How to use the summit.get_submit_job_command function in summit
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ECP-WarpX / WarpX / Tools / performance_tests / run_automated.py View on Github 
test_list_n_node = copy.deepcopy(test_list)
job_time_min = time_min(len(test_list))
batch_string = get_batch_string(test_list_n_node, job_time_min, module_Cname[architecture], n_node)
# Loop on tests
for count, current_run in enumerate(test_list_n_node):
current_run.scale_n_cell(n_node)
runtime_param_string = ' amr.n_cell=' + ' '.join(str(i) for i in current_run.n_cell)
runtime_param_string += ' amr.max_grid_size=' + str(current_run.max_grid_size)
runtime_param_string += ' amr.blocking_factor=' + str(current_run.blocking_factor)
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:
