Feather

The feather object stores the output from the fitting routine. It is called feather because it is a light-weight wrapper around the fit_data struct. The name was originally temporary, but it has stuck because there are many different components within BrainTrack and the distinctive name makes it easy to remember what this particular class does.

The main role of the feather object is to group together a series of fits. Each fit returns a fit_data and plot_data struct, but when performing state tracking, you get a sequence of structs that are temporally related. The feather object stores all of these structs and encapsulates the relationship between them. The main functionality provided by the feather class is

• A wrapper to arrays of fit_data and plot_data structs
• An interface for analysis routines
• A standardized way to store and exchange fit data

The feather object incorporates a lot of helper methods. These are

• Concatenating multiple feather objects
• Retrieving a subset of the data (which is returned as another feather)
• Inserting fit_data and plot_data

Dynamic allocation

The feather class dynamically grows the arrays to provide decent performance when using feather.subrange() or otherwise adding many points. This is a significant feature because there can be over 20000 fits contained in a single feather. When you call feather.insert, the internal arrays are dynamically grown in powers of 2. The actual length of the arrays is stored in feather.prealloc_size. The amount of data contained is stored in feather.latest. If you run feather.compress() then the arrays are truncated so that feather.prealloc_size=feather.latest, which saves memory once you are done adding things to the feather.

File 'pointers'

The clouds whose data is stored in plot_data are important to be able to plot. However, they consume quite a lot of data, which is a huge issue for fits that have over 20000 spectra. To deal with this, instead of storing the actual structs in the feather, you can instead store the file name of a .mat file that contains the plot_data variable. This files are then automatically loaded by mcmc.viewer. To use this functionality, you can simply insert a string containing the full file name of the .mat file. Everything else works as usual.

• The file is automatically split into the parent folder and the file name itself. All of the files need to be stored in the same folder
• This folder is stored in feather.path_prefix. If you move the fit folder somewhere else, simply change feather.path_prefix appropriately. This way you don't need to change the path in all of the plot_data strings
• If plot_data contains strings, the method feather.full iterates over the strings and loads the plot data into memory, converting the feather into one which stores the actual plot data. This provides better performance for visualization, but is only recommended if you have a few (e.g. < 500) spectra in the feather