In [1]:

    

import time
import os
import shutil
from collections import namedtuple
import numpy as np
import h5py
import pickle
from multiprocessing import Pool
import pyximport; pyximport.install()
from Iterate import iterate


    

In [2]:

    

def init_grid(c):
    '''Initialized the 2D grid with random values, with an empty border.'''

    Z = np.random.randint(0, 2, (c.rows, c.cols))
    
    Z[0, :] = 0
    Z[-1, :] = 0
    Z[:, 0] = 0
    Z[:, -1] = 0
    
    return Z


    

In [3]:

    

# Configure parameters
Const = namedtuple('c', ['rows', 'cols', 'n_iterations', 'n_trials', 'n_cores', 'rootdir'])
c = Const(rows=150, cols=150, n_iterations=600, n_trials=64, n_cores=4, 
                    rootdir='./results/')

assert (c.n_trials % c.n_cores) == 0

# Create a fresh results directory
if os.path.exists(c.rootdir):
    shutil.rmtree(c.rootdir)
os.makedirs(c.rootdir)

pickle.dump(c._asdict(), open('./results/c.p', 'wb'))


    

In [4]:

    

def start_trial(trialnum):

    # Initialize grid
    np.random.seed(trialnum)
    Z = init_grid(c)

    Z_history = np.empty((c.rows, c.cols, c.n_iterations), dtype=int)
    Z_history[:, :, 0] = Z  # Initial state
    
    for i in range(c.n_iterations):

        Z = iterate(Z, c)
        Z_history[:, :, i] = Z 
    
    return Z_history


    

In [5]:

    

start = time.time()

p = Pool(c.n_cores)
all_trials = p.map(start_trial, range(c.n_trials))

print('Time elapsed: ', time.time() - start)


    

    




Time elapsed:  16.05678153038025

In [6]:

    

# Create new store
f = h5py.File('./results/results.hdf5', 'w')
dset = f.create_dataset("Results", (c.n_trials, c.rows, c.cols, c.n_iterations), dtype=int)
dset[...] = all_trials
f.close()


    

In [7]:

    

print(np.array(all_trials).shape)
print(np.array(all_trials).nbytes / 1e9, 'GB')


    

    




(64, 150, 150, 600)
6.912 GB