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generate sorted random numbers
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""" | |
Generate sorted random numbers. | |
method from: http://repository.cmu.edu/cgi/viewcontent.cgi?article=3483&context=compsci | |
Has same interface as random module except it takes N as the first argument | |
for the number of numbers to generate. | |
""" | |
from random import random as rand, seed | |
def random(N): | |
""" | |
Generate N sorted uniform random numbers between 0 and 1 | |
>>> seed(42) | |
>>> r = list(random(10)) | |
>>> all(r0 < r1 for r0, r1 in zip(r, r[1:])) | |
True | |
>>> len(r) | |
10 | |
""" | |
curmax = 1.0 | |
for I in range(N, 0, -1): | |
curmax *= rand() ** (1.0 / float(I)) | |
yield (1.0 - curmax) | |
def randint(N, imin, imax, include_end=False): | |
""" | |
Generate N sorted uniform random numbers between imin and imax. | |
>>> seed(42) | |
>>> list(randint(6, 100, 200)) | |
[107, 155, 167, 180, 183, 188] | |
""" | |
# include end-point like random.randint() | |
span = imax - imin + int(bool(include_end)) | |
for r in random(N): | |
yield int(imin + r * span) | |
if "__main__" == __name__: | |
import doctest | |
doctest.testmod() | |
import numpy as np | |
import seaborn as sns | |
from matplotlib import pyplot as plt | |
seed() | |
N = 10000 | |
chrom_size = 500000 | |
starts = np.array(list(randint(N, 0, chrom_size))) | |
assert np.all(starts[1:] >= starts[:-1]) | |
print starts.min(), starts.max() | |
plt.hist(starts, 15) | |
plt.show() |
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Once we get a breather, we should sit down and implement this in bedtools.