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CoVEMDA-1.0

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مشاهده بیشتر
1.0
1.0

توضیحات

CoronaVirus - Electricity Market Data Analyzer (CoVEMDA)
ویژگی مقدار
سیستم عامل -
نام فایل CoVEMDA-1.0
نام CoVEMDA
نسخه کتابخانه 1.0
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Guangchun Ruan
ایمیل نویسنده rgcthu@163.com
آدرس صفحه اصلی https://github.com/tamu-engineering-research/COVID-EMDA
آدرس اینترنتی https://pypi.org/project/CoVEMDA/
مجوز -
# CoVEMDA (Python Version) **CoronaVirus - Electricity Market Data Analyzer (CoVEMDA)** is an open-access and ready-to-use toolbox to track COVID-19 impacts on U.S. power systems. This document is a quick overview of this toolbox. ## Features CoVEMDA is primarily working with COVID-EMDA+ data hub, with some major functions such as: baseline estimation, regression analysis, scientific visualization, and other useful supplementary functions. Extenal data and models are allowed for further extensions. ## Navigation CoVEMDA root directory contains four folders, a setup.py script, a README.md document, and a LICENSE text file. One can run the setup script to check the dependencies of current environment, or use pip command to retrieve from PyPI. Folder `lib/` contains the source codes for CoVEMDA, which are collectively organized in several script files according to the realized functions. It is recommended to call the **integrated functions** or **high-level functions** as they are user-oriented and simple to use. Turn to **low-level functions** only in case that more flexible and refined configurations are required. Folder `docs/` contains a **User Manual** for CoVEMDA. This manual includes simple guidance for first-time users, as well as detailed explanation of all the features and functions, along with illustrative examples. Though this is a complete guide for anyone that is interested in more details, reading **Section 1 (Introduction)** and **Section 2 (Getting Started)** is enough for beginners to try it out. Folder `data/` contains the temporary files of CoVEMDA, including a data collection updated to March 2021 (`data/data_archive/`) and several pretrained backcast models (`data/backcast`). ## User Manual An extensive **User Manual** is attached to the toolbox, which can be found at `docs/`. In this manual, users may find some basic-level guidances as well as comprehensive details of the toolbox implementation. Here, the the manual are organized with the following sections: 1. Introduction 2. Getting Started 3. Data Hub 4. Toolbox 5. Baseline Estimation 6. Regression Analysis 7. Scientific Visualization 8. Acknowledgments We highly recommend you to read Section 1 and 2 before using CoVEMDA. The rest of the manual introduces all the features, classes, and functions from principle to practice in detail. Read Section 3 and 4 to get some knowledge of the programming architecture and useful interfaces. Read Section 5, 6, and 7 for advanced usage and customization.


نیازمندی

مقدار نام
>=1.2.4 pandas
>=1.6.2 scipy
>=0.12.2 statsmodels
>=0.24.1 scikit-learn
>=3.3.4 matplotlib


زبان مورد نیاز

مقدار نام
>=3.5 Python


نحوه نصب


نصب پکیج whl CoVEMDA-1.0:

    pip install CoVEMDA-1.0.whl


نصب پکیج tar.gz CoVEMDA-1.0:

    pip install CoVEMDA-1.0.tar.gz