numpy or _numpy or Numeric?

auditory pkyoung at gmail.com
Wed Jan 24 03:12:35 EST 2007


George Sakkis ? ?:
> On Jan 24, 2:24 am, auditory <pkyo... at gmail.com> wrote:
> 
>> I am a newbie here
>>
>> I am trying to read "space separated floating point data" from file
>>
>> I read about csv module by searching this group,
>> but I couldn't read space separated values with csv.
>> (which may be matter of course..)
>>
>> I also read about numpy.fromfile(file, sep=' ') which i can use.
>> but on my machine(ubuntu linux) numpy is unknown module,
>> which I didn't install by myself.
>>
>> While trying to install numpy accroding to its homepage.
>> (http://numpy.scipy.org/numpydoc/numdoc.htm).
>> i am quite confused.
>>
>> it's talking about the Numerical Python,
>> and it says to test whether it is installed or not,
>> try import Numeric instead of numpy.
>>
>> I got Nurmeric modules and
>> as a matter of fact i got a file named '_numpy.so' in lib directory.
>>
>> I can import _numpy but _numpy does not have 'fromfile' method
>>
>> My question is:
>> 1. Do i need to install numpy module?
>> 2. Then Is it different from Numeric module?
>> 3. Then where can i get it?
>>
>> 4. Or what is general way to read 'space separated values' from file?
>>
>> Thanks in advance.
> 
> If *all* you need is to read a space-separated file with floating point
> values, installing numpy (or Numeric or numarray..) is an overkill; you
> can do it in one line in pure Python:
> 
> matrix = [map(float, line.split()) for line in
> open('my_space_separated_file.txt')]
> 
> This stores the values as a list of lists, each list corresponding to a
> row in the file. Depending on what you plan to do next with these
> numbers, this may or may not be the best way to go about it, but since
> you only mentioned the file reading part, we can't assume much.
> 
> George
> 
Thanks a lot for your 'elegant' suggestion.
As a next step i wish to do some math with matrix and produce a vector
and write it on a file. (in fact math is just averaging now)

I hope i can do this with a little more efforts.




More information about the Python-list mailing list