Resampling » History » Version 1

Marcus Pearce, 2013-07-15 03:29 PM

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h1. Resampling
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These are some low-level functions in the <code>resampling</code> package, which are called by the <code>idyom:idyom</code> function. You shouldn't need to use them unless you are developing the code.
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h2. <code>resampling:idyom-resample</code>
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<code>idyom:idyom</code> uses <code>resampling:idyom-resample</code> 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):
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* Required: dataset-id, target-viewpoints, source-viewpoints (no viewpoint selection)
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* Model: models, ltmo, stmo
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* Training: pretraining-ids, k, resampling-indices
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h2. <code>resampling:output-information-content</code>
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Takes the output of <code>resampling:idyom-resample</code> and returns the average information content. It takes the following arguments:
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* predictions: the output of <code>resampling:idyom-resample</code>
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* detail: an integer which determines how the information content is averaged (these are returned as multiple values): 
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** 1: averaged over the entire dataset 
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** 2: and also averaged over each composition 
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** 3: and also for each event in each composition
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h2. <code>resampling:format-information-content</code>
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<code>resampling:format-information-content</code> takes the output of <code>resampling:idyom-resample</code> and writes it to file. It takes the following arguments:
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* predictions: the output of <code>resampling:idyom-resample</code>
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* file: a string denoting a file
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* dataset-id: an integer reflecting the dataset-id
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* detail: an integer which determines how the information content is averaged (these are returned as multiple values): 
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** 1: averaged over the entire dataset 
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** 2: and also averaged over each composition 
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** 3: and also for each event in each composition