[Numpy-discussion] saving groups of numpy arrays to disk
Chris.Barker
Chris.Barker@noaa....
Thu Aug 25 13:42:04 CDT 2011
On 8/24/11 9:22 AM, Anthony Scopatz wrote:
> You can use Python pickling, if you do *not* have a requirement for:
I can't recall why, but it seem pickling of numpy arrays has been
fragile and not very performant.
I like the npy / npz format, built in to numpy, if you don't need:
> - access from non-Python programs
it's quick and easy to use:
In [5]: a
Out[5]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
In [6]: b
Out[6]: array([ 0., 1., 2., 3., 4.])
In [7]: filename = "test.npz"
In [8]: np.savez(filename, a=a, b=b)
In [9]: del a, b
In [10]: # now reload:
In [11]: data = np.load(filename)
In [14]: data['a']
Out[14]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
In [15]: data['b']
Out[15]: array([ 0., 1., 2., 3., 4.])
I'd go with hdf5 or netcdf if you want a standard format that can be
read by non-python software.
-Chris
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Christopher Barker, Ph.D.
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Chris.Barker@noaa.gov
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