Python package use cuda to normalize input variables using cuda package in ATLAS analysis
Function use to do Guassian Normalization: Mean: $$\mu_{i}=\frac{\sum x_{i}\times w_{i}}{\sum w_{i}}$$ Variance: $$\sigma_{i}=\frac{\sum (x_{i}-\mu_{i})^{2}\times w_{i}}{\frac{N-1}{N}\times\sum w_{i}}$$ Normalized input feature: $$\bar{x_{i}}=\frac{x_{i}-\mu_{i}}{\sigma_{i}}$$
Main function: guass_normal((1),(2),(3))
Input:
(1):Numpy array contain all input features you want to normalize. (2):Numpy array used to calculate each feature's mean and variance. (3):1-d Numpy array contains each events weight in (2)
(1) and (2) must have the same number of columns.
cuda_cut((1),(2),(3)): Used to calculate event yield after applying DNN cut.
Input: (1): 1-d numpy array include the variable you want to cut. (2): 1-d numpy array include event weight. (3): cut threshold
1 maintainer
Release files for cuda-guass-normal 1.13
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Source distribution (sdist)
| File | Size | Uploaded | |
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| cuda_guass_normal-1.13.tar.gz | 2.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cuda_guass_normal-1.13-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:10.4 kB
Release files / cuda_guass_normal-1.13.tar.gz
| Download URL | cuda_guass_normal-1.13.tar.gz |
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| Size | 2.9 kB |
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Release files / cuda_guass_normal-1.13-py3-none-any.whl
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| Tags | Python 3 |
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