dayabay-model 1.6.1

Model of the Daya Bay reactor antineutrino experiment for neutrino oscillation analysis based on gadolinium capture data.

dayabay-model

Official model of the Daya Bay reactor antineutrino experiment for neutrino oscillation analysis based on gadolinium capture data.

Content

• Repositories
• Minimal working example

Repositories

• Development/CI: https://git.jinr.ru/dagflow-team/dayabay-model
• Contact/pypi/mirror: https://github.com/dagflow-team/dayabay-model
• PYPI: https://pypi.org/project/dayabay-model

Minimal working example

If you want to run examples from extras/mwe, clone this repository git clone https://github.com/dagflow-team/dayabay-model and change position to cloned reposiotry cd dayabay-model. However, you can just copy examples that are listed below and run them where you want after installation of package and several others steps:

1. Install package pip install dayabay-model
2. Install required packages: pip install -r requirements
3. Clone the repository with Daya Bay data git clone https://github.com/dayabay-experiment/dayabay-data-official

• Make sure that you have git-lfs in your system or install it
• After installing git-lfs, change directory to dayabay-data-official and run command git lfs pull to download more files
• Check any file that it was properly uploaded: cat parameters-common/reactor_antineutrino_spectrum_edges.tsv
• Go back to the analysis directory cd ../
• More details on how to work with data repository you can find in README.md of the data repository

4. Create soft links ln -s dayabay-data-official/hdf5 data
5. Set PYTHONPATH variable to the current directory: set PYTHONPATH=$PHYTHONPATH:$PWD. Alternative: set variable value when you are running example: PYTHONPATH=PWD python ./extras/...
6. Run script python extras/mwe/run.py or PYTHONPATH=PWD python extras/mwe/run.py

from dayabay_model import model_dayabay

model = model_dayabay()
print(model.storage["outputs.statistic.full.pull.chi2p"].data)

within python

python extras/mwe/run.py

7. Check output in console, it might be something like below

INFO: Model version: model_dayabay
INFO: Source type: npz
INFO: Data path: data
INFO: Concatenation mode: detector_period
INFO: Spectrum correction mode: exponential
INFO: Spectrum correction location: before integration
[0.]

8. Also, you may pass custom path to data, if you put path_data parameter to model. For example,

from dayabay_model import model_dayabay

model = model_dayabay(path_data="dayabay-data-official/npz")
print(model.storage["outputs.statistic.full.pull.chi2p"].data)

Example can be executed: python extras/mwe/run-custom-data-path.py or PYTHONPATH=PWD python extras/mwe/run-custom-data-path.py

9. If you want to switch between Asimov and observed data, you need to switch input in the next way

from dayabay_model import model_dayabay

model = model_dayabay(path_data="dayabay-data-official/npz")

print(model.storage["outputs.statistic.full.pull.chi2p"].data)

model.switch_data("real")
print(model.storage["outputs.statistic.full.pull.chi2p"].data)

model.switch_data("asimov")
print(model.storage["outputs.statistic.full.pull.chi2p"].data)

Example can be executed: python extras/mwe/run-switch-asimov-real-data.py or PYTHONPATH=PWD python extras/mwe/run-switch-asimov-real-data.py