for file_name in os.listdir(args.data_root):
if 'rasters' in file_name:
print(file_name)
env.register_class(
noisefigs.plotters.PopulationActivityPlotter,
config={
'data_root' : args.data_root,
'data_file_name': file_name,
'PopulationActivityPlotter': {
'fig_size': (6, 5),
't_limits': (5e3, 6e3),
'raster_rect': (.125, 0.35, 0.99, 0.97),
'snapshot_tstep': 1,
'e_snapshots_rect': (.125, .15, 0.99, 0.25),
'i_snapshots_rect': (.125, .02, 0.99, 0.12),
'fname_prefix': 'thesis_rasters_%s_' % file_name,
'fig_saver': SeparateMultipageSaver(None, 'pdf'),
'reshape_senders' : False,
'max_e_rate': False,
'max_i_rate': False,
'scale_bar': 250,
'scale_x': .73,
'ann_ei': False,
'y_label_pos': -.1
},
})
env.plot()
shape = (o.shapeRows, o.shapeCols)
sp = JobTrialSpace2D(shape, o.output_dir)
if common.pop_type in o.type:
env = MplEnvironment(config=config.get_config())
env.register_class(
noisefigs.plotters.PopulationActivityPlotter,
config={
'data_root' : o.output_dir,
'data_file_name': sp[o.row][o.col].file_name_base,
'output_dir' : o.figure_dir,
'PopulationActivityPlotter': {
'fname_prefix': 'r%03d_c%03d_' % (o.row, o.col),
'raster_rect': (.075, 0.35, 0.95, 0.97),
'fig_saver': SeparateMultipageSaver(None, 'pdf'),
'fig_size': (10, 6),
't_limits': (0, 5e3),
'snapshot_tstep': 4,
'e_snapshots_rect': (.075, .15, 0.95, 0.25),
'i_snapshots_rect': (.075, .02, 0.95, 0.12),
},
})
env.plot()
print('Total time: %.3f s' % (time.time() - startT))
parser = flagparse.FlagParser()
parser.add_flag('--param_exploration')
parser.add_argument('--data_root',
type=str,
help='Data root directory',
default='simulation_data/network_test/150pA')
args = parser.parse_args()
env = MplEnvironment(config=config.get_config())
if args.param_exploration or args.all:
for file_name in os.listdir(args.data_root):
if 'job' in file_name:
print(file_name)
env.register_class(noisefigs.plotters.PopulationActivityPlotter,
config={
'data_root': args.data_root,
'data_file_name': file_name,
'PopulationActivityPlotter': {
'fname_prefix':
'test_%s_' % file_name,
'fig_size': (4, 6),
't_limits': (0, 2.5e3),
'fig_saver':
SeparateMultipageSaver(None, 'pdf'),
},
})
env.plot()
o = parser.parse_args()
###############################################################################
startT = time.time()
shape = (o.shapeRows, o.shapeCols)
sp = JobTrialSpace2D(shape, o.output_dir)
if common.pop_type in o.type:
env = MplEnvironment(config=config.get_config())
env.register_class(noisefigs.plotters.PopulationActivityPlotter,
config={
'data_root': o.output_dir,
'data_file_name': sp[o.row][o.col].file_name_base,
'output_dir': o.figure_dir,
'PopulationActivityPlotter': {
'fname_prefix': 'r%03d_c%03d_' % (o.row, o.col),
'raster_rect': (.075, 0.35, 0.95, 0.97),
'fig_saver':
SeparateMultipageSaver(None, 'pdf'),
'fig_size': (10, 6),
't_limits': (0, 5e3),
'snapshot_tstep': 4,
'e_snapshots_rect': (.075, .15, 0.95, 0.25),
'i_snapshots_rect': (.075, .02, 0.95, 0.12),
},
})
env.plot()
print('Total time: %.3f s' % (time.time() - startT))
import matplotlib; matplotlib.use('Agg')
from grid_cell_model.submitting import flagparse
import noisefigs
from noisefigs.env import MplEnvironment
import config
parser = flagparse.FlagParser()
parser.add_flag('--rasters_and_bumps')
parser.add_flag('--rasters_and_bumps_test')
args = parser.parse_args()
env = MplEnvironment(config=config.get_config())
if args.rasters_and_bumps or args.all:
env.register_class(noisefigs.plotters.PopulationActivityPlotter)
if args.rasters_and_bumps_test or args.all:
env.register_class(
noisefigs.plotters.PopulationActivityPlotter,
config={
'data_root' : 'simulation_data_local/network_test/150pA',
'PopulationActivityPlotter': {
'fname_prefix': 'test_',
'fig_size': (4, 6),
't_limits': (0, 2.5e3),
},
})
env.plot()
env.register_class(noisefigs.plotters.PopulationActivityPlotter,
config={
'data_root': args.data_root,
'data_file_name': file_name,
'PopulationActivityPlotter': {
'fig_size': (6, 5),
't_limits': (5e3, 6e3),
'raster_rect': (.125, 0.35, 0.99, 0.97),
'snapshot_tstep':
1,
'e_snapshots_rect':
(.125, .15, 0.99, 0.25),
'i_snapshots_rect':
(.125, .02, 0.99, 0.12),
'fname_prefix':
'thesis_rasters_%s_' % file_name,
'fig_saver':
SeparateMultipageSaver(None, 'pdf'),
'reshape_senders':
False,
'max_e_rate':
False,
'max_i_rate':
False,
'scale_bar':
250,
'scale_x':
.73,
'ann_ei':
False,
'y_label_pos':
-.1
},
})
