Resampling¶

These are some low-level functions in the resampling package, which are called by the idyom:idyom function. You shouldn't need to use them unless you are developing the code.

resampling:idyom-resample¶

idyom:idyom uses resampling:idyom-resample to compute the note-by-note IC values, and can be used to obtain these a list. The function takes a subset of the top-level arguments (see above):

• Required: dataset-id, target-viewpoints, source-viewpoints (no viewpoint selection)
• Model: models, ltmo, stmo
• Training: pretraining-ids, k, resampling-indices

resampling:output-information-content¶

Takes the output of resampling:idyom-resample and returns the average information content. It takes the following arguments:

• predictions: the output of resampling:idyom-resample
• detail: an integer which determines how the information content is averaged (these are returned as multiple values):
  • 1: averaged over the entire dataset
  • 2: and also averaged over each composition
  • 3: and also for each event in each composition

resampling:format-information-content¶

resampling:format-information-content takes the output of resampling:idyom-resample and writes it to file. It takes the following arguments:

• predictions: the output of resampling:idyom-resample
• file: a string denoting a file
• dataset-id: an integer reflecting the dataset-id
• detail: an integer which determines how the information content is averaged (these are returned as multiple values):
  • 1: averaged over the entire dataset
  • 2: and also averaged over each composition
  • 3: and also for each event in each composition