From dca478528f231c5a57c7441d2b1bf3b1b04c626b Mon Sep 17 00:00:00 2001 From: Daniel Baker Date: Tue, 20 Feb 2024 16:20:56 +0800 Subject: [PATCH 01/12] Option for taking time average of chunk curvatures before frequency fitting --- scintools/dynspec.py | 25 ++++++++++++++++++------- 1 file changed, 18 insertions(+), 7 deletions(-) diff --git a/scintools/dynspec.py b/scintools/dynspec.py index 6ed966c..c7d6c16 100755 --- a/scintools/dynspec.py +++ b/scintools/dynspec.py @@ -1583,7 +1583,7 @@ def thetatheta_single(self, cf=0, ct=0,fname=None,verbose=False): plt.ylabel(r'Eigenvalue') return(etas,eigs,popt) - def fit_thetatheta(self,verbose=False,plot=False,pool=None): + def fit_thetatheta(self,verbose=False,plot=False,pool=None,time_avg=False): """ Loop theta-theta over all fitting chunks and fits for the global curvature evolution. @@ -1639,18 +1639,29 @@ def fit_thetatheta(self,verbose=False,plot=False,pool=None): for ct in range(self.nct_fit): self.eta_evo[cf,ct]=res[cf*self.nct_fit+ct][0] self.eta_evo_err[cf,ct]=res[cf*self.nct_fit+ct][1] - tofit = np.isfinite(self.eta_evo)*np.isfinite(self.eta_evo_err) - A = (np.sum(self.eta_evo[tofit] / (self.f0s[:,np.newaxis] * self.eta_evo_err)[tofit] ** 2)/ np.sum(1 / ((self.f0s[:,np.newaxis]**2) * self.eta_evo_err)[tofit] ** 2)).to(u.s**3 * u.MHz**2) - A_err = np.sqrt(1 / np.sum(2 / ((self.f0s[:,np.newaxis]**2) * self.eta_evo_err)[tofit] ** 2)).to(u.s**3 * u.MHz**2) + if time_avg: + eta_avg = np.nanmean(self.eta_evo,1) + eta_count = np.nansum(self.eta_evo,1)/eta_avg + avg_err = np.nanstd(self.eta_evo,1)/np.sqrt(eta_count-1) + tofit = np.isfinite(eta_avg)*np.isfinite(avg_err) + A = (np.sum(eta_avg[tofit] / (self.f0s * avg_err)[tofit] ** 2)/ np.sum(1 / ((self.f0s**2) * avg_err)[tofit] ** 2)).to(u.s**3 * u.MHz**2) + A_err = np.sqrt(1 / np.sum(2 / ((self.f0s**2) * avg_err)[tofit] ** 2)).to(u.s**3 * u.MHz**2) + else: + tofit = np.isfinite(self.eta_evo)*np.isfinite(self.eta_evo_err) + A = (np.sum(self.eta_evo[tofit] / (self.f0s[:,np.newaxis] * self.eta_evo_err)[tofit] ** 2)/ np.sum(1 / ((self.f0s[:,np.newaxis]**2) * self.eta_evo_err)[tofit] ** 2)).to(u.s**3 * u.MHz**2) + A_err = np.sqrt(1 / np.sum(2 / ((self.f0s[:,np.newaxis]**2) * self.eta_evo_err)[tofit] ** 2)).to(u.s**3 * u.MHz**2) self.ththeta = A/self.fref**2 self.ththetaerr = A_err/self.fref**2 if plot: fit_string,err_string = thth.errString(self.ththeta*(self.fref/np.floor(self.fref))**2,self.ththetaerr*(self.fref/np.floor(self.fref))**2) plt.figure() - plt.errorbar(np.ravel(self.f0s.value[:,np.newaxis]*np.ones(self.eta_evo.shape)), - np.ravel(self.eta_evo.value), - yerr=np.ravel(self.eta_evo_err.value),fmt='.') + if time_avg: + plt.errorbar(self.f0s.value,eta_avg,yerr=avg_err,fmt='.') + else: + plt.errorbar(np.ravel(self.f0s.value[:,np.newaxis]*np.ones(self.eta_evo.shape)), + np.ravel(self.eta_evo.value), + yerr=np.ravel(self.eta_evo_err.value),fmt='.') plt.plot(self.f0s,A/self.f0s**2,label = r'$\eta_{%s}$ = %s $\pm$ %s $s^3$' % (np.floor(self.fref),fit_string, err_string)) plt.xlabel(r'$\rm{Freq}~\left(\rm{MHz}\right)$') From 87de59a01f215cdbe0432f46437562d7a3b51603 Mon Sep 17 00:00:00 2001 From: Daniel Baker Date: Tue, 5 Mar 2024 07:47:55 +0800 Subject: [PATCH 02/12] Allow thin arcs to extend closer to the edge --- scintools/dynspec.py | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/scintools/dynspec.py b/scintools/dynspec.py index c7d6c16..f41665f 100755 --- a/scintools/dynspec.py +++ b/scintools/dynspec.py @@ -1447,7 +1447,10 @@ def prep_thetatheta(self, fw = .1, npad=3, verbose = False, fitting_proc = 'stan self.neta = int(1+ (l1-l0)/np.log10(1+self.fw/10)) - fd_cut = (fd.max()/2)*(self.fref.value/self.freqs.max()) + if self.thetatheta_proc=='thin': + fd_cut = (fd.max())*(self.fref.value/self.freqs.max()) + else: + fd_cut = (fd.max()/2)*(self.fref.value/self.freqs.max()) if 'edges_lim' in kwargs.keys(): edges_lim = min((thth.unit_checks(kwargs['edges_lim'],'edges limit',u.mHz),fd_cut)) else: From 24e26d98ea09aef841134cb1ec28decf201b59cd Mon Sep 17 00:00:00 2001 From: Daniel Baker Date: Tue, 5 Mar 2024 07:56:37 +0800 Subject: [PATCH 03/12] control output of thetatheta_single --- scintools/dynspec.py | 28 +++++++++++++++------------- 1 file changed, 15 insertions(+), 13 deletions(-) diff --git a/scintools/dynspec.py b/scintools/dynspec.py index f41665f..dd9888a 100755 --- a/scintools/dynspec.py +++ b/scintools/dynspec.py @@ -1488,7 +1488,7 @@ def prep_thetatheta(self, fw = .1, npad=3, verbose = False, fitting_proc = 'stan print(f'Zero paddings: {self.npad}') print(f'Fitting Procedure: {self.thetatheta_proc}') - def thetatheta_single(self, cf=0, ct=0,fname=None,verbose=False): + def thetatheta_single(self, cf=0, ct=0,fname=None,verbose=False,plot=True,arrays=False): """ Run theta-theta on a single chunk for diagnostics. @@ -1573,18 +1573,20 @@ def thetatheta_single(self, cf=0, ct=0,fname=None,verbose=False): eta_sig=np.nan ## Plotting - try: - # Create diagnostic plots where requested - thth.PlotFunc(np.nan_to_num(dspec2)+mn,time2,freq2,CS,fd,tau,edges,eta_fit,eta_sig,etas,eigs,etas_fit,popt) - if fname: - plt.savefig(fname) - except Exception as e: - print(f"Plotting Error :{e}",flush=True) - plt.figure() - plt.plot(etas,eigs) - plt.xlabel(r'$\eta~\left(\rm{s}^3\right)$') - plt.ylabel(r'Eigenvalue') - return(etas,eigs,popt) + if plot: + try: + # Create diagnostic plots where requested + thth.PlotFunc(np.nan_to_num(dspec2)+mn,time2,freq2,CS,fd,tau,edges,eta_fit,eta_sig,etas,eigs,etas_fit,popt) + if fname: + plt.savefig(fname) + except Exception as e: + print(f"Plotting Error :{e}",flush=True) + plt.figure() + plt.plot(etas,eigs) + plt.xlabel(r'$\eta~\left(\rm{s}^3\right)$') + plt.ylabel(r'Eigenvalue') + if arrays: + return(etas,eigs,popt) def fit_thetatheta(self,verbose=False,plot=False,pool=None,time_avg=False): """ From 2b280597bd26c80956dbcf3d93c25b05c7d930d4 Mon Sep 17 00:00:00 2001 From: Daniel Baker Date: Wed, 6 Mar 2024 11:36:32 +0800 Subject: [PATCH 04/12] Sync to Daniel Reardon's Version --- scintools/dynspec.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scintools/dynspec.py b/scintools/dynspec.py index 82f9cd0..00bf471 100755 --- a/scintools/dynspec.py +++ b/scintools/dynspec.py @@ -1534,7 +1534,7 @@ def prep_thetatheta(self, fw=.1, npad=3, verbose=False, print(f'Zero paddings: {self.npad}') print(f'Fitting Procedure: {self.thetatheta_proc}') - def thetatheta_single(self, cf=0, ct=0, fname=None, verbose=False): + def thetatheta_single(self, cf=0, ct=0, fname=None, verbose=False plot=True, arrays=False): """ Run theta-theta on a single chunk for diagnostics. From e2850f88c84be880428041558a998bc2f180b30f Mon Sep 17 00:00:00 2001 From: Daniel Baker Date: Thu, 20 Jun 2024 14:22:13 +0800 Subject: [PATCH 05/12] Sync to Daniel Reardon's Version --- scintools/dynspec.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/scintools/dynspec.py b/scintools/dynspec.py index 00bf471..ff7d051 100755 --- a/scintools/dynspec.py +++ b/scintools/dynspec.py @@ -1526,15 +1526,15 @@ def prep_thetatheta(self, fw=.1, npad=3, verbose=False, print(f'Reference Frequency: {self.fref}') print( f'Eta range: {self.eta_min} to {self.eta_max}' - 'with {self.neta} points') + f'with {self.neta} points') print( f'Edges has {self.edges.shape[0]} point out to' - '{self.edges[-1]}') + f'{self.edges[-1]}') print(f'Fractional fitting width: {self.fw}') print(f'Zero paddings: {self.npad}') print(f'Fitting Procedure: {self.thetatheta_proc}') - def thetatheta_single(self, cf=0, ct=0, fname=None, verbose=False plot=True, arrays=False): + def thetatheta_single(self, cf=0, ct=0, fname=None, verbose=False, plot=True, arrays=False): """ Run theta-theta on a single chunk for diagnostics. From a882d91a39830ab594683a55effe04e7e0b02c62 Mon Sep 17 00:00:00 2001 From: Daniel Baker Date: Fri, 12 Jul 2024 12:49:48 +0800 Subject: [PATCH 06/12] always refresh wavefield --- scintools/dynspec.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/scintools/dynspec.py b/scintools/dynspec.py index ff7d051..4af06d6 100755 --- a/scintools/dynspec.py +++ b/scintools/dynspec.py @@ -1860,8 +1860,7 @@ def gerchberg_saxton(self, niter=1, verbose=False, pool=None): from multiprocessing and MPIPool from mpipool. Defaults to None and runs chunks in series. """ - if not hasattr(self, "wavefield"): - self.calc_wavefield(verbose=verbose, pool=pool) + self.calc_wavefield(verbose=verbose, pool=pool) posdspec = np.isfinite(self.dyn[:self.wavefield.shape[0], :self.wavefield.shape[1]]) * ( self.dyn[:self.wavefield.shape[0], :self.wavefield.shape[1]] > 0) From 1e8be096bc5fee008b1aa470ff3227c4e9e93df0 Mon Sep 17 00:00:00 2001 From: Daniel Baker Date: Fri, 23 Aug 2024 16:37:24 +0800 Subject: [PATCH 07/12] adding masking for low tau confusion region --- scintools/dynspec.py | 20 +++++++++++++++----- scintools/ththmod.py | 43 ++++++++++++++++++++++++++++--------------- 2 files changed, 43 insertions(+), 20 deletions(-) diff --git a/scintools/dynspec.py b/scintools/dynspec.py index 4af06d6..8c5589b 100755 --- a/scintools/dynspec.py +++ b/scintools/dynspec.py @@ -1516,6 +1516,10 @@ def prep_thetatheta(self, fw=.1, npad=3, verbose=False, kwargs['center_cut'], 'Central Cut', u.mHz) else: self.center_cut = 0 + if 'tau_mask' in kwargs.keys(): + self.thth_tau_mask = kwargs['tau_mask'] + else: + self.thth_tau_mask = 0*u.us if verbose: print("\n\t THETA-THETA PROPERTIES\n") @@ -1528,11 +1532,12 @@ def prep_thetatheta(self, fw=.1, npad=3, verbose=False, f'Eta range: {self.eta_min} to {self.eta_max}' f'with {self.neta} points') print( - f'Edges has {self.edges.shape[0]} point out to' + f'Edges has {self.edges.shape[0]} point out to ' f'{self.edges[-1]}') print(f'Fractional fitting width: {self.fw}') print(f'Zero paddings: {self.npad}') print(f'Fitting Procedure: {self.thetatheta_proc}') + print(f'Masking |tau| < {self.thth_tau_mask}') def thetatheta_single(self, cf=0, ct=0, fname=None, verbose=False, plot=True, arrays=False): """ @@ -1564,6 +1569,9 @@ def thetatheta_single(self, cf=0, ct=0, fname=None, verbose=False, plot=True, ar time2 = self.times[ts]*u.s freq2 = self.freqs[fs]*u.MHz + tau = thth.fft_axis(freq2, u.us, self.npad) + fd = thth.fft_axis(time2, u.mHz, self.npad) + dspec2 = np.copy(self.dyn[fs, ts]) mn = np.nanmean(dspec2) dspec2 -= mn @@ -1571,10 +1579,9 @@ def thetatheta_single(self, cf=0, ct=0, fname=None, verbose=False, plot=True, ar 0, self.npad*self.cwf), (0, self.npad*self.cwt)), mode='constant', constant_values=0) CS = np.fft.fftshift(np.fft.fft2(dspec_pad)) + CS[np.abs(tau)0]), vmax=SS.max() ), origin="lower", aspect="auto", @@ -1046,7 +1050,7 @@ def PlotFunc( plt.imshow( np.abs(recov) ** 2, norm=LogNorm( - vmin=np.median(np.abs(CS) ** 2), vmax=np.abs(CS).max() ** 2 + vmin=np.median(SS[SS>0]), vmax=SS.max() ), origin="lower", aspect="auto", @@ -1056,13 +1060,14 @@ def PlotFunc( plt.ylim((0, tau_lim.value)) plt.title("Model Secondary Spectrum") + Sthth = np.abs(thth_red) ** 2 # Data TH-TH plt.subplot(grid[2, 0]) plt.imshow( - np.abs(thth_red) ** 2, + Sthth, norm=LogNorm( - vmin=np.median(np.abs(thth_red) ** 2), - vmax=np.abs(thth_red).max() ** 2, + vmin=np.median(Sthth[Sthth>0]), + vmax=Sthth.max(), ), origin="lower", aspect="auto", @@ -1082,8 +1087,8 @@ def PlotFunc( plt.imshow( np.abs(thth2_red) ** 2, norm=LogNorm( - vmin=np.median(np.abs(thth_red) ** 2), - vmax=np.abs(thth_red).max() ** 2, + vmin=np.median(Sthth[Sthth>0]), + vmax=Sthth.max(), ), origin="lower", aspect="auto", @@ -1103,7 +1108,7 @@ def PlotFunc( plt.imshow( thth_derot.real, norm=SymLogNorm( - np.median(np.abs(thth_red) ** 2), + np.median(np.abs(thth_red[thth_red!=0]) ** 2), vmin=-np.abs(thth_derot).max(), vmax=np.abs(thth_derot).max(), ), @@ -1125,7 +1130,7 @@ def PlotFunc( plt.imshow( thth_derot.imag, norm=SymLogNorm( - np.median(np.abs(thth_red) ** 2), + np.median(np.abs(thth_red[thth_red!=0]) ** 2), vmin=-np.abs(thth_derot).max(), vmax=np.abs(thth_derot).max(), ), @@ -1224,6 +1229,8 @@ def VLBI_chunk_retrieval(params): Number of zeros paddings to add to end of dspec n_dish : int Number of stations used for VLBI + tauMask : Astropy Quantity + Sets all points with abs(tau) Date: Fri, 6 Sep 2024 15:27:18 +0800 Subject: [PATCH 08/12] Fixed unit check error for eta_min and eta_max --- scintools/dynspec.py | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/scintools/dynspec.py b/scintools/dynspec.py index 8c5589b..f4ed3f5 100755 --- a/scintools/dynspec.py +++ b/scintools/dynspec.py @@ -1451,13 +1451,11 @@ def prep_thetatheta(self, fw=.1, npad=3, verbose=False, self.eta_min *= (self.freqs.max()/self.fref.value)**2 self.eta_max *= (self.freqs.min()/self.fref.value)**2 if 'eta_min' in kwargs.keys(): - eta_min = kwargs['eta_min'] - self.eta_min = thth.unit_checks( - max((eta_min, self.eta_min)), 'eta_min', u.s**3) + eta_min = thth.unit_checks(kwargs['eta_min'], 'eta_min', u.s**3) + self.eta_min = max((eta_min, self.eta_min)) if 'eta_max' in kwargs.keys(): - eta_max = kwargs['eta_max'] - self.eta_max = thth.unit_checks( - min((eta_max, self.eta_max)), 'eta_max', u.s**3) + eta_max = thth.unit_checks(kwargs['eta_max'], 'eta_max', u.s**3) + self.eta_max = min((eta_max, self.eta_max)) if not ('eta_min' in kwargs.keys() and 'eta_max' in kwargs.keys()): if not hasattr(self, "betaeta"): self.fit_arc(lamsteps=True, numsteps=1e4, @@ -1806,7 +1804,7 @@ def thetatheta_chunks(self, verbose=False, pool=None, memmap=False): dspec2 -= np.nanmean(dspec2) dspec2 = np.nan_to_num(dspec2) params = (dspec2, self.edges*(freq/self.fref), time2, - freq2, eta, ct, cf, self.npad, verbose) + freq2, eta, ct, cf, self.npad,self.thth_tau_mask, verbose) if pool is None: res = thth.single_chunk_retrieval(params) self.chunks[cf, ct, :, :] = res[0] From 1bdfa395c8830f94dae464385badc45f5aeb6061 Mon Sep 17 00:00:00 2001 From: Daniel Baker Date: Mon, 30 Sep 2024 10:19:54 +0800 Subject: [PATCH 09/12] organized sample data --- scintools/examples/THTHSample.ipynb | 77 +++++++----------- .../examples/acf_strong_scintillation.ipynb | 41 ++++++++-- scintools/examples/arc_modelling.ipynb | 11 ++- .../J0437-4715/p111220_074112.rf.pcm.dynspec | 0 .../J0437-4715/p111220_084944.rf.pcm.dynspec | 0 .../J0437-4715/p111220_095816.rf.pcm.dynspec | 0 .../J0437-4715/p111220_110656.rf.pcm.dynspec | 0 .../J0437-4715/p111220_121536.rf.pcm.dynspec | 0 .../J0437-4715/p111220_132416.rf.pcm.dynspec | 0 .../J0437-4715/p111220_143248.rf.pcm.dynspec | 0 .../J0437-4715/p111220_154120.rf.pcm.dynspec | 0 .../{ => data/ththsims}/Sample_Data.npz | Bin 12 files changed, 76 insertions(+), 53 deletions(-) rename scintools/examples/{ => data}/J0437-4715/p111220_074112.rf.pcm.dynspec (100%) rename scintools/examples/{ => data}/J0437-4715/p111220_084944.rf.pcm.dynspec (100%) rename scintools/examples/{ => data}/J0437-4715/p111220_095816.rf.pcm.dynspec (100%) rename scintools/examples/{ => data}/J0437-4715/p111220_110656.rf.pcm.dynspec (100%) rename scintools/examples/{ => data}/J0437-4715/p111220_121536.rf.pcm.dynspec (100%) rename scintools/examples/{ => data}/J0437-4715/p111220_132416.rf.pcm.dynspec (100%) rename scintools/examples/{ => data}/J0437-4715/p111220_143248.rf.pcm.dynspec (100%) rename scintools/examples/{ => data}/J0437-4715/p111220_154120.rf.pcm.dynspec (100%) rename scintools/examples/{ => data/ththsims}/Sample_Data.npz (100%) diff --git a/scintools/examples/THTHSample.ipynb b/scintools/examples/THTHSample.ipynb index e5155dc..6ad5a8e 100644 --- a/scintools/examples/THTHSample.ipynb +++ b/scintools/examples/THTHSample.ipynb @@ -14,8 +14,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:00:18.387939Z", "start_time": "2022-03-29T15:00:08.227772Z" - }, - "tags": [] + } }, "outputs": [], "source": [ @@ -40,8 +39,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:00:18.394863Z", "start_time": "2022-03-29T15:00:18.389914Z" - }, - "tags": [] + } }, "outputs": [], "source": [ @@ -71,8 +69,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:37:33.720702Z", "start_time": "2022-03-29T15:37:32.697922Z" - }, - "tags": [] + } }, "outputs": [ { @@ -98,7 +95,7 @@ ], "source": [ "##Load Sample Data\n", - "arch = np.load(\"Sample_Data.npz\")\n", + "arch = np.load(\"data/ththsims/Sample_Data.npz\")\n", "time = arch[\"t_s\"] * u.s\n", "freq = arch[\"f_MHz\"] * u.MHz\n", "##Define Wavefield\n", @@ -161,8 +158,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:07:53.779732Z", "start_time": "2022-03-29T15:07:50.359223Z" - }, - "tags": [] + } }, "outputs": [ { @@ -1041,8 +1037,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:09:18.963544Z", "start_time": "2022-03-29T15:08:08.501422Z" - }, - "tags": [] + } }, "outputs": [ { @@ -1182,8 +1177,7 @@ "ExecuteTime": { "end_time": "2021-12-15T20:55:14.271658Z", "start_time": "2021-12-15T20:46:27.940860Z" - }, - "tags": [] + } }, "outputs": [], "source": [ @@ -1286,8 +1280,7 @@ "ExecuteTime": { "end_time": "2021-12-15T20:55:14.800807Z", "start_time": "2021-12-15T20:55:14.274432Z" - }, - "tags": [] + } }, "outputs": [ { @@ -1420,8 +1413,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:40:51.468981Z", "start_time": "2022-03-29T15:40:46.541274Z" - }, - "tags": [] + } }, "outputs": [], "source": [ @@ -1491,8 +1483,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:41:49.744002Z", "start_time": "2022-03-29T15:41:49.258899Z" - }, - "tags": [] + } }, "outputs": [ { @@ -1555,8 +1546,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:40:52.405762Z", "start_time": "2022-03-29T15:40:51.961730Z" - }, - "tags": [] + } }, "outputs": [ { @@ -1631,8 +1621,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:40:53.298287Z", "start_time": "2022-03-29T15:40:52.423427Z" - }, - "tags": [] + } }, "outputs": [ { @@ -1719,8 +1708,7 @@ "ExecuteTime": { "end_time": "2021-12-15T20:55:26.478085Z", "start_time": "2021-12-15T20:55:25.198452Z" - }, - "tags": [] + } }, "outputs": [ { @@ -1797,8 +1785,7 @@ "ExecuteTime": { "end_time": "2021-12-15T20:55:27.528427Z", "start_time": "2021-12-15T20:55:26.484531Z" - }, - "tags": [] + } }, "outputs": [ { @@ -1925,8 +1912,7 @@ "ExecuteTime": { "end_time": "2022-03-29T16:06:38.662379Z", "start_time": "2022-03-29T16:05:58.943518Z" - }, - "tags": [] + } }, "outputs": [ { @@ -2046,8 +2032,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:39:06.424647Z", "start_time": "2022-03-29T15:38:34.938380Z" - }, - "tags": [] + } }, "outputs": [], "source": [ @@ -2128,8 +2113,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:39:06.656717Z", "start_time": "2022-03-29T15:39:06.426655Z" - }, - "tags": [] + } }, "outputs": [ { @@ -2253,8 +2237,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:40:51.468981Z", "start_time": "2022-03-29T15:40:46.541274Z" - }, - "tags": [] + } }, "outputs": [], "source": [ @@ -2321,8 +2304,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:41:49.744002Z", "start_time": "2022-03-29T15:41:49.258899Z" - }, - "tags": [] + } }, "outputs": [ { @@ -2378,8 +2360,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:40:52.405762Z", "start_time": "2022-03-29T15:40:51.961730Z" - }, - "tags": [] + } }, "outputs": [ { @@ -2440,8 +2421,7 @@ "ExecuteTime": { "end_time": "2022-03-29T15:40:53.298287Z", "start_time": "2022-03-29T15:40:52.423427Z" - }, - "tags": [] + } }, "outputs": [ { @@ -2514,8 +2494,7 @@ "ExecuteTime": { "end_time": "2021-12-15T20:55:26.478085Z", "start_time": "2021-12-15T20:55:25.198452Z" - }, - "tags": [] + } }, "outputs": [ { @@ -2592,8 +2571,7 @@ "ExecuteTime": { "end_time": "2021-12-15T20:55:27.528427Z", "start_time": "2021-12-15T20:55:26.484531Z" - }, - "tags": [] + } }, "outputs": [ { @@ -2711,7 +2689,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.18" + "version": "3.9.16" }, "latex_envs": { "LaTeX_envs_menu_present": true, @@ -2731,6 +2709,13 @@ "report_style_numbering": false, "user_envs_cfg": false }, + "scenes_data": { + "active_scene": "Default Scene", + "init_scene": "", + "scenes": [ + "Default Scene" + ] + }, "toc": { "base_numbering": 1, "nav_menu": {}, diff --git a/scintools/examples/acf_strong_scintillation.ipynb b/scintools/examples/acf_strong_scintillation.ipynb index 79dfea2..3a5b521 100644 --- a/scintools/examples/acf_strong_scintillation.ipynb +++ b/scintools/examples/acf_strong_scintillation.ipynb @@ -16,7 +16,15 @@ "cell_type": "code", "execution_count": 1, "id": "7400c82f", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2024-09-27T01:35:02.141760Z", + "iopub.status.busy": "2024-09-27T01:35:02.141292Z", + "iopub.status.idle": "2024-09-27T01:35:03.041663Z", + "shell.execute_reply": "2024-09-27T01:35:03.041370Z", + "shell.execute_reply.started": "2024-09-27T01:35:02.141726Z" + } + }, "outputs": [], "source": [ "# Import theoretical ACF code\n", @@ -35,7 +43,15 @@ "cell_type": "code", "execution_count": 2, "id": "0ff915b4", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2024-09-27T01:35:03.605758Z", + "iopub.status.busy": "2024-09-27T01:35:03.605581Z", + "iopub.status.idle": "2024-09-27T01:35:03.666437Z", + "shell.execute_reply": "2024-09-27T01:35:03.666080Z", + "shell.execute_reply.started": "2024-09-27T01:35:03.605744Z" + } + }, "outputs": [], "source": [ "acf_obj = ACF()" @@ -45,11 +61,19 @@ "cell_type": "code", "execution_count": 3, "id": "3b9b8043", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2024-09-27T01:35:04.234407Z", + "iopub.status.busy": "2024-09-27T01:35:04.233956Z", + "iopub.status.idle": "2024-09-27T01:35:04.465382Z", + "shell.execute_reply": "2024-09-27T01:35:04.465085Z", + "shell.execute_reply.started": "2024-09-27T01:35:04.234374Z" + } + }, "outputs": [ { "data": { - "image/png": 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4lvZYy9FZtytnbU6U8LlnLa0OBKTrk8iORnIIIYQQEpEoySGEEEJIRKIkhxBCCCERiZIcQgghhEQkSnIIIYQQEpEoySGEEEJIRKIScikxlnaKjLu/ciwlj6w7ySoUbMdJSepybjn6lHLncNayajl2lmdsS5TyuerRX7EY7yfrRs6sTynLe4jUO30ztce6S7bEpeZSnm/MpfdSLlkg8VIELFg/EyT+vJJ82QWJ9Oi3GUIIIYSQUFGSQwghhJCIREkOIYQQQiISJTmEEEIIiUiU5BBCCCEkIlGSQwghhJCIREkOIYQQQiISrZMDNNX3d7AWAMv6D6zroJDQsKxfIeXaMQDb+jcAoGA4jjU2lrY60R7T2jasX3d68tpHUmJd84P1cWNdk4RpyRq2x4PjpFwnhxFrnwHG9niG9ljXKpLjPCKtMa/dxPCkMp63vXYk57XXXsPIkSNhNpthNpsxefJkrF27Vu6wCCGEENJD9NokJy0tDX/5y1+wa9cu7Nq1C7NmzcLChQuRm5srd2iEEEII6QF67eWqyy+/vNW/n332Wbz22mvYvn07hg0bJlNUhBBCCOkpem2Sc6ZAIIDPPvsMTqcTkydPbvc4j8cDj8fT8m+73d4d4RFCCCFEBr32chUAHDx4EEajERqNBnfddRfWrFmDoUOHtnv88uXLYbFYWn7S09O7MVpCCCGEdKdeneTk5ORg37592L59O+6++24sWbIEhw8fbvf4xx57DDabreWnuLi4G6MlhBBCSHfq1Zer1Go1BgwYAAAYP348du7cif/7v//DG2+8cc7jNRoNNBpNd4bYczCXiUpcgs3UloQl08yl4VKXmjMcJ3VpuELC2BifA6ZydEDar089uYScFWOZM8fSL8fWGOtd4FjKuVnP3QDjHWV9XYkSLn/A0hbA/n4UYHjgWO8na0m91OdlH9CrR3LOJopiqzk3hBBCCOm7eu1Izp/+9CfMnz8f6enpcDgcWLlyJTZv3ozvv/9e7tAIIYQQ0gP02iSnsrISixcvRnl5OSwWC0aOHInvv/8eF198sdyhEUIIIaQH6LVJzjvvvCN3CIQQQgjpwSJqTg4hhBBCSDNKcgghhBASkXrt5apux7IrKstO5QBzaikKHffJKRRsjZHWWHcXZy0nZSixFZnbkrYMnqlfqfuUsuxbjq9irDtbM+JYdtNGsEK0QwHGXcgZ3j8AQGTZOTzAFr/kxf4su1aLrPXX5Ewsny/BAxnL1pmeK4lfWAxoJIcQQgghEYmSHEIIIYREJEpyCCGEEBKRKMkhhBBCSESiJIcQQgghEYmSHEIIIYREJCohByAKYodllJyUu25LSa5daVnKBSUuS2Y6To7dxVmPY308WHcEl7A9SXc0B2MJOetLqifvQs768mNur+PjOJaSb7BX63JM5eGs5cYSv65YXqdS9ynl+cbyPim1CNipXGR43JiWWwCN5BBCCCEkQlGSQwghhJCIREkOIYQQQiISJTmEEEIIiUiU5BBCCCEkIlGSQwghhJCIREkOIYQQQiISrZMDNC0ocf51IESh43yQ4xnXkmBoC4C0KajAumgG4xoRitBDCSuO8UGTeD0dpnVmJF7/RlQwPgkM7YlS3k+A6fFlXd6kJ6+Tw7hkDfOaHkxr1rB2GmB93AIdd8n4ZiQqWB83xtgElvWWWN8oGd8D5cC6ng7r+zgL1vV0WGNjWJiJZf0b1rZYF4KikRxCCCGERCRKcgghhBASkSjJIYQQQkhEoiSHEEIIIRGJkhxCCCGERCSqriKE9Fj+gAcejx0ejx1ujw2eph+fzwVB8CMg+CAIPggBPwKCF4LghxDwNd3uB8fx4HklFLwKvELV9P9q8AoleF4FBa+CQqGCWm2GVmOBRmOGpvm/ahM45sodQkhPREmOhFjL4zgJy69FxpJCjrXcuK9gLEsWGcu+WcrDpS4NF5WMZb1K6UrIpSypF5ueA7/PjQZHGRyOMriclfC4g4mM221DwO9mi6u9PsQAAoEAAgEP4OvkH3M8NGoTNFoLNBoLtLpoGE0pMJpToNfHgeN4cFKWhgMQ+Y6P41jfZ1hLzZl0XGYOAJzIeE4yr/TQg8u+eyjWzwTp+5XyfJMOJTmEkG7j9Ta0JDQORzka7KVobKw9798olBpoNFHBZENrhlYbBZXK0DQyo4KiaVTm9L+DIza8QgVRFCAEgqM9gYC/adSn9b8D/ubRIlswwXLb4PHYAVFoGTk6G8+rYDSlwGRKgcmcApMpFXpDAnievkwQ0pNQkkMICQtRFOFyVqG+7iTq6/PhsJeeM2EAAI02KjhKYkqGVtuU0GiioNGaoVRpuzny4Ldhr6fhdOLjscLlrEGDowwNjnIIgg922ynYbada/objFDAak2C2pCM6ZgCiovtDpdJ1e+yEkNMoySGESMbttqKuPg/11jzU1+XB63W0OUanj4XJlNp06Sf4X7XaIEO07eM4HhqtGRqtGbCkt/qdKApNCU8pGuylcDjK0OAog9/vhsNRCoejFKUl2wFwMJlTER0zADFR2bCY+0GhUMlzhwjpoyjJIYSEzOdrRH19Hurr81BXf7LNpSeeV8ISlYnomAGwWPrBaEqGUhkcmRHl2K5BAhzHw2BMgMGYgKSk0QCCo1buxno4HKWw1uejvi4PLlc1HPYSOOwlKMLm4GNhyUB09ADERGfDZEqhic2EhBklOYSQThGEAOrqTqC8Yjdqao5CFM+clMrBbE5DdMwARMdkw2zpG6MXHMdBp4+BTh+DhMQRAAC32xa8VFeXh/q6k/B6HS0JYT4AjSYKycljkZw0FjpdjLx3gJAIRUkOIYSJ01WN8so9qKjY2+oylF4fj5joAcHEJioLSqWWfSPPCKbVWpCcMg7JKeMAvwCXqxp19SebEp18eDxWFBZuRGHhRkRF9Udy8jgkxA6FQqGWO3RCIgYlOQiWvokdlFsy7TDOOvTMuHsq027lrKPdrDvOMh4nMtwH1p2LmWNjKV9mLYVm3oWc7TCmUnPWXcglLA0HAFHBUN7eTlt+vwdVlQdQXra71SRblcqAhJTRSEodD6MpudXfBMBYks6aB7GWrbM+9SynG/NuyWydcgoOWk0SUqKTkIKpCAR8qK3KRXnpLlhr82C15sNqzcdxhQaJSaOQlDIOZnM6uHOdp37WUl3WUuKOzw/WUnnm0nCW91OA7XUq8fIHYCz3Z8HyPtl0oHTHybC7ODPGtljK0UXG+0lJDiGkDbutGKUl21FVeRCC0LzADIeY+BwkpY5HbPxg8Dy9fYRKoVAhIXk0EpJHw91Yj4rS3ags2wN3Yx3KSnegrHQH9IYEJKeMQ0rqBS3zmAghnUPvUoSQFjZbEQrzf0Bd7YmW2/T6eCSljENS8hio9BYZo4tMWl00MgfMQUb2LNhr8lFethvVVYfgclYh78RanCrYhLR+FyIt/UIqSSekk3ptkrN8+XKsXr0aR48ehU6nw5QpU/D8888jJydH7tAI6XXstmIU5P+AutrjAIIVRIlJo5CSOhFmS7+Wyya0/mz4cByP6JhsRMdkw++/AlUVB1BcvBUuZxUK8zegpGgr0vtNQ3rKZBrZIYRRr01yfvzxR9x7772YMGEC/H4/Hn/8ccydOxeHDx+GwdCz1twgpKdyOEqRX7gBtbVHAQQ/aJOSxyIjcyZ0eqr4kYtSqUVK2gVITh2P6qpcFOZvgNNZiYL89Sgu+hn90qcjLXUSlEqN3KES0qNxIuvsnR6uuroaCQkJ+PHHHzF9+nSmv7Hb7bBYLJjBXQkld/4yV45pIiXbrDumtljbY2yLee8q5uMYJisqGXNo1j5VDO1J3KeoZt1HiiU2tvNDULH2GfrEY0dDOQoKN6Cm5nDTLRySksciM2smdPrY9mNj3X+rz0w8ZuyTsT2+nUmvoiigqvIQCvN/gMtVDQBQqfTISL8IqakTz1mRxQUY97VjmMjM+9j2roKftU8/23Fehn4DrLGx9Qkf43EM/YqsfTI+V0x9sj4eEk88Ztq7SsK2/KIPm8U1sNlsMJvN7R7Xa0dyzmazBZeLj4lp/9unx+OBx+Np+bfdbg97XIT0JK7GWuTl/xfV1YeabuGQmDgKmf1nQW+IlzU20r7g5cORSEgcjqqy/Sgo3IDGxlqczF+LouItyMiYgbTUSbS4ICFniYiRHFEUsXDhQtTX12PLli3tHvfkk0/iqaeeanM7y0gOC0lHaFjbY31TYxh5AaQd8eFYRl4AaUdf1IzPI2NsIuuoCsNxopqtT0Elbam5oOIhigLKin9F3vHvmqqlOCQkjURG/9kwGBPYR2iYR49YdiFnaop5xEfSkRzWERrW4xjLkplGVQIiBCGAyvK9OJW/Ee7GOgCA2dIPg4df25Ks8j7WUZWOj2Nuy8s4QsM4MsR0HOvIi5dxG3oJR4ZECUeFAMZRGtZRISlHaBjbk3KnctaRnIhIcu699158++23+Pnnn5GWltbucecayUlPT6ck58zmKMlpJRKSHKffimO5n8NalwcAiIrujwGDr4DRlHS6T0pyzmpMwrYgfZLTTBACqCjdhbwTaxHwu8HzSmQNmIe0jAuhYPx8pSTnLJTknHVY705yev3lqvvvvx9fffUVfvrpp/MmOACg0Wig0dBEPdI3iKKIsvKdOHnyOwQCXvC8CtmDLkVK+kS6rBEheF6BlPSJiIkfjGO5n6O+9jjyjn+LmqpcDMm5GvrzzK8ipC/otUmOKIq4//77sWbNGmzevBlZWVlyh0RIj+H1NuDI0c9RW3sMAGCJysTg4deed1Ix6b20WgtGjr0N5aU7kXfsG9ishdix8x8YNOhyJCeNO/fKyYT0AV1Kcnw+HyoqKuByuRAfH3/eSb9Su/fee/Hxxx/jyy+/hMlkQkVFBQDAYrFAp6MFs0jfVV+fj9zDn8LrtQcvXwy8BGn9ptDoTYTjOA4paRcgJnYgjuaugrUuD0ePrkZ9fR5yBi2ktXVIn9Tpd72Ghga88cYbmDFjBiwWCzIzMzF06FDEx8cjIyMDd955J3bu3BmOWFt57bXXYLPZMGPGDCQnJ7f8fPLJJ2Hvm5CeSBACyM9fj7373oHXa4deH4/x4+5BesZUSnD6EK0uGqPG3Y7+/eeB43hUVu7Hzl3/hN1eIndohHS7To3kvPzyy3j22WeRmZmJK664An/84x+RmpoKnU6Huro6HDp0CFu2bMHFF1+MSZMm4ZVXXsHAgQPDEngEzJcmRDJebwMOHvoYNlshACA5eTwGDbwMCoWaVinugziOR2bGRYiOykLu4ZVobKzD7j1vYOCAS5GWNlnu8AjpNp1KcrZt24ZNmzZhxIgR5/z9BRdcgKVLl+K1117Du+++ix9//DFsSQ4hJMjttmLvvnfQ2FgLhUKDwTmLkJg4Su6wSA9gsfTDhPH34+ix1aiuzsXxE1/D43Wgf9bFNE+H9AkRUUIeqpYVj7Gw4xJyCYf7pSw1Z26LsTRc0hJy1tJwJeuKxwzl4VKXkDOWfbMcJzCunsx+HA+nswoHdr0Dj8cGjTYKo8bd3mZRP4Gh7FtQsZ1HLG0BjCXkjE870+rJEmNdoZhjrDZmLSHnmVYf7nxboiiiqGAzCk7+FwCQkjYJA4dcAY7jwXsZSshZVh7uxHHMpeYsx0ldQu5jPM4v5YrHUpaQM7Ylx4rHrBj69Is+bMaX3VtCXlFRgZ07d4LjOEyYMAGJiYlSNk8IOYPDXooDu9+Fz+eE3hCPkePugFZLu4STtjiOQ0b/mVCqdDhx5EuUlWyH3+/G4OHXgmfeX4OQ3key4YmPP/4YU6dOxbfffouvvvoK06ZNw8qVK6VqnhByBpu9GPt2vgmfzwmjORWjJ9xFCQ7pUGr6JAwZcT04jkdVxT7k7v8QgsA4HEVILyTZSM7zzz+PnTt3Ijo6GgBQX1+PGTNm4Prrr5eqC0IIAJerBgcOvI9AwANLdBZGjFlC5cGEWWLyKCiVGuTu/wi11UdwTPEFBudcRXN0SESSbCRHEAQYjcaWfxuNRggC1XUQIiWv14F9B96Dz++CyZyGkWNuowSHdFps/GAMHXUjAA7lFbtRULhB7pAICQvJRnJuvvlmTJkyBVdffTVEUcTq1atxyy23SNU8IX2e3+/B/gP/httdD602BiPG3AqFUi13WKSXiosfgkFDF+H44TUoPLURGo0FqSkT5A6LEElJluQ8+uijmDNnDn7++WcAwBtvvIGxY8dK1TwhfZogBJB7+D9wNJRCpdJj9MhbodYYO/5DQs4jJW0ivE4rCk9twvHjX0KjMSEudrDcYREiGcmSnPXr12Py5MkYN24c/vWvf+H111/HQw89hMGDI+QFw1JGx1hmzlpqx/Esu7oy7i7OuF2yyDHuNsxw/V5kLD3kRMarpnKsdsA4T0FkeTxC3OlbFEUcO/4lauuOg+dVGDF6CXTmeAQYy7kFdcePb4C1hFzNeBxDeTh7CTnbcVLiBLb7yVpCzgcYn3svwznOuvU54zKQmQMuhttrR0X5bhzK/Q/GjLsTZkt667hY42d8vcgy/4f1/YPxOKb3N8YpGyLr1A6Gz47eXhouNcnePn7/+9/DaDRi+/bt+OCDDzBjxgzcfvvtUjVPSJ9VWLAB5WW7AHAYNuIGWCz95A6JRBCO45Az5ErExA6EIPhwYN/7aHTVyh0WIZKQ/DvSF198gfvuuw833ngjXC6X1M0T0qfU1BxFYX5wUuigwQsRFz9E5ohIJOJ5BYaNuAlGUwp8PicOHfgIgQDjoniE9GCSJTkpKSlYvHgxVq5ciQULFsDj8SDAuPIiIaQtv9+NY4dXAwDS0qcgNW2izBGRSKZUajBy9BKoVAY0NJSj6NSPcodESJdJluSsWrUKV155JdavX4/o6GjU1dXhxRdflKp5Qvqcgvwf4PU6oNPFoP+AS+QOh/QBGo0ZgwYvBAAUFf4Il6tG5ogI6RrJkhyDwYCrrrqqZUPO5ORkzJ07V6rmCelTGhzlKC3+BQAwMOcKKBSMe3IR0kXxCcMRHTMQguDHiWNfoQ9vb0giQJerqxYvXowPPvgAEyZMaDVjXhRFcByHHTt2dLULQvoUURRw7OgXEEUB8QnDERuXI3dIpA/hOA6DBl+BHb/8HXW1J1BddQhJUUPlDouQkHQ5yXnhhRcABC9X9Xms5XESlpqzlJkHG2Ms2WSdRsUz3AfmUkYJj5Oy3LEzWHbdZtxNu6xiD+y2IigUamQPuRxCO22z7hweYCj7DmgY22IcUGKJTeoSctZTnKUCm3ElBfYScsadwxUs5whr9TXjA8Kdozxca4pHv/4zcCpvA04c/wax4wdAqdR03BjjMgmSkuN9hrVf1rYCrO/jDMfJURreiX67W5eTnOTkZABARkZGl4MhpK/z+pzIP74WAJAx4GJoaNNNIpP0rBmoLNsHd2MtCgo3YOCAS+UOiZBOk2GZLUJIe/Ly/wu/zwWDMQlp/abIHQ7pwxQKFQYMuQIAUFL6CxwN5TJHREjnhS3JKS8vh8fjCVfzhEScBmclyit2AwAGDl0Ejme8nkNImMTG5yAucThECMjL/6/c4RDSaWFLchYvXozBgwfj97//fbi6ICSilJb9CgCISxgGS3SmvMEQ0qT/oPkAONTVn4CrkVZCJr1Ll5OcoqKic97+ww8/oKCgAHfccUdXuyAk4vkDHlRU7gMApPSbJG8whJxBp49FTPQAAEBZGVXLkt6lyxOPb7nlFpw6dQrp6ekYOXJky8+IESNgMBgiZ4NOQsKosnI/AgEPdLpYRMVkyx0OIa2kpkxEXf0JlFfsQVbWHCh4WreJ9A5dTnI2b94MAHj55ZexefNm6PV6fPrpp9i8eTOys7Nx7NixrnYReSQsNWcvA2SrdeVYy3oZtuxg3WmYtbSaUzKcrqyPrRyl5u3cT1EUUVoe/IacmjIRUCrAEp2gYhuIZSkP97OWkDNUEQOAwPAZyFpCzrKjOYBOlFZ3fAjPWBrOXELOuGO8lDuucwJbYyzl7XHxg6HRWODx2FBVk4vkpDFdDY8NU5k2a/k14+7irNsRMRzH3BZr2TdLn32kNJxVl5OcZv/+97+xd+/eln+vW7cOH3/8sVTNExKx7PZiNDSUg+eVSE4eK3c4hLTBcTxSUy5AfsF6lJb+2n1JDiFdJNn3Bq1W22rUZu7cuTh06JBUzRMSsUpLgxOOExJGQqXSyxwNIeeWnDweHMfDbi+Cw1EmdziEMJFsJOftt9/Gtddei5kzZ2LkyJHIzc2VqmlCIpbP14iq6oMAgLRU2mU8FGLAj4DHDcHngeB1I+AJ/lfweMApFODVGvAaLRRqLXiNBrxKC16tBse48jgJ0mhMiI8fhqqqgygr24mcnIVyh0RIhyRLcoYNG4YdO3ZgzZo1yM3NRXp6OtauXStV84REJKutEILgh14fB5MpTe5weiS/qwGemopWP74GGwSvB4LHDTHgD6ldXq0Br9ZCodVBHR0HTVwyNHFJ0MQlQWuJB6+Q7O0xYiQljkFV1UHU1Z+UOxRCmIT8KhYEAVu3bkV1dTWmTJmCpKQkaLVa3HDDDVLGR0hEs1oLAABRUf2ZJ2pHKsHvh7uqBO6acnhqK+BuSmj8LgfT33MqNRRNoza8OjhaIwaE4KhOU0IU8LhbJlIKXg8Erwf+Bhs8NRVwnDjj8jrPQxOdAG1cEjSxSdDGJUGbkAa1JSYcd73XiIrKBMChsbEWHo8dGo1Z7pAIOa+Qk5yEhAR4PB5otVpYrVbcfPPNeOWVV2A0GqWMj5CIZrUWAmj+8Oh7Al43GgqOwn7iIBwFhyF4z71KusoS0zLKoolLgtoSG7wEdUZCwyk6LsMSRRGiz9eU4AQvbQUanfDUVsJTUw5PTfC/gtcDT20FPLUVrf5eE5sE88ARMA8YAW1CKjjmkq7IoFRqYTImw9FQBqu1AImJo+QOiZDzCjnJ+eyzzzBz5kwAwL59+/DQQw/hggsuwMaNG5GUlCRZgIREKr/fg4aG4ATOKEumvMF0I39jA+z5ubDnHUTDqeOtLjcp9EboElKbRk+SoYlNhDohCbyasXa9AxzHgVOpwavUgMHUcrsxK6fl/0VRRMBqbRpNKoenthLumnK4q8vgqa1AdW0Fqrevh8ocA3P2cFgGjIQ+ORMc3zfm+ERFZTUlOYWU5JAeL+QkpznBAYDRo0djw4YNeOSRRzB16lRs2bKlZXdy0gUs6xMwTp5kXjuBYzuOY1h3R2S8/ML84cCy5kSAdaEfxseDdW0NhvsqKlofY7MWQRQFaHXR0BiiW5ZvERnXVGFZiwYAAmqGY7SMbTHmGmcf57PXw3HsIBzHDsJVnN/qcVXFxME0eASMQ0ZAm9qvzYRgQQF070odHDh9NLQp0dBiSMutgUYXGk4cRsPRg3CeOAqfvQ61e39C7d6foNAbYRo0DKackdBnDAR/1ppOCtZt/BieesaXKHjGqUos59uZ564lJgvFJVthtRW2OadZX/OSvv4CjGcH8/o30q1Zw9on6/uzpGvg9PL1b1hJNrPO6XTi9ttvR25uLubOnYuDBw9K1TQhEclaXwgg+M04UjWWF6N26w9wHG/9fqBJTIVxyAiYhoyAOj6pV8xHUuj0sIwcD8vI8RB8XjjzjsF5+CAcJ3IRcDXAuu9XWPf9CoXeiJiJFyF67IVQaBizx17EEpUBAHA6K+H1OqFWG2SOiJD2hZzk3HbbbSgtLUVJSQlKS0vR0NAAIDjUq9FIM7RMSCQ7Pek48pIcV0kBan5eB2f+6bWzdOn9YcoZAdOgEVBHxTCPRPVEvEoN0+ARsGSPgBgIwFWUFxypOn4Q/gY7qjd9i9pfNiJm/DTETJgOBR856x+p1UboDQlwOatgsxYiPmGY3CER0q6Qk5zKykpkZGRgypQpSE1NbfUTFxcnZYyERCSnsxIAYLJETum4syQfVb+sg7PoePAGjodl+FjETpoFTXxkztXjFAoYsgbBkDUIiRcvgu3wHtRu2wBvbRVqfl6Hup0/IXbMNMSOnQ6lLjJGPczmNLicVXA6qxAPSnJIzxVykvPdd9+1+7t9+/Zh9OjRoTbN7KeffsJf//pX7N69G+Xl5VizZg0WLVoU9n4J6apAwAe/rxEAoNFYZI6m65wleU3JzYngDTyPqJETEDtlDtRRsfIG1404hQJRIybAMnwcHEcPoubndfBUl6N6+3rU7mlKdsZd1OuTHY02eM56PXaZIyHk/CSbk2Oz2fDRRx/hnXfewf79++H3h7ZAV2c4nU6MGjUKt912G66++uqw90eIVJo/HHheBaWy987bcJbko2rbWjiL8wAAHK9A1PAJiJk6B+qovrumDMfxMA8ZBdPgEXAcO4jaLevgri5H9a8/oHbPFsSMuRBx42f22mSneX0cDyU5pIfrcpKzceNGvPvuu1i9ejVMJhOmTp2Kffv2SRBax+bPn4/58+d3S1+ESKn5w0GjMfeKSbdnE/x+VG75BrV7fgIQTG6iR0xE3AWzoDbHMFdhRTqO42EePApRmSPgOHkIVb+sh7u6FDU7NsJ6eDfSF9wMQ1q23GF22ukkxyZzJIScX0hJTklJCVasWIH33nsPlZWVWLhwIVatWoV58+bhyJEj+OKLLyQOk7SLtQyQdZ8exvZEoeP2ONbSTp6xzJJhdJBlQTgAgMAYG2OpK8dw3JnltW5vcBVftdbcpuxWUDCWkDOWmgfUHR/HmpT49YC3rhplqz+Au7wEAGAZMxFx0+ZCZYkOHgO2kvSAmrFslvVdijVXZOiWYxyIVnjZOlUoeOhHjUTGyBFoOJ6Lqh++hq+uGgWfvoq46XMRO/Vi5qUUuABjn16mw5jOt7PPUXXT5SqPx9Hqdyyvg2CDjMexvE5Zy7RZry5IWGrOXPItZTl3HykNZ9XpJOfSSy/Fpk2bMGvWLDz99NNYtGgRDIbTQ649+Vupx+OBx3N6wQq7nYZaiTy87uA34N62LL7t4G5UfrcKgtcDXqdH8uXXw5QzXO6weg2O42DKGQ5D1kBUrF0N+4GdqPnxv3AWnkTKopugVEbJHSITddN56/U4IAgB8DzjlwtCulmnl+j8/vvvcfXVV+Opp57CTTfd1CrB6emWL18Oi8XS8pOeni53SKSPOn25qndMOhb8PpR8vxLlX3wEweuBrl9/ZP3P7ynBCRGv1iBl4Q1IXngjOJUajafyUPjm3+AoOCJ3aEzUamPT6LAIn7dB7nAIaVenk5ytW7dCp9Nh1qxZyMnJwdNPP42TJ3vHjrSPPfYYbDZby09xcbHcIZE+yudzAgBUvWAhNb+rAYWfvQ5r7g6A4xA3fR76Lb4HKnOU3KH1epaR45F150PQJKUi0OjEqTVvo3bfVrnD6hDH8VCpgmv/eJvOZUJ6ok4nOZMnT8Zbb72FiooKPProo1i3bh1ycnIwadIkvPLKK6isrAxHnJLQaDQwm82tfgiRQ/PWBSLr3ASZeOqrkf+ff8BVVgBeo0X6Tb9F3EXz+sw+Td1BHZuAjNuWwTLqAkAUUb7hc1T8+BXEnj63ouncPXsbDkJ6kpCrq/R6PZYuXYqlS5fi2LFjeOedd/Dcc8+hsrKy2+blNDQ0tBpFKigowL59+xATE4N+/fp1SwyEhILngy89UQj/Uguhcpbko+jL9xBwO6EyxyDjqjuhTE+UO6yIxCuVSLr8OmiMsajauhY1uzbDa6tD2vwbg5uJ9kBC07nLc5KtREKI5CRJwXNycvDCCy+gpKQEq1evxoIFC6RotkO7du3CmDFjMGbMGADAQw89hDFjxuCJJ57olv4JCRXXlOQIPTTJsR3bh8JVryHgdkKXlI7sG5dBG0sJTjhxHIeESRcj7dKbwCkUsJ84gILPXoW/sWdeDhLEYBVSc8JOSE/U6bPzT3/6ExYtWoQLLrigze8UCgUWLVrUbasOz5gxo8cP9/cYEpaGAwDHM5RPMlZigmfcrZxlh3HW8k/mclLGb9EM5+GZ5bU8F7wvouBvW3bLOBAqML56BYa74Ned/n9nwQkUf/chIAgw5gxHyqKbAZUafgRLyFn4DQznh4bxcoyK8TXOuj23yPAA+xjL+D1srxeR9fKeCBjHjkN6rAUln72HxvIinPr6XaTfdHfLzuasu4uznh9sO5+3fmxFUWwZhVRw/Onfs74fBxiPY3mdyrG7OOtxzO+7MpSa9xGdHskpLy/HZZddhuTkZPzP//wPvv3221Zl2YSQjjWX3Pa0kRxPTSVKP18BCAJMQ8cg9epbe+zlkkimzxiAjFvuA6/RorG4ABXffNKjvtCJZ3yD4Wgkh/RgnU5ymhcA/PTTTxEVFYWHH34YcXFxuOqqq7BixQrU1NSEI05CIkrzPAaBebgr/PzOBpSsfBuCuxG6tEwkX3E9TTCWkSYhGalXLwE4HvZDu1G7ZZ3cIbUQhNPnLV2uIj1ZSO9gHMdh2rRpeOGFF3D06FHs2LEDkyZNwltvvYXU1FRMnz4dL774IkpLS6WOl5CIwCuakpyAT+ZIgkRRRPk3K+Gz1kIVFYvUa5eCV6rkDqvPM/TPQdL84L58NT/9F86CEzJHFCQIp89bWgiQ9GSSfE0bMmQIHnnkEWzduhUlJSVYsmQJtmzZgv/85z9SNE9IxNFqowAAjY118gbSxHFkP5wnDgO8Amm/WQqlwSh3SKRJ1NjJiBo7GQBQ8d1nEPyM+zWEUfN5q9FYqISc9GghjzMKgoCtW7eiuroaU6ZMQVJSEgAgPj4et99+O26//XbJgiQk0uj18QAAl7MKoijKuh2K3+1C5X/XAABiL5wNTUKybLGQc4ufdRkaTuTCV1+Dqh0/IGnKpbLG43JWAQD0hnhZ4yCkIyEnOQkJCfB4PNBqtbBarbj55pvxyiuvwGikb4CEdESnjwPAwe93w+dtgFpjki2Wiq3fIOB0QB2bgNgL58gWR6hEUYTY6EagoQGCw4lA04/gcIJTKaEwG8GbDFCYDOBNRiiMBnDK3jWPRKHVIXHeVShdtQJVuzciatAYaOPkS0ZdzmoAp5N1QnqqkF/pn332GWbOnAkA2LdvHx566CFccMEF2LhxY8uoDolcLCWPLGXmANh3EfYxzF9RMJbA+9lOfc7PFhvnZ7ivZxyi4FTQaqPhdtfB2VANtep0ksNS4Qyw71YeOM/UGmdJPuoObQcAJCy6FqJBifPdY5bScAAQTR1XjSl0bJVlKlUwooDTDVduIVwH8uAtq0XA7kTA5kLA7oTI+Dw14/VaKMx6KCwGKKOM0A1Kg35UNjQZieB4Hj4f2zyTQCPbeeRnfKvl/O2fv/pRI2HIHQ7nkUMo3vgpsm68/7yXiljPD6bz7aynvVWSc8bvmF4HYH9dgeE41t3Fmd4/APaSdIZybubScBI2ISc5zQkOAIwePRobNmzAI488gqlTp2LLli1ITqYhb0LOR6+PhdtdB3djHRDdv9v7F/x+lK37FABgHj8Juszsbo/hfER/AO4TxbAdPgHngXy4T5QCQvsfLJxWBaXZAIVFH/yvWQ/R64ff7kTA5oTf5kLA4QIEEYLLDcHlhq8iOLek4dcjwAfroTAboB+RBc3wgdCPyIYyLqqb7i2b+AVXoTHvBBrLT6F+3y+IGXOhLHE0z8nR62Jl6Z8QVpKN2TqdTtx+++3Izc3F3LlzcfDgQamaJiQiabXRAAC3u16W/mt2bIC3rgpKvQlxcy+TJYYziaIIX2k1Gg+cROOhPDQeLoDobj3JVpUUA8OobGgHpEIRZYTSrIeiKbFR6Tt+OxMFET67B36bEwF7cBTIV1UP18ECuA6fQsDuhGPrITi2Hgr2lxwH3Yjs4M+w/uD12rDcd1YqSxQSpi1AxYbVqNzyLUwDhkFliurWGERRbDlntbrobu2bkM4KOcm57bbbUFpaipKSEpSWlqKhoQFA8AWg0WgkC5CQSNWc5DTKkOR47fWo+fUHAEDSrCuh0DEuZRwGoiiicd9x1K/aBE9eSavf8SY9DCP7Qz+yPwwj+0OVcL4P1Y4vH3A8B4VJD4Wp9f2NueJCiD4/Go+XwHUgDw37C+A5WQJfeQ185TWwr/sVnEoJ0+wJiLpiGpQx8m3uGzNqCmyHd6Ox/BQqf/oGaQtu7tb+fT4XAoFg8qnRRHVr34R0VshJTmVlJTIyMjBlyhSkpqa2+omLi5MyRkIiksGQAABwOLp/PSnb4V0QAwHo0/rDnDMKcqzWI4oiGvceR/3nG+HJCz4GnEoJ7eAM6EYMgG5ENtQZSVBrumdeA6dSQj8sE/phmbBco0DA2Qh3bgEaD+XBdeAk/BW1sH//CxwbdrYkO5wupltiaxUnzyN59lXI//Bl2I/vR2D21VBodR3/oUQcjmAiqtPFQKGgtZRIzxZykvPdd9+1+7t9+/Zh9OjRoTZNSJ9gtmQACJbj+nxOqFSGbulXFEVYD+8GAEQNv6Dby9dFUUTjgWOwf7Uenvym5EajgnnuRERdNhUKy9kVmvKsCq0w6GC4YCgMFwwNXqI5lI+6VRvgOVbUkuwYL7oA5ksvgjLa0q2xaRPToIlLgqemAvbj+xE9clK39W2zngIAWCyZ3dYnIaGSbE6OzWbDRx99hHfeeQf79++Hn3UDREL6KLXaAL0+Hi5XNWy2IsTFDemWft2VJfDWVYFTKmEeOLJb+gSakpv9R2H7cgO8hcHRgGByMwlRl114juSm5+A4DroR2UgZ3h/uQ/moX7UR7mOn4PhhGxybd8B00QSYF8zotmSH4zhYhoxD1ZZvYT28u3uTHFshAMASldltfRISqi4nORs3bsS7776L1atXw2QyYerUqdi3b58EoRES+SyWzGCSYy3stiTHdmQPAMCUPRwKTfgn0gaTmyNNyU3zyI0a5nlNIzfm7hnBkkJzsqMd3h/u3HzUfboJnuOFcGz4BY4fd8A0/QKYL+ueZCdqyFhUbfkWrpI8eO31UJvDPwlYEPyw24sBAJamkUhCerKQkpySkhKsWLGiZbPOhQsXYtWqVZg3bx6OHDmCL774QuIwSbdhWPsBACDHUu4suzD7GEcQlYzHMbbHsj4IF2h7TJS5H8rLd8JmLWz5Pcc6BYXxKpN4xqtcFAKwHQ0mOZYR41p+F9CydSoY2C4dac2e4PEeHyrf+BqOH/cHQ9aqEXXJBYi+YgriU3gAIoCG87Zl0riZ+lTzbLF5hY7XwHF4GJK/qYkwjr4VjYcKUfvJJjQeOQXHxl/g3L4XyQ9eA8PYgS2HugXGNY08HR8nOoPHKGOioe+XDVdRHmzH9yBu0uzWBzKeHyznW/O52WAvgSD4oVLqYdDEtjmnWdfJYX6dslwRYG2rB+3i3gbr+y7ptE4nOZdeeik2bdqEWbNm4emnn8aiRYtgMJz+Jibn8vSE9DbN34btjlIEBB8UfHgncjpPnYTf6YBCZ4Axa3BY+/LV2lH2wkp4TpYCPI/oKyYjZuGFZ4zcNIa1/+7AcRz0I7KgG56JxkOFqP5wPTwnS1G6/CPE3TQH0QsvDOt7omXYuGCSc2g3YifOCvv7r81WFOzX0o/e60mv0Omv499//z2uvvpqPPXUU7jppptaJTiEkM7RaWOgVhkhigE47OGvsrIf3gsAMA8eBU4Rvt2jPcVVKHrkDXhOloI36pD2xGLEL57bqy5NdUZzspP+zFKY54wFBBE1H6xH5atfQjzPAoZdZc4ZBU6hhKemAp6airD108zaPB+HJh2TXqLTSc7WrVuh0+kwa9Ys5OTk4Omnn8bJkyfDERshEY/jOERFZQEAauuPh72/xorgfApj9tCw9eGvs6L0//sAAWsD1P0S0O/5/4F+RPev6CwHXqVE4l1XIOGOSwGeh33jXtR8sD5s/Sm0OujSguePu7w4bP0Awfk49dZ8AEA0JTmkl+h0kjN58mS89dZbqKiowKOPPop169YhJycHkyZNwiuvvILKyspwxElIxIqLDU44rq45HPa+fA4rAEAdFZ71XQRXI6r//h78tXaoU+OQ/vRtUCd1/1oycuI4DlHzJyLp3oUAgPqvtsG+fkvY+lNbghOOfQ22sPUBAPX1eQgEPFCrTTCZUsPaFyFSCXn2qF6vx9KlS/Hzzz/j8OHDmD59Op577jnMmdP7djEmRE5xsTngOAVcrmo4XdVh60fweiC4g/NglGHYCkD0+VD9yvvwlVZAEW1C6v8ubrOycF9injEacTcF3w+tK7+Bc8f+sPTT/Fz6HeFNcqqakvD4uCHn3RiUkJ5EkjM1JycHL7zwAkpKSrB69WosWLBAimYJ6ROUSi2io4KXc8I5muNr+hDk1RrJS8dFQUDNW5/Ac7wAnE6DtP+9GaqEKEn76I2ir5yKqEsnAgBq3/kE7iPSX9pXmYLl6j67VfK2m4migJraIwCA+NhhYeuHEKl1qrqqqKgI/fr1a/f3CoUCixYtwqJFiwAApaWlSE2lYU1yfqLAVtrJSTlP9hzl3OfEuqilr+PyZd7Xfp8J0UNQV38CNdW5SPUzjoYyVsSKTV9lfA1WAMFv/uJZX28Exq0TlPq2j4coiqhd8Q0adx8EFAokPXQTUkeYADjP21amuY6pz2Stnek4Dce2OYVH7LiCrdzNtjdVId/xpbi4+6fhQK0Tzl8Pofpf/0bKn++EJiP5nMcKzo5PcpFvXdWktEQBCF6KbPW8Mp4fvL/jA+11hfD5nFAqtIgxZLR/LjO8DgCwv65YX6cSYn0/Ir1Dp0ZyJkyYgDvvvBM7duxo9xibzYa33noLw4cPx+rVq7scICF9QXzMEAAc7A2l8DRaw9JH80iOyhwlabu2r36Cfd12AEDCvddANzxb0vZ7O07BI/6ea6AdkgWx0YOKv7wPX7V0m7J2x+Wq6qZRnLiYHPB8+KryCJFap0Zyjhw5gueeew6XXHIJVCoVxo8fj5SUFGi1WtTX1+Pw4cPIzc3F+PHj8de//hXz588PV9yERBSN2ogoUz9YHadQU56L1P4XSt6Hv+lyhtIs3Wq8ji37ULdyHQAgdvGlME7uvm0iziSKIhrtXtjLXbCVu2Ara4SjqhEqnQKWZD3MyXpYUvQwJ+ok3MyGHa9WIfHhm1D21FvwFVei4i8rkPLUXVAYu76xZnPSGmh0QvB5wavUXW7zTKIooqoueBk1ISZ8VXmEhEOnXu4xMTF48cUX8cwzz+C7777Dli1bUFhYiMbGRsTFxeGmm27CvHnzMHz48HDFS0jEio8ZAqvjFOorj4QlyQm4XQAAhUaaHasFtwe1738NALBcNhWWS6WP+WyiKKJ4VzXKD9bCUe6CvcwJe4UL9nIXfC6GSyAcYIzTwdSU+JiT9bCkGjBgZioMceHdyVth0CH5j0tQ+sQb8JXVwPr1T4i9YV6X2+XVGgSXNxYRcLskT3JcDVVwe6zgeSViowZI2jYh4RbSdxqtVourrroKV111ldTxENJnxUT1B04F5z+IQgCcxJcFVM2lxja2uTAdce0+CsHphjIxBjESfFifj8/tx5HvirDno+OozWt/jo4+RgNLsi6YwCTp4HP5YStrhK3cBXuFC36PgIbqRjRUN6L8QG3L3218fh8GX5KOsTcNQuKQ8O0BpYyxIG7JAlS+9DEatuxFzHUXg+O7Vv8RnHAsglMooDSwzSXqDFtNHgDAYuoHhULaBIqQcJNh4JYQci5GfSKUSh38/kY02Ephim5/kn8o1DHxAABvnTRl6g3bDwIAjJNHdvmDuj2uKid+/vIg9n+eB7fVCwBQ6ZTIvigFUekGmJINLSMycclqqLTtJ4aiKMJV50VNmbdp9McJe5kLFYdqUX6wDoe/OYXD35xC6tg4ZF0zCmnTM8Arpb9f+tE54HQaBOod8BwvgnZwZpfaa34+VdFxYXkebLVNCwCaMyVvm5BwoySHkB6C43hEmzNQXXcUttr88CU59TUQRaFLa50ILjca958AABgmjZAkvjPV5Fbh2Ce5KNqQDzEQrHYxJ+sx5saBGL4wC1pz2xEFVQfVVRzHwRCrgTLGiKThrauiyg/WYs/HJ3B8fTFK99SgdM8GGJKMGHTtUGRfkQO1SSPZfeNUShjGD0XDlr1o2H5IsiSn+fmVkiiKZyQ5WZK3T0i4UZJDeg+W0k6pdxpmbI9jOI5jiD/alBlMcqrzkZ5x0XmPZSn9DfYbLDlWm6IBXgHR70fAamu5fNUZak0wkbBtz4Xo80OdEgvjwBhwZyUYKYaOy76Hm1rv1RXwC8hdX4ltHxaiaJ+15fYhE4y49NZ4jJ8dBYWSA1B0zvbMPNuGn3bhHHNvJgOLJsehrtKMdR/V4Pv/1MJZ0YC9r+xA7tu7MXZRKqbcnIm4zNZ7b3kDbG+hdQ2tF0WMmjYEDVv2wrXjIFR3XAxOEUw43eg4meLOqqr21QaTHE10fKvfMZ8fvvaPa2yogs/TAJ5TwmJI6fAcZnkdAJD2dcraFpWG90mU5BDSgzRfErDVF3R5tOVsHK+AOioW3roqeOqrQ0pymjm25QIATFOGSbIbtbPeiw9/twen9gRLqxUqDiPnp2DK4gxcNMbd5fZZxSSqcf1DKRh1+0js/7YMWz8oROWJBmz/TxF2fFqMyx8fionXdX2EzTCqP3i9Bv76BjQeLYJ+WGbIbXnqm0ZyouO6HNfZrHXBURyLMQ0KvuP1hQjpaSjJIaQHMemToFBqEfC70WAvg8mSJmn76ph4eOuqgpc4MgeF1EbA5YZzb3DlXtOFXV/9tuaUE+/ftQu1RS5ojEpceEsmJv6mH0zxzaMa3ZfkNFNpFRh/dTrGXZWG/F/r8NO7+TixtQZfPp2L2iIXLnk4BzwfenLHqZQwThwM+6b9sG873KUkJ5yXq2x1BQBoPg7pvWgDEkJ6EI7jYYnOBADY609J3r46KhZA1yqsXIcKIfoDUCXHQNMvoUvxiKKIjx/Yi9oiF6JTdbjro0mYc+/AMxIceXEch+xJsbj1jfGYc/9AAMDPKwqw7+uyLrdtnhxcc8a550TIbYiiAJ89OPrV/NxKyW4NnoOU5JDeKuSRnIceeuict3McB61WiwEDBmDhwoWIielbOxAT0lVqbbAM2O+XfgRDaTAG23Y1hN5I0xwIhUnf5UtVBbvqUHHcAZVOgd9+NAnmeGn31JIKx3GYddcACAERG189iV8+KsSYK1K61KYUm5cK7kZACE7EURpMXW7vbAFf8BzUqKUvTSekO4Sc5Ozduxd79uxBIBBATk4ORFHEiRMnoFAoMHjwYLz66qt4+OGH8fPPP2PoUFolkxBWfNPcB0Fg3N+nExS64MTZQKMr5DZ4fTAREVxdT8J+XRmcRDz6spQem+CcafKNGfjp7XyU5tpRctAGdGF6TsAZfPx4feijVv6m55FXa8AppJ99IAjBCeU8TzMbSO8U8uWqhQsXYs6cOSgrK8Pu3buxZ88elJaW4uKLL8YNN9yA0tJSTJ8+HQ8++KCU8RIS8Zo/UESBbcPJzjid5Jx/88zzttH0oSw4u5bk2KvdyP2hEgAw6Xppy+XDxRCtxohLkgAA2/9z7iovVs1JosIQenLX/Dw2P69SEkWxJdHmOUpySO8U8pn717/+FevXr4fZfHoY02w248knn8TcuXOxbNkyPPHEE5g7d64kgbbn1VdfxV//+leUl5dj2LBh+Pvf/45p06aFtU9C2mApY2UsdW1OcoTA+UdyONaK2DPKihWa4CWSQKOr1e2sbYkiB04fLMEOuDwQxXNfrlIrOh6FOrbyOAS/iIFjjZgwwg/g3POEJmnZ5r+kKtgu15QGOm7PLbRfSXTF4mjs/aoMh74vQ9Y9DdBGdZyknOtxCjg9AABep235PdPzcMbzFnA1bdWh1be6nbmt8xCF0zuK85xC0nOckO4S8kiOzWZDVVVVm9urq6thtwfXyIiKioLX6w09ug588skneOCBB/D4449j7969mDZtGubPn4+ioq59wyJETnzTZYfwXq4KfSSn+fKK6PFB9Ac6OPrcBL+AzZ8E3z/m3JwYcixy6D/SgMzhBvi8IvK/PhZyOwFXU5JjCP1yVThHcoQzRhIVdLmK9FJduly1dOlSrFmzBiUlJSgtLcWaNWtw++23Y9GiRQCAHTt2YNCg0MpUWbz00ku4/fbbcccdd2DIkCH4+9//jvT0dLz22mth65OQcGsZyQlDkqNsTnLcLoii0MHR56bQnx65EBo9IbVR8tMp1Ff5YI5VYvzc3lWcwHEcZt8YrCo7sfoIhEBoj6PQMienZ16uEs4YyeE4afdRI6S7hJzkvPHGG5g9ezauv/56ZGRkoF+/frj++usxe/bsliRj8ODBePvttyUL9kxerxe7d+9uczls7ty52LZt2zn/xuPxwG63t/ohpKdpmXgcCMecnKaKHlEMVuaEgFMqwGmCMQZCnJdT8F2wbPqiaxOgUve+lSwmXxYHg0UBZ3kDqvdVhNSG0DSSo+jCxOPmCeRKXdcrtc7WPJLD8UpJFnwkRA4hj0EajUa89dZbePnll5Gfnw9RFJGdnQ2j0dhyzOjRo6WI8ZxqamoQCASQmNh6qDsxMREVFed+01m+fDmeeuqpsMVEiDSa5jWE4YNFPHPORFc2c2xaIp8LcUE8hTb41uOySz9a1R28bgFed3AEp/m+dFrTYyd2ZbuBpnNEDMtcGEpsSO/X5a9QRUVFKCsrw6lTp7Bx40Z89dVX+Oqrr6SIjcnZ3zBEUWz3W8djjz0Gm83W8lNcXNwdIRLSKS0VLWGYB9EyF4fnwatDu0wi+PwQfU0xhnipZcDCHADA1i9r0NgQ2rweOW1ZXQ2fR0TUwBjEDg1tpeGWKjVXaJf8AGnmWLXndJWfP0xJFCHhF/K7aH5+Pq688kocPHgQHMe1vAiaE4xAILxvXHFxcVAoFG1GbaqqqtqM7jTTaDTQaHrGSqqEtKe5qiqcSY5CG/pCfmeuj8PrQns9JY5PQXKWFuUFbmz9sgZzbuo9k48FQcSGj4Ol74OuHhry4yjFekPNlx/DkuQoTleYCaIfCo72riK9T8gjOcuWLUNWVhYqKyuh1+tx6NAh/PTTTxg/fjw2b94sYYjnplarMW7cOKxfv77V7evXr8eUKVPC3j8h4dKyAJtC+g+V03M4Qp+oKjSVPnNadcvu2Z3FcRxmNyU2Gz6q7FUjBYd+tqGqyAO9SYHMedkht9NcpRbowkiOUoLFHdvD86cnG4djEjwh3SHkr4q//PILNm7ciPj4ePA8D4VCgalTp2L58uX43e9+h71790oZ5zk99NBDWLx4McaPH4/JkyfjzTffRFFREe66666w901IKyzf5hm/8bNermpniZq2zshDAp4zqnHOuJ21LY4TITQGJywrDFpw7SzG4g10/NYy9LKBUP2tBKUnG7HlF6D/hHNXWW13s03ANvNsE6ntQsfbMZT42q/4+ubD4KaVoxemQVDr4GUYtD7X46Qwnh7Jaf490/NwxvOmMASTHL/b2eYrK/P50Y5gRRUHQIQgBiQ9xwnpLiGP5AQCgZZJxnFxcSgrCy6wlZGRgWPHQl87ojOuu+46/P3vf8fTTz+N0aNH46effsJ3332HjIyMbumfkHAI55wcv6s5yQm9GkeQYDsCANCaVBh9WTDh6Orqwd2lvtSFYz8G1/eZ2MVVmqVYObplTo5L+stVHMeFdTkDQrpDyEnO8OHDceDAAQDAxIkT8cILL2Dr1q14+umn0b9/f8kC7Mg999yDwsJCeDwe7N69G9OnT++2vgkJh9NJTvguV3VlXZVAS+lz1/eamnRDMFE4vKES5Ud79pIOoihi0xt5EEVgwORYxGcZO/6j82iekxPoypwcbTBZFf0+CD7pF15tWZhSpCSH9E4hJzn/+7//C6Fp99tnnnkGp06dwrRp0/Ddd9/hH//4h2QBEtLXuF21AACVWvoF3vzOYCKhMIT+Ac03rZHjq7ZCFEJbCK9Zco4Z2ZNiIfhFvHnLdhz/ubpL7YWL3xvAZ388gF2flwAALlyS1eU2fVVWAKcfz1DwGm3Lxpx+p6PLMZ2t+Rx0uc+95QYhPV3I4+Hz5s1r+f/+/fvj8OHDqKurQ3R0NC0cRUiIBMEPe33w0o0lJlPy9r31NQAAtSX0VYb1wzPB69Tw1znQeLwE+sFdu2xzw99G48Nle1C4qx7v370Lw+cm4cLFmUgfFSX7e4nH6ceeL0ux7cNC1J5ygVdwWPjEMORMC61s/Ez2bbkAANMFg0Nug+M4qKJi4K2tgre+Buqo2C7HdSZLdBYanTWotxciPjpH0rYJ6Q6SLjUaExMj+5sSIb2Z3VkKQfBBpTZCZ0iQvP2WJCcm9LZ5tQrGpg9mx9bcLsekj1Jj6VsTMO7KVIgCcPD7Crx+03a8dsMv2PdNGfzero0WhaK+1IXv/noUz8/ehK+fPYzaUy7oLCoseX08JlyT3uX2hUYPnHuCqz6bLhzWpbbU0cGEq/m5lZIlJjj1oN5eKHnbhHSHTo3kPPTQQ8zHvvTSS50OhpC+rq7pw8QSkyX5FwbB74fPFrzsoInp2kiEacow2H88AMcvh5Fw2zxwXVk9GYBSrcDVz4zElJszse3DQuz/thwlB2349NH9WP+SCvNuisec6+NgjgnfRpGiKOLYbie+fa8KO9Zb0by1V2yGHlNuzsTYhanQGKTpv2H3cYheP1TJMdBkJnWpLU1MPBoAeOvabpjcVZaY4GU5h7Mc/oAHSgWtM0Z6l069YlnLwmk0h4QFyxYCUp97jO2JDMeJDPE3f2O2xGdDVJ3/eEHJGFtT/uG11wKiCF6tAW8yhVRi7PUE54+ohwwGp9PAX+eA41AFtDmtKxrLnOYO21IrUtvemJqKnEeHIOPORpz44ihOfH4Y9ZWNWPlSGVb9qxJDLu2HsTcNQtwAS5s/1XBspeYesfUcGL83gOPrirH7oxOoOlLfcnvSBanIuW4YUiang+M5nBAAnDXtheV+Aqcft2bWLUcAAIaJI+DzqpnaaCaelU+qYoMJq6e+utXvmM+P85xnGlUMtPoYuF11qG8oRlz0wPO3xfh6kfQzgrUt1i1Iet8C3OQ8OpXkbNq0KVxxENLnCUIAVkfTfJxY6SsUvXXBSb3qmPguf8hwKiUM44egYcs+NGw/2CbJ6SptjA4jlo7B0MUjYf/pMPZ8dByVh+txcE0BDq4pQMLgKESlGWFK0cOcpIc52YDYZDUsKXpozao29y/gE+CoaoS9ohG1ZR7Yy11NP05UH7PCVResGFNqFBiyIAPpV49GVHZ4dkcXGj1o3HccAGCYNKLL7ambRuW8ddJfrgKC56LbVQervaDDJIeQniZ8Y7+EkE5pno+jVOuhN4VhPs4ZSY4UDJNGoGHLPjh/OYiY6+eC13RuRIKFQqXA0AUZGHJpP5Ttq8Wej47jxMZSVB21ouqo9Zx/o9YrYU7SwZykg9flh628EQ3VjS2Xn87FGK/D6OsHYMRV/aGP1qDczTZCE4qGXw5A9PmhSo6Dul/XLlUBp59Pn7UOYsDfUm0lFUtsf1QW70K9rVDSdgnpDpTkENJD1FlPAgh+qHCcpDUBAAB/Q7B8XGlqe6knFPqRA6CItSBQa0P1q6uQsOz6Ls/NaQ/HcUgdE4fUMXFwVLpQkVsPR7kT9orgiIyjaVTGVeeB1+VHTb4DNfmtry0pVDzMyTqYkgwwJZ8eAbKkGpAyOg4KVXhiP5OnsAy1H64FAJhmjJPkso3SaApeshEF+F0NUJmiutzmmSxxwVFFe0MpfD4XVKrQF5IkpLtRkkNID1FVG5ynEZs4NCztN6+NE3A2SNIep1Qi4Z5rUL58BZw7clH7/jeIvfXysM/JMyXqYUps+0Gr4XzwuQNNiU8j7BUuqPRKWJL1sKToYYjRgOO5NnNyuouvuh4Vz78PsdED7dAsWOZLs8dewOUCmvb+Uuq7tkDhuWj1MTDoE+B0VaG6/hhSEsZI3gch4UJJDiE9gMtdhwZXBTjwiEkaEpY+mr/h+xxWydrUDe2PhHuuRdUrn8C+7lcooi2IXnSRZO13lkqrQGymCbGZJtliOJeAw4WKv6xAwNoAdXoikh6+GZxKmrdff9PzqTCYJL9U1SwhZigKXFWorjtCSQ7pVcI/PksI6VB10yhOlDkjLCsdA6cvU/kdNknbNU4egdjFlwIA6j9ZB8ePeyRtv7cLuH2o+Ou/4SurgTIuCkl/XNKypYMUfE3Pp0qiy5DnEh8TTLxrrScRCEi/fQQh4RJy2n/rrbdi6dKltFcU6TKOtbRTSgrG/F7J+BJRKTo8RDjPnI+q+mCSE58wjLn0F6yHNU24VZuiAQA+uxUIiK0uK/Eetsb8rnM/HoaLpsNb1QDH9z+i+s01UMfdCMOY81fiBAS256BKw3YJRs2z1f56hY6fK4eHLQmpd+rO+3sxEEDZ81/Ac6IYvF6H+GVLAW0s/K5zH69keB64syZQ+21WAMGRula/Yzw/WM43Q1QqtNpouN31qHbkISH+3AsYKhheBwDYX1esr1MJsb4fiVRq3iuEfAY5HA7MnTsXAwcOxHPPPYfS0lIp4yKkz/B4HbDZg6XjcXHhmY8DAEpjsGJI9PsguNv5lO2CqKsvgX7SGEAQUPbip3Cf7NvvCaIoovLNb+DcfRycSon4390KVUqi5P00j8wpJZ5wfCaO4xAfGzw3q2sOh60fQqQWcpLz+eefo7S0FPfddx8+++wzZGZmYv78+Vi1ahV8PrZFuQghQE3NEQAiTKZUaDXhu+TAK1VQNE1M9dmtkrfP8Txib7sG2mEDIbq9KH32I3jLaiXvp7eo/WQT7D/sAXgOsb+9EZqBmWHpp/m5VJnDd+4AQHxTAl5bdxSCQMMYpHfo0lhgbGwsli1bhr1792LHjh0YMGAAFi9ejJSUFDz44IM4ceKEVHESErFqao8CAOLjuraHEYvmycfh2OcICFZcxd29GJr+yQjYnSh+/B24Dp8KS189legPoPKtb1H32Y8AgIQ7F0A/JnzPrdcafC6lLh0/m8XSDyqVAX6/GzZb33pOSe8lyQXP8vJyrFu3DuvWrYNCocCll16K3NxcDB06FC+//LIUXRASkURRaPnAiIkeEPb+9GmZAADHiUNh64PXaZD6+M3QZCYhYHei5Kn3YV23K2z99SQBuxMlT/8btu93AADiFl+MqLkTwtafz2FDY1nw/NGlZoWtHwDgOB4x0dkAACstDEh6iZCTHJ/Ph88//xyXXXYZMjIy8Nlnn+HBBx9EeXk53n//faxbtw4ffPABnn76aSnjJSSiOJ1V8AfcUPBqGI1dX/22I+ahYwEA9uMHIXg9YetHGWVE+rO3wzhlGOAPoOqNr1H6l4/hzi8PW59yEnx+WL/fgcKHX0NjbiE4rRopj96AmEVTw9qv/cheQBShS82EOio821CcyWIObt9htdNIDukdQq6uSk5OhiAIuOGGG7Bjxw6MHj26zTHz5s1DVFRUF8IjJLI1f1iYzengOcbKlC7QpWRAFRULn7UWjhOHYBk2Lmx98Vo1kh+6FnWZSahduRHOncfg3HkMhgk5iP3NDGBEdNj67i6Czw/7hj2oW70F/trgitKqpBikPHoDNP2k35rjbLbc3QAQ1ufxTFGWTACA3V4EQQx0yzlLSFeEnOS8/PLLuPbaa6HVtl9qGR0djYKCglC7IHIIw3YCkmFZSZd1gTXm0nC240Rlx4+beI5y2OaqKktUZsvvmXcHF9kO4/xn/D84RA0Zh+pf1sF2cDeicoIfjgo3W6eCk+1DzcNrWv7fePHF0AwfBdtXG+H8dX9LslMzbjCir54JTf9z7EZ+Bqvq/GXazRSK82xOdYZAoOPnyuc7//0UvD44Nu2G9YufEKgPJjeKaDMsl82Ecdp4QKWCx376eJ7xcWN5HpqfT3dNBdyVpQDPwzJwdKvnGQDz+cFyvjWfm3pzEhQKDQIBDxoaq2AytX7uWF4HANgXQmR5nbK2FejBk6VZ33fPtwEbOaeQk5ySkhJ8/PHHWLp0aavb3333XVRXV+PRRx/tcnCERDpb09wGS1Rmt/VpGRpMchpOHYff6YDSEP7VgVXJCYj77fWwXDEbtq83wrl9H1y7j8K1+yj0jMlOTyB4fXBs3A3rlz8iUB/cG+t0cjNBslWMWdiOBBddNGUNgVIXngUkz8ZxPCyWDNTVHYfNWtgmySGkpwn5a/sbb7yBwYMHt7l92LBheP3117sUFCF9gdttg9ttBcfxMJvTu61fTXQ8dMn9AFGA7djebusXAFTJ8Yj7n+uQ8txDME4bDXAcXLuPovRPr6HihQ/gPlkCUWQcguhGgtsL2/fbUbzsJdSu+AaBegcUMWbELF6E1OcfgWnW5G5NcERRgO1I06Wqod1zqapZc0JOFVakNwj5VVlRUYHk5OQ2t8fHx6O8PDInFxIiJXvTh4TRmAylUtPB0dKyDBmHxvIi1B/YjpjRFwLo3rkVqqR4JNx7DaKunAHrF5vRsGU/XHuOwbXnGBQxZuhGZAd/hg+AKp7tcpWUREGAp6AMjQfz0HjwJNzHigB/8HKHIja4P5dpxlgIfum2Z+iMhsJj8Nnrwas1MPUP3wKS52KxNE0+tlKSQ3q+kJOc9PR0bN26FVlZrcsWt27dipSUlC4HRkikc7mqAQSTnO5mGTIWVVvXwlNTgbq9P8M0S55NNdUpcUi45xpEXzkD9Ws2w/nLIQTq7Gj4cS8afgyOMmkyEqEflQ3DyP7QDc0Ar1GHJRZvRR1cB/LhPJAH18ECCA2NrX6vTIhG1OXTYJox9vSozdnzYLqB4POiYsMaAEDU8AvAq8LzeLTHZAq+v3u9dvj9nm5P0AnpjJCTnDvuuAMPPPAAfD4fZs2aBQDYsGEDHnnkETz88MOSBUhIpHK7rQAArbb7q4yUOgMSp1+O8vWfoerntdCOHQFVN5Qgt0eVHEx2hNuvgPvoKTQeykPjwTx4C8vhOVUJz6lK1H+1DZxSAd3gftAOTIXCYoDCbIDSbIDCooc6SgeFxQBe3fZtTRRFCE43/DYXvPUuBOwuBGxOBOxO+KptcB3Mh6+yvtXfcDoNdMP6t4wqqZLjWu33JZfq7T/Aa62B0mhGwoWXdHv/SqUWSqUOfn8jPG4rlEbpt6ogRCohJzmPPPII6urqcM8998DrDe5Kq9Vq8eijj+Kxxx6TLEBCIlWjO/ihqtXJU0odPXIibId3wVVagKqvVyPl5ttl/xDnNWroRw2EflRwc8+A3QnvkRNw7c+D80A+/DU2uA4VwHWo/apNXquGwqKHwqyH6PUjYHfBb3cBgQ4qUxQ8dIPSoR/ZH5phA6HJTgWn6Fkl0p6KMtTs3AgASJ59FRSa7r+UBwQT84aGRjS662CgJIf0YCEnORzH4fnnn8f/+3//D0eOHIFOp8PAgQOh0dDQJSEsGl3B5fh1OnlGUDiOR8rc3yDv/RfhOn4YDbn7YRo+WpZY2qMwG2CeOgLmqSMgiiJ85bVwHsiHt7QmOBpjdyJgc8JvdyHgcAJ+AYLbC8Htha/S2qY9Xq+BwmyAwqxvGgXSQxFlhC4nHfphmeB1wfevjkrI5SAKAqq++gwQBJgGDId54EjZYtHpYtDQUIZGV9/dm4z0Dl0uBzAajZgwIXzLlpOeieMZvvGzrv3A+G2ZU6k6PoZ1/RslW58i83EM9/WMQ/x+Dzye4O7RemN8q99xjMVFfIDtQIWv/edKb05E/ITZqPp1Haq/WQNT2iAodPp2jxedbM+pn+GtJeBlayugOuN+GtKgm5yGc41fiBAgNrqDiY/DCaHBCU6lhMJsBG8yQGE0BOfStLMwjNcLwNv0j/M8ZmfiPGz3Qcn4uCnOswh1/a5f4C4+BV6tQer0q6DoYB9k1vOD6Xw7K3y9MR6oBlyN1a1+x7pODuvrimM4jvk1r2JbY4a5uk/o+DiOZ+yToS0Smi4lORs2bMCGDRtQVVUFQWj9ZL777rtdCoyQSNY86VilNkKlaj+p6A4J4+fAenIfvLVVqN74DZIW/EbWeELFcRw4vQ68XgdVUpzc4UjKZ7eieuM3AICkKQugDvNmnB3R6+MBAE5ntaxxENKRkNfJeeqppzB37lxs2LABNTU1qK+vb/VDCGmfy1kFADA0fVjIiVcqkXTptQAA697tcBYclzkiciZRFFCxdhUErwfa1AzEjpgid0gwGIJbVjSfx4T0VCGP5Lz++utYsWIFFi9eLGU8hPQJHk9wtVyNNkreQJroM7IRNWYSrHu3o/Tz95Fx2zJoYsO/9xLpWPWm7+A8cRjgFUhacC04Xv6tV7RN563P54QgBMDzPW8OEyFAF0ZyvF4vpkyR/xsFIb2RKAQXWFEoOp5n1F0S5i6CNjUDgrsRJSvfgt/VIHdIfZ5136+o29ZUTXXZddAm9Iw1yPgzzltR7MF7QpE+L+Qk54477sDHH38sZSyE9BmCEPxg4HrQN2BepUbab5ZCZYmBr74WpZ+9B8F7npmwJKwa8o6i4rvPAACxUy+GZeR4mSM6jTtj9/Hmc5mQnijky1VutxtvvvkmfvjhB4wcORKqsypfXnrppS4HR0ikEsTgSA7Pdd9+RyyUBhPSrr8Dp1b8A43FBTj1738i7bo7oDJZ5A6tT7Ht34nybz8BBAHmYWMQd1H3L/p3PhzHA+AAiBAEGZZ9JoRRyO+wBw4cwOjRowEAhw4davU7uRcUI+fAWM7NVBrO2B7rQmrMC64pGO4Da1usZacK1sej4+PEM45pGclRKFvdHjyQrUue8bOF93Z8jPKMHQyUxiRkXv1bnFrzDjwVpSh69/+QceUd0ManBD/XGHBCx89VwMPWmMj6LsX6tsPw+HKMj63Cy9apws3YnktE1bbvUb19PQDAkjMGqXNuAO8+3Q/L8wmwnx8sj0ebc5TjwPMKCIIfghg4/XvW937W1xXL61TB+mQxvgeyvocwlH2zXsljLzVnuA8iW1t9RchJzqZNm6SMo9OeffZZfPvtt9i3bx/UajWsVqus8RDSGc1JDs/1nMtVZ9InZyD7xmUoXP0WvPVVyF/5CtIvvxW6oTlyhxaxBL8f5Ws/adldPH7iHCRceEnTqEnPw/FKQPDTSA7p0Xrmq4eB1+vFtddei7vvvlvuUAjpNLH5chXfsy5XnUkdFYv+N9wPfVo2BK8Hp1a/hfrd29gXSyPM/E4Hij9+I5jgNK1EnTj10h6b4ACnE3Sak0N6si69grZs2YKbb74ZkydPRmlpKQDggw8+wM8//yxJcOfz1FNP4cEHH8SIESPC3hchUustiYJSZ0Dm1b+FZcg4QBRQ+d0qlK3+AAF3Y8d/TJg4C46j4M0X0XgqD7xai8yr7kTMiElyh9WxlktTdHmE9FwhJzmff/455s2bB51Oh71798LjCVZhOBwOPPfcc5IFKCWPxwO73d7qhxA5qDUmAIDX65A5ko7xSiXS5t+IxOmXATwPx+F9KHzrb2gsPSV3aL2aKARQvfE7FH/4BgINDqjjk9D/ht/BmNnzLwkKQgA+rxMAoFabZI6GkPaFnOQ888wzeP311/HWW2+1qqyaMmUK9uzZI0lwUlu+fDksFkvLT3p6utwhkT5K05TkeDy9I9HmOA7xE2Yh49b7oYqKgc9ah1MrXkHtto0QaaJjp/msdSh6/1+o3foDABFRYych8/YHoI1Lkjs0JsHkXATHKaBSG+QOh5B2hZzkHDt2DNOnT29zu9lsDnkS8JNPPhncf+Y8P7t27Qo1ZDz22GOw2WwtP8XFxSG3RUhXqDXBkmyPu3ckOc10qRnIvPNhmIaMAgQB1Ru+QdG/X4Xr1Em5Q+sVAh43arduQMFbf0NjSSF4jRYpV92CpAW/Aa9Syx0es+bzVq0x9eh5Q4SEPOsxOTkZJ0+eRGZmZqvbf/75Z/Tv3z+kNu+77z5cf/315z3m7P46Q6PRQKPRhPz3PZLUbzBSlpozlmwy70LOVE7KWK3EujQ+Y0lsmxLbczV1xjwcbdMQv9djb3U7wL57NO9n3IWcoeRYZC3pBaCEDv3m34L6tO0o37QGjUX5KPr3q9CnZSNh8lwY0geAC3TcHs9Yfi3KUIDGMc6l5TvYCbyF3Y3afT+jdtdmBNwuAIAuqR/SL1sMtSUWCN503l3Imym80p4fLOfb2eeoz2MDEByRPPN3LK+DYIOMx7G8TqV8/wAgBhhHJoWOj+MYRzmZSsMBAAwnJutnQh8ZgQ05yfntb3+LZcuW4d133wXHcSgrK8Mvv/yC3//+93jiiSdCajMuLg5xcZG1ezAh56LRNo3keOwQRbHXrS3FcRxiRk6GMXMwanZsQP2hX+EqyUPhZ69Bn9ofcdPnQp85sNfdL6kFPG7U79yCuh2bWyZrq6PjET9xDqKGjO1RK153RvNIjkZDi0SSni3kJOeRRx6BzWbDzJkz4Xa7MX36dGg0Gvz+97/HfffdJ2WM51RUVIS6ujoUFRUhEAhg3759AIABAwbAaDSGvX9CukKtDp6johiAz+ds+XdvozZHI2XONYi7YDZqdmxE/aHtcJXmo+g/r0OXloW4aXNhyBzU55KdgLsRdbu2oG7HjxBakpsEJEyaA8vgMb02uWnWPJdMozHLHAkh59elRTqeffZZPP744zh8+DAEQcDQoUO7LcF44okn8P7777f8e8yYMQCCixTOmDGjW2IgJFQ8r4RabYTX2wC329prk5xmwWTnasRPnI3qHRtRf3A7GksKUPyfN6BNTkfclDkwDhzWI3bQDid/gwN1u35C/e6tEDzBZY7VsQlImHgxLDljIub+u91WAICakhzSw4Wc5Dz99NNtbvv+++9b/j/US1asVqxYgRUrVoS1D0LCyWBMhrfuBOy2YpjNaXKHIwmVKQops69CzLTZqP1lI6z7tsNdXoySz9+DQm+EadBwmHJGwJA5EFD13IUQO8Nnr4fj2CE4jh+Eqyi/Za6DJi4JsRdeDPOQUVD6IiO5aWa3FwEAjKZkmSMh5PxCfpdZs2ZNq3/7fD4UFBRAqVQiOzs77EkOIb1dVHQW6utOwGYtQFr6ZLnDkZTKZEHS3CsRd+Ec1O3cgvo9WxFwNcC6bzus+7aD12hhGDgEpsEjYBg4BLy6dxUEeGoq0XDkIBqOHIS7vHWVpi41A7GTZ8M4cGhEVh653Va4G+sBcLBYMuQOh5DzCjnJ2bt3b5vb7HY7br31Vlx55ZVdCoqQviAqKhMAYK0v7JWTj1koDSYkzLgU8dPmwnkqD45jB+E4fhABpwOOQ3vhOLQXnEIJfXZOMOHJGQqlvudduhNFAZ7yUjiOHETD0YPw1lSe8VsOurRMmHJGwDRoBNTRsbLF2R1s1kIAgMmcAqWydyWnpO+RdLzYbDbj6aefxmWXXYbFixdL2XTfJOG3QNbdxZl3IWco25R0d3HGPpnbkrjU9ewS23Mec1aprtmQCp5Xwut1wN1QA70+WFnIsZb+MpYvM5WQS7iDN3CuEmwlopJyEJWUA3H6VXCVF8GefwD2kwfhtdbCeTwXzuO5AACVKRqauCRoY5OgiUuCOiEZmtiEjteRkeA+iKIIf4MdnqoKeGrK4a6tgKemAp7aCgi+0w8kxytg6DcQluwRMPUfBpXhjLkprrbtMj9XTCXkbG2x9slyvp157lrrCgAAUZasNuc0y+sgeKCErz+Jl6pg3q1c6Lg91u1bOJbScIDphSoy7I4e7LRvlJpLflHcarXCZrNJ3SwhEUehUMFsSoPVVgirtaAlyYl0HMfDkJIJfXomEqdfDk9NOewnD8J+4hDc1aXwOerhc9SjoeDImX8FdVQsNPHBxEdliYFCowOv1oBXa8FrtFBomv5frWk1wVcURYgBPwSPG4LXjYDH0/T/HgheN/yNTnhrq+CuKYenugKC59z7cvEqNYxZQ2AeMBym/kOh0OiY19OJJFZrU5ITlSVzJIR0LOQk5x//+Eerf4uiiPLycnzwwQe45JJLuhwYIX1BVFRWU5JTiJSUCXKH0+04joM2PgXa+BQkTJ6HgNsFd9PISfC/5XDXVCDQ6ITXWgOvtQaOE4c6blelhkKtgRgIIOD1AJ3ZKZvjoYmOgyYuuWU0SRubBHV0XK8v/e4qr7cBLlc1ACCK5uOQXiDkJOfll19u9W+e5xEfH48lS5bgscce63JghPQFUVGZwCmg3poPURQicqJqZyi0ehjS+sOQdnrVdEEB+J2O4GWjmgq4q8vhb7BD8AZHYwJed8vIjBjwAwBEnxd+X9vrOsGRnzNGf5r+q46JhzYuCZq4ZKhjEqDkIqPyS2r19fkAAIMhCSqVXuZoCOlYyK/kgoICKeMgpE+yWDKgVGrh8dhQV5+H2JiBcofUIykNJigNJhgyzvP4cIDg97ckP4LHDU6hDCY1Gi14tTqYRLJMWeiDl6FYlJfvBgDExfb8ndIJAcIwJ4cQwk6hUCMpcQxKSn9BaemvlOR0Ea9UglcagR5YodXbuVy1qKs/AYDrk5dWSe8UcpLz0EMPMR/70ksvhdoNIREvNfUClJT+gpqaI3C7rVDqIrsEmfROpWW/AgBiYwZCp4uRORpC2HRpnZw9e/bA7/cjJyc4dHn8+HEoFAqMHTu25bhIXPuDECkZDInBCcjWApSV7US/aJq4T3qWQMDXcqkqNXWizNEQwi7kJOfyyy+HyWTC+++/j+joaABAfX09brvtNkybNg0PP/ywZEFGHDnWv2FdI4IxNqb2GPtkj43hvrI+tqzrAUnpPOtXpCZPDCY55buQPmgOeIYqHt7Htn6FQsL9kjjGJTMEP8N6HoxPu8i6nAfr0isMc3JY7ydrCTnvY1u7RMGwto3Cw7qOEtudOHutm3OpqjwIv78RGk0UYqMHnfdclhTL65T1Nc+65hXj+xHLejSs6waxrm3DMYXGdlL2lfV0Qn73+9vf/obly5e3JDgAEB0djWeeeQZ/+9vfJAmOkL4iPm4I1CojvF4HaqsOyx0OIa00X6pKTR7f5ysASe8S8tlqt9tRWVnZ5vaqqio4HI4uBUVIX8PzSiQnjwcAlBZtY14plZBwc9hKYHcUg+P4lnOUkN4i5CTnyiuvxG233YZVq1ahpKQEJSUlWLVqFW6//XZcddVVUsZISJ+QmjwBHKeArb4AtVW5codDCERRwMmjXwMAEuJHQKM2yRwRIZ0TcpLz+uuvY8GCBbj55puRkZGBjIwM3HTTTZg/fz5effVVKWMkpE/QaqPQL30aAODk0a8R8DNsZERIGFWW7YHdego8r0J21ly5wyGk00JOcvR6PV599VXU1ta2VFrV1dXh1VdfhcFgkDJGQvqMzH4zoNXFwOO2oTBvg9zhkD7M53Ui/9haAEBW5mxotVHyBkRICLo8g8xgMGDkyJEYNWoUJTeEdJFCocKAwZcDAEpP/Qyno0LmiEhfVXDiv/D5nNAbE5GeOkXucAgJSZdWPN6yZQveeOMN5OXlYdWqVUhNTcUHH3yArKwsTJ06VaoYew+Jqw6YysOZyycZj1NIWI7JWqbNupaSlH1KjaEMl2Ms2YyPHYy4+KGoqT6ME4e/wJhx/3PO9aZExrJkpppp1qYEtsdX8HfcoNQl5FKSvISc9Thvx4+bgvF5Zy1b589x7tpsRSgv2QkAyMlZCAV4trJxhteB5OR4n2Htl7Ut1vddlvOI5fUOgOPZTnJJS81lKDMP+e3j888/x7x586DT6bB37154PMH5Aw6HA88995xkARLSFw3MuRw8r4LNWoiK8j1yh0P6EEEI4PiRLwCISEoei6joLLlDIiRkISc5zzzzDF5//XW89dZbUKlULbdPmTIFe/bQmzIhXaHVRiGz/2wAQN6JtfB5nTJHRPqK0pLtaGgoh1KpQ/bA+XKHQ0iXhJzkHDt2DNOnT29zu9lshtVq7UpMhBAA6f0uhN6QAJ/PiaNHVkPsoSuKksjR0FCB/JP/BQD0HzAPajVtdEp6t5CTnOTkZJw8ebLN7T///DP69+/fpaAIIcEFAocO+w04ToGa6sPIa/rwISQcPG4bDuxdAUHwITpmIFJSaadx0vuFnOT89re/xbJly/Drr7+C4ziUlZXho48+wu9//3vcc889UsZISJ9lMqdi8JDg4prFp35CSdE2mSMikcjvd2P/vhXweGzQ6+MxbPh1tH0DiQghV1c98sgjsNlsmDlzJtxuN6ZPnw6NRoPf//73uO+++6SMkZA+LSllLNweGwry1uHE8W+g1piRkDhc7rBIhBAEPw7u/xDOhgqo1SaMHHMbVGpaDoREhi6VkD/77LN4/PHHcfjwYQiCgKFDh8JojNBruDLsHM7SJ3NbrLuVs+5YzXAc8zdBqUs7pcS4hxTLbsMsuz0DAHeO8uvMtIvgbbSitGwHjhz6BBqFAeYE1svCDHN5GLfwZi0h5xVS7kLe/c87a7k/awk563PPM5TeM5eGs5TxiwKOHloFa30eFAo1Ro1YAr0qCjjrb5nPXdY91+TYm03i9xmW9zeR8f2UebdylvcZxteyKDDGJmWpuQw7mof0ye3z+TBz5kwcP34cer0e48ePxwUXXBC5CQ4hMuM4DoMGXoG42CEQRD8OHPoAzoYqucMivVz+if+ismo/OI7H8GE3wWRKkTskQiQVUpKjUqlw6NChcy5QRggJD47jMWzodTCb0+H3N+LAnnfhcdvlDov0UiVF21Bc+CMAYHDOVYiNGShzRIRIL+RrMLfccgveeecdKWMhhHRAoVBj5PBboNPFwuO2Yt+uN+FurJc7LNLLlBRtxcmjXwEA+mddjOSksTJHREh4hDwnx+v14u2338b69esxfvz4NvtWvfTSS10OjhDSllptwOiRt2HP/rfR6KrB3h2vY+T422EwJMgdGunhRFHEqfwNKMz7AQCQ1u9CZPSbIW9QhIRRyEnOoUOHMHZsMPs/fvx4q9/RZSxCwkuni8HYC+7G/t3vwOWswr4db2DkuNtgMqfJHRrpoURRQN6xb1FStBUAkJk9Bxn9Z4Nj3QONkF6o00lOfn4+srKysGnTpnDEQwhhpNFaMHrCb3Fwz3tw2Euwb+dbGD56MaJjB8gdGulhBMGPY4dXo7IsuOXOgJzLkZZxYdNvKckhkavTSc7AgQNRXl6OhITg0Ph1112Hf/zjH0hMTJQ8uG7D8ZKUiEtZGs7cnlxl2lLuCM5ati4H1lJXoeOSR461ZDPAVj7J+wAtp8OYUUtx4OAHsFoLsH/3O8jMnInMjJng+eYabZbdgZm6ZN6dm6U8nLHSlXlXZdb2mJqTcIN3oGvLB5ztXLuGn/M4X/DJcrlqcCh3JRoaysBxPAYPvio4B6fp9yznG2tJPcvrAIA8JeSsmJfRYLivcrzvMn++sJaGS9eepDuag2d6nXb60+XsOv3vvvsOTidtHkiIXJRKLUaNvBXJyeMAiCgs3Ih9+96B222TOzQis/KKvdi5659oaCiDSqXHyBG30CRj0qf04K/QhBBWCoUKQwZfjaFDr4NCoYHVVogdO/+BmpojcodGZOD3e3D4yGc4cuQzBAJeREX1xwUTfofY2EFyh0ZIt+p0ksNxXJuJxd090biwsBC33347srKyoNPpkJ2djT//+c/wer3dGgchPU1S4ihMmHAfTKbU4Fo6Bz/AscOr4fd75A6NdBNrfSF2/fIPVFTsBcAhK2sOxoxeCo3GLHdohHS7Ts/JEUURt956KzQaDQDA7XbjrrvualNCvnr1amkiPIejR49CEAS88cYbGDBgAA4dOoQ777wTTqcTL774Ytj6JaQ30OtiMW7sb5GXvw7FxT+jvGQH6mqOY/Cwa2hScgQLBHwoOPlflJzaCkCERmPBsKG/QVRUltyhESIbTmTZDOMMt912G9Nx7733XkgBheqvf/0rXnvtNeTn5zP/jd1uh8ViwQzuSig5VZdj6NETjxWMfSoYNxRiOI5TMebQSsbjWGJTMz6PjLGJKrbHg+U4Uc3Wp6Bie65EZcfH1dfn48ix1XA31gEAUtIno//AS6BUalr3ybDXVLBPxuNY9q5innjMdlhfnnhssxbh6KFP0eiqAQAkpY7HoP6XQqnUMvTZ8YTR5knMHbbl9bMd52Pb9IvpOB9bn/D62I4LMG5I5u+4X5E1NsY+RZbjGAsXWPeHYp4szNAec1sM/KIPm8U1sNlsMJvbH6Xs9EhOdycvrGw2G2JiYuQOg5AeJTq6P8ZPXob842tRVrIdZcW/oK7mGLIHXYq4hKHsm6iSHsnracCpgk0oLdoGQIRaY0bO0KsQGz+YOTEhJJJ1aRfyniIvLw+vvPIK/va3v533OI/HA4/n9NwEu532/SGRT6nUYNDQRYhLHIZjuZ/D3ViH3P0fwmhKRmb2xYiNHwLm4RLSI3i9ThQX/oTSom0QhOAIRWLyWAwYfBlUKr3M0RHSc3T6clU4Pfnkk3jqqafOe8zOnTsxfvz4ln+XlZXhoosuwkUXXYS33347pPZZLldJeelI0stajG1JeRkqeFzHsXFSXoYC2C4xSdynqGY8jqVfhstLACCwXiJjvnR0ul+/342i4i0oLtmGQCCY8JuMqcgaMAcxsTkdFhEwX9Zier0wNcV8jkt6uYp5iJ6xT8b2OloDx+dzobhgC0pKtyEQCBZamExp6J91cZsNNlnXW2K6RMZ4eQkMl76CfTJe1vKyXJ6R7vISAPbLXwz9iqx9sl5iYumT9fGQ8DJU8DCG9iRsi/VyVY9KcmpqalBTU3PeYzIzM6HVBq8zl5WVYebMmZg4cSJWrFgBvoNFnM41kpOenk5JzpkoyWkl0pKcZj6fC0XFW1BS8gsCQvDD0mxOR1b2HETHDGw32aEk5+xOGfvsYpLj8zWipOhnFBdtbUlOjcYU9M+cg9h2klNKcs5CSU5rfSTJ6VGXq+Li4hAXF8d0bGlpKWbOnIlx48bhvffe6zDBAQCNRtNSFUZIX6ZS6ZHdfx7S0y4MJjul22G3F2P/3vdgtmQgq/+s8yY7pHv4fI0oKd6KkqKt8PvdAACjIQlZmXMQFzeEnh9COtCjkhxWZWVlmDFjBvr164cXX3wR1dXVLb9LSkqSMTJCehe12ogB2fORljkNRad+RFnJr7DbTmH/3vdgMqchJfUCJCSObFONRcKroaEC5WW7UFG2uyW50RsSkNV/DhJiaMI4Iax6ZZKzbt06nDx5EidPnkRaWutdl3vQ1TdCeg2NxoSBgy5Dv4zpKCr8EWWlO+Cwl+CYvQQnjn2NhMQRSE4ZD1NsFo0ehInP50JN6T6Ul++Gw17acrvekIDMrNlISBwOjuOZLi8RQoJ61Jyc7taZdXJoTs7Zx9GcnFbH9bI5OR215fE4UFG+B+Vlu1rWXgEArS4WSanjkJQ6Dhqtpf32aE5O6z7baU8UBdTX5qGidBdqqnIhCsE5HBzHIy5uCJJSxiE2LqfVyA1rkkNzcs5Cc3Jaozk5hJC+SqMxISPzIvTLmA67rQjlZbtQVXkA7sZaFJ5ch8KT6xEdOxBJqeMQlzAUvKLri2n2JY2uWlSU7kZl2W54zthI1WBMQnLKOCQmjYZabZQxQkIiAyU5CI6sdDgEL+U1cNa2mL4Ns359lfY4SecEsMbG8k2B9dsJz3gc4xcsTmBZ7ZOxLT/zEAfjcQwdtzMMwgGIMqQjamA6BvVfgKqaXJSX74LVVoj62uOorz0OnlfCYslETHQ2oqOzYTKlAEqGFaCZz0kZBpuZVzxmO9DvdqHemof6ujzU1+fB1Xh6dEyp1CIxcRSSk8bBZEg5/V7UzmJ+rJVazCM+LKMvDOc3wPY6CLbHdhhYHl/W1zzrcRJejmV9nxSZl86W8DOB+e2D9UCGESTmqx0dnyCcyDF1SUkOIYSJQqFGcvJYJCePhctVi/KK3aio2AuPx4b6+pOorz8JAFAqdYiO7o/omGxExwyATh/X5+bxBAI+2KynUF8XfFwc9jK0zpw4REdnIyV5HOLihkLRPBIm4bL3hBBKcgghIdDrY5Hdfy76Z10Mp6sK9fV5wQ90awH8/kZUV+eiujoXAKDRWBAdMwBmSzpMphQYjEmnP9QjhMdjh8NRBoe9FNb6AthtpyAIredj6PXxTaNdAxAVlQWVSidTtIT0HZTkEEJCxnEcjIZEGA2JSE+bAkEIwOEoRZ0tH/V1J2GznoLHY0NF+W5UlO9u+hseekMCjKYUmMypMJpSYTQl94oydVEU4XbXo8FeBoejFA32UjQ4yuD1NrQ5VqMxt4xmxVj6Q6Npf6I2ISQ8KMkhhEiG5xWwWPrBHJOBzKyZCAS8wcs29Xlw2MvQ4CiDz+eEs6ECzoYKVJbvafpLDjp9LIymZGi10dBozdBooqDRWqDRWqDWGLttbZhAwAtPow0etw0eT/C/brcNjY01aLCXtqxb0xoHvSEeJlMKzJZ0xMQMbHWZjnUXckKItCjJIYSEjUKhRkzsQMTEBvdVEkURHo8NDnsZHA1lLSMiXo8dja6aVuXqZ+I4HmqN+XTSozKAV6jA8yrwChUUvBK8Qg2eV0GhULbcLooChIAPguBDIOCDIPghBLwICD4IAX/wdr8HHo89mNS4bfD7G897nzhOAYMxEUZTCsymFBjNqTAak6BQqCV//AghXUNJDiGk23AcB602ClptFOISh7Xc7vU2oMFeBqezstUISvD/7RBFAR63FR63tVviVCjU0GijoNFYmkaVLNDqomE0pcBgTATPB986WaurCCHyoCRHQsyL/EnaJy3vHhLGDyfWkliW8nAuwHp+MC7mxYhjWCWPafE+ACLjBp0s9/XMsLTQQWvORpw5u81xgijA52uAuyn5cXuCoy2BphEaQfA3jcz4gv89Y5SG4/imUR0lFPyZIz8q8LyyaeRHDY3aFBwl0lig1Vig4NXtV4T5gebniLm6nfV8Y7isxVpCDsZLZBzD4nHMl9ukLjWnJLLTWD8TmBcNZO6X4TUvQ/UgJTmEkB6N5xXBEZXunLhLH66ERAQaBiCEEEJIRKIkhxBCCCERiZIcQgghhEQkSnIIIYQQEpEoySGEEEJIRKLqKiC4M2oHq6kylYdLubs4IOluuGAtNZehDF5SrFt9M5RVA2DeMJGlxFbkGMtrmb97MJaAigztsZaGC4yl5gznLvPpLcfmnqzVVRLvVs7Sr+Tl3CztSdkWwL4RKcvjxvqa78lY33dZXsuspeEy7FbOsrs4AIhMO5+zBUYjOYQQQgiJSJTkEEIIISQiUZJDCCGEkIhESQ4hhBBCIhIlOYQQQgiJSJTkEEIIISQiUQk5guXh7e443NPJFbeUpeYSltcyt8VawspLGBtreS0Yy3UZy+BZqk5Z22I+3yRd/kC6pphJXJUsZQk58+7iUu70zXruSnk/AbbXqdR9Srk5K+v7pJQbgvfWz7IzsCzZwvqeRSM5hBBCCIlIlOQQQgghJCJRkkMIIYSQiERJDiGEEEIiEiU5hBBCCIlIlOQQQgghJCJRkkMIIYSQiETr5LDiGPJB1jURGNcx4HjKQcNGZFxDRJBuzQnmlljXv1EwnkdM6wuxnWsi87nLdBgbCZ8DZlKulQIwr7vD9FxJuf4NAI5lDRzWxyPA+rpivQ8SL1hEWrB+voiszxVLcwLjG4OEzzt9ihJCCCEkIlGSQwghhJCIREkOIYQQQiISJTmEEEIIiUi9Nsm54oor0K9fP2i1WiQnJ2Px4sUoKyuTOyxCCCGE9BC9NsmZOXMmPv30Uxw7dgyff/458vLycM0118gdFiGEEEJ6iF5bQv7ggw+2/H9GRgb++Mc/YtGiRfD5fFCpVDJG1kMxlv4yExhKShlLnJnLSVnuA0tcAHt6z9oex3Aca3mtgi04LsDWHFNFusjWGMd6HklZ9i31uctC6hJy1vaYSsjZmmIqR2ftk/XcZe2T9XXF9HhI2BbA/n7E1JbE55Ecr4VertcmOWeqq6vDRx99hClTppw3wfF4PPB4PC3/ttvt3REeIYQQQmTQay9XAcCjjz4Kg8GA2NhYFBUV4csvvzzv8cuXL4fFYmn5SU9P76ZICSGEENLdelSS8+STT4LjuPP+7Nq1q+X4P/zhD9i7dy/WrVsHhUKBW265BeJ5hiQfe+wx2Gy2lp/i4uLuuFuEEEIIkQEnni8r6GY1NTWoqak57zGZmZnQarVtbi8pKUF6ejq2bduGyZMnM/Vnt9thsVgwS30tlFwH83h66rYOrNdoFQq24xjvA8fyeDDOLZH0PrBuhcH6XPGMjxvLfWW+n9I+bkxbMbB+3WG9D1LOHaA5Oa1Fwpwc5u0fGOaKsc57YZ1rE2Cd7Cbd4yYybzPD0qeE8aMT2zpIOn+q4z79og8bvZ/BZrPBbDa3e1yPmpMTFxeHuLi4kP62OVc7c84NIYQQQvquHpXksNqxYwd27NiBqVOnIjo6Gvn5+XjiiSeQnZ3NPIpDCCGEkMjWK5McnU6H1atX489//jOcTieSk5NxySWXYOXKldBoNJ1vkOM6vhzFenmDhA/TbtqsQ9eMfXKsQ9wMx0h9DjFf9mQ4jnXnc/at1Ds+pEfNCAyRxJtks+0YL0eZtoSXUwD2XaZZ2pPyshwJL9b3QKbdytna6pVJzogRI7Bx40a5wyCEEEJIDxYJ36UIIYQQQtqgJIcQQgghEYmSHEIIIYREJEpyCCGEEBKRKMkhhBBCSETqldVVPZaUKxmztsfalhzkKNmUa6VallpiprJIxrYA9pWAWeq+Wc9dth7ZSkWZy/gjYMVjKXejlrpkuptXqmXuk/W4nrw6tRxYPxMYlwVg/bxiWhlZhsesB39CEkIIIYSEjpIcQgghhEQkSnIIIYQQEpEoySGEEEJIRKIkhxBCCCERiZIcQgghhEQkSnIIIYQQEpFonRzSe7CswyD1ukGs64Mwdcu4hgjzejqssUm3Tg4zlrV5pMa8blAvX7+JtS1J1+aReP0b5nV3JFwnh3FdGBJZaCSHEEIIIRGJkhxCCCGERCRKcgghhBASkSjJIYQQQkhEoiSHEEIIIRGJkhxCCCGERCQqIe/tWMsiWUurWStF+Y4P5FhLoaVMtSV/PFgfEAnLtHnGkljW9pieBwnL0QFpS6blKA2Xo8wc6Lll31KWfEt9HPNrVOLYGB4TkfU5kPLxpVL5VmgkhxBCCCERiZIcQgghhEQkSnIIIYQQEpEoySGEEEJIRKIkhxBCCCERiZIcQgghhEQkKiEHgmWxUu/CTCKDHKXErBWgzJuVBzo+hvX8Z2iKGSfxbutyYC0RlrRPiR8PlvJlOUrDSd/FslQFy7IdoJEcQgghhEQoSnIIIYQQEpEoySGEEEJIRKIkhxBCCCERiZIcQgghhEQkSnIIIYQQEpF6fQm5x+PBxIkTsX//fuzduxejR4+WOyTpsJRZRkLpO+sOvD15t3I5SmIDUu5WLvEu5CxYStv7Gkl3IZehLcnL2xlepzLsLh4R+kgZf68fyXnkkUeQkpIidxiEEEII6WF6dZKzdu1arFu3Di+++KLcoRBCCCGkh+m1l6sqKytx55134osvvoBer2f6G4/HA4/H0/Jvu90ervAIIYQQIrNeOZIjiiJuvfVW3HXXXRg/fjzz3y1fvhwWi6XlJz09PYxREkIIIUROPSrJefLJJ8Fx3Hl/du3ahVdeeQV2ux2PPfZYp9p/7LHHYLPZWn6Ki4vDdE8IIYQQIjdOFHvOFOuamhrU1NSc95jMzExcf/31+Prrr8GdUTUSCASgUChw00034f3332fqz263w2KxYJbuOig5dZdiB8Bc6cSxVuxI2CdzlRBzex0fxzFvwMiIpbKHNX6pHzcp+5S6Yk7K9qSsriJtUXVVa728ukpk3cCVtU+W+8BaOSrxcyVK+Vwx8ItebGz8BDabDWazud3jelSSw6qoqKjVfJqysjLMmzcPq1atwsSJE5GWlsbUjs1mQ1RUFKZrr4KSU3U9sL6U5DAcR0lOiH1KnUdQktN79NgkR4Y+gb6T5Eh5H/pMkuPDT+7VsFqtsFgs7R7XKyce9+vXr9W/jUYjACA7O5s5wQEAh8MBAPjJvVq64AghhBDSLRwOR+QlOVJJSUlBcXExTCZTy6Uvu92O9PR0FBcXn3cILFL0tfsL0H2m+xy5+tp97mv3F6D73HyfRVGEw+HocJ28iEhyMjMzEcpVN57n2x35MZvNfeYEAvre/QXoPvcVdJ8jX1+7vwDdZwDnHcFp1qOqqwghhBBCpEJJDiGEEEIiEiU5Z9FoNPjzn/8MjUYjdyjdoq/dX4Duc19B9zny9bX7C9B97qxeWUJOCCGEENIRGskhhBBCSESiJIcQQgghEYmSHEIIIYREJEpyCCGEEBKRKMlh4PF4MHr0aHAch3379skdTlhdccUV6NevH7RaLZKTk7F48WKUlZXJHVZYFBYW4vbbb0dWVhZ0Oh2ys7Px5z//GV6vV+7QwurZZ5/FlClToNfrERUVJXc4YfHqq68iKysLWq0W48aNw5YtW+QOKax++uknXH755UhJSQHHcfjiiy/kDimsli9fjgkTJsBkMiEhIQGLFi3CsWPH5A4rrF577TWMHDmyZUG8yZMnY+3atXKH1W2WL18OjuPwwAMPdOrvKMlh8Mgjj3S4dHSkmDlzJj799FMcO3YMn3/+OfLy8nDNNdfIHVZYHD16FIIg4I033kBubi5efvllvP766/jTn/4kd2hh5fV6ce211+Luu++WO5Sw+OSTT/DAAw/g8ccfx969ezFt2jTMnz8fRUVFcocWNk6nE6NGjcI///lPuUPpFj/++CPuvfdebN++HevXr4ff78fcuXPhdDrlDi1s0tLS8Je//AW7du3Crl27MGvWLCxcuBC5ublyhxZ2O3fuxJtvvomRI0d2/o9Fcl7fffedOHjwYDE3N1cEIO7du1fukLrVl19+KXIcJ3q9XrlD6RYvvPCCmJWVJXcY3eK9994TLRaL3GFI7oILLhDvuuuuVrcNHjxY/OMf/yhTRN0LgLhmzRq5w+hWVVVVIgDxxx9/lDuUbhUdHS2+/fbbcocRVg6HQxw4cKC4fv168aKLLhKXLVvWqb+nkZzzqKysxJ133okPPvgAer1e7nC6XV1dHT766CNMmTIFKpVK7nC6hc1mQ0xMjNxhkBB5vV7s3r0bc+fObXX73LlzsW3bNpmiIuFms9kAoM+8dgOBAFauXAmn04nJkyfLHU5Y3XvvvViwYAHmzJkT0t9TktMOURRx66234q677sL48ePlDqdbPfroozAYDIiNjUVRURG+/PJLuUPqFnl5eXjllVdw1113yR0KCVFNTQ0CgQASExNb3Z6YmIiKigqZoiLhJIoiHnroIUydOhXDhw+XO5ywOnjwIIxGIzQaDe666y6sWbMGQ4cOlTussFm5ciX27NmD5cuXh9xGn0tynnzySXAcd96fXbt24ZVXXoHdbsdjjz0md8hdxnqfm/3hD3/A3r17sW7dOigUCtxyyy0h7fIul87eXwAoKyvDJZdcgmuvvRZ33HGHTJGHLpT7HMk4jmv1b1EU29xGIsN9992HAwcO4D//+Y/coYRdTk4O9u3bh+3bt+Puu+/GkiVLcPjwYbnDCovi4mIsW7YMH374IbRabcjt9LltHWpqalBTU3PeYzIzM3H99dfj66+/bvXGGAgEoFAocNNNN+H9998Pd6iSYb3P5zqRSkpKkJ6ejm3btvWaYdHO3t+ysjLMnDkTEydOxIoVK8DzvS/3D+U5XrFiBR544AFYrdYwR9d9vF4v9Ho9PvvsM1x55ZUtty9btgz79u3Djz/+KGN03YPjOKxZswaLFi2SO5Swu//++/HFF1/gp59+QlZWltzhdLs5c+YgOzsbb7zxhtyhSO6LL77AlVdeCYVC0XJbIBAAx3HgeR4ej6fV79qjDGeQPVFcXBzi4uI6PO4f//gHnnnmmZZ/l5WVYd68efjkk08wceLEcIYoOdb7fC7NObDH45EypLDqzP0tLS3FzJkzMW7cOLz33nu9MsEBuvYcRxK1Wo1x48Zh/fr1rZKc9evXY+HChTJGRqQkiiLuv/9+rFmzBps3b+6TCQ4QfBx603tzZ8yePRsHDx5sddttt92GwYMH49FHH2VKcIA+mOSw6tevX6t/G41GAEB2djbS0tLkCCnsduzYgR07dmDq1KmIjo5Gfn4+nnjiCWRnZ/eaUZzOKCsrw4wZM9CvXz+8+OKLqK6ubvldUlKSjJGFV1FREerq6lBUVIRAINCy9tOAAQNazvPe7KGHHsLixYsxfvx4TJ48GW+++SaKiooieq5VQ0MDTp482fLvgoIC7Nu3DzExMW3eyyLBvffei48//hhffvklTCZTy3wri8UCnU4nc3Th8ac//Qnz589Heno6HA4HVq5cic2bN+P777+XO7SwMJlMbeZYNc8V7dTcK0lrvSJYQUFBxJeQHzhwQJw5c6YYExMjajQaMTMzU7zrrrvEkpISuUMLi/fee08EcM6fSLZkyZJz3udNmzbJHZpk/vWvf4kZGRmiWq0Wx44dG/GlxZs2bTrnc7pkyRK5QwuL9l637733ntyhhc3SpUtbzun4+Hhx9uzZ4rp16+QOq1uFUkLe5+bkEEIIIaRv6J0TEAghhBBCOkBJDiGEEEIiEiU5hBBCCIlIlOQQQgghJCJRkkMIIYSQiERJDiGEEEIiEiU5hBBCCIlIlOQQQgghJCJRkkMIIYSQiERJDiGkxYwZM/DAAw9EdL+1tbVISEhAYWFht/QXTtdccw1eeuklucMgpMeiDToJ6SM4jjvv75csWYLVq1dDpVJ1U0TyWL58OS6//HJkZmZ2+m9vvfVWJCUl4S9/+Yv0gYXgiSeewMyZM3HHHXfAbDbLHQ4hPQ4lOYT0EeXl5S3//8knn+CJJ57AsWPHWm7T6XSwWCxyhNZtGhsb8c477+C7777r9N8KgoBvv/0WX331VRgiC83IkSORmZmJjz76CHfffbfc4RDS49DlKkL6iKSkpJYfi8UCjuPa3Hb2ZaMZM2bg/vvvxwMPPIDo6GgkJibizTffhNPpxG233QaTyYTs7GysXbu25W9EUcQLL7yA/v37Q6fTYdSoUVi1alWnYv3+++/x/7d3dyFNd3EcwL+bmZqY5azQEhJBc8zAZopl2Ys2El+IFDIVQe2iizLFoosKqouQyi4yoixEMiq7kCZWEhXlS+LMkbYs1FyiDaSs1JxZ7TwX0R6Xc84In6f5/YDgzjm/3/l79+XvORoVFYUFCxZAJpMhPj4eXV1dFmuGhoaQlpYGd3d3+Pj44MyZM1P+2uvOnTuYM2cOIiMjzWOJiYmQSCRWv8YHmvr6ekilUkRERNhdMxMSExNx7dq1Gd2T6G/BkENENpWVlcHb2xtNTU3Ys2cPdu/ejZSUFKxZswYtLS1QqVTIyMjAyMgIAODQoUMoLS3F+fPnodPpkJeXh/T0dDx69MjuPT9//oz8/HxoNBrcv38fUqkU27Ztg8lkMq/Jz89HfX091Go17t27h9raWrS0tNjs+/jxY4SFhVmMlZaWwmAwoKOjAwBw+/ZtGAwGGAwGxMXFmdep1WokJCRAKpXaXTMTwsPD0dTUhC9fvszovkR/BUFEs05paanw9PScMB4dHS1yc3MtPkdFRZk/f/v2Tbi7u4uMjAzzmMFgEADEkydPxPDwsHB1dRUNDQ0WfbOzs0Vqauqkz/Prvr/q7+8XAERbW5sQQojBwUHh7Owsbt68aV7z8eNHMW/ePJt9kpKSRFZWltW5hoYGIZFIxODgoNX5wMBAoVarp1Uz3vr160V3d/eE8b6+PrFz584p6yfz7NkzAUDo9frf7kHkqHgmh4hsWrlypfl7JycnyGQyhISEmMeWLFkCAOjv78eLFy8wOjqK2NhYix5jY2MIDQ21e8+uri4cPnwYjY2NePfunfkNTk9PDxQKBV6/fo2vX78iPDzcXOPp6YmgoCCbfY1GI1xdXa3Otba2Yvny5fDw8Jgw197ejt7eXsTExNhd8yu9Xm/1sLOvry+uXr06Zf1k3NzcAMD8Jo2I/sWQQ0Q2/XrbSiKRWIz9vLVlMpnMYaS6uhpLly61qHNxcbF7z4SEBPj5+aGkpAS+vr4wmUxQKBQYGxsD8OPcz/i9f/o5Phlvb298+PDB6lxra6tFoBtPrVYjNjbWHCjsqdHpdMjOzobRaERmZib8/PysrtPr9UhOTkZzczOGh4eRnJyMvr4+AMCpU6egUqlQWFiIK1euQCKR4ODBg0hLSzPXDwwMAAAWLVpk82cnmo0Ycojoj5HL5XBxcUFPTw+io6N/q8f79+/R3t6OCxcuYN26dQCAuro6izUBAQFwdnZGU1OTOTwMDg6io6PD5r6hoaEoLy+3OqfX66FQKKzO3bp1Czk5OXbXGI1G7NixAzdu3IBcLkdiYuKkYWi8mpoayGQy3L17F0IIDA0Nobm5GRUVFWhubsbIyAhWr16NjRs3wtfXFwDw/PlzLFu2DN7e3lP2J5ptePCYiP4YDw8PFBQUIC8vD2VlZejq6oJWq8W5c+dQVlZmV4+FCxdCJpPh4sWL6OzsxIMHD5Cfnz9hn8zMTOzfvx8PHz6ETqdDVlYWpFKpzb8HpFKpoNPprL7NMZlMePPmDXp7ey3eCPX390Oj0SA+Pt7umsrKSmzYsAFyuRwAEBQUZFfICQkJQW1tLQ4cOIDGxkbMnz8fdXV12L59O1xdXeHl5YXNmzdDo9GYa2pra7Fly5YpexPNRgw5RPRHHT9+HEeOHMGJEycQHBwMlUqFqqoq+Pv721UvlUpx/fp1PH36FAqFAnl5eTh58uSEdUVFRYiMjER8fDxiYmKwdu1aBAcHT3rmBvgRIsLCwlBRUTFhbu/evaivr8eKFSssAktVVRUiIiKwePFiu2t0Op1FqGlpabEr5AQGBkKr1UKhUCA3NxfFxcUT1gghzEFudHQUlZWV2LVr15S9iWal/+7MMxHRnzM8PCw8PT3FpUuXbK6rrq4WwcHB4vv373b1TUhIEIWFhdN6ltOnT4t9+/YJIYSoqakRUqnUfANr06ZNore317y2u7tbKJVKIcSPm1ZGo1EIIUR5ebnIzs4WGo1GKJVKMTo6KgYGBkRAQIB4+/atEEKI4uJiERsbO61nI5pNeCaHiP5KWq0WL1++RHh4OD59+oRjx44BAJKSkmzWxcXFoaOjA319fZMeBh4vKioKqamp03q29PR0bN26FatWrYJCoYC/vz88PDwghEBnZye8vLys1rW1taGgoABOTk5wc3PD5cuXIZfLkZKSAqVSCYlEgqNHj8LHxwfAj0PhZ8+endazEc0mEiGmuI5ARPQ/pNVqkZOTg1evXmHu3LlQKpUoKiqyuN7+f9Pe3o6SkhL+U02iGcKQQ0RERA6JB4+JiIjIITHkEBERkUNiyCEiIiKHxJBDREREDokhh4iIiBwSQw4RERE5JIYcIiIickgMOUREROSQGHKIiIjIITHkEBERkUNiyCEiIiKH9A8YlYC9wCzKxQAAAABJRU5ErkJggg==", + "image/png": 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", "text/plain": [ "
" ] @@ -346,7 +370,14 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.18" + "version": "3.9.16" + }, + "scenes_data": { + "active_scene": "Default Scene", + "init_scene": "", + "scenes": [ + "Default Scene" + ] } }, "nbformat": 4, diff --git a/scintools/examples/arc_modelling.ipynb b/scintools/examples/arc_modelling.ipynb index db257b7..5f1aa4e 100644 --- a/scintools/examples/arc_modelling.ipynb +++ b/scintools/examples/arc_modelling.ipynb @@ -25,7 +25,7 @@ "import glob # for creating a list of files\n", "from scintools.dynspec import Dynspec # The dynamic spectrum class\n", "\n", - "data_dir = \"./J0437-4715\"\n", + "data_dir = \".data/J0437-4715\"\n", "dyn_files = sorted(glob.glob(data_dir + \"/*.dynspec\"))" ] }, @@ -537,7 +537,14 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.18" + "version": "3.9.16" + }, + "scenes_data": { + "active_scene": "Default Scene", + "init_scene": "", + "scenes": [ + "Default Scene" + ] } }, "nbformat": 4, diff --git a/scintools/examples/J0437-4715/p111220_074112.rf.pcm.dynspec b/scintools/examples/data/J0437-4715/p111220_074112.rf.pcm.dynspec similarity index 100% rename from scintools/examples/J0437-4715/p111220_074112.rf.pcm.dynspec rename to scintools/examples/data/J0437-4715/p111220_074112.rf.pcm.dynspec diff --git a/scintools/examples/J0437-4715/p111220_084944.rf.pcm.dynspec b/scintools/examples/data/J0437-4715/p111220_084944.rf.pcm.dynspec similarity index 100% rename from scintools/examples/J0437-4715/p111220_084944.rf.pcm.dynspec rename to scintools/examples/data/J0437-4715/p111220_084944.rf.pcm.dynspec diff --git a/scintools/examples/J0437-4715/p111220_095816.rf.pcm.dynspec b/scintools/examples/data/J0437-4715/p111220_095816.rf.pcm.dynspec similarity index 100% rename from scintools/examples/J0437-4715/p111220_095816.rf.pcm.dynspec rename to scintools/examples/data/J0437-4715/p111220_095816.rf.pcm.dynspec diff --git a/scintools/examples/J0437-4715/p111220_110656.rf.pcm.dynspec b/scintools/examples/data/J0437-4715/p111220_110656.rf.pcm.dynspec similarity index 100% rename from scintools/examples/J0437-4715/p111220_110656.rf.pcm.dynspec rename to scintools/examples/data/J0437-4715/p111220_110656.rf.pcm.dynspec diff --git a/scintools/examples/J0437-4715/p111220_121536.rf.pcm.dynspec b/scintools/examples/data/J0437-4715/p111220_121536.rf.pcm.dynspec similarity index 100% rename from scintools/examples/J0437-4715/p111220_121536.rf.pcm.dynspec rename to scintools/examples/data/J0437-4715/p111220_121536.rf.pcm.dynspec diff --git a/scintools/examples/J0437-4715/p111220_132416.rf.pcm.dynspec b/scintools/examples/data/J0437-4715/p111220_132416.rf.pcm.dynspec similarity index 100% rename from scintools/examples/J0437-4715/p111220_132416.rf.pcm.dynspec rename to scintools/examples/data/J0437-4715/p111220_132416.rf.pcm.dynspec diff --git a/scintools/examples/J0437-4715/p111220_143248.rf.pcm.dynspec b/scintools/examples/data/J0437-4715/p111220_143248.rf.pcm.dynspec similarity index 100% rename from scintools/examples/J0437-4715/p111220_143248.rf.pcm.dynspec rename to scintools/examples/data/J0437-4715/p111220_143248.rf.pcm.dynspec diff --git a/scintools/examples/J0437-4715/p111220_154120.rf.pcm.dynspec b/scintools/examples/data/J0437-4715/p111220_154120.rf.pcm.dynspec similarity index 100% rename from scintools/examples/J0437-4715/p111220_154120.rf.pcm.dynspec rename to scintools/examples/data/J0437-4715/p111220_154120.rf.pcm.dynspec diff --git a/scintools/examples/Sample_Data.npz b/scintools/examples/data/ththsims/Sample_Data.npz similarity index 100% rename from scintools/examples/Sample_Data.npz rename to scintools/examples/data/ththsims/Sample_Data.npz From 25fe246a0b8f449348dc22f37a1881ea8c841b5a Mon Sep 17 00:00:00 2001 From: Daniel Baker Date: Mon, 30 Sep 2024 11:09:02 +0800 Subject: [PATCH 10/12] moved theta-theta examples into docs --- .gitignore | 5 + docs/build/doctrees/acf.doctree | Bin 17579 -> 17502 bytes docs/build/doctrees/dynspec.doctree | Bin 5323 -> 5960 bytes docs/build/doctrees/environment.pickle | Bin 10322 -> 773738 bytes docs/build/doctrees/index.doctree | Bin 4882 -> 5698 bytes docs/build/doctrees/scint_models.doctree | Bin 87157 -> 94632 bytes docs/build/doctrees/scint_utils.doctree | Bin 57270 -> 62634 bytes docs/build/doctrees/simulation.doctree | Bin 3823 -> 4078 bytes docs/build/html/.buildinfo | 2 +- docs/build/html/_sources/dynspec.rst.txt | 4 +- docs/build/html/_sources/index.rst.txt | 4 +- docs/build/html/_static/basic.css | 364 +++++- docs/build/html/_static/doctools.js | 375 ++---- .../html/_static/documentation_options.js | 12 +- docs/build/html/_static/jquery.js | 6 +- docs/build/html/_static/pygments.css | 8 +- docs/build/html/_static/searchtools.js | 1107 +++++++---------- docs/build/html/acf.html | 241 +--- docs/build/html/dynspec.html | 221 +--- docs/build/html/genindex.html | 348 ++++-- docs/build/html/index.html | 208 +--- docs/build/html/objects.inv | Bin 322 -> 699 bytes docs/build/html/scint_models.html | 474 +++---- docs/build/html/scint_utils.html | 427 +++---- docs/build/html/search.html | 176 +-- docs/build/html/searchindex.js | 2 +- docs/build/html/simulation.html | 197 +-- docs/source/conf.py | 12 +- docs/source/thetatheta.rst | 17 +- docs/source/tutorials/dynspec_thth.rst | 299 +++++ docs/source/tutorials/thth_intro.rst | 743 +++++++++++ 31 files changed, 2769 insertions(+), 2483 deletions(-) create mode 100644 docs/source/tutorials/dynspec_thth.rst create mode 100644 docs/source/tutorials/thth_intro.rst diff --git a/.gitignore b/.gitignore index b89776d..84a7532 100644 --- a/.gitignore +++ b/.gitignore @@ -5,9 +5,14 @@ scintools/__pycache__/* scintools/__pycache__ scintools/examples/.ipynb_checkpoints/* scintools/examples/.ipynb_checkpoints +scintools/.ipynb_checkpoints/* +scintools/.ipynb_checkpoints build/ build/* *egg* dist/ dist/* .vscode/settings.json 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b/docs/build/doctrees/simulation.doctree index 8ee807c7cf45fb14006ef39dfc7ab90399c4fde2..ee27415f0f243758d87b1c4827e073b5e4d70eab 100644 GIT binary patch delta 1283 zcmb7^T~E_c7{}RIH}(R9gaFBS5fKnJy2NNSC?@I!CX-$Gl6b*fy7sWA(6vo_igKag zg%>kN6Fi3y6AXG!yx~(|{03fX;+=j16Q6c8E}9re2wNyVaEap0$9USbFBU@bx8#L!yEYy?iXTfb>f23Z_~IskJ;vIT@t-B{q(* zU$J3?EuS0~{&zZr28FCjLs3@dAEjJ0mEz_2g+wc7nQuvXlsS;5uIIo$y-YXC7(u?N z_zeWziC^2y!L!qY`dc9K-=?k}H`P}SD(2Px1h6?*Z+M3CCNV1ohTz4-#mzQLq%i8( ze_@^5qI+A>RJY7I)lghlD50-d+uWIO?k{j>TLaO&p*ipW>rNJTEzePjfCB5Mj$*oo z;;U9|$ErI7h0#__q83#QQR-l+a1GJ$)kAahXxIG=i(4MGJu1qOJ$%^pHZu5$^$^Fg zoGLMKE9qukFv+7Uhh3@RNTk3g(-V9&Gds{{=q9Ne#H>@O8hS&gVySnUFQ(594FRRL zJ6|l?#CBzSgMwwsmQ&}=^y2tbIH@UA!JJgwv$9U;ioc?WJDq<|U*@+n?*_W{hEhif zOKD{hL&Y`0zh&fHpG(x>XI)~fpgMkUvQA>Ii!#r5ujlt+4|YL#ENLnYLN{zYVEkRS z--O+!2jl+p9(GYciGS`sDx`F+s#=~&i6dBAwG5-hcLht_I{wa)@Iu@b{6o+DxwLMo ahNt=2)kQ_Hltxs`2^xTv#KXy}$-e<{O||?0 delta 1194 zcmb7E&rcIU811&*E&V|Or4prt5+Xl}?Is2zsUgwCKoHXt#Kc&e?e54|Xm{4#Sqd6b zIhc4@iOmcLA{_Y# 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object.align-right { clear: right; float: right; margin-left: 1em; } -img.align-center, .figure.align-center, object.align-center { +img.align-center, figure.align-center, .figure.align-center, object.align-center { + display: block; + margin-left: auto; + margin-right: auto; +} + +img.align-default, figure.align-default, .figure.align-default { display: block; margin-left: auto; margin-right: auto; @@ -283,30 +303,45 @@ img.align-center, .figure.align-center, object.align-center { text-align: center; } +.align-default { + text-align: center; +} + .align-right { text-align: right; } /* -- sidebars -------------------------------------------------------------- */ -div.sidebar { +div.sidebar, +aside.sidebar { margin: 0 0 0.5em 1em; border: 1px solid #ddb; - padding: 7px 7px 0 7px; + padding: 7px; background-color: #ffe; width: 40%; float: right; + clear: right; + overflow-x: auto; } p.sidebar-title { font-weight: bold; } +nav.contents, +aside.topic, +div.admonition, div.topic, blockquote { + clear: left; +} + /* -- topics ---------------------------------------------------------------- */ +nav.contents, +aside.topic, div.topic { border: 1px solid #ccc; - padding: 7px 7px 0 7px; + padding: 7px; margin: 10px 0 10px 0; } @@ -328,10 +363,6 @@ div.admonition dt { font-weight: bold; } -div.admonition dl { - margin-bottom: 0; -} - p.admonition-title { margin: 0px 10px 5px 0px; font-weight: bold; @@ -342,9 +373,34 @@ div.body p.centered { margin-top: 25px; } +/* -- content of sidebars/topics/admonitions -------------------------------- */ + +div.sidebar > :last-child, +aside.sidebar > :last-child, +nav.contents > :last-child, +aside.topic > :last-child, +div.topic > :last-child, +div.admonition > :last-child { + margin-bottom: 0; +} + +div.sidebar::after, +aside.sidebar::after, +nav.contents::after, +aside.topic::after, +div.topic::after, +div.admonition::after, +blockquote::after { + display: block; + content: ''; + clear: both; +} + /* -- tables ---------------------------------------------------------------- */ table.docutils { + margin-top: 10px; + margin-bottom: 10px; border: 0; border-collapse: collapse; } @@ -354,6 +410,11 @@ table.align-center { margin-right: auto; } +table.align-default { + margin-left: auto; + margin-right: auto; +} + table caption span.caption-number { font-style: italic; } @@ -369,10 +430,6 @@ table.docutils td, table.docutils th { border-bottom: 1px solid #aaa; } -table.footnote td, table.footnote th { - border: 0 !important; -} - th { text-align: left; padding-right: 5px; @@ -387,22 +444,34 @@ table.citation td { border-bottom: none; } +th > :first-child, +td > :first-child { + margin-top: 0px; +} + +th > :last-child, +td > :last-child { + margin-bottom: 0px; +} + /* -- figures --------------------------------------------------------------- */ -div.figure { +div.figure, figure { margin: 0.5em; padding: 0.5em; } -div.figure p.caption { +div.figure p.caption, figcaption { padding: 0.3em; } -div.figure p.caption span.caption-number { +div.figure p.caption span.caption-number, +figcaption span.caption-number { font-style: italic; } -div.figure p.caption span.caption-text { +div.figure p.caption span.caption-text, +figcaption span.caption-text { } /* -- field list styles ----------------------------------------------------- */ @@ -427,6 +496,74 @@ table.field-list td, table.field-list th { hyphens: manual; } +/* -- hlist styles ---------------------------------------------------------- */ + +table.hlist { + margin: 1em 0; +} + +table.hlist td { + vertical-align: top; +} + +/* -- object description styles --------------------------------------------- */ + +.sig { + font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace; +} + +.sig-name, code.descname { + background-color: transparent; + font-weight: bold; +} + +.sig-name { + font-size: 1.1em; +} + +code.descname { + font-size: 1.2em; +} + +.sig-prename, code.descclassname { + background-color: transparent; +} + +.optional { + font-size: 1.3em; +} + +.sig-paren { + font-size: larger; +} + +.sig-param.n { + font-style: italic; +} + +/* C++ specific styling */ + +.sig-inline.c-texpr, +.sig-inline.cpp-texpr { + font-family: unset; +} + +.sig.c .k, .sig.c .kt, +.sig.cpp .k, .sig.cpp .kt { + color: #0033B3; +} + +.sig.c .m, +.sig.cpp .m { + color: #1750EB; +} + +.sig.c .s, .sig.c .sc, +.sig.cpp .s, .sig.cpp .sc { + color: #067D17; +} + + /* -- other body styles ----------------------------------------------------- */ ol.arabic { @@ -449,11 +586,81 @@ ol.upperroman { list-style: upper-roman; } +:not(li) > ol > li:first-child > :first-child, +:not(li) > ul > li:first-child > :first-child { + margin-top: 0px; +} + +:not(li) > ol > li:last-child > :last-child, +:not(li) > ul > li:last-child > :last-child { + margin-bottom: 0px; +} + +ol.simple ol p, +ol.simple ul p, +ul.simple ol p, +ul.simple ul p { + margin-top: 0; +} + +ol.simple > li:not(:first-child) > p, +ul.simple > li:not(:first-child) > p { + margin-top: 0; +} + +ol.simple p, +ul.simple p { + margin-bottom: 0; +} + +aside.footnote > span, +div.citation > span { + float: left; +} +aside.footnote > span:last-of-type, +div.citation > span:last-of-type { + padding-right: 0.5em; +} +aside.footnote > p { + margin-left: 2em; +} +div.citation > p { + margin-left: 4em; +} +aside.footnote > p:last-of-type, +div.citation > p:last-of-type { + margin-bottom: 0em; +} +aside.footnote > p:last-of-type:after, +div.citation > p:last-of-type:after { + content: ""; + clear: both; +} + +dl.field-list { + display: grid; + grid-template-columns: fit-content(30%) auto; +} + +dl.field-list > dt { + font-weight: bold; + word-break: break-word; + padding-left: 0.5em; + padding-right: 5px; +} + +dl.field-list > dd { + padding-left: 0.5em; + margin-top: 0em; + margin-left: 0em; + margin-bottom: 0em; +} + dl { margin-bottom: 15px; } -dd p { +dd > :first-child { margin-top: 0px; } @@ -467,6 +674,21 @@ dd { margin-left: 30px; } +.sig dd { + margin-top: 0px; + margin-bottom: 0px; +} + +.sig dl { + margin-top: 0px; + margin-bottom: 0px; +} + +dl > dd:last-child, +dl > dd:last-child > :last-child { + margin-bottom: 0; +} + dt:target, span.highlighted { background-color: #fbe54e; } @@ -480,14 +702,6 @@ dl.glossary dt { font-size: 1.1em; } -.optional { - font-size: 1.3em; -} - -.sig-paren { - font-size: larger; -} - .versionmodified { font-style: italic; } @@ -526,11 +740,26 @@ dl.glossary dt { font-style: oblique; } +.classifier:before { + font-style: normal; + margin: 0 0.5em; + content: ":"; + display: inline-block; +} + abbr, acronym { border-bottom: dotted 1px; cursor: help; } +.translated { + background-color: rgba(207, 255, 207, 0.2) +} + +.untranslated { + background-color: rgba(255, 207, 207, 0.2) +} + /* -- code displays --------------------------------------------------------- */ pre { @@ -538,29 +767,69 @@ pre { overflow-y: hidden; /* fixes display issues on Chrome browsers */ } +pre, div[class*="highlight-"] { + clear: both; +} + span.pre { -moz-hyphens: none; -ms-hyphens: none; -webkit-hyphens: none; hyphens: none; + white-space: nowrap; +} + +div[class*="highlight-"] { + margin: 1em 0; } td.linenos pre { - padding: 5px 0px; border: 0; background-color: transparent; color: #aaa; } table.highlighttable { - margin-left: 0.5em; + display: block; +} + +table.highlighttable tbody { + display: block; +} + +table.highlighttable tr { + display: flex; } table.highlighttable td { - padding: 0 0.5em 0 0.5em; + margin: 0; + padding: 0; +} + +table.highlighttable td.linenos { + padding-right: 0.5em; +} + +table.highlighttable td.code { + flex: 1; + overflow: hidden; +} + +.highlight .hll { + display: block; +} + +div.highlight pre, +table.highlighttable pre { + margin: 0; +} + +div.code-block-caption + div { + margin-top: 0; } div.code-block-caption { + margin-top: 1em; padding: 2px 5px; font-size: small; } @@ -569,8 +838,14 @@ div.code-block-caption code { background-color: transparent; } -div.code-block-caption + div > div.highlight > pre { - margin-top: 0; +table.highlighttable td.linenos, +span.linenos, +div.highlight span.gp { /* gp: Generic.Prompt */ + user-select: none; + -webkit-user-select: text; /* Safari fallback only */ + -webkit-user-select: none; /* Chrome/Safari */ + -moz-user-select: none; /* Firefox */ + -ms-user-select: none; /* IE10+ */ } div.code-block-caption span.caption-number { @@ -582,21 +857,7 @@ div.code-block-caption span.caption-text { } div.literal-block-wrapper { - padding: 1em 1em 0; -} - -div.literal-block-wrapper div.highlight { - margin: 0; -} - -code.descname { - background-color: transparent; - font-weight: bold; - font-size: 1.2em; -} - -code.descclassname { - background-color: transparent; + margin: 1em 0; } code.xref, a code { @@ -637,8 +898,7 @@ span.eqno { } span.eqno a.headerlink { - position: relative; - left: 0px; + position: absolute; z-index: 1; } diff --git a/docs/build/html/_static/doctools.js b/docs/build/html/_static/doctools.js index d892892..d06a71d 100644 --- a/docs/build/html/_static/doctools.js +++ b/docs/build/html/_static/doctools.js @@ -2,312 +2,155 @@ * doctools.js * ~~~~~~~~~~~ * - * Sphinx JavaScript utilities for all documentation. + * Base JavaScript utilities for all Sphinx HTML documentation. * - * :copyright: Copyright 2007-2018 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ - -/** - * select a different prefix for underscore - */ -$u = _.noConflict(); - -/** - * make the code below compatible with browsers without - * an installed firebug like debugger -if (!window.console || !console.firebug) { - var names = ["log", "debug", "info", "warn", "error", "assert", "dir", - "dirxml", "group", "groupEnd", "time", "timeEnd", "count", "trace", - "profile", "profileEnd"]; - window.console = {}; - for (var i = 0; i < names.length; ++i) - window.console[names[i]] = function() {}; -} - */ - -/** - * small helper function to urldecode strings - */ -jQuery.urldecode = function(x) { - return decodeURIComponent(x).replace(/\+/g, ' '); -}; - -/** - * small helper function to urlencode strings - */ -jQuery.urlencode = encodeURIComponent; - -/** - * This function returns the parsed url parameters of the - * current request. Multiple values per key are supported, - * it will always return arrays of strings for the value parts. - */ -jQuery.getQueryParameters = function(s) { - if (typeof s === 'undefined') - s = document.location.search; - var parts = s.substr(s.indexOf('?') + 1).split('&'); - var result = {}; - for (var i = 0; i < parts.length; i++) { - var tmp = parts[i].split('=', 2); - var key = jQuery.urldecode(tmp[0]); - var value = jQuery.urldecode(tmp[1]); - if (key in result) - result[key].push(value); - else - result[key] = [value]; +"use strict"; + +const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([ + "TEXTAREA", + "INPUT", + "SELECT", + "BUTTON", +]); + +const _ready = (callback) => { + if (document.readyState !== "loading") { + callback(); + } else { + document.addEventListener("DOMContentLoaded", callback); } - return result; }; -/** - * highlight a given string on a jquery object by wrapping it in - * span elements with the given class name. - */ -jQuery.fn.highlightText = function(text, className) { - function highlight(node, addItems) { - if (node.nodeType === 3) { - var val = node.nodeValue; - var pos = val.toLowerCase().indexOf(text); - if (pos >= 0 && - !jQuery(node.parentNode).hasClass(className) && - !jQuery(node.parentNode).hasClass("nohighlight")) { - var span; - var isInSVG = jQuery(node).closest("body, svg, foreignObject").is("svg"); - if (isInSVG) { - span = document.createElementNS("http://www.w3.org/2000/svg", "tspan"); - } else { - span = document.createElement("span"); - span.className = className; - } - span.appendChild(document.createTextNode(val.substr(pos, text.length))); - node.parentNode.insertBefore(span, node.parentNode.insertBefore( - document.createTextNode(val.substr(pos + text.length)), - node.nextSibling)); - node.nodeValue = val.substr(0, pos); - if (isInSVG) { - var bbox = span.getBBox(); - var rect = document.createElementNS("http://www.w3.org/2000/svg", "rect"); - rect.x.baseVal.value = bbox.x; - rect.y.baseVal.value = bbox.y; - rect.width.baseVal.value = bbox.width; - rect.height.baseVal.value = bbox.height; - rect.setAttribute('class', className); - var parentOfText = node.parentNode.parentNode; - addItems.push({ - "parent": node.parentNode, - "target": rect}); - } - } - } - else if (!jQuery(node).is("button, select, textarea")) { - jQuery.each(node.childNodes, function() { - highlight(this, addItems); - }); - } - } - var addItems = []; - var result = this.each(function() { - highlight(this, addItems); - }); - for (var i = 0; i < addItems.length; ++i) { - jQuery(addItems[i].parent).before(addItems[i].target); - } - return result; -}; - -/* - * backward compatibility for jQuery.browser - * This will be supported until firefox bug is fixed. - */ -if (!jQuery.browser) { - jQuery.uaMatch = function(ua) { - ua = ua.toLowerCase(); - - var match = /(chrome)[ \/]([\w.]+)/.exec(ua) || - /(webkit)[ \/]([\w.]+)/.exec(ua) || - /(opera)(?:.*version|)[ \/]([\w.]+)/.exec(ua) || - /(msie) ([\w.]+)/.exec(ua) || - ua.indexOf("compatible") < 0 && /(mozilla)(?:.*? rv:([\w.]+)|)/.exec(ua) || - []; - - return { - browser: match[ 1 ] || "", - version: match[ 2 ] || "0" - }; - }; - jQuery.browser = {}; - jQuery.browser[jQuery.uaMatch(navigator.userAgent).browser] = true; -} - /** * Small JavaScript module for the documentation. */ -var Documentation = { - - init : function() { - this.fixFirefoxAnchorBug(); - this.highlightSearchWords(); - this.initIndexTable(); - +const Documentation = { + init: () => { + Documentation.initDomainIndexTable(); + Documentation.initOnKeyListeners(); }, /** * i18n support */ - TRANSLATIONS : {}, - PLURAL_EXPR : function(n) { return n === 1 ? 0 : 1; }, - LOCALE : 'unknown', + TRANSLATIONS: {}, + PLURAL_EXPR: (n) => (n === 1 ? 0 : 1), + LOCALE: "unknown", // gettext and ngettext don't access this so that the functions // can safely bound to a different name (_ = Documentation.gettext) - gettext : function(string) { - var translated = Documentation.TRANSLATIONS[string]; - if (typeof translated === 'undefined') - return string; - return (typeof translated === 'string') ? translated : translated[0]; - }, - - ngettext : function(singular, plural, n) { - var translated = Documentation.TRANSLATIONS[singular]; - if (typeof translated === 'undefined') - return (n == 1) ? singular : plural; - return translated[Documentation.PLURALEXPR(n)]; + gettext: (string) => { + const translated = Documentation.TRANSLATIONS[string]; + switch (typeof translated) { + case "undefined": + return string; // no translation + case "string": + return translated; // translation exists + default: + return translated[0]; // (singular, plural) translation tuple exists + } }, - addTranslations : function(catalog) { - for (var key in catalog.messages) - this.TRANSLATIONS[key] = catalog.messages[key]; - this.PLURAL_EXPR = new Function('n', 'return +(' + catalog.plural_expr + ')'); - this.LOCALE = catalog.locale; + ngettext: (singular, plural, n) => { + const translated = Documentation.TRANSLATIONS[singular]; + if (typeof translated !== "undefined") + return translated[Documentation.PLURAL_EXPR(n)]; + return n === 1 ? singular : plural; }, - /** - * add context elements like header anchor links - */ - addContextElements : function() { - $('div[id] > :header:first').each(function() { - $('\u00B6'). - attr('href', '#' + this.id). - attr('title', _('Permalink to this headline')). - appendTo(this); - }); - $('dt[id]').each(function() { - $('\u00B6'). - attr('href', '#' + this.id). - attr('title', _('Permalink to this definition')). - appendTo(this); - }); + addTranslations: (catalog) => { + Object.assign(Documentation.TRANSLATIONS, catalog.messages); + Documentation.PLURAL_EXPR = new Function( + "n", + `return (${catalog.plural_expr})` + ); + Documentation.LOCALE = catalog.locale; }, /** - * workaround a firefox stupidity - * see: https://bugzilla.mozilla.org/show_bug.cgi?id=645075 + * helper function to focus on search bar */ - fixFirefoxAnchorBug : function() { - if (document.location.hash && $.browser.mozilla) - window.setTimeout(function() { - document.location.href += ''; - }, 10); + focusSearchBar: () => { + document.querySelectorAll("input[name=q]")[0]?.focus(); }, /** - * highlight the search words provided in the url in the text + * Initialise the domain index toggle buttons */ - highlightSearchWords : function() { - var params = $.getQueryParameters(); - var terms = (params.highlight) ? params.highlight[0].split(/\s+/) : []; - if (terms.length) { - var body = $('div.body'); - if (!body.length) { - body = $('body'); + initDomainIndexTable: () => { + const toggler = (el) => { + const idNumber = el.id.substr(7); + const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`); + if (el.src.substr(-9) === "minus.png") { + el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`; + toggledRows.forEach((el) => (el.style.display = "none")); + } else { + el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`; + toggledRows.forEach((el) => (el.style.display = "")); } - window.setTimeout(function() { - $.each(terms, function() { - body.highlightText(this.toLowerCase(), 'highlighted'); - }); - }, 10); - $('

' + _('Hide Search Matches') + '

') - .appendTo($('#searchbox')); - } - }, - - /** - * init the domain index toggle buttons - */ - initIndexTable : function() { - var togglers = $('img.toggler').click(function() { - var src = $(this).attr('src'); - var idnum = $(this).attr('id').substr(7); - $('tr.cg-' + idnum).toggle(); - if (src.substr(-9) === 'minus.png') - $(this).attr('src', src.substr(0, src.length-9) + 'plus.png'); - else - $(this).attr('src', src.substr(0, src.length-8) + 'minus.png'); - }).css('display', ''); - if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) { - togglers.click(); - } - }, - - /** - * helper function to hide the search marks again - */ - hideSearchWords : function() { - $('#searchbox .highlight-link').fadeOut(300); - $('span.highlighted').removeClass('highlighted'); - }, - - /** - * make the url absolute - */ - makeURL : function(relativeURL) { - return DOCUMENTATION_OPTIONS.URL_ROOT + '/' + relativeURL; - }, + }; - /** - * get the current relative url - */ - getCurrentURL : function() { - var path = document.location.pathname; - var parts = path.split(/\//); - $.each(DOCUMENTATION_OPTIONS.URL_ROOT.split(/\//), function() { - if (this === '..') - parts.pop(); - }); - var url = parts.join('/'); - return path.substring(url.lastIndexOf('/') + 1, path.length - 1); + const togglerElements = document.querySelectorAll("img.toggler"); + togglerElements.forEach((el) => + el.addEventListener("click", (event) => toggler(event.currentTarget)) + ); + togglerElements.forEach((el) => (el.style.display = "")); + if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler); }, - initOnKeyListeners: function() { - $(document).keyup(function(event) { - var activeElementType = document.activeElement.tagName; - // don't navigate when in search box or textarea - if (activeElementType !== 'TEXTAREA' && activeElementType !== 'INPUT' && activeElementType !== 'SELECT') { - switch (event.keyCode) { - case 37: // left - var prevHref = $('link[rel="prev"]').prop('href'); - if (prevHref) { - window.location.href = prevHref; - return false; + initOnKeyListeners: () => { + // only install a listener if it is really needed + if ( + !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS && + !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS + ) + return; + + document.addEventListener("keydown", (event) => { + // bail for input elements + if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return; + // bail with special keys + if (event.altKey || event.ctrlKey || event.metaKey) return; + + if (!event.shiftKey) { + switch (event.key) { + case "ArrowLeft": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const prevLink = document.querySelector('link[rel="prev"]'); + if (prevLink && prevLink.href) { + window.location.href = prevLink.href; + event.preventDefault(); } - case 39: // right - var nextHref = $('link[rel="next"]').prop('href'); - if (nextHref) { - window.location.href = nextHref; - return false; + break; + case "ArrowRight": + if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break; + + const nextLink = document.querySelector('link[rel="next"]'); + if (nextLink && nextLink.href) { + window.location.href = nextLink.href; + event.preventDefault(); } + break; } } + + // some keyboard layouts may need Shift to get / + switch (event.key) { + case "/": + if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break; + Documentation.focusSearchBar(); + event.preventDefault(); + } }); - } + }, }; // quick alias for translations -_ = Documentation.gettext; +const _ = Documentation.gettext; -$(document).ready(function() { - Documentation.init(); -}); \ No newline at end of file +_ready(Documentation.init); diff --git a/docs/build/html/_static/documentation_options.js b/docs/build/html/_static/documentation_options.js index 4d31fbb..ded30b0 100644 --- a/docs/build/html/_static/documentation_options.js +++ b/docs/build/html/_static/documentation_options.js @@ -1,9 +1,13 @@ -var DOCUMENTATION_OPTIONS = { - URL_ROOT: '', +const DOCUMENTATION_OPTIONS = { VERSION: '0.2', - LANGUAGE: 'None', + LANGUAGE: 'en', COLLAPSE_INDEX: false, + BUILDER: 'html', FILE_SUFFIX: '.html', + LINK_SUFFIX: '.html', HAS_SOURCE: true, - SOURCELINK_SUFFIX: '.txt' + SOURCELINK_SUFFIX: '.txt', + NAVIGATION_WITH_KEYS: false, + SHOW_SEARCH_SUMMARY: true, + ENABLE_SEARCH_SHORTCUTS: true, }; \ No newline at end of file diff --git a/docs/build/html/_static/jquery.js b/docs/build/html/_static/jquery.js index 644d35e..c4c6022 100644 --- a/docs/build/html/_static/jquery.js +++ b/docs/build/html/_static/jquery.js @@ -1,4 +1,2 @@ -/*! jQuery v3.2.1 | (c) JS Foundation and other contributors | jquery.org/license */ -!function(a,b){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=a.document?b(a,!0):function(a){if(!a.document)throw new Error("jQuery requires a window with a document");return b(a)}:b(a)}("undefined"!=typeof window?window:this,function(a,b){"use strict";var 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Secondary spectra

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