Python 在编写自己的RNG时，如何操纵种子以便不断生成新的数字？

我必须用python（3.x）为赋值实现Wichmann-Hill随机数生成算法。该算法需要使用三个随机数进行播种

我试着用

time.time\u ns（）

为它设定种子，但是如果我连续多次尝试生成一个新的数字（我必须能够连续生成至少100000个），我会得到大量重复，因为时间显然还没有改变

Wichmann Hill的算法如下：

    i1 = (170 * i1) % 30323
    i2 = (171 * i2) % 30269
    i3 = (172 * i3) % 30307

    i1 = i1 / 30323.0
    i2 = i2 / 30269.0
    i3 = i3 / 30307.0
    return (i1 + i2 + i3) % 1.0

其中i1、i2和i3应为种子

---

我一直在寻找一种方法，为下一次需要一个数字时为算法播种。非常感谢您的建议。

如果您可以使用0到2**31-1范围内的种子，您可以使用numpys

random.randint（低、高、大小）

：

我没有检查碰撞：

gen seeds of length:100000 in time:0.0024sec
wh of length:100000 in time:1.1818sec

基于，您的实现应该如下所示

class WHGen:
    def __init__(self):
        # Initialize the seeds with "random" numbers between 1 and 30,000.
        # Note: if you don't actually have nanosecond precision, you'll want
        # to divide time.time_ns() by some power of 10 first to discard
        # any low-order zeros.
        self.i1 = time.time_ns() % 30000 + 1
        self.i2 = time.time_ns() % 30000 + 1
        self.i3 = time.time_ns() % 30000 + 1
        # If you want to "cheat", you can just random.randint(1,30000) instead.

    def __iter__(self):
        while True:
            # The new seed is just the remainder, not the result of
            # the division used to compute the next number in the sequence.
            self.i1 = (171 * self.i1) % 30369
            self.i2 = (172 * self.i2) % 30307
            self.i3 = (170 * self.i3) % 30323

            # Do *not* reset the seeds themselves to these results.
            # I.e., not self.i1 /= 30269
            x = self.i1 / 30269
            y = self.i2 / 30307
            z = self.i3 / 30323

            yield (x + y + z) % 1.0

# 10 random numbers
gen = WHGen()
nums = list(islice(gen, 10))

---

你如何准确地初始化

i1

、

i2

和

i3

，连续三次调用

time.time

？我不认为你应该根据–Hill设置

i1/=30323

，等等。谢谢你的帮助，但我不允许使用任何内置的RNG来播种我的值。什么是

__（self）

do？我想这会让函数变得更易使用，但我以前从未见过。此外，我将无法使用randint，因为我不允许使用任何内置RNG（将添加到问题描述中）.在我的例子中，你在这里写的东西，我的三个种子都是一样的，但我想它应该可以工作，因为它们被修改和分割等等。

\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu。
class WHGen:
    def __init__(self):
        # Initialize the seeds with "random" numbers between 1 and 30,000.
        # Note: if you don't actually have nanosecond precision, you'll want
        # to divide time.time_ns() by some power of 10 first to discard
        # any low-order zeros.
        self.i1 = time.time_ns() % 30000 + 1
        self.i2 = time.time_ns() % 30000 + 1
        self.i3 = time.time_ns() % 30000 + 1
        # If you want to "cheat", you can just random.randint(1,30000) instead.

    def __iter__(self):
        while True:
            # The new seed is just the remainder, not the result of
            # the division used to compute the next number in the sequence.
            self.i1 = (171 * self.i1) % 30369
            self.i2 = (172 * self.i2) % 30307
            self.i3 = (170 * self.i3) % 30323

            # Do *not* reset the seeds themselves to these results.
            # I.e., not self.i1 /= 30269
            x = self.i1 / 30269
            y = self.i2 / 30307
            z = self.i3 / 30323

            yield (x + y + z) % 1.0

# 10 random numbers
gen = WHGen()
nums = list(islice(gen, 10))