AMI and pyAMI

Last update: 26 Oct 2023 [History] [Edit]

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.

Making an account in AMI

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.

Finding datasets


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

  • From the main AMI web page click on Dataset Browser, select mc16 in simulated data and then select some tags to find our dataset
  • For example, select Data Type and use the wildcard %DAOD_PHYS%
  • Then select dataset number and type the ttbar process we have been using %410470%
  • If you click View Selection you should see quite a few datasets
  • Find the one that matches e6337_s3126_r10201_p4172 and there you go!

tip 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.