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dlma/scripts/scatter_curves/setup_simulation_dlca.py
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setup_simulation_dlca.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 4 13:56:09 2021
@author: samarth
"""
import pandas as pd
import os
import sys
from pathlib import Path
from joblib import Parallel, delayed
from matplotlib import pyplot as plt
import numpy as np
from sklearn.linear_model import LinearRegression
from random import random, seed
import subprocess
def create_dirs(phi, dim):
global D
D = dim
global params_dir
phi_str = format(phi, '.4f')
params_dir = './act_values/params/phi='+phi_str+'/'
path = Path(params_dir)
try:
path.mkdir(parents=True, exist_ok=True)
except OSError:
pass
else:
pass
global results_dir
results_dir = './act_values/results/phi='+phi_str+'/'
path = Path(results_dir)
try:
path.mkdir(parents=True, exist_ok=True)
except OSError:
pass
else:
pass
global config_files_dir
config_files_dir = './act_values/config_files/phi='+phi_str+'/'
path = Path(config_files_dir)
try:
path.mkdir(parents=True, exist_ok=True)
except OSError:
pass
else:
pass
def run_simulation(phi, L, rng_seed):
lattice=1
alpha=0.5
seedMass=1e12
params_file = params_dir+'params_'+str(rng_seed)+'.csv'
file = open(params_file, "w")
file.write("system=dlma\n")
file.write("lattice="+str(lattice)+"\n")
file.write("aggregation_type=normal\n")
file.write("aggregation_condition=mass\n")
file.write("bind=normal\n")
file.write("movement=brownian\n")
file.write("agg_dist_tolerance=0.0\n")
file.write("D="+str(D)+"\n")
file.write("seed_pct=100\n")
for axis in range(D):
file.write("x"+str(axis)+"_bc=periodic\n")
#for axis in range(D):
#file.write("x"+str(axis)+"_L="+str(L)+"\n")
file.write("N=10000\n")
file.write("phi="+str(phi)+"\n")
file.write("alpha="+str(alpha)+"\n")
file.write("seedMass="+str(seedMass)+"\n")
file.write("rng_seed="+str(rng_seed)+"\n")
file.close()
print("phi = {}, rng_seed={} simulation".format(phi,rng_seed))
config_filename=config_files_dir+str(rng_seed)+'.csv'
command = 'simulation '+params_file+' '+config_filename
os.system(command)
results_filename=results_dir+str(rng_seed)+'.csv'
command = "long_range_scattering "+config_filename+" 1000 0.02 10 1000 "+ results_filename
os.system(command)
seed(1)
seeds=50
seed_pct_range=[100]
dim = 3
L=57.7
phi_range = [(100-96.21)/100, (100-94.83)/100, (100-93.01)/100, (100-91.08)/100, (100-88.20)/100, (100-86.80)/100]
for phi in phi_range:
create_dirs(phi, dim)
Parallel(n_jobs=10)(delayed(run_simulation)(phi, L, rng_seed) for rng_seed in range(seeds))
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