kopia lustrzana https://github.com/inkstitch/inkstitch
59 wiersze
2.2 KiB
Python
59 wiersze
2.2 KiB
Python
from hashlib import blake2s
|
|
from math import ceil
|
|
from itertools import count, chain
|
|
import numpy as np
|
|
|
|
# Framework for reproducible pseudo-random number generation.
|
|
|
|
# Unlike python's random module (which uses a stateful generator based on global variables),
|
|
# a counter-mode PRNG like uniformFloats can be used to generate multiple, independent random streams
|
|
# by including an additional parameter before the loop counter.
|
|
# This allows different aspects of an embroidery element to not effect each other's rolls,
|
|
# making random generation resistant to small edits in the control paths or refactoring.
|
|
# Using multiple counters for n-dimentional random streams is also possible and is useful for grid-like structures.
|
|
|
|
|
|
def join_args(*args):
|
|
# Stringifies parameters into a slash-separated string for use in hash keys.
|
|
# Idempotent and associative.
|
|
return "/".join([str(x) for x in args])
|
|
|
|
|
|
MAX_UNIFORM_INT = 2 ** 32 - 1
|
|
|
|
|
|
def uniform_ints(*args):
|
|
# Single pseudo-random drawing determined by the joined parameters.
|
|
# To get a longer sequence of random numbers, call this loop with a counter as one of the parameters.
|
|
# Returns 8 uniformly random uint32.
|
|
|
|
s = join_args(*args)
|
|
# blake2s is python's fastest hash algorithm for small inputs and is designed to be usable as a PRNG.
|
|
h = blake2s(s.encode()).hexdigest()
|
|
nums = []
|
|
for i in range(0, 64, 8):
|
|
nums.append(int(h[i:i + 8], 16))
|
|
return np.array(nums)
|
|
|
|
|
|
def uniform_floats(*args):
|
|
# Single pseudo-random drawing determined by the joined parameters.
|
|
# To get a longer sequence of random numbers, call this loop with a counter as one of the parameters.
|
|
# Returns an array of 8 floats in the range [0,1]
|
|
return uniform_ints(*args) / MAX_UNIFORM_INT
|
|
|
|
|
|
def n_uniform_floats(n: int, *args):
|
|
# returns a fixed number (which may exceed 8) of floats in the range [0,1]
|
|
seed = join_args(*args)
|
|
nBlocks = ceil(n / 8)
|
|
blocks = [uniform_floats(seed, x) for x in range(nBlocks)]
|
|
return np.concatenate(blocks)[0:n]
|
|
|
|
|
|
def iter_uniform_floats(*args):
|
|
# returns an infinite sequence of floats in the range [0,1]
|
|
seed = join_args(*args)
|
|
blocks = map(lambda x: list(uniform_floats(seed, x)), count(0))
|
|
return chain.from_iterable(blocks)
|