def replot(csv=None, rm=False, show_out=None):
# Load csv graph data
data = np.loadtxt(csv, delimiter=',')
# Re-plot graph
if 'atoms_per_core_vs_running_time' in csv:
do_plot_1(*data, show_graph=show_out)
if 'graph_size_vs_running_time' in csv:
do_plot_2(*data, show_graph=show_out)
if 'packet_drop_vs_time_scale_factor' in csv:
do_plot_3(*data, show_graph=show_out)
# If demanded, remove original graph
if rm:
os.unlink(csv)
os.unlink(csv[:-4] + '.png')
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Plots graph size vs. Python / SpiNNaker running times.')
parser.add_argument('csv', help='CSV data file to recompute from')
parser.add_argument('-r', '--rm', action='store_true')
parser.add_argument('-o', '--show-out', action='store_true')
# Recreate the same graphs for the same arguments
random.seed(42)
setup_cli_and_run(parser, replot)
def run(runs=None, **kwargs):
import tqdm
results = [runner(_mk_sim_run, **kwargs)
for _ in tqdm.tqdm(range(runs), total=runs)]
correct = sum(map(int, results))
print('Finished robustness test with %d/%d passed.' % (correct, runs))
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Run random Page Rank graphs')
parser.add_argument('-r', '--runs', type=int, default=1,
help='# runs. Default is 1.')
parser.add_argument('node_count', metavar='NODES', type=int,
help='# nodes per graph')
parser.add_argument('edge_count', metavar='EDGES', type=int,
help='# edges per graph')
parser.add_argument('-v', '--verify', action='store_true',
help='Verify sim w/ Python PR impl')
parser.add_argument('-p', '--pause', action='store_true',
help='Pause after each runs')
parser.add_argument('-o', '--show-out', action='store_true',
help='Display ranks curves output')
parser.add_argument('-l', '--log-level', type=int, default=25,
help='The integer log level to set')
# Recreate the same graphs for the same arguments
random.seed(42)
setup_cli_and_run(parser, run)
help='# nodes per graph')
parser.add_argument('edge_count',
metavar='EDGES',
type=int,
help='# edges per graph')
parser.add_argument('tsf_min',
metavar='TSF_MIN',
type=int,
help='min time_scale_factor')
parser.add_argument('tsf_res',
metavar='TSF_res',
type=int,
default=10,
help='time_scale_factor resolution. Default is 10.')
parser.add_argument('tsf_max',
metavar='TSF_MAX',
type=int,
help='max time_scale_factor')
parser.add_argument('-v',
'--verify',
action='store_true',
help='Verify sim w/ Python PR impl')
parser.add_argument('-p',
'--pause',
action='store_true',
help='Pause after each runs')
# Recreate the same graphs for the same arguments
random.seed(42)
setup_cli_and_run(parser, sim_worker)