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 }, })