#run population simulation and collect the data
pop.run()
pop.collect_data()
#object no longer needed
del pop
####### Postprocess the simulation output ######################################
#reset seed, but output should be deterministic from now on
np.random.seed(SIMULATIONSEED)
#do some postprocessing on the collected data, i.e., superposition
#of population LFPs, CSDs etc
postproc = PostProcess(y = params.y,
dt_output = params.dt_output,
savefolder = params.savefolder,
mapping_Yy = params.mapping_Yy,
)
#run through the procedure
postproc.run()
#create tar-archive with output for plotting
postproc.create_tar_archive()
#tic toc
print 'Execution time: %.3f seconds' % (time() - tic)
#run population simulation and collect the data
pop.run()
pop.collect_data()
#object no longer needed
del pop
####### Postprocess the simulation output ######################################
#reset seed, but output should be deterministic from now on
np.random.seed(SIMULATIONSEED)
#do some postprocessing on the collected data, i.e., superposition
#of population LFPs, CSDs etc
postproc = PostProcess(y = params.y,
dt_output = params.dt_output,
savefolder = params.savefolder,
mapping_Yy = params.mapping_Yy,
)
#run through the procedure
postproc.run()
#create tar-archive with output for plotting
postproc.create_tar_archive()
#tic toc
print 'Execution time: %.3f seconds' % (time() - tic)
####### Postprocess the simulation output ######################################
#reset seed, but output should be deterministic from now on
np.random.seed(SIMULATIONSEED)
if properrun:
#do some postprocessing on the collected data, i.e., superposition
#of population LFPs, CSDs etc
postproc = PostProcess(y = PS.X,
dt_output = PS.dt_output,
savefolder = PS.savefolder,
mapping_Yy = PS.mapping_Yy,
savelist = PS.savelist,
cells_subfolder = os.path.split(PS.cells_path)[-1],
populations_subfolder = os.path.split(PS.populations_path)[-1],
figures_subfolder = os.path.split(PS.figures_path)[-1]
)
#run through the procedure
postproc.run()
#create tar-archive with output for plotting, ssh-ing etc.
postproc.create_tar_archive()
COMM.Barrier()
#tic toc
#object no longer needed
del pop
####### Postprocess the simulation output ######################################
#reset seed, but output should be deterministic from now on
np.random.seed(SIMULATIONSEED)
#do some postprocessing on the collected data, i.e., superposition
#of population LFPs, CSDs etc
postproc = PostProcess(y = PSET['X'],
dt_output = PSET['dt_output'],
savefolder = output_path,
mapping_Yy = PSET['mapping_Yy'],
savelist = PSET['pp_savelist'],
cells_subfolder = os.path.split(cell_path)[-1],
populations_subfolder = os.path.split(population_path)[-1],
figures_subfolder = os.path.split(figure_path)[-1],
compound_file = '{}_{}sum.h5'.format('kernel', 'LFP')
)
#run through the procedure
postproc.run()
COMM.Barrier()
## get LFP output and create kernel to be used for LFP predictions
if RANK == 0:
with h5py.File(os.path.join(output_path, 'kernel_LFPsum.h5'), 'r') as f:
lfp = f['data'][()]