From physics-based simulation to ML-ready datasets — all in one Python workflow.
Before diving into tutorials and benchmarks, let's ensure that your Inductiva Python package is properly set up. To confirm everything is working as expected, simply run a quick SWASH simulation — it only takes a few seconds!
To get started, copy the code below and paste it into a Python script.
When you run the script, all the necessary simulation artifacts and configuration files will be automatically downloaded to your computer. The SWASH simulation will then be sent to a cloud machine for execution.
"""SWASH example."""
import inductiva
# Allocate cloud machine on Google Cloud Platform
cloud_machine = inductiva.resources.MachineGroup( \
provider="GCP",
machine_type="c2d-highcpu-4",
spot=True)
# Download the input files into a folder
input_dir = inductiva.utils.download_from_url(
"https://storage.googleapis.com/inductiva-api-demo-files/"
"swash-input-example.zip",
unzip=True)
# Initialize the Simulator
swash = inductiva.simulators.SWASH( \
version="10.05")
# Run simulation
task = swash.run( \
input_dir=input_dir,
sim_config_filename="input.sws",
on=cloud_machine)
# Wait for the simulation to finish and download the results
task.wait()
cloud_machine.terminate()
task.download_outputs()
task.print_summary()
After the simulation completes, a task summary will be displayed in your terminal. If the task status shows Success, congratulations! You've successfully run a SWASH simulation.
You're ready to start running simulations seamlessly!
If you encounter any issues or need further assistance, don't hesitate to Contact Us. We're here to help!