# Direct surface.py

(Difference between revisions)
 Revision as of 21:41, 22 September 2015Werner (Talk | contribs)← Previous diff Current revisionWerner (Talk | contribs) Line 1: Line 1: - This page presents the program markov_disks_box.py, a Markov-chain algorithm for four disks in a square box of sides 1. + This page presents the program direct_surface.py, a direct-sampling algorithm for uniform points on the surface of a d-dimensional unit sphere __FORCETOC__ __FORCETOC__ Line 5: Line 5: =Program= =Program= - - import random - - L = [[0.25, 0.25], [0.75, 0.25], [0.25, 0.75], [0.75, 0.75]] - sigma = 0.15 - sigma_sq = sigma ** 2 - delta = 0.1 - n_steps = 1000 - for steps in range(n_steps): - a = random.choice(L) - b = [a[0] + random.uniform(-delta, delta), a[1] + random.uniform(-delta, delta)] - min_dist = min((b[0] - c[0]) ** 2 + (b[1] - c[1]) ** 2 for c in L if c != a) - box_cond = min(b[0], b[1]) < sigma or max(b[0], b[1]) > 1.0 - sigma - if not (box_cond or min_dist < 4.0 * sigma ** 2): - a[:] = b - print L - - =Version= - See history for version information. - - [[Category:Python]] - import random, math import random, math Line 35: Line 13: radius = math.sqrt(sum(x ** 2 for x in R)) radius = math.sqrt(sum(x ** 2 for x in R)) print [x / radius for x in R] print [x / radius for x in R] + =Version= + See history for version information. + + [[Category:Python]] + [[Category:Honnef_2015]] + [[Category:MOOC_SMAC]]

## Current revision

This page presents the program direct_surface.py, a direct-sampling algorithm for uniform points on the surface of a d-dimensional unit sphere

# Program

```import random, math

dimensions = 5
nsamples = 20
for sample in xrange(nsamples):
R = [random.gauss(0.0, 1.0) for d in xrange(dimensions)]
radius = math.sqrt(sum(x ** 2 for x in R))
print [x / radius for x in R]
```

# Version

See history for version information.