Saving With H5py Arrays Of Different Sizes

I am trying to store about 3000 numpy arrays using HDF5 data format. Arrays vary in length from 5306 to 121999 np.float64 I am getting Object dtype dtype('O') has no native HDF5 e

Solution 1:

Looks like you tried something like:

In [364]: f=h5py.File('test.hdf5','w')    
In [365]: grp=f.create_group('alist')

In [366]: grp.create_dataset('alist',data=[a,b,c])
...
TypeError: Object dtype dtype('O') has no native HDF5 equivalent

But if instead you save the arrays as separate datasets it works:

In [367]: adict=dict(a=a,b=b,c=c)

In [368]: for k,v in adict.items():
    grp.create_dataset(k,data=v)
   .....:     

In [369]: grp
Out[369]: <HDF5 group "/alist" (3 members)>

In [370]: grp['a'][:]
Out[370]: array([ 0.1,  0.2,  0.3])

and to access all the datasets in the group:

In [389]: [i[:] for i in grp.values()]
Out[389]: 
[array([ 0.1,  0.2,  0.3]),
 array([ 0.1,  0.2,  0.3,  0.4,  0.5]),
 array([ 0.1,  0.2])]

Solution 2:

Clean method for variable length internal arrays: http://docs.h5py.org/en/latest/special.html?highlight=dtype#arbitrary-vlen-data

hdf5_file = h5py.File('yourdataset.hdf5', mode='w')
dt = h5py.special_dtype(vlen=np.dtype('float64'))
hdf5_file.create_dataset('dataset', (3,), dtype=dt)
hdf5_file['dataset'][...] = arrs

print (hdf5_file['dataset'][...])
>>>array([array([0.1,0.2,0.3],dtype=np.float64), 
>>>array([0.1,0.2,0.3,0.4,0.5],dtype=np.float64, 
>>>array([0.1,0.2],dtype=np.float64], dtype=object)

Only works for 1D arrays, https://github.com/h5py/h5py/issues/876