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"""Cython wrapper for MurmurHash3 non-cryptographic hash function
MurmurHash is an extensively tested and very fast hash function that has
good distribution properties suitable for machine learning use cases
such as feature hashing and random projections.
The original C++ code by Austin Appleby is released the public domain
and can be found here:
https://code.google.com/p/smhasher/
"""
# Author: Olivier Grisel <olivier.grisel@ensta.org>
#
# License: BSD Style.
cimport cython
cimport numpy as np
import numpy as np
cpdef np.uint32_t murmurhash3_int_u32(int key, unsigned int seed):
"""Compute the 32bit murmurhash3 of a int key at seed."""
cdef np.uint32_t out
MurmurHash3_x86_32(&key, sizeof(int), seed, &out)
return out
cpdef np.int32_t murmurhash3_int_s32(int key, unsigned int seed):
"""Compute the 32bit murmurhash3 of a int key at seed."""
cdef np.int32_t out
MurmurHash3_x86_32(&key, sizeof(int), seed, &out)
return out
cpdef np.uint32_t murmurhash3_bytes_u32(bytes key, unsigned int seed):
"""Compute the 32bit murmurhash3 of a bytes key at seed."""
cdef np.uint32_t out
MurmurHash3_x86_32(<char*> key, len(key), seed, &out)
return out
cpdef np.int32_t murmurhash3_bytes_s32(bytes key, unsigned int seed):
"""Compute the 32bit murmurhash3 of a bytes key at seed."""
cdef np.int32_t out
MurmurHash3_x86_32(<char*> key, len(key), seed, &out)
return out
@cython.boundscheck(False)
cpdef np.ndarray[np.uint32_t, ndim=1] murmurhash3_bytes_array_u32(
np.ndarray[np.int32_t] key, unsigned int seed):
"""Compute 32bit murmurhash3 hashes of a key int array at seed."""
# TODO make it possible to pass preallocated ouput array
cdef np.ndarray[np.uint32_t, ndim=1] out = np.zeros(key.size, np.uint32)
cdef Py_ssize_t i
for i in range(key.shape[0]):
out[i] = murmurhash3_int_u32(key[i], seed)
return out
@cython.boundscheck(False)
cpdef np.ndarray[np.int32_t, ndim=1] murmurhash3_bytes_array_s32(
np.ndarray[np.int32_t] key, unsigned int seed):
"""Compute 32bit murmurhash3 hashes of a key int array at seed."""
# TODO make it possible to pass preallocated ouput array
cdef np.ndarray[np.int32_t, ndim=1] out = np.zeros(key.size, np.int32)
cdef Py_ssize_t i
for i in range(key.shape[0]):
out[i] = murmurhash3_int_s32(key[i], seed)
return out
def murmurhash3_32(key, seed=0, positive=False):
"""Compute the 32bit murmurhash3 of key at seed.
The underlying implementation is MurmurHash3_x86_32 generating low
latency 32bits hash suitable for implementing lookup tables, Bloom
filters, count min sketch or feature hashing.
Parameters
----------
key: int32, bytes, unicode or ndarray with dtype int32
the physical object to hash
seed: int, optional default is 0
integer seed for the hashing algorithm.
positive: boolean, optional default is False
True: the results is casted to an unsigned int
from 0 to 2 ** 32 - 1
False: the results is casted to a signed int
from -(2 ** 31) to 2 ** 31 - 1
"""
if isinstance(key, bytes):
if positive:
return murmurhash3_bytes_u32(key, seed)
else:
return murmurhash3_bytes_s32(key, seed)
elif isinstance(key, unicode):
if positive:
return murmurhash3_bytes_u32(key.encode('utf-8'), seed)
else:
return murmurhash3_bytes_s32(key.encode('utf-8'), seed)
elif isinstance(key, int) or isinstance(key, np.int32):
if positive:
return murmurhash3_int_u32(<np.int32_t>key, seed)
else:
return murmurhash3_int_s32(<np.int32_t>key, seed)
elif isinstance(key, np.ndarray):
if key.dtype != np.int32:
raise TypeError(
"key.dtype should be int32, got %s" % key.dtype)
if positive:
return murmurhash3_bytes_array_u32(key.ravel(),
seed).reshape(key.shape)
else:
return murmurhash3_bytes_array_s32(key.ravel(),
seed).reshape(key.shape)
else:
raise TypeError(
"key %r with type %s is not supported. "
"Explicit conversion to bytes is required" % (key, type(key)))
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