Skip to main content

numbyte - numerical bytearray - c++ numerical buffer interface extending bytearray into numpy-like, 2d array

Project description

numbyte - numerical bytearray - c++ numerical buffer interface extending bytearray into numpy-like, 2d array

REQUIRES PYTHON3.1

QUICK TEST: $ python3.1 setup.py build dev –quicktest

DESCRIPTION: numbyte - numerical bytearray - c++ numerical buffer interface extending bytearray into numpy-like, 2d array

SUMMARY: numbyte is a python3.1 extension module, efficiently implementing numerical 2d arrays. numbyte uses python bytearray as the underlying data structure, simplifying io operation with other python objects.

RECENT CHANGELOG: 20091224 - modularized package - fix install issues - added sdist check 20091209 - improved documentation 20091205 - moved source code to c++ 20091116 - package integrated

DEMO USAGE:

>>> from numbyte import *
>>> ## subclass numbyte
>>> class numbyte2(numbyte): pass
>>> ## create bytearray containing 3x4 array of longlong
>>> integers = numbyte2('i', range(12), shape0 = 3, shape1 = 4)
>>> print( integers.debug() )
<class 'numbyte.numbyte2'> i refcnt=4 tcode=i tsize=8 offset=0 shape=<3 4> stride=<4 1> transposed=0
[[          0           1           2           3]
[          4           5           6           7]
[          8           9          10          11]]
>>> ## modify underlying bytearray
>>> integers.bytes()[0] = 0xff; integers.bytes()[1] = 0xff
>>> print( integers.bytes() )
bytearray(b'\xff\xff\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\x00\x00\x00\x02\x00\x00\x00\x00\x00\x00\x00\x03\x00\x00\x00\x00\x00\x00\x00\x04\x00\x00\x00\x00\x00\x00\x00\x05\x00\x00\x00\x00\x00\x00\x00\x06\x00\x00\x00\x00\x00\x00\x00\x07\x00\x00\x00\x00\x00\x00\x00\x08\x00\x00\x00\x00\x00\x00\x00\t\x00\x00\x00\x00\x00\x00\x00\n\x00\x00\x00\x00\x00\x00\x00\x0b\x00\x00\x00\x00\x00\x00\x00')
>>> print( integers.debug() )
<class 'numbyte.numbyte2'> i refcnt=4 tcode=i tsize=8 offset=0 shape=<3 4> stride=<4 1> transposed=0
[[      65535           1           2           3]
[          4           5           6           7]
[          8           9          10          11]]
>>> ## bytearray as sequence
>>> print( 2 in integers )
True
>>> print( integers.count(2) )
1
>>> print( integers.index(2) )
2
>>> for aa in integers.rows(): print( aa )
[[      65535           1           2           3]]
[[          4           5           6           7]]
[[          8           9          10          11]]
>>> ## slice
>>> print( integers[1:, 2:].debug() )
<class 'numbyte.numbyte2'> i refcnt=3 tcode=i tsize=8 offset=6 shape=<2 2> stride=<4 1> transposed=0
[[          6           7]
[         10          11]]
>>> ## transpose
>>> print( integers.T()[2:, 1:].debug() )
<class 'numbyte.numbyte2'> i refcnt=3 tcode=i tsize=8 offset=6 shape=<2 2> stride=<1 4> transposed=1
[[          6          10]
[          7          11]]
>>> ## reshape
>>> print( integers.reshape(2, -1).debug() )
<class 'numbyte.numbyte2'> i refcnt=3 tcode=i tsize=8 offset=0 shape=<2 6> stride=<6 1> transposed=0
[[      65535           1           2           3           4           5]
[          6           7           8           9          10          11]]
>>> ## setslice
>>> integers.T()[2:, 1:] = range(4); print( integers )
[[      65535           1           2           3]
[          4           5           0           2]
[          8           9           1           3]]
>>> ## almost all arithmetic operations are inplace - use copy to avoid side-effects
>>> ## recast to double
>>> floats = integers.recast('f') / 3; print( floats )
[[        21845      0.333333      0.666667             1]
[      1.33333       1.66667             0      0.666667]
[      2.66667             3      0.333333             1]]
>>> ## copy
>>> print( floats.copy() + integers[0, :] )
[[        87380       1.33333       2.66667             4]
[      65536.3       2.66667             2       3.66667]
[      65537.7             4       2.33333             4]]
>>> ## inplace
>>> print( floats + integers[:, 0] )
[[        87380       65535.3       65535.7         65536]
[      5.33333       5.66667             4       4.66667]
[      10.6667            11       8.33333             9]]
>>> ## inplace
>>> print( floats - integers[:, 0] )
[[        21845      0.333333      0.666667             1]
[      1.33333       1.66667             0      0.666667]
[      2.66667             3      0.333333             1]]
>>> ## inplace
>>> print( floats ** 2 )
[[  4.77204e+08      0.111111      0.444444             1]
[      1.77778       2.77778             0      0.444444]
[      7.11111             9      0.111111             1]]
>>> ## inplace
>>> print( floats.sqrt() )
[[        21845      0.333333      0.666667             1]
[      1.33333       1.66667             0      0.666667]
[      2.66667             3      0.333333             1]]
>>> ## the only inplace exception are logical comparisons, which return new char arrays
>>> print( floats )
[[        21845      0.333333      0.666667             1]
[      1.33333       1.66667             0      0.666667]
[      2.66667             3      0.333333             1]]
>>> ## copy as char
>>> print( floats == floats[:, 1] )
[[ 00  01  00  00]
[ 00  01  00  00]
[ 00  01  00  00]]
>>> ## copy as char
>>> print( floats > 1.5 )
[[ 01  00  00  00]
[ 01  01  00  00]
[ 01  01  00  00]]

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

numbyte-2009.12.24.py3k.cpp.tar.gz (80.4 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page