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)