My concern is the part between the two hash-lines. The following code runs too long for me to wait for its output. When I replace the problematic part by another chunk of code, the programme runs in a few seconds (see the end of this post). my aim is to generate 90 data points that are uniformly distributed in a unit square (var1
, var2
), and then generate 12 points that are randomly placed in a circle of radius 1/8 that lies entirely within the unit square (cir1
, cir2
), and finally join these two sets (sph1
, sph2
).
I've been digging in this code since yesterday ad I'm really sure it is correct (apparently it is not). I'm probably missing something really obvious...
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import random
import math
import numpy as np
import sys
from heapq import merge
import multiprocessing as mp
from multiprocessing import Pool
boot = 2
RRpoints = 90
rrpoints = 12
step = np.arange(-8.0 , 0.5 , 0.5)
def distance_between_points(ite, jte):
xi, yi = ite
xj, yj = jte
x2 = (xi - xj) ** 2
y2 = (yi - yj) ** 2
d = math.sqrt(x2 + y2)
return d
def heaviside_step(n):
return int(n >= 0)
def myscript(iteration_number):
RRfile_name = "MC_out_cluster_1/output%d.txt" % iteration_number
with open(RRfile_name, "w") as RRf:
#############################################################################
np.random.seed()
var1 = np.random.uniform(0, 1 , RRpoints)
var2 = np.random.uniform(0, 1 , RRpoints)
cir1 = []
cir2 = []
x0 = np.random.uniform(0.125 , 0.875)
y0 = np.random.uniform(0.125 , 0.875)
while ( len(cir1) < rrpoints and len(cir2) < rrpoints ):
np.random.seed()
col1 = np.random.uniform(x0 - 0.125 , x0 + 0.125)
col2 = np.random.uniform(y0 - 0.125 , y0 + 0.125)
if (x0 - col1) ** 2 + (y0 - col2) ** 2 <= 1/64:
cir1.append(col1)
cir2.append(col2)
sph1 = list(merge(var1 , cir1))
sph2 = list(merge(var2 , cir2))
############################################################################
corr = []
for k in xrange(0, len(step)):
h = 0
for i in xrange(0, RRpoints):
for j in xrange(1 + i, RRpoints):
ite = sph1[i] , sph2[i]
jte = sph1[j] , sph2[j]
dbp = distance_between_points(ite, jte)
h += heaviside_step(math.exp( step[k] ) - dbp)
corr.append([math.exp(step[k]) , h])
for item in corr:
RRf.write("{0}\t{1}\n".format(item[0], item[1]))
x = xrange(boot)
p = mp.Pool()
y = p.imap(myscript, x)
list(y)
This is another (working) chunk that I modified to create the above code:
#############################################################################
var1 = []
var2 = []
while (len(var1) < RRpoints):
np.random.seed()
col1 = np.random.uniform(0 , 1)
col2 = np.random.uniform(0 , 1)
if ( col1 ** 2 + (col2 - 0.5) ** 2 > 1/16 and (col1 - 1) ** 2 + (col2 - 0.5) ** 2 > 1/16 ):
var1.append(col1)
var2.append(col2)
cir1 = []
cir2 = []
while (len(cir1) < rrpoints and len(cir2) < rrpoints):
np.random.seed()
new1 = np.random.uniform(0.125 , 0.875)
new2 = np.random.uniform(0.125 , 0.875)
if ( new1 ** 2 + (new2 - 0.5) ** 2 >= 0.140625 and (new1 - 1) ** 2 + (new2 - 0.5) ** 2 >= 0.140625 ):
cir1.append(new1)
cir2.append(new2)
sph1 = list(merge(var1 , cir1))
sph2 = list(merge(var2 , cir2))
#############################################################################
You are using Python 2.x so 1/64==0
(in Python 2, division of two integers gives an integer result). If you can, upgrade to Python 3.x, or failing that change the test to use 1./64