phi

phi is a web application that aims to deliver flow data series and estimate basic hydrologic and ecohydrologic statistics from daily flow data. It is the successor of comphydro, developed by Ewerton Amorim.

Getting Started

phi is under heavy development and it is not live anywhere but you can try/contribute to it's current development version. Just follow the installation guide.

Prerequisites

• Python 3
• Django 2
• psycopg2

If you already have Python 3 installed along with pip, you can simply run pip install -r requirements.txt to install the dependencies.

Installing

In order to use phi locally, do the following.

Using PostgreSQL

1. Install the postgres extension PostGIS;
2. Create a new database;
3. Using psql connect to the created database and run the SQL script with \i /path/to/file/ODM2_for_PostgreSQL.sql to import the blank schema;
4. Clone the phi repository to your machine;
5. Edit postgres database settings in settings.py with the addition of this key: 'OPTIONS: {'options: -c search_path=public,admin,odm2}
6. Load the Controled Vocabulary terms into the database following the readme.md file at load_cvs directory;
7. Run the migrate command: python manage.py migrate
8. Run the development server with python manage.py runserver

If everything went right, this should get you going.

Using other databases

If you want to use another database system, follow the steps in the previous section replacing the ones related to the database with proper actions according to the chosen database. Here are some other blank schema scripts for you to use.

Built With

• Python - Programming language
• Django - Web framework
• pandas - Python data analysis toolkit
• Plotly - Python graphing library
• PostgreSQL - Relational database
• PostGIS- Spatial database extender for PostgreSQL
• Observations Data Model 2 - Data model used

Authors

• Augusto José Alencar - ajtga
• Ewerton Amorim - ewerton94
• Adelson Santos - ajadelson
• Clebson Carvalho - clebsonpy

See also the list of contributors who participated in this project.

Acknowledgments

The authors gratefully acknowledge the support provided by Fundação de Amparo à Pesquisa do Estado de Alagoas (FAPEAL) and the technology center (CTEC) of Universidade Federal de Alagoas (UFAL).