2. UFO Buster analysis tool A brief introduction / Software layout
Martyna Dziadosz
TE-MPE-PE |

3. Presentation plan Motivations UFO Buster Analysis Tool
layout diagram
functionalities
UFO Buster vs. UFO Buster Analysis Tool
Summary
During today’s presentation I’m going to talk about
Project motivation
Tool itself, it’s layout and offered functionalities
Finally I will move to its comparison with UFO Buster in accordance to the analyzes feature
Will finish by summing everything up
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

4. We want an analysis tool which is:
Motivation
We want an analysis tool which is:
Fast
Easy
Reliable & reproducible
Enables advanced analysis
Focus on real UFO data
All in one place + manual/readme
One module for frequent analyses
Search for correlations
What prompted us for the analysis tool development?
So the need of the tool, that will allows fast and easy advanced analysis focused on UFO events independently from UFO Buster software. Which has to be reliable and reproducible.
Obtaining mentioned requirements throught the application of certain conditions. We’re focus on only real UFO data.
Software wasn;t interferring with the originial UFO data.
The tool consist of several, independent from each other moduls, What is more it provide searching for the correlations in UFO events
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

5. Structure of the UFO Buster analysis tool
Data Extraction
Raw Data Analysis
plot UFO event
analysis signal shape
group like events
Collimator Losses
correlation with elastic losses (IP7/IP3/IP6)
Advanced Analysis
statistical analysis (UFO rates etc.)
correlations to LHC parameters
determination of UFO location
access data
select only real UFO events (reduce data volume)
discard empty files
The following slide presents the bigger picture of the UFO Buster analysis tool. As I’ve already have mentioned it contains 4 independent from each other modules:
data extraction, raw data analysis, collimator losses and advanced analysis. The 1st one is intendent to access the data and selecting only real once avoiding empty files.
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

6. DATA EXTRACTION ü ü ü Step 1 Access and retrive data Original PM data
UFO Buster data
PM data
.sdds decoding with JAVA
REST API ü
standard year analysis ü
16L2 area analysis
1st modile is devoted to to access and retrive the data. Here depending n the purpose od the analysis we can either take original UFO Buster Captur Buffer data
To proceed with standard year analysis or location analysis
OR PM data from which then 16L2 area analysis were conducted ü
analysis via locations
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

7. ü RAW DATA ANALYSIS Plot time-resolved UFO event
Step 2
RAW DATA ANALYSIS
Plot UFO event & compare with UFO Buster output
Losses in Gy/s
Time (here in 80 µs bits)
UFO Buster from capture buffer
After data obtainment initial analysis were conducted. First of all to check the corectness of retrive data,
Time-resolved UFO event was plot and compared with the UFO Buster display.
As we can see from attached plots, the obained results (plot on the left) corresponds to the one from UFO Buster (right hand side)
Plot time-resolved UFO event ü
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

8.  ü RAW DATA ANALYSIS Gaussian fitting signal shape analysis
Step 2
RAW DATA ANALYSIS
Analyse and group UFO events
Losses in Gy/s
Time (here in 80 µs bits)
ONGOING
subsequently the analysis of the UFO event (in accordance to its duration, totall losses, max value) were made.
Furthermore the Gaussian function was fit in order to observe the time signal changes.
Right now work is focused on grouping like events by the FWHD, max and symmertry values, ü 
Gaussian fitting
signal shape analysis
Group events by FWHD, max, symmetry
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

9. ü STATISTICAL ANALYSIS Plot of loss distribution along LHC
Step 3
STATISTICAL ANALYSIS
on reduced sample size
number of UFOs
Location in LHC [m]
UFO rate vs. time or location
number of UFOs
The next step are statistical analysis made on reduced sample size.
Presented plots of the UFO rate vs time and location. Losses distibution along LHC, which
Gives usmore information about area, that are more pronounced to the UFO occurnece
Integrated losses[Gy/s] ü
Plot of loss distribution along LHC
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

10. UFO Buster Analysis Tool
vs.
access to CaptureBuffer data display
- manual UFO event verification (by eye)
possibility to look into different BLMs, sectors, RS
nice GUI
analysis part works relatively slow
access to CaptureBuffer & PM data
- automated verification of real UFO events
- plot losses data
possibility to look into different BLMs, sectors, RS
advantages for future users
- easy, user friendly
- independent modules for frequent analysis
- .json file to set interesting parameters
- fast analysis
- python scripts, that enables dedicated analysis
depending on needs
- documented in a GitLab repository
dataset reduction
searching for correlation plots
enable fast analysis
Let’s move to the most interesting part of the following presentation, namely the comparison of UFO Buster & UFO Buster analysis tool functionalities.
Here it is very important to mention that those concern the analysis module as Ufo Buster itself is a software intended for UFO event detection.
So it’s main application
Both provide
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

11. Summary of Achievementsü
Reduced data volume
→ faster analysis ü
BLM losses vs time
→ UFO event visualization ü
UFO rate plots
→ vs time, location or BLM name ü
Plot of loss distribution along LHC
What is done? ü
Gaussian fitting & signal shape analysis
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

12. Conclusion – future needs
Functionality validation with big data needed
UFO events grouping
Advanced, dedicated statistical analysis
UFO shape analysis
Extension to look at long straight section
Analysis for collimators area
Eventual analysis of ULO
Creation of user-friendly GUI
To conclude now we have principally working tool created within usage of Python software.
Which has still a way of imporvement and development
-> validation with big data as so far the data volume was reduced nad the focus was kept at real UFO events
-> currently ongoing UFO events grouping
-> advanced analysis
-> almost doen UFO shape analysis
-.... (read)
… to be continued!
10/10/2017 | Schematic overview of UFO Buster analysis tool
Document reference

13. Thank you for your attention. 
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

15. F4 DATA EXTRACTION – (UFO Buster) Step 1
Merge only relevant info into one file F3 & F4
Basic info (timestamp, fill number, machine parameters)
UFO BLM + neighbours (losses + DCUM)
Time-resolved data (capture buffer)
Presented at the previous slides consecutive steps and applied conditions for F1 and F2 yield in a result to creating file F3, which contains necessary for the further steps
-> basic informations, such as timestamp, fill number and machine parameters
-> registered by BLMs losses for UFO BLM + it’s neighbours and selected BLMs localized in the collimators area F4
excel file (.csv)
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

16. F2 F1 F2 INPUT Condition 1 Condition 2 Condition 3 Condition 4
STABLE beam mode
verified UFO
Condition 1
F2 for which matching F1 exist
Condition 2 F2
losses > threshold (5 * 10-3)
Condition 3
2 consecutive points fullfill cond3
Condition 4
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

17. ü F4 DATA EXTRACTION Reduces data volume for quick analysis Step 1
excel file (.csv)
Reduces data volume for quick analysis ü
As F3 is created only for event fulfilling certain conditions,
Data volume has been reduced, what allows for quick analysis
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

18. F1 F2 2 WAYS OUTPUT: EXTRACT find the corresponding file type 2
.sdds ASCII file
.sdds binary file
EXTRACT
DECONVERSION !!!
JAVA
1) looking for F2 with the same timestamp and fillnumber
2) go to an appropriate path using fillnumber. Then look for the corresponding F2 using naming convention
Fillnumber
Timestamp
UFO_BLM_Expert_name
Dcum []
VerificationLevel
beam_mode
Expert Name
Java objects:
String[] header (1D matrix with BLMs names)
Int[][] value (2D matrix with all BLMs signal losses)
OUTPUT:
List of files type F1 for which the exist the corresponding file type F2
07/12/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

19. DATA EXTRACTION – (PM REST API)
Step 1
DATA EXTRACTION – (PM REST API)
Presented at the previous slides consecutive steps and applied conditions for F1 and F2 yield in a result to creating file F3, which contains necessary for the further steps
-> basic informations, such as timestamp, fill number and machine parameters
-> registered by BLMs losses for UFO BLM + it’s neighbours and selected BLMs localized in the collimators area
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

20. Integrated losses of all UFOs per BLM
ROMAN POT AREA
Hot spots, where more than one UFO event occured during 2016 LHC-working time
Those are mainly the roman pots area, where we can expect such an behaviour
10/10/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

21. Appendix – F1 structure
07/12/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz

22. Appendix – F2 structure
07/12/2017 | Schematic overview of UFO Buster analysis tool
Martyna Dziadosz