Merge pull request #65 from sigp/shuffling_update

Fix shuffle() function errors
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Danny Ryan 2018-10-15 22:08:40 -05:00 committed by GitHub
commit 11012448fa
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1 changed files with 26 additions and 15 deletions

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@ -325,36 +325,47 @@ def shuffle(values: List[Any],
"""
values_count = len(values)
# entropy is consumed in 3 byte chunks
# sample_max is defined to remove the modulo bias from this entropy source
sample_max = 2 ** 24
assert values_count <= sample_max
# Entropy is consumed from the seed in 3-byte (24 bit) chunks.
rand_bytes = 3
# The highest possible result of the RNG.
rand_max = 2 ** (rand_bytes * 8) - 1
# The range of the RNG places an upper-bound on the size of the list that
# may be shuffled. It is a logic error to supply an oversized list.
assert values_count < rand_max
output = [x for x in values]
source = seed
index = 0
while index < values_count:
# Re-hash the source
while index < values_count - 1:
# Re-hash the `source` to obtain a new pattern of bytes.
source = hash(source)
for position in range(0, 30, 3): # gets indices 3 bytes at a time
# Select a 3-byte sampled int
sample_from_source = int.from_bytes(source[position:position + 3], 'big')
# `remaining` is the size of remaining indices of this round
# Iterate through the `source` bytes in 3-byte chunks.
for position in range(0, 32 - (32 % rand_bytes), rand_bytes):
# Determine the number of indices remaining in `values` and exit
# once the last index is reached.
remaining = values_count - index
if remaining == 1:
break
# Set a random maximum bound of sample_from_source
sample_max = sample_max - sample_max % remaining
# Read 3-bytes of `source` as a 24-bit big-endian integer.
sample_from_source = int.from_bytes(
source[position:position + rand_bytes], 'big'
)
# Select `replacement_position` with the given `sample_from_source` and `remaining`
# Sample values greater than or equal to `sample_max` will cause
# modulo bias when mapped into the `remaining` range.
sample_max = rand_max - rand_max % remaining
# Perform a swap if the consumed entropy will not cause modulo bias.
if sample_from_source < sample_max:
# Use random number to get `replacement_position`, where it's not `index`
# Select a replacement index for the current index.
replacement_position = (sample_from_source % remaining) + index
# Swap the index-th and replacement_position-th elements
# Swap the current index with the replacement index.
output[index], output[replacement_position] = output[replacement_position], output[index]
index += 1
else:
# The sample causes modulo bias. A new sample should be read.
pass
return output