For many experiment, the analysis of the smalldata h5 files is not too computing intensive and the analysis team can benefit from the quick and iterative nature of the Jupyter notebooks framework over the more involved cube production.
In this section, a few template notebook for common experiments are discussed.
Common features
All templates will start with a section where the experiment and run can be defined:
run = 21
exp = 'xppx47019'
ffb = True
# if 'drp' in socket.gethostname():
# p = Path('/cds/data/drpsrcf/{}/{}/scratch/hdf5/smalldata'.format(exp[:3], exp))
# else:
# p = Path('/cds/data/psdm/{}/{}/hdf5/smalldata/'.format(exp[:3], exp))
# # p = Path('/cds/data/psdm/{}/{}/scratch/ffb/hdf5/smalldata/'.format(exp[:3], exp))
# print(p.exists())
# it = p.glob('{}_Run{:04d}*'.format(exp,run))
# try: f = next(it)
# except: print('No files found at this path.')
# print(f)
# print('\n')
f = Path('./example_ccm_2d_scan.h5') # only for example. Comment or delete later
rr = tables.File(f).root
h5 = h5py.File(f)
print('\n'.join(h5.keys()))
The commented block should be uncommented whenever actual data are being analyzed.
Overview
Content Tools