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https://github.com/loiccoyle/pylossmap
Python package to help with the handling of the LHC's BLM measurements.
https://github.com/loiccoyle/pylossmap
Last synced: about 2 months ago
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Python package to help with the handling of the LHC's BLM measurements.
- Host: GitHub
- URL: https://github.com/loiccoyle/pylossmap
- Owner: loiccoyle
- Created: 2019-10-28T09:26:05.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2021-11-17T15:10:18.000Z (about 3 years ago)
- Last Synced: 2023-03-06T08:27:46.913Z (almost 2 years ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 132 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
[](https://pylossmap.readthedocs.io/en/latest/?badge=latest)
# pylossmap
This library facilitates the fetching and handling of the LHC's BLM measurements.
# Installation
```sh
git clone https://github.com/loiccoyle/pylossmap
cd pylossmap
pip install .
```
# Requirements
* [pytimber](https://www.github.com/rdemaria/pytimber)
* pandas
* numpy
* matplotlib
Optional:
* tqdm
# Usage
**See examples in the** `notebooks` **folder.**
There are 3 main classes:
## The BLMDataFetcher class
This class will handle the fetching of BLM data and assigning the correct header information.
It has 2 main methods of fetching data:
* `from_datetime`: which takes 2 datetime objects or epoch/unix time `int`s/`float`s.
* `from_fill`: which takes a fill number along with the requeted beam modes.
It also has a helper method to fetch data surrounding triggers of the ADT blowup:
* `iter_from_adt`: iteratively yield BLMData instances of data surrounding the trigger of the ADT blowup within the requested time range.
A helper method to facilitate the fetching of BLM background for data following an ADT trigger:
* `bg_from_ADT_trigger`: takes datetime of the ADT trigger, it will figure out a time interval where no ADT blowup triggers occurred and fetches the background data.
The fetcher class returns the data in the shape of a BLMData instance.
## The BLMData class
This class handles the BLM data, the main methods are:
* `plot`: creates a waterfall plot of the BLM data.
* `iter_max`: iterates on index of the max values of the desired BLMS, defaults to the primary IR 7 BLMs.
* `fetch_intensity`,`fetch_filling_scheme`,`fetch_number_bunches`,`fetch_energy`: fetches some additional beam information for the current time range.
You can access the raw data through the `data` attribute.
In order to create a loss map of a given time, use the `loss_map` method, and provide the desired datetime. This outputs a `LossMap` instance.
## The LossMap class
This class handles the loss map processing. It provides a pandas/numpy style interface for filtering and selecting BLMs.
Some main methods are:
* `plot`: to create a loss map plot.
* `set_background`: to set another LossMap instance as the background signal.
* `clean_background`: to substract the background.
* `normalize`: to normalize the data to the max value, or the signal of the provided BLM.
* `fetch_intensity`,`fetch_filling_scheme`,`fetch_number_bunches`,`fetch_energy`: fetches some additional beam information for the current timestamp.
* various methods for filtering based on `cell`, `IR`, `side`, collimator `type`, `beam`, ...