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#!/usr/bin/python
import time
from scipy.stats import norm
import numpy as np
LIVE_DATA = True
LIVE_DATA_DEBUG = True
fileName = "out.txt" # name of the output file
sleepInterval = 1 # sleep interval in seconds
itersTotal = 100000 # total number of iterations to compute
iters = 1000 # number of iterations done before the results are written out to the file
pathes = 1 # Number of pathes to compute
delta = 0.25
dt = 0.1
# trajectories
x = np.zeros(pathes)
# generate header
out = "t"
for p in range(pathes):
out += "\tx" + str(p+1)
# Iterate to compute the steps of the Brownian motion.
i = 0
for k in range(itersTotal):
if out != "":
out += "\n"
out += str(k*dt)
for p in range(pathes):
x[p] += norm.rvs(scale=delta**2*dt)
out += "\t" + str(x[p])
i += 1
if LIVE_DATA and i >= iters:
datafile = open(fileName, "a")
datafile.write(out)
datafile.close()
if LIVE_DATA_DEBUG:
print(out)
out = ""
i = 0
time.sleep(sleepInterval)
if LIVE_DATA and out != "":
datafile = open(fileName, "a")
datafile.write(out)
datafile.close()
if LIVE_DATA_DEBUG:
print(out)
if not LIVE_DATA:
datafile = open(fileName, "a")
datafile.write(out)
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