Hi there,
I wanna compile a 6000x1000 array with python. The array starts from
'empty', each time I get a 6000 length list, I wanna add it to the
exist array as a column vector. Is there any function to do so?
Or, I can add the list as a rows, if this is easier, and transpose the
whole array after all the rows are setup.
Thanks so much. 4 8953
"CC" <ch*******@gmai l.com> wrote in message
news:11******** **************@ j55g2000cwa.goo glegroups.com.. . I wanna compile a 6000x1000 array with python. The array starts from 'empty', each time I get a 6000 length list, I wanna add it to the exist array as a column vector. Is there any function to do so?
Or, I can add the list as a rows, if this is easier, and transpose the whole array after all the rows are setup.
Python does not come with a 2D array type either as a builtin type or as a
standard library module. You can only simulate one with a sequence of
sequences (list of lists, for instance). You could initialize as follows:
aray = []
for l6000 in source(): aray.append(l60 00)
While this will print as a list of rows, you are free to think of it as a
list of columns.
That said, I suspect you should use the 3rd party NumPy package which
defines multiple-dimensional arrays of several base types.
Terry Jan Reedy
Terry Reedy wrote: "CC" <ch*******@gmai l.com> wrote in message news:11******** **************@ j55g2000cwa.goo glegroups.com.. . I wanna compile a 6000x1000 array with python. The array starts from 'empty', each time I get a 6000 length list, I wanna add it to the exist array as a column vector. Is there any function to do so?
Or, I can add the list as a rows, if this is easier, and transpose the whole array after all the rows are setup.
Python does not come with a 2D array type either as a builtin type or as a standard library module. You can only simulate one with a sequence of sequences (list of lists, for instance). You could initialize as follows:
aray = [] for l6000 in source(): aray.append(l60 00)
While this will print as a list of rows, you are free to think of it as a list of columns.
That said, I suspect you should use the 3rd party NumPy package which defines multiple-dimensional arrays of several base types.
Terry Jan Reedy
If you're just looking for a multi-dimensional array type, and don't need
maximum speed or the vast range of array-processing that numpy offers, then
*pyarray* provides a pure-python single module solution.
the latest pyarray is available with tests and documentation at: http://svn.brownspencer.com/pyarray/trunk/
Introduction
============
pyarray is a pure-Python implementation of a multi-dimensional array type.
pyarray.ListVie w and pyarray.ArrayVi ew offer a substantial subset of
numpy.ArrayType functionality, by wrapping standard python 'list' and
'array.array' respectively.
Key features include:
* Views: all subscripting operations apart from individual cell access
access return views to existing 'live' data
* Extended Indexing: slicing, arbitrary 'takes', index arrays etc...
* Unlimited re-shaping: while still addressing one data-source
* Elementwise binary operations: all basic arithmetic and comparison
operations
* Data broadcasting: allows assignment and binary operations between
views of different shapes
* Friendly __repr__: work safely with big arrays at the interactive prompt
Regards
Michael
"Michael Spencer" <ma**@telcopart ners.com> wrote in message
news:e4******** **@sea.gmane.or g... If you're just looking for a multi-dimensional array type, and don't need maximum speed or the vast range of array-processing that numpy offers, then *pyarray* provides a pure-python single module solution.
the latest pyarray is available with tests and documentation at: http://svn.brownspencer.com/pyarray/trunk/
Nice. I downloaded and expect to give it a try sometime. I suggest
putting the url in the module file itself to make it easier to search for
updated versions ;-)
tjr
Terry Reedy wrote: "Michael Spencer" <ma**@telcopart ners.com> wrote in message news:e4******** **@sea.gmane.or g... If you're just looking for a multi-dimensional array type, and don't need maximum speed or the vast range of array-processing that numpy offers, then *pyarray* provides a pure-python single module solution.
the latest pyarray is available with tests and documentation at: http://svn.brownspencer.com/pyarray/trunk/
Nice. I downloaded and expect to give it a try sometime. I suggest putting the url in the module file itself to make it easier to search for updated versions ;-)
tjr
Thanks for the suggestion, Terry. I've added a static link in each source file
to the repository at: http://svn.brownspencer.com/pyarray/
and also added an email address. If you do try it, I'd be interested to hear
your feedback.
Michael This thread has been closed and replies have been disabled. Please start a new discussion. Similar topics |
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