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(ps-4.3.2) psanagpu109 tests $ mpirun -n 3 python livemode.py |
Jump to events
Psana2 can jump to particular events when given a list of timestamps. In the example below, we only want to process these four timestamps. Note that timestamp array should be formatted to np.uint64.
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from psana import DataSource
import numpy as np
timestamps = np.array([4194783241933859761,4194783249723600225,4194783254218190609,4194783258712780993], dtype=np.uint64)
ds = DataSource(exp='tmoc00118', run=222, dir='/cds/data/psdm/prj/public01/xtc',
timestamps=timestamps)
myrun = next(ds.runs())
opal = myrun.Detector('tmo_atmopal')
for nevt, evt in enumerate(myrun.events()):
img = opal.raw.image(evt)
print(nevt, evt.timestamp, img.shape) |
Here is the output
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(ps-4.5.5) monarin@psanagpu111 (master *) psana2 $ python test_jump.py
0 4194783241933859761 (1024, 1024)
1 4194783249723600225 (1024, 1024)
2 4194783254218190609 (1024, 1024)
3 4194783258712780993 (1024, 1024) |
MPI Task Structure
To allow for scaling, many hdf5 files are written, one per "SRV" node. The total number of SRV nodes is defined by the environment variable PS_SRV_NODES (defaults to 0). These many hdf5 files are joined by psana into what appears to be one file using the hdf5 "virtual dataset" feature.
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