[AstroPy] question on matplotlib's loadtxt

Derek Homeier derek@astro.physik.uni-goettingen...
Fri Nov 4 10:14:15 CDT 2011


Hi Grigoris,

> Hello to all!  I would like to ask about an error I face with 
> matplotlib's loadtxt...
> 
> Suppose that we have a file (called "test.test") with 6 columns like:
> 
> 1496548.  862.235400937  14.008  0  20110523.201416  tth*g
> 1690289.  919.424007603  13.875  0  20110523.221527  hgf4
> 1667241.  996.262754039  13.890  0  20110524.001639  nb.mj
> 739181.6  881.1753527  14.774  0  20110524.010203  vbfhg
> 
> When I use
> x, y = loadtxt('test.test', unpack=True, usecols=(0,1), dtype=(float,float))
> 
> it prints normally the first and second column.
> If I add another column like:
> 
> x, y, z = loadtxt('test.test', unpack=True,usecols=(0,1,3), 
> dtype=(float,float,float))
> 
> the output is this:
>   File "/usr/lib/python2.7/site-packages/numpy/lib/io.py", line 584, in 
> loadtxt
>     dtype = np.dtype(dtype)
> TypeError: data type not understood
> 
I don't quit understand that part, I admit - dtype only takes a single type or pairs of names and 
types, so it would seem the first case actually only worked by accident:

In [193]: np.dtype((float,float))
Out[193]: dtype('float64')

I have no idea how it interprets the second float, but as you see it has no effect anyway. 
You could in fact get the same result with 'usecols=[0,1,3], dtype=float' 
which will simply apply the dtype to all columns (and is the default already...). 
> 
> Even if I use a dictionary, like:
> dt = dtype({'names':['n1','n2','n3'],'formats':[float,float,float]})
> x, y, z = loadtxt('test.test', unpack=True, usecols=(0,1,2) , dtype=dt)
> 
> the output is the same as previous.
> 
No things are getting strange - the above is the correct (and I think, only) way to 
define dtypes with different formats - 
np.dtype([('n1',float),('n2',float),('n3',float)]) 
would be equivalent. As there is no error on the first line (i.e., dt is a valid dtype), 
this seems to be a bug in loadtxt. Could you check what happens if you try the 
above without the 'unpack' option? Should return a structured array with the 3 
fields 'n1','n2','n3'...
Also (as loadtxt is actually part of numpy), which is your installed version of numpy 
(numpy.__version__ or np.__version__, you may have to re-import it as pylab 
unfortunately imports everything into one namespace). I recall that there have 
been issues with unpacking structured arrays prior to 1.6 or 1.6.1. 

> Additionaly, when I am trying to load the last column as strings:
> x, y = loadtxt('test.test', delimiter='  ', unpack=True,usecols=(0,5), 
> dtype=(float,'S5'))
> 
> I get this error:
>   File "/usr/lib/python2.7/site-packages/numpy/lib/io.py", line 584, in 
> loadtxt
>     dtype = np.dtype(dtype)
> ValueError: mismatch in size of old and new data-descriptor
> 
> 
> What am I doing wrong ? I am sorry if it is something really obvious ... 
> but I am unable to find it...

Similar problem - this ought to work with dtype=[('n1', 'f'), ('n6','S5')] ; but it might 
be broken in the same way as above - if you can update to numpy 1.6.x, you 
should hopefully be set.

HTH,
						Derek




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