Metadata-Version: 2.1
Name: cuda_guass_normal
Version: 0.6
Summary: A package used in DNN trainning in ATLAS analysis
Home-page: UNKNOWN
Author: shuzhouz
Author-email: shuzhouz@umich.edu
License: MIT
Description: 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 
        
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown
