This package has been tested on Windows, WSL on Windows, and Linux. If you encounter issues a linux based system is recommended, if you are on windows please look into WSL ‘Windows Subsystem for Linux’

Cloning the GitHub repository to use CUWALID allows greater control over the code.
This installation method uses Conda to install Python and all dependencies.

If you only need to run the model as it is, the PyPi package installation may be simpler.

1. Clone the GitHub Repository

First, open your terminal and clone the repository:

git clone https://github.com/CornishLeo/CUWALID.git
cd CUWALID

2. Set Up the Conda Environment

Navigate to the installers directory and run the installation script:

cd installers

# For Windows:
cwld_wos.bat

# For Linux and WSL:
sh cwld_linux.sh

Wait for the installation to complete, then activate your environment:

conda activate cwld

Now, exit the installers directory and go back to the main CUWALID folder:

cd ..

3. Download Additional Data Files

Some required files are too large to be stored on GitHub, so you need to download them separately.

From the root directory of the project, run:

cd cuwalid/tools/
python download_data.py

4. Test the Installation

Currently, testing is available for the DRYP model.

First, ensure your Conda environment is activated, then navigate to the test directory and run:

cd tests/dryp/
python run_tests.py

Once all the tests complete, the final output should look similar to this:

************************************************************
Infiltration approach: Philips
Run Interception component
100%|███████████████████████████████████████████████████████████████████████████████| 733/733 [00:21<00:00, 34.04days/s]
*** SAVING RESULTS ***
Traceback (most recent call last):
  File "/home/<username>/CUWALID/tests/test_dryp.py", line 24, in <module>
    test_dryp()
  File "/home/<username>/CUWALID/tests/test_dryp.py", line 19, in test_dryp
    assert np.allclose(out, ans)
AssertionError
Basin delineation: Test runs successfully

If the tests start running, the installation was successful! You can stop them early if needed.

5. Learn How to Run CUWALID

You can learn how to run the model using the CUWALID Example GitHub Repository
or by checking the tutorial.