If npy files do in fact work cross-platform, then I'm baffled. Any
ideas about what could be causing these NaNs in Leon's script? The
files on the website haven't been modified since they were put online.
Here's a more compact version of the NaN checking:
>>> import numpy as np
>>> data = np.load('sdss_photoz.npy')
>>> np.sum([np.isnan(data[col]) for col in data.dtype.names])
0
Leon, what version of numpy are you using?
Jake
On 11/16/2012 08:22 AM, Nelle Varoquaux wrote:
On 16 November 2012 17:14, Robert Kern <[email protected]
<mailto:[email protected]>> wrote:
On Fri, Nov 16, 2012 at 4:03 PM, Nelle Varoquaux
<[email protected] <mailto:[email protected]>> wrote:
>> Hi Leon,
>> When I run your script, I get no instances of NaN in the data.
>>
>> I wonder if it's a problem with storing the data as a npy file.
I asked
>> around last spring and everybody seemed to think that the format is
>> compatible across platforms and numpy versions, but I may be
wrong. Does
>> anybody know?
>
> I think numpy relies on pickle for those. These are plateform
dependant
> (32bits vers 64bits), and python version dependant. Pickle is
not a safe way
> to store data, thought I never had problems on my personal
computers.
> Saving as txt is more reliable.
The NPY file format only uses pickle for object arrays, which this
isn't. Otherwise, it records floats in standard IEEE-754 binary format
with enough header information to reconstruct it portably across
platforms. I see no NaNs, myself.
OK. Good to know :)
Cheers,
N
--
Robert Kern
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