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HARPgroup / HSPsquared

Hydrologic Simulation Program Python (HSPsquared)
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Hydrologic Simulation Program - Python (HSP2)

The Hydrologic Simulation Program–Python (HSP2) watershed model is is a port of the well-established Hydrological Simulation Program - FORTRAN (HSPF), re-coded with modern scientific Python and data formats.

HSP2 (pronouced "HSP-squared") is being developed by an open source team launched and led by RESPEC with internal funding. Our list of collaborators is growing, now including LimnoTech and with additional support from the U.S. Army Corps of Engineers (Engineer Research and Development Center (ERDC), Environmental Laboratory), modelers at the Virginia Department of Environmental Quality, and others.

HSP2 currently supports all HSPF hydrology and detailed water quality modules. Support for specialty modules is currently in progress. See our Release Notes_ for up-to-date details.

Read our wiki for more information on our motivation and goals for HSP2:

The HSPF Conversion Project slides (January 2017) and the Introduction to HSP2 by Jason Love (RESPEC) video (December 2017) provide additional background on the initial release_.

HSPsquared is released under the GNU Affero General Public License (AGPL), copyrighted 2017 by RESPEC_.

Source Code Directories

Getting Started

We recommend getting started by:

  1. Following our HSP2 Installation_ Instructions.

  2. Opening our interactive JupyterLab_ HSP2 tutorials in the examples sub-directory.

HSP2 Installation

We recommend Python 3.10.

Install From Pre-built Packages

Python Package Index (PyPI) +++++++++++++++++++++++++++ Starting with version 0.11.0a1 we provide a PyPI wheel package for HSP2 which should work on any supported platform for Python 3.10, 3.11, and 3.12.

.. code-block:: console

python -m pip install hsp2

Windows Executable ++++++++++++++++++ On the Releases_ page, we provide a Windows package in the zip file named HSP2_Driver_MonthYear.zip. HSP2_Driver_MonthYear.zip contains an .exe for running HSP2, enabling a user to run HSP2 without needing to do anything with Python code or Jupyter notebooks. The driver uses a file dialog to prompt for the name of the HDF5 file to run, or if that doesn't exist yet you can give it the name of a UCI or WDM file to import. It also runs with the H5 file name on the command line.

Install From Source

Clone or Download the HSPsquared Repository +++++++++++++++++++++++++++++++++++++++++++ From the HSP2squared Github page, download and extract the code using one of the options found by clicking on the green "Code" drop down button near the upper right of the page, or by downloading one of the compressed source files from the Releases page.

Place your copy of the HSPsquared folder in any convenient location on your computer.

For the rest of the installation steps, let's call this location /path/to/module/hsp2.

Create a Python Environment +++++++++++++++++++++++++++ We provide two options to installing HSP2, yet recommend option 1.

Install using only one of these options.

Option 1: Install using "conda"

Follow these steps to install using the conda_ package manager.

1. Install the Anaconda Python Distribution
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Install the `latest release`_ of the Anaconda Distribution, which includes the
conda package manager, a complete Python (and R) data science stack, and the
Anaconda Navigator GUI.  Follow `Anaconda Installation`_ documentation.

A lighter-weight alternative is to install Miniconda_.

2. Create a Conda Environment for HSP2 Modeling (optional)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Although HSP2 can be run from the default `base` environment created by
Anaconda, we recommend creating a custom environment that includes the exact
combination of software dependencies that we've in development and testing.

Use the following `conda create`_ command in your terminal or console:

.. code-block:: console

    conda create -c conda-forge -n hsp2_310 python=3.10 

Install the necessary and optional packages for HSP2 in the new environment:

.. code-block:: console

    conda install -c conda-forge -n hsp2_310 cltoolbox numba pandas pytables
    conda install -c conda-forge -n hsp2_310 h5py jupyterlab matplotlib notebook

.. code-block:: console

    conda activate hsp2_310

    cd /path/to/module/hsp2
    pip install .  # or "pip install -e ." to install in editable mode

You should now be able to run the Tutorials and create your own Jupyter
Notebooks!

Option 2: Install From Source Code Using `pip`

Installing HSP2 using pip, the Package Installer for Python_ is an alternative method to installing with conda.

  1. Install Python ^^^^^^^^^^^^^^^^^ Instructions for downloading Python to your computer based on your operating system can be found in this helpful wiki_.

  2. Create a Python Environment for HSP2 Modeling (optional) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Create a custom Python virtual environment for using HSP2, following the venv — Creation of virtual environments_ package documentation to create and activate a new environment for running HSP2.

.. code-block:: console

python -m venv hsp2_env /path/to/python/virtual/environments/hsp2_env
  1. PIP install HSP2 ^^^^^^^^^^^^^^^^^^^ Navigate to your copy of the HSPsquared folder (for these instructions /path/to/module/hsp2) on your computer in the command line.

To install using pip:

.. code-block:: console

source /path/to/python/virtual/environments/hsp2_env/bin/activate
cd /path/to/module/hsp2
pip install .  # or "pip install -e ." to install in editable mode
  1. Run PIP Installed HSP2 from the Command Line ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The pip installed 'hsp2' command has help created from the function docstrings in HSP2tools/HSP2_CLI.py.

Command Line Usage ++++++++++++++++++ Use the help to learn how to use the model and each sub-command:

.. code-block:: console

hsp2 --help
hsp2 import_uci --help
hsp2 run --help

Intended workflow from the command line:

.. code-block:: console

hsp2 import_uci import_test.uci new_model.h5
hsp2 run new_model.h5

API Usage +++++++++ The HSP2 API is designed to be used in Python scripts and Jupyter notebooks.

.. code-block:: python

from HSP2 import HSP2

.. _HSP2: https://github.com/respec/HSPsquared .. _Releases: https://github.com/respec/HSPsquared/releases .. HSPF: https://www.epa.gov/ceam/hydrological-simulation-program-fortran-hspf .. Release Notes: https://github.com/respec/HSPsquared/releases .. HSPF Conversion Project: https://github.com/respec/HSPsquared/blob/archivePy2/Why%20HSP2%20(EAA).pdf .. Introduction to HSP2 by Jason Love (RESPEC): https://www.youtube.com/watch?v=aeLScKsP1Wk .. initial release: https://github.com/respec/HSPsquared/releases/tag/0.7.7 .. GNU Affero General Public License (AGPL), copyrighted 2017 by RESPEC: https://github.com/respec/HSPsquared/blob/master/LICENSE .. _JupyterLab: https://jupyterlab.readthedocs.io/en/stable/ .. conda: https://docs.conda.io/en/latest/ .. latest release: https://docs.anaconda.com/anaconda/reference/release-notes/ .. _Anaconda Installation: https://docs.anaconda.com/anaconda/install/ .. _Miniconda: https://docs.conda.io/en/latest/miniconda.html .. HSP2squared: https://github.com/respec/HSPsquared .. conda create: https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html#managing-environments .. conda develop: https://docs.conda.io/projects/conda-build/en/latest/resources/commands/conda-develop.html .. Package Installer for Python: https://packaging.python.org/en/latest/guides/tool-recommendations/ .. this helpful wiki: https://wiki.python.org/moin/BeginnersGuide/Download .. venv — Creation of virtual environments: https://docs.python.org/3.9/library/venv.html