, :
def spaced_choice(low, high, delta, n_samples):
draw = np.random.choice(high-low-(n_samples-1)*delta, n_samples, replace=False)
idx = np.argsort(draw)
draw[idx] += np.arange(low, low + delta*n_samples, delta)
return draw
:
spaced_choice(4, 20, 3, 4)
spaced_choice(1, 50, 5, 5)
, , . 10
, accpet/reject . insert-the-spaces-after .
, :
low, high, delta, size = 1, 100, 5, 5
add_spaces 0.04245870 ms
redraw 0.11335560 ms
low, high, delta, size = 1, 20, 1, 10
add_spaces 0.03201030 ms
redraw 27881.01527220 ms
:
import numpy as np
import types
from timeit import timeit
def f_add_spaces(low, high, delta, n_samples):
draw = np.random.choice(high-low-(n_samples-1)*delta, n_samples, replace=False)
idx = np.argsort(draw)
draw[idx] += np.arange(low, low + delta*n_samples, delta)
return draw
def f_redraw(low, high, delta, n_samples):
foo = np.random.choice(np.arange(low, high), n_samples)
while any(x <= delta for x in np.diff(np.sort(foo))):
foo = np.random.choice(np.arange(low, high), n_samples)
return foo
for l, h, k, n in [(1, 100, 5, 5), (1, 20, 1, 10)]:
print(f'low, high, delta, size = {l}, {h}, {k}, {n}')
for name, func in list(globals().items()):
if not name.startswith('f_') or not isinstance(func, types.FunctionType):
continue
print("{:16s}{:16.8f} ms".format(name[2:], timeit(
'f(*args)', globals={'f':func, 'args':(l,h,k,n)}, number=10)*100))