\nBJhk24AC+AlqvZhRtQaR+U4sBzWFAJFBCqic7UmmvesPLj8IAEcap/Clay2cratYLctYq8iwWBuS\nk8HkJYWgoOwVXY4MkrOYZN8wKAdIbt8g8saYGcl0pNxqSfY/S3bd8Jxk7949yADJe50xik4MSJ5h\n5TerCnG3nqnsB4O69YYiR0+yZtowbReVgghUTx1Nbh0A5GpBA9gJThRPxj+frtN6GCicLJ/ET771\nJ/Hc4XP41O1PJX+cbeBQO5je50nR9+7z8kam3HouJtkcA8YAiqDMZdzl9yQnjIAKMXyuG2GSOZZB\nWebRnYNJrgtldDkOZkCOfzg0UM/ZjwwE5NZJTLLWQc8rkiQ5FvtRXCFJsp4MEpckDyTH9SUP9zGR\nG3Bc4ORSAbvDXb9Fxw967yYAWAqoo0yygDUfJOdgkjk5tfeZu/E5AMDWW/5bDHQLT9/pgmM5lMTS\nfMZdwLHMSqZ970mMbK+9D4mx4BajINkHQEnXuz8DO/s4ayoLhrXhOOnXYP3gZXykZ+P3/84fR7xH\n8kR3PEG/4K1B7ak6JQvwU5Ii0VfCGIYMQWfDdV10jW5sT/LA4qCyFjhvegmdupJVuH/4RBV32lq4\n1cJxiLpvQSb5ZmsEw3Jw/xq5Z2nOtVUKMMnjKZMMEAVUUtACY/AaeeJaCw+fqOLdFxr41EueitPO\nllv7I07/poFkADsAvgbgqZT/PfdqHeC9IFWendEOzlbO4g31N8ByLFxuX15oVnJ/FiS7LrTHfxEA\noDzyP5Bk8+n/FwAyx90ovAKWYWPnF2ZFXE/yxHJwMNCxXp0mPbGzksctgJMi1bh8xl3e5x3V4Vrr\nAAyLQ5MsHI0MJvnO4A4KfCEEEGdnSxblaFJIk4KCujr93IyQ2SIYTvN6kr1NZU4mebOqwGV1KFxg\nMU9gkgFSycxikps6kXWlMskzcut1lcx+zGMKBhCZtOaK0/eaM8aGBVXkQuO8NHsCJbBU+lXrFKMQ\neh0uKyS5SSskzcqtt4fb2CxuYkleQoEvZBYfksJ1XXz1ZhuPnCXnzXIsmKwL3mGzjTriQlCmTPKR\n2xVooSvFNCjGc0Eztajc2h//FAXJ+32SIKyUJT+JkBwHtmv7En6J51AtCKlMsmk7GA/b4GDnYJJl\n7Pd12HKy3LooxIBkPZtJ7mtkfagoAlA7dUS59TTx5kRyPsrCavzz/XUzChQ+cPYDOF0+jY8895FY\nQ7cXmy/i/X/wfjxu/I9wao+lHxdltUprKEo8xhMbthN/rc5l3AUAw4OFmGSRY2Ml4j2jF06qjQHp\n3Zsp3tZUMbe7NQA0PODdDBQGDwcGGjnMIWkIHItqIWV2rN5D3zun2UxyNuijDt+xIHl0gAFPfqfT\ndRV74z1/XfdDrhD578FLse9P77G4nuQNpgWLV1NbFXxX/OX7Ej/DdV2c7n0FHWEV9z/4JgDASzte\nMV+sxEvJYw+Wgs+jM8ldz88gSW6ttcjewFXWI3/zAVDS9V6MN0eMfWqBFI8tK+Ma3HkG2HhTIhjN\nip5mYlz0etVbV/3H6T2eaNzlFbESQfJkkApMNUuDYRuxILlvsiiw07xsVY0hbmLifo/tDTlM03Ox\nIJN8aZfkzXTE0/XedSi8QsikGRKD9lBvp0iuZ5lkbWLj2TtdPHp2GQ9tVnCzNcbEcjy5dXqrx43e\nDTBgfHPab5bIA5Ivua571nXdM0n/A5CtA70XCwft4TlbOYvzNZII3uzdnKsSSKM7ngHJh5ehtUmS\nqVROAGffCzz3MQBTJjlpo2UYBiqvLgSS+5M+OIYLJTh3O2M4LnBqabqA0JEYoVnJtFo/sxBXFAHj\nCWHwEuM45dZyFa0RWTwzmeTBbZwsnwzJ5ZaUJfQnfT9ZL0o8TNsNyWNG5ggsw0IpeBtaDsk1hwIY\nVvN6khdnkhlWh8AEFvOZSmXo+TlAcksjxx6sMJM5pCaqajxI9osks7OyE0IReWjwCgILGncVpPBm\noDsmFCYIkr3iUYrkmsor6ypJQAcp7FVRnjLJrutiZ7iDjeIGGIbBidIJ3Bncmft7AMDdjoa+buEN\nm+GZvpzN+/PI5wpBQcVzan7VmWTAH9kUelkck9zyxj8txzDJAwM8y5CeUu/6lT2315DDdUlK7Une\n7+tEag2EQfJkGJkDulaRYTkuOo73eMz9UhQT5NYZPcm0+FJW+CmTvEjBY0babbGkgCUj2tsIgPSj\nCWosSOZYDj/y0I/gSucKPnPnM+HjNXr48c/8OGRORtl+O4byp/DcYUpN3XOhRmnDV1hQM73Z0CwN\nDBjIXEYBsERB8l7+kSdedEYTLKlirMw5MponYepCVRHmk1t7gPMwkIS3hvnGDAajXkyZ/6110ZPJ\nfZTdk5zdY+vLrWOZ5EO0PbHhyZqC3eFuFCQDwNobgN34ayOJSa54TPJITijueDG2xsQ7YOPNwPbT\nsY7zzf4Yb3VfwEHjHVgpyyhJPK4dks+rSJX8TLJYJPvtMfQkUyY5CSQbHWKWKdSiUvNM464E34fY\np0okJ5lMUoCSqQMHlwhIXjB6mgmzcpqMGwr0judmkpPaCyaj1LGHHcObeR4jt+5OWMjM9P4tCkUo\nvJIqtwaABzy29/JeYJ2nIHlBJvnqwRAMA5xbIa+/3r2OM5UzZH2Sw2of2kN9N8W8a1ZtcO1wCMtx\n8dBWBedWVNiOi9vtkQeS03Pc3dEu6kodYg6Dr9dS5AHJjx7Tc+7FgkHllmcqZ7CuroNlWJI4z1EJ\npNHTTFQLAZB86TFoDKmSK7wC3Pc+oHMD6O9mMskAafxfCCQbfZTFcij5uNUiN+rpegAkq2tgGTbs\nnDzuxPYyUvCfyib7cuucG15SaB1AqfkFhKye5Nv92zhRCo+noawyrRbHjQIamSOoggpG9RLzuJ6v\nmXAdGQznGaAtyCRv1QpgOB1MsAcpQW4NEIfrQ+0wdSwMBclBNl03HUwsB1WFsr/DkKmUwiuoSbXc\nTHJBOJrcemTY/nmgobkWFEyZpLpfPMpmktdUsun2UwA7laD2dQstvQXd1n054lZpa2GQ/KLHgjy4\nQTZrWi1mHQHP3V3g+ucVlI8LJGsdkgjJKQl6cSXWuCvSg9q8ApQ2YpOgA6+Xk2WZKZPstSyEHK5L\nKYACxCthiYLkAAgamaMIk0zH9OxN5Ol3nYmSUIJmadM+XmtCCloZ0tfQnPvqCXKN51CXRGKmJ9kA\nAcmck1K0kCuJktvvOvNdOFE6gV979tdCKoVf+fqvoKk18Uvf9ktQ+z8IHqX0sWZ9r9BWXveLR0lj\noDRLg8zL2X26gR7RuZnk0SRWag0QABMCmL6hZJhJrhTE+eTWFCR7SbjjuGiPJpmF2NlYK8vY6yes\nx3oXPW/UXqbcWs1WrFXECliGjYJkxwFGh9i3K1AEDpwwwsSZ+MXPUKw/RApeMe1jfk/yLJOskJ7k\ngZBQ3PFiZBKDPWy9jez9MeZdOy89gTIzBs6+FwzD4NxKEVcPCEgui+X86hmG8czOjg8kJxUynB65\nX5Sl6Oi7TLn1HGBeksi6o09S2iVaVwHXBlYeyHy/uHAcFz3NRFEtAEtnQnOzKUhO+i513809TW6d\nYtqVwNjrpo2uyULENKdkGIa0ymWA5NWyhGpBCDPJVN22IJN8pz3GRkWBxJN85Hrv+nRknxRWSdIe\n6rQ2IrqX0uLD9SY5vrMNFWfr5J67djjy3K3TW2V2RwnFr9d4ZIJk13V1AGAY5vsZhil5//0vGIb5\nI4Zh3hx8zr14deJO/w5YhsWp8ikInIB1dZ1IMAMysjxhWDY00w4zyVc+CW2VLGoKrwCnvHrH7Sew\npIpgmZQxEiBVtUXl1rOb880WeZ9Ty9PFTOAErBXWwkBhxhyFBgX/6SD5GJlkb/wTgNQRUJZj4e7w\nbsi0C4hK1OjYIeqwDJDKuSqogSph9kZtmyIEfgKBYxdmktcrMsDqcO0A+KfgIIFJBtJl0S3dA8kB\nuXVXI5tatSAQRmwGJAOkULIzyjYXAQBFDMitFwLJFgoz0krNtaCwU+DszyBN2XzoNbhSrIABMHSS\nl0iJZyFwDIaG5bPx1DH8ROkEtgfbC80lfmmnB45lcHGNFIYoC8M6Al7aXQDkCgoU1wXHcMcjt1Zq\n6bI8b2RT6GUxo+rQfCVWag0QBtifLUtBskWuuTCTLKcqA3a6GsqMt84F1p64nmTqln04ssh9Gye3\nFmfceul6NA9Ipj2Y/Xz3RiiMfuiz+tY+HLOMftotI5cTQTLP8vjhN/wwLrUv4fHtxwEAzx4+i99/\n5ffxofs/hAeXH8RI57HBvRNf3P5i8p4x2CUycFH118Mkh+vEcWCzQffJwf787tajCZbUaHLoui76\nRj+cVCd4ZdQKOaYuBKLhKW1a3nz4vm7Cclwsq/MxyevUZT0utC56Alkncxl3AakuyBzLoSpVoyBZ\nawOujdsTFaeWCz6wiAXJaw+Rdq8YObTIiuBZPtKioIo81pg2Onx0BFIwxtaY7KNbbyMP3P1K5DnO\nlU/CcRksveE7AADnGlOQXJEq8xUGF5g8Ehc9oweRFZOvc095Ua5HmeRMuTXDEKIlB5Ns2OQ6Gusp\nfhYU1DYuZr5fXAwMC67rrW31i8DhtJDhj4BKKDaXZQE8yySPgZoMgZQZz7Hj3ECKowZECG4YfK8W\nVjN7khmGwcXVEl6OZZIXA8m322OcWCLndWSOsD/ex7mqN5FALAJg/MktIp/RcoGo3PrG4QgMA5xe\nVnG24bHVh6Ncxl17o734+/o1HvO4W/8L13UHDMN8K4BvB/AbAP6vV+ew7kUw/snD/wSf/YHP+jKG\nraLHLs05aiCUYAFEHrP7DLTV1wHwQPLaQ6TKdftJcCyDJTWdYVGFxeXWs+OfbrXGUEUuAjgjbJrW\njiQiAHG3Dn7P2BAUwmAdE0huDicoSTxkIXnz2BvtwXKskGkXMF2QKXikDCbtTQUCTBUdTZADnOgT\nASzvLeqmRlyCM/pJZkMWOHC8DtMMMNBigYDtGMk3ZT7TJNdNrelLlWh0RuS7VhWBAHrXiVR880i5\naUg8C505wgioiRWakQwAmutACWwQ9awZpIDPHNUKEorgMLCTr0mGYVCUeAx001dM0N/zROkEJs4k\nt7t3MF7a7eNsXfWvTXqfSmzBlxHOEw4vgwHgmCK+cH0xdtuPcTvZ2ZqGWgfMUai3nMom/XBdoHk1\nESQfDgwftPpya6+vepZJPugnj7vb6eqowDuOAPs9miQzyft9b1ZynHHX7Egbel9n9CSHQbKXGM8L\nkl03YtzVnuzBMZfSXdtTmGQA+MC5D+BE6QR+7smfw4vNF/FTj/8UGkoDP/amHyOHqZk4U3gEpmPi\n8buPx7/JYJe4UQMo+evhEUGyUiNSQU9urVla7qJTZ2yiFjP+aWgOYblWvNy6EJVbd1L8C2ZjSamD\ncV0ceiCZsmPzMskbVQWHQyO+/UjvoseTNS2TSS4kF0dDxy0vRUGyl5tc01ScXCr4bTOxjNP6Q+Tf\n3Wcjf2IYhvTxz8itWdfCCtNFi4vmA8EYmSMCCJbvI8Xem9H585s7n8ZTuB/1FbL23rdSxMHAIJ4Z\n88itgdgC3yJBJf1JaglutIeWW0KpGGVJM+XW9Dhz5I8URA21FJB8+ArAsLGj+PJE328lEYDGBaB9\nzR+DliW3ZlkGNVVM6UkepsqtKWM/C5LvdsYwIIBzZkCyms0kAwRs3m4H8hBf2beY3PpOZ4wTNXJe\n6dg9vweYZUnhM0CkZE3imFUbXG8OsVFRIAscSrKARkkiuYJtpsqtXdfF3ijGa+CbIOYByZTe+m4A\nH3Fd9+MAvrnE539Ng2GY0M27Vdoi1u+cQBKAnC6KdBGq0E1/91nAnmC8TOQaBb5A3nP9YWDveQAk\neUy9ydLk1o4D/NW/Af79eeB3f5AMrqfHMulHxj/dao1walmNbAgnSid8q3sAJBmJ6WWk4D91DBTD\nkOTwOIy7PLl1nn5kAJlMcjGGSaZy66mUJnuj1g0eLuOxZJY+N4tMg2F1GJOZ75aw+VMmOSSLn4m9\n0Z7vVk5jyiSLUzA0w8zR8581YgYg9wpLQfYCxZvxxI6Y9GhwoLDT36Eo8ZB4NvW+8MFMQUCJ4TFw\n05mkkixgqFuRJDLPuImkuHowxIXV6T3mO7zyKq4dzA+Sv3KXbPCcLeLywb4/Lmuh8O6f1JhhsFzX\njc5JHh4Q+WTM+CdghkkWFICTIHmJStAEZqUkwbCcREC209WwInrP9wpWjutMlR6BoF4OBwODrFNp\nTPJkBiTn7EkOMck5RriEwtSIfC7wWXujbTDWUrrDdwZIFlgBP/+un0dTa+KDH/8gDsYHRGYtkN62\ngWHhTPFBlMUyntx9Mv5N+rtAmVz7mXJrMydIZhhvVjIx7nLhpraFBKM1NGLHP8XKM5NAckFEX7cS\nDchmgxdULNkODr0+ScqOzduTvFGV4bpT87pQaF30WA6qoE5H/CUFJxB2P8MPIx4kk3XrlaFCnK09\npVFsMl05Qe6tveS+5EiuMdgDCxd7SAfJY9NjklkWuO/bgaufBoL7SfMKVvTr+LL8rX7+cXqZrDN3\nO2OUxTJ6k15+RU9h+fhAcszsXhqSdoAWsxQymvQPQciQWwNESp/jOOkoyv4oBTIcXiY+CVkj2RIi\ntLY17idrVJu0GmaOswJR87WSilEZcuuO7vUkz4Dk7Y6GicuDce3QZJGVwgqa42bm9XCqXkBzOMFA\n9/Z/P8eZn0nWTRv7fQMnPc8e2obpy60BsqYbQZAsZrZLAgEmuTnyGWQAOFFTiBrFNlPl1l2jC93W\nsV78mw2StxmG+TUAHwTwCYZhpDlffy+OKbZKW2jrbbJhFOrAON9iHGGS73wZAKDVCHjzE46VB4jk\nyXUzb7JUufXzvwd8/t8TQ46bXwB+4/1Aj4DdwWQQYZKvHAxxphFdyELf13FI0hnDJOfqSQa8heS4\n5NaTzOTlZu8mAOBU+VTocR8ke0yTb+AUyyRTkByduRoMx3Ex0gXY0MkCbmpz9yMDwMSewGVM6MbM\nwhhjpgQADaUBnuVTQfL+aN93hqRBxyNUC8L0nMxsZifKJ2A6Zm42lRck2OAWMu4aGjFMMlwogSoq\nwzBehTaZHeprJhiGsGElTkLfTQf4hEm20NbbkDjJB14Nz7CtmfMepzGxHNzpaKENj7IwRbmC681R\n7qSdxl9dI+fndKUCG2P8+Qv5zNRiQ++l9yMDEWMZ3dbhwg3LrVOcrQ3LRmdsYpUyyQwDFJYgewoD\nwwozycB0ZNRs7PY0bMne+faOW7M0uHAjTLLEc1hSxSmTHGfc5b2GuvxP5dZZ7tbkfinJAgF+DDs/\nkzzzWaZtYn+8D5VdwV6aoZtcyVSyvKHxBvzx3/5j/NTbfwr/9Xv+Kx5uPAxgKpmuFmS8ceWN+PrB\n1+PfYLBH+ssxnVWeJreOSO+TorgCDPay+zQDMbEc9HUrVuYca6g0bhOV0kz/aK42oGAIMuq2jab3\nGTTxn5dJXq+Q/Txi0mcZgKWhzyKyByeGupyZZyzJSz7Y8MO7d3esEjaqCnZHu5A5Ob7HlmEyzbsi\nUwL6ZL/ZTuulB8LFtfPfSb7LduAa/PpvwQaLl+vf7j+0ERihU5EqcFwnv2pObZCiwiKmeoHoGb1E\n0y4AUI0DdBJYdJEVwTJsOpNcbOSShdPv3UkDya2ricXKPBHKT1fJ+ENK1vhy65TvUi9KKcZd0Tau\nYHSMDjiGQ0kIr793OxpMxrvvAoW1ulKH5VqZ6oLTXusg9ds5irs1NeA66RVvrnevg2f5sNdNLJOc\nnKfM9nrfbo99EA4QE8r9vu4ZdyWDZFr8oka730wxD8j9AQB/AeA7XNftAlgC8JOvylHdi9Tw+z+H\nu3PJeqjDpg+S954DylvQvIt/CpJfR5LYwW6moU0ik+zYwF/9HLD+RuCH/gD47z5BEqyPfggw9Yjc\nuqeZuNvRfJOhYNBF4M7gDgGJrhPfk+x9r0yTFOmIINmxye+j1NAaZTPJ13vXURbLkbmBZbEMnuED\nTDJhMAeBpHBoDsnmzkuEEc5gklujiT+mYWyOF2aSafI+1mdBcnwPE8dyWFfXU2XR++P9SM8K7dWr\nFoRplVWKMsnAlJHPioLEY8LKC8mtx4btJ+cAANuExgDKjINuvSimy601MvuZZRkUOQlDxklNmEoy\nj4FhoaW1sCwv+2xGQyFA8VCbb+bm7TYBwUGQPPZ+3yV1CRPLSXW9nI39vo6nd0mSsKqoEAQdX7p2\nhKEGuUCyd79415s/xiWYYKQ4W9N1ayU4X1apQfKuiyCT3MgwKdzp6lgVDZLc8OT+oizwbE8y/cz9\nvkHWqTjjLjHcJ+4nNjl6kksST2Z2cgJhgvrJhanY8KXd5PffGe3AhYuauJZs9ESPLYeS5UT5BD70\nwIdwojxN3voek1KWebxp5U240bvhs7F+OA4w3JvKrf2i4RHl1gD8AfswAAAgAElEQVRQWicg2bt2\nknobg0ET7nophkmOM1SiXhlsOK2icu3c5l08AcmHXgI+9b2Yn0kGEO1L9s5hH26ms3V3PME/+s9f\nwc6kAHeUzSTT1iE/PCnvoVvFZk3x+xYTzdbWHyYFejt6zmP7yb2i+20rHSSPrNG0oHL+fQAvA0//\nFvn/kxHwzO/gM3g7istb/ms2/RE6Y/93yi25VuuAY+a6X2JjeAhceixqDjcTJbOJvhA/j5hhmGyj\nOpo/xrh9B4PmeK0B4ltSXBfo3CSGWwtGKD+tXyQ9sB5IZhkWCq+kKkCWi2ly61FqAZLOPJ+9Lre7\nGiTPBR6Boir1VWlq6bn3KQ/Q+pJrn0meX259xxvlREc7Xe9dx6nSKfABv5QokyyleqfwLA+RFaFZ\nGjEpG5vEj8aLlZJM9jEnXW5NCYxZEuSbIeYByQ6AMwD+HcMwfwjCKH/+VTmqe5EaodmxCcxeXNBK\nHQWTOLgErL4uOm+SuhMevIRGUUJzNEns1UvsSb77VaB3G3j0x0jSsP4w8L3/Edh9Fu7nfh59Iyy3\nvuQZCb1uPZok0p6La91riQ6iQLAnOUMGKpVz9fYmBt34vJ7kLGfrq92rOFc9F1mAGYYJSdSKEjn+\nkNw62POYIXcECOMFhxzPyBwtzCTT5H0wFmDagQ00xehjo7iRyCSbtomm1ozIrTte4lhVxMQNJFQk\nyRGKyMNgpIXk1iPDQkEKyK3NMTSGhcLPguT0Cm3QRb7EyRgyTCqzXZIJk9zSWyFjsyV5CSzDzg2S\nrx16LpX1KYAbeixPo0qA99U5JNefuXyAsUuuqzIrQRB13z17oZgxjoqNmfmstNodZpKvEOBK+3MD\nQaXDPpMMAEoNskG+d5BJXilTiXR8ErbT01Dnx1NvAEwTx1kmmbyfjMPBPD3J+Yy7+prpr3MAiOR6\nbiY53P9MW1nWCpvZTLLeW4gd6wX6Dd/YeCMAYuwVitEhkVh6MnLfuOs4QHJ5E+jvzMUkNwfk/o5T\nCsUzyQltQN460Mk7BoqX0LBtNL0RYc3hBAxDDMDmCcokb8+CZI0ce8+1Mk27PvyxZ/D5Vw7xUk9A\np5muHKnJNQwmA5hB/4XRIRxWwAAKNqtKdt/i2kOksBtwNqZR4AuJIPn6JJltBQJtSwC5Jx/+e8Cz\nHyPA7vO/AIxb+D+Nv+UDEIDId0WexU5P9wv6uWclF2iBb0HJ9cc/DHzsh9Dt30lmkm0LZaeLsZRs\nWhb7mwVDWSKO1JN00oACbWMixLekjNuEra2eiv4tZ/SCBXNeJHloQHqfZbq3rErxxl2O4zHJKe7W\nRjd2RvLdzhgF1XtdwMOiLpPzmw2SyWupKe1RmOQDr4BJ97MbvRs4Wz0bftJMIbNRkjAwLOhmspKt\nIJBCClVRBffLtYqMoWHBtibE2yYhaA4bnFzyzRLzgOTfAvAAgP8A4FcBvA7Ab78aB3UvwmE7Lp67\nO626+7Njx3seSF5Abm2bwOHLwEoAJNNekgYFyZexXBQxsZzERIXKrSMg+vJjpBJ44f3Tx+7/buDh\nvwftS78Ky7VChiHTcTXRTftM+Qx4hseVzpVpwhmTjAgcC1XksmVtUuloINljhmypgs44W259vXs9\n3DcSiJpc82f0qR44C8mtrcDmnuIuS2O3p8MNgmRLJ1XzOYMyya4jhxlTyiTHJMppM30PtUO4cCMg\nuTc2IfEsFJEjGxkQdbcurIFn+dxMsipy0CHNLbd2XRejiRUeATUZQ2OZSDKeZYjR06bzyEuCigHL\nhgyoZqMkCxgaJlpay5fhA4ShX5KXMjfj2bhOQXKASR55G9nmMgEh85h3PX6liVKRgKoyKwCshisH\ng/SZ5EnhupERRLFBmWSPjYplkptXgOVzEfYOmEqnG7NMsk6u7ZBxV9FzpI6pumsTUmGvseMQ+03n\nHM/2JAMBJllZIvfsTD/9UXqSKxGQnG88mh96+LNoYetUeQt7PT2xIAq5QkDsAq7xUyZZwAPLZH+5\n3L4cftLA+x4lAqL89TDN3Tpv/2N5AzB6ULzvlsfhupnSC0wZxYjcOqZ4S5nknpaXSVbQsG20rBFs\nx0ZrZKBWEMFz83W3qRKPelHErdbMuuMx+D1nkmrade1wiM+8fIgPv+8CbGUZTkYxftZjAwAwbkET\nqgAYbHpy69S+xc03k3+DUmgvYkFSfxs6q2JXT1dzaaYWvk+/9Z+S4vFHvg34wi9hcPHv4uvuBZ99\nB0gRe7OqYLur+Wxubld/unbN2SYDgKx3L/8ZXJBzVE0yeRodgoMDU0mWuCqCkl4QUrzrN2OM3Mgc\ngQUHuHy82qZ7k/xbOzpI9te3tYeI9N67ZzNBclHEaGJDm8wAQlosT5Nbe0zybGx3NBQpSJ6RWwPZ\nILko8VhWRdxpe8c9OQpInu5nhm3gzuDO1LSLxgyTnKWQAkghZWyNfRVRCCR7/22b6XOSk9zBvxli\nnlX39a7r/veu637G+98PA3jw1TqwezGNX/zky/i7//FLuO31NdSVOjiGm8qtx61IEhYXVM5SVgTS\nP+KYPkhmGRYiNSdSl4kUr3PDl3glyVgKQgG2a4cSTgDAlU8DZ94VkVS63/6v0PUY1d5wCka+fruD\n1bIUTmi9EDgBpyuncaV7JdEchUZFEfKB5KMYd3kbypAtw3Wnbsdx0dbb6BidqU3/TFSlqi879Hvw\nPCaZ9kBNQXIOJrmrwXXIwjZlkheXW8OWw32aaoMkyjG90afLp9E1ulEZJZA4+qM7DsztTmCSOZbD\n6fJpXO9ez3XsishBw/xya9104LhAISC3No0+LIaBwoePqV4S0R5N4CT09XbHUzBT5FUMWGZaBIgJ\n2pM8yyQDRHJ9OJ6PSb5+OESjJJHeVS9Gegey46BcWUa9KOZmkm3HxReuNvGG0+TclRkepjuGadt4\nZX+BtgVTI2tPltxaUMg65Jn/RBQvAGGcYqTWwJQVpiwxAEAq+0xyUG5dVniIPBubTOz0yOeWMZom\nlSAqDyBebr1alnA4NOBQ5nnmvo3Iredwtw6B5IT2h9QwwtLuu4O7EFgBZ2rrmNgO2knmN3OMoZuN\nvqfuKSs8VEHFidIJvNyZYQspSPaMuySeg8izGCYYxM3Vk+wpDQrempBnVjIdCdZIYJIZMGHzSS3e\nsX3aBpSfSa5bNmy46BgdtIaT1BGDaXG2XsSN5gxIpkyyraVKeT/6ldsQOAYffPtJrK1tomT3cauZ\nvGZQFikEkrUOhmwZBZGDKhFQkdq3uHSOXGfbX4v8SRGU6HnrbaMvrflFmLhwXRcjaxReN2qngR/6\nQ+DUO4B3/lM896afBTBl32lsVMkYLcq4zyW3BhZjkq9+GnAsDP6bn4HNMKiMElzFPcM+p5gscS3w\nhfTWAmqeqKV7nYytMWS+AICJB1ydW+TfIzLJAsdAoZNCNt9EigydmwAAmZMzepLJPRLpS05o4wpG\nHJNs2g72+joq1Dk8oDyiIDliVBcT61WZKPyAAGCfHyTvD3TUCgIknsPVzlXYro2LtZlxW7M9yaXs\nSRzU8Z+C5LWg3NrbOx0rHSS3tBYKfMHvHf9minlA8tcZhvkW+n8YhnkEQHQluxfHHv/g0dPgWQb/\n5uNkfiDP8lgprBDgoTYAuJnjGQCvn032+tkOLpEHVx7wZWshOXDtJNC55ffbJhkiUNlgSHKtdYHD\nS8DJd0Se/9kdDr/nvAUA8Lufv0Us9i0bn3v5EN92cSXx2M/XzhMmOUVuDRDn7syK/VGNuzyQ3HbJ\n4pnWK/Zi80UAiC5mXlTlqi/dY1kGqsj5zAlNCMJy6/QEdbevgwdZqIbmcGEmmSbvriOH3VGpBHYY\nTcxPl08DAG4NbkX+Rl2b4+TWVcVbfBOYZAA4Xz2Pq92ruY69IHLQIM7NeI28ZLwYkFtrnkRZmQHu\n9aIE23F9ufhs9ANgpiiWMGRZuCnXXEnmMdQn6OidiGSpUWjMzyQ3Rzg3Y4I3NPpQHReQKjjXKPqS\n7Ky4vNdHTzPxxnMkua2AgwsHYCe4crDAfTQD0lIjICeOyK2NIdC9TTwUYuKgb4BjmfD9KVcge+ch\nKLdmGAaNYrz/Au3pLNjDELD3jdBi5NarZRm242LIeiBqZn2WOAkCK0yLUXqfKG8y7tVYkJyzSOrH\njHHX3eFdbBY3sVElv2vE6ImGbx44f59lkEkGgPuX7sfL7RmQTGXjpSnTWJT4o89JBnwJt+Ktn7nk\n1pRJTuhJrkgVcGygNWPcit2XqvPKrQXCJAMk+WwNJ3ObdtE421B9VYkfepewlOY4UW7tui4+8fwe\n3n2+gUZJwubmJiTGxFNXkvvflzx1V8i8a9xCxyWmXQfaAVy46bNUWRbYeDOw/VTkT/FM8l1oyhom\nlpMoKTVsA47rRBUfJ94GfPB3gO/433CokWLnbJF+s6pgu6P5DtNU9ZUZvtx6zgIWAOy/CPAyeg9+\nDwCg2roZ+zSjQ+4XprKR+FYKn8UkU5CczSTTdTfWAb9LQfLJ6N9yRl8nPh5+HnryUfLvbeKEn0du\nDcQQOkZyXkGDjtoKxl5Ph+MC1bK37gWYZFVQIXFSrn15vaJgt+u9djIGwCyUk+33DZ/lvdQm+TtV\n5fhBmWSPfa/nZZLNcUTODUyZZNeapI4RbevtkALumynmAclvAfAEwzA3GYa5CeBLAN7GMMzzDMPE\n2xHei2OJtYqMH33vOXzypX08c4cAqjV1jfQk0005h6wnmLijfY38u3xffLJRPQV0bwVusngwQDee\nEEimG9zWWyPPf+y5XXxGfBMA4I3ObfzEx57FZy4fYmhYeP+DyRXRi7WL2B3tok1HQSUyyXxOufXR\nQXLL9kBySgLz9MHT4Bker6+/PvbvVaka2niLMu+PPPFH9ojzMMk6lgtkUR+b4yMzya6thDdFNXnz\np+7dt/pRkExl2HT+7//P3ptHSXbVZ4LffUu8JfaM3Coza1eVSioQWkGAFkBgG4yx20uP7fYA7oN7\nZs749MHu8TEDdjPu9nJ6PH185tBept3emm4vmGZpY2xMI7AQSCAhCUlIJdVemVm5RmTs8eK9iHfn\nj3vvi/fiLfEiq2Qs0HcOR3ZWZMaLeMu93+/7ft9PoN6LUpLDi9kN5Ruw3l6fmC5KKYWrbOCsokxN\nkrtcwfcryT2uiutqmCQDiO1L9pOZglaESwi6Eb2pAjldwZB0MaTDaCV56p7kNo7NBb/Hjt1CjrqA\nXsAN8zmc227HW2t9eOwiO+5bj7JzV+DLBpG7IxvZNPDsvtEb9D98+CLu/vUv4GOPrTJVkZMnoYh4\ndmvRtzh/U9SfwVbTwmwuw4qCAnrBs1v7lWSAVc13IiruYoOjDVvpe5L5ZnuP8n+LGgOl5nx2az63\nOC7QiKPRc1AwfJuV3DzSFkk9jNmt11prWM4vY5GraJEjgwCfkrwPkuyfgQrgZPkkVlurQWWwvQWA\njApxYCQ5agQUpXRfJNnssmNP25NsZuTA80AgtKmmdBTcNQbh5kgcTeiHpGCOO1R2ejvY7fQn5l7E\n4dhcFtWO7U0RAAD06ugRggEdxCrJT681sF7v4e2vZgWLmTn2/b1w8WLse4lNciC8q1vDrpv1rNYA\nJo+JWbkT2Hou5ASK60m2Tfb34tZ9cZ+aCRbXOGv9YtHAbruPnFIAAUmlHAK4Nrv11reAuRtR57N5\ny/XowkSvyvZCahJJVpOJpfc8m0CSu04Xeb4ub0UV0fYuM8I9qYUmAW1r4IX1AWBtf3oRuPJVAJM/\nS6ygIwqRMSSZUhqZIr7Kgy3LBV7oHIzWekIIZo3ZVCR5qaiPwvOcLnPKTXjOR2G7aWGek9YztTPI\nq3ms5FaCL9IKvCWGvZ8o+kxKuO4NethsWNBVCQXfORCqMp0wJ7lm1bwi2XcapiHJ3wcW3HU//99R\n/rN3AviB639o1wZCyPcRQl4ghJwjhHzg230814r3vvEoyqaK//AgS3NdzC6O7NZAqoplPUCSL7JR\nGxnWjxCyrZWPAPUrmM0mK8li4QmQl7XHABBg+Y7AawdDF184s4X8QWY9/qnSZXz9Ug3/63/5Bg5X\nTLzheHRKIwDcscD+1uP1s+xmjXngpbNbF1gIwyC+upYIvqDsDNgGbTanYae7g3/22X+GBz72AP7q\n/F95L31i+wncVLkpdoEu62U0+01vBnBOU7z+79AmPAVJ3mxYmM+xhepalGRP4aL6GEkW11t4bMRy\nfhkykb2RV36stlYxZ8yFvodGwG4tKr7hHqwTJWapPbt3NvaYd7o7+OnP/TQetT+IX1pq4VfpdOnL\n4nv3j4DqcZXfGJvpLRbkKBsTpTRwr+X4RrSVsKDmdRVEZp9/vCIrRqukndFZ69iodx0cmw1+jx27\nBdOlgFbA8bkcGj0ncfEUeOzyHpaKOpbn2HEVOK+eLQxHqZ3TQFzDEST5qdU6/s1nnsNm08IHP/kM\nuvp8vJLsc8NEYbvVD4Z2Acxuzb/H8RaRuZwWOQLqaqMHQgC5H0zkFvdINuJ6FZuZ3SE/1qjwrkzO\n62tGP0WPNpjaElSSRdEq3Xg09l5i08iu6fX2OlZyK16qabySHG0dTwP/SDSAOYMoKC42fKSrs8tI\npk+xyPqeh344roMhHU6Xbg3A5O06aezWu+1+bN5EKHW432Kb0wglWZYI8pqSaAkOgBDMgn0HO90d\nNmZwn3brozy477zfJm010OA9/HEk+bPPbkCRCN52EytcS/w6u7IaH54o7KrjPcmbjuklWwMpxsQs\n38HCpDaCwW5iM+89B50e0K1iyK30cUUIca6jsgMEdts2MnKQIACsbcKlQL3roqSVvHGNE6FobJ8x\nIRE8EtvPAfOnRwnqtcuRGSB2/SqGlMCYif8+J6ZbCyV5wmjJjtNBLmMim5G99pMAmutAcSX88ynQ\n7g+8MZgAmKvg4N2pleTYwvUEu3XLaWFIhyGSvMbTpCulsJIMsITrVEpyyUCrP2Czku3OvvqRAbae\nieLr89XncePMjeGUeLGGcLeWUNeT7Naib32zaWGxoAf+pplRYGZkENdhTqcYfFcryYSQ1xNCCKX0\nctL//iEONi0IITKA3wbwdrCAsZ8ghER78l4myGkK/ufXH8EXzmzj4m4Hi9lFbHW34IpFOQVJ9ifu\nonoemGFhUrFK8sDCDOWqacxmOpTSCrCwhdkToU3f+Z0O27wvssvu2N6z+I0fvBFvunEOv//uO6Gr\nMuJwevY0DMXA17urLAyHEFBKUbNqAfKQmiQD+1eTOUne6LMH0Gwugw89/CG8UHsB+UweH3r4Q3ho\n7SHUrBqe2XkGt8/fHvunSloJFBRNmz3UcpripUeK79Rb3EVyYYL6d7XRw1KePexZT7K1LyW57bRB\nQDBj5FlKr0BOJA6HFwdVUnEwfzC48eVYba0G5/lx1Ht+u3WHzX2NON6TM2z+YsiiybHb28W7/+bd\neK76HG7Pvhd3N7L4C9XG3136u0kf1UPXFiTZb7dm58UY6xWdy8UvPu3+AEOXjkgy3zy2e/Ebprym\ngCjRJLmslzGkw1HhYgIu8ECu4+NK8qCLnOsCehHH53OB18aBUorHLtZw55EZQJIBOeOR5Lmii9X9\nkGTR1xdht/6zr12BmZHxt++/Fy6leLJuMoVx6ISDu7afZwWg8pHIt9lqWsHxTwCgF6AAkCCFxonE\nKclX6z3MZ1WQfivYkyycHkoESebvu2lzkh7R8xeYMS+U5AT0B0NYjhu2WwPT2Tr7TUDNArKCpt1E\n025iJbeC2ZwGWSLxCdeiQLCP0MOmNUBeUyBxVV8Ezlxo+HIGurshkpmPIcniWkhNklUdyM7BbLH+\n9rR267i8iZDy5GVlRLcBFQzV68tOg1k+m3Wrs4NGz9m3knxygd3nYnoEAMCqo6mxazZqTjKlFH/z\nzCbecMOsl8wtPlevsR1L9vNqHoo0GmkI1wXt7WHDCSrJiXZrAFjmDrSxvmRxrr37VtjzC4ycxa37\n4lxH3acCu202ynGcdCzk2f271bQCkyhSwaxMb7fuVNnzbuHmUYK61Ywc8+Y21rGNMmZy8ffAZLt1\nSiV5wOZMHyj5rMN+NDciJwxMg7Y1FpoJAIdfD+y+CHR2UwV3AUl26+jzLzJUSnqQJK/vseJopSiU\n5ODaMKvPhkeeRUDM295oWFxJnp4kuy7lRV8NQ3eIF/deDFutgdGMdr5vySgSioaa0m4dUVQG+14l\n10mck1yzat+RydZAOiX53QC+QQj5c0LIewkhL4dp0a8FcI5SeoFSagP4cwA/+G0+pmvGT919CIpE\n8F8fvYwD2QNwXAc1hT9UUlQsA/1stQveTLtIksxTCjOtVRR0JTpaHyMCF6hWbn9rNAzehxd4yE/e\n5CEuTg8/sVzFH//0a3FyIXmDqEoq7ly4Ew/1dzAwZ+C4Dn7hoV/A/X9xP97zN++BPWQPxtTBXcD+\nE657e4BWxE53CEUiuNw+g0c2HsHP3vqz+LN3/hlOlk/igw9/EB946AOwXRs/fOKHY/+U2GgJy7WZ\nUdCNI8l6gQUexcwKdF2KraaF5SIjZSzdurdvJTmn5rCQN1hKr4AxA4DELv43lG5gAWtjWG2GSTKl\nFHt+JbnfZg6BCCvSUnYJc8YcntgOp54O3AF+7os/h6pVxe9/z+/jNYV34s3b8zg+oPiTb/1J6s8s\nNuMBuzUnpsZY716S3VoEH4mNbYHbp1sJ1fq8roDI7B4ar2iL/z9taMwFHtRzdFxJHvSQdZndWvQr\nT+pLXq31sN3q466jnLirBgp8JFg5N/Sq7VNhzO7r/dgZ4q+f2cD3v/oATi0WcM+JOXx9VwNAgfZW\ntJI8e5KR9wjstPqYy49d+3oRBIAmqxFKso5axw4ldq/Xe7ih6LLj8G2k2k4bpmIG+1LF3+Ik+arF\n3z/i3Ocz+WBP8oSZtaH0V8BHkqewdfpU6/UW23wv55chSwTzeS1eSRZFjQkb6iiMj646mDsImchj\nSnJ11MvJkdXkSJIcGeI2CaXD0OurICCp061TK8nC7h5jOczrUyjJAHRFRw4yrvJk9/32JB+aMVE2\nVTx1xXf99epo6GwN/MYFC7/0qWfwjcsj8vfkah1Xal2841W+rR4nyWW08OJmdLFufKQh+g0QOkSd\n5rzxTzP6zORwn9wc620d60v2ZlyLc9dgqrYyw9aVSXbrpCT0KifJ4xB2082mhRljSpKcnZ3ebs1D\nqlC5YZSg7rrMfj4GubmGq7TipadHYRKxhGoAijHxnhYheQeKvhAqP5rrXkvDftHqD7wxmB58fcmT\nPouZUWCocniv6jnUoveYYu8VpSQv5HWoGr9uxvZds8YsqgmFb4Glom9eud1lBcopUevaGLoU83kd\nl5qXYA0t3DQTQZLHlGSAiTiTgruEkhxFkmeyGmQ6iLVbu9TFnrX33askU0r/N0rp7QD+LwBlAH9M\nCHmEEPLrhJD7uGr7jw3LAPy+oDX+s5c15vM6Hji1gE89tY45ndmgNoc9pr6lsVuLxN1+i9nzJinJ\ngNeXvBuTeBrqSe632YM+Ikzn7FYLskSQybCHTc51gUtfnnjcAj9y4kewAQefMDP4xYd+EZ+79Dnc\ns3wPntp5Cn/07B+xwzYzsJz4EA8AvgCaayDJRslbWD957hMwFRM/duOPwVAM/NabfgumYuKRjUfw\njqPvCM+y86GsMULrJVxrCjp8hEEouEs85PvR6t9upw9nSLFSYhX9a1GSW3YLuUwO8wUtODtWVpgl\nsh1t7zxZPokrzSuBxaw36GG7tx0iyZbjwh64KJm+4K6Yai8hBLcv3I7Htx4P9dH+wTN/gKd2nsKH\nX/9hvGbuNWxOMnT8UNfC07tPRyrbUejaI8u7d+ycxJhj1uCioUKRSOTiUxUkmVskczwJs5VAcnOa\nAiKz72zcAjleSJmE1VoXskSwXA6e9/awjywFoJpYKhrQVWniGKivX2KbwruOcFueYqDAWwPypoOr\njd70Y6Bi7NZPXNlDuz/A9/HN+T03VPB0i1/7zQ2PJHub7O3nY0O7nKGLasfGQmGM5HCip0thkiyS\nPMfP6WqthxMFN3TMHacT2Y8MsGTmsqniSo9v+iKU5KJWHI2USaEkj/f1Atifkmw1A6FdALzetsWi\njs1mzEb0mpRkxwvtAtjEgoP5g7jUvDR6UbfKJiv4kNPVyOCufZHk8mGQ+mWmrqWyW9uYjZi2AOxX\nSU5PkqHqqBAVm21GspLCIZNACMGtB0telgkAwKqjwZXk/+9Lm/jLx9fwo7/3CD7xBLsW/uDhi8hr\nCr7/Fl/vMP9cM6SJMzEkGWAJ115wFy8c1Hhw10ZnY7KKLLB8B7AWJMniXI9IMivwaBUWFhVXhPAc\nHxPs1lEFEW9++n6U5Ozc9HZrTvxRPIi9/h4kIiHvukx4GIPWuYqrtIKZBCu+SC5OhFFKRZJ1RceB\noo6r40U0x2LtJNdIktt9J9iTDABLtwGyBlx5ZDLhBysmVcf3qgltXEDMODcA6/Uum5st1psxJbli\nsGvdcZPva6/Q0rBYuvU+lORR4T2D56qsYHJq5lT4haKQOTYrOZEkcyV5q2kFkq0FZk0VCgaxSnKz\n38SQDr8jxz8BU/QkU0rPUEp/i1L6fQDeAuBhAD8G4Gsv1cG91CCE/AtCyOOEkMd3dvaRQvhtwI/d\nuYLdto31Xfbw3uhtp7L1UEp5cFdmVK3kNsVoksxTCnnC9SQl2bNb74gwnfDm9cWtFg5XTPSGHeTV\nPOS5U8Dq15M/sA9vPvRmnBoS/FtSw+cvfx6/cOcv4Hff+ru4a/EufPbiZwGMNpCJGxJPSb4Gu7VR\nRrVtYyar4ourX8T9K/d738XBwkF8/F0fx8fe+TH8xr2/kfinhMVHWKuymuwF1Yjv1LOXTlDAhQ1q\nqWQiq2Z5T/L+lOS23UZWzWI+H9GnmZ2Pvd5Er+H5+nnvZ1eabL7xoUIw+bLOU8gDwV0xCxnA+tK3\nu9tYE+FtYOnhv/fN38Pbj74d33/s+wEAhiqhBw3vaLLv6Wy2ZokAACAASURBVMErD6b4xH4leVT3\ns/gCa4xZsSSJoJLLYDfCxlRrjxY0AMiZjMi07XiSzHqS2cZ9nCSLxSdqtFYUrtS6WCrpUMfmqnZd\nBzlJAQiBJBEcm81NJMmPX6qhoCs4Oc+vPdVAYcC+J0Pvg1JEKwtJiEm3fvRCDRKBp1q/4fgsNimv\nTjdW0XPYc0oiEiOdraux/cjCXjYfUpLZe2pECdmtD/gr/hxDl+JqvYejOb7x8tmtW3Yrsh9ZYD6v\nY7szZMWtiE1oIVNAQ1wT/UaqGcnAmJKslwBJiS1aRaLf9L57oSSv5BlJPlDU4+3Wqs42rPvqSR4E\nA8cAHCkeCRawIuzWLKMhXPDcr5KMxpqnnCRhMHSx140mTtbAQm/QC24KRa9qTKBkQVfRjEnpjoSi\nowLZ63lMGjM4CbcdKuPsdnsU3tWrY4uwa+hdrz6Ox3/prbj7aAX/x19+Ez/znx/HZ5/ZwE/efSgw\nPg56EZTIWFQ6eCGBJAeIJCfJe8h5PckT+5EFlu8EGlcC17U419654xbk7CxbVxox6eFp7NbVdj+y\nEDGbZS0IW80+ZvSZVPZaD2ZleiXZI8kraPQbKGQKkArLYSXZdWFaW7hKZ4PPgzEYioH+sO9lnkS/\nqDxxBNRISWZBZoHCaEuk0l8jSY6yWysasHIXcOlh6EryCCiAFaZDJFmICjE9yaKoIwQLgbW9His0\nK/y6GCuqzhqzoKDBNPcICFfRdqvPleTpSbKwkM+YGZypnYEma+EZyUCMkqwlZo+IQkp/MIxUkmez\nfD8UQ5LFGhY1Z/o7AdNNp+eglPYAtABIlNJwhPG3H+sA/LLVCv9ZAJTS/0gpvZNSeufc3Nw/2MFd\nC+49MYe8ruAJ3sq12dlkFrUJJNlyXNhD3s/GK7Aosq+o5/TCVqSMychQ/RIq2fibLGS33uYP84jN\n69mtNk7O59HsN1HQCsCB1wCbz6T41AwSkfBH1TY+lD2Fj779o3j36XcDAN52+G240LiA8/Xz3oKR\naLnWwg+SqcBJ8m67Dz13BTWrhrcefmvgJYVMATdVbmIb+gR4SnJ/pCSL3thQcJd4yMfM2xU2yQNF\nHTk1h67dZmEy+1CSOwOmki0UdOy2+xj65wFnZ2PtnSfLrHf4xb0XvZ+Jeaji3wT2OuwciTmik0jy\nvcv3AoBXEOk6XXzgyx9AxajgQ6/7kPc6M6OgRzOYd/o4kj+Mp7afSvORPZu7f6HuDrhVL8JKxBaf\nKCWZ/UxU+At8499KmJMs7NYyUaHLwYVKkGZxjUzC5WoXh2bCC3GbOjCl0Wb7+Pxkkvz1S6wfWfSS\nQjVgDvqQiQxJYddb5EiQJFgNgMihc/3o+SpevVz0FMebDhRQzfCN195FdAfdESnaOcP+mxDaBSBC\nSWbfpU6kkJJ8kH9nItUUYAWAgUtxyODPv5RKMsBVjbbNiHVEgUMoyZTSVEpyI0pJlqRUz/8AfO+1\n1l5DIVPw5v0uFgxsNKz41PMUY+iiMK4kA2xk3JXmFZYp4bqMVI3ZrXOajHY//CwXxCfJQhtC+Qjg\nDmBKmYlKcq1jg1JgLoKceoFK/mKWKIIY0WpKwVCmU5IVDRVKsNdnRHO/PckAcM8J9p3+3XMsOMvt\n7eFFPvLol99+J/K6ij947514+6sP4PPPbeH+k3P4ubcGn9UgBMSs4LBheW1TUSjr5RFJ5oWDBilg\nIa9ho7MxOdlaQIR++izXYSV5FcjOI8/n2DZier5DWQZjoJRy10D4XEu8BWGTK8ktuwVnmPI8inUy\nxQQBD401VlTTi6ME9fmbR/sq70PtQqE29tT5YHr/GERrSiK5TEmSDcXAUkkHpWMJ+E0x33z/JJlS\nGg7uEjhyD7D5NAxK4LgOBm58samS0yLs1vFTMwDf/ex7tg+GLjYaFg6WTZ+SHA7uAjDRcq0pMkom\n7wsW6dZTQijJM7kMnq89j5Plk1CkiO9KC7skZ2NGGwoYigEKChAnvF4CmDfZHpbGBHcJJT5p5vrL\nGVORZELIbYSQ3+QjoP4NgOdfkqO6djwG4AQh5CghJAPgxwH892/zMV0XZBQJD5yax5fOtKHLOgvD\nyM6O7F4xEKpd0VBHIRBF5kAPbD79KB9mCdf5eCXZUAwQEHQ4mUD1HEvBGwvTcV2K1b0uDs+aaNpN\ntilbvIVVIdP207lD5Do1/HjlNtw6f6v34zetvAkA8LWNr6UkyddHSd5t23C1s5CIhNcvvX5ff0o8\nWEQ1MpuRQ+nWnk1MPORj7NYiYGuhoMNUTbR5GNh+lOSu0/WUZJcieP6zc7Fpuiv5FeTVPJ7ZHRU/\nnq8+D13WvTnKAt416U+3jukbEn/7dYuvwyfPfRL9YR+/+fhv4nLzMn79nl8PPKD1jIwu2MP+ttlX\n4amdp1IlQwubu+kP7hIBQREhU5WYCu3Ibs2OIcc/UythfFVeVwC5C13Kh8Jjxgspk7Ba6+LQTHAh\ndoYObFDkfAT8+FwWa3u92NaEaruPCzsd3HXEVyBQDZCBhUKmACqx7yYqEToRFu+J9X3OwdDF0+t1\nFhDGIUsEhw/MY08qA9ULwRT+hGIcMNrEhZVkdp1okEIjoJZ5wIp/rJX4vw/ogiQHe5KTSTIvohil\nyE1oIVOA7dqwBj1ugU5WkkXwU0g5ys5N15NsjXqS19prnooMsAJb1x564YEhpEjYj8J4TzIALOeW\nYbs2U0utOks0zo6TZBWW42IwDN6/+7VbA4AJaaKSLALcoshppD1TnN+YsWZMSZ6GJBuYpQQtR5Dk\na1CSD5ZwaMbEp55i6367vostKkEhKmZMdv2aGQW//ZO349yvvR1//NOvjQ7RzM5iOcOU5LgiSpSS\nrOYq6A076DgdHMimJMkHXsMKaWuj8K4Q4WusA8VlqLKEbEbet9261R/AHrqYjbG0zxd0L7gLwBRj\noOZYhsg090tjjaVEEzIiyQunmUPPT8654tzWk5X5UGEhCnqy3ZpSCmtgwVAMHOBj4vxum1GA2v5J\ncn/gwhnSsJIMMJJMXZjcVZB071aymXBwl91ifdcx2RX1fh0ykZFXR3uPjYaFoUtxcMYY9eKOB3fx\nNqo0Cdfzed625uxPSa7xwnvZVHGmdia6HxmIVJLn8hra/QF6dvQ6L+4rItneXGQ/5ky2Tvdp9Pcn\nQmejQgC/E5Am3fokIeTDhJAzAD4C4AoAQil9M6X0P7zkR7gPUEoHAH4WwOfAiPzHKKXhpo6XKd56\n8wIa3QHK2jxTkrNzE5UEQRpLJifJkgLkWF+zsNKEUDrM7NZZDXtdJ7RRAZi6ywgZJ261C4wgjz2Q\nRL/scslAy26xG2rx1ewfx0Y9xKK3B4CG1IbF7CIqegXfqn7LUyXTKcn7J8mUK8lt6UXcWL7RU2Km\nhaEY0GQtoCRbjouhS9F22lAlFRnxkBbkPkaR3Gn1IRGmYHpKMrA/JdnpwFRNL/gooBbm5mM35RKR\ncOv8rXhiaxSwdaZ2BifLJ0MBR8IeV07RkyzwntPvwXp7Hd/z8e/Bx1/8ON77qvfitQdeG3iNqcro\ngR33baUbUe/Xg72PcZ+5P4AqE2iKjyTzzUVU2ExcIEa1zearGty2rckaFErRTljcs5oCIvWQIWHS\nlVWzUCRloq0LYJbxascOKcmjJObRtXB8LgdKgYu70eT9sUvs/V571KeOqSbg9FDQChhSTpJbMfbc\nOPTDhPDcThuW4+LVy0GScXqpiAvDBdDaeXSd7kgN2vgmU4WL4cR0dkzcbj1eGRd2axD0xzY9uipj\nPq9hzackC1V5TuGbwnElOUadANj1UW3bsZtQUdhpdLYYQUypJIdIcm7y8z8An5K83lrHcm4U17EY\nYTkPQC/sjyRbg5CSLN53vb0e29MrkuY7Y5br/ZHkI+wtKPVmbsdBFL+i7NaRJNmqs2s6ZiNeMFS0\n+wO4bkpVUdFQcV303Q4yiuuNztoPCCH4n+46iK+cq+LnP/YUpH4TyGoo6cVQQU6RE7aEZgWzUhuN\nnhMMc/RhRp9Bb9Bj6i0/p7nyopdsvZBdSHfQGRNYuDmoJPN1zDt3e5e87JSkwM5Q4N8YRMtMXCFi\nsaBhq2mNlMO0lmuxT5kgYATQWPVGKXl97wunGdmunvO9jrUcWUYyMU1Fko1y4ggo/7i1pdIoyMxD\niyvJ+ZQFkAgIYSDUkwywudmSCpM7IJPu3UpOQ7XTDxZx+u1YqzUwmnnuvxfE1IZEJZmnOacjyfrI\nbs17kh+88iDe8rG34Oe/9PMTi/ii8N6jO2jZLZyqRPQjA1xkIGNKcvy4SsDnsJBi0q0N9r20B9HP\nBvE8LEwo8r5ckUZJPgPWg/xOSuk9lNKPAEhocPjHAUrpZymlJymlxymlv/btPp7rCTFPWB6WOUme\nbLcThMSzW+cPAJIMl7qMJEdVt8qsh2uO2y1q3RjLtZIdVfdqF4DK8dBrrtaFFdhA024GSXJay7Ug\nZmPhLoQQnJ49jeeqz3kbyHpMfxIAX3DX9Js9uC7Q24OdKaI/tFEdnMWdi/vvOCCEoKSVRiSZJyt3\n7QFaditIvj0lOZrc77T7qPAxLqZqjvrE96Ekd5wOsmrW66cJ2HWys4zoONHk6PaF23GhcQF71h6G\n7hAv1F6IDJmo+ws3wES7NQDcu3IvfvnuX8ah/CH8y9v+Jd5/+/tDrzEzMnqULQyneCBR0nxlga49\nDCRbA8mbcRGIMb7xrXXsQJgKIQQFStBK2KiosgRF7UHB2OdvrIF87oMoyUYqJflKld2H4yTZS0r3\n9eWJEVFxluvHLtWgKRJe5Seuis5IcqaA3rANRSL7s1uP9d8+s8buxVeNkeSbDxRwfriA4e75oJK8\n9g1g5Y7IJHQA2GlakMgoPG10/Boga9ApDdmtAWa59ivJl6sdKBJBiavmoZ7khDCg2ZyGVn+AoVaM\ntVsDQKPNN5n76UkGEp0dkeizJG2XumxGsk9JFmFv63Gp5ftQkgdDF+1+uCd5Oc9I8lprbfRsH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8RmGf8z7FQvK0VQWRbLxhOV7NSouyXkaz38TAHXjBXZ3+AG2nHU7N1nKRSnKj58AZUs8y5s2v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rr8rntn7rVPuC6nscVxmBdnBiIjBxWsH9LpusZah957fg6feOIUPnLxCH7zh87f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\nXdVKMu3WgQjJkv6ZpBFJnzXGfNUY8y8kyVr7TUmflvQtSf+fpF+01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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# trajectory\n", - "plt.plot(np.arange(1000)*j.DT_FS/1000., j.traj[:1000,:]);\n", - "plt.xlabel(r'$t$ [ps]')\n", - "plt.ylabel(r'$J$ [eV A/ps]');" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Compute the **Power Spectral Density** and filter it for visualization." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "500.0\n" - ] - }, - { - "data": { - "image/png": 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9un5UjSz7zA0AAAAAFa9kA7C73y9pV9B1ZHLP2h1qbovqic17hnR9ddjUEYvL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\naGRFXH9+fatikYhaUmml0t7ttYbFo5owslyptGv73hYdVFW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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Periodogram with give filtering window width\n", - "j.plot_periodogram(PSD_FILTER_W=0.5)\n", - "print j.Nyquist_f_THz\n", - "#plt.xlim([0, 100]);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Resampling\n", - "Choose the resampling frequency $f^*$ or the resampling step (TSKIP). Visualize the resulting PSD.\n", - "(Notice: if you choose an $f^*$ it may be approximated to the closest applicable)." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Original Nyquist freq f_Ny = 500.00000 THz\n", - " Resampling freq f* = 27.77778 THz\n", - " Sampling time TSKIP = 18 steps\n", - " = 18.000 fs\n", - " Original n. of frequencies = 50001\n", - " Resampled n. of frequencies = 2778\n", - " PSD @cutoff (pre-filter) = 3173093.88767\n", - " (post-filter) = 2635454.95726\n", - " log(PSD) @cutoff (pre-filter) = 14.79703\n", - " (post-filter) = 14.62837\n", - " min(PSD) (pre-filter) = 0.97609\n", - " min(PSD) (post-filter) = 62691.79434\n", - " % of original PSD Power f" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "FSTAR_THZ = 28.0\n", - "jf, ax = tc.heatcurrent.resample_current(j, fstar_THz=FSTAR_THZ, plot=True, freq_units='thz')\n", - "plt.xlim([0, 80])\n", - "ax[1].set_ylim([12,18]);\n", - "ax[1].set_xlim()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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21NnB7BPPH/OMTdPzNs2A3VLB5cAjde08+zn+4n2X471XLcKbL5mHcCj3lfZw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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "ax = jf.plot_periodogram(PSD_FILTER_W=0.1)\n", - "ax[1].set_ylim([12,18]);" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. Cepstral Analysis\n", - "- compute \n", - "Perform Cepstral Analysis:\n", - " - first the theoretical distribution parameters are computed\n", - " - then the Cepstral coefficients are computed\n", - " - estimates of $\\kappa$ are performed" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " AIC_Kmin = 37 (P* = 38)\n", - " L_0* = 13.395456 +/- 0.103277\n", - " S_0* = 950203.538450 +/- 98134.481881\n", - "-------------------------------------------------\n", - " kappa* = 2.484534 +/- 0.256596 W/mK\n", - "-------------------------------------------------\n" - ] - } - ], - "source": [ - "jf.cepstral_analysis(aic_type='aic', Kmin_corrfactor=1.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "c_k = [ 1.52991432e+01 -6.79075038e-01 -1.52991190e-01 ..., -7.74510541e-03\n", - " 7.38870817e-03 8.29678141e-03]\n" - ] - }, - { - "data": { - "image/png": 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d65omtkICAAAAgK9iCHQMm8vqJEmRiCnHEXZlD1Vl8x7ALcOYj4RhGHI5DQXD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xaWaXZJlj522yZ99s5Xh/y3IEm1Ld361jsXxiUmAJPTwFSNRJ8jC2D0kqNkEQMDtaZYjEEa+BB5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\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Cepstral Coefficients\n", - "print 'c_k = ', jf.dct.logpsdK\n", - "\n", - "ax = jf.plot_ck()\n", - "ax.set_xlim([0, 50])\n", - "ax.set_ylim([-0.5, 0.5])\n", - "ax.grid();" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "K of AIC_min = 37\n", - "AIC_min = 2820.804281\n" - ] - }, - { - "data": { - "image/png": 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uJREg4HE96v8MtUUoFGrpsFIrSZKkMjZrRQtf+tVMTh85mBs/cAZzVm12u7H6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\ndy8HjmjLBkv7atCh6d7ZVZlQ+9TsVXzpngpSEf740kLuv+60gxZsN9U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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# AIC\n", - "plt.plot(jf.dct.aic, '.-', c=c[0])\n", - "plt.xlim([0,200])\n", - "plt.ylim([2800, 3000]);\n", - "\n", - "print 'K of AIC_min = {:d}'.format(jf.dct.aic_Kmin)\n", - "print 'AIC_min = {:f}'.format(jf.dct.aic_min)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Plot the thermal conductivity $\\kappa$ as a function of the cutoff" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "K of AIC_min = 37\n", - "AIC_min = 2820.804281\n" - ] - }, - { - "data": { - "image/png": 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cM0hPLcjTlU8tlrVWidH7t0Ft78Ro/fenx2r64F76/btrNfquD3Xag/NVVFUv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xNoEhISEm1BCpJboX4bqK4Okvu5WnHrwF4UV9Vg1M5tmRjK+XZREDO/OspDG8PZ8cQYbMyal/fN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\nSoqSNNdbwuk/3raNzOyLPPetKukySdNOeNjnzGyVmcVKGijpo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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# kappa as a function of cutoff K\n", - "ax = jf.plot_L0_Pstar()\n", - "ax.set_xlim([0,200])\n", - "ax.set_ylim([12.5, 14.5]);\n", - "\n", - "print 'K of AIC_min = {:d}'.format(jf.dct.aic_Kmin)\n", - "print 'AIC_min = {:f}'.format(jf.dct.aic_min)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "K of AIC_min = 37\n", - "AIC_min = 2820.804281\n" - ] - }, - { - "data": { - "image/png": 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vgxV12ldWp6YpSou2Fun/vbxS03KS9Z2zBmtaTvIxH9s0zebO0yfr7vOGq7re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\nANqWmVoAAAAaS6kFAACgsZRaAAAAGss1tdCivQf1r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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# L_0 as a function of cutoff K\n", - "ax = jf.plot_kappa_Pstar()\n", - "ax.set_xlim([0,200])\n", - "ax.set_ylim([0, 5.0]);\n", - "\n", - "print 'K of AIC_min = {:d}'.format(jf.dct.aic_Kmin)\n", - "print 'AIC_min = {:f}'.format(jf.dct.aic_min)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Print the results :)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " L_0* = 13.3955 +/- 0.103277\n", - " S_0* = 950203.538450 +/- 98134.481881\n", - "-------------------------------------------------\n", - " kappa* = 2.484534 +/- 0.256596 W/mK\n", - "-------------------------------------------------\n" - ] - } - ], - "source": [ - "# Manually print results\n", - "print ' L_0* = {:15g} +/- {:10f}'.format(jf.dct.logtau_Kmin, jf.dct.logtau_std_Kmin)\n", - "print ' S_0* = {:15f} +/- {:10f}'.format(jf.dct.tau_Kmin, jf.dct.tau_std_Kmin)\n", - "print '-------------------------------------------------'\n", - "print ' kappa* = {:15f} +/- {:10f} W/mK'.format(jf.kappa_Kmin, jf.kappa_Kmin_std)\n", - "print '-------------------------------------------------'" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can also visualize the filtered PSD..." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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u+v+Zf/CCkfzfXbOb7LltStWc3fbone3XxVkPd9F/TSMpznnd566cCEB2UXnI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HHaA3+Hzu41+Db6IOdjz3Pg5gHqedczHusUWJJfD1whOT0TW8sH+1GjqipvL9Fmn3z7Us0HjiM3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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# filtered log-PSD\n", - "ax = j.plot_periodogram(0.5)\n", - "ax = jf.plot_periodogram(0.5, axes=ax)\n", - "ax[0].plot(jf.freqs_THz, jf.dct.psd, c=c[2], lw=2, label='filtered')\n", - "ax[1].plot(jf.freqs_THz, jf.dct.logpsd, c=c[2], lw=2, label='filtered')\n", - "ax[0].axvline(x = jf.Nyquist_f_THz, ls='--', c='r')\n", - "ax[1].axvline(x = jf.Nyquist_f_THz, ls='--', c='r')\n", - "plt.xlim([0., 50.])\n", - "ax[1].set_ylim([12,18])\n", - "ax[0].legend(['original', 'resampled', 'cepstrum-filtered'])\n", - "ax[1].legend(['original', 'resampled', 'cepstrum-filtered']);" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 2", - "language": "python", - "name": "python2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.12" - }, - "widgets": { - "state": {}, - "version": "1.1.2" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/thermocepstrum/example/example_cepstrum_silica_old.ipynb b/thermocepstrum/example/example_cepstrum_silica_old.ipynb deleted file mode 100644 index 638e212..0000000 --- a/thermocepstrum/example/example_cepstrum_silica_old.ipynb +++ /dev/null @@ -1,647 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Example: Cepstral Analysis of solid amorphous Silica\n", - "## without API" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "import numpy as np\n", - "import scipy as sp\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline\n", - "from sys import path\n", - "path.append('/u/cm/lercole/software/scripts')\n", - "import thermocepstrum as tc\n", - "plt.rcParams['figure.figsize'] = (16, 9)\n", - "c = plt.rcParams['axes.prop_cycle'].by_key()['color']" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 1. Load trajectory\n", - "Read the trajectory file, selecting the desired columns." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "# Solid Silica - BKS potential, melted and quenched\n", - "# 216 atoms, T~1000K, dens~2.295g/cm^3\n", - "# NVE, dt = 1.0 fs, 50 ns, output_step = 1.0 fs\n", - "# Temperature = 1065.705630 K, Volume = 3130.431110818 A^3\n", - "# LAMMPS metal units\n", - "c_flux1[1] c_flux1[2] c_flux1[3]\n", - " #####################################\n", - " all_ckeys = {'flux1': array([0, 1, 2])}\n", - " #####################################\n", - "Data length = 100001\n" - ] - } - ], - "source": [ - "jfile = tc.io.TableFile('Silica.dat', group_vectors=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " ckey = {'flux1': array([0, 1, 2])}\n", - " step = 100000 - 100.00% completed\n", - " ( 100000 ) steps read.\n", - "DONE. Elapsed time: 1.71427512169 seconds\n" - ] - }, - { - "data": { - "text/plain": [ - "{'flux1': array([[ 91.472925, 630.61992 , 199.16002 ],\n", - " [ 71.403952, 666.80601 , 274.30247 ],\n", - " [ 47.754737, 678.10914 , 305.95706 ],\n", - " ..., \n", - " [ 466.489 , -360.14259 , -47.286976],\n", - " [ 414.3014 , -378.42595 , 166.42152 ],\n", - " [ 331.99113 , -400.35311 , 378.13009 ]])}" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jfile.read_datalines(start_step=0, NSTEPS=0, select_ckeys=['flux1'])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Define constants and conversion factors." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "kappa_scale = 5.229478e-06\n" - ] - } - ], - "source": [ - "DT_FS = 1.0 # time step [fs]\n", - "TEMPERATURE = 1065.705630 # temperature [K]\n", - "VOLUME = 3130.431110818 # volume [A^3]\n", - "kappa_scale = tc.md.scale_kappa_METALtoSI(TEMPERATURE, VOLUME, DT_FS)\n", - "print 'kappa_scale = {:e}'.format(kappa_scale)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Define a **MDSample** from the trajectory." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "j = tc.md.MDSample(traj = jfile.data['flux1'], DT_FS=DT_FS)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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md54Pm9tB2TWTHLsKTN6lPp48A8Sus3nXQcltAS6/miDoIDl529ox7dGt9C0UK0WcHT+L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8RmGf8z7FQvK0VQWRbLxhOV7NSouyXkaz38TAHXjBXZ3+AG2nHU7N1nKRSnKj58AZUs8y5s2v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rr8rntn7rVPuC6nscVxmBdnBiIjBxWsH9LpusZah957fg6feOIUPnLxCH7zh87f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\nXdVKMu3WgQjJkv6ZpBFJnzXGfNUY8y8kyVr7TUmflvQtSf+fpF+01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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# trajectory\n", - "plt.plot(np.arange(1000)*j.DT_FS/1000., j.traj[:1000,:]);\n", - "plt.xlabel(r'$t$ [ps]')\n", - "plt.ylabel(r'$J$ [eV A/ps]');" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 2. Compute PSD\n", - "Compute Power Spectral Density and filter it for visualization." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "FILTER_WINDOW_WIDTH = 0.0005 # filter window width [reduced frequency units]\n", - "j.compute_psd(FILTER_WINDOW_WIDTH, average_components=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "There are 50001 frequencies.\n", - "Nyquist frequency = 500.000000 THz\n", - "freqs = [ 0.00000000e+00 1.00000000e-02 2.00000000e-02 ..., 4.99980000e+02\n", - " 4.99990000e+02 5.00000000e+02] THz\n" - ] - } - ], - "source": [ - "print 'There are {:d} frequencies.'.format(j.Nfreqs)\n", - "print 'Nyquist frequency = {:f} THz'.format(j.Nyquist_f_THz)\n", - "print 'freqs = ', j.freqs_THz, 'THz'" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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AAMC3CK0AEGDxeFyO47h6zs3DjenkAgAALxFaASDgFhcXXT0fIRUAAPgJoRUAAAAA4FuE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\nUw+K3V9tJh42HYuX1mNY8R7gv3x3C5xGDlO7MXz6O1Jc4H2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mCAI2NzdVu5tS6sv09LRS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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# PSD (in reduced units)\n", - "plt.plot(j.freqs, j.psd, '0.8')\n", - "plt.plot(j.freqs, j.fpsd, c=c[0])\n", - "plt.xlim([0., 0.05])\n", - "plt.ylim([0., 1e8])\n", - "plt.xlabel(r'$f$ [reduced units]');" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 3. Resample and compute PSD\n", - "Choose a cutoff frequency $f^*$ from previous graph. Resample trajectory and recompute PSD." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Sampling time = 18 steps\n", - " = 18.00 fs\n" - ] - } - ], - "source": [ - "TSKIP = int(round(0.5/0.028))\n", - "jf = tc.md.MDSample(traj = tc.md.tools.filter_and_sample(j.traj, TSKIP, TSKIP), DT_FS=TSKIP*DT_FS)\n", - "print 'Sampling time = {:6d} steps\\n = {:6.2f} fs'.format(TSKIP, TSKIP*DT_FS)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "FILTER_WINDOW_WIDTH = 0.0005*TSKIP # filter window width [reduced frequency units]\n", - "jf.compute_psd(FILTER_WINDOW_WIDTH, average_components=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "There are 2778 frequencies.\n", - "Nyquist frequency = 27.777778 THz\n", - "freqs = [ 0.00000000e+00 1.00028008e-02 2.00056016e-02 ..., 2.77577722e+01\n", - " 2.77677750e+01 2.77777778e+01] THz\n" - ] - } - ], - "source": [ - "print 'There are {:d} frequencies.'.format(jf.Nfreqs)\n", - "print 'Nyquist frequency = {:f} THz'.format(jf.Nyquist_f_THz)\n", - "print 'freqs = ', jf.freqs_THz, 'THz'" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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F1toBY8wxfhUMAM2sngemptNp5ogCAIA5FTIH9XxJHdbaTkkyxvxY0tWStmWd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\nT0XneNs+reuvk1UwGFItqM0uBQ3pOqphgbKq4lWvUl91SDytUDO1To0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OzyXhYIB7X9pR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l/8cCL/vZUkqShGtDB3gFmXb4IgiFpCApUgthihUEjjnrW8tAhFMlkuRbZeVsUbHTPc5xDMZRmd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\nUGndaakhWjBKGq2xGxoa2n2jQ9wzKIrC8PBwRbuUQ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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# PSD of resampled series (in THz)\n", - "plt.plot(j.freqs_THz, j.psd, '0.8')\n", - "plt.plot(jf.freqs_THz, jf.psd, c=c[1], alpha=0.2 )\n", - "plt.plot(j.freqs_THz, j.fpsd, c=c[0], label='original')\n", - "plt.plot(jf.freqs_THz, jf.fpsd, c=c[1], label='resampled')\n", - "plt.axvline(x = jf.Nyquist_f_THz, ls='--', c='r')\n", - "plt.xlim([0., 50.])\n", - "plt.ylim([0., 1e8])\n", - "plt.xlabel(r'$f$ [THz]')\n", - "plt.legend();" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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8p3ZbJHp7eyt2LI4tJSKqDAalRESz+Hy+so9hCLmK2n4qINDl1OGrJ6x4YsiE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\nQmCC\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# log-PSD\n", - "plt.plot(j.freqs_THz, j.logpsd, '0.8')\n", - "plt.plot(jf.freqs_THz, jf.logpsd, c=c[1], alpha=0.2)\n", - "plt.plot(j.freqs_THz, j.flogpsd, c=c[0], label='original')\n", - "plt.plot(jf.freqs_THz, jf.flogpsd, c=c[1], label='resampled')\n", - "plt.axvline(x = jf.Nyquist_f_THz, ls='--', c='r')\n", - "plt.xlim([0., 50.])\n", - "plt.ylim([11., 19.])\n", - "plt.xlabel(r'$f$ [THz]')\n", - "plt.legend();" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 4. Cepstral Analysis\n", - "- compute theoretical distribution parameters for Cepstral Analysis." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "ck_THEORY_var, psd_THEORY_mean = tc.md.cepstral.multicomp_cepstral_parameters(jf.Nfreqs, jf.N_COMPONENTS)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- compute Cepstral coefficients and AIC" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "jf.dct = tc.md.CosFilter(jf.logpsd, ck_theory_var=ck_THEORY_var, psd_theory_mean=psd_THEORY_mean, \\\n", - " aic_type='aic', Kmin_corrfactor=1.0)" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([ 1.52991432e+01, -6.79075038e-01, -1.52991190e-01, ...,\n", - " -7.74510541e-03, 7.38870817e-03, 8.29678141e-03])" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jf.dct.logpsdK" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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sAQAAAHSLZQOszWYc/klRUJSbIkk6f9rgqBwvI7Jn95XPyqNyPBydJ5ft1Fsb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\nEq36v7YQBIHEgjq2JhaxPbmEepUOd1s5oV62HM+uamf60HrDu7OvJw1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eJpqhwSCYdLGh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\npL6LMcYj6a8l3Szpy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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Cepstral Coefficients\n", - "plt.plot(jf.dct.logpsdK, 'o-', c=c[0])\n", - "plt.plot(jf.dct.logpsdK + jf.dct.logpsdK_THEORY_std, '--', c=c[0])\n", - "plt.plot(jf.dct.logpsdK - jf.dct.logpsdK_THEORY_std, '--', c=c[0])\n", - "plt.xlim([0, 50])\n", - "plt.ylim([-0.5, 0.5]);\n", - "plt.grid();" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "K of AIC_min = 37\n", - "AIC_min = 2820.804281\n" - ] - }, - { - "data": { - "image/png": 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uJREg4HE96v8MtUUoFGrpsFIrSZKkMjZrRQtf+tVMTh85mBs/cAZzVm12u7H6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\ndy8HjmjLBkv7atCh6d7ZVZlQ+9TsVXzpngpSEf740kLuv+60gxZsN9U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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# AIC\n", - "plt.plot(jf.dct.aic, '.-', c=c[0])\n", - "plt.xlim([0,200])\n", - "plt.ylim([2800, 3000]);\n", - "\n", - "print 'K of AIC_min = {:d}'.format(jf.dct.aic_Kmin)\n", - "print 'AIC_min = {:f}'.format(jf.dct.aic_min)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- compute $L_0$ (tau) as a function of the cutoff" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "jf.dct.scan_filter_tau()" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "K of AIC_min = 37\n", - "AIC_min = 2820.804281\n" - ] - }, - { - "data": { - "image/png": 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9szxbd72xXG/eNkXj+3Y5rOc6f0xPnT+m52HHNLBrvAZ2rT8V+fTh3XTJuAw9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dhcnaewRqkhrEEI63f741l6JIlHRrpx7yAXwpMLde+Nn6MZiw8nciAmRxeufCNpjzHWlWW7RFHk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\nk2Xq2qKOLu/WwtO/RXkJXfc4J68gbPw/rs/QvZMXq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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# L_0 as a function of cutoff K\n", - "plt.plot(jf.dct.logtau, '.-', c=c[0])\n", - "plt.plot(jf.dct.logtau + jf.dct.logtau_THEORY_std, '--', c=c[0])\n", - "plt.plot(jf.dct.logtau - jf.dct.logtau_THEORY_std, '--', c=c[0])\n", - "plt.xlim([0,200])\n", - "plt.ylim([12.5, 14.5]);\n", - "plt.axvline(x=jf.dct.aic_Kmin, ls='--', c='r')\n", - "\n", - "print 'K of AIC_min = {:d}'.format(jf.dct.aic_Kmin)\n", - "print 'AIC_min = {:f}'.format(jf.dct.aic_min)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- collect the results :)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "L_0* = 13.395456 +/- 0.103277\n", - "S_0* = 950203.538450 +/- 98134.481881\n" - ] - } - ], - "source": [ - "print 'L_0* = {:15f} +/- {:10f}'.format(jf.dct.logtau_Kmin, jf.dct.logtau_std_Kmin)\n", - "print 'S_0* = {:15f} +/- {:10f}'.format(jf.dct.tau_Kmin, jf.dct.tau_std_Kmin)" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "kappa* = 2.484534 +/- 0.256596 W/mK\n" - ] - } - ], - "source": [ - "kappa_Kmin = jf.dct.tau_Kmin * kappa_scale * 0.5\n", - "kappa_Kmin_std = jf.dct.tau_std_Kmin * kappa_scale * 0.5\n", - "print 'kappa* = {:15f} +/- {:10f} W/mK'.format(kappa_Kmin, kappa_Kmin_std)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "- you can also visualize the filtered PSD..." - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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SME17mbwevF5vzC9XWFGXiCi/GJQSEU0H466Dje7+nByy3am+xV+/cnJ2plQP\n/PliO3SSeuLDfe4JBZYiP6c6dDmVdrl6bLmUKMMry3LOhm7T1Dpy5Eja+7S0tGB4eDhnfQi/triG\nKRFRYgxKiYgS6OnpyXq+YioM3sGE2zPJ0wx5NdhaHYQ2wTv9T85TK4/6PWkWJUpC70n8eGaKhoYG\nHDt2rNDdoAxl8oWCy5Xb/wtERJQcg1IiogT6+/vR1NSU/o4ivaGg2oAzeaM0DXsl1BgTD2FcXCRQ\nbVRgD8QPe7u7u9M7sQTofekvL6P1Z/ccZDrEUigyiqzRf2NvKJhhlnRmy3ZIdlNTEwYGoguT+f1+\nDvUmIsoxLglDRBRDttnRVOZ85lNQASx+CfNMyYcNVhkEhr0axCu2NH4dx3zSJphLK03IFStaIzRy\negGjxWKFcYkMrVYbvUGePJ/W6/Vg8uquc9TNNxe6BylLdf5zqhwOBxwOB6qqqsbu6+rqwuDgIDZu\n3Bh3P85BJSJKD4NSIqIYMsqOZiPHc85GfRIEkmdKAWBZiYxjlokfB9NrDtzEi3whaeO0jM9isSDQ\n1YXa2tqkbTkHcJwZFJR2dnZOyXl8Ph8GBgZQXV0NnS75pRRfT0REiXH4LhFRPhT4IvS5bnWZl3mm\n5EFpmV4kHL6btjw8dJstveHAiqLEzJr5/X5YJlQJFgXOak97w8PqbZZIlk1NNcvZ3d0ddxmhvr6+\ndLtFRDSnMSglIsoDvW80o/3+2qPHwyezGzjqCAB72o0AgJoUhu+WGwS8soR22/QNztLNNDU0NOCd\nd96Byx1dtMbhcODUqVNJhyQzsTXO1Vert1mitbU1Z8fi3FIiotxgUEpENIHb7c76GDq/Pa32w14J\nTTYNfnDCjOe6DBj2qtkaTxD48sEivDyQ+myL4+OG4i4vTh5obg+tWfp6d3ZFfaRwijQHSVe9Zwja\ngBNSMPGarfF4vep+VkvsDOvgYKQ6MIdWzlwulws2my1pu87OzrG/eSrFq5xOZ05fF3yNERElxjml\nREQT5HKdwlhEjKjtxpdLo37vcmlg8Qv86IQZzQ4t3rHo8KeL7Eg2srDZrsFfe/UAgO9ucyVtDwCr\nyxQsLZLH1jUNdTInwSUA6HxWaIPxA/1et4SjFh0uWRIpOKT3WQCfOszWXXF6SudJp7iMxWKBLMco\nekQzysmTJ1NqNzQ0BACYP39+0rZWqxXDw8NYsWJF0rYMNomIcoNBKRHRBNlWzpSUydVcExnwTD6f\nxa/BVw8Mc2mYAAAgAElEQVSZo+7b22HAVSv8MQNNTxD419dKMOKLBJZ1lakPLVxVqqDRFidAEwKa\noAuKvgQAIMk+CK0x5WPrfJaE2z//VjGsfg0uWBiAqRAxYozAgsHG3BWec+rxeJK25euEiCg3OHyX\niCjHjM6utNqfHBcMhqvlnowRID7ebMK1+0vxzujkbSdt2qiA9MPLfdCkEVufVipjwKuBM0Y8rfcO\nw+TqhSbohtZng9nRAU3ANblhWBrX6T9vNcLqV/s95M39R5IY35kJz0cwGITD4YgZWDDWmD3yudYs\ng1IiotxgUEpEc8rw8DDq6+sRCKSXzQzT+mwwuhNX1pREesVP+j3qW/E3z3TjiZ1O6CSB57oMMds6\ngxK+XF+Mve2R7Y81GfHVQ8VR7c5fkN56jYuL1GB4IEZgGM78SooMTWgtUU2a2eBYPEHgl6ciGdch\n79Su7djU1DT1S//MRLfdpt5mqBMnTmS0H+eUEhFNHQalRDSnhOeW+f3+uG0SBax6f2ZVdRPp92hQ\nYVCwY34QWg1Qqo++gDVpBe46M3pO5mPNJuxpN0AIYG9HJLA7vUzG8xfZsaEivcA4XKV3OBSUahQ/\niqxN0MSdCxr/IjvVgLXDFZ3xzUumdEIwoPcMQecdARB5DTBgSOK669TbDKUomVWVHv+64GuEiCi/\nGJQSEU0wcR3LaLnN5skC2NerxwJz5MI5POz20iV+fGK1F/ef5UJNjPVGH2824dC4obx1lUE8eI4L\n2gy6OC80bLjVEQpKg+p8uklVhLOcbzveqdC5vr1FDXwfOGGGL88rbOh9FhhCQWlEjOG7+Vhsdabq\n6lJvNAmDVSKi3GBQSkRzUqoXkzrvKCTZD0kJQOu3QyPHz7Bm4uCwDkEhYUtVJBq7d5sbRTqBa2t9\nuHalHytLFawsVXDjaV48cLYTlyyO9OHr44bt7l6aed8qjQILzQqOjIbr341/ftSftUEn9L7YS6xk\n4nedBpi1Aturg9hQEVqWZii39fdS+TszsEji4x9Xb7NQuKjReOFCZxy+S0Q0dRiUEtGcMrGybiAQ\nQH19Pdrb2yc3VoIweIdhdPfA5OiA0d2fkz74ZODlPgmvDepw9+EiAOqw27AlxQr2vtuBRUWRC1mt\nBNywyo+15Qru3OBFkW7yRe7qsjhpRkVGZc/fElYF1kjAxoogej2R4bsT6fyOcb+JjC+0j1q0uOzF\nMnS5tPDIEiQJ+J9tarb03qNFYxnURBItMROPpKSehmUQMTuE16uN5+jRo1PUE1W2lb2JiGYrLglD\nRHNaeF7hyMgIFi5cCJPJNLZNCmcLhYAkMpuXNpEQwGdeM6HXrcH4t+C6yvQKE31ouX+sSNCuBQGc\nNz+AxUWTAymDqxenHfo2AGDhqd+iddvd8BctjHnMaqPAqE+CIiIBqICU4wHLwHePRJa6+fBytTKq\nflwc+rk3i/H79zom7paZcU9JvLmuDEBnr7a2toTbY803Db8e+LogIpo6DEqJiABAyOjvaMKy1Ruy\nO0yS7a8M6kIBacRHV/lQok/vPNfW+rClKoiNSdYire55Mer30+rvBgC0bf4yvKW10W1NCmQhweqX\nUGXM3wW5HDr0qhIZt6yZvFyHX5HgCQLmcZ9QUozM7eQdXcBoDzBvXdKmevcAAkUL1F/ysE6pEAK9\nvb2YN28eDIbYlZQpM06nE8XFxXnPOnLoNxHR1OHwXSKa08IXlQZ3Pzzdx9Fxqjmv5/MEoy+kq40K\nrl2Z/jqKRi2SBqQAICmxM7AV/a9Mum9JaFmYf/SnECGncS0ezlAeGdXi4wdKxnb9wdkuaMd9Cv1/\n5zkxP1TQ6aglEpEWWZtgdA8k75KjD5D9gN85dp/dbo/ZVu+3RfbLQ1zhcrnQ398fe1g4ZcxisaCx\nsREjIxOLVeVerPmmmWLwSkSUGINSIiJEAiclmP36m4kEQ9em5y5Q8JsL7fjFu5ww5Omd2OAeQPnQ\nWwAAb9FijC5+z9i2gLFqUvszQ8WWHm0yjQVqer8NUpwLaofDkfJyG90uDR46acKwTwN7QIPz5wdg\niF4RBkuLFfz4XDWgvCs01zY9kYDf6OiE2Zr5GqS5ysIpigKv14tDhw7B50v/y4dp4fOfV29TzGq1\nwmazRd0Xfg6TzRXNBYcjMoScQSURUX5x+C4RUc5JiJdKdATUYOc/z5QRYwpoThXZGgEAAyuvwuCS\n9+A19wn0mv1YP3gYF1lPAssvj2qvlYCd8wN4ZVAPq19C5dgQ3vgdTbSm63j/+lpJ1O9GbexjFo/7\nVHq+S4/dyzL7kkArpx60xA04/C5ISgBCk+bY6glGRkYghMDo6CgWLVqU1bEK4gMfKMhpW1tbAQDb\ntm0ryPlzgcEsEVFqmCklIhonfBGp9w5DG3Dl/PiOgASjRsCoTd42W+EKtSfmbcIXBx7HQ5bn8IzS\nif+qqcLHSp0Ydk0uAnPRYjUIbLAl62DqF9tW/+SsY4879sePJKmFmwDgxyfNMdtMmeEmmO3qczQV\nw0WnrcZG9UaTpBp0htux+i4RUWwMSomIAIwf+gkhoPeOwuAZTLiHJs58zUTeHNZBFoA26El733QZ\nXd3oMZbgrpGn0R0cxkJdJa4t24XThAk9eh3uHfw5vBMKCJ1ZpT6mpqRBaer+0hPJNF62RD3fx0+L\nP5T1q5s8OKtGDUxfHcj/gJ6mpuQBV3d3d977MW3927+ptwKSZRnDw8NZB3cjIyMpZ/eJiGjqMCgl\nIhpHLW6SWvZDI6c3R1ARQJdLi6CYmmyJ5DiF2xfMg0VxYr1hGe6d/y+4umwXvrn4dqz2+9Gh1+G3\n9pej9jFpgfkmBS8P6KCMPQ3Jnw+9ZwjagDPmtrdHdFhaJGPvu+24Y70Xf77Yjm3ViYs0XbhQDY7v\nOZLB3FIOmZx1Ojo60NHRAZcru9ELLDxFRDQ9MSglIhrH44mVwcxNEGmLMYw1bxQZPy4SOKWVsVhX\nhf+suRpmjbquqVlrwj0L3wsAeMF5ECPB6Aq1g14Nej1avH9f2bjANFp4Ddex4c4+C/Q+S8y2joCE\nZcUKinTq8NxUvGdRJJsVa/hvIsN5GGqby0qslL5wdjPVwlrpiP1/PjWcM0pElBsMSoloTmpsbER/\nf/+k+6V01jpJw7BXwn8eVLN+Xz/TnZdzjHfS/jZ+WV4KLST8e9WHUKKJnp+5YeV78T6nCwHIeMF2\nIGrb2TWRgLDZnv3HhC0goUSf/vP6qbVqsaJ9vSkWGgpFvHN6qC2lra+vL+N9kw0FdjgcqK+vzyrw\nJSKaCxiUEtGc1dPTM/azyFE2NF4q8EsHi9DjVudpVhvzm11xB9142PonAMAN+rVYZVg4uVHVKtxs\nU5e82O98G3BEih59c3PkAtrij/0xkerz9cBxE0Z8Giwyp5/h2lipZicfbzZBzn2CbJzJfw/Jn/si\nV2M8VvVGM0amGdHwcGOnM/bQdiIiUjEoJSKaJLdBoyMA9HrUgLSuMog1ZYnnU2br/0Z+j36dDnVe\nH3bXvD9uuwWXP4UzfD7YtFocHf7b2P1aCfjJDvUiusWevOCRpMTOFskK8JdeAwCgtiT9qHKBKbJP\np2tqP66kCUvKGJ1dEH3vRO5QFMBrQ0Ysbeptpvj619XbNBAODmONcpguOjo6Jt3HYb5ERIkxKCUi\nyrO+0PIna8pkfG+7G9o0k7J6zxC0fnvyhgDe9DTipUAbjIqCfy+9ABqtMW5bSZKwq3Q7AOAfiM7c\nLS9RsLRIjjt81+Adgc47AkmSYHTGHi57eDQS0G6tTn9OZokeeOBsNTg+bk2jGnCOAoBAINJnbdCj\nBqJhti5g9BQQmAPDMi+6SL3NYbkKKrkkDBFRbAxKiYjyrDs0bPfT6xIHMMuP3I+ajj8CYlzwIxSs\nPvgNnHbwLuh8iYd8WmUnfmJRh+1+zmJF+bwLkvZtS/WFkATwhs4HtxJdTbhEL/DmsB7PnFI/KiZe\nlut9VjQ3N0MTJ1O6r88w9nOm67IuK1afix+fNOPFJHNLhRAIynL085eFzq7O+Bvl0FI6Suys96zK\njB0+rN5mgUyDwq6urhz3hIiIxmNQSkRzgtVqnVRBVaMZ9xaYwwSGNC4okhXgf4+pRYZqEswllZQA\nim1NmNf5HKq7XgAAGJ2dqOhTl2zRyh6sefPLcfdXhMAjlj/BoXhwjseLG+xOQBM7EiwuLh77uUpb\nik2KAX5JwiFvS1S7cAXcnzXGjyh9vvjL4lQZ1efhufemluWNpWjcMqX3HzcnnVsqhIA2mPp8UCno\nhSlOpjcX61lOCoLco1kfc8rdead6mwLHjh1DU1NT3O1+vz/utnzK1ZzQ8V9WCCFm15cXRERZSBqU\nSpL0U0mSBiVJOjbuvqclSTocurVLkjQ7vkIlolnJ7/ejtbUVbW3R8/jiZk0mXCfGywRO5AwADh/w\n9UNF+MJbRbD4JAx4I+eoTBCUVvS/OvZz6Yj6lrq04VEsav1VSufeY38Zh7wtKIYe9wyNxH1zLysv\nw9KlSwEABqOaydyplAAADntbo9p+YFkAq0tl1FWp/U4nbrf7JTzTYUS1UYEuy68/Hz0vEhDs/lsZ\nnmyJPSTZarWipbkFujjrpcZi9Ayk3DaTAEIIAQgBrV8tKgXr5PmGFOHz+eBwOOJuzzYozdfw2ba2\nNoyksBSRoihj7U6cOIG33347L/0hIpppUrlUeALApePvEEJcJ4TYLITYDGAvgGfy0DciopwIr204\nMaun1cbKAKYfePhk4LftBlyzvwwfPVCC+hEdjlt1eLTJhLveVpeBKdEJaOJdDwsZC1t/Pfar2dkJ\nTcAFg3d4UtNVB++GJhCdCdznfBt7HK9AgoTv9/dgoSyj77QbYp7KoDdAE+pIWWkZlq9YjrOkKgDA\nO95TUCYEXlVGBc4MEoaHQvNJ37c4+2zjsmIFN6yM/O1+3WZEk23yx9fg4FAGR0/+9051Pm88GvcQ\njO4+SL7sjkPTU39/P0ZHU8+A22xqgSyv18tMKRFRSNKgVAhxAEDMd1tJ/crxWgCpfZVPRDSNGAyG\ncb9llkGRFeBDL5Xhp80mAEBQRI6zv18/Np/0J+fFz94tbHkaAOCsOAOyVj1O2XD92PaAsQqekuUA\nAKOnH+WDb6Ci7wAUoWCP/WU8av0zAOBfSnbhfI9aNTZgqk7ad0kCzCYzlujKsTAYhE1xoz0QnTlc\nXKSg2yWlvSRLq10LnSRww6r4w3vTcePq6ON89s2SnBw3kXDAoA1mvq6sJEmR6sRiDsw/nUJ2e/pB\nfj4ypYODgwXvAxHRTKdL3iShXQAGhBDN8RpIknQrgFsBYPny5Vmejogod2Q5+6VZDo2m9jZaFWfo\nrtZvR2X/AQBA56Lz8JdlW9A+8Bd0eV5CYMkiFJsWoMK4EIuFFnVdI1gSDELb8wc0GvT4hdSArqA6\nFPDmsvfilu5D6uPSmuCqWBd1nurq6rjDC4W2COfbvdhbVoLD3taodU1PL5PxO0VCh0uDVaWpRaY2\nv4Q9HeoQW/0MrVwwNC7rqgtlSkXMrGp2AaXNZkNLSwvWr1+PoqKirI4116QbDOaLouR1EV0iojkh\n26D0BiTJkgohHgXwKABs376dXwcT0bTh8XjiZFuSv1UdHNbilEOLn7Womc1yvYId84N4oceAnfMD\nGPRq0BRa4/POM+JX3TW6ehEA8GR5GR7xvQSfNwgUjwtOlFHAow5W+e28CdnP4AhqtGX4t8rLscMb\nQOmIuo5m56b/ADTRb+/xsjOSJMFXvBjn9Xqwt6wEx30duBLnj20PB6LtztSD0ndCQ3d1UvLncTho\nByBQoytP2vb377VDA+CHDSYcGsn24ysPhAD6DgMlCwCpNMb2yXdZrWpFZafTOX2D0v/+70L3IKZY\nw+8lSUqYec5HljLdoJSZUiKiyTL+VJckSQfgSgDbctcdIqIpIhQA0uTsoRDQyImHnFr9Er7xdnHU\nfV8704NXB9S31JWlMjZXBdFkN+Nbm904e178NTpLT/wQn1w0H4dMJkAEscm4Elf3HsE6rxOuBTvR\nvvBcDMt2DAQtGAwMw2E9DAEJi4NBnCNKsHrdp6CXdNBbXxs7pt80L62nwlO6Clu96hDTJl83gkKG\nTlIv+CsM6gX+r9uMeM+i1NYatfrVi+7/tyN+FVy/COCh0efwhuckAOAs0+m4o+qDqFu3Ac1NsQff\nGEJZ1+XFCl7s1eCxJiNuWeNDxtf4WQybDQQD0CgKosKicNVl1zBQEiMojWFGBCjnnVfoHsQUVT07\nJFlQmqlEx0zlfByiTUSUWDZfNV8E4KQQInYtfSKiHOru7kZ5eTlKS1O72E+myNYCRWuEV1oBANAG\nI9lMk6sn4b7uGLHZxgoZQQV4rsuAbdVBrC1XcMmSQMLKs6OyA59fsghdOi0qNSW4vWo3zjStwvK+\nXhT7LeguOR3FphVR+6xv+Ou430bQYWuFotGjyK4u52JZuAuKzpz4wU8kSXCv/zfUWp9BuwFo8/dj\njXEJALVAEwB0ubT4/jETPnuGN2k13RGfBjpJYHFR7AySEGIsIDWEwrq3vE14YPR3eEJTl7S7myrV\nP8DeDiP8ioTb13kTtM5dMDA+sGhsbIQRQayZd3rOjj9tvRb6wmOaBaczIqAnIqKUpLIkzK8AvA5g\nrSRJ3ZIk3RLadD1Y4IiIpsjAwMCk9QtjrfOXztp/yTKi8biD0RfDX93khiQBW6plPH+RA2vL1WAs\nUfBmlZ349tBT6NJpsUbR438WfAJnmlYBAIZqP4SRJRfBVbF+0n4tZ90Db9ESuMvUtiuO/gAr3/ke\nKgbUwKF/zUczekzekuXY5lWfjwZ/19j92nGPYV+fAW8NJ/8us82pQZUxfrXht7xNeMNzEmbo8HR3\nN/Z2daFclnHI24I/9L2S9PjV4+bn/qN/XH+mKkgRAoA0ad3bWLQ+KzRea/77lE9f/ap6IyIiypNU\nqu/eIIRYJITQCyGWCiEeD91/sxDikfx3kYgotrfffhvHjh1Lel9YasFq8jYDHvWt06wV+P5ZLuxa\nEAlOksZFQoap/1X8b//P0Bscxek+P37kNKFKG8kAe8pOw+Cqq6HoTJN2D5hq0LbtG+iPs+RLpmRD\nOTYJNcPa4OuK2vaTnZHgfV+fPumx2hxarC+PXURKEQK/sauFnT7l0WN1IIDaYBBfHFUDt4da9yIY\np0ptWKkh8jeqMU3xsEj3KEaOvxSpqJuEztWX5w7NXTN1SGy+hhgTEc1kM7QuIhGRelHq9/uT3jd+\nmF8uhvy1OrTQQODXFzpwRkV6FXyrul/EY5Y/olk4sCSo4NH+QZRnULzTV7IMDTv/H5wVZwAArPPP\nRcOu+N8TakIpT402+m1//NNRB3WZlZO+rqj1ShcVCeycrwZhpxyx1naN6PdIGPZpsMAc+0Ed9rai\nMzCEam0pPiBHAvHdThdW+/3o945iv+tIwnMYNMC921y4ZLEfnU5NzOHUETm++PdYMDgwCI2S2vxa\noliam+MuWkBENCcxKCWiaSMQCODEiRPw+XKztmUsWs8wiqxNyRsmMOCVUGMSY4V30vFc4BT+UFoC\ns6Lgwf4BVCsKetd+IrOOSBL6V18HZ+UGDJx2fcKmVZVVmL9gPqoqqyZtMxepGdL52lIskBW4hBfd\nwciSKFqNwNfO9ODixX4EkwTQh0NVcTfECdZfch0GAFxSvB3zhg4CABp2PQINgFusaiXkv7oOJc0k\nbapSi0kFhYRBb4I/RA5jUiEE4JtQrdk1nLsTUFxOZ/x1fmcaSZLgcDgK3Q0iommFQSkRTRsWiwUe\njwcDAwN5O4fOEyOIUCIBlJTCsLoBjwbzTemnN0/4OvCQXh2m+u3hUawNBDC6+N2Q9SVpHyssYF6A\nro13xBzqG1ZSUgJJAqqrqhIOL5Z1xdgyVoV3crEns1bAIyfONIe3r6+YnEm0yS7Ue1uggYRLZPUx\ne4vVgko9az+Bi91uVEg6tAcGcCrQn/A8QGQY722vl0RldvNp0mlm+nzRGWDiyIdEkn2ZkYu1iXPN\n7XYXugtERAXHoJSIZhSv15vTrImkBGB09479bnQnnwPY79FgYZzhqfEMB+24f+RZyBLwCasdl7rU\nC9Hh5e9Pr8MZWLp06aR1S2OR9SWo86r9avFHnhONrAaqJi3gCkoY9sYOTP0y8GiTGhybY4zyfd3T\nABkKdgQ02HrsxwAwNjfWVbkBRgF80Kquyfp31ztJ+7tm3Lqpr3fHrsAr5TBV2tLcgq6uruQNZ5sH\nHlBvBTJp2aYsFGoup8cTf63ihoYG2Gw2NDc3c64pEc1ZDEqJaEY5fvw4GhsbM95/YlbCbG+LWg4m\nGUUAFp+E6jQK7PhFEN8f2Qu74sa5Hg9u9ZfCWXkGBms/nDRLajLHz4CmSpIAlC9L2k7WFWNTaOh0\n87igNMwXigHvOxZ7yZnHmiN9jVV5uN6jDpu+3Do4dp+n7DT13KHnYbdTXdv0n55GKCJx4F9mEPhK\nnfr3vP8NW5xWub3Id7nir70KObXiRzPO5s3qrUB6eye/FgFgeHjmDJ0e/0VarHntra2tsNvtDEqJ\naM5iUEpE00b4Yi1fF2bpDAOMxyMDCqSx9TuTEULgMcsLaA30YXEgiP8dHMHwadeia+O/Y2TZJQn3\nPX3t6VixfEXCNikzFCdtIuuLsd7vhw4adAeH4FGi5/Z+bJX6+zsWHf7YpQfGXVvLQl2jFQC+tmny\ncES34sVxXwc0QmCXe9yXAOMu0E+e/yOsqzgNywJB2BTXpCrAsRRH/R3SLWKV49fZUENujzdd7Nun\n3oiIiPKEQSkRzQqyLOe1QFKYM6AGPqX61AKaF12HsN99BCZFwYODQ6hQFASNlSntq9VooBm32Gft\nytp0uzvuYHpg4aaETWRdCYwCWB1UB722+qOHMpfogUWhYcsPnTTj/qMGPHrIhj3tBuzeVzbWbueC\nyfNJj9neRhACm30+VCrqMezVW6LaCI0e0vor8L5QNvJ1T/Igb0u1OkdQpwF0fnuMFgI9Lg1cszSJ\nOSXuuUe9Ud4wQ0pEcx2DUiIqKJfLlfWcMUVR0NjYGLU+qcVigdVqzfnF3m/ajACQMFOqCXpQ0/Ec\nGj1t+Jn1RQDAXcMWrPMHMLroAgRMNRmdW6tJvBxLcrEzieEMtd+s9muzWy3e0xJjCO/4x72vV4+/\ntHrw+Lhhu4+eF3u+74mBPwEA3uNSs6Sjiy5Azxn/Nrnh/DNwSWi+rTqEN/HfTyMBHztNrQo86pv8\n+BotEj75Wgmu3l+GkThzYYmmUi5GbBARzTYMSomooE6ePIn29vao+1IJJMfPDfX7/ZMKibS3t6O1\ntRUWiyUn/Qz7U486RLU4Qaa0su8f8PW+gPuHfwMZCnabz8Rulwv9q67FwOobsjp/0FCWvFGGAuYF\nUDSGhPNKv7zJjSuW+fDpdZPn4X5rsxvLiifPAxVC4A2z+rztCv2d4gbmRVVY5w9gSWgIb2uMPgBA\ndXX12M/lRvVvceeb0UOUhQD+45+RgPnuw0Wxz5lnbo/6WpUUBiOUOCgNBrn+LRHNTQxKiWjaiFUA\nJJ5k6/wpoSGigUBo3KZQoEmjoFEs42NlszZ2UCopARg6/4DbFsyHRZJRZ6zFrVgOAPCWJC82lEzA\nVJ28UTwpPL+ddXeizqteNLf4eyd9QbC4SOBT63xYVz55aY2z58W+oO4KDmFUq8X8YBArA0FY558D\n68LzY3fAUAIJkeD1kLclaZ/Da6IOTViv9H+PRReJanPm6SOv922InrehKOOeq3HPmyc0h1bjHpq4\nJ1GUo0ePFroLREQFwaCUiGa8cAAaSyAQgMVigdHdB5OzK+1SOOOFq89uqw5ibZkMSZk8UdE08Bru\nWDAP7QY9VgeBz1dfieWNj6n7h9bkTMW8+fOy6GnmPCXLsVwWKJNlWBQnRuTYwf/ioshzbtIK/P49\nseZzqhpcatXds7w+tJ51D/rWfgKKLk7WUpLQsPNh7PKo2dq33SeTfpmwohTYvdQPs1ZEfXHw9341\nO3v9SvVYK2JkcXNl1DKKxsZG9PX3A0KGZjC94IJzCueOdL58IyKaKxiUEtGM19enFuTRewZhtrdG\nbRsYGEBPTw80wdjrWKZKVoDhUCZu14IA1r36Gax79Q5ogl7ofBYUWRux+pXP4EH7izhsMmJBMIgf\nD1pQLACtrAZFcQOxGGqqs8iIxpPKxbBGB2f1majzqdnSNtfJmM2KQsuenlapw68ucMAQZ7qrJuBC\no+MIAGBd6abU5tNKGqwtqYNJUXBKHkHVm5+HJMf/+0kQWFEiwyNLGAnNKw3PL/3gMh9uWu3DJYv9\nsPjzFwzYbWpQbrVY4zeKEXfOiADlJz9RbzNAvoJ7nyxg9U4eHUBERLmRfDV1IqIplu6FZbi93hcj\nIBAitWAsiY+9XAKrXw1Kq7QeSEK9QF37+p3qaQDcW1WJfcVFKJUV3OepwGJfL/Td6lIajqrElW9T\nJbLK9abGumAH6npa8WqRGS2edpxVfnbMdr+50A6ULIQpQdHjNW98HkeXLwG0Wpyx8kNAitMqnUsv\nwTk9/w//KDLjZbMZm/wOBOKs2SopMpaFppN2ujQw62R89EApAGBJKKNbZRSw+DV4eUCH7dVBmKfJ\np5/ks0WPC5+O1q4tdA9S8lKbG2trDFhSmts/ri8o8PkXh9HnlPF/V8xHsYHf5xMR5RrfWYlo2oiX\nNco0+6H3DKLI1pyTi/5wQAoAq7ST5wY+Xl6Gp8pLoRcC31ZWoGzZlQCAeZ3PI6grQc+6W7LuQyx6\ngx7FxcnXIE2Hr3gp6sLFjoKDcduV6oFSX3/CYzUZ9LBptVgoA4uMqWd//cWLsb7mvQCAA0VmaIPR\na5+KCWnH5aGhuW8N6/B8aL1UAHj/UnWItT80cve/jxThyr+XYagQlXgnntI1Ap2jGzp/guzqdPDc\nc+otD+x2O2Q5+wxkQBb48UE7vv5SepW8ZUWMvb8EFIGnjjrwp2YXZEXg0UM2XL+3H881u9DnVPv4\nnUBXPlkAACAASURBVJdzWziNiIhU0+S7YiKi9KQSqOpiZU4z0OaI/v5uuRQdlP6upBgPVlVAEsB/\nDVmwZtVV8OvMY9utC8+D0Bpz0peJiouLsWjhQjQ0xB5mm4mgsRIlG74EjPwMTcKBoJChkzJYjkbI\neNOkZjfrtPNSHqq6fMVyDA4MYlPZFsD9Gl4zm3CnswsoXRF3nwqD+nr4XWfkedZJAtrQn+6aWj/2\ndkS2PdZkwmcXFDhDGZqTLClxKq5auwChAJXxH/eU+P731X8/8IGcHtbv96O5uRkVFRU47bTTsjrW\niEcNGu1+9W8qCwFtktebXxb4lz8M4swFBgy4ZLRZI38HRQB/aVXnMv/qWGSZo+bRAKxeGRWmzJdn\nSvbeJcsytNpsl38iIppZmCklomkvN/PEMj/Gn7oNUb8vb3gYANC58d/x4vwNuLumCgBwc8XFqN38\nXbgr1kHRRbKXma5LGoskUi/WI48LjNNhNBphNi/CiqACvyTQGYifLU2kxHICb4aG3J5RdHrK+xUX\nFaGmpgY1unIs182DR6NBb/ce6LwjmH9qjxqoTSBJkysi//KCSJGmcoNQhxuHdLoK8PGX7kvQPQx4\nRvPSlekgXKBs4nJOmWgYjhQd+0OjC9fuGcBP6m0J97nvdSs8QYE3enxRASkAvNk7eUz6ty9U/5/v\na8u+v4kcPnwYw8PDeT0HEdF0w6CUiKadiUFoR0dHgXqiMoSCnQfOduKH50SyJi0lC/D1Ej9kScKH\nSnfgstKzAI06AEXRmdC+6fMYXPFBWBecF/O4VdVVWLY8skzMosWLMu6jRpubt/OKyoqxnzfIegBA\nk78no2PpHW2oN6nZybVlWzI6xlbzGgDqEN41b30N1T37YLafitn2qhWRQOLebS6U6qO3l+qB/9rq\nAgC0O7UIuB3I5ssKyk44c57tl04BReChtyIB6JNH1C8j/nrKg35nEL2O6IDTFVAw4pFR3zc58PzW\nBZU4c4EBx4fUyc/zi9WMZW25Dmuq1BfUiDv/BY9stsQBNRHRbMOglIimhNPpjJo7JoRAfX19VJt4\nwztHRydki6a4MMwphxZLi2SsLVewpkxBwFCO3gXn4Hsje+AWPpxtOh3Xl104aT9P+RqMLL98LFCd\nqKioCCXj5oMmG94qICC0Biha/aRtZtPkrKiijV0YKJ5ly5dh0cKFY/2oC6jPc4flrbSOE9bh6YRT\no8ECbSVqdGVR21KdB7vdtBoAsL/IPBY+aoOumG09strvfz3di01VsQOHrdWR+wdHhiElWE6I8itX\nQWnTSCRLes6S6GHyn/7zMO54YRh7TkS+TPrOAQtufX7yvPA9Vy/AxvlGLCuL/H/94nkV+PL5FfjG\nuyph0EqYX6zFX095ICuZ9zmVx+v1ZlctnIhopmFQSkR5J8syGhsb0dLSEnVfJnQ+i1q8KN48vBzz\nBIHDozp0u9WMiTbghN5vw30mN3qCI1iqq8Gnqz4AzRQu7REwVKXUTslyHuvKkvUAgMYExY4SOSIP\nAAA2mCbPiZQ0qT1fqw2LUQY9evQ6nNKrwYLeF3tI61Ur/LhwYQCXLElc4vdjq9QL/nandqyKckHN\nhGVh8iBXQakjtIDwHWeX44vnVeKGjSU4d0Jw+qvj0fNCw85cEBmaH+7PJadFlm5aXqbDWYtNY3NI\nl5Sq/1q8+f0yg0EpEc01DEqJKO/CF525mDum94YCkjTmVmbDHlAvVLWS+hhWHbwLLxQX4UWNDQZJ\nhy9UXwWzJj9FjCbRp77OaZiQtICxLHnDGMoX74ZZEejW62H3p1d11ODuR30oobvRmHmhHo2kwRaz\nOh/1H0VqNljnd8QMZCqNAl+q86A4SQm/61f6odcItDunz0eg5LUAfnfyhoXw85+rtzzJNij939fV\ngmYb56kB5tXrS3DdhpKx7etr1Bfi08cdcAei3zfetdyMBy+pwc8+OH/svsWlOjx4SQ1+feUCaCd8\neRIOWA90eqBk2O98raVKRDSTTZ9PZCKikMQXbZlc0GV+EegNDQn94kY1oLYID75TXQkAuLH8vVis\nT32Zk2Sk0JohJSUlSVrG2DdOts1TfhpQnVllU61GizVaNSvb5mpMeT9N0Ivl9Xfj7dB80g1ZBKUA\nsC0UlL6w4AwoGgM0cYbvJqLTRSJVrQYIKBKe6TBi1CfBEUqcKQK496gZP202wpeHBKrXFz/7pXX0\nAMOpP8dTatky9ZYn2QRp8rh9q8yRS5qaokj12p3L1C8zfnPChTd61L+BBsC7a804d6kRS8t0KDNG\nXw4tLdNBr538f6o81O6po05cs2cALj+HfxMR5QKDUiKaNlJdMgTIf7bhtteLcdmLZThmUS9uzTpA\nkv24v6oSdq0WW7QLcXHx1rz2YTpYo18IAGj2daa8z9rX78RxowFujQaLdVWo1E4OstP5W28yrYIW\nGpwM9GPIVAFtIP2gVG+Inoe7rVod/v3RA6W46eVSAMAxixb7+/X4bbsRH3qpDK8P5nbVNKdDHUIq\nKwqULOYkTrmnn1ZveZLN/+Vw0aFbtpRGDaEv0mtwy+ZS/OvWMqwLZUpNWgmvdXmxoFiLX1+9AJ85\nqxwmXXqXQROXgrnx95kNbSciomgMSolo2hJCpHTBmlqAk/qFr9Uvod2pXnw+dFLNspTqZDQ7juH5\nkmIYFIFPVl6aVmAVi8FgSN4oytTPPTzdqGbIGuX0lqgIr0+60Vg7dl+mz1eRxogzjMshIPBKkfn/\nZ+/M4yQp6/v/eaqq72Om575n74PdZYEFBDmECHIoEgQSEWO8EjwxJhqTH5pEUWPEKAavqDEmXqiI\niOFSQU4Rlj1m2d3Z2Z17556eo++jjuf3R01P391V3dU9xz7v12tgu7rqeZ6urq76fp7v9/l+wUvB\n4gcV4RN7kqGyEZmg389hvzddhH6mR0e4tI6PdrLvJIaGh7QfsNJ885vqX4UoR5QOLKiTC9012cm/\nrt/qwLWb7dhQa0J3jYCoTHFoKg6PlStawzQfjfZss6nUMF4Gg8FgJGGilMFgrFoO7f8jeo8dzdha\neWE2EMi+NV489X38z9zDAICbrbvQaG0rux9LhigtJtrKFcEAALu+cOPN1g0AgD7qh6xxHS8FwUt2\nVdCdX7NdV3/52GdVS8M8ZxHAS/rWXprD0yByevkPlwngSFJMPD9jwgMjarhxQrBauPLFRiScvo46\noV/isXj2xjMMI6IdfEsJh9pcfMH9YnKyr4EFscCehSGE4Oe3NOPCNsuyQA2J+j4HW1PKYDAY2TBR\nymAwVh2UUkQiEdgCw6D51tkVMez4uL9k+RqR0o+styh4JdyDPosZrZKEN7svUYdQYvsAYHfoT1pk\nNpmwcePG3G9q/bC1XQDJfetfNpZT2nKb69EuSohCwWkxu4xGLiK8BYcsqsC7svsCjQMrzPlL9Ur/\nYJIQl4KaDXtLaBybD/wzGg/dl/XenTujaLCoomYyrJ4TC0dxRYuEN3bEYeGNFw+Li4uGt3kmM+wT\nYeYBl7mwOfO+fclkXxd36CuVlAlHCD5xiQe371HDvn15MvGenIvj5p9PYbAMEZzA6/Wya4fBYKxr\nmChlMBhVRZZlxGLZReuBdE9gIlMvJ5dm0Anx0g24uKKO477XBHFunYRP713ENz01AID3L/jAW8pP\nbmS36xelAFBXp60cjIo2pUoK7UcI9i2Vpxid/DWIUvj7MEVmccxEIRKKblMTGu16xpufJqEWW0xt\niBCKPwiiNu8ipdh08G4AgH3u1ay3r2kX8YPLgxAIxbPTavjnfRep61XrLQr8IoepiLGe+ampqVwD\nZd6zDLSejzG/hM0eE4QiJYb2NFnw45ua8dVrGvCBC2qMGOJyciR/LFuUTgQk/OcBPwDgyaHys46P\njIxgYGCg7HYYDAZjtcJEKYPBqCqnTp3C0aOZIbnA0NAQRDEpeDJDVTmdIZul8uiYCT8dUsNqa8wU\nn98XhjfwM4yaTOgSRdwQDOX1NFacFapnuZeo2YaPRodRN/a7gvs6Fk/gpaX1pLss3eA5487VJfaz\nAACP2y0wz58our8lNJb2Op+glmjyvHbYVYGx2aX+/24N60plRSnZbU4IAUkNi14cBRSW0XVmpngC\nof55Eb1eEU2OwqG7CSwCUbPqaqyRW4xEJl5fTMFvBsO4+edTmA5JGPWJ+PDjXgz71PWu5ozhsQkI\nBoPByIaJUgaDUVVCodyZU+fn5zE2lhQRqaKUj/thDY6Bj/uWt1FddUqLG4GLcYL5GMF9vTaMhlQr\n0spTSFTGj+URAMBfhSj8rVckx6hjBMZQmR6Xz/XSaVIER9r7rZveDQB4xWYFH5ks2BYvBvCSLZHk\nqLtkAW+2ZCeButi+EwTAc3YbTC9+pngbEVXYzHVcDQCw+07m3O9926MgoLj3wuCy7j9nKTuvP174\nnFOqJi6KRvOXe9FFeA6I6KsJW3EeeED9qyLFzufAgohPPDkHAPBYtYlSo0n1lCa8oh941IuRJTGa\nIBg3VoTGYjGMjY0xcctgMNYVTJQyGIyKo9V4SogjSmmaKE14uDhFXNZlfGgaVr9xGUxve8aF2591\npW2z8sArkZOY5Cm6JIqtu/4J01vealifRqIrCVIRoSjb0sOTG8z16JCBIMehH/lDEYkiwnz6/3DE\nYgYPDmeVUZ/UYjaD49PHWce7sNvUDpEQPOJwgMiFhYsppoqWxaaLIZtcaBh9LOd+N3bF8ejVAWyv\nSU50mDnghs74cp3aikIrUBTVSBoa1D+DSY2M0Mvnn08K97BYHc+yyZSe4de1JEqnQ+nf32iGKA1k\n1DItV0wODAxgenrauIkQBoPBWAUwUcpgMFYlxUQWFw+qItUActmIXQ4ZJg54InQAAHBrTABXpbDd\nintA6rcCrlZdh+z2qDVZD5L8otTlPYgXbFYohGCnpRN2zlLWMLkcob+vd6mJk+53u7D55bsKHu+c\nP4aovQ1xRxvCTefC7u8HkeMFj0mlyaogKBEES7jM9HyHgta6q2IEiPr1D6Zcvv999c9g+vv7SzqO\nUorFpeRCmz0CbtzuKHJEZTBxBAIH/Kov/ft78ETy9dY6E/ZPxPDtg77Mw0uGeUgZDMZ6hIlSBoNR\ncbR68dK8o7mOKccYK3CsT8zuS6HAqDiDY7FR2BQF10hOXd01NjWiqblJ3xgNdspZXHXo7OzMfsNk\nBVwtWf0ms+9mD2SvQ81++7KQO0kVoGa6fdau1nU9z7ol6/36+vITRF1o2w4P58Cg2YSDggT3zP68\n+5pic4g5OgAA1gU1i3Pn7JOa+2q2qcJnJrpKHpWzJ4D5FUh2UyFRKklS3vcK3TNeHEteg1+8qgEt\nTiHvvpVGSnGCbq9P96R+5Q31qLOp184TAxHDxGSiHUNKRDEYDMYqYZU8aRkMxnomzRijFFByG6NF\nRalGTJHiSVJSmY0m+7IulQEROOA3wYMAgDcHQ5CbXpP3+K7uLtiWxFgCQgjsttIy7BoBJRzcnno0\nNekUxnk4z7EVPAUOmYCAFEwT+ebQBJzew3BPPIMXlrIKJ0Vpyrm1lOc5BQCB8LjaqXptv11bg7a+\n/4IlNJ61nykyC3PUC4VX+5TNLsgA0P8w7PPHNPXVZFUVx5OTpiJ75qaoV3ade7xisVhZIbr5WIyq\n4bIfNiiLrhHUWDj84yVqQjCOAP91QyO6akxppWrCS/VMmaeTwWAwsmGilMFgVA1CCMyRadj9g0CB\nREWU0rxOw/zvJDHF0svBcFL+tVeiAtz5UtIL+sEdUdSYFLy5249nwmoZkbf6gwjX7ijabyGam5vL\nOr6SLK/lXU4IlX2OnbwNezkPZEIw8eo/o6P3WwClEGIL2HzwM+js/Rb2Wwh8HEGbUIdWwZhSMLm4\n1nk+XIIdL9useNFmXS77ksAaGMaWVz4FAJB5C/4QPo73tjThgg2duGhDJ97pfxA/XHwKQaVwqY4u\nh3qNPjhiQagEbWULDBd8P1LimkBJkiDLq28d6vT0dFois6NHj+LIkSOG9zMfVUAAXNZVXr1RI3ht\nhxVtTh7fe3MTXBYO99/cjJ/e3IzaHMmXFvLUM9XDxMQE85QyGIx1CROlDAaj4qTWJeUT6+d0Zc8t\nbHwpRUpoWEPjOVt4atKEW36fTG702NV+XNUm4v4rgoD7IGJUxAWRKLaIImTelqOFxOhKMA4r7iwx\n3mA937EbAPCk3QbXXA8ci73oOP7N5fcfdahe0kvtuypqMDs5G9694Y0AgM/WexAmJC1ZUOupHwEA\n+kwmvN8Zwr3zD6EnNgaREJgVCq/A4+HgH/Hx6e9iOD6dtx+bAPz9brUU0eGF3CGi5Xi9piYnSjqu\np6cHhw8fLrnfSjE2NoYTJ4qX6snFiRMncODAAU37Di+K6KoRwBtU2qUc/u7iWtx3XePyaxNHwKVc\n+xe2J4Xzc6Pl1yudnCyc/ZrBYDDWKkyUMhiMitPX15e1LZcxny5kChv7qcf7/X4IscwyGoUN1rAE\n3HPUhrii7vfBHUmDkSoKfrfwDADgrf6AupFbmbITWjFCBBYTWOc594JQihfsNixwHBwLx2ELjgIA\nwoTgdw414cyl9l1l91WMd3Rfi26hHqdNJnyisR51Az9dfm+yfhf+ra4Wf9bRhhPxcbg5O/5h29vx\n/Ou+gVeCFvxoYgpb+QbMyQH8y+wPMSrmD/feW6eK3fmY8QJIiM7nfiNmXFKctUK+UlGZiArFoak4\nArG1Uct1X6sFP7tFjZI44VXd7eVe+8xTymAw1iNMlDIYjFWPOeotvk9kVlebXzqa7vnc7Ul62o5F\nTuI0iaNJknBlOIKpTbfqartUqKutKv1kotW4rRPcuCwShUgIHnI5UD/+u+X3HnY6EOYItps70FLB\n0N0EZs6Ej9S/BQ5ixdMOO+4QRvCg/wV8b+EJ3M6dwA9r3KAArnXsw1db3ofbu9+AGrMT5NKP4uxY\nHF+Vu3GBdRvCNIZ/9f4Ui3IwZz81ZgqOUMzHqvi4jGaI0ngYCOcRsAaxsLCAwcHB3G8++qj6two4\nPquu0503IBS2WvCE4C07HDg6G8dkMH9yp3Lo6elhXlQGg7GmYaKUwWCsOiilFUsC88dZAVEZeHUp\nHPOGzjhe2ySi05E0cp8IqQmObg0EEa3fi4W2KysyliyqVHImH5RSwOQoKFL/bMlz/MPaekSX9hMB\n/KBGDYN+o/MCTX3J1gKZeB2N+d9LocPUiE81vg1tMsGAQHG//xk8HjqAAFFwbkzEvzW9G+/2XAMH\nl7L2sGknAKBz6Jf4pNKF7eYOzMkBfGP+/6DkuOZ4AnjMFHM6PaWGJrPx9gGLI8a1l4PBwUEsLGRG\nGyxht6t/VSTfNTjuV0XdXZd6qjmcsrmgTU249aHHik+wFSPz2qKUQpIkTEyUFg7OYDAYqwEmShkM\nRvlURETma6/0kLXxEIdPH7bj04ftiMrAG9ri+MCOKD61NwJ+qVmv5MP++AgESnFLIAhK+JLEYknr\nTPPQ3t6O2tpaXcdQHWNOjFX2bAbqs0u5pLKl7SZsIi7McAq+V+MGAHx1+/UYNZnQKtThQtv2jMYJ\nOrs60dHRoW0wVn2fc5O5Bf8tduHzM1682X4u/tx9Ob4drsN35yVsMOdILpVyXjb1fQ8frb8JTs6G\nw7FBPBF6JWcfdoEiIlU2VDIe014/tep84xvq3wojKxT/06NOipzbYl7h0ehjS10yg7OeCYtgMIiZ\nmdzh5Yl2Zmf1RYkwGAzGaoSJUgaDUT7Tx4BJYxOv5DTcUpIj0RIyBUWWInQPzwuQKEG7PTsE8Deh\nQ1BAcXUojAZZgWipfChqMdxuF1pbW4rvuETc2oCYo11/R5wAcIUfC/621+Ht9TcAAL5V68ZHWjvx\nv/GjAIB31V4NLocYdjoccLmK13nt7u4GPBt0D1uwNOCGUBifO/Yr3Oy8GLtFGbKQPzFV1JGs3VoP\nM95Xey0A4Me+p+GV/ABV0Dj8MPi4GkZr5QA9SxjFAvU38+HzreJ1pD/7mfq3wrxwOgqJAnU2bs2t\np+QIwfmtFnTX6Kup2tfXh9OnTxfcJxIpP4ESg8FgrDRMlDIYjPJRctfLiEaj8Hq1h6sRUJhD4yBy\nLKfn1RT3gcvTlxZ88XRDdo8nvaxGnEp4MnQIAPA2fwBTm/4csxtuLLm/lUKy1oHy2j1JyyVhNHpw\ndls34PaaK0EJwVNWAgrgnU3X4Bzr5lKGCwDgeA52uw0oQWwoXNLQbzj9KDgpCoXPXy5k6Ly7MNP9\nZgDAjj98BG/v+Q5eY9uOGBXx34u/gSU0hobTj2LbS58AAFh4iqCYe1xSDgE6NTWl+zMwivPyhFpC\nJ1EPdK3Bc8CIT8Lvh7QldcoHq3PKYDDWI/qm7BgMBkMHx44dy/tezuy7Yhi8GAIfmgLQmX1QmQwE\n0jPobqtJF6V/DPcioESwhVpxdkzCyZaLQTkTSsFmy++pK0YpXuCSwoXrNgPhOQAJEaW9jRtdF2On\nuRN98XFsN7djp617xWpnCmIySVHj6CMAgEDd2QWPCdbtQdPIwwAAXgrjXTVX4Uh0CPujJ9E3O4xN\nS/s1Df4ce4Kb8BPpSnz6sA3/fE66VyoUziEwjNAMM6WVVlnPDCxIuKTTik2e0n6T5VKud7bRrt5/\n/uNlHzrdwop9DgaDwViNME8pg8FYNcTjS+vq6PJ/8lKKt2Axw1PKZ9iYT4TUOolv944j7mgHLeBt\nK4bNZi2o8SS3RtHt1rgWMwdFjWirG6jbuPxS7zndZunADa7XYJulw1hByumbLyU5vOcKbyl4TMyR\nfl6bJRFvN6t1WL9sC6u1TwHUjz+JfxW+Axui+OOsNhERDAYxNjamad+8SCwkMxN/VIHHunJmS01N\nTVnHp4796GzxNcT5QrqZp5TBYKxHmChlMBirBx2eiIQISqz708JgkIeFo7ALFG/dGEt7b9R3GKfi\nE3DJCq4PhSGZXJrbpaC5DcUCyYaoOXuNJbWUZ/RmtafReK31qMmFyjW6c6PtO03z9DpzJCgqgLfz\nOsx1XI2F1suXt/Fi7hIvMDmWOiTovexbGNnztwAA98x+3BqRsSsWw5Qg4Oue9HNxOfcqACCUGa2b\n7xRr1A1GJsRaz4REBVGZGi5K29rasGfPHs37n3POOSX3dfVmO67ZbINVIBhZFBGKK/AVWKzc399f\ncl+5WFxcxIkTJ5ioZTAYqxImShkMxqqDIJnNN5/5lPCqWsLTmtr86ZAZPfMCLm6S8IsrA/jLLSmi\nlCp4bkJN5HJTMAgbpbBEtNf8y5XcBwAgFPbWZUL4Yh7CyhiTNqsVO3fugMWijpcUSXZUcQgBdIRN\nKyYHZjbeDJrySOPkaO6d3a1pLyOuLgCAOTKN2vmj+CfvPDhK8UO3C/t3v3V5v9e7xwEAk+Ez8LH5\n9NPqXxVZjppYYjKgTkK1utJ/I3V15SUi43keZrP29dc8zxffKQ8OE4e/Pq8GZzWY8fRIFO/41Qze\n/XDuzLqFUBRVyOoVl4ODgwiFQkyUMhiMVckZ+HRlMBhGIysKRDE74QsfD8DqH9RRLiY14U7hY6KR\nPKIjB3EF+H6/Gorb7cwOMw1HJvCYwwFCKf7cr3rYqA4PVjmGqi74bKFWjSyka8WEnd1wI6Y33YJA\n3R5MbblN0zGUtyLs3gJLeAK2wBDOiot4o203FELwBWUUxy79BmTehgudasKuwYx1yczArwyLi4tp\nr71h9XebWJeZoK2trWpjMuq3dklX6csCjIBSinA4vLozPjMYjDMOJkoZDEbZDA4OpoeaKQogRmCO\nTINTpLRSLtpICYct2RBMHvfAcNITcmt39lqupwMHEOcILolE0SVJmG99HcbOer/mnkymfF49AwUj\n4YGa7HWoZlN+L49RRnSlhG/YvQmyYJyBrgg2zLdfhbFdH0TM2ZVnr+zPIplrYAuOAgAmt9yOW+uu\nQz3vxsnIGB4PHoBo8cCjzOGvTE/gmpEvAkpyAkaUSs8GDWQntfL7AxgbHy+rTcP50pfUvxUknyjl\nuMqVh3G73RVp9/IMURqV9N4fy6e3t9fw8GAGg8EoByZKGQxGWczNzUHK9JL6TgOzJ0AKiNGiHqYy\nPVC8FF7+d1RWjdZ/2BMGn3HXk6mCR0TVOLvNH8Bi00WY3nIbYk5tiYg6OjtK1816sHkALt0g7+ru\ngseTvzyGUV48q0VfGLJmOGE5u3Fra2uRnStHalKkQP1eWDkz3lP7BgDAj/2/xyCvoGa+B3fx/4Md\nch9M8UXUTj4Hm38QC7Pawse1Mj4+joA/YGibZfN//6f+lUhmEixRFCGK+sT8TFiGhSdwmqu3Bjdz\njbVR4pcjBD/806bl195waaI0FouV9Btn3n0Gg7EaYSVhGAxGWQwPD8OeuTFeXh2+9IBRgnICSKcj\nBD8fVkXH61pSxDOlsAUGcfLU1zDb3IgNcRFtO/4OU/aWkvvSQ319PTA/W1YbDnvWmS+TdKO7ta0V\nPMfDarNhcmIia2+zxYx4rEgWUY2GvMuVnfipInDZodaSOekRkwX1nJ5v24ZrPOfjiYVX8I9ugh8H\nCRxLxvyW/Z9MO7730q+rnuwSOBMEQqaYO3LkiO42xvwS2l284V5RPe0Z2bfNxOGfLvfgM88uwBuW\nUW/jwHEElsyU4AXo7+9He3u7YWMSRRE+nw8NDQ2GtclgMBhaYZ5SBoNRNXIZdabIDMxhNamQnnWc\nWvjffgve+XyOLLqUoqP3W9jQcw9+VKO+f5s/ANHZWXJd0tzk/jxt7W2wmDV6H8swhMs1onmeh8vl\nhEnIPX/Z0ZG/XI2nzoPNmzcXbb/qmLLrx851qF7RmK05rRzNh9pvQofQgEGzCXc2NyKW53QKMbY2\nr5Kc9kvomY7nnJrKvMY5jsOuXbsqMg6jBWyrU73+f3kihLc/NIOPPuHVPaZAQL9XPd9ESH9/P0ZG\nRnR7sRkMBsMImChlMBjaCc0BC8NFd5NkGcFQEW/pkmFkii1CiKcbVlTJ9JTqZyJM8JOh3MLP6uz1\nKQAAIABJREFU5T0A11wPjptNOGi1wqkoOL/t1pL6WUavw8tgj49sqze0PS0UKmfidDphNhcW+OWU\n19BCfb22c6IIdvRe9i0Mnv/ptO123opPNNwKD+fEyzYrbu3ai2vk/wcl49Fpis2phv6r9+DI+M/x\n+1APeqKDCCvpZYdyYYinlFIgMK2u5V6HvDSmJjWLSsXPlcVigdVqzDrlTGGpR5Q2NjYW3afOxoND\nsmbpdEjG8KI+QaiU8J3nu+YSYpRSitnZWUhSdvI6BoPBqBQsfJfBWOf09fWhvr7emJAsn5oMBp4N\nBXcbGRlGPJynTuQSuet6php95RnrH33Zkfb6k3uTa0wt4SkAwI/cqpf09ZbtkJteo6v9sHsz7P4B\ncIXKp2gyYo0Rp4ql1pB29FCOJ7YUMcbzfNb6xEI0NTVibm4ua3tNTY3mzKPNggefbLwNn/fejyEs\ngG76Gd7G3YirnW64Fo5jPtiHI7P343DQgYBHBOgpYOEUAMBCTLjGsQ9/VnMZzCS3QBfj5XulRP8M\n+l95Cl2bt8PRug2wGBwKbcv2LlcTi6BeZ/94af710xXpN2MttdGhwwJH0FkjYMSXFH+jPgkbanWU\nQ8oQpeFwGPYSw/oTv8lQKITR0VH4/f6i0Q4MBoNhFEyUMhjrnGAwiGAwWNV1QtFoLN2XpNGWSyRG\nSq1TWuqSUr+ojuD1rXHc2BXHVveS8abI4OQIJnkejzodICC4qv4q3e2fc94++PtCsNvyG4DVKNdS\nbfQKQyMxW8yIhCNlt0M4fd9Lp6kR/9r0Lnxn4XHsj57EMRzAsSAAEwDP0mQAjaJekrEnFoPScCEm\npHn0ixN4OPhHHIn241Oem+CypHvPwpEwFFm/p4uPB0BTwozDIXUCaH56HA4zAdrO1d1mQR57zLCm\nIhF9399CRMb3ewLodAtocxYP9zbyN5c54VSJ9aebPSaM+CRsrTPh1LwIUdF3s8sUpb29vdi3b1/B\nY4pNCCXeT3hKKaU4ePAg2tvb0dJSnTX3DAbjzKOoKCWEfA/AmwDMUEp3p2z/MIAPApABPEIp/fuK\njZLBYJwRmJc8mGklYTTAZ4T/Pjet3touaBDxsd3JeqZEEbHjhQ8DAD5b74FECC61nYVmQb8Hhud5\neGq1eyelhp3AdEqmVt2ewiKGZCUFcErbNpsNwWBhL3jGwXm26p9paGlpwdDgkO7jjKCWd+LjDbfg\njc8GILiP4bKOCfCEYPP0AeyJhnF2LIZ2SQYBEA0exvA5n8BJyYv7Fh7GsOTFF8a/jh9MTOP0xfeC\nLmX7LSZIA4EgbHYbhIy1t5alNdgAgIlDIKHyhXo1CAQCOHnypK5jvrZf9Wg32o1PcqSXSvTfYFeF\n74VtFpyaF7EQ1TdJEYvFEI2m12z2er0YGRnBnj17YDZnl4zSc29VFGVZnE5OTuYVpYqiLAtkIc8a\ndAaDwSiEljWl3wdwbeoGQsiVAG4EsJdSugvAyhYwYzAYaxJzKD2jK6ck1zQlRFix5EeiAvRN+dI0\n3kOjqiH2+tb00Eghrhq4MzyPX7rU0N2b3K8tefzFKTB2jlPfr8lOFlTuOsPyvRmrwMPLZRu2HFn5\nNAhKrB3x2TfgdvvN+Gj9Tbh540dwfSiMjiVBCgDW8AR2/OEj2Gppx2ca/gIb4iJOmc3454Y6OL09\nmvqRZBljY2M4ffo0AoEg5AJrB4lSYc/13XerfyUiyzKi0ShiseJrbDPpX1B/w5JOD6JWVir7boI3\nbXPghm12XLdVjbj4yVE9Ez657xWJkPVSzjeQ/JyUUvT29uLVV18tesyhQ4fQ09ODnh5t1zeDwWBk\nUvQJTyl9FsB8xub3A/gCpTS2tM9MBcbGYDDWEabwNDgxaXBRSiGkvC61Luk3TljxiZcEvDgrQKZA\nUAQCIsGOGim9BAywnOX3+zUuxAnwGtt2dJqKJySpGG3nAI5kWHU5Rm/qsSW3U0VPVNFMy57uqozD\nbMn2JBXi6jY1KY03pj4+RVsjJrfcnnNfIsdRT4H/mJmFXaF4wunAkcmHNPWTEBvRSBRjY2M42Vfc\nwxiNRYvuUxJPPqn+lcjAwACOHTtW0rHBuHoeEutKM6mm97TUvgqVbXGYOLxzrxs2IWmOKRUuE6Rn\n0ivTC8tgMBiVotRp520ALiOEvEQIeYYQckG+HQkhf00IeYUQ8srsbHk1+RgMxloh2+gxxX2wBMfz\nHmENDKccTjWL1MfHVVFxd48d737eiVufduN0iMfVbeleUiLH0XXs65jkefx0yUv6FtclmvowGn2e\n0FXgtQQQr92U9tpqswJCSiKYfMPMY8gXDd/N4SmtBAUTVeXglm5VlM5Fk59rsfUyzHTfiNHdH8ZM\n95sRdagixBYYRt34k9goSniPWV398qVaq6asvJrI8JBKogRphdb7FiK0lIm7lAiATbXqdfCec91F\n9qw8pYpSp9MJm4ZkUX91nvoZ5yOVzaJ8JtTGZTAYa49SRakAoA7ARQA+DuBnJM/dmlL6bUrp+ZTS\n87WkSGcwGGsMxZiyAYnQXQAATTXK8huCDwyne7lmoslb2mXN6aK0eegBAMBX62oR5wiuIE3YaDYu\naUdZht7q0J0FSayDTHxOq9UKas6f5XX5kZAacivkKtWxAh9e41eV67FWb1WvzYSnNMFc13UIeXZh\nrut6nN59JwCg+9Uvo+G0miToKutZ2CXxmBUE/Drwx6x2HQ5H1raiTB3J2kQrEOYai8cRi8dLPj5x\nHktJkBVXgIvaLWi0V7+mbTklYUohkchpMriypVi0fE5FUTA0NMRqmjIYDMMoVZSOAXiQqrwMQAFQ\nvdSeDAZj1WD3D5Z4ZDHjOff7cQW47rduXPdbN/7rVO56hB/bFYErtaoCVeCZfBZHzWY84nTABB63\nNN1c2rB1ErfWI+LsKihat2zZgg0bN2hus7m5qTQRYzRajHSSLiZEa12FBqMdrfVLc+EQAIdAMRLM\n//iUzDVZ20RnJ+5AJwDg0cBLCCrpyYlCoRAUnYIyFo9jbj5zdU0GsgjM9AJRv662U4nHYoiXuD4R\nSHqjS6mpGY4rcJhXfi0xoN+rrpcWp+oVngpW1tutdQKt0H5zc3OYn5/HxMRE3n0YDAZDD6XeYR8C\ncCUAEEK2ATAD8Bo1KAaDsboZHBzEzIyOpeQ5bBtawEjOZwzdddCOj7yULca+8BoJLTbV4L2yJY7X\nZ4TuCrFFyADubm4DAFznvABNpurUPJSs9aAZHkLF0Zz22iQIsFkzBHbdJqBxR1L4pXgcW1ta0dXV\nWZHxAkBHRzscDgccdgOEL58ehkszkhVt2rQJTc1NmpoyylNlNpuW1/kRQnQ7a/fWSfjdpBlPTWqr\nJzm6+04oghXb7FtxcSSCCCT8ZurBjIgA5KypWrDdkVHMTM9Azkx0NDeQ/Pf0UUCKAr7TutpORaqp\ngVSTLbS1kvjeFhYWdB8bEikcptURSlBpT2m9nYPAlS9KWXgug8FYixQVpYSQnwB4EcB2QsgYIeQ9\nAL4HYBMh5CiA+wH8JWV3QQZjXXPixAkMDQ0DUI3L0yPDgKw/zIxQ1eAi/rECe1HQhFclxQ48OCdg\nOJjuefvk2WHsrqP4z4uDuG1jDHdsz/bomGLz+LHbheOCgnrehbe4V2AtaYpBS+0aljJYawCTDbB5\nAFeb+lclrBYruro6wRWp55lqpOf1IpldgDN/mLTDbkd9XeW8p5kiOOt9SiHw+tavikuX5j1HbXjF\nmzustP/8u0FBEPTsQshzFgAg4urCBxbUDNCPiEPwnPhu2jFKqkjV8ETNEqMJYqV7RXMxeM89GLzn\nnrLb0Zs0R1QoYjKFw5T/O6xmiG2lRSlPCCQFeKgvhIGF8sNi9Y63VDOOmX8MBsMItGTfvY1S2kop\nNVFKOyil/0UpjVNK304p3U0pPY9S+lQ1BstgnOnIsrxiBkAoFEozKu3+AWC6eKmAkkgpCZMgmmF/\n37Ihhof+xI9LmiVwUgRmHnjHlhhqzNnnZzY2ifs8qqfnvbXXws5ZsvYBAJu9eDISPRhixBICuJqX\nSsisXkghd6O1dC9bGnnOgWDKLyoVPneIdznfTYsteY196pADsRzaULQ14sRl38Tp3R9ObrM2YofQ\njHOiMQR4Ds/ETqLr1XtLHoeW9aOUAr29JzCzBhMNPtYfBgB01lQu6dVKl4TJxy969ZWGyUVfX19Z\n2XOZ2GQwGNVkdVs5DAYjjcOHD2NkZKTq/Y6Pj8MUKceo1Wnc5DCGxsPpt6t3bo7BsuSkKmQqRpU4\nPhs/gAjH4RLLVuyzbc27r9mkrzyIHpzOZFKgXAXtVwcrHCZZNONu7vFt3LjR+LEU4N1bo/j73eHl\n15MRjY9SwmHovLtwZdObAQA/crtgXzwBImsTDpIsIx7X50FLCAuvV19ocCptX/sa2r72tZKPL5X9\n4+p52deaexKp2lRDlH7/RjWU3ajETl4vW1nFYDDWBkyUMhhrDL3rzvQwPT2NeI4sm1NTUzDFsteD\naS0/wclqSK2e8ESS8a+FWHLLbRtj4DXcvSil+Ob8wxhEGF2ihPfWvVHTeIvBaek8A4fdge3bt6O7\nuxsut8HlLcwurLigLJfabqBlT8oG9fOkhd/mEQUCn9+AVzht6z5zkueUWnngylYJf71NFU1TYX3X\nw96mq1BPrBgym/Ci1Yq2k/+r6bjh4WEMDAwU37FUqIzA0EHEQr60zc4jR+A8kp3pt5LMRWQc94po\ncvAQioSRrwW0ClqXmUOnW8CkQcmOcnk7mQeUwWCsRpgoZTDWEJwUBlEqk4J/enoaY2Nj6O/v13zM\nqZOn0l7Lspwzw6Y1pNYnVeTS6+9FZNWo+8ZFQbxji7ZMoA/P/wYvRk/CqSj4QqwODt5ecv+puHOI\nSqrBG8xxBHaDQ4QBAA1bUsZhAEZ7hFLa29C9Qe/BZXUt2rQlUQIAd42+yYI/aVV/iw+NmjEf0z5O\ngQi42nk+AOBBlwNu70FNx4k6vaSAtusyAS+GMTbYh1MHn9Xdj9EMLq2pvPWs6maZLuR1r3T23QTd\nNQIOTMYgGVDep1ICNOmB9+LgQW3XL4PBYBSCiVIGY41AKYU1OAZrYLgi7Y+NqYmHitUSPJkhRFM5\nfPgwjh49WvZYKKVZIbwRSTX67YI2I+tA5BR+HD4AQim+MONFTdOVZY+rWpRjSFbap5Tw+FTLQM/o\nvYRD8hxjwIlym9TvqWdBwL8f0zfZ8DrHOSAAnnI44OM4cFKk6DFayLx2Eq8T31tPTw96e3s1t6G1\njEtmv+XWr0xkoL2gNfea4EohCMkQ8kzvZqnXvN7f86szarTKbwfDRfYsn0LfUyRizDXJYDAYWmCi\nlMFYY5AVDr0qJlqNL6auGoZTS+v2tIjSMdGL+7y/ACXAHVELms6/F6G6XQaPy3g0r1lbwaRHtbW1\nqKuvQ0NDemlqPR45YJWFEJYoUAkBrmhRr/eDcwKu+60bL8+qouakj8NkOF/DBPWCG2dbNkEkwCMO\nO8zRSiciUsciSRLCYW1iJxKJ4NChQyX1tri4WNJxCaZDMuwCgdOsPQN0peELhIkbyScuqQUAPD5Q\nGVGY+tsbHh6uSB8MBoOhFyZKGQzGilBIlMiynFUH9SdDarITZ5FcOCElinu8P0eYKLgmGMJ1LbeW\nPVZDMNJ4tnmAmsrVKS0IAZqbmsBrFsbp33M1RUQWNuNr035sV7pw+OfDdsxECD7yshP/9mrucHG6\nJBCvdJwNAHjI5YQpMov5uXnDx1eO+A+FQgCAeHMz4s1qbd1oNApJ0l8KSi+nfRJaXbzu66WS+1cr\nOmB7vRkNNg5jfgkLEWPWluaj2CQjg8FgVAsmShkMxqokFFCTrXByDHKKXV3IhlSogq/OPYRJeQHb\nY3F8xjuPmHOFxFulcTQU32cVYrWq4ZgeDbVJPR6DRaRnQ8G3M8vaaBEsuXJe/eXzLgBAn7+wZ+18\n2zY4iQW9FjNOR4aL9lUSid9Ojs8yNzenSZQM3303hu++GwBw7NgxHDt2rHi3ZXrCT/sldNeUkaTK\nQHieR3d3d05P6TnnnJPzmHInXz5wgVpG6denKhvCmzrOYt+Z1lBuBoPBKAUmShmMMvD5fJpD4dYK\nRoRVEgPS7ZijyVIGieymf3NW/nA2S3AUP5/5BQ7HBlEDE746Mwvvrg8D5My6zZV15nUb0voNb7PZ\njJ07d6C2JqN2aY7rrqG+HmedtRNkOfuqcV5WIz22G5z5hV3OXDVLXZuJgEvtalj5M8HSk8VMTkwu\n/ztvGHXGxw2HwxgeHi6pxFSlPaURUYEvpqDVWZ1w2WKYzeascPUElQrp3dusRob8qi9UkfYTEEIg\niiLGxsaWReeqCq1nMBhnDGeWtcZgGEx/f3/RpCGrGmVthG69MqfG7G5x5x/vqb6v4BfiKfAg+PLU\nNOqs7QjVbtfVz4qGlp4x6D/Hq91I/vvd+SdL+ny5REvyHFzh2AsAeNRhhUSN/z0uJzrKOO8JD2mu\nElCZdPz7v6Pj3/+9pH5L4YXTaqmdlmKx+kus199tQpSLsrHXf+p3w3EchoaGMD09bWgfDAaDoRcm\nShmMdUxBw1AWgakjQHAm/z46sYTGAUpBNIhdrYlxPrbfjm/1WWHhKDa7coSPUQVzcy/jU431AICP\nz83hwkgQ3q43AaR0L4bVpi/rZ65zvV6N5VXFKjjFzbbs69JtUrd5l0rF9C7yODKffT1uNLWgm1qx\nwPPoCZ80blBSHIj6k15Noj80OYG9rw/2vj7N+5caPRKTKB7vD+ObB/wAgE2e4qJ0JX9jW7ZsKb5T\nGVy/VV2THJZKF6Wzs7NZYbep3nFCSJbne7VPAjEYjPUJE6UMxpmKtFTrM1JelsxUeDEEm39A076y\npEG4UuDYomqYxpTcxqdr8Kf4ou8xRDgO1wdDeJs/CAAIes7SOOrcbNywQfcxCr861sCtN5aFR4YA\n2b59O7ZvS/eGd3d362szBZfblVYSRCv2pUNu6IzjkiY1G+99r1HDLj9/xI73v+jA3+534BMH1Jqb\nlHCI2ZuXx/F6vhUA8GzosO6+M1kWFDPHgPkBfeG5GeekVHHS29uLYDCou51H+kP4ziH/8uvV7imt\nyQxBNxi7STXRwqK+tZyZ5zszaVyqdzz1e2IwGIyVRP/Tl8FgnPEQKZr/ParNgJqYnCi6z3Q0aWz+\nv7Nze1++pvRjyGbClngcf0u7MLbrreCkMMBV//YWdXbD7uuver9A0jBvaWlB/m+nclTTuyJa1SRJ\nHJctRixWS8ntmkwmbN26Bf0DAxDj+kobPXa1KqYUChBE0vTdcDDpIU3oC9lcA4TVkMkrzJvx35FB\n7I+PIKhE0D5zEMQdB2Au+bNkole4lVujMhaL6T7GwifH+LcXVVbwJdByXkq9ti0Wy/J5KEU42wX1\nmLBY3m+rUDIrSZJgMrHJNAaDsfIwTymDsUYoZBgFg8Hl2W9KqT6DsATviC04qr39PNCcGWCSyBT4\n5gk1hPaTe8P4i9d0wOl0pu0z2PdlPGLjYVUUfHnGC3d0DsG6PfA3vabs8ZVEoaRKayqUN3OsFRx7\nCedFFhwVGIgxcCT5ka5tz16vORPJvkZqLc24KBqFBAV/DBxC26kfgH/qXyo80sIcP368rONLqVec\n6hA8v1V7+Hyq4DPSa5ooAVOqaKuvry/reLspIUqrm/W2GhNMfr8f/f39LFSYwWAsw0Qpg7EO6Ovr\nw9GjRwEA09PT6D34AiLz43n3p5RqXtOpHlD9hEi/mzDhZa9qzDkFCpvNulxOxD2zH00vfABftKoh\nku+l7XC0XY/Tuz5Y9XEmcLlcK9Z3xVmB779UMhP6AADlCq8tzidkcm2P27SX4rlzZ9Jn/dlz1Wv1\n+ZlsD75kduOGgPr+S7NPqH1HSqtZqtXIP3lS+/rVaHc3ohrDohOUkqH3tE8Vsp+9sg4WoXITIeee\ne66m0Fur1Yru7m5s3LixpH5aWlqwZ8+e5fuWXpLhu/qEW6ZntJhQX4nw5/7+fvh8PiZKGQzGMkyU\nMhjrhMTDPRAIwBKehuQdzLvv4cOHy/aEVJrRUPL21JKaSIYqaO/7L3yh3oN5nse5shWXdr0Tc13X\nqyGRK0RTYxPOPvtsAPqTJBmCEXalTuO02rYsLfFDRlwbgOY9adtyiVdtY+Ahm7R5agkBvnJhCO/Y\nHMXZdTLa7TKensr2mknmWlwZlWBXFPRYLRheWtfqWCheD7RUssSAIsEUncu57+hdd2H0rruyjk/8\n5WxPJ8G4gqdHorh2sx07G/KHLe/bt6+sfgBVhGkVYg0NDSV7OgkhMJtLD8F2mtUxPt4fxqn54lmS\nE5QSOs1gMBgrDROlDMYZiKIoiKesmStoUK5Q2ZhfjqjG3KfPCaPZpo7POvRb1I3/Di9aLXjc6YBV\nUfCe1neC06GOlAqtNSVEDdPbsHEDurq6ymtsDToPLJZCazlXOHSZ8ABf/TXGCmfCjhoZt22Kw8QB\nu2tlBMQc54IQeHfdiatD6jrOXztV0Wv3naraWC2hCXCydjETDAbR29uLgwdLr6+aynRIvc+c3axf\nxBUTmK2trVnb1oKHrsHOgwA4MhPHPzxZmue8FNbCuWEwGOsPJkoZjDOYULHSDWIEmDoCIR6ozoBS\noCDYXSvhwsalMEBFguvwf6Ju6EF8vl5NdHOz62I0meuqPrZC2KxW8Fxpt9a1XEKms7Nz+d9aPYnr\nHVmwp7228BQxmUCmFFLGmupIzRbs3fheAMCD9R2QOBOIoj8EdmF+AYFAdkbVYkKDIP+6xa7PfQ5d\nn/tcVnvlJkOKyxQ/OxbEQlTGzJIobXKUXsYpH1ardXl9KFC5Naha0NMfRwjOb0tO9tz38iImAvqv\niUqE7zLhymAwjIaJUsYZz+TkJA4cOKA+ZGURkLMf+nNzcxgY0FbqZCUZHS2egGhycnLpXxSjIxn7\nZxoaomp08lLIgNFpJ75kH59Xn/JdLKpj/UGNC8NmE1p5D66vfV1Vx1VpEmvPGhq0r1tcWZLGrMAb\nLyayeitR7BeEVk+YWHkgKgP/8EwEf/HQdNb7Z1k2oIF3w6sEsN/uKul35/P5MDY2lrWdK5AxOx80\nHoJ98SSsw0OwZpSWKVeUUErxHy/78NPjQbz317N4blS91zTZ9V9Ha3kypxh/d3Etzm5SvcdPj0Tx\n65PVvRczGAxGtWCilHHGMzGRUppk+igw/WrWPsPDw1hcNK6eZ0GivqxNWpOGzM7OphmLqf8+cOAA\n4vE4JiYmQKQoOCnby2H3nYIQmlo+dqXmwhdiqpHpMaeMILIAL8/hW7XqutF3e66BiWSHZG7evLn0\njitk22o1mnmex86dO+ByOYvvzCiLqgiZjD6sPIVECfoXFcRzRMVzhOBy+24AwCM2HrXTLxo7HikG\n++LJtN9+IXHJiaoAIhVIdPXqTBwvjiWF8kvjMThMBA4zM0tSMXEEH72odvn1QlRBIKYvG6/ea515\nQRkMxkrA7v4MhgEUeohTSjE3N6ftQR/yAvODQDi5figWi6GnpyerAHopJMLtbMFRmJeTmpC08g1C\nXBXfBw8exKlTpxCJVL/q5fFF1VvS4UgxvqI+fKu2BhGOw2WigL3WTVUflyaazgLcHeq/168Dp/Jw\nPGB2AbXpWV83bd6EzVu2lN/+0neTbxJH3cXYL7DLkS4m/jibPalyuV1NyPRbhw1hQuAZ/70hfcuy\nDBpVa6kK8ZSJrxUSIHORbGHltpQf9r4evaYuM0GihOv+iRje+fAM/uKX03h1xpiERtU+Z5FIhAlf\nBoORBROlZwq+MWBheKVHsWaQZTnpnRSj4EV1jZbX681ZiHx8PH/5lYWFBQwPD2Nqaipt+8TEBAYH\nMzLkyvH0/yOZSbGQp5YXg7D5TsESSIbjjp3ODuHr7+/PeXxfX1/O7eFwGMPDw3n7rQQLMYIvHlXX\n4u2sTZ7rkeA4fuFyggPBTR3vKqntxqZGQ8ZYEMGi/lWN9WeEA1C9jA1bAKs7dSMsZjPchcrvmLRl\nPk4Y4hTUcPGZj+X10Us8OJKd1KfNVI+t5naECfCU3QbP5DOG9Z+4hySyGHNiCNaFPiCWvgaVUyTY\nF0+CiPnXnKeKirm5OYSLrU/P4OBkUlDddakHABCRmFDJBSEEX7++EW/YZFveFpYo/uWZBRyaMj7T\nbqUFYzCYveaZwWAwmCg9UwjNApGFlR7Fqib1QXz06FH09PSoL2Z7YQmpIb4jIyM5120WMsgS4jaz\nmPzk5CQWFjK/kxTjOEcYb04UGZbQBAil4GX9Xs1wJIx4PA4iFyg5UIVZbZkC9x6z4p6jquHVYZeX\nvQMA8B8LhyERgivse9Bh0i8ubXYbGpaK2a8b6jarnllGkprO4vsgRZRW9NpOF7smDri2PY6PX2AF\nAVBnzt3365ZCeB+qrYfCGzfBMTq6tC506bPz0tJ9K56+TjGRhZfE1ARnka2bEN6+PW+7w8PDeSe2\nchEWFfxhKXR3V6MJ2+tN4Alww1Z7kSPXLuV6IxvtPFw5PMnfO+yHUiyJ1Tr0HjMYjPVH9XPkMxhr\ngEJrODPFZYKxsTGYTCY0NzeXP4DgNEAVwLMRAKeu7VLyeIAyDJJCRjaR46Ak3bCZm5sD4IYtMFze\nmMvkpI/HExNJz9GXL0wayv3xCfxGnIWFUtzqvryk9pOGWfUNtIoZhWleRIYeEt5RSmlVL4mPnBVF\n2N2OrQMy/GLu+8xr7Wfh+4u/w8smCf7IGFzeQwg0nFt23+bIbEnHTd75Poi2RhhwZwMAzKeE7n7m\nCnWi6Kc3l976mZI99trNdvTOxrGt3owL2y14diSKxwfCeGYkij1NZjSUkCSKwWAwVgtMlDIYBjE9\nrWbTNESU0iWjTZEAGbCGxmHi48jpy9SRhMQWGM6RvGhlZ9EfHzPBwtOsUbiW6tVTSvGjxacAAH9O\na1EvMCGWi6bGJpweEeByuVD2KuBSRLS5CsmZXC1AcBwQbMX3LcKykKHp/y4Hq82KaOrWBBVsAAAg\nAElEQVQa7HznkePhtnCYD+R+38nZsM+2BS9F+vCI044/9Z0yRJSmDKzsFsoRdeNLZU0+d2WynNNK\nefMq1W8l2q2z8bj7ymS0R7ODx+MDYXxtvxpV88AtzTn71VsSZi0KdgaDsfZh4bsMxmonIVDzFbZf\nPK2ruWKmUrpBUllDMSwBX+214YtH7ZiM5L4d9cSGcCw+Crcs43bXnoqOZy1jtVqxdesWmIQVmmt0\nlFvGRoMhbHEBLXuAAqVhtIoBjlfbsNnzC9xyhEXc1gCFM2VtF81q9mi3hYNPzN/+65YSHj3sdMC2\neKLkceSCUBlQik9mJSbaOj/zRWz41KcM679nOgarQLC5Lvv8lILFUs013KuHGgsHc4pz9OmR/NNR\n4+PjTGwyGIxVDROlBhKYn8Zoz3Or4sYfDAZx4MCB5SQ5qUiShJ6eHoRCrN7ZiqJIOQ1DRaH6lnDm\nE6saybS7qUIBJTMzZmWu6ZdSso/u9yb/fUWLGiJNKcX9vqcBAO/x+eFaMugZa5hEEigDvJ3lwHMc\nNm7aiLbWtuVtSm0XUJed1ZlwBJ46NRkPz3N511iniljJlMejv7SPwAFzMQ7RPNrwHOtmuDgbBsxm\n9Jr0h2UWuocIcT/s/oHkhFcRTLNemKez66qWysvjMZzdZIaJM2bSa+PGjWW3kagRvJYghIBLueZ6\npnM/CwghWYn2UgkEApr77O/vx/Hjx7UPsgj57KVYLIZ4vECeAwaDse5gotRAxnqeQcg7BiprqylZ\nSbxeL4DcD5tAIABJkgo+pBiVx+4fVA3DDPr6+jAxqSZWisaiiMX0PZhTH/K5MgVnQUgOj1B1Jlbm\nY8lbUK9PQI1JwZcvCOFDO9XSNS9H+zAoTqFeIbjNHwQVihuOWrxbUWcHos7shDiNjZXJzssSjaRg\ndQONOwDHyiedslos4DiSLA/DWwFr9sSHzWaDw+4wtO+hRfU58fRkbm+hQHhctpTw6JemEEw614Mu\n+orXVTbFNSZTy4GeydfEvgcmo7j551NYiCrY5DHGSwqo9X0TlPpb27lzJ/bu3WvUkKqGkPJxnxuN\nQjZgUrzQd+vz+RCJRDA2lp3dPYHWutqFOHr0KF59NbtmOIPBWL8wUXqGQGly5nw1eHIZhfH71HqC\nfSdO4PRpfeG5qZw4YWzYn1H0+zlc91s3vnvKCoEkr8cGK8XOWhkOAVAUCQ94HwEA3DE/BxulkGIR\nQ/pXBDuUHJ46gV/LiULWkPA16fOSxpxdiFvLDQ8unaxappqED0Gh7+R9+1RPakwBlDy35Gud+0Ao\nxSNOB6S5l3WMGJrnlYwQEFr5/PNJoWwRVtf1ynEchJUKfS+DN21Lnyy54/+yJy+q/cxP1MPWSzWv\nRQaDsfpgonS1IktZtePK4dSpU+g7mZ6yn3lvVgBF0bSWSxcFDA4t4U8EJHcbiqSuPasAH34pmRSn\nwZrsu9mWDCd8af4ZjJAY2kUJtwTU34KorK1bFvuNGYMi2CBZ64rvWElSv8qyjHy1oQ63KoC+1WfD\nd07mXhPZItThspgCkRD8JlwZr1GpQkCv0FmIpN9Lrtq4suHbK4XR94S37HTgxzc140c3NQEAFqJK\nVomYciY2q0UoFEJPTw/m5uagZC0fYTAYZwJry8I7k/D2AXOnSj4802CQZVldK8gwHE4Maheas73A\n1BFNu4bDGbPNOdZ/xeNxHO81Yn1P9rVh9w/CHJnJ+36p/H4y3RsxFeHwN2epn7XboX5Gicr4eeB5\nAMD7Fn1IBPqFms4v2PaGDRvyvkdW0JO45sWpJff6SFIg4ZB2Vv7cVKdmaTpCynrKh0bzJ+r5k5a3\nAAAetMgQFe2h/P6AX/tgwnOF3961E8Gzz9beXgajPhHvTfHgnd1sgd20suZH4rte679NnhBYBAKr\nwOGO89Tf6Rf/sIiIWLqwW4loqkSt7+HhYRw6dKjq/TMYjJWHidLVimzMAv+1/sBd7RBFhDU0AVNo\nUtsBOr7XkZERcHIMnJQ/FCoYzPam0zyzzJyYO7EVISQrGnF+fl7zOPVy/1C2AX5Zs4gP7ojg/Y7f\nw+Y7haeCBzFmMmFjXMSbgiFMb7oFeNdjRcMmTWbj1qkBQNTZiZitjBI/6yVUntdyXpPfzTr51FVj\nkzP/pNZOx1nYrJgwxxMcH/im5jbDobD2AcgxFPrWpt73Lkx86EPa20uBUoqPPJ4UpHfsc+PvLlm5\nUOzVTFNTU1nHd9WoE377J2J4pF/H978KKGarzM3N5a0RzmAw1gdMlJ6pVMlYjsfjOH369Ppdx7rk\nvSQ6PBh6EOJ+WCL5s17mOq/mYO5QLXPUm7+jjHZGBjJCvQ0K443KwGhIXbd5ebOIdruML10Qgl0A\nbmoYQ1f//6Ll1S/jQb/qJX27eSeCTRdhoeVy7esQDZyIUQQbZEsN4rbKJEBaO5RxTq21xg1jLaHh\nlP3dLnXCyWnKf38khOBmtAIAfsQvQtGYMVcvnKzP4NcqEKZC6feOfa0W1NvX3trNalBXV16Ieqc7\neV7nwqXfs1fb81oURQwPD6O/v3+lh8JgMCoIezIYCKV0FQSiaUCOw+47Bc6+reJdDQ0NIRgMora2\nFi6Xq+L9GQUnBqHwGZleqQKbfwCcZWvlOjZAUHFi+TPkpli6p1SvwZoPX1z9fJc3i/j47ggEDnDN\nHkD94d9ivu1PAAA/dTkxTyPYGYtjb/tVmOzQZ6jRPKVGampLLycjWTzgxQB4KQpZsEN2lOE9PZPw\nbAR4QS1/tIrRFb5b4DeqN4v1VW0iXvYKODAnQKYAn6fp85uuQ/vk1zFsNuEPkV5cat9VfJwwbu6x\n+5OfhcKZgaee0n3s0Rl1wu5zV9ZBVCjqbWs5mVjpaI1a2rZtGwKBACYnNUbfpOAwc+AAKADmI+tn\nXWbid8k8pQzG+oZ5SqvA/Pw8FhYWVnoYSSS1lhkX17Hm6AzDGpqA3T+Yto3IcRBKIegszVBpSMZ6\n1lTDmpMiRde7EkJAqhRwOR5WbzmXNYsQlu4+HSe+A1tgGHbfSfg5gu/WquuiPrSwCCUjuU3p5R52\noMa9tC6yTN0vWuug2LSFHya+ilUfRl+/FXC25H9/tY+/iujyImnYdY9HQlgieHjUnH8naz1up6q3\n/gH/cxXzluaD9/kh+EorH9M/L8JpJtheb8KepvxrZ9cbpXobXS4XampKn0D735uasKfJjLlIZZLU\nMRgMRqVgorQKDA0NYXBwsPiOBlLogVgtAbLWKGZEJM9bioFexWQZOccnRQseYw2ehjU4WrhhQqBo\nqWdqAM9Pq2sTPZZEfaJkv+bIDL5bU4NFnsf5kSg2dt1eWic6vgtK9N0Cm5vXqYfU4gTcrfnf13me\nVhQNtWwzcS9NWFitGcemXEql/Ma13Gs3uVSB+e2T1oKezWtlB9pFCRPSPF6IaEtuVknxqvV8RCQK\nl5lL2z8Wi1VqWHkxm9NF/2oLUTUKm8Ch1cljNiyX/BmreW7WS8IpBoNRPmvI0mAUIxKJIBRaSmYj\nx2H1D4Ks8rC5khGjQLgyyXiUIlmKlRRL1WiBr9sY0JD1l1MKhzzJVRKkARF4bFw1DM+qUfu0+5Jr\nhOZiM/hhjRrifWeIR7DpgoqPSTJr90hQTh07PSNvm9oMxqizE6LFU+GxFIbwAsK1+pYmeGprsWPH\njizhUoza2mLrZYv/njekJDnyiep57vNxkDP0ZKj5UtyxqHor7198CnFaPJRRS0moUtFatiMiUthW\nONMuoIbFppKYYLLb7SsxnIqyyWNCME4xGUxeWz85GsCfPTC1bsU4g8FY+6z8k4JhGMePH8eJEycA\nAHx0HpwigcRKC7la9cz2AosjFWmaZhiSvb0nlt/JxLqUVCjXamJKacXXwBhhYCwuLqKS+VJlqgrS\noUByLVliUlxICSH/mouHSAgus+2Cbc8/Vmw8mmnenfYybmuC7O4E1eOJ0+oFcLYA9nq9I6weGr0Y\nimCDWMGkUJX0phjfNIGW35VDAD6+W10HfnyRx2CAw9+87MS9x9Ovs4h7E/Zs+gC2xeKYVYJ4JLC/\naNvDQ8OaRlrKbWRiYqLoPifn4jg4FYNVSD+5HR0d+jvUCM+r9xmn05m23WRKzyBdW1uLffv2QRDW\nX2qNNpf6mb7xSvL5/0BvCDJV65gmeHYkgtt/OY2Z0MqH+jJPKYPBYKL0DITNlBYm9fwcOHAg9Q31\n/xofnrOzszhy5AgikfwlXdKIh4DAlNZh5iVTVGs7qHLXxI8HLfizp90YDmbfbnhRLWlzxGLGY04H\nzBS4reYKUF6fx6oi8CY4HI7ka8KBWktf61UQdytQ21WZtg1hlRqMFcrsG3d2GtOQxp/VHo8qCgYD\n/PLv5MBctliS7S34+Lyan+CXgT9gUc4uCVUKwyPDBd8P7jsH/gsvxPj4uK52v3NQnXTKfOZwhtS3\nzU1np/rdlbMuc6UwKpR1W50qwHu96qToZDAZMXVoKhk6/fVXfIhKFEdm0sOpmY3AYDBWAiZKVymx\neBw+f2UTEZFKrROLrs8ESjnXlBbAv/T9JdZPFX3QB2dKHVrZZIYhc0XWqurhuWnVuP5mn5oV99Pn\nJLMD82IACgi+VKeKi1vlGjQIeYxJRyNEe3YdP4fDAY6vzLW8Y8eOirRbEHc7YCuvNIThrMY1pW3n\nAnUb0zZFDRKTislRfCcAhEu/F2TfU7UZ941WinqLgqOLPB4aVZMBmXOccsXkwAUSj9fKdkRpHD/2\nPa2p/WJEI4V/7zPvfBum3vteTE1pnzTzRWUMLqpi6M3b0s9nJb2TK+H5PPvss6veZyFMPMEV3VaY\nOeDFsSg+9FiyHNj+CfV5pFAKaclp6otWJ3HW6OgovN700mTHjh2Dr8QkWgwGY32xCi0NBgAMDgxi\nYrx4eNSqI+QF5geAyCrKNqyDufl5+H3FRHVps9her7da5WFzwsm5k4sQRVwOQ17eZlBdUgCos6R/\n6O7EGjqqQBADeMjtwSGrFXWyjLfHCoTGKnLlJlJWE84mwNO90qNIR1gbWVOVPOWANFMoQVxK2Ri6\n9G+TyQSbPX+fickeyVy8HNYVLSJ65gWc8qvhp34x930mbm3A3wQVmMDj6fARHI0OF217JXjPr9Us\n5VdttOHC9vTf9WoOmS3FS5kZGrwaqLPxiCvAl15cXN52XosFkwF1oiBRqgdAVqbeSnlKZ2dnMTKS\nvuxGkiQMDw9XpD8Gg7G2OAMsvDOUKpcMWGap3AwMqmtZbWamZzA9PV1eI8HZvAmIimXDLGQMlGMo\ncFL+2qWcXLlkKKNBDlPh9NtMs039HF2v3gtu5nncW6t6Ue6QmxHtelP+xrQK5dUQepYQMKhiZslK\n9MFbgMYdgNVtfNtriOzfXvJcFwwTXTpO4YqHo++uTb++IzLBizPZ4i3i3oLtC4N4i/NCAMB3Fh9H\nnFY2od2Gj30KW+68U/P+lNLlmqtv2+0svHMRKhnqu56Jy+nXbKdbQGeNgKmQDJlS3PtS0jtZ6Zqm\nfr8f4XD+ZxCllK0pZTAYTJSud9iNvkxyCpw8okeRwccDgH8M8I2leVbU9/wFM1ae6u/HwOCAtnHJ\nUnICIGvI2ePjxZC2dg3EFye440UnpqMcbumO4XPnhfDd1ybXwDl8J3GfpxYLPMFOcyfO2fhXEG0F\nSq4UqqO5SjGZTOA4Du3t7Ss9FH2kXkOmMr2PpfS52sl3X037DCTPv3Oz0ZUUpW/qUCeKvnMyO3LA\n33AeOCrhPQvzaBfqMSnN45f+F7SMumS4WAxcVHtI/93PLUCiwLktZtRY+eIHFMDlKu5lBph4zeSy\nLvV3u6lWwD9d7sE9V9Wj1clDUoDjs3E02NXzdW6LGSM+qaLrSE+dOoXe3t6872vN5MxgMNY37C5e\nATJv7kSKghi4Ro9RTbIf1LkfoAR2/wAs4cmlw2RAFmEJngYUGZbwOCzhKdAC5Wai0SgkUaPHY7YX\nmDmu2SNuZDhuLkaCHO7rtSIxOf/MlIC3PpM0JpttCs6rl9HuUMfLx/04ZjbhZy4neErxHs81xSdQ\nzOmlGxqb1CyvlZ546eoqPQERRzice+658HhWtkzKSrBek6Wo15u2a042OZf+X3yNapOVwiFQbHbJ\nePdW9XlxTp0EJSPpV8yu1pNtHfst7vBcDwD4lf95RAZ/oPUjVIznRyP46BNe9EyrotpexVIwO3fu\nLOu3WmmqPUG8pc6EX9zagnuubsDeZgtMPMHZzeq19NxoFBGR4uIOKzZ7TJgJyQhLyd9rtX+76/Ve\nwWAw9MFEaRWwBUdhC46uUO/MU2o00WgUklRcPApRL3gpAj7uX64Xa1gxe531Z1NLr1SCfzlsx6Nj\nZsxG1evtDzPJNVatNgXn1aePt/vwv+Lz9XWghOBmuQZdpuwERsWwmKuzztHtLhC6Wr8FcBbw7p6h\nrJe7TsL7JvDJMFqbTXtdS0WwIVy7DZQvfq0SAjxwZQBfuygEm6DWL12MEyh8urc0NQnTDksnrrLv\ngUQIvqL0Q9FQt7iSfOMVP0b9yd/6X51bfth3ITGXmojMarWisbFy5YjWA80OAftaLXhyKIKJoAyP\nlUOrU722/bGV9VayqC4Gg8FEKaMqrOhMqBRT13kWIfcYk9ssoWTiKT31R1PbnZqaKjlKMR7XtvZz\nJc71VES9lYyHONw/ZMZiPGlgfPu1QbTZ08f0kFnEEasFjZKEazd8wODRaDduRGuZWW4tLsDdVl4b\na5g1a0g279G0m9VqRXNzM1rbWtO21zfkFj9Gno8GiwJvtPAjeudz78Onex9FoyThsNWCV498Aubw\nFHgxCE7SWIrKQGIp6xg/dZkHLktlTIzNmzdjw4YN6SWb1jmZdVdLpdOdnGDprBHQ5lLDqz/0mBef\nfW6eeS0ZDMaKwUTpOmW1PFiMNNLC4XBpn8t7Sl3nWcq6lTzdaftcyX0SntJIOALvnDffAWuK2SjB\nQ6NmvLqQXDP2yUMO/E+/FUcWVMPnsav9EDLuMnOSH19ZKgHzjoYbYXJ0aO7TcBFEeMhCgYy/DO2s\nJYHKa8/+WlfngcDzICm/Z8VsjEAohMdCcSrA41dDQDTDAdp38VeW/+1WKO6aU7Od31tXC8fhu7Ht\njx9Dd8//Z++8wyQp68T/qarO3ZNzns15lxVBEAUkKCKKAQyIemdG7zDh4RkwnJ6nh+dPORMIcuZ8\nhyAmRJLkzWF2dzbM7E6entQ9nbuqfn/UzPT0TE93de6Zrc/z7LPT3VVvvZXe9/t9v+k/c9YXz4vP\nZ+qlL026TTAaG19/+voGzmnMnydDZWUlNTU1eWt/JfPGLbFn9/xmK+uqY14te4bCeMJq3uUHWS6u\nRd/AwKA0Kd287LlCkcE7CGXNUOhECGH/oji4fGIOuhGUeAueIAiLJpjY59RCZKJi3tFoFEEQkKTs\nElikw/T0NEePHqW5uZmmpqbUO8wnz/GUAOFQ4qRDAFJokvnOq+5RN5k4mc2vJSorCpOTk6iVxSsQ\n//bHkycgcZkWCzaqqnLP6G/wiSIXqeWc79xOWrl/c6L4LCPl6WxgdlFAKr2yGkuh6ijxku2z+vqO\nMH8ZsPD9w7B/xM7nd8YsnwtL31zuD3BpUOURm8gXa6u5Y3gUmz93JcXcb7mOiD35qDU0rY2zb9ni\nwiqdfe+Y3W5HUZS5utSZkEwZzNWCnFUS+M318UnjLuu083CP9nwNeqOsycmRlqa/v3/Rd8vW68LA\nwCBnrHhLqW/kFF3PP45/tDf1xrkkMAHuo3mv1zk0NITHo8ULmoPjmMLeuN+DoRC7d+9OuK+eSaC7\nu3vR/vv27WPfvn0Z9jgzZl1XA4Hcu6Qlvw76SrSEF7rzKgrSTBynIOc+ydXIyAgjwyNMFqno+P7x\npRckXlQb4f0bAnx6x+ISAE8FunhOHsSlKPxj1asMQWSFMT/GTzeuOqhZB/bK3HcoGQ1bk/6silJM\nYU5B0NUGgGxbOqFV1JJefGWnK2Z5fNZt5r+7bLzyL+V88KnFLqvjTZfy5lU341RUHnXY+ZNzZjG0\ngDGmgzNK6bnNy6Omba7ZvHkzW7cmf6YyxWw2Y7fnLwv26zfFnqlhn2HFNDAwKA4rXimdmhHap6e9\nKbbMMZFg/P8ZoigKiqIs6e7S399Pd3f3kvsHg9kpcV5v4utWKu7BRSHRuS/UrcLevFpoZzMAq0VI\npa+qcOuuxYLxp7ZrSmibS+Ha9gg7quPP3yv7uWfyzwB8dHyKcmdHrMGs+qNis2nKg6Hk5pg0r6fT\n6dRdwiMOa/7dYReT/NwC5WtQazfoamk2oVHUuXTZooVZdBcSsSbP0Pz7Pm3/k9MSQRl6tt/CqXNu\n5fnz7+BE+xuplsp4a/UrAfhSfRNToki5+3nsHp1lppKw+p//hfXvfW/SbU5ORBCARlfhPGjOFpqb\nmxeNbdu3b6exMTdlsppcJt6xQ3tvPSGFYW+Yx3ozlx1OnjzJqVOnctI3AwODs4cVr5TOUVBhVc3Z\n8fbs2cOePXvYu3dv2l3IG0o07eyv2n4yDB2A0HTqbRcQV/MzDwjRIIweWfx9FhfS75uxFCZoIu37\nuSQJGs/zesFUJPZsX9qoWYhFVC6qj/LRLQFuXJ3Yfe2HU3/Fo/g5NxDkDV4vCLkbflpbW2nvaEcy\nahWWFqW8SCAurTzFjTP1m+N/05FJNxMSucf+4crEWbP/3yE7gYq1TNhXcd1jNVz/aCW/P2PmMudO\nNlnamCTC16oraTn6AzpzGFuajN6pKG0VJuwLg8iLxEorw1RfX4/DEQsHShSakw2vXudAEjSl9P2/\nOcE3np3i8dOZKabRaJTx8fG09llqQdGoYWpgcPZQGrOHwbJAlmV6e3txeE7i8Jyc+35oaEhfHE3E\nrymz3qGs+zI4OETXkcVK5CLCfl21PC3BUUhUSzaDSd87PU1UlpMmc5j/WzqZfGPdKp6lemoms+6V\nzWE+sFETWtZVyAgCXNkcwZpA1t8fPMWj/gOYkficezznA48kijircmM1MDhL0Kswm2JKqL9iLUoa\nSmlrq/4kXkvxtYu0/zdVRPnQJu19e3RYi7/9nxOxvvz3ETuiIPC+qqsxI/G/ZS6etmm/i9HFrvS5\nZjqsUJmnbLuZYLVaqawssEt4HrFYLGzatGnus16vEKtV3/MqCAJlVpGpkMJ4QJufHustfn11IymS\ngcHZQ+nMICuC5CVFCkmiBEXzfsyozdHRUdzu+Myx4XCY/v5+jh8/nlGbmTI5Oanr0g4efJSuriPJ\nFVhVZanGRDn9leK+M32cOX1G9/b79++fczNPSgl4TMsq3LZHW62/rClCmRk+d46fz5+z9HUKKmG+\nN/EgAG+xbqEzGmWy4cUZ9iCJIOZMkT7Kmn3NRIMVRmUH1OmLgxUEIaV1f+F4O+tWng3rK+HJN5q4\n/Tw/VzbHFrDcQYH7TscrHEEZms01vKH8JQB8obaakADtB76RdT9S4QkpeSsBc7ZgsSR38V6IHsV0\nwwZ9LugAFVaRv5+JKaJHx8LIZ3OojoGBQUFJOYMIgnCPIAgjgiAcnPfd5wRB6BcEYe/Mv6vz283l\nRXd3t379IZzvFezcuc8lss7NflcIFxtBDjM5MZHWsSYnJrU/VCCU2BXOPnUMKZGVNAmHDh1aMt4W\nIBiMtafHqjk9nZ5Ls6pobYph3+Lf8ihEnPGJjMzUTqwwa8d5UV2UCsvSx/yl5zFG5Sk6zQ28Kapl\nC3a3vTL3nbO4wFqOehbXDTVIE0c1mJdOIDMn9KeIB803ZklEFEAS4VsXaGPF824TVjH+vTvu0dwU\nXlN2AW2mGs6YzfyovBz7dC+mUH6T7nlDCmUWfUrpWZ2TYB4tLS1zf2/fvl23VXOWXF/HcqtIMKq1\neVmnHV9E5dREBqE6BgYGBhmgZwa5F7gqwfdfV1X1nJl/D+a2W8sbn89PMBhKbZCcHtEy9GYQY5kT\nChHvpUQxB91ZJ7MhGsTu7cEcdGfuzjMxL/GCrHOiTdLtkZGReZ8KGzs3q8SKWWb2jSigpHFrJkKx\n80ymiKIqlI88x/FQPw9OP4uoqtxs3YnLP4AimonYclBjcOElF0WoWZNUyVjZlHD85nJhKUto7QaU\nmnWLvi6GcjWblfcbXXZCikCbU+a/ZxTVjz/vJKzAZ/eU0eK/BoDvVVUzIknYvJlnoJ+67GImrrxy\nyd9lRWU6olJu1f8Mtre3Z9wfvZRy4rPOzs64REVmc/FLItlMsev1uo1aMrvTU+mHl2RCLt6laDRq\nxKAaGCxjUiqlqqo+BqQXsX6WI8kBpqe9HDlyBL8/iSU0MvObnFalxsUoUVR//C0qeLbhJTD5hzEH\nx7VstNkwU9ogE3faWcbHNUuBGvYx3vXYomumf1LMj3XYFCns4oSiwmv+Ws6dx1Kvzisq7BuX6Pdr\nQ8a1bSGqrUtcL1Wh+egPqD96N3eN/AIFeMeUlxcNPk/Z2D5CztacJTkKOg2raCKcTmfc/wY6MS1h\nEZVMcYsdBVd25h1OXHDoMz6JVfPKx+wbN7F7zMRfTmyiJrKJoKDwjaoKKkafZTQo0OdL/90be/2r\nGb3++iV/n45oY4Fe911BECgvz787fTaKjsmUXRn3hcfOd7K+XGCZqS9bYxdpcEpIQqzUTyYMDw9n\nfb7RaDSuDVVVOXjwoBbCs4B9+/YVPJTIwMAgd2QjGf6TIAj7Z9x7l0xzJwjCewVBeF4QhOdHR0ez\nOFyGFGECsPoG5lw7dcUKJkGQQzP/llZcbb4+jjz1p7nP85UlQRCS7ptvhNnrXwIT8fDwMADuwTMM\nDw8z2h+fsr6npyet9pK576bL0MDiYuKZoseS7AkLfPgZTWFZGJeWiM/ttfOJXU6+dUQTzN+6JnFi\nq+Yjd7N61xeoGH2OH1SUc0oI0haJcNPkFOXu3ZhD43jqzk3jbJYJtgotPrFEqKioYPv27VRUVBS7\nKwZ54Icv9bKpQvP2eGlDBFGAn1ysjUf/dSgWxyqNvRITEr8rc9GlTvP2x8t4z0LfDmcAACAASURB\nVJMuwmnqGUIwiBBc2ivDG9LmnPIV5L6bi3jgUiCdBZQbt5Wxtc7CV6+oQRIFWspNnJjI3FLa19c3\nV0c9Uw4fPhz3ORAIEAqF6OvrS7h9LudlAwODwpKpUvodYA1wDjAIfG2pDVVVvVNV1ReqqvrCuroU\niUjySOHdeLTjZauI2729M/96Ev5u85xCXKB0luKEn3WfZu9fDk5NnXGXVhYob9HIYpfebErCzB1P\nVxuFvWd/HzHR7dXiz2xS6mM/5453LXMtMCJYfX107LuditHnsAaGOGk28b1KTSH6rHsc+7z7P1V3\n3oLW9Z+7nvthsVioqamhuaWAVtTq1Vp8YglRCu6AuaYU3DEXjWVmndboLF7xheddZ1P5r/P93HOR\nl49t0bxHqq0q17aHmAxr03qHU+bERD1XOF4EwNetPkBTHn93JmYRlnU4fKz+6L+y7uabl/zdM6OU\n5irRkbGYUhzqnRKfv7SaSps2N6ypMnNiPJJVsqP+fn0LrnotnLOLritxfDMwONvJaAZRVXVYVVVZ\nVVUFuAs4P7fdyiXFUdB0CU85UB5FJfEqppCkjmg+lFZVVTl58iSBJKvppYIQzG/Cj/yx+L4Jso5S\nPAkYC8Ve/U6XzFhQ4GsHbQQTWFCmFzxit5/nWxSO3HDiVzg8mlARBT5VV0NYFHi9d5oXBeP7KFty\nKXAufs8EQaC+vg6LuYjJaWbLhtiWacZfkxVMdqjIvqRJsens7GTdusXxoOmycExXJE0oVqrXZN12\nuseepcmhxpVg2lwRe4GvmMnU+8C+l1Mmmzhklagt/zsAd3fbCCvwzKiJa/5azglvalFAUJc2r37m\nES0UQm+io1TkopTOfGavXyFchvNBsRaat9VbmI6o7B0K84fjPu7dl77VMxDIPOQmEbOeYKJRk9rA\nYMWR0VstCELTvI+vAw4uta2BDvKw+i/F1aVLPKHpUZzFaABTaHHsxkIikQgTExOcOaO/FIouAhMQ\nDTOrfOTCcrmiUDKL93lsOGbqDMoCd3TZeGjQwjOji+OoDk9q3/3bTh/3X+5hS+XiYzqnjs79fU9F\nOQetVpqiUT4+pi0ADHe+DgDZ5Fi074rEZIGGbeCqL3ZPMkMQoH4jWMvmvpotVyGJCQrRFhVtbOhc\n1ZlQmampqcmLMhJ0tROtXp+TtnI1qm2vjr2bb+jQPGgCURvlI5p3glr/MJdZdgNw7V/LeWDGYtrj\njb+nqqo/AdojPTGlo9aRm2cjXxbxtWvXsnPnzry0vZzQW791e732fIz6Zb6/x8v9x/Jf7zYVsxZV\nQyk1MFh5pIzkFwThZ8ClQK0gCH3AZ4FLBUE4B20u7QHel8c+FhW/34/ZbE7bVSQ2qeqY2cM+sC8Z\nlps9i1ZZ9YtAtunslMyshYuJHhBNCFLtzBdqgV34Fl8rKbp45TfRd7lGUBf72aW7gv7IkInHhsyc\n8UlsrYzSaFd4eNBMz7QmTP7HAQcvafAgzbvEo0Htw+oyBVMiOWBev45azHynSrOE/rPtPKZX27H0\n/ZnxlssZb70ChOyE1mK4b2ZspZCyS5RSarS1teENNONwLJXwp7iutXabDXtDQ+EOKEggWQqSTErQ\neW0rLSoXN0Sosihxa53jky9hU/WjdFnh/Oo7WTN6DXfJ1zBT/QNPRNt415iEOyjy81NWhgIiN20I\ncHXr0jGFE0GZO57T8ia8fXsZ5SVep1QQhJRjiN2uPd8NSZ6lbdu25bRfqUikgCU6D5vNFleOLFtc\nM/dzzB9b7JBVFanA43CiMdhQSg0MVh4ppSZVVd+S4Ou789CXkqSrqwtJkjjnnHMS/q4oCqqqIkkL\nhW1tEDUnsjIqCkwPEY6EGRscoqFBRZzvJpeh9St26KWF6MnJSQYHB1Pf+AwRBIFIJErY58PpylGj\nShRMuZsE3aPurNsQowEUk77SIymVGiWKw3My6z6l7gd85UDMUnlebZSwIqAsEHjf8biLH710mt/0\nWriwLjonsLrMic9DnFHIT696A7dIJ4nKY7zc+QLWVl3FBDDRfGkuzyL+oyDoX2OZcbeMmstSbGiQ\nCFEUqVim7o/5ZGFCHFUQYgneklBXV4dv8ljO+/Ov22MLZNuqohyYMOEzVfLx8Qne2dTAPRXl/Mzz\nO+7yX8PecW0muOuYlde0h/n07ngF+ztH7XRNmfh/CpgSrCe9+/5YzoRrN6SnnJdCfHAiTCYT556b\nPBnbrNdANqRz/tXV+uLV6+rqcuqtZBYF6h0Svz0Sq4d9xB1hS11hQyMOHTq06LtSfX4MDAwyZ2Uu\nNQWnYDR3k32ybKYHDhxg7969i74Xokli/byDMD3McM8xJicn8fl8cT+PndyTcV8X9UMQ41xeT5w4\nkXmdT50cP36c4yfyk5ZdlMMQyjybX7bZkGPot55FwsmzFy4VF6yvF/r74Y3ET+KvaguzrSoWe/zR\nmYQpYyGR/RMSd3fb+Pw+O1MRAZuksjBczBSawD7VTeXwkwB8V+inRx6jQarkxorLMjyjHFHegmpb\n4KImmqBxO9EFNVI7OzoL1y+DZU+qRaZA+Wr85avTazSFgG2xZqYEfGp7gLsv8nLHi/ycFwxxhc9P\nQBT5Tm38u6Ei8PBgYm+gR4bMfLH9FYy/Kr5c+WzGXYCbXpi/xYrlmgU3l4l49Cpg+VDU1lbHn8fv\nu31LbGlgYGCQHSvLv2yWiR7NpVCREQOzSW0yHKxTCCDRaOKEQkJS1xJ1pumZthd0zT2UXXkQNZB+\nIp9ZRXWxxVfjzJkzjIyMZNWvTFAUFVmRYZ5M5u3dl3F7x48fJ72oxtKOYQ2H9JX7UVT4x7/HTNdf\n2OnHaYId1TLvXR9EFFTOq409y5/YpVk9zvgkzvgk6m2LXYc7934Fc1jzBPiTw8796gASIh+ueR02\nsVAr6Uu81656VMEJLFgwmhcPuW7dOvx+Py6TUUJAN4IY565dqjQ2NoI6lNM2dQv8gqRruklHgXDY\nM4vFrrCoVMy8in2b3scN8iSPhp/iT06RVtte+oLn8Plz/Hx2r4PvHIlX/lodMn1+7X359bYreNNV\nzrhV7J4pbTHtghYrV6zKX6x4c3MzLpeL48ePz7nWLgfq60snnrysrCzjUinDPm1euGadgwe6/ayv\nNrLeGhgY5IcVaSmdmJigq+sIqqqiLsgY2N/fz/j4uO62HFPdWH3pK4nJrJE+n4+uriNzFtJcr26q\n4z1p77N///6EFt9ZMlJIg1OIken095vHwOAAx7uPx1knhgZzI2wW0/3HHIy5EGcbt5sKVYW3P+7C\nH9XO9+vn++IU0Nd1hLm2PUKlReV/L0tshV7oulvb+8CcQnrEYuW2Os36+PbKy1ljaVq0fylSXl6u\nKS8G+qnbCFWrit2LeBK8xy0tLbQ0F7AkUNYkH4sEQcBqTV1POBne2p24Gl7GdVFtcWpN07386pIp\nzq/TxoKArPVhR7X2+bsX+vj1yzxc1xmiyj9F0B0fijId1saE6zfnJk5j/frFSaNmY0Bn6+5u3Lgx\nJ8cqBAvnl6Xmm9ra2ryPQ9lYbW/cVka1TeTNW1yIAvgipbFQOzY2Rm9vb7G7YWBgkENWpFI6NDwM\naDauyQltInW73ezatYuhoSFOnTqVVnvxmWzjMQXHMfuHF30/Pb1YGQt6xgAYn4i3ZHqmFioC2SlL\nQ0MLlbbUk8hsmvWMUVXMgVFEZZ7lbvxk1mVvvJ70Vnd9Ph/hcBLr4YJSObIsZ2QMtU0nLtytF3NQ\n/8JItrhDQlwJmI3zykbUnP4DjnlxbTYJPrFt8fN+ZXPMxViMBqk7/QAAQ5LEBxtq8IsiL7Zv5irn\nC/NxCjESPE+qKEFFW36Pa6BhsoJdX+bOs4lMFMZ0F8VytYj2FrGTallmt83G4dA+TOEp1pbFxoQv\nnOPnF5d4kURwmmBdmcx3/u/LbLrtc8iqiqqqyKqKNzxTmzSDMjCJPHLKypLHepvN5hWZ3Kajo4OW\nlpZid2NJtjdYuevV9djNIuVWkd8e8fHD/aXhXeJ2Z58fwsDAoHRYeSP8EoQj+twc08USdGMO64tT\nPLPvUWBxJsWFcY6CkN1tCYVj8ayFsAZKkWkcU92YQxMpLaOhcFhzx9WLnu4HPTCwB+QIR44c4cCB\nA0tuOj+hUCQSSWodBkrde1cXU+HYRfzI5lgSFKuvj/re++g48F9x279wxor6j2uDPHC5h59e7OW1\n7bH3x+49AcCgJPGupnpGTCZ2BoN8oPqaDJ83/fvMuu+1tceU0HDVenDWLrWLgUHe2bx585LJ8EqN\nYNvVvCusWTd/5v4d7c/eyr9u9yMKKh/YGMAiQbklNvCVzXhJHJ+QeeOvh7nu18N8+YkJ9g5p84wr\nA6V0YcbihRbQ2XGkrq4u7bbPZhKNv7mUARqc2mLCfUd9XP/rIaYSFbbOI4niuWVZZteuXWl5wBkY\nGJQmKzOmdJZ8FpwOTGqJU+YOFX8sKbo4GYDe0hJqskkk5NVilixLx/AsSqyj57iqjN3bQ9S/FpOj\nQlc/Z12UzYHRFFvGOHniJJayasxBO83NzZhMix9Bj8eDLMtUVcXK5AwMDCy9guKbOX44vQQMWjxw\n5i5xjjxkzswWRQV/FE56JWySyvoKhYmwduX+cW2Ql7doz4YpNMHq3V+c28/iG6D52L30bXofTlsN\nf7gyZr2vssaeH0GJ0H7wDvZbLXyoZRVuNcCmUJh/D9fhFTIbTmSzfve/xsZGKgQfDocdbwJvhKSY\ncpcwJWNBr2YdRPJfPsigsCwrC55o4vzWG1k7+C2OWyz8pLyMiyx+fn9F4nmiLEHW7T1DsUUqyxJV\nnpqamohEIrqsWQuVVEEQeMELXpByP4PC4jDHxj1Fhb/2BHj9xlyl2c+MUEhbHFnsIWZgYLDcWEYz\nafrksl7XQiZO7sHbE8uSu9D9VUhiDRTUBMmRVBWSZeydZew4uI9qSrEOkinC4xMTHD16FNBcMgVF\nZrBbf+ZfzfVV0Zk9NtaPQCDA6OgoAwMDCbfs7u7m5Mn4EikhPQl9iuQOV0r8vs/M9Y+Uc+suJx96\n1kVYhidHNGXxJQ2x++SY6p77e0wUGTv8FZ6VRxju+hr9ETchJYLFNzCX1EZQItSe/j1e3ym+Ul3J\nO5oacKsBNlha+WTzTUxvyKJUcRr3QRCEuTqZLqeL2tpaOjo6Uu9Yux4c+soqJG2mtpa6ujqamjKM\nm7W6wJUn688KfJ5LidkFtFRupssB1V7Hx8e0OeTOygoiY7sAECM+pHB8OEm1Nfmi5lLjaFNTU1Zj\nrJ6aosuJlXAuDnO8yPiTA9P893NTmddyTpNkluBAwFjsMzBY7qxIS6mqqgjAwJmevB1j4aqc7kE5\n7EcMJ0gmM9EDwUlo3EE0KideLfAMztv+FNh3pjycNN2PzbdQgY31dWHs69TkJCO7drF9+3Z9yRGS\nnLesKCjzMnUmvEaqqpXwyUmcWj6U0uXhvxuW4dCkxLePxGen7PWJHPNopow6W+xcLNO93Ody8cP6\nDo6pC+KDhu8EoDYq0yCVUeHoxOo7w3DEzZHJvSgV5Qiqyquc5/HWysswCVLhrtK8Z0gQoK21FfTU\nDLSkV0NxKURRpL29PSdtrTikYmXlLIywbzab2bp1KxaLhf5+LfldoYTxfLC28Sou9v+dxxx2fuH9\nOzfUv5gNT38MgK6Xfnduu2qrSrlTQRFM/Pz1DYz4ZbrHI+xstMZZzgyS09bWhslkIhKJMDk5uSyf\nnZd12jniDjMWiM3rf+sJcNUax6LSMfkgElm8AJ7vEncGBgaFY0UqpbNIvmEWDWGqTL6EGD0F05VI\nYC75UhyhWcUgSeXJ6QXuKcOH0+leWgSDwSXL3SRjvqJ37KgO91bvkHZewmqw6XMbXkSC6z4wMJA6\no6GO+2UOpV9eJ1fICjw+YuLihihiikf22ocT1wm8+RnNtepNnSHMIqCquAOn+TxdHKqrBtWLXVHY\nEI5gcbSi+s4wZJIYNFlwmyTc+CFwWPOpsFoxqSqX+/y8quENNFemXhRZCawEC0e+iZpdYJ63ILIM\nBW49zCY0WgnPxFjbVbwu8kKeHPoe91llrur62txvghxElWLu7uobLke2VWGWBFrKTLSUpRYdVsI1\nyiVms5n29vZFXkCZUozru7PRyp3X1DPik7npwVjYzsnJSEGU0kQMDy9ONGlgYLA8WdFK6XwrlxgN\nYpGHMIU9qIIE/jVpufPNugIvWchbpxA2MZFaydEtzsk63H0zZHJykpGRkeQ1PdOpV7jUSckzbrly\nTAEW5PCitsWoDteceZP04OBgwnjV+M1TT+pCEWsy3nfGwl3HbKiqn5c1LV4gCMrgjwpUWOIv7hs6\nQlzeFOEDT8difSySts3gibv4tHkEr8VEnSpxfeUVvOPAD4nUnMNA0zto3/91nJ5uZGBEkugzmzhR\ns4nyyWPUyTKbQ2Gcqsrx9tbFCz5JsFqtc7E/yw2LHkvsWY6r0kg0BdkoCqlKwmTYbApazLXcEHHx\nQ4uPL9r9/EYQcKgqrokuvLWxRSfvyy4k5FxOJXaKx+rVqxNm3y8EhVJU650SFhFmEjBz1B3m5avz\nV6s2Gcbih4HBymFFx5TOd48xRaYxzbjNCqoMk70g6xerDx06xKFDh3QdK3uSD7KRSJRIJH0rZjrH\n0RWfIS+O81Rk/Urc7GTi9U7HufnavT3Yp0/HKfrWQLLV0Nnt4s8nVZmbUpzLxoKxTj06pK08f/Vg\n4sn+7Y+7eOtjZfz7/niX3Td0hFlVpnD/5R5WuTTXpkoxyOnen3KrZQSvJHKpz8/X6t7JpWXn0vvi\nbzCw4R9BEDmz9YMASECTLHNeMMSb+/dytc/PVlMDVsnJZMOLidhq0jqvjs4O1qxZk9Y+pYIh9CyN\ngMCaNWv0xfUaZEeeHsM32l/AhlCYPrOZr9ZoyeVs0/H1H00jY5iHM6hVnYSV+l5VVVXR1lacElWJ\nSu3ki3+/vIZt9RbObbLySG+Q8UBx3GhX6nNkYHA2sqKV0pB3LPkGOVUk9balYwBNMshGZZnjx49z\n/PhxnccrLEtZwyYmJhIq7tN+P319fdllzpttN4PJqZQy6O4fl7jx8TIeHjTztsdcc7GgAEemFgsb\n3oj2+j45oimvLpPKRfURKmcspyYRvn2hj2++aJorxj/Fp4WTBEWR13unubnlJmy2xQl3VMmGv2wV\nAGe2fDDut6G1b6X7wtsZXP92SLNskSSKWRVwn9fD+I867vmS3g0G2SOIWCxmRKmITjcrWCgNlHXm\n/Rj+ppfygdrXY1ZVflPm4udVjdg98S6mzf/xbTo+/6W0216OcZPLmbKyspQeQrliVaWZz11STb9X\nWyB/zwOjBKLF8ywyMDBY/qxs990CzoeFmny7j3Wn3igHJE5KpGAJjMzfaEkd2xKILwMwOTnJXHqY\neW3PJinINFPykSNH2FiTuBN+vz/5zkourM25Y/eY9jr+50H7ot92uSU2VsRWon/QHV/Kptqi8OOL\npxPK502Wfm6pthMURV7jneaGzo8Stc9ztxSIe1d6z7k1Yf8i1uyy1xZad5gVzhzO7N3KtmzZYgjY\niXDWAerM/wa5RpUK4zreVLGd95jg2xMP8JUKCy3jkxTTIXslW79ydW5LZaKtrq5mZCS3Vu1kvGqd\ng7v3aDkx9g6FubDVWAQ0MDDIjBVtKS0oOgVWfRNSaU7IprBnzgU6GyQ5iH3yGMjhueuRqbzv882v\nTRp/3VLG75aY4DMWWtyff9oYoM6m8OOTNvaNx6ylv+zRlNJ6m7YyfWF9NO50pMg0qCpRVeZrE/cz\nZDKxIxjis+5xFHu8uLlu3bol+9S77SNzf6dTT7QUsFqtrFmzhvq6+rT3DS9wT7bZbNjtixcLznpE\nEcoai/suuWYTmuWuD/X12jOTrtUp2fZWa7yCWWqLHJc6t/Mq1/lEBfhIlZW93v15Oc6GDRvy0q5B\nYvKt4F+91smVq7Wxsd9T+IXe8fHxgh/TwMAgPxReKVXkuKQ2S6GqKr6p/A02obCOupfzkMKepJqT\nPgFDzanwNjIymnqjJJjCHsz+YfAMYvP1x/2W6HzirKQZML9NATD5R+YppYuPp+uaqmpW7rtLMZtl\ns1AcmpR4aDAmtN6yJcCDV3h4VVuEF9drsc+f2OVkNCgQnDGYmgSVV7eF5/6exeY5xfqnb6HxxM+4\nd/IvHJLd1EejfF5uZWD7LWn1y1+xnqCjmYmmi0tOideDxWJOu9v+yvVE04yZNUjBrMXPmf4CQUps\nM5mnxdzF0zU0NHDuueemHaPX2tpKe3s75eWxbNiVlVq5q3TdyINFSCz0torLuYZGQqLAlyfv51ee\nPxLxdCNFU3idLMFskrBVq1bNfedyLa/FreVGIiU03wsg79qpPe+/OFScBE8GBgYrg4IrpZ4TzzDe\n9VjK7dynj3L6+T/hcQ/kpR8nT5wkFPTTd/JoyoQ4AFb/EHbP0nGcapZZWmUdfVjI2FiKmNmlmDc/\nmcNTcaVmBDWqKaoLzyfLSc0UmkBemARJVbSkUws7NUNPT0/KVV7HVDeTY0P09fcn3S4xS7ctK4VN\n2vDrHk1421Ed5Q9Xeri8OTKnTL2pM7aA8sd+C6entdf2E9sD7KjWFni2V8/0V1VYte8rADzs3cWf\nfbsxq/BfI+NEV99AoGJteh0TBE694NMMrb0hi7PLITkQrpxOJw5HcTJFFgRb4vJAxWHmIRZFaN4J\nzpWt7IuiSF1dblyZlSJ4JoiCwPvt5/HBiUkE4Fee3fzD1C85FRkmEBhMuf9CGhsbWbNmDVVVVbnv\nrEHJYBYF6h0SthKsWzs2NmbUMjUwWCYUXCntP92rq65UaFpzvQz703MXjXpHddULBRg88hzeU7uZ\nHI/FP6qqypkzZwgnsKQKqsro6Gjmq46quqSS5fV6E35faEQ5gjk8hRiMr6XqmMoullWSgxw6HJ+9\nWIxMI87UZ1UVhXA4HJf1V69bzuDAIF5PaVy/TBkNaq/iJ7ctznpcZVW5/3LtPXjgjJlvH9UsLnVW\nhXXlCr++1MOL6zXltGxsLwB7rRa+VKvFgH5yKsxaWzuK2ZlZ59JMapQMs6U4tezms3HjRjZt2lTs\nbuQeQYD6zVDZWeyeGCQg0byxdm2ai0QFIFixlvdPevjxwDAv9geICALfurqeH16R/kKOIAhUVlau\n6BhRA41LOm0EIioRuXTc0n0+Hz09PZw+fbrYXTEwMNBBCceUZjaJdT/7kO5tlbCmAIhqbBXN6/Uy\nMjJCb29vwn1Onz6dUIFUM7B0zmdgoJ+uriOoqooiFl9wF1R9K4u5dAs6cOAAhw8fzlv7aTFz2LCi\n1QMdTxDvmUvGQwJXtYQptyQ+X5MI68tlPBGRo1Na3FqVVdvWOe9xMQfdDEkSNzd3EBEEbpjyct3E\nUNolXAyWKSarZpU0WBYIYukpa4rJTv/6f2BbOMz3hkf59tAIj+4s5+lzjVq0K5ls3aqbXSZUYMhX\nOlbJWQtpJJJOVe3C4Xa72bdvX8nFlxsYFIsSll7y/5LKMwOBJMUuw6wrb7KV3UTuvkcP7c2qL7PW\n3VwPTh5P9omJ8oWAgJrqPqdxOdK9dmJ46fgXVVVxBwWu/Ws5r3u4nLc+VsbBifzUgFNV8EQEKszJ\n+9/iiJ/sK+YpsGLER83pB7G4d/OhhnomCLFdauCW8RmPA3tDyn5ESziRUSlYWA3SwxC0EuNyubDb\n7XPJlPRSSGujp+ECTu3QsnDXyDKdgyFqxvUn+qqoqMhX1wzyRLalZJrLtP0HvMXPaq8nJKsU6O3t\nJRot/vUyMCgVSlgpzT+zQpMwY5UNhUJzA0S6AoB1WkdMo6oipIw9TZZMKa0uAaAsjOPUie7ETTla\nPMiFwJXLiWg6qvL7vvhsmbvG8lNBqd8vIqvCklbSWa7vjHcpt8x7e5uP/Q9Vvb/jUw4fh61mGqRK\nPlT/FnrO/3cmGy5ioumS1B0pURe71WtW09nZOfPJUHRKgtoNUNlR7F4sS0wmE5s3by54MjW9WGay\nBAfLVxGt30rE2cZt9/bzge8f1N3Gio7ZXqF0dGT3PreUSQhAz2Sk6AtSR48eLfgxZVnO+LyLfb0M\nDEqFElZKCyAgzyqlM8L4wYMHNbddRUZM4gKXjQIlevpSbrNUoowjR45kfNxZhGgQKZqbDHmCO/ua\nqckH4/QG6lwN7GEFXv+Qi5+fihcaT3jz87rcPlOXVErxWK0qU/jehdq9e9caL5sefz+bHn8/zolD\nWCb28/H6Wh532CkTrNxaez1lkoOotZrB9W9DMS3fciZWiwVTmllQDfKMxQGO5HVrjThCHVSvKXYP\nFjE/43Dgiv9gctv7Zz5p46ueRE7GvS8MuUwgla2l1G4Waasw8cvDPq779TCP9C7Oj1AoUtYozzGy\nLLN3717600y4aLwnBgbxlJ5SGgnAwB4EOVSAgy1WYkyhSRyeE0jh4iTOUVUVMY9xRvbp05givpTb\nqaqa8h6kqwRKC46b6wE5V0rp0yOxyXm+y2yfL/eKkT8Kp33aazhb+mUWq6+f9U9+GPtULOtzu0vh\nZ5d4+Uz/+2LbdX2bdzc28FengzJZ4VM1b6bVnEkG0OU4QS7HPp8dGKv/OjDNlInJ8WOcTTmZhfdt\n1pNo9ls9VlDj3hcGpzPD5HV5os4RmyPveHaqJFx5C8Gsh13K2ugGBgZJKTmldHr0DF1dRwh7i1MQ\neVYRU+Sl65jmfXWrBOZzMerD7k2c7GmWQDC9lVAxgZI7K7z4fKkV5VSkKwhNTU0l/P7LB2JC17Xt\nYf5wpYd3tw0xEhTIVWLBXW6JAb/AvcdtBGTteaqzxTdeMfw0khykc//tWKdj2QMrZ9x8PaLAPRVl\nvLa1ib02K/WCja+Jm1lta8lNJw0MMiRqKdP+MKVXm9MgV+RujhJna0kT71mULcnaKcQxDHKPzRR/\nvfs8Z4dSamBgkBvyEySXBZ6ZzLbBYLBgx0ykzOSrwHeqSbIYK8yTCZQza6a6uQAAIABJREFUIZra\nUj00NERHu/7jLCzAHn+u2Z93Lq7dUCD+/rxB+BtrHv8xnwaOC/9C1+Q6/nWXg49tDXBpY3oT7lhQ\nixsVgE/viV/hflVrGFQZ58QRfFWbqDn9IL7hv/Gky8GwZGJ49He4I6sJKGECSohwUwNdVisz+iyX\n+AO8c/PHsUczTwikFtDqKIgCqpLB/Ur3HlevAcUQjAqNbKlAqV8DJkvqjZcxuRyvKysrCU+m3m4p\nMn6nUiCqM+NCCSyWpktbWxtms5nKyspid+WsYOEMcnoqyvklsEZqWO4NDJYHJaeUFpKFA5UU9mKK\nJM9W65g8Rl+ffUU5DQ4OpF8UPReMjY3Ram8tyrGX4nm39kp8bGsA/3g/a079eO63ey1fpfP5nwLw\nlQMOLm3Un9lYVeHGx8vYUBHlnzYuXnC5aWOQyqEnaTz+E36y9hX8X3QfR9vmu+B5wDcvw7PNigi8\nQHHy7pFT7DS3MmoqIxhNfzFnbqGkAFaFpqYmRkZGaGxspOdUD2XlZWzYuZOjfzs2t42/Yg2OqRO5\nOaCtPDftGOimkM9TsSgVC1xlVSWTE5omu3HDBrq6ZvIO5LB/kiBy52vqcUlObqR0zl0PZrOZtra2\nYnejqCy8X/m8fy5LvPNd/wL3XVVVebo/xAubrJhTJVHIAcvpWTUwMDjLldIYmnJq9etTzgL+afKW\nW3D4EKJvLF+t554sVyBLbQVz15iJGqvCqx2HqZx6lAlRxKyquGb6uUM4zn3W27g5/EEUdRt6w3/H\nZuqcHp0y8W/74p+ee1/ipXrkKSwnf8Z7Gut5Ru4Cq4VyBTY41tMeidA2uhuXojK57h+on+iidfAJ\nnGveTWVkmuZAF32dl2F32AvqYZAJToeDVTOZdFvbWnE4HIiiiGxyIEX9BMpXgWAkNVrOuFwuPB4P\nFkvurKTl5eVMTk4uIWSubMEzWY3hpsbGOaU0HwiCgITI01tclEtl3Ji3IxnkgoXvR01NTUEVs3ee\nU0Z7hQmzCN963sN0OH5+PzAS5vanJnntBidv215WsH4ZGBgsD0pOKRWWgY+QoGRRHDrF/KCmLBlT\nGPQoi4qszBWnXgl8ZreD58dMvFe6n6Fjv+UjNVUc79AsuedFLdw61Mt93AbANy3f4m/B79Fo1/e8\nnpqOKVojwfjV5FqbSuDQ//HO5kb6zSaqZJkPj0+yceOtCHatlmG1XEPDqd/SF4jQeuqvABwrW8WU\nyUnI3kCwfDUb6xuYGM8m0UJhhfuyeS7yIZdei3npjw9nO42NjVRVVWGz5S6edNWqVYTD4aRZ0UuV\nbJUCVTRDWTOQPMY/FVarlVAo/QSCoiCyoTeAQwI2GdanUmXHjh1FvzeSKPCKNdqi6xNngnjD8fLM\neED7POyLyQ0PnfLT5DKxpW5lu/obGBikpuSU0oKScV1LQzCepX9gIKv9xyfiE1oJSRJM5RNFhefH\nTIDK1qrf8d7aelRBwK4KRASR50xhbmxu4CujY1zmDzCoVvPLU1b+eVMwpaecosJte7SJ+s2rQpSb\nVdqdMs+4zUyFBSZkDx+udTFsktgaCnHH8Ci1skLXjEIKEChbBUBr1/cAmKp7IbJZU+qC5auB0vCW\nrKioWDKBVE6wloFvNH/tG2SNIAg5VUgBRFHMeZv5pFQ8QEwm01xm0FnC9nosgRHdbYiqwK0/HUQU\nJLgq1z00yBXZlnQB2LhxI4Ig0NXVlXVbjS6JP50IoKjqXLKs33drCQ2f6gsSiCj8vS/Id57XwmD+\n7dJqNhuKqYHBWU1BlVI1Gkm90QpGlmWUFIpwNBpFKQFrqV6ZKlvhK+DXMvhaAqMIqowYyVF9MUXG\n4dEfl3h4UrNkXtf2NLc5q1EFgRto5pqWGwgi88PJh3jEf4Bb6mv59tAI2wM+/tBvocMlc2370s+1\nqsJ7/h5LavSOtTFLxbm1Mn4lyG3DP2bYJLEzGORTNW9iqrEK9wKXvZAzPi5KyIfQm6VWW1a+2B0r\n6GzG5stu4SIOWwU07gD3UcggftbAoGiUiKKqiCmSoS3opiiIcT8U2xp3NlCs7MO5LDHTWWEGAtz8\nRzd3XFULwMnJ2ALJzX90Mx6MyTqfeWScd51TxtXrSqvMjR6ylYNKZRHLwKDYFNQXSl7o9hoNQVSz\njAWDQfY880TRs+7q3DHjYw70JxfQe071ZOmCmRsEVZ9bbi7vlzk4jsA8hTzt6xzbfmGm31R8/Hkn\nCGH22e9HFgSutW3hta3/gEm04BLt3FR1DW+d8hIRBG6pr2XKFKUSL98/Zovr5gmvyHFP7LX6ba+F\ngYCm8H7jnKE5S3DF8JPYpo7z3YkHOS1PsiYc5pNlL0ep2kLY2YwqWeP6pyz4LEWm0zo/PeQy+64s\n2Qi62vITH7oMXTgNzi7mKwOzgr45hzG2hcQqmFlvbWWdpQTSqBosGy7u0DwbBqdlRvwy//lUfOzz\nfIV0lrv3Fqc+fK4wFmwMDLKjqNKd9+Sz+HqeA2BquBfb9BkCY33F7JIurIGhYnch7+hV2Be6hmV/\n4NhEZfNl8yzoV2gH/NpEYql+giFJYX0ozJvqXxO3jSAI/Mv4BC/xB5iSJG6pr+Udpj8QVaHXF3uN\nvn7Izh1d9rnP3+/WJuYKU5Rrj3yU1q7vIchBmo/9kGd67+HpwBGciso3h91Q+8KlOykI+CrWzX2c\nbLhQ9/npJ3cTqmKyo5jsqTdMwLp161JvNIshBBiUIPPHz/r6erZs2YLDkcgClC8LSQ7rlCJgQkKa\nERcMwbu0mX9/KioqitYPmyk2L/7qsI9n+jUvoS9fVs15zbFF1k+/tIqr1+Y+daTH48kohjoZenNo\nRKPRFZVvw8CgUBQ1prTvjKZ0bFp7EYKsuUCm5ZboG9Pc+aSZ0whkZmFM12IqFinusRQxhXMbPzj/\n/otyehNKpnVPe6YlBGmasvpHCAMfDloxCyZU4icVd+dr+ezoc7zF5WS/DV5U9zfePFLLcOACOl0K\nQRlOTYs4Tdqx/21fTCn7xfk9sBtcE4ew+gY5YjHzn5WakPpZ9xgtWDgmJY+ZO7Pln7AERgg5mkHM\nvQUyUyUy1zgcOgQUw93JYJkwG2Pr1zEmKZI17XFvubBhwwbdiarOdsXXarVis9ky8kRqbGwkGo3S\n2tqKJBU3k/ntV9Zwy1/G+FuPFqZTbhFYX2OhszLEcwMhrlnnYGejlZ2NVo64w4Tk3I3r3d3dOWsL\nwOfzceTIEVavXk1VVVXSbfft24fJZGLHjh057YOBwUqn5P3gllIY1UiQke5dhIdj9Q2Z6Emz7eLH\nbpYqqk6lzhLMbfkavW7DuaTPJ2KufoIwYS7yB9ipuhJuN9Z2FRMv+Aw3V70aUVX5fkU5NscxTnq1\n16jbI6GoAt6IiC8CT45osVuf3u7HHo4ldGrY/1U+XldLWBS4zuPllT4/4y2Xp+ynKlkJudryopAC\nKKKFkKMpL23nj7NbeDVY3ixUvoJlHYQcjQTKOovToSUYfdebGHnXm4DMFUaXy6VvwckAURTZsmVL\nRvtKkkRHR0ecQlqsmMXOChNOc+x5+e6rZrLJ27W+ra6KxTe3VZgIREt3sdHv10KCPB599cn1eJEZ\nsaQGBvGUvFK6lG4UDPgZGxvjTO/JzJueGxCMgWHFkcYt7fVHsVY9A8D7J6fwl69Nuv1G+2reM+lB\nFQQebjzN8xOa5fzoVEwIuPFxLenPa9pCXNQQxRyKKe//WV1Jj8XMmnCYW8cnOXHuZ3G3XT33uyiV\n/mu5FIkE1vKK8jwcyXhnDXJIw1btX47JRIGTLeWokoW6urqc9wegubk57X0CW9YT2LI+p/04W62h\nZ5MiIggCdQ5tXrx6rQOrSbvnV6yy88mXVHFRW8w7qN8jMx5QeKQ3kLf+yLJcMm61Z9NzYGCgl+Ur\n/c4w/8UOh9PL7js7JQ4e3Q0De3LYK4NicOZMLAY1nXq33ep+kAJsD4Y4JxRmvPWKlPu8ofJlbA+G\nmDApuB2/4MPP2rm7OzbBBmXt6dpUKVM5+BjN3T8C4Geb3syvy8uwKCofc7wUf+PFhB1NcbGRa9cm\nV4rzRp5kxFj2zjyQC8HW1WCouGc7kln7VyQSJRnLZSbUTBEEAVVVsR86hv1w99x3BtlztlzHpjJN\nKd1aH0v0JQoC5zZZMYmxa7ChVnv/ukbzFx61d+9e9u7dm7f202Hfvn3F7oKBQcmxLJXS06dP03Xk\nyKLvT5zQXwJkPnJAnzvG2cRyXMXzeudn7tPXf1VVmXQ8BcDbPF56t30EVTQjpNDQJtuu4kPlr8Cp\nKATKTnASbaI7rza2MFJlUbiiYpim4z8FYFCS+GZYW/x4p2k9tY2XM7z2LXpPL2+kOtd0UPPkWpxX\nbOUEKnNrBTIwWISkCeWqlEEWXmdt1ofPRgmqu/sX1N/986z7YHD28Z6d5bxtm4sXNluTbvf27WUI\nwEOnArj9MqenIgQiuQuxKjWZZr7FttT6ZmBQLEpCKR3u72WkT78brnuoH1NkQerwYHYJdwIBo+bh\nckdAwTp9GkGJoFcp3ecfAssoNVGZK3x+/OVrdB+vrO4CPuXWYkWtjb/jguYBPrk9QI1Vm0hf1xGm\n9cidAPgFgfet2s60EmCnbQ0va7ouvZMrCEJWlkdtYp3dP4eTrNkJzgWujHOT+NlhbTBY/qi2SoLO\nFhRb8iQps8QpkaKEIuawpEyS1yaVgLxQuS0vz4d7vsFKocIm8dqNLqQUc4tJFFhXrVlL3/f7UT7y\n5zG+9vRk0n3Sob+/P2dtGRgY5IeSUErHjzyJFPHp3t42fQZzcDz+S392CXd6enriPguR4FwN1bOR\n5bhyJ4W9SNEgZh3Jl4IyfHm/nd9NHgTgap+PkXVvAzGNhNSCyHbHBbxq2ocgRvDX/gJFCPHji6e5\n+yIvN9Sewj7dSxi4acMlnJLHaDRV8c/Vr1kWrls19Q3F7oJG3XqoaE382zK4jgYGsyjm4rvkQnyG\n64gledkQvUnvDAyy5bZL4hds9gyFGQ/kJgZ0bCy3SRnnsxzlJQODUqQklNJ0KUSGVjE4ASOH8n4c\ngzyxxBzxlwEzr/xLOa97uJzHhgX2R7R7/JppH4GyVWkfRqhs41PuccRwOaciw3xx6AdMj++m2aFS\nNfIUblHknetexO7QSVyinX+puR6XmLz0Si7dadMj/rimIpcTSI4hBBgYpGJ+mSeHc4nMt2nGfC+H\nBbVSZlaBMa7jYuwmkfefG295/88nJ7nlL25OTqSXMyRTFEXJOBmScU8NDLJjWSqliVCU3AqpxsrX\n8kaUF2fwC8rwX4diQprJdRTR5Kcy5GBDOELEVjP3m6pzclHsdZSpKv8cOY8G0cVxZZwPTj/IN8fu\n4yuc4pq2FvZFBykT7dxWewOtZn2xYZs2bdS13bIgr/O0IQQYFI905omE2854ZkSsNYt+EgQBk8lE\ndXV1wvYs1ty486r5TERmYJAmtY74xdBj4xFOTUZ5pj+7ECu9CuPRo0dLJhmSgcHZRhq+irllqm9x\noqJMmB1ohkeGc9KewQzLWCeXItMICWrQnvHFC1+mit0AXBO1IpvLUKVYIgZBVYma7EjR5Onpg2Ud\nALx75Ae8dkzkSzXVPOR08ETgEFgABHZYV/P+qqupMRmxVznDWDQyKCI5s4gIIv4kSbZ27Nix5G81\nNYsVWT0sVI4VkwNI7to4/IG3zS3UGdYgg3xSY4/N0y9tt/H4aU0ZnQwWpq78bD1SAwODwlO0JdKB\nozpLsEz1pdzE6/UyOdibZY9yy4lJmV/tG0E2ZOeCk0gh/eUpCzc/4wLg9vN81DmmMZcdQUDgjZEg\nEetia4RsdqU8lirGykjUygpfH3Hzf30DfMB2Lp8am+SuyCo+VffmklJIa+sWWGtnLSXLUdhcjn02\nMCgYsQkoUVhA2F6fsBzNQkJrOwmt7cxlx5JiKL65ZTldz9m6pletcdBREbObeMOZK6WJvBTC4TCT\nk7lLpGRgYJA9Je+343a7U25z5syZAvREPyGfh2sOfJAPTX+Wh90H2B88RUgpTDxEKaCqcN9pC6PB\n0pgIwzL84HishuiGcpkbdzwHgsx26yqagxNEbPGKmmYV0Nd/97o3A+CrWE/vto+wJhLljR4vb/Z4\naK5c2tJRDFxlLuz2BTGttWsJOpsTbl9WXpZW++pMrUdVyC4etXNVZ6ojZdW+gUGx0KsgLN4u9X7p\n1jaNWiuT9wGtTqlj1wGcuw4s0S+DdCh2aFCp3z+7WeTOa+p4584yXtYZm6u8odxaSru6ujIuI5hr\niv1MGBiUCkVz380VelZ5C8npsWlefvhf+HF5Gd+sqiAQuh9CUCbaeXvFFVzi3FaQfogRH4pkgyLU\njRwOCnz3qI1Hh0y8cVWY0aDAq9uKp5T3+bW1l82VUV7ZEsEkwqN+LevupbYNWIKP463ZmXH7no5X\nMFG1g6i5HJtPs+zX9D8EaIpqKdHW2sq0b0Gma9GMsoRVuLWlhS6PTld7FRRbNSG7gmzJzjJst9lS\nbwQYMaUGy42MBVAdykRrayuKqnBgIPP4u1AoFPfZ6XRS/ZP/AwHcl70+43YN4imkcjj/WKtWrVqU\niba9vb1gfdFDjV2TWyptEv/9ylru2eNl91CI7+2a4n3nJs8WrZdoNJqTdgwMDHJHyVtK9ZDIXbNY\nCCcf4o6qCr5SU0VAFOkImOk0N+BVAnxr4n5+NP4ET42YCOUxgbCqyGx4+mPYDhen2Pn9Z7QEHF1T\nJj6/18G3j9jxF3H8/22v1p+bNwW5stHP+MReusP92DFx5dQQgirjT1N5VOP+Volaq0CUiFhjKe39\n5avTKzGTR4KutoIcRxUkZGtFnACtR/hatSrNzMfGyrLBCiP1e5L6PRJFASnHC5EtzS3YbPPi7Uvc\n0mawmNl71tHRQWXlYuu41Wpd9F2p0OQyYTNp/f/zyQDRHCe1NDAwKB2WvVIaCgWx+Idy3q7H6yEQ\nSG+1+UjfCAPCAe6qrEBSVT46buc3g718vvofeG/lKxERuN//GPb+j/PkU48AIEq5vwV+7wQA7eNP\n4J4Opdg69/y214qIwnzV7bgnN4LS1w/Z+NtgeoreXwc1pbTVGmTj3/+Z3X0/A+AV3kk6Tt0HaLFV\n6aBIMUteOBSrZytbygm4tORHZ7b8k662FgoE+RD6krnT5up4EWcjqiV1HG4iqqurkTIpQWMIyAbL\njEzddzP1Cgq42gm6lqjzqwNRFBDykKHXUG4Lz1JWej33wpbAe0UUCyNCXrM+Vs7o+HjphULp9X5w\nu93s2rUr45IzBgYrnWWvlAIIeYjXDPgD9PT06N5eVuD8nn/nzjptcL/acjlrTDuxClF6J8Jc4drJ\nucGLAbi9xsXLTb8B4gczVYXpLE/F4hvghfs/DYAkqLx0z4dAVbR/BUBWwUqYk7YbuUm6f+77W3c5\nM076pKhwyivymr+W8ecBC1896EBOcDrm8FTC/RvtChc4B9n69M0owAMuLe7qNdMxN9aIbXGio0yF\nwJ5zPsGRF39zJqvlMkAQ2Lx5M5BZpObswopiq0qxZQ4pglu6gUFR0TkcLdQvVJMNRUpiCUtTOTSU\nyewoRvzgwntmseSmnFAiRTUfbKixcMuFmoU3EC1dS2mqd2N4WKsSEQ6Hk25nEE8oFDKSUp0lLB+l\nVFUTuuwJioxQoNW6ZDzU1c9dNQ68kshF/gA31r+I6ipN0Tl4RhuI7hn8Ea/zThMWBT5RV0NQifdp\n/VWPhesfKWcynPmk337wG4u+c+27k01PfCDjNtPh6RETt5u/C8Ct5p/TY7uBByyfBFT+1G9OvvMS\n/OykhQ887SKixK7LNX8t595ufS5H/ij8XP4YALtsVgbMJpqiUc4NalbkUzs/CVkm5olDEFAl/ZN+\nQYQ8QUioeM+yKPlRGjQ3JU6SlAuWrKFYsw7KWw1LqcHSz4BkBfvSz/yyQ1jaQyTOE6IiN/GBSRVZ\ng6wpRkzprELc0tLC6tWrcbky82wpBuuqNfnhi49PEM5xWYNwOMyuXbsWxdrOEo1G8Xg8WR/HSGiU\nGQcPHiyZpFQG+aX42pxO+nf/kTPPPbDoe0GVl7RoHRpT+fuh40yF8j8QnDv9fX7rcmJSVd4ubNIK\nn1drbpz/MH03735UExpuHZugNRLhqNXCew4/C0DfuIf//ftefnRCEwKeGU0/DnFK9vGE/xC/tMk8\nabcxX91t82qFoPeM5ce6NC572RXo5vlANw/2jfBq6em437eKPXzS9FO8GS4O/ro3sXD0ix5rytDC\nqAKhSOxq/N+MlfTCqks4/qKv0n3elwi6EghxK3DyyDYjrizFr4qLksjatWuzajMVCe8NgNkGrrq8\nHttgmdOwGao6inLo+notHCDVYk8yxWSha2TE2ThXK3QhgbIOMOmzWukZ2vwVa+Ped/nf/5XBj7wH\nMCyly5GFSqkoilRVVdHS0oLFYsHhKI5XT2Njo+5t59cvHfHl1v11VuGcr5RGIpG563XixIk5S50s\ny0xMTOT0+AYGBhqlkYVFB54kpntFXpxFZyqocN1hzTrY90wt3ou/mLe+AfyosgJV8PNy8xqqWq8H\nQJ3JQNomjvJ3tAndqaq8JbiF201HCVU8yt/G13LTodu4EgiKAT5h+jnvGfwGr2iJte2NgEUEawKd\nIqiE+YXnMf44/TwyCtRoloHGaJTPuMe5eF5cbHT/L1EvfUPOjEt9ETc/nnqY3cHjsS8b4K3BBm6a\nnOIl8479XtPv+dFUI97IeXRNmji/Tl/mI1mBoKx1+KNbAlSYVe48ZqXfr12MrimJzZVLT1AHJiSu\nFp8B4MTq6/kTu0CNcqlzG3Kp1A5dLjLegn5KkoTZbCI4L/Q6kcCajRCbjsXZwKBUqKys5Nxzz81o\n3/b2dmRZXmzFEkSilkrMoXiBOOhq0xKqWZwQXSoPgpDyPVRFCUGR544Vx5oOwhhxcCsNl8vFtm1L\nVwRob2/n9OnTeT2+XuY/v8M+mdby9MTXSCRxbJSiKPT2Lq5zv3//fqqrq1m1ahXBeZPcxMQEExMT\nbN26lfHxcZxO55w7bqaWUMOCamCgsWwspcmI+BbHEvYO9M/93Sq4+fPe44u2yRUT8jTPOvwIKlxV\n8/LYhJ5ACOi68Jt0Wldzg2caBJU73A8wO1R+wfw/OIQQjqljHJ2K3Zo3PlLOG/62uF6kOzrFbaM/\n4vfTz6KgcJE/wPUeL53hCEMmEx9srOf7FeVzcYJvN/2Fn5zIjZD/hP8Qtw7fw+7gcQTVRKO/HHl6\nLXYZ9tus3NRYz83rLmLPebHFgM2ex7jv8Wf5xb4RTnr1PXqjIQFQuaf1Qa4TH+FFNQG+f5GPu148\nDcCgP3k7z7lNXC1pFum/uJyE1CibLG00mtJz6yuvyJ8CW6i4nHyT7cSaUaKjHCLrtDQZGOQTSZJo\nbGxMqEQucsG3lqOYZqyxSeadTJntg/DQ47ie3JWzdg0KS76s29mO+WVl6dXB/tYrtXriw7700vn7\nFpZBm0eycxgfH0dV1YTlYxRFYWBggO7u7jmldr7ymgzD28DAIDHLQildWDdND6/v+w8AFOAJuw2n\neCcPDj9LWM19bZI/TT+PLMDOoJVGU3yyl5Mv+Mzc31GTC0wWylxl3DwxSWskgmQb4vuV8QrPF8z3\nsm/G1XZ2vJRVgd3z3G/HZS+3jfyYnsgwTaZq/sv1Cr47PMptYxP4Tn4Yy/iVCMA3qiv5YXls4Lf0\nPZ7xeZqCY5gDo/zVt5c7xu8jQpRNwla+csrKX4YP8sr+9Txy5gwfHZ/AIpj4W/QM/zr5Gx7feQsA\n54rdfMl8Dw9aP8nnn9aX0WnQL3KpuI/L3D+muftH1PXcB6pCjVXLdDQWWnpwf2zIxP+etlIu+PBV\nrOfhUDcAlzi36zp2Q2ODru2yoaGhYc7VL9/oUX4zmioz2cm52PV23bp1tLS0YDIVx4Ej5GyDxh20\nt7fT0tKSegcDg0Kz0AW/Yl6pp7JmKGsCe2wOSihwp/G+zrl73vUTan6thc8kE6gbGnIzZq5koX32\nmhbyHJuamqitraW2trZgx9RDutegwak9/3fv8XJgJMSAN/+15oaGcl/dwcDAIDEplVJBEO4RBGFE\nEISDCX77mCAIqiAIeR3p0g1wDoYjmAUZjyjw5nUXcFNjPd+oruTeyEN8fPj79EVGc9a3kBLhT9O7\nAbgkuFiQDTlb6HrJt+l6ybfpvuArADgr63GoKl9wjwNwZ2UFR82xJEBNwjhr/Vqbfx4w80LhCNeK\nT/CNwzYCUZhWAnxp9Ge4lSm2hEJ8qf4dXHHgrrn9T6qt3NJ6Ae8qfzUAt1dX8d9r3wbAVikzVxx3\nANY99ykmDn6Ruyb+gAp8ZHyCX558kFcKXQB8zfJdHKrKjX74av27aDPV0h8d4+NTv+NZW3xc6Kul\nJ3UddzAgskYYmPtc0/8QLV13YZ/RW37ft7Tl98sHtDiZNeZxTlnsdIXPYBXMXGjfmMaZ5xe73Y6w\nQErMh6zS0dHOhvUbgGxWt3PYMeviFXKbzZZWjFHOEQQQRerq6orbDwMDPQgimOaNf6IIZY1ZDSD+\n8jVafeUMsNlsc3GwhjtiaSFJEh0dHVl7o7S1Fabe9VLMV2I/9+gEN//RnfdjDgwMJPxezzMuyzKK\nUpjKB3pRVZWpqSnjHTUoSfRYSu8Frlr4pSAIbcDLgfwFHMxgdh/SvW3/iJveg48TAW5s3UpXdIAK\nxcRbprw0RU0MRsf57OiPGYgkzrKWLo9O78GnBtkWDNFhWSKphiDO/NMmBNlSwdCq6zgvGOJNHi9R\nQeBfOrbhbriAicaXAlAW6KN3WuTOwwK/tn6Bb1i+zZbwfm4/LPJl9y84E3WzJhzmO0OjWJ6+Z+5Q\n5we/xbcu8HFOtczLy7exVb4cBPih8hTPW1upUcYIpxka9La/qPzpqWcYkiRuqa9FQf3/7J13mBzV\nlfbfW6FzDpPzaJIQigTbBAsw2QQbw2IbL06LA05413gxGHvBcfnkETGoAAAgAElEQVQMfGzA4F3W\nYbH9IeQIGJuMiUZCWRqkUZzR5DzT07nr+6Omp3N3VXdVh5n7e55+pOmuunUr33PPOe/BJ6dn8MmZ\nubTLD5zyedTxTtxddSM26lbBI/jwmZoqPGY2LYlSfZN/NOd2t4+zeLBXhw+yid5dy8QO6GaPiscy\nw3M1tPgeOIUchSs8iseMohV7ln419Ix8Vclkw7EsMUkzpLQaqqpJoRQbq9UKjuOKFhmRmSzPMoYV\n81Ozrb2MvZiURJLPdemvXeD+i2M+kHI3q3bu3Ine3t5SdyOBmZkZ9PX1LZWnUZKRkRFa7oZSEDmN\nUkEQXgYwmean+wDciiI8F+JVCHPNOr3vnTtwtecxPGyz4ig7AydrxvfrPoOvTszj62ONWK9tw1zE\nix9NbIUvUtjNM+cL4pmJPwEA/n52Dka79JC/qbrzMNx+Pa5o/0dUET2OhMfxUE0Hhjs+ipOCGxHP\nGL6904Avcb9ZWufH2ntwUvsgDgUG4WCseGh4DPZIBOvCewAA3wh+CqOwo9kYO0bfbDoDZ+q74BUC\n+F6VFi2kH1uOScsrHfMRbJ9gsU33OdzJ/w++WuXCJMviXV4vvjSVmMcb4oxL//eZROPcwGhxq/ND\nuNL0LoQIwd0uB2499QNLysDDOYqy3rHDCLswjVOY4ynKr627foh1jhAm/ExKfuqIl+CjL5sACHhS\nezs8hOBpIoqDXGI6TdK+JyOodZkrOb6z1CKgc2b+XSN6jjUaHt3d6b3F8Xup1ExqRRj0FEoeyLlH\neJ7HunXrFFM6FXg57WS7B2O/JdevlPLcixoupQq7X+l0dXVlFSsqZ/KZ4GgwszivRcyjZgDM+Qvz\nRO7cubOg9XPh9XpVbV8uUcGnfNLishEIBDAwMIC+PvX0WyjLn7xySgkhVwE4KQjCLoX7k5aAP2Y8\nHty7I+fy/Ry7lKf5RcdVcHFWjBEHqoNjuMX5AdRzTvSHxvHY7MsF9evJ4y/jOM+jNhRCdeftsFbJ\nqA/HsJiq2wyN1oWbnFcDAB6ffQXHAiMI6Fy4mn0NnG8Cn+XEPJ4ggK+5XZg0ToAP6XATcymqw4ku\nz7f1Z+NPF86CjTurhBB8xn4Z3KwVh7ggtjjCeOwIi77Z7Kf+3/dr8ORr23D63n8BAHzfaccenRam\noAb/OjoBFsB3gh/FOF+HvtPuQt8Z38eM+zT0nf6dBOVGhjC4wXY+Pm9/P1gweHp+G26oa8cgx+Kn\nbw5gzJf+pXRgWvQqtxIxn2Oo80ZMV5+VsMwHyEsAgJ2TiYOhz71uwmyQwb9wPwUA/M5shBeiwFGL\nRrk80UzlGcoWjRGoXQ9AmRDhbANyu92e8TcKpdJRw1tYU1MDnudhsUgTVYtYlS1301DfkNm4idvd\n5H3X6XRoampCW1sb9aKWAJPJlDKZsJxIvqYIIfjC6VZ861w7IgCOTEvTp8hnWxTpRMcD4TBV6abk\nj2yjlBBiAPANAHdKXP4mQsg2Qsi2bApoUhHGDmb8bXZCjP3/sc2KECE413AqVmtFQ7FXux5rwvsR\nfudlfNFxJQgInpx/C0cC+Sex7+LFNFv/xFnQmbJ4qHKwVteK9xnXI4Qwvjv+K8yaxAfjK9ovi33v\nvBGfq6vHC0YDLOEwfj18FLZ5cfbthbZb8WjoAtwc+BK+c1r6mS8To8eXHVeBAcHPbRa0ml7GF980\n4fEMHtOZAMG7Rx7FD/mfoIsZwG9MRjxuMUMjCBgb+DTskQgiAsFl55yFsXfdiaC+CgKrwWD3pxHU\npU8v3mxci2+5PwoLY8A+bRBX19fiHPeD+M/XD6Vd/sF3RM9oIxHzf33GOgx13IC+0+5eWubjnv8G\nAPiTnoHexRIyN3LPIADgJ24xD+Yy8+lpt5UWQhAdiYU5Q1pvX0Bf3FAmIblMgww4dtFwT1eyRYIn\nM6Cvyrh9lhEnEPi4vOhKKspOoZQDBoMBa9eule5xzPN5kE/8Q/i+f8HJr38+4+9utxs8z8vyHK9U\nA6C5uRkul0u28iwlkVa7+L656+UpzAdKm7dZ6LVcjPzOQCCA7du3Y35+XtXt0FxVSiHk81ZrB9AK\nYBch5BiABgBvE0LSJrQJgvCwIAinCYJwmtFoTLeIYswP9mKAY/GEyQhWILjOcs7Sb4GajQCA08e3\nwvn2n/F+3RoIEPCTqT8hksdNdCQwhMMaD4yRCO7oOSf3Cjn4uO0irNW2YiaygE9ZfPiJ1YLtWi3+\nn9mEz4T/hje1LBzhMB4eHkNnMIgzBn8GALDZHKg64+/wD5tXw8hnbr9T24AbDKJR5ql7Gn+n/S1e\nG0w/o7VrgsEN3HMAgL0aDb67WPv00/bLcGunCxt8P8b72Eeg5+VdPt3aRvyf6k/j3dp2eBkG/9dh\nw4m2X+M/Jv+I1xb2Yyg4uXQu2s1hXMS8hX/V/xQAENI6AEIQ1LsxvOlrS+HCbkzj54d1CC6+k3yL\nu+SGGK77aMN6TEQ8aOTcOF3XJbmv8S8ZgckkDlH4oIqQ3PUDoyyVfpBJQ2MDrFar1B4t/c8Qd7+G\ntLaUJaOGp8GgR119HZqaZEQKUCiU4pLzMZPlPVhXjVCVOPG6Uo1JpdBqtWhubqbHsUDMmtj4Y9eI\nvFDUdHVJ1cTj8ZQ81zJqjE5OpsvGKxwlrueRkREcPXpUgd5QKhXZSSCCIOwBsOQiWjRMTxMEQX0Z\ntBxcMP0Y7rXbECEE5xrWoIqLDaRbGpsxf0wHE/HhXcE3sLaX4M2GWhzGEF5Y2IULjOtlbeupaVF8\n5+pZDxqaCg+d0RAOX3N+CA9NPYVXvPvwgCPOCIh40Mk6cX//bjSGRKvLTWYBAFq9GQ2MtFnCy+wX\n4PDEK3hVr8Fg3cv46vAJAJ/ATIDAwgtLTrTew6I3epRl8eVqFwIMwYXGDdhs2gDBGMLQKg02ufIL\nmbGxJtzi/jtcNvYcfjvzEt7W6fDSwh68tCDmxWoJjwbOhd5ILb7ufg6vBoBNPgKBiVncPtcaDHZ/\nCk17H0AzGcaYYMPxeQarLBG8MSZe0hex2zFHCB7RLAACcK3lbDBZHprNzc0JL6pyzIP0G2phmJGf\nr2HO5bVMc1xMZhP0Oh0QSS+5X1VdBYc9VjPRarGI6p8UCqV8KNBrsVS+5I/PwDI0DO8HOrMuX+jA\n1OFwqDZophRGORrRbTYOR6ZD8AblXefj48oOVwkhWT2Evb29YBgmIZqIksrAwAAAoLW1tcQ9oZQK\nKSVhfgXgdQBdhJABQsin1O9WfvgIwW/MonfnEtOmhN8YAmxf/z28DVHgxSAI+KfJaQDAL2dewHxE\nWjL6+NwCXjnwBl7x94EVBJweXKVY/7UMjy85r8I3XNfjIl8Ea31+nKltw5ccV+Gumn/A/Lv/A4dO\n+07COiSjFy8VhhD8Q+NnURUKYadOi6ed/Rj1Ate/ZMbW46JhPReI4D7hHngIwReqazDKcejRNOIT\ntovE7RHgutYA2s2Fhct0uS/AP4Xfg98PDOI941XYqFsFO2OCXwjicHAIvO1t3Ouw4+aaKpzT3IR/\nHd+Cnb4jSw/+oFactX+/cwgAMO4TL+Xdkxw0COK7/CP4d7sN04IPnZp6nCGzDExJ3798hogCwkBI\nrlOYulD6rxllXoaEiYmaSD1G5TiYoVBWFPGRH3lMuDH/uxX2Pz672JR693NLSwvWr5c3QUwpDqVS\n3s2WCvKd88RxwNB8+ecxlltpGAqlHMnpKRUE4cM5fm9RrDcFMD1yDE8bDZhhWbTztVilqUtZxm0z\nY2zV1UDfDwAAl3gW8AufgD06Lx6beRmftF+csDwJ+4BIGELUSBAiOGfnV/Gqw44IMeOy+QX4G65T\nfF/W69qwvu02AEKKPH9I78Ifa76IK4b/La+2DboafM9jxBfMXvzFzGFs6hl8jfPj+ePn4ANNVvzy\nzSPoYhh8odqNA1oWbtaKf3ReAy6nMSQfp1mPutEQHgpuwwHXjzEdIPjwKwxYzSjO1j+Hbt0O7NNq\nsFunxTbfIWzzHUIj58Z1rvfidK0o8nFt6Al8G+dhMiAOlMZ8BKebJvASr8MvrWYwIPi07ZKsXtJ0\nFMuQSrsdidtub29HIBhA/4n+7AvWbZDUXk9PD0b6D8PnOZlxGZPJhLnZ9KWAMqHV5leCxu6wo7qZ\nzphSKGrCLE40MQXWsFQCQkjBtTSXE6tWrVpSS41is9mg0+kyrKEOTqcTLleqXkQx8gezvYu1HEGz\nlUP/bPqIHjWJ33eWZcve6FTiXHk8Hmg0GurxpahGUePtQgFlJajjMfT9AU+aRIn8C03pB+Ecx6Gq\ntmXp75eEjfj2+DAYAfiz520cCyTWbdK8cT/a37gVs288gtnZaUwOHcU0wyx5Y62Bi9DqVkmsIFu9\nOL0j/fcScbb9Pe4dHQcnCNgReQvbGv6GG3X3Y8uAD5z+VVxbX4OdOi1crAV3uj8CC6tMCYNkFuwx\n7+VcEHhpmAfCRoS9rbh4FrhtcgrfavwKHqr9Ej5i2QwXb0V/aAw/Gn4cXxl7BL81GaHxiZ7SPw2I\nnt5JP4Nu3Uv4epX4Ar3esjkvxV0iKRS1BB7AuE1qNDwMeuXOjcFggM2WmjtaKBZLfvdITXU1HI7C\nrnUKhZJM4nOrpaUVdfV1MKYpVZNuIEsjH4qH1WpNMQbb29tRXy+9/Nxyx6Jl4Cmx0JHb7U74txLI\nx0jt7e3Fvn37FG+XQolS3CQwQb0QCw/8+JtOBxYMztBnErQRX6azgvjyHTKvRWcwiA/PzkGAgP+Z\n+jPI7kcRmh5A1Su3oS1yDDzCODP4N+Dws2g++Qf83GqGl2Fw1oIXF/a8V7X9yYbOLA7U96Ajr/WD\nejeabefjoeFRGMIMtul1uL2ex2+Ye/HnmpMY4jis4mtxl/tjqOaULe0RH4oT1Fdjt/V8TAkmXPei\nBT9+RwcdKwAQ8BHueQBASGuHjTXhast78Ni6b+Oz9stQw9sxHJrCnW4nrmiog8X+HI4Eh7DLM4QB\n/TPY6toJD8PgbO0qXGl+V179tFmtKJfS3E3NTWXiPaCDUQqlEpAaoltbWwubzQarxUKNTUpFYuAJ\nPDJzStViJdxDmUq+rIR9p6jPsqh2veBdQL9hBBHiwAZdK0xMdpXSbT23wTs/DS7CA/PA56en8aTJ\niAMYwOHQOC7f89eUdfyhCPhgH35RXQsAsEyfBVOJIhhqLVrcZ/ln9DTXIt9Kdd6Gs3HG0FP488AJ\n/NRqxgsGA44xZqwNzeCKeQ961n1dlZBdq9WaIElea+Jhn5mHBkGsIifxFP8NRDRcWnuQZzicb1yP\nS91n4pmxbfjd9PMY4D1AzTMw4hl8dwrQuoAwgA/PzOHK1R+SHbYbxeFwYLgINa8JSJpo3cQvjAYD\nGJaKCFEoy41CBnL5rhvvyaClmyhSUMP71d0tT+chEy4Di7eH/AiEBWjYyjSMSuVdjEQimJ2dlR0h\nNT09DUKIDFX/5YnP58O+ffvQ3t6uSpTZSmRZGKWjA4fwzGLo7rv1PTmXr3W7AbcbR6cCwCBgiQj4\n6qToebvXYcPmBS+Miw+Jm/EN/Ae+h3N9z+N2lwM+hsHp2i7cePolqu5TNlgCXLKupaA2IoslPmyR\nCL4yNYOvTM0AEENh+07/DoIqGKRA6kCKgRh2c1B3Y+w7QcwPOX7qLWnbYAmLc42n4mx9DwZ2fA1/\ntrrxNMQQXaffiH/zvIb1/gAOyKjjJ5jrEObGwIYW0vZTKBOvqaC6LrAyrdMQHgpFXaTcY/HPsaX/\nyzFmFzcRfvAHOHnkSJlEbFCKhVrer46ODihVIrDJwiEYAWb9EbgMhV2fxfL2lSL/NN3z4uTJkxgd\nHUVXV5esCarDhw8DADZt2pRjyeWNx+MBAExNTS0bo3R4eBiBQCChxN/Y2Bi0Wi0sFovq218W7hev\n5wTe0mnBgsHp+uyS9fG02DT4lvNHAICr5j041efHKMfhAbt4cd3nvAtfOEc8MS8Y9PiD2QQiMLjB\ndh6YypyQixFnsJ045eal/we0TgR1qYIGajFdc1bG3xasieHJ0RdG1CxjGA4XL3hx79AJfCJwFRaO\n3oI7x2ax3h/A0KqPyOqHwHIQFnN4nU6ntJUUeIFFBPHlVM4zjkTGxV5dXQ2DwUBzQSmUMqC5uRmn\nnnoq1qxZU1A7xGmH303zGFcS+QrUScFslq4zkGvyxawVxzLTvvIQGspWAzUa+ho16kqN3y/qvIRC\nxReKygc62a0+J0+exNjYWMJ3J06cwKFDh4qy/WVhlPay/YgQgnW6NhgZ6ap0hAAf6jLgf3AVFgQd\nbp+YAisI+KXVjH82r8bFPWLS+h5eg2+4RUPlY7bzUcsvjwH3O+++H4c3fRsex6lL351Ym947qRhJ\n9k3AUIORqnOX/p63rUaIM2K0+aoEwzkX11YN4YY2H9bViKHb2YzdXOgN2cO/lcJms0GrEV/8tbW1\nsR/KLDejuytTjnYqWq0WPT09VJ2PQlEZKV4dnU4HjUYjGhgyy0KRuOgQsuWPMD/7luw+UiqTDRs2\nYPXq1aXuhiRabOJk8sGJQFG3m8nbKaUGaiCQua+BQKCia/VSw5FSCMvCKN2rE2/gnKG7aV7iHEtw\n+tmX4sQ594M58wFcGj4bAPCkax7fGf8V/nPyCfx9Qz3mGQaN81W4zHS64v0vFRFOh4ChBgDgsYqG\nR0hTfI/dVMe1OLHmSwCAgKEah979I0w0XZpx+fjBWP/qzwIAOCGAj7YHoA/PwWdsABQNP069bsxm\nE8KcHoKMOrHJ1NbWIGNEnS19tnCYSwx5yivcyJ3lPsnWXnytw0y1VCkUSkUT7yGLDjCZLU/C+cQT\npeoSpcgwDAMmgwJ9utIwpaTKwMLEk6KXhTl48ODS/5U0xN555x0cPXqUGneUFUnF55RO+GewV0fA\nCgSn6fNTo43Pjf/7lveibcGFh6aewh7/saXvNxvW4tN18utdVgoDqz8LjXcYgszZdCUQGB4e+2qc\nWPMleKzSw68BwG9sAAAwYTEMhQ3OI8wXSbyDsPBa2mGYOai8UK8hvTc+qHOBD8wovLE4JJ7/iLkO\nCI3kXpBCoZQ5ie+0np4eHDx4EIvp9eptdZm+S5c7TU1NS97AfA0nJc89IQT1Fg4n59Sr7iCVXMdD\nyvHK5kWlUJY7FW+UvjL2CgRC0BVyygrdzcbZhlOwVtuKbb6D8EYCOEXbnFety0oiwunhM7eqvp1s\nLyOPXX64UIQRZ/X188cwI7wLXHAOXl2+msRZyOJ5ra6qxshICQw0SwMwM6Bsm2xmo1QgHIDKyD2h\nrCSocSOFiGZxsi5HFAnLstBoNPROp1QMVi2DYU/pjdLkXDy5ZCq3ogTJBjH1xBYOPYbKU/Hhu73e\nNwEA6yO1OZaUh4U14HzjelxuPqPsDNKamppSd6G0xI1Bw5youmwfehmOk89D4xtDmJcuohCPyZR5\nvaBZ9MimewSVbMY/Xeiwil0ppgAWhVIJVNKgJGKqg9fSmv65kUQ0hDdaiqpy9pKyEkgWYTJpGCwE\nChc6mplRMQopC9HnSDaRpEKIRCJLObCVHKFQrs9bpY/p1NQUvN78axIODQ3h2LFjynWoiFS0UToZ\nnsPbOi00EQFn17y31N2hlAKGxXS1KGpUffRxAADnn1J8M0I2CfcMzyMh3weVDIGnokIIBFY9RUYK\npVJQehCihtKpxZok308IBIaXNLCrq6tDU1MTTEYFctgpFAVhWRZutzvhO7OWwYw/gmC4NEaLUsZS\nMBhUpJ1kduzYgYGB7FFVSm27XA3HSuLIkSPYv38/AFEZeWhoSNZxHRwcxMTExNLfExMTS3+Pjo5i\naGhI2Q4rSJmOfqXxprcXAiHo9hvgMqhfP6dcqOSbXo1BzVDHDYjE5UKOtXxA8W0s+Qpk9F9gOHhN\nTbkXTMbaCACwO+yqyvIXS2WYQlluuFwu2O32RNXsPCCEoL29HV0yFK6lsGHDetTV1iV8Fy3DIaX8\nFMMwCcuFf/4ADj3wgKJ9pCwvzGYzWlvVTwFKp3rb5eQRjACHJtUx6pY7Ho8Hu3fvLkj1t5LHpcUg\nEAjgwIEDssvvnDhxAoODg5ibm8t728eOHVvynPb392NwcDDvttSmoo3S1xcOAADW+6UWraWzvKVA\nUNjzl2LYEoLR1muW/gwYEsOtpTwq0xWFT2dAE7n7InP5oNYOsGKqd011Ndra1HvJNzY2or29XbX2\nKZTlCsuyaGtrA8cVLstgs9kklVCSM+gjICnzZ0ajERs3bsyvALpeD0GnjGYDZXlCCMlYn5plWVRX\nK5MGle4+WO3WAAC++eIkIhVsHEmdtBcEAdu3b8fo6GhB24gey2ioaCGGDyU7IyMjWFhYSPBgSiE6\nCZOpBFGhhEIhTE9Pq9J2PlSsUToRmkVvYACaiICeEM11K1dEg1SZyYBsg7Kp2izh2zlyqCxWC/Rp\nBlzx28u2B9GBaUq4nBooaOCzLA9NTVfm46NdOdEHFEq5o4QnIt9IFeZnj8G9ZUvB26dUJoVeeyzL\nKjKBkwmzJvZe9AYrzygdHh6G3+9P+C7bMY8aKCdPnpS9rWJ6NGdmZqiacJlz9OhRHD58uGzOU8Ua\npa97ewEA7/V6wRoaS9yb4iIUUXYiKiRUTqQdWBGCBUsbRluult2eQZ97HyOcaLQGtfaU3xiGQU9P\nt6SwOAAF1TYFIQgpVfKG4QBdlj7b8gg9plAoqhAdiAb0bkTicrs7OjrQ2SmvlFZasgxWyRPPwP7M\nM4Vvg1JRVGIO8Vf+Mo5AiXJL82VychJ9fX2Sj3d0uXwMzGIapX19fUu5kUpAQ4SVx+fzAVDPEyuX\nijVKX1sQL/SL5z0w2qpK3Jv8UXP2UAlCmsrxlh1fdysmGi+RtGxDQ0POfM2EFwTDY8HWiYgMI93l\nTO/B91raY4NKWzOgTx/yVHLUGJBwNASQQsmH6IAspLXDZ46VvbJYLEv5omlWyt1wBRoelNJRqKGq\nlk7CJ9eL98CkN4J7XituOKJUY0mK91MuShp+Shh9yW2oWeam1Cw9k0MhLCxkL+xcaE1ftQ3ycpmA\nqkijdCQ0hb7gILQRgnO9PpitZTqol0A+RimdLSoclmWh16sr9ON2u9HT05OjI5qVNShkynsShkIp\nV4r+3Gdy57lSKHKRGlEklwvbYhPGbw/78bmnCqsZWk4sLCxgYGAgba3RmZmZgsqHAOVjkFQqMzMz\nOHDgQMr3giDkNFYpiVSkUfraosDRBQvz0AsCdNqV5X3RrVDBiQgvlicgVLCKQqGsMIpulJprALOy\n9b8pywup12QxjB4NS3D/xS7UmMT0mFFPGBPeyvHSRSKRlOPk8/kQiURw4MABjIyMKLo96txQn9HR\nURw4cADz8/N53wPF8pSWC0U1Sr2RADwRX0FtCIKAvy7sBQBc4pE3A1GOs0ECwyHMyfPYJdeOqyQK\nMSgFQ36CVoICRmz0gZDuEoo4OtKuU4zrTY1NBLV2hPVUPIxCKSfSKYRnRIkHAyGAcTE1hqVeU0r5\n02jhsK5as/T3TU9Ujrc0XamQffv2oa+vb+nv4eFh7Nixo5jdUpWdO3dmrJ86MzOTEtLs8/kwOztb\njK4BEFWJCzEGo15Sv98vqR1BEIpufJabsVtUo3QwNIFPDN6LR6b+jLmgD/5gGK/tP4xD/dJr5hwM\nnMRAaBxm6HD2ghdP2j6mYo/VRyAM/IblPBut3AWfd0x+pj6QwtotTwofjAb1boQNyuRpR1iNoorB\nFMpKpaMj/eSXqjAMULcB4RdexsGHHy7+9inLDrUnaz+yxoxWW2WmiaQ7NvFlWgYHB1URpCmVNy4c\nDqf1AHs8HvT19aUYrL29vTh06FBR+hYIBLB//3709/cr2m6263/fvn3YuXNnwnfRnFyaU6oiT3u2\n47aB++Hc9iV8auIeXHnsLgBA+NX70PPXz2JkLPPs1nMe8YRdNT0FHoC9XgHVwVIiCFgJ9VN1euVC\njsvl5kkmr37ltQ6T/7pqwWfw3hMWqF1X3L5QKMsQrVYLg0Gi0Bq76C0yuhXZdvTZJnn7MnA6nYq3\nSVEfWZ77ImLSMPje+cW9popdrkktA2VychJ79uwpqA0l+hb1GieXySkmUWNQ6dqt8ccnGAwm1Jv1\n+/0pkw7F9AyXA0U3Sr89FESnP4BRPoKP1dbg2KLQTygUxJrIOwCAzb3fTKsa2Dc1jVcXVXc/PDeF\ncdhgs9EXWlmj6MMzPyNMUNlTR5ji3kYBvRsBnQvQZhaMKHopH+eq4m6PQlmBSB7wMSxQtwEwKvN+\n5O6/H6c8/TTa2toUaS/Khg0b0NzcnHtBSlnR0tKSW8SvhGhYgr9bLZZOC0cqJxKqHCbc861Xmfxs\nSmdQCoKAsbGxslLk7e/vx+TkZMr3zOK4LptnulADPHqsJyYmCmpHDdKdo3Qh5kpTdKN0c2AEPx8a\nwZleHyY4Fp+tqcI4y8C74/8lLNfzyufgnxtf+tsfCmOk/3sIIoTOgBkNwTDeWXOrPIOgAOMkzOly\n1pcMcwYIpDxnDyuBXErESw8Amc9t3p1P2Fv6jZTDSwOERUjnSPCU6g2JeckRVpO8lroU2TCnUChK\nIeGZ9sQT0D3zjOLeMYZhyuOZSpGF0+lUrbSLUgQXjdED4/kZWSuJ5HtQidzGwcHUtLz5+XmcOHEC\nJ06cKKhtJRkdHcXRo0dTvo8eE6XDpfN93hU7tPrgwYMp373zzjuqb7foI0kOgFEQ8OUxI9oCHE7y\nHD5XXYXV/lcBAC9brlhadrrv9aX/T7zxX/hfi1iH6h8nD2MUdjjs8krBBIx1efdbICy8puwzuhFW\nA6+1XVJ7vCYqHCEs6+jdUu5aVXUVGhoawPCpL09CSCyPIm3OqfIPAL+hBl5Tk+LttrW3obGxMeX7\nkMZcfOOUQqGUPVEFd56nAkaU5cnaRcGjv54oTFxTSbIZFoIglM0Ezdtvv614LiUQM/DU8LgFAgH0\n9vbm7enNRCgUwliWlMJKJybimXjtpStl4/Opfy8V3ShlBXCtO8EAACAASURBVAEvuT4K7j1fxzea\nb0Y1Y0OvVoOvVLsxKpjgXnc5HnZ8DQCwef5JBBddyEcthzHBsejxB/Burw+jjPxcGYHhEMqU+1Zk\n6uvqS92F4qKEjSfzge2wO2BuWqNKbcz4G1hqiZ6wxgKBU76cj1ajAZvGUxkw1MJnblF8exQKpbKp\nOuVcNG04T/VazZTlgRwvTbmEY59aJU5GP3u0MAVVKajRfqkFGCvNEJucnITH41G8dA6Agj278ecy\n3/NaiushGAzKWl6JyYbiG6UAnB3vBgBYWCPuqPownKEw3tTrcHt1DSKCgLNXx7yNI4e2YTw0gwdt\nNgDAP05OgQA42f0Pxe66ZExmU+6FClF+dXXJX6dcMOSf45RpRicrWfIus5MazpIJjis/b0Nnp7oC\nYKV+YSpNa2srVq9eXepuUChFgfB6GB01pe4GpczJx3PncskrJ1YM7+Dbw36cmJE3wC4F5eIpjZLO\nW1auRFML1FAnzpdyO59ykZP7Oz8/j127dmFqaqqgbRY/fFcQwMblDlZzdjw4MgpjJII3jAE8PP0n\nhBHGcYihtsHQPH4w+GsEGOCc+SACpg/gb6u+ihaXBMMvLYkXibtKGXXCdG2rhiaziE17u7TwYenE\n9qmltQU2u62g1gRz8QZCSj4PrNZF43bJFkttPLkGq5oPpI0bN2b9XadSvo+i+2RtBBzKCqfki8Ph\noF4jCiUTer34oVDiUGJyUs0JzlvOFN/b33tlGrf8ZaLsRY+KOdkbbzxkeq8fOHCgWN0pCL/fXxQR\nnlx4PJ6c53BgYADDw8MA5J1vta6NXCHlUvF4PABE47QQim6UvtVzZ8p3x22fwGdHzeDB4nnPTtw1\n9ihePOUq7NBq8LB+J04wE6gJhXC58B64ejbDXKucF4jNIV6UiHID8sSHgHLtajTqee30Oh20mvyN\nnQVLW0GhtHl5SrO0ZbWILyyjMXtIt9vtTt2m1D4sLscrfF5yHgNBQHd3N7q7uxXdrqIYXYAuX082\nhUIpGn/6k/iRyHKLpKBUJptqE8cr120dQaSMr00lwjzz3V4ltZ3M3r170worZUIJIad09Pb24uTJ\nkzmXS15Gycl+pUvYFJuiVhgmAOyuVLGhde86H81TG/Et/0ncM/E4egMD6A0MAHU1APyoCoXw4PAY\ngu+6MGv7QY0VfGBGnc5TssJxXBFmqpSrAypAgEGvR0+PNKMt9gCL/iuvL5kfOkR2W1LJaGyXNKSk\nssNZKBQKhVJcGIbJKyxTzzPYWKPF28Ox8iQT3gjchvKskhBvKA0NDZWwJ6kU08hUs2RMMBjE7t27\n0djYiKqqqoLaSndMvF5vQW0Wgs/nS6uamy/5nPNCr5Mie0ozDEgXFUI7tfW4r+YmfNB8Flr5GtQH\nOXxsZhZbTg5jlYSEW4FJ9Eb5C1DbVYIwK03UZt26dWhpbVGlD4qqr7oz1yVraWlRbjtFQMqN43a5\nYLVa4XbHh3gr/WBWtj2GlmahUChykDJJdffd4oeyoohOppb6vVKIJ+n2c+x45IrYO/ye16Yw41PW\n6FHDYCtmPme247t9+/as3r/x8XHFRZHSlWhRiiNHjgAoz9qgyci9rsohhLlQivqkyXTZR/hYfqiJ\n0eN663vxw+pP4keNt+As9xcxFa7BC6b3q9MpTsVaWxKeo0IkAo7jwbHpndYOp7yyN0pjsVjE/xAA\nvA6CzpJ2OcKo7wFbCt9VwNuW7mYP6V0JRjzLsKirq02rbJu4tvz+CPHrSAhpDmukhbl2d/eoNsFB\noVBWKM89J35yUOnCHpRErFYrampq0pYcy0WutJhiYtWx+D8XiiKLh6dC+Pnu8gxxlBq+W+zw+GgO\nZDqOHz9eVnVHo7mNmSg053G5ofR1Vug7oDw8pRlgOB6OqnoEzr0TNRtyG6Vud3bVt3TevIhBmtCR\n1WrFKadkV+c0mUTjWopgitQTV11VBb2hdAITzc3N6O7uRldnquLvgi2W28sQ9S8lIcv1IztnM929\nxvLwGRuyrkaiN6mSgy9zDcBmnxxh7WnqmxIC6O0JX/E8D73EEjUUCoUSo3xz7SilgRCC+vp6cJy8\nTK9TTz0VHR0deW1z06ZNaftRKA3m2D54Q7mv9eH5EK7ZMrz0OTatvnpvsY3NYucfFmP/vF4vAoEA\nQqFQSZR4I5EIIpEI/H6/5DBkj8eT1liuxNz8igrftbHqzpwxObx1RqMRZkt6T18uCAjYDN7MKCaT\nGZs2bYJWJeXTUsCyDAgRJwiykeulIelCzfneUe4GjQjKP6xkvTijiwqCaFwas0+otLa2pldWtrdI\n3yaFQqFQKCqj0WiWSnSUCzxL8O+XumDRECwEc48ltuxPNBKyeVelDsRzLTc7OyupHaVRSjyymNvL\nRiAQwK5du9Db2ytrvUOHDmUNVQ6FQti+fXvW0N/5+Xns2LEDe/fuxfT0tORtp6uvWmqjNNf2Q6GQ\n4vm/RTVK7Wy+ZVxWMLwh4cIISgzjDHOZy8ZIpbq6OvbHkic08WES0FchzCV6cuON8hCfOBGhxMMo\nXRty2y38Zi9umBrLsrDZCivHkxf2VsCWoxi6ubS52xQKhUJZnig5MK81cehxazC+EMaoJ3v+3YvH\nfQl/7xoJZFxWjfzEXGGo2fD7/fD5fLkXXCRfj+nu3buX/l9ONU39flHYKpvoULox4+zsbNZQ5Wi7\no6OjsvojxThNlw+qpuDTvn37EsS00t1nue69Xbt2JVwDSlAmqijFGuAXbsxIan7xPEbDebOvImQP\nBTXXJOTcCqy0MFVBpZmo5JskpLXBb2pM2IXmlualcJ+AQTmDJRq+K7A8glp7jqWzk39NyjTqu3kd\n66SLpZhwWsDgBBytuZfV2wBDjrxmc3X23ykUSmXjdIofCiWOYnlylByndTo1GJoP43NPjeP1gfSG\nW/x+2XUMokF43mDxw0HlIAgCAoEA9u7di3379kleT4oBm+5cB+MESEsRKpuJY8eOFdxGuv2NGqVy\nr8eZmdxVQdK1qfRkR7yR7vP5MDg4WPA9HD3vSt2jZWGUquXJNxhSvYUpIjkqhhHIEuTJNLBPUhQO\naXIYY6Ya6dvMAymzdyzDoKZ2sR8KHt8loSOGLahdhmWg1chQJSYENpsNWq02Z95yMsk3fNkIgdia\nAL50ucoUCqWC2LpV/FAoeVA27z0AZ9TFIrl2xJWKifKbA/P40ONiKOVNGy34ryuqcOt7xCilO1+c\nLE4n82RiYgJ79uwpdTcAlD70VA2SVYHV3kc5arozMzM5PbL79+8vtEuqUxZGqVpUVaWKGAlqqu3K\nIGqwLl3UmYxJTZJhXcSHu6wXib0VXnMLFixp8h6VRs6DoJDjxS8KBvFG8DyPNWvWQBcNTZbZLgHB\nhg0b4sS2FteXvC85tqdk6Z9sLMMXDYVCoVCWNzwvTvDXmGK5rslv1b7JIB7dG8sl7XCI6zRaxMiv\nI9PlXXJDTWVZpcu+FEK+xmA2p8r27dvz7Y5qyAmJ7uvrS8lL7e/vx+Rk/hMppZhYWFZGqZTjp3U0\nIqCvQkRCGY5kiIK1ugSnaLyFNebcy8oR5TE4IAAI89F2CzRipXr69DYIrAZgWEBf2jI2iqExAlWn\nAMZY2JqgsyGkMSMkUbU5HtVqvbm7AVeqOjKFQlleJNZMVgoJ74jbbhM/FEoJUNLTyhCCH17ghE3L\nYMKbmI709edi4ZIXtOrRZo8ashx0nNiH/tnyNEzVFkkaGBhQtf1iIFf4KBNKXI/Hjh3LmvMKJE4y\n5GMgjo6OFlTzVU5eslIsK6NUCjW1tQhpbQARZ8uUDSuR0ZbGhAVLO4L6wvLxAvqkQQqnhdfWiQij\nkudMyvHSqKOyHKvGUtg5k3Vzc4nHUQBBwFCbFFYt9kej1UiXzl/ah8W+aMVJhDCfhxgYrwdyKENT\nKJTKx+12w24vLJ8+L15/XfxQKBVK/Ht/lYNHl4vHjuEAhudDmPGF8fHfx7xMnzvNgs+fligqGQ3h\nPTiRWfCoWKQbwxw6dEgVwaVyJhAIlMRwUoKJiQlZ9V0HBgYKEr/KRLbxcH9/f07DWWlWnFFKCBHL\ntqhRyzG5Vmcu46nA3MhSkC5PtrOzM82SiQhFEPQRilArNUo6w5hlGHR0rEpeMntD0QcCr8eCrRMR\nTqk8TxpmS6FQKJTKR42c1FOrxAnnR/fM45N/HMNcIPbOPK859T282i0u/5/bZhEpcRqLHGNmORI1\npPbs2SNL0KmU5MoPlXKNZ1MGVotAIP0kTCZjdmxsrKCJgrIwSjPtHMcr6/1Jf9IlPuxyXDAh3oSI\nXr46YUy8pyxORV6YzaKXr7u7Gw0NDVmXLeTlEi01w2cQKRIYHmFOhckGFahUk5FbzMsptxp0FAqF\nQln+aOSIFGbh4nYDOAZ4LUmB92dXVYFNU/Oej/su3oAtBXLqX5YDgiBgdnY2YaxfyUJIgiAgHA5n\nrWmazNTUVMHbVfu8x6spR5ESFh4KhRIUhgvJYy1rS8jozlEfsYwIae2yvJ6yjLMi3LuhfMJGkzAa\njYm1TRXAbInl3LpcTjQ1N8FqsSi6jUoivgZsetT1vFe53aitq13R54BCoVAoxSM6XmpoaEB3d7ci\nbTKEwGVInFy9ussIkybzsLjKKC4/Ml+eeaXlwvbt2xMMnLGxMRw6dGjJqEoe/8oNSz18+HDBfSzE\nQeLxeLBz586C+1BupKs5KqUma19fX4LxWkh5oLI2SssPaRdxxFKfc5mop8nhUF4UqKmpSax/qgKS\nPLraVIOF50QPm9wHQbyRS0BgNBjKTwG2GHVKF7exevVqrFu3Lo/tKQPDMLBZrWUl8U+hUFSmoUH8\nUCglIDoZa7PZllR0lWC1K+Z1ffhyNz62Nrvw5PfOF8dr/7VjFtdsGcaoJ5x1+ZVEsucz3tCM1vfM\nFAqaSYAoOs5IHm8oJeoUDtPzly/x51vJvN4Vr44iZ3CdblmNVoOAP4B440KQUJ6DZVmsX79eFUVW\nt9sNAweceLtf8bYlHa44cSCLxYKO+h6Egn6YdI3QFZLLK2njJZxnIQwgUSk5wi4eB5mlXBiGUU/F\nl0KhUNLxv/9b6h5QVjCtra2Ym5uTECkkj89ssqDZyuGsJh3sutwpKXYdi3Y7h8NToqf0zZM+XNGp\njrDjciLfUF2lQnx9Pl9aAzS5hAolN4Ig5LSbCjlvdHRbQliWlWgUyz/BAqdDiDfBb8hQ/1QhTCZp\nYb8cy6b1CvsNNQhq06tJBrV2oHqNvA5ViAcvpHOIpVxUUiqmUCgUtdi4cSPq63NHBFGWN8XKC2RZ\nFjabTfF2OYbg/Z1GSQZplFpTzJczPE89bXKQG2GllCdz3759ab2xcq7fQkJSlxNRb7da9/7y8pTm\nOkjpbogCbZglNdoCT1C2mzX7yc+wHiEIGOsK6lP6voj/6g161Hd0LIkc5UuE1SGssYD3pyaBRxgN\nILGebPQ85DoLAb0bTLnIDPFKKe1SKBSKinzlK+K/998PQB01VApFTZQaRM8HYsbJUJbc0qH5EKqN\nLJgVcq9kUwTON7wzGgJMCEk5f1KVaJUyJpXIY80GfaaKlImntEyMhDyIXUjlqSpmNKZ64pTwntrt\ndlgsFkVvJOltSTTSa1JzL0NaO0J6F6BY6ZUkbJUjzpUO6dcufYBSKCuGnTvFD4WywrlxXWwiftdI\nAIenUhVLnz2ygC/8aRxPHlooZtfKlrm5uZTvpI41JiYm0hqWcpRvMyFnrK5UHmsm4tVrK4FsSspR\ndeJ8KAujNKK1pv2+GDMH6epupl2OkKye1koaooc1laqcmiOOHUnnKE6xLwVnO6BY+Zi4bRoc8Jpb\nFGq3nBEAUw3AyBSdoLOBFEp5Eb0n5d7LFMoKpMnKY+u1sYn9vaMx8Z4/9XlwxwsTeHC7aMC8M5Fo\nsP563xx2DvuL09EyJJ1xmotjx44VtM1shmc5OZBKjdRjIdUuy1eduCyMUoFRpu6UHErhKu/q6ir6\nNpVmqa6qLDM887KdnZ359SNjm6nfpxVXYnlAl34ypCwp0vUq676w1AI1mXN+Ozo6lsU1T6EsawgB\n7C2Aq6PUPaEsM3p6ekrdhbQoOf6b8IZxZCqIOX8E/7VjDgfGY4aoJi5VNRAWsGW/B3f/tfB6lRRK\nlEOHDmFwcLDgduQa6GoZ+2WRU8px0pPMS0m6B5mgtQJeX9qc0uTlmTQFmdMR1DnA+2LFZ+NPsNRk\n/0qZAcqmpicw4nUR0DnB+6UVDQ7qnOACBYRZRM9ZPvmeFXLMlSH3tWyhtUwplMpAn15sjkJZjhgM\nBtm1MZP5j0tduPlP4xieD+Nrz06gKqnmaYOZxYmZELbsn8cbAz602GLD7Tl/BFqOQMOuzMghv9+P\niYmJhO/m5+eL3o9KGSdnY3Z2VpHQ4v5+edU64uvQKklZeEqdTmepu7CEX1+de6E4IryoPhuJD33K\nNoMgoc2gzpXxt/b2dqldA5BqGAf0VbLWT2bJU6qC506vTzQEo8c2pHPCa20XS64AGRVrq6urIBQa\ngkZYROxtoudAAUr20CuxBDuFQllGdHaKHwolD5ajiEuNicNptVpsHxLDcUcXwim/H50O4df75nFs\nJoQXj8fEfj7+h1Hc+uwE5gIRXLNlGM8eWVm5p16vN0UY6Z133ilqH9KJJ1USCwsLitYHlWvYZsvp\nrfiSMISk74bcB5kSF1g4Kb81U7mSKBGdDQuWNggS8xN95hb4DbUp32ff18Ie6IQhYFjxGAsS1Wwz\nEfXU5qoXlo9xWF0dmxBIeyZZTiyjYm1K+Fqj1aC+oR52u0Kz/RoTwKT33lfyQ0wOy3EQQaFQ8uTh\nh8UPhVKhqPHubralH09du9oIqy778Lp/NoSP/34UAJZyUNUgWsKDIo1KqQN/4MAB7Nu3r+jbTTc2\nVLJcTs6jTwh5hBAySgjZG/fd3YSQ3YSQnYSQvxBClK89Im5IlWblEGGzG1+EkKxlS9ra2xL+FlgN\nwhp5ZVQKfZh2d3WhrbUt94ISsFmt6OnphkaT3eiMODuxYF2V9gL2mprSrAEwGSYnEuD1QNJDo7am\nFlqNBhwr1+DO//oihGDNmjVYs0ZmHdV8qDpF/W0ksVKMbwqFohwulwtWqzVhgpGycom+/zmuLDLF\nFGd9der48JErq/B3q02wauUZN/+5TR311T179qjSbqUgN/cxes3SMVB6pERLJodmy0HKXfNTAJck\nfXePIAhrBUFYD+AJAHfm3QMAJMPMRCV4a3L1UasRRZz8+mpRrbTEyLrNCGIeQ22SIZ3L40qYWLht\nch84HQQpBmjOzpUWrVYreoyX1CtTj4lm8fxbbQWIKnEyhMAKvGcq4Z6jUChF5qabxE8OOI7DqlWr\nwPNUyZcipuQ0NjaitbW11F1RhdVuDT6zyYI7z7XDomXQ6eBh1TIghMAe5yndVKtFm43DL66uwvkt\nenzj7FRtkOeOehGMUEOomNDxTv6odexyTl8JgvAyIaQl6bv4WAMjVCo0WshEBccrPzOX7iRYLJaU\n+kLR2qB2uwPRQxPWWkW1UgzCapVnoIQjEdkmmOzcz0zLERaoWg2wSYaRpV5mjzJttvALWyh1nVtC\nxJBirSnlJ57n0dXVVTEPv0yzg06nMy85dwqFsgw4eLDUPaCUIdlqFUapqipMx6LcuajNAAD4nysT\n93NjrRb/vXMOHQ4e3zg7llp08+ni+O8XV1fhY78bhYkn8IUFhCLAz3fN4ZPrzRUzXqh0lMzJXElE\nIhFMT0sTH5VL3pYbIeS7AP4ewAyA8wrphFI3ILuYN+mucsNhd0BulH4kydPFcRxyVZRyu93weDyY\nnIyp5Wp4Hj093aJ30Z/Yi40bN8rslfiwl3uEojmfFosFiBSmMgcuewizGlSKIvMSxsxiXelUl8vd\nk5B8T7a0tIj/GT1QWMM6m3hPKFYjlkKhUCilplThjjzPw+FwYGRkRPI6xTD6akwctnyoGkyGbRl4\nBjefZsGp1VpMecO47flJPNW3gAvb9Giylvf4YLlQCsXf5YCSOaTJ5B1DKQjC7YIgNAJ4FMAXMi1H\nCLmJELKNELItc2vKPCDcbjfcVW44HU7J5VeiCITAZ04MMWlobEhZLpCkjEsIkWVgEELSPhCzPSTb\n2uTng2q1Wqxdu3ZF5PZUYuy/yZTqVV0RGBxA7fqSTHRQKBQKRR2UfA/nElJMpqGhAatWrVJs+0qR\nySCNcn6rAW4DC6c+Ngl/y1/yz8ejSCdb5Fc4HMahQ4eK2BvpqGkQlgNKyEw9CuCaTD8KgvCwIAin\nCYJwWqZllJq1YggDl9OZZ1odAQhBY2Pj0jd6nS7hbwAI6RyFdTIPkkulSIXn+fIIA4nW/MyRR1pw\nX8thXwtEbmi3Wqhq6C+D80ShrHSi4jXLVcSGIg8l3xldXV2oq1NHP7McsSUp9f7tJA0rVYp8vKEz\nMzNlq1q8f//+UndBVfIySgkhHXF/XgWgN98OGIyGjEJHuYwYd5U7380inXd2zZo1quQ/tLS2VFSi\nv6C00WBvBVyd6cus5LutuNXkvAzNZnPM85zHttU01jZu3JhYh1ZrUW1bmSiLSQwKhVJerF8vfuJw\nOp1obm5eEdE4lNwo+W7keV7xaKJyjqhiGYJ/v9SF02pFD/EPX5vGGwPUMFWCw4cPl7oLiuL350oq\nVBe176OcU5yEkF8B2AzARQgZAPAtAJcRQroARAAcB/BZtTpod9gxNTmV8n1bexs0vAZjo2MAAJ+x\nMOEdlmVlh4xEiQ7kMw3o9Tod9I7ie1gTkGhrhDRmCIQD70895nnDMIDGqFx7BdCpUAH47MZbfjdt\nSpuOtsLUvvKgnF/cFAqlRNx/f8pXhBC4XK40C1NWIvTdURi1Jg7/sNGCbU+KY9p7Xp/G1mtLX7Fh\nJUIn57Oj5r0uRX33w2m+/m+lOhDhDCBZPKIGvQFTSDWQtBoNoIuFOkb4JKOH5C+Uo9Pp0oZRZrpQ\na2pqIAgC3O5CPLfZKN4NEuaMYMKlnYlRjEp/sBBSsn2gD2UKpTzR6/WYmppaKjdFoZQDlWSUluv7\nzWVIHLfOBSIwa5TIsqNQKoMyuNpVeDgY3UD1KTK7EetHa2sLHA57xkWTYVkWDQ0NYDKFIUvavLj9\nEL+yBHAUeTlUzruwiBR2UFQbYJTpYIBCqRRqamrQ3d1dXLG0G24QPxRKBtR6Z1SSsasEFk3sHfn5\np8Zo7dIiU64TFiuFMjBKkXWgKvBZRH70McNRDMtcvHkZLn3+olxq1ua5Yn4PkQVbJwLG0if322w2\n6HQ6mM3mom43/jKora2FRqORJKKRb9h1Jir6JRi9X/LMR6UPZAqlvCGELNXCLhoDA+KHQikSct9F\ny+Xd9a33OnDz6eL7eyEo4PqtI9h6QPnSJf6QgBn/8lZypVQeJZfNy1QiJYpgdAPoS/2hbkPCn2az\nGfAJAEYk5S9KeoApYdhWIFqtFtWtLSXtg9lkxqmdp+Zcrru7mzrf4uH14mRKntduRRvkFAqFQika\n0feF2+1WMX1pZdFi49Fi4zHvF/Cz3WLZkl/uncf+sQAubjfApmPQ6Sw8dP97r0xh71gAv7i6Cga+\nPPxT5cJymeBQA7XHiMvrStRZxAG5VrqHT0jn1eQNCnZKAZhizh1UilESFZdSoeVKfyApMJlS8ceA\nsnKIXqvl9tymUFYIDQ0NeZeuKxaVNuF6ZZcRN58Wi3jaORLAD1+bxm3PT+LAuLRyJdmUWveOiW18\n/TlaFzWeUCiEkZGRUncjK+FwuNRdUI2yM0oDhni1sTweInIH5Ok24ewAqtfI37ZaWDIrCwtFFEFS\nC6PRCIu1+OVPMuUzZ3t5VdqLjUJZ9jCsWHLK3lLqnlAoFIpinN9qwGc3pY6N3h6SJkYppdYmz4jj\noLcGfbj75Um8csKLSNI459V+L+5+eRLB8MoY/+RT27SYHDp0qNRdUI2Sh+8m03HKOhx/axhACQ0A\nhkHUXk/uQ2NjIyamD5agPxkoU5tUzrnr7u4GBr0KbLV4ByNfT6JOpwOAoufryoUa35SKokxKTi1b\n3v3uUveAQsnKclWjfl+rHi4DC6eegV3P4pO/HwUjcfjBsumdNL1xntbjMyFcs2V46e+dIwHc9+YM\nHvtQNVhCEAgLuPeNGQDA9b8ZoWVqygCPx1PqLqhG2XlK5Q72bc2nQO9qKHy7GQyaqIiObjE0paqq\nquBtKYm7YRWCWulKwdJQziCRfD5NNQnCVUUnLvRPzdBVg8GAtWvXrrz6fnJD0GvWAtW5c4opFEoR\n+P73xQ+FkidqT3TqdDp0dXVJWraS0lMIIdhQo0WTlYdZw8CgIXj8gAf/9Mw4huZDOddNx+/eyW3U\nXPf4CPpnQ3hk52zGZf5yZAH/5/WpFM8qZfmyb98+zM3NqdZ+2RilVdVVaGlpkbSszxJbrnbVWrSs\nO0edTgEwm0xobWuF0+FQbRuFoNFqEdTnFhjI/RCO/S4UMTdrqV+WWsDaJGdN5Tphqga4mIJvoS/P\nVe3tqK2rzfg7z/Nl/1JUvH+uTsDaKH15hgXYsgvkoFAoFEqZUu55rUrg0Ivez6PTIbx4LL8IMyMv\nvt/vOCfREdBuT3znfuXP43jmiLiNyzvEcWHfZHDp94e2z+L1AT/GF6iK70pifHxctbbLZtTndDgA\njRlSbrHVq2XWIE2DnFxMnVa7ouorClorwISBsLRk+sIo4XE1OAHfDGBQ1mtpsTkAv1WW4Nayh9Mm\nGP4UCqWCuOYa8d+tW0vbD0pZodfrsbCwUOpuLJEuXLW5uRnHjx8vQW/U4ZYzrbjlL6I40eMHPDi7\nSY9Gi/Sh/Kv9Xrx43IcqA4sNNdqlcNxwRADLEAiCgO+/Oo3tcXmrd5xjR6OFw5OHFvCb3nnsHQ3g\nM3G5rn894cU1PUWsm1xEOI5DOBymKU1FovSe0qixV30q4GgrwebF7ev0uqJvuxCI1KSCfGGXZ35G\nAiwHuDsBLnFfC/YSsjxQtTqrQBWFQqFUDBMT4odC9NBHOwAAIABJREFUiaOjowMdHR1gsulelBC9\nXl/8mr4q02BJ9Wb+tncenmBub+WUN7yUH+pLEi1imWhFA4JvnG1Ht5MHANzzPic21Ghh14vn+M2T\nfniCsTxTAJgPLF9Pafy1fe8b07jxd+WtzFsM1DTQy8ZTWqpQPZZj0dzcDK1ZwXxGrQUwusWw0JG9\nijTpN9SACfuW/m5rbYPX50UxfJmlpru7G16vEkJI0lBEfZd6BSkUCoWyjOE4DhZLKZTzVy4MIfjI\nGhN+uTemEPu/e+axY9iPuzY7s657YjaWg5ocupvMN862Y9ofQb1ZHJuzGSbrq4wsRj3Lt0RJPK/2\n+3IvRCmI8pzeSoPeoFKuAMPBUL8arKtDuTYJAawNix6zUwB3d8FNhjUWBPUxkSWNhodVwZdBiBdD\nTSPs4nGOCtMQtS4R6d5Io9GYXRioqHVcRco9J5RCoVAolHIj+d1pt5dQ4LBCuabHhBvXJqYH7RsL\n5pw0v+vlKQDAz6+uQrudz7qsUcMsGaRR/vsKN+rNLFa7Yus2WznsH1ve7pHk46qmp/CZIwv49B9H\n8YNXp+Av0xI8au5/UY1SlmVhs9nyXjcKUTpURG9Tz1PLaQC+/JPvjY4aLNg6IUTDdm1NgK0Z0FRA\nQXpjqtBTU7Mc0aREqMFJoVAoFIr6tLa2Yv369aq1n+59rsY7vtglaa7sMmLrtTX41Qerl7773FNj\nktY18vmNoW06Fg9c4sZdm2PCn11OHrMBARMLy9NbGggEcGImiDteiKUveILqGWU/3j6LKV8Ebw36\n8ZU/j6+4XNaiGqW83gRTfeFew+VKMWcMa2prYmrHJM1DmmEBQ5EVh2W8KHIJVel1+U8ErLSHAIVC\noWTlggvED4WSJ9Ea3dF/oxBCMtbTrCRKVXtcwxL86EIxbHdsIYJAnHctOpYJCwJ+uVcs4/HRNYUL\nEhFCcOt7bPjiGVboFw3cO16cLLjdckQQBNzylwkcGI+pDvfPhiAIAn7y9izueGECwzlK80hh1h/B\nwGxiO6OeMF7IU2G5Uilu+C5hIdBcu4y0tRVP6Mlus4HXZA/fKAbJxrBOp0NNTe7izGFe3oM1oHcj\noM9eY5Z6SCkUCiUN3/ym+KFQ8sRut6O7uxuOMi2vV8m02Hhc3C5OxMfXLv3xX4/hmi3DuO7xEWw9\nINYm3VirzBj8zHodNjfrYdaI46ZoXmk4EvOa9o4H8Jcj5aPOHI8gCBicSzUmtx6YR+94LBx5JE2+\n7B0vTOLodAhPH17AgfEgtuyfT1lGLp/4wyi+/Gex1MqHTzFhc7M4eXN4qnCDNxgRlvZJEAQ8uG0G\n+woIuV424buU0pHL4CoXg6y1tQV2u4QQb4ZFJFkhOMs+hLR2hLT5hY4XxmKf+GWiAEi9yBQKhULJ\nA6PRWPSxRrmMbdTmwjYx1SrqbfOFInjghaMpy7XYlHVGvLsh5vl+6bgX120dwU1PjuHX++Zw+wuT\neGj7rOS2AmGhKJFqe0f9+PgfRvHFp8dxcCJmnAUjAn65dx63vxDz+k56RWXhKkOiN/9rz8bCeXeO\nFJZTm5w76tAzuPl0Kxx6Bu9MFJ6v+9D2Wdz+wiRGPSH89h0Pnj3qxV0vp/ds7xrx45otw4p4f/Oh\nvI1SQX2Zaek3wMp4sAEr5yGeD7IfmCwH2FtKUu6IQqFQFOHSS8UPhVJBcFz5FJhQmzqTuK/3vjGD\nHcN+fPOFVKPDplN+yM8QgjPrRe/rA3+LlYnZst+z9H9vMIITM0Fcs2U4o4dOEAR86o+j+MGr0/j1\nvjn84NUp1QzUb700hfmA2PZtz8eOU7yH9MiUGK67e1Ss1/rPZ9uw9dqahHxaADirUQdfUo7pXCAC\nb0i6/fJskje5zc6DIQQcQ3B0OoQHt81kWDM34YiwFAI8vhDB7kUDWpOhrOQzi33ZPx7Ak4c8afeD\nekpVoFztLimhq5TSI8tw19tLVvJIccr1xqFQKOrh9YofCqWCaG1tXTGT7FqOwMSL+/qdv07hyLTo\n6bqk3YBffqAad2924LvnqRM6fXVX9kiwCW8EP90l5rTe+eIkfvL2LK7ZMowdw37M+EUDbiEoYCEo\nYNuQH1v2e/DWoB97xwIY9YQkl5w5Nh1EMCLg6HQQ//a3aYQj0oynqCH2x4Mx4/AHr4pKxQcnROM0\nqkTc40r0NDdZOfjCAh7fPw9BEDDrj+Djvx/Ft1+cwvPHFhCU0Ie3Bv0Jf9cv1qL98hlWAMCzR724\n/81p2cbghDeM67bG6qr+8NUpcItW30JIwJw/ZnAGwwLCEQHvLObOPn/Ui0d2zuHRPYWHJsuh5CNl\nqQ+MCG8CoMLBKbNwxPr6etTX1+PAcwclLW+z2TA4NKxyr9Shrr4u7xdGa2sr2MnlqfZW1pTZ/UKh\nUCgUSjJWqxU8zyMQKE65knIQSHzgUjc++YfRhO8+ssYELUew2q2eOnB8eZnbz7bj8FQQU74wzBoG\njx/wLOVKRnn6sGj8feevouFn5Al8odTj9+2Xppb+v/Xa7A6bgxMB3Pb8JK7sNOAPi8bllV1GNFsT\njchkMSFAVLw9q1GHgxMBbKrVYvuQHz0uDSKCgD2j4nfcomeRIQQ/vMCJrz83gc3NOqxa3Pdf7ZtH\nWBDw2KKHuG8qiL63gviPt2bx6w9Wg2fTj3UFQcDhySD0HIF38Rjwi9vqdmmwrlqDXSMB/PWEDx9Z\nY0KVUbrZNjyfOEaeDwrYMRwAxwChCPCLPXP4/GlWBCMCPv/UGKpNLCZ9oqEaFXb6U98Cblxrzth/\npSm6p3SlzFoVC57XYN26daXuRgrR88xkKd8j1lnN73pwOByK1mmlUCgUCoWy/FFjHFoORqlVy+Ce\n9zmX/v7MJguMGvWH+SxD8NFTTehw8NhYq8W1q024aaMV159iQo0xt7KyJyggV0nObOGwgiAsheH+\nIc7b+dW/TGDKm2iY/W3QBwC49yInHvtQNS5bJebifux3o5gLCNjcrMe6ag32jAbwzBEvIgLgTson\nXeXgsfXaGnzxDFuCsf9YXMhyPNf/ZgTBsICIkKiMfO8b03j+mBcLIQEf7E7vbb50Vaws4+GpEHrH\nA5Kvtdf6fUv/j7cp11WL4dbPHfViz6gfr/X7MOmLJCgMxzOWVO4n2/YFQcDjB+axe8SfcZlsrNjw\nXYq6WK1W1NbWorGxUfpKCr4o6OQHhUKhUCgrm2KNBcrBKAWARkvMk2YugkEa5YPdJvzgAmfCd4QQ\nnNUkCiH1uHg8dk017rvIia++y5rWCDPyYqmZ+H2IMjiXGhnnDUbw4LYZ9E2lN6YA4EdvTKN/NoQJ\nbxjHZ4J4dM88akwsmq08WEJwTU9iP3rcPNZWaTDjj+Dht0WRpmy5uBpW9Jzm4vrfjOD+N8Xc0HBE\nwKQ3glf7ffjPbeI2Gq0cHn6/Gw9e5kpY7/Q6Hf7vxeJ3v+0VRZg+9PgIpLBnMR+208Hjp1fFqk90\nO2Pe42+/NJWQCxzPHeeIZSqTjdJMHJkK4o2Tfvxq7zz+5eWp3CukoeThu6UiojEDmACSFVyT4RaV\nxbSlqUGlJmo+rAkhqKurU619CoVCoRSJ97+/1D2gUMqacjFKeZbg3y5x4ee757ChRr2QXalc2GbA\n4ckgPthjAssQNFl5NFl5vKtBwG96Ez2LD17uhpFncGa9Ds8fW8ArJ3xYW6XBL/bMY2A2lBAmDAA3\n/E4MVZ7wphpNH11jwqN75+ELCfhKUviwSx/zfNp0LJqsHE7MiGG9Ni2T4l3WctnHyqscPNrtHA5P\nhbCuWoMbTjUvqfPecqYV9y0ao6/2+zA4N46j0yFc2KZPaGN9tTZjiGyDhYNZQxLKw8z6I7BoMxvL\n+8YCODkXxqWrDPj0BjGq8KHL3fivHbO4eJUBjVYOP3h1OmGdC1r12NysxzcXa85G82jHPLk9peGI\nkKBInC8r1ihlLTWYCbJgtYbsC2oMQM1agCnv4s56gx5Wi7XU3VAO6umkUCiU8uCf/qnUPaAsc1pa\nWqDX63MvWKaUi1EKAHVmDv98lr3U3QAghr5+89xUgSWWEFy2yoDnjnrhDwu44xw7jHzMyDq/xYDz\nWwwIRgQ8unce+8cCOKNOCz2faohFy7Z89zzHUjmXD/aY0DsRxPah1DDSW96VOFa+7yIXrtkiarMQ\nQnBaXC3Xc9ttuGxV7tqut51tx72vT+PqLiPa7DzueZ8TNl3UwI15Io8uClA9cyRROC5XzmaVkcVc\nIGaUHhgP4Mx6XcblDywqCcd7gl0Gdum6iBqcUc5v0ePzp4nH5b6LnOBZBk49A4YAo0meUr8/9Zim\nq+eaD5VjlMYZKYQUHpLQ1NQEm80GgyGHUQpkNEjDnIR1i0RLc3PW38myLGlT/JdAOb14KBQKhUJZ\nDjiduUMg82Glhe9WEp/aYMGnNlggCELG88QzBBFBVKB99qgX159iwrWrTQAALUvgDws4vujlbHfw\nuGmjBYZFFeI1bk1ao9Smy+5ksutZnN+ix/PHvPjO5e0YGzqZc1/sOhZ3nxe7htvsmevBdjl5vDMR\nCzmukpB3yyWVcNk26E8xSr2hCPQcg8NTQfxq7/xSv9JRZ+bw2Ieqcd1iKPDxmVh/mqw8CCEQBAHV\nRhYn04hDJbNjOPE4O3QMjudcK5UVm1PKsizs9vxmkoI6cdbHb2pQskuUvCm+wU1zVikUyoph82bx\nQ6GUAZFIYTXsiyl0pNGUPoS23Ml1Ps5qjBlff1lU7g1HBPjj1JHcBgY8Q3BxuwHnNIke98s7Y46j\n28/OPt7/2VVVCXmXn9lkwY8vd8OgKdx3F9//ejOL757ngEXLwKZj8L3zpZXq2dwSiyJosXKYCyTe\nA7/rnccNvx3F8ZkgbpUYRsvGHfdzm9JHKbTYOBybyW6U/uGgB4/snEOzNXasfnJFVZY1MlM5ntI8\nUMs7GNS5ENS5ci9YoeRrrFMoFAqFQqGoSbxRWi4TxBaLBfPzxa3puFL48plWfHaTBf/2txnsHwtg\ncC6En+8W655+ZqMFQ/MhXLfoPY2HJQT/fYUbAgADz0DHkYwqt6akPFKOISmqu/nyxTOsuPl0Kw5P\nBtFo4UAIwUOXuyEIufNVo1zUZkDfZBDNVg5vDfqxa8SPhWAEBp5BRBDwi8V6ok/EqQ/ftTm3sVtt\nZDHiCePyjsTIz6intNHC4fUBPz7x+xE8cmVV2vvtZ4s1aLtdPE6v08KQJsRaKiU3SrMGPAgCBI0F\nQY0VIWMNMDEkq22L1YKA24XxsfHcC8tg9erV2L9/v6JtFoy9VZFm2tvbodXmjp+nUCgUCoVCKTZR\no5QQgo6OjqzLphtEq2HI8nzmcE1KYbCEwMATdDl5/G3Qjy8+HRvTr3ZrcFF75lS6+FDdX1xdBaYE\nkxjRuqPx5WM0edT9jOZ87hj24/+3d+8xcp3nfcd/z1x2Zi8ze53ZC/fKJXe5XHGz9KpBHDuAY7iG\n6lpxGvgSIw0i1IhcpwVswG7guAbaBLHbIrXroGnsCI4hI0gdG3bd2GmKRIllqGmctHIsxVJlyZFN\n2ZJDUTRFUhQlkrt8+8fMLIfLuZ45Z845M98PMNid2Zlznp05uzjPed73ea/uSR/9q/P64E9M6Be/\n/Nz+c75yqjRX9X2vHNNmC2vT/rvXTuji1frDp+fKc08vXnV6adftD42u2Lt+I4t7x3ZeyURn72/0\nh++a6drQtJRo/w/eMnkVZtpYkqRFYUzGbzr3dXCsdAtauhxHs67FAAAAPksmS4nG8vKystn6zV6k\n2mulR6W6ivbcVry1YDI70no1M4yENEjfOH1VZ17c1fkrpYs0J4o3zsurh9I2MppN1lyCp/I3Ut0Q\n6eKVW4fNV4ZQ37E61HFCKkU8Ke144ngiKRWP+RNMyI4dO6aTJ0+GHYY0UpCm1qXMrUMluo7GAuHp\nsX/uAIB4mJmZ0fLycktTjWoloPPz9AOJo9Xxm5OnXzzZeWUujn56vTQEOWnS3565uv94pZL6+sOD\n+xXOTs3mbiT9B+exSjeS0sUWk+BmQh++i9aYWXSu7g342XU4mMQyKm8VAMTeW98adgToU7WKE4lE\noqNuvakUp75xZGb7XXE//+bp6JwTd9ltxYzufkVe9/zNRX38wYtKJ6R731RUNpXQF94y4+u+BlMJ\n/atXjuk3vnZeL1y59W/xym7psYyH4ci18Jfp0ebmpnZ3m7dJjgoXwvIpvajv274nUtLerS3WAfSw\nX/qlsCMAIq1RgrS5uanHH3+84Tnj4cOH9Z3vfCeI0HrKu27P6507+b5NSCuql5HJJE3ZVHADX1fK\nFeoP/cXzGkqbPnlncT8JfeaF0jHdasOmZiI9fDfKstmsRkYiMIS1RQlLyBKm68nG8y/Qmr79hzix\nIo0uSCmaYQF94/Ll0g2IKT8bOG5ubqpQKNz0WKML1tlstuncV1Y9aE3C7JY1O/tRdWfgRADvR/U5\nbrFqX5evOT3w1Ev79z/8F+clSVND/qSTkU9KK8MsWOupM2bSsZ/82VKlq9f0a4IYhmRaGu7d5ZAA\n1PCGN5RuQJf4eeF3a2tLGxsbvm2vlelUZqZkMsn8VQRipqrB05vWay9z4xcz0ztfkd+//4mvX9TT\nF3f1xW/dWAJpedSf7tOhZSjOkjK3p+vpxtXGXC6n1dVV5fN5Pf5E6bG+rVJ5NTIjWY0OdAGt4xpF\nJ06c8OW4KRaLunr1qmZm/B23DwAA/FdruZa1tTU98cQTvu3j4PlFIpHQ9va2b9sHqqUSpj/4mWld\nb2Ot0068fnVI44MJ/fv/XaqMvvtPbizL8/5XjSkd1zml6VTpn0NqcFgvpKY0MNh8cdexsQNLnZCU\ntic/G3YEAWl9fqdflfZkMqmlpSVftgUAALovl8uFHQLQEb8SwVpqFXFeMZvRieKAvlnV8VeS/sGc\nf9MCuz58Nzs4qJXDK1paWZUSqY46qAE34WIFAAAIUCujrg7OMWWEH+Iuaaa7q4bxSlLa5yyy+8N3\nB4aVLR6RBse1M9P6oreoo81/dFtbW6V/jme+GVBALeL/MwAACEDQSWC72ycpRS+Yy6U0PZzUsy/u\nSZJ+9TXNR7u2I5xGR8NTUoKENAzpdLrUPCo9LI0eCjscAEDU3XVX6QZE3MSEvyfJkmr2kJiZmdHU\nFE3/Dhoa8nMde0TRB15d6hT9a6+Z0Pqkv01oI92Kte/XhAxSYU3ai886qwCAkJCQIibGxsZ07tw5\n37aXy+U0Pj6u06dP3/R4KpXS0tKSzp49e9Pjo6OjunDhwi3boVKKOGl0vM7nU/rCW4Jp9hn5JWEA\nAECIzp4t3QB4EtWkNKpxoT+RlPax2Fei9+PnnyoABObNby7dAPSU4eFg17jsBZlMpqPXHzrEVLlW\nRXr4bj9bW19rnDRaQnLXfdlXt6+Ura+v66XT5X3WWD9VkpT39ke8urqqF574gafXVtYySyaZ7wwA\nQD84evSovv3tb7f8fC/nTFGtSEY1rl4Sx8Q/rOOCpDSikokmReypNenli90JxmcjIyMaWT0p7V2r\n3/Bq2FsDgbGxMY3Nz3t67cLCgnK5HOuXAQDQJ/L5fPMnhWRxcVHf+973wg4jFqampm6Z44t4Yfhu\nXKUHpdx02FF4ZyalfOralSxfW0l1toBvIpEIpHMfAADoX3GuSGaznZ1bdcvY2FjYITDSTuqoK3Ws\nKqVOpdmDcf7jjpLK+5hOpxXr2aUDI9LEqpShwgkAAJrb3NzU1atXGz7Hr/PNbiZ26XRa165d83V7\nL7/8sm/bQ28bHh72XLGOVVIKfyUSSR06dEiDQ4O6ODyuCxcuxOaKWElVKp2N7vAbAIi1d70r7AgA\n32Wz2YbnPDMzMyoWi74keDMzM7p48aIuXbrU8baamZ+f13e/+92WnttK0h2XQlA3mnfOl6eHPf30\n04HvK0zMKW1LPP5A4iCfL1UXJycnNT4+rkSzuawAgP7ytreFHQHQdZWuqdev39xU0mujo3w+f1NS\n6ndFMyicF96QTqc1MTFRNynNZDK6fPlyl6PqHdE70uK+TEmMxfcfDxcpACAw3/9+6Qb0oUwmo/X1\ndd+3OzDgU1+NDvRSpTQK5ms02uT9a13EsxASVAAAQvXzP1+6AX1qZGTE9wv3XoebTk5OanNz05cY\nKgnTyspK3eeMj4/7sq+gdWP4brMEM77FnZuFlUhH793jigIAAAD6XK3kYHR0VNlsVplMpunrFxYW\n2t5+tWKx2NcdZbuR6OKG6CWlVTgYAAAAgPY1SyorSenB8+3Keu3tnoeHed4ehUqp1wpjOp3en8Pc\nz6KXlDY4qBiXjZtw0QIAAPhsbm4u7BCaanZOPDIy0vI2DjZzqkaBKHhbW1uamZkJO4zQNU1KzexT\nZnbGzB6peuw3zOxbZva3ZvZFMwt/xVoAAACgQ7Ozs7c8VknO4lIgaWXYbb3fpdKEqZUhwog2L/Nc\nozyn9F5Jdxx47D5JtznntiQ9IelXfIsoJn/siBCOGQAIznvfW7oB6Cn1hu+OjY1pbW1NxWKx5W1t\nbGx4imF0dNTT66rNzs52VNHd2dlp6XmVYc1+mpiY8H2b1eJQ9a9ompQ65x6QdO7AY3/qnNst3/0r\nSbf2QPaqhYMqLlep4BWfLwBExp13lm4AfBOFYbHT09MaGhqq2WE3l8u1fL6dSCQ0NDTkKYZUKuXp\ndQf33w3Nqs9e8pNGnY8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- "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# filtered log-PSD\n", - "plt.plot(j.freqs_THz, j.logpsd, '0.8')\n", - "plt.plot(jf.freqs_THz, jf.logpsd, c=c[1], alpha=0.2)\n", - "plt.plot(j.freqs_THz, j.flogpsd, c=c[0], label='original')\n", - "plt.plot(jf.freqs_THz, jf.flogpsd, c=c[1], label='resampled')\n", - "plt.plot(jf.freqs_THz, jf.dct.logpsd, c=c[2], lw=2, label='filtered')\n", - "plt.axvline(x = jf.Nyquist_f_THz, ls='--', c='r')\n", - "plt.xlim([0., 50.])\n", - "plt.ylim([11., 19.])\n", - "plt.xlabel(r'$f$ [THz]')\n", - "plt.legend();" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 2", - "language": "python", - "name": "python2" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.12" - }, - "widgets": { - "state": {}, - "version": "1.1.2" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/thermocepstrum/example/Silica.dat b/thermocepstrum/examples/data/Silica.dat similarity index 100% rename from thermocepstrum/example/Silica.dat rename to thermocepstrum/examples/data/Silica.dat diff --git a/thermocepstrum/examples/example_cepstrum_singlecomp_silica.ipynb b/thermocepstrum/examples/example_cepstrum_singlecomp_silica.ipynb new file mode 100644 index 0000000..1c8d124 --- /dev/null +++ b/thermocepstrum/examples/example_cepstrum_singlecomp_silica.ipynb @@ -0,0 +1,7578 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Example 1: Cepstral Analysis of solid amorphous Silica\n", + "This example shows the basic usage of *thermocepstrum* to compute the thermal conductivity of a classical MD simulation of a-SiO$_2$." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import scipy as sp\n", + "import matplotlib.pyplot as plt\n", + "from sys import path\n", + "path.append('../..')\n", + "import thermocepstrum as tc\n", + "\n", + "c = plt.rcParams['axes.prop_cycle'].by_key()['color']" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib notebook" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Load trajectory\n", + "Read the heat current from a simple column-formatted file. The desired columns are selected based on their header (e.g. with LAMMPS format).\n", + "\n", + "For other input formats see corresponding the example." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "# Solid Silica - BKS potential, melted and quenched\n", + "# 216 atoms, T~1000K, dens~2.295g/cm^3\n", + "# NVE, dt = 1.0 fs, 50 ns, output_step = 1.0 fs\n", + "# Temperature = 1065.705630 K, Volume = 3130.431110818 A^3\n", + "# LAMMPS metal units\n", + "c_flux1[1] c_flux1[2] c_flux1[3]\n", + " #####################################\n", + " all_ckeys = {'flux1': array([0, 1, 2])}\n", + " #####################################\n", + "Data length = 100001\n" + ] + } + ], + "source": [ + "jfile = tc.i_o.TableFile('./data/Silica.dat', group_vectors=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ckey = {'flux1': array([0, 1, 2])}\n", + " step = 100000 - 100.00% completed\n", + " ( 100000 ) steps read.\n", + "DONE. Elapsed time: 0.46349811554 seconds\n" + ] + }, + { + "data": { + "text/plain": [ + "{'flux1': array([[ 91.472925, 630.61992 , 199.16002 ],\n", + " [ 71.403952, 666.80601 , 274.30247 ],\n", + " [ 47.754737, 678.10914 , 305.95706 ],\n", + " ...,\n", + " [ 466.489 , -360.14259 , -47.286976],\n", + " [ 414.3014 , -378.42595 , 166.42152 ],\n", + " [ 331.99113 , -400.35311 , 378.13009 ]])}" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jfile.read_datalines(start_step=0, NSTEPS=0, select_ckeys=['flux1'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Heat Current\n", + "Define a **HeatCurrent** from the trajectory, with the correct parameters." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "DT_FS = 1.0 # time step [fs]\n", + "TEMPERATURE = 1065.705630 # temperature [K]\n", + "VOLUME = 3130.431110818 # volume [A^3]\n", + "\n", + "j = tc.HeatCurrent(jfile.data['flux1'], 'metal', DT_FS, TEMPERATURE, VOLUME)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "500.0\n" + ] + } + ], + "source": [ + "# Periodogram with given filtering window width\n", + "ax = j.plot_periodogram(PSD_FILTER_W=0.5, kappa_units=True)\n", + "print j.Nyquist_f_THz\n", + "plt.xlim([0, 50])\n", + "ax[1].set_ylim([12, 18]);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3. Resampling\n", + "If the Nyquist frequency is very high (i.e. the sampling time is small), such that the log-spectrum goes to low values, you may want resample your time series to obtain a maximum frequency $f^*$.\n", + "Before performing that operation, the time series is automatically filtered to reduce the amount of aliasing introduced. Ideally you do not want to go too low in $f^*$. In an intermediate region the results should not change. \n", + "\n", + "To perform resampling you can choose the resampling frequency $f^*$ or the resampling step (TSKIP). If you choose $f^*$, the code will try to choose the closest value allowed.\n", + "The resulting PSD is visualized to ensure that the low-frequency region is not affected. " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = jf.plot_periodogram(PSD_FILTER_W=0.1)\n", + "ax[1].set_ylim([12, 18]);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4. Cepstral Analysis\n", + "Perform Cepstral Analysis. The code will:\n", + " 1. the parameters describing the theoretical distribution of the PSD are computed\n", + " 2. the Cepstral coefficients are computed by Fourier transforming the log(PSD)\n", + " 3. the Akaike Information Criterion is applied\n", + " 4. the resulting $\\kappa$ is returned" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-----------------------------------------------------\n", + " CEPSTRAL ANALYSIS\n", + "-----------------------------------------------------\n", + " AIC_Kmin = 37 (P* = 38, corr_factor = 1.000000)\n", + " L_0* = 13.395456 +/- 0.103277\n", + " S_0* = 950203.538450 +/- 98134.481881\n", + "-----------------------------------------------------\n", + " kappa* = 2.484534 +/- 0.256596 W/mK\n", + "-----------------------------------------------------\n", + "\n" + ] + } + ], + "source": [ + "jf.cepstral_analysis()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "c_k = [ 1.52991432e+01 -6.79075038e-01 -1.52991190e-01 ... -7.74510541e-03\n", + " 7.38870817e-03 8.29678141e-03]\n" + ] + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "K of AIC_min = 37\n", + "AIC_min = 2820.804281\n" + ] + } + ], + "source": [ + "# AIC function\n", + "f = plt.figure()\n", + "plt.plot(jf.dct.aic, '.-', c=c[0])\n", + "plt.xlim([0,200])\n", + "plt.ylim([2800, 3000]);\n", + "\n", + "print 'K of AIC_min = {:d}'.format(jf.dct.aic_Kmin)\n", + "print 'AIC_min = {:f}'.format(jf.dct.aic_min)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Plot the thermal conductivity $\\kappa$ as a function of the cutoff $P^*$" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('');\n", + " button.click(method_name, toolbar_event);\n", + " button.mouseover(tooltip, toolbar_mouse_event);\n", + " nav_element.append(button);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = $('');\n", + " nav_element.append(status_bar);\n", + " this.message = status_bar[0];\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = $('
');\n", + " var button = $('');\n", + " button.click(function (evt) { fig.handle_close(fig, {}); } );\n", + " button.mouseover('Stop Interaction', toolbar_mouse_event);\n", + " buttongrp.append(button);\n", + " var titlebar = this.root.find($('.ui-dialog-titlebar'));\n", + " titlebar.prepend(buttongrp);\n", + "}\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(el){\n", + " var fig = this\n", + " el.on(\"remove\", function(){\n", + "\tfig.close_ws(fig, {});\n", + " });\n", + "}\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(el){\n", + " // this is important to make the div 'focusable\n", + " el.attr('tabindex', 0)\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " }\n", + " else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._key_event_extra = function(event, name) {\n", + " var manager = IPython.notebook.keyboard_manager;\n", + " if (!manager)\n", + " manager = IPython.keyboard_manager;\n", + "\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which == 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "}\n", + "\n", + "mpl.figure.prototype.handle_save = function(fig, msg) {\n", + " fig.ondownload(fig, null);\n", + "}\n", + "\n", + "\n", + "mpl.find_output_cell = function(html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i=0; i= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] == html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "}\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel != null) {\n", + " IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "K of AIC_min = 37\n", + "AIC_min = 2820.804281\n" + ] + } + ], + "source": [ + "# kappa as a function of cutoff K\n", + "ax = jf.plot_kappa_Pstar()\n", + "ax.set_xlim([0,200])\n", + "ax.set_ylim([0, 5.0]);\n", + "\n", + "print 'K of AIC_min = {:d}'.format(jf.dct.aic_Kmin)\n", + "print 'AIC_min = {:f}'.format(jf.dct.aic_min)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Print the results :)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-----------------------------------------------------\n", + " CEPSTRAL ANALYSIS\n", + "-----------------------------------------------------\n", + " AIC_Kmin = 37 (P* = 38, corr_factor = 1.000000)\n", + " L_0* = 13.395456 +/- 0.103277\n", + " S_0* = 950203.538450 +/- 98134.481881\n", + "-----------------------------------------------------\n", + " kappa* = 2.484534 +/- 0.256596 W/mK\n", + "-----------------------------------------------------\n", + "\n" + ] + } + ], + "source": [ + "print jf.cepstral_log" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can now visualize the filtered PSD..." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "window.mpl = {};\n", + "\n", + "\n", + "mpl.get_websocket_type = function() {\n", + " if (typeof(WebSocket) !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof(MozWebSocket) !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert('Your browser does not have WebSocket support.' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.');\n", + " };\n", + "}\n", + "\n", + "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = (this.ws.binaryType != undefined);\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById(\"mpl-warnings\");\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent = (\n", + " \"This browser does not support binary websocket messages. \" +\n", + " \"Performance may be slow.\");\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = $('
');\n", + " this._root_extra_style(this.root)\n", + " this.root.attr('style', 'display: inline-block');\n", + "\n", + " $(parent_element).append(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n", + " fig.send_message(\"send_image_mode\", {});\n", + " if (mpl.ratio != 1) {\n", + " fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n", + " }\n", + " fig.send_message(\"refresh\", {});\n", + " }\n", + "\n", + " this.imageObj.onload = function() {\n", + " if (fig.image_mode == 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function() {\n", + " this.ws.close();\n", + " }\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "}\n", + "\n", + "mpl.figure.prototype._init_header = function() {\n", + " var titlebar = $(\n", + " '
');\n", + " var titletext = $(\n", + " '
');\n", + " titlebar.append(titletext)\n", + " this.root.append(titlebar);\n", + " this.header = titletext[0];\n", + "}\n", + "\n", + "\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "\n", + "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n", + "\n", + "}\n", + "\n", + "mpl.figure.prototype._init_canvas = function() {\n", + " var fig = this;\n", + "\n", + " var canvas_div = $('
');\n", + "\n", + " canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n", + "\n", + " function canvas_keyboard_event(event) {\n", + " return fig.key_event(event, event['data']);\n", + " }\n", + "\n", + " canvas_div.keydown('key_press', canvas_keyboard_event);\n", + " canvas_div.keyup('key_release', canvas_keyboard_event);\n", + " this.canvas_div = canvas_div\n", + " this._canvas_extra_style(canvas_div)\n", + " this.root.append(canvas_div);\n", + "\n", + " var canvas = $('');\n", + " canvas.addClass('mpl-canvas');\n", + " canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n", + "\n", + " this.canvas = canvas[0];\n", + " this.context = canvas[0].getContext(\"2d\");\n", + "\n", + " var backingStore = this.context.backingStorePixelRatio ||\n", + "\tthis.context.webkitBackingStorePixelRatio ||\n", + "\tthis.context.mozBackingStorePixelRatio ||\n", + "\tthis.context.msBackingStorePixelRatio ||\n", + "\tthis.context.oBackingStorePixelRatio ||\n", + "\tthis.context.backingStorePixelRatio || 1;\n", + "\n", + " mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband = $('');\n", + " rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n", + "\n", + " var pass_mouse_events = true;\n", + "\n", + " canvas_div.resizable({\n", + " start: function(event, ui) {\n", + " pass_mouse_events = false;\n", + " },\n", + " resize: function(event, ui) {\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " stop: function(event, ui) {\n", + " pass_mouse_events = true;\n", + " fig.request_resize(ui.size.width, ui.size.height);\n", + " },\n", + " });\n", + "\n", + " function mouse_event_fn(event) {\n", + " if (pass_mouse_events)\n", + " return fig.mouse_event(event, event['data']);\n", + " }\n", + "\n", + " rubberband.mousedown('button_press', mouse_event_fn);\n", + " rubberband.mouseup('button_release', mouse_event_fn);\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " rubberband.mousemove('motion_notify', mouse_event_fn);\n", + "\n", + " rubberband.mouseenter('figure_enter', mouse_event_fn);\n", + " rubberband.mouseleave('figure_leave', mouse_event_fn);\n", + "\n", + " canvas_div.on(\"wheel\", function (event) {\n", + " event = event.originalEvent;\n", + " event['data'] = 'scroll'\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " mouse_event_fn(event);\n", + " });\n", + "\n", + " canvas_div.append(canvas);\n", + " canvas_div.append(rubberband);\n", + "\n", + " this.rubberband = rubberband;\n", + " this.rubberband_canvas = rubberband[0];\n", + " this.rubberband_context = rubberband[0].getContext(\"2d\");\n", + " this.rubberband_context.strokeStyle = \"#000000\";\n", + "\n", + " this._resize_canvas = function(width, height) {\n", + " // Keep the size of the canvas, canvas container, and rubber band\n", + " // canvas in synch.\n", + " canvas_div.css('width', width)\n", + " canvas_div.css('height', height)\n", + "\n", + " canvas.attr('width', width * mpl.ratio);\n", + " canvas.attr('height', height * mpl.ratio);\n", + " canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n", + "\n", + " rubberband.attr('width', width);\n", + " rubberband.attr('height', height);\n", + " }\n", + "\n", + " // Set the figure to an initial 600x600px, this will subsequently be updated\n", + " // upon first draw.\n", + " this._resize_canvas(600, 600);\n", + "\n", + " // Disable right mouse context menu.\n", + " $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n", + " return false;\n", + " });\n", + "\n", + " function set_focus () {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "}\n", + "\n", + "mpl.figure.prototype._init_toolbar = function() {\n", + " var fig = this;\n", + "\n", + " var nav_element = $('
')\n", + " nav_element.attr('style', 'width: 100%');\n", + " this.root.append(nav_element);\n", + "\n", + " // Define a callback function for later on.\n", + " function toolbar_event(event) {\n", + " return fig.toolbar_button_onclick(event['data']);\n", + " }\n", + " function toolbar_mouse_event(event) {\n", + " return fig.toolbar_button_onmouseover(event['data']);\n", + " }\n", + "\n", + " for(var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " // put a spacer in here.\n", + " continue;\n", + " }\n", + " var button = $('