Generalizes the way that sarracen rendering and interpolation functions work with mass and density data, to work seamlessly in more scenarios. As well, the read_phantom method has been extended with more options, to work better in more cases:
drop_sinks: Sink particles can cause significant conflicts and memory issues when included in the DataFrame structure. When true, the sink particles are dropped from the dataset. This is true by default.
separate_types: The existence of several particle types with different properties (such as masses) can cause confusion and issues with rendering & interpolation functions. When true, the different particle types are separated into different DataFrames (in this case, read_phantom returns a list of dataframes). This is true by default.
When using the rendering / interpolation functions mass must exist as a single column in the dataset, or in a singlemassparameter in the param dictionary.
Generalizes the way that sarracen rendering and interpolation functions work with mass and density data, to work seamlessly in more scenarios. As well, the
read_phantommethod has been extended with more options, to work better in more cases:drop_sinks: Sink particles can cause significant conflicts and memory issues when included in the DataFrame structure. When true, the sink particles are dropped from the dataset. This is true by default.separate_types: The existence of several particle types with different properties (such as masses) can cause confusion and issues with rendering & interpolation functions. When true, the different particle types are separated into different DataFrames (in this case, read_phantom returns a list of dataframes). This is true by default.When using the rendering / interpolation functions mass must exist as a single column in the dataset, or in a single
massparameter in theparamdictionary.