Re: [Matplotlib-users] load function

[Humufr <hu...@ya...>]

I agree with you but in the load function documentation I can read this:

x,y = load('test.dat')  # data in two columns

so if I interpret this correctly that means a data file like:

1 2
1 2
1 2
1 2
1 2

and not a file like:

1 1 1 1 1
2 2 2 2 2

it's why I suggest to add the transpose in the load function.

For the second things (the columns). Your example show that you can read 
two columns  consecutive but if you want read the columns 3,5,7,8 that 
can't work. Like it's only an optionnal argument I was thinking that was 
possible to add this possibilty in the load function inside pylab.

For the comments for the beggining of an array indexing I know it :) but 
I hate it (it's just a tast :) ) and I prefer to name/count the column 
in a data file from 1 so instead to tell to someone: "Use the zero 
columns" I prefer to tell "Use the first columns". It's only a matter of 
choice. But it's why I add: array(columns)-1.


Nicolas


Stephen Walton wrote:

> I don't think the load function needs to be changed in the way you 
> suggest.  The "problem" is not the load function.  It is the fact that 
> numarray arrays are stored in row-major, not column-major, order, and 
> so tuple unpacking a numarray array goes by row, not by column.
>
> In [15]: A=arange(6)
>
> In [16]: A.shape=(3,2)
>
> In [17]: x,y=A
> --------------------------------------------------------------------------- 
>
> exceptions.ValueError                                Traceback (most 
> recent call last)
>
> ValueError: too many values to unpack
>
> The transpose is required here as well if you want to unpack by 
> columns.  If I have a file containing 731 rows and 17 columns and use 
> 'load', I get an array with 731 rows and 17 columns, exactly as I expect.
>
> I'm far from a Python expert myself ;-) , but you can do what you're 
> trying with the single line
>
> x,y=transpose(load('toto.dat')[:,1:3])
>
> (note that array indexing in Python is zero-based, not one-based, and 
> also read up on how slices work).
>
>