52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
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"""Simulation of random streams of data.
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This module defines:
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- a generator object `data` modeling an infinite stream of integers
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- a function `make_finite_stream()` that creates finite streams of data
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The probability distribution underlying the integers is Gaussian-like with a
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mean of 42 and a standard deviation of 8. The left tail of the distribution is
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cut off meaning that the streams only produce non-negative numbers. Further,
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one in a hundred random numbers has an increased chance to be an outlier.
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"""
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import itertools as _itertools
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import random as _random
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_random.seed(87)
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def _infinite_stream():
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"""Internal generator function to simulate an infinite stream of data."""
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while True:
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number = max(0, int(_random.gauss(42, 8)))
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if _random.randint(1, 100) == 1:
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number *= 2
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yield number
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def make_finite_stream(min_=5, max_=15):
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"""Simulate a finite stream of data.
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The returned stream is finite, but the number of elements to be produced
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by it is still random. This default behavior may be turned off by passing
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in `min_` and `max_` arguments with `min_ == max_`.
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Args:
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min_ (optional, int): minimum numbers in the stream; defaults to 5
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max_ (optional, int): maximum numbers in the stream; defaults to 15
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Returns:
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finite_stream (generator)
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Raises:
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ValueError: if max_ < min_
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"""
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stream = _infinite_stream()
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n = _random.randint(min_, max_)
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yield from _itertools.islice(stream, n)
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data = _infinite_stream()
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