BFScan/run_job.py at main · kevinCassou/BFScan · GitHub

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#######################################################################
############         Performance scan launcher           ##############
#######################################################################

import os,sys,re
from sklearn.model_selection import ParameterGrid
import pandas as pd
import numpy as np

### 0 - Define path and executables

# The input namelist - Remember, this namelist must NOT contain the parameters clrw and tasks_on_projection in Main block
name_input_namelist = "LWFA_ii-env-bfs.py"
name_submission_script = "runSmilei_ii-env-bfs.sh"
#name_input_namelist = "tst3d_laser_wakefield.py"

# necessary paths - they must be absolute paths
starting_directory = os.getcwd()
path_input_namelist = "/ccc/scratch/cont003/smilei/cassouke/BF-TEST/"+name_input_namelist
path_input_submission_script = "/ccc/scratch/cont003/smilei/cassouke/BF-TEST/"+name_submission_script

path_executable_develop = "/ccc/scratch/cont003/smilei/cassouke/BF-TEST/"
path_executable_test_develop = "/ccc/scratch/cont003/smilei/cassouke/BF-TEST/"

# save content of input namelist
with open(path_input_namelist, "r") as file:
	namelist_file_content = file.readlines()
# save content of submission_script
with open(path_input_submission_script, "r") as file:
	submission_script_file_content = file.readlines()

### 1 - Prepare dataframe with scan parameters

n_e_1 = 1.0e18*np.array([3.0,4.5,6.0])
n_e_2 = 1.0e18*np.array([1.5 , 4])
l_1 =  np.array([0.3, 0.6, 1.2])
x_foc = np.array([0.1, 0.2, 0.3])
c_N2 =  np.array([0.3, 1, 3])


param_grid = {'n_e_1':n_e_1, 'n_e_2':n_e_2, 'l_1':l_1,'x_foc':x_foc,'c_N2':c_N2 }

df = pd.DataFrame((ParameterGrid(param_grid)))
#add column Config
df['Config'] = df.index
#rearrange columns cols = list(df.columns.values)
df = df[['Config','n_e_1', 'n_e_2', 'l_1', 'x_foc', 'c_N2' ]]


### 2 - create folders and submit job one by one

# create the folder tree
#directories_to_create = [starting_directory+"/Config_" +str(x) for x in df['Config']]

# create directory tree with necessary files and launch each simulation
#for directory in directories_to_create:


for index, row in df.iterrows():

	directory = [starting_directory+"/Config_" +str(row['Config'])]

	# create the directory and enter it
	os.makedirs(directory)
	os.chdir(directory)

	# add link to executable smilei and smilei_test
	os.system("ln -s "+path_executable_develop)
	os.system("ln -s "+path_executable_test_develop)

	# prepare namelist
    write_to_namelist = "config_external = " +str(row.to_dict())
	print("dictionary for namelist",write_to_namelist)

	# !! insert in the original namelist file dictionary with parameters after the line External_config !!
	with open(name_input_namelist, 'w') as namelist:
	    for line in namelist_file_content:
	        newline = line
	        if "External_config" in line:
	            #print(line)
	            newline = newline + "\n" + write_to_namelist + "\n"
	        namelist.write(newline)

	# set the MPI and threads in the submission script
	with open("submission_script.sh", 'w') as submission_script_file:
		for line in submission_script_file_content:
			submission_script_file.write(line)

	# launch the simulation
	# os.system("sbatch submission_script.sh")

	# go back to the original folder
	os.chdir(starting_directory)