Metadata-Version: 2.1
Name: thickbrick
Version: 0.1.1
Summary: A data analysis package
Home-page: https://prasanthcakewalk.gitlab.io/thickbrick
Author: Prasanth Shyamsundar
Author-email: prasanth.s.cmi@gmail.com
License: MIT
Description: # Welcome to ThickBrick!
        
        ThickBrick is a Python 3 implementation of certain data selection and categorization algorithms originally conceived in the context of data analysis in high energy physics.
        
        The algorithms are intended to train event selectors and categorizers that maximize the sensitivity of physics analyses to the presence of a signal being searched for, or to the value of a parameter being measured.
        
        Project website: <https://prasanthcakewalk.gitlab.io/thickbrick/>  
        
        ### References and citation guide
        
        If you use the algorithms implemented in ThickBrick in your work, please consider citing the original papers that introduced them.
        
        * Konstantin K. Matchev, Prasanth Shyamsundar, _"Optimal event selection and categorization in high energy physics, Part 1: Signal discovery"_, [arXiv:1911.12299 [physics.data-an]](https://arxiv.org/abs/1911.12299).
        * Parts 2 and 3 to follow.
        
        This list does not include the now-mainstream algorithms and ideas from mathematics, statistics, machine learning, etc, used in the package. The package documentation mentions the methods used where appropriate.
        
        ### Copyright
        
        Copyright &copy; 2019 Konstantin Matchev and Prasanth Shyamsundar  
        <details>
        <summary>ThickBrick is licensed under the MIT License (click to expand).</summary>
        <br>
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        </details>
        
Keywords: thick brick taab autocategorizer
Platform: any
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 3 - Alpha
Requires-Python: >=3.6
Description-Content-Type: text/markdown
