Use pyDeltaRCM in ten minutes! This simple guide will show you the absolute basics of getting a pyDeltaRCM model running, and give you some direction on where to go from there.
If you haven’t already, be sure to follow the installation guide to get pyDeltaRCM set up properly on your computer.
A default model¶
You can get a model running with five simple lines of code.
First, we instantiate the main
DeltaModel model object.
>>> import pyDeltaRCM >>> default_delta = pyDeltaRCM.DeltaModel()
DeltaModel() without any arguments will use a set of default parameters to configure the model run.
The default options are a reasonable set for exploring some controls of the model, and would work perfectly well for a simple demonstration here.
The delta model is run forward with a call to the
So, we simply create a for loop, and call the update function, and then wrap everything up with a call to
finalize() the model:
>>> for _ in range(0, 5): ... default_delta.update() >>> default_delta.finalize()
That’s it! You ran the pyDeltaRCM model for five timesteps, with just five lines of code.
We can visualize the delta bed elevation, though it’s not very exciting after only five timesteps…
>>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots() >>> ax.imshow(default_delta.bed_elevation, vmax=-3) >>> plt.show()
The model with set parameters¶
To run a simulation with a non-default set of parameters, we use a configuration file written in the YAML markup language named 10min_tutorial.yaml. This markup file allows us to specify model boundary conditions and input and output settings. Anything you set in this file will override the default parameters for the model.
The YAML configuration file is central to managing pyDeltaRCM simulations, so we did not create this file for you; you will need to create the YAML file yourself.
To create the YAML file, open up your favorite plain-text editing application (e.g., gedit, notepad).
YAML syntax is pretty simple for basic configurations, essentially amounting to each line representing a parameter-value pair, separated by a colon.
For this example, let’s specify three simulation controls: where we want the output file to be placed via the out_dir parameter, we will ensure that our simulation is easily reproducible by setting the random seed parameter, and we can examine what is the effect of a high fraction of bedload with the f_bedload parameter.
Enter the following in your text editor, and save the file as
10min_tutorial.yaml, making sure to place the file in a location accessible to your interpreter.
out_dir: '10min_tutorial' seed: 451220118313 f_bedload: 0.9
Now, we can create a second instance of the
DeltaModel(), this time using the input yaml file.
>>> second_delta = pyDeltaRCM.DeltaModel(input_file='10min_tutorial.yaml')
and repeat the same for loop operation as above:
>>> for _ in range(0, 5): ... second_delta.update() >>> second_delta.finalize()
Consider reading through the User Guide as a first action, and determine how to set up the model to complete your experiment, including tutorials and examples for customizing the model to achieve any arbitrary behavior you need!