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import numpy as np
import psana
import h5py

NUM_EVENTS_TO_WRITE=203

ds = psana.DataSource('exp=xpptut15:run=54:smd')

h5out = h5py.File("simple_saved_data_for_xppdaq12_run54_cspaduserSmallData.h5", 'w')
saved = h5out.create_dataset('saved',(0,), dtype='f8', chunks=True, maxshape=(None,))

cspad = psana.Detector('cspad', ds.env())

for idx, evt in enumerate(ds.events()):
    if idx > NUM_EVENTS_TO_WRITE: break
    calib = cspad.calib(evt)
    if (calib is None): continue
    saved.resize((idx+1,))
    saved[idx] = np.sum(calib)

h5out.close()

Good tools to inspect an h5 files are h5ls and h5dump. For example, doing:

 h5ls -d -r simple_saved_data_for_xppdaq12_run54_cspaduserSmallData.h5

shows the dataset and its values:

/                        Group
/saved                   Dataset {21/Inf}

    Data:
        (0) 23773.12109375, 135712.25, 65513.67578125, 16749.18359375, 141970.578125, -3539.29711914062, 11022.4033203125,
        (7) 27192.0703125, -6797.27734375, 39909.9140625, 18433.25, 3982.2890625, 20780.5, 43662.01953125, 81957.65625,
        (15) 86769.421875, 96112.8515625, 115826.53125, -22957.05078125, -99477.6875, 79700.59375

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[cpo@psana1511]$ h5ls -d -r userSmallData.h5 
/                        Group
/saved                   Dataset {4/Inf}
    Data:
        (0) 23773.12109375, 135712.25, 65513.67578125, 16749.18359375 

A more advanced tutorial on saving data to an hdf5 file can be found on the page: More Advanced Tutorial on Saving Output in Hdf5

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