AMI web interface is the dataset metadata catalogue. It is a “mediating” application, which means it correlates information from many sources.
pyAMI
is the python client for AMI
. It is in the ATLAS release and
also available standalone on lxplus or as a tar file for download to your
laptop. pyAMI documentation explains
how to use pyAMI.
To use AMI
you must have a valid grid certificate and be registered with
the ATLAS VO.
If this is your first time accessing AMI
through the web interface you
will need to set up an account. If you have not already done so, follow
the instructions described in
Registering with AMI.
Using the AMI web interface, find a simulated dataset.
We will look for the ttbar sample:
mc16_13TeV.410470.PhPy8EG_A14_ttbar_hdamp258p75_nonallhad.deriv.DAOD_PHYS.e6337_s3126_r10201_p4172
Dataset Browser
, select mc16
in
simulated data and then select some tags to find our datasetData Type
and use the wildcard %DAOD_PHYS%
%410470%
View Selection
you should see quite a few datasetse6337_s3126_r10201_p4172
and there you go!The exact ttbar dataset listed above will have been probably deleted (according to ATLAS data deletion policy) by the time you follow this tutorial, so don’t expect to find it. You can probably still find another similar dataset with the only difference a higher p-tag number.