Visualizing Particle Datasets with Firefly¶

Firefly is an interactive, browser-based, particle visualization platform that allows you to filter, colormap, and fly through their data. The Python frontend allows users to both load in their own datasets and customize every aspect of the user interface. yt offers to ability to export your data to Firefly’s ffly or JSON format through the create_firefly_object() method.

You can adjust the interface settings, particle colors, decimation factors, and other Firefly settings through the returned Firefly.reader object. Once the settings are tuned to your liking, calling the reader.writeToDisk() method will produce the final ffly files. Note that reader.clean_datadir defaults to true when using create_firefly_object() so if you would like to manage multiple datasets make sure to pass different datadir keyword arguments.

Screenshot of a sample Firefly visualization

Exporting an Example Dataset to Firefly¶

Here is an example of how to use yt to export data to Firefly using some sample data.

ramses_ds = yt.load("DICEGalaxyDisk_nonCosmological/output_00002/info_00002.txt")

region = ramses_ds.sphere(ramses_ds.domain_center, (1000, "kpc"))

reader = region.create_firefly_object(
    "IsoGalaxyRamses",
    fields_to_include=["particle_extra_field_1", "particle_extra_field_2"],
    fields_units=["dimensionless", "dimensionless"],
)

## adjust some of the options
reader.settings["color"]["io"] = [1, 1, 0, 1]  ## set default color
reader.particleGroups[0].decimation_factor = 100  ## increase the decimation factor

## dump files to
##  ~/IsoGalaxyRamses/Dataio000.ffly
##  ~/IsoGalaxyRamses/filenames.json
##  ~/IsoGalaxyRamses/DataSettings.json
reader.writeToDisk()