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 user interface can be entirely customized through the python api yt offers to ability to export your data to Firefly’s JSON format through the create_firefly_object() method. You will still need to clone the repository and ensure these data files are stored in the Firefly/data directory, this is easily done using the path_to_firefly argument of create_firefly_object() which should point at Firefly’s index.html.

You can adjust the interface settings, particle colors, decimation factors, and other Firefly settings through the returned firefly_api.reader object. Once the settings are tuned to your liking, calling the reader.dumpToJSON() method will produce the final JSON files. Note that reader.clean_JSONdir defaults to true when using create_firefly_object() so if you would like to manage multiple datasets you will need to use the dataset_name keyword argument of create_firefly_object().

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(
    path_to_firefly="repos/Firefly",
    fields_to_include=[
    'particle_extra_field_1',
    'particle_extra_field_2'],
    fields_units = ['dimensionless','dimensionless'],
    dataset_name = 'IsoGalaxyRamses')

reader.options['color']['io']=[1,1,0,1]
reader.particleGroups[0].decimation_factor=100
reader.dumpToJSON()