fcpgtools 2.0.5

Tools to create Flow-Conditioned Parameter Grids (FCPGs) from Flow Direction Rasters (FDRs) and arbitrary rasterized parameter data.

Flow-Conditioned Parameter Grid (FCPG) Tools Documentation

For detailed documentation please reference our ReadTheDocs site!

Note that the most recent version of this repository is available on GitLab. While mirrored on GitHub, the repos can get out of sync.

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Getting Started

Installation

FCPGtools can be installed from PyPI into a virtual environment containing GDAL, and for full functionality, TauDEM as well.

We strongly encourage the following installation workflow:

1. Install the Anaconda Python Distribution or Miniconda

   • Anaconda Individual Edition - includes conda, a complete Python (and R) data science stack, and the helpful Anaconda Navigator GUI.
   • A lighter-weight alternative is to install Miniconda.

2. Use the conda command line to clone our lightweight fcpgtools_base virtual environment that contains non-Python dependencies from the environment.yml file available in our repo. Either clone the repo, or just download the .yml file locally, and run the following commands:

   conda env create -f {PATH}/environment.yml
   

   • Note: We also provide a more robust environment_dev.yml virtual environment for developers containing all libraries relevant to making contributions as well as running our example notebooks.

3. Activate the fcpgtools_base environment, and pip install fcpgtools.

   pip install fcpgtools
   

4. (optional) pip install optional libraries required to run our demo notebook (examples/v2_fcpgtools_demo.ipynb), and to leverage in-line function completion/type-hints.

   pip install jupyterlab
   pip install ipympl
   pip install python-lsp-server
   pip install jupyterlab-lsp
   pip install pydaymet
   

Using FCPGtools

Version 2.0 of FCPGtools has a "flat" architecture, meaning all functions can be accessed by importing the main fcpgtools module as shown in a simple example below:

# creating an flow accumulation raster from a Flow Direction Raster (FDR)
import fcpgtools

path_to_fdr = r'YOUR/PATH/HERE/fdr.tif'

flow_accumulation_grid = fcpgtools.accumulate_flow(
    d8_fdr=path_to_fdr,
) -> xarray.DataArray

Please refer to our documentation's Cookbook page for more intricate examples of usage.

Citation

• Version 2.0 was released in January, 2023.
  • Barnhart, T.B., Nogueira, X.R., Siefken, S.A., Schultz, A.R., Aufenkampe, A., Tomasula, P., 2023, Flow-Conditioned Parameter Grid Tools Version 2.0.
• Version 1.1 was released in September, 2022.
• Version 1.0 (IP-112996) was approved on September 3, 2020.
  • Barnhart, T.B., Sando, R., Siefken, S.A., McCarthy, P.M., and Rea, A.H., 2020, Flow-Conditioned Parameter Grid Tools: U.S. Geological Survey Software Release, DOI: https://doi.org/10.5066/P9W8UZ47.

Migrating from Version 1.0

Version 2.0 of FCPGtools is a ground-up refactor and rebuild of Version 1.0. Backwards compatibility is broken, and many work-flows have been significantly streamlined. We strongly suggest that any users accustomed to Version 1.0 reference our updated documentation site.

A non-exhaustive list of key updates is below:

• All functions output an in-memory xarray.DataArray object, allowing for functions to be strung together into performance oriented pipelines.
  • xarray.DataArray objects have a variety of powerful features and optimizations. For more information please reference the library's documentation.
  • Rasters can still be saved to a local GeoTIFF file by providing a valid .tif path to param:out_path.
• All functions can now accept either local string paths, local pathlib.Path objects, or in-memory xarray.DataArray objects.
• Multi-band parameter grids are now supported!
  • Example: Passing a 12-month precipitation raster (where each month is a raster band) into fcpgtools.accumulate_parameter() will output a 12-band xarray.DataArray object.
• Flow Direction Raster format conversion (i.e. ESRI -> TauDEM) is now automated behind-the-scenes.
• Support for multiple "terrain engines" gives users optionality and increases dependency deprecation resiliancy.
  • Where necessary users can set param:engine to taudem (default) or pysheds.
  • Note that the pysheds terrain engine is signifcantly more performant, however it currently only supports accumulate_flow() and accumulate_parameter().

Please reference our markdown refactored_names document for a complete mapping of Version 1.1 to Version 2.0 function names.

Disclaimers

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.

Please see DISCLAIMER.md in the project repository.

License

Please see LICENSE.md in the project repository.