Simulated Data Analysis: Particle Pion Simulation and Validation
Extracting simulated data of particle pion, converting files, analysis using Jupyter notebook, validation, and final summary for accurate data generation. Process includes generating, dumping, validating, and analyzing data with visualization for precision.
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Presentation Transcript
Generate data Zhou ting 2019/12/5
Content: Motivation Generate simulated data of particle ?+? Dump the data from rtraw to csv file Validate data on jupyter notebook Summary
Motivation: Prepare simulation data of pion ,and make data samples for later machine learning training
Dump the date from rtraw to csv file: Dump algorithm : get some message from mc truth eg: Px , Py , Pz , x , y , z , rawtime , cell Job script limiting conditions: take multiturn and minTurn =2
Why I draw data on jupyter notebook: Jupyter notebook is a web-based application for interactive computing.It can be applied to full process computing: developing, documenting, running code, and presenting results. By drawing on jupyter notebook, analyzing the structure of the data and observing various distributions, I verified whether the simulated data I got was correct , so that provide accurate data for later work
Validate data on jupyter notebook: 10000 events: select trackId = 0 maxTurn <6 , pdg=211 , minTturn=2
Peak? 10000 events : no selection
Summary: I got the simulated data of the particle pion, and convert rtraw file to to csv file. Then I drew and analyzed the data on the jupyter notebook, and checked the data. Now I have the simulated data ready.
Generate simulated data of particle ?+? Events: 9878 vs 26162