Module music_df.scripts

Sub-modules

music_df.scripts.census

music_df.scripts.collate_sequence_level_predictions

music_df.scripts.compare_annotations

music_df.scripts.configs

music_df.scripts.csvs_to_midi

music_df.scripts.dedouble_csvs

We want to process data in the following order: 1. detrill 2. quantize 3. merge notes 4. salami slice 5. dedouble

music_df.scripts.detremolo_csvs

TODO: (Malcolm 2024-08-09) Think about where this should go in the overall data processing pipeline

music_df.scripts.humdrum_export

music_df.scripts.krn_to_csvs

Convenience script so we don't have to convert from krn on HPC (where we'd have to build the TOTABLE binary.)

music_df.scripts.label_dfs

music_df.scripts.merge_notes_csvs

We want to process data in the following order: 1. detrill 2. quantize 3. merge notes 4. salami slice 5. dedouble

music_df.scripts.midi_to_csvs

music_df.scripts.missing_files_to_csvs

music_df.scripts.open_as_midi

music_df.scripts.plot_predictions

music_df.scripts.plot_predictions2

music_df.scripts.plot_scores

music_df.scripts.quantize_with_mscore

music_df.scripts.salami_slice_csvs

music_df.scripts.search_for_feature

music_df.scripts.xml_to_csvs

For unlabeled data, we are using the YCAC midi corpus …