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Upload _Compressor.py
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_Compressor.py
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'''
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Imports
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'''
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import guitarpro
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from guitarpro import *
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import numpy as np
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import os
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import pickle
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from tqdm import tqdm
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from keras.utils import np_utils
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from _NoteData import NoteData
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'''
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Constants
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'''
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# PITCH[i] = the pitch associated with midi note number i.
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# For example, PITCH[69] = 'A4'
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PITCH = {val : str(GuitarString(number=0, value=val)) for val in range(128)}
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# MIDI[string] = the midi number associated with the note described by string.
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# For example, MIDI['A4'] = 69.
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MIDI = {str(GuitarString(number=0, value=val)) : val for val in range(128)}
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'''
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process_notes function
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'''
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def process_notes(beat, tuning, as_fingerings=True):
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noteData = NoteData()
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duration = (beat.duration.value, beat.duration.isDotted)
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# Tuplets are cool but rare.
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# If a tuplet is found, simply halve its play time (by doubling its duration value) to simplify things.
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if beat.duration.tuplet.enters != 1 or beat.duration.tuplet.times != 1:
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duration = (duration[0] * 2, duration[1]) # Tuples aren't mutable, so just re-assign the tuple.
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noteData.duration = duration[0]
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noteData.isDotted = duration[1]
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if len(beat.notes) == 0:
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# return 'rest', duration[0], duration[1], False
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noteData.value = 'rest'
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return noteData
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noteData.palmMute = beat.notes[0].effect.palmMute
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note_types = [note.type for note in beat.notes]
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if all(note_type == NoteType.rest for note_type in note_types):
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#return 'rest', duration[0], duration[1], False
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noteData.value = 'rest'
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return noteData
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if all(note_type == NoteType.tie for note_type in note_types):
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#return 'tied', duration[0], duration[1], False
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noteData.value = 'tied'
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return noteData
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if all(note_type == NoteType.dead for note_type in note_types):
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# return 'dead', duration[0], duration[1], False
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noteData.value = 'dead'
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return noteData
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lowest_string = len(tuning)
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if as_fingerings:
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# NEW CODE: Represent each pitch as its distance (in semitones) from the tuning of the lowest string.
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pitches = np.array([note.value + tuning[note.string] - tuning[lowest_string] for note in beat.notes if note.type == NoteType.normal])
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else:
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# note_number = MIDI note number, where A4 = 440 Hz = note 69
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# OLD CODE:
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pitches = np.array([note.value + tuning[note.string] for note in beat.notes if note.type == NoteType.normal])
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# Remove any possible NaN values.
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pitches = pitches[~np.isnan(pitches)]
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# Pitches are often stored in descending order, but we want to make sure they're in ascending order.
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# Thus, we flip the pitches before sorting, so as to help the algorithm.
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pitches = np.sort(pitches[::-1])
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if len(pitches) == 0:
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#return 'rest', duration[0], duration[1]
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noteData.value = 'rest'
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return noteData
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if len(pitches) == 1:
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if as_fingerings:
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# NEW CODE:
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# return str(pitches[0]), duration[0], duration[1]
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noteData.value = str(pitches[0])
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return noteData
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else:
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# OLD CODE:
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# return PITCH[pitches[0]], duration[0], duration[1]
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noteData.value = PITCH[pitches[0]]
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return noteData
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# Look at the pitch intervals in the lowest 3 notes that are being played.
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# Usually, chords will start at the lowest 2 notes.
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# However, sometimes players will strum the open lowest string constantly throughout the song.
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# (see: 'Be Quiet and Drive', 'Kaiowas')
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# Thus, the next-highest pair of notes should be considered when labeling a chord.
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if len(pitches) == 2:
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note_pairs = [(0, 1)]
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if len(pitches) == 3:
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note_pairs = [(0, 1), (0, 2), (1, 2)]
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elif len(pitches) >= 4:
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note_pairs = [(0, 1), (0, 2), (1, 2), (1, 3), (2, 3)]
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for idx1, idx2 in note_pairs:
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interval = pitches[idx2] - pitches[idx1]
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if interval == 12 or interval == 7:
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# Return a power chord associated with pitches[idx1]
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if as_fingerings:
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# NEW CODE:
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# return str(pitches[idx1]) + '_5', duration[0], duration[1]
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noteData.value = str(pitches[idx1]) + '_5'
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return noteData
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else:
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# OLD CODE:
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# return PITCH[pitches[idx1]] + '_5', duration[0], duration[1]
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noteData.value = PITCH[pitches[idx1]] + '_5'
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return noteData
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if interval == 6:
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# Return a tritone chord associated with pitches[idx1]
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if as_fingerings:
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# NEW CODE:
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# return str(pitches[idx1]) + '_dim5', duration[0], duration[1]
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noteData.value = str(pitches[idx1]) + '_dim5'
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return noteData
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else:
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# OLD CODE:
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# return PITCH[pitches[idx1]] + '_dim5', duration[0], duration[1]
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noteData.value = PITCH[pitches[idx1]] + 'dim_5'
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return noteData
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if interval == 5:
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# Return a P4 chord associated with pitches[idx1]
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if as_fingerings:
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# return str(pitches[idx1]) + '_4', duration[0], duration[1]
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noteData.value = str(pitches[idx1]) + '_4'
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return noteData
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else:
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# return PITCH[pitches[idx1]] + '_4', duration[0], duration[1]
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noteData.value = PITCH[pitches[idx1]] + '_4'
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return noteData
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if as_fingerings:
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# NEW CODE:
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#return str(pitches[0]), duration[0], duration[1]
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noteData.value = str(pitches[0])
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return noteData
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else:
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# OLD CODE:
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# return PITCH[pitches[0]], duration[0], duration[1]
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noteData.value = PITCH[pitches[0]]
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return noteData
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'''
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compress_track function
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'''
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def compress_track(track, as_fingerings=True):
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# 'song' contains the compressed representation of track.
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song = np.empty(len(track.measures), dtype=object)
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# Get the tuning and lowest string of the instrument in this track.
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tuning = {string.number : string.value for string in track.strings}
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lowest_string = len(tuning) # Bass have 4-6 strings, while metal guitars have 6 - 8 strings.
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#print(f'Tuning = {[PITCH[x] for x in tuning.values()]}')
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for m_i, measure in enumerate(track.measures):
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'''
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Upon inspection of some of the most popular Songsterr .gp5 tabs,
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it turns out that each measure always has two Voices.
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The first Voice (index 0) always contains music, while
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the second Voice (index 1) always just contains an empty Beat with no notes.
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Therefore, only the first Voice (index 0) actually matters.
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'''
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song[m_i] = []
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#print(m_i+1)
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for b_i, beat in enumerate(measure.voices[0].beats):
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song[m_i].append(process_notes(beat, tuning, as_fingerings).as_tuple())
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#print('\t', song[m_i][b_i], '\t', beat.duration)
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return song
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