mirror of
https://github.com/kovidgoyal/calibre.git
synced 2025-06-21 22:40:44 -04:00
94 lines
2.9 KiB
Plaintext
94 lines
2.9 KiB
Plaintext
###########################################################
|
||
# RapydScript Standard Library
|
||
# Author: Alexander Tsepkov
|
||
# Copyright 2013 Pyjeon Software LLC
|
||
# License: Apache License 2.0
|
||
# This library is covered under Apache license, so that
|
||
# you can distribute it with your RapydScript applications.
|
||
###########################################################
|
||
|
||
|
||
# basic implementation of Python's 'random' library
|
||
|
||
# JavaScript's Math.random() does not allow seeding its random generator, to bypass that, this module implements its own
|
||
# version that can be seeded. I decided on RC4 algorithm for this.
|
||
|
||
# please don't mess with this from the outside
|
||
|
||
ρσ_seed_state = {
|
||
'key': [],
|
||
'key_i': 0,
|
||
'key_j': 0
|
||
}
|
||
|
||
ρσ_get_random_byte = def():
|
||
ρσ_seed_state.key_i = (ρσ_seed_state.key_i + 1) % 256
|
||
ρσ_seed_state.key_j = (ρσ_seed_state.key_j + ρσ_seed_state.key[ρσ_seed_state.key_i]) % 256
|
||
ρσ_seed_state.key[ρσ_seed_state.key_i], ρσ_seed_state.key[ρσ_seed_state.key_j] = \
|
||
ρσ_seed_state.key[ρσ_seed_state.key_j], ρσ_seed_state.key[ρσ_seed_state.key_i]
|
||
return ρσ_seed_state.key[(ρσ_seed_state.key[ρσ_seed_state.key_i] + \
|
||
ρσ_seed_state.key[ρσ_seed_state.key_j]) % 256]
|
||
|
||
def seed(x=Date().getTime()):
|
||
if jstype(x) is 'number':
|
||
x = x.toString()
|
||
elif jstype(x) is not 'string':
|
||
raise TypeError("unhashable type: '" + jstype(x) + "'")
|
||
for i in range(256):
|
||
ρσ_seed_state.key[i] = i
|
||
j = 0
|
||
for i in range(256):
|
||
j = (j + ρσ_seed_state.key[i] + x.charCodeAt(i % x.length)) % 256
|
||
ρσ_seed_state.key[i], ρσ_seed_state.key[j] = ρσ_seed_state.key[j], ρσ_seed_state.key[i]
|
||
seed()
|
||
|
||
def random():
|
||
n = 0
|
||
m = 1
|
||
for i in range(8):
|
||
n += ρσ_get_random_byte() * m
|
||
m *= 256
|
||
return v'n / 0x10000000000000000'
|
||
|
||
# unlike the python version, this DOES build a range object, feel free to reimplement
|
||
def randrange():
|
||
return choice(range.apply(this, arguments))
|
||
|
||
def randint(a, b):
|
||
return int(random()*(b-a+1) + a)
|
||
|
||
def uniform(a, b):
|
||
return random()*(b-a) + a
|
||
|
||
def choice(seq):
|
||
if seq.length > 0:
|
||
return seq[Math.floor(random()*seq.length)]
|
||
else:
|
||
raise IndexError()
|
||
|
||
# uses Fisher-Yates algorithm to shuffle an array
|
||
def shuffle(x, random_f=random):
|
||
for i in range(x.length):
|
||
j = Math.floor(random_f() * (i+1))
|
||
x[i], x[j] = x[j], x[i]
|
||
return x
|
||
|
||
# similar to shuffle, but only shuffles a subset and creates a copy
|
||
def sample(population, k):
|
||
x = population.slice()
|
||
for i in range(population.length-1, population.length-k-1, -1):
|
||
j = Math.floor(random() * (i+1))
|
||
x[i], x[j] = x[j], x[i]
|
||
return x.slice(population.length-k)
|
||
|
||
|
||
#import stdlib
|
||
#a = range(50)
|
||
#random.seed(5)
|
||
#print(random.choice(a))
|
||
#print(random.shuffle(a))
|
||
#print(random.randrange(10))
|
||
#print(random.randint(1,5))
|
||
#print(random.uniform(1,5))
|
||
#print(random.sample(range(20),5))
|