How to use the summit.process_analysis function in summit
To help you get started, we’ve selected a few summit examples, based on popular ways it is used in public projects.
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ECP-WarpX / WarpX / Tools / performance_tests / run_automated.py View on Github 
runtime_param_string += ' max_step=' + str( current_run.n_step )
# runtime_param_list.append( runtime_param_string )
run_string = get_run_string(current_run, architecture, n_node, count, bin_name, runtime_param_string)
batch_string += run_string
batch_string += 'rm -rf plotfiles lab_frame_data diags\n'
submit_job_command = get_submit_job_command()
# Run the simulations.
run_batch_nnode(test_list_n_node, res_dir, bin_name, config_command, batch_string, submit_job_command)
os.chdir(cwd)
# submit batch for analysis
if os.path.exists( 'read_error.txt' ):
os.remove( 'read_error.txt' )
if os.path.exists( 'read_output.txt' ):
os.remove( 'read_output.txt' )
process_analysis(args.automated, cwd, compiler, architecture, args.n_node_list, start_date)
# read the output file from each test and store timers in
# hdf5 file with pandas format
# -------------------------------------------------------
for n_node in n_node_list:
print(n_node)
if browse_output_files:
res_dir = res_dir_base
res_dir += '_'.join([run_name, compiler,\
architecture, str(n_node)]) + '/'
for count, current_run in enumerate(test_list):
# Read performance data from the output file
output_filename = 'out_' + '_'.join([current_run.input_file, str(n_node), str(current_run.n_mpi_per_node), str(current_run.n_omp), str(count)]) + '.txt'
# Read data for all test to put in hdf5 a database
# This is an hdf5 file containing ALL the simulation
# parameters and results. Might be too large for a repo
