ripple1d 0.3.11

HEC-RAS model automation

ripple1d

Utilities for repurposing HEC-RAS models for use in the production of Flood Inundation Maps (FIMs) and rating curves for use in near-real time flood forecasting on the NOAA National Water Model network. Go to ReadTheDocs for more information on ripple1d.

Contents

• api : Source code for the Flask API and Huey queueing system for managing parallel compute.
• production (Deprecation Warning) : This directory contains scripts used by the development team for testing ripple1d outside of the API. The contents are not included in the PyPi package and may not be stable or up to date.
• ripple1d: Source code for the ripple1d library.
• tests: Unit tests.up

Requirements

OS Dependency: Ripple requires Python version >=3.10 and a Windows environment with Desktop Experience (GUI, not a headless Windows server) and HEC-RAS installed (currently version 6.3.1 is supported).

Installing Ripple

NOTE: Using a python virtual environment is not required but is highly recommended.

Using pip

1. Activate virtual environment as shown below and install the ripple1d package using pip using PowerShell:

   pip install ripple1d
   

Building from source

1. Activate virtual environment as shown below and build from source:

   git clone https://github.com/dewberry/ripple1d.git
   cd ripple1d
   
   # if needed install build tools
   pip install setuptools wheel build
   python -m build_wheel
   pip install dist/*.whl
   
   # Either have PowerShell get the file name or look in the dist/ directory for the latest .whl file
   # Example filename: `ripple1d-0.3.0-py3-none-any.whl`
    $wheel = Get-ChildItem -Path dist -Filter *.whl | Select-Object -First 1
    pip install $wheel.FullName
   

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Testing the Installation

1. Verify the installation by importing ripple1d in a Python shell:

   python
   >>> import ripple1d
   >>> print(ripple1d.__version__)
   

2. Run the unit tests to ensure everything is working correctly:

   pytest tests/
   

See the REST API documentation for available endpoints and usage.

Setting up a virtual environment

1. Install Python

2. Create a virtual Python environment using Command Prompt or PowerShell:

   Option 1: Windows Command Prompt

   %LOCALAPPDATA%\Programs\Python\Python312\python.exe -m venv %homepath%\venvs\venv-py312
   

   Option 2: Windows PowerShell

   $pythonExe = "$env:LOCALAPPDATA\Programs\Python\Python312\python.exe"
   $venvPath = "$env:USERPROFILE\venvs\venv-py312"
   & $pythonExe -m venv $venvPath
   

3. Activate (enter) the new virtual environment:

   Option 1: Windows Command Prompt

   %homepath%\venvs\venv-py312\Scripts\activate.bat
   

   Option 2: Windows PowerShell

   & "$env:USERPROFILE\venvs\venv-py312\Scripts\Activate.ps1"
   

4. Confirm that the activation worked.

   1. You should see that a parenthetical (venv-py312) has been added to the left side of your current line in the terminal.
   2. Enter where python and confirm that the top result is sourcing Python from the new directory.

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Credits and References

1. Office of Water Prediction (OWP)
2. Dewberry
3. Raytheon
4. Earth Resources Technology, Inc.
5. ras2fim
6. USACE HEC-RAS
7. NOAA National Water Model (NWM)

Special Thanks to: David Bascom (FEMA), Christina Lindemer (FEMA), Dave Rosa (FEMA), Paul Rooney (FEMA), Julia Signell and Dan Pilone of Element84, and the developers of STAC.