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Running
on
Zero
Upload TMIDIX.py
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TMIDIX.py
CHANGED
@@ -1471,6 +1471,8 @@ import csv
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import tqdm
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from itertools import zip_longest
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from itertools import groupby
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from collections import Counter
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@@ -5589,7 +5591,7 @@ def split_melody(enhanced_melody_score_notes,
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for e in enhanced_melody_score_notes:
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dtime = max(0, min(max_score_time, e[1]-pe[1]))
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-
if dtime >
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if chu:
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mel_chunks.append(chu)
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chu = []
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@@ -9603,7 +9605,7 @@ def escore_notes_to_text_description(escore_notes,
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all_patches = [e[6] for e in escore_notes]
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-
patches = ordered_set(all_patches)
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instruments = [alpha_str(Number2patch[p]) for p in patches if p < 128]
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@@ -9762,7 +9764,6 @@ def escore_notes_to_text_description(escore_notes,
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description += 'This ' + mood + ' melody has '
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-
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else:
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description += 'TThis drum track has '
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@@ -9776,19 +9777,17 @@ def escore_notes_to_text_description(escore_notes,
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if instruments:
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if comp_type not in ['monophonic melody', 'drum track']:
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description += 'The song '
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-
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description += 'The melody '
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-
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if len(instruments) == 1:
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description += 'is played on a solo ' + instruments[0] + '.'
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-
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-
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-
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-
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-
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description += '\n'
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@@ -9829,7 +9828,7 @@ def escore_notes_to_text_description(escore_notes,
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description += 'The song has ' + NUMERALS[len(lead_melodies)-1] + ' distinct lead ' + mword + ' played on '
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if len(lead_melodies) > 1:
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description += ', '.join(lead_melodies[:-1]
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else:
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description += lead_melodies[0][0] + '.'
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@@ -9847,7 +9846,7 @@ def escore_notes_to_text_description(escore_notes,
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description += 'The song has ' + NUMERALS[len(base_melodies)-1] + ' distinct base ' + mword + ' played on '
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if len(base_melodies) > 1:
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description += ', '.join(base_melodies[:-1]
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else:
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description += base_melodies[0][0] + '.'
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@@ -9865,7 +9864,7 @@ def escore_notes_to_text_description(escore_notes,
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description += 'The song has ' + NUMERALS[len(lead_melodies)-1] + ' distinct lead ' + lmword + ' played on '
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if len(lead_melodies) > 1:
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description += ', '.join(lead_melodies[:-1]
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else:
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description += lead_melodies[0][0] + '.'
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@@ -9879,7 +9878,7 @@ def escore_notes_to_text_description(escore_notes,
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description += ' And ' + NUMERALS[len(base_melodies)-1] + ' distinct base ' + bmword + ' played on '
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if len(base_melodies) > 1:
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description += ', '.join(base_melodies[:-1]
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else:
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description += base_melodies[0][0] + '.'
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@@ -11048,7 +11047,7 @@ LEAD_INSTRUMENTS = [0, 1, 2, 3, 4, 5, 6, 7, # Piano
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8, 9, 10, 11, 12, 13, 14, 15, # Chromatic Percussion
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16, 17, 18, 19, 20, 21, 22, 23, # Organ
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24, 25, 26, 27, 28, 29, 30, 31, # Guitar
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-
40, 41, # Strings
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52, 53, 54, # Ensemble
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56, 57, 59, 60, # Brass
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64, 65, 66, 67, 68, 69, 70, 71, # Reed
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@@ -11091,6 +11090,97 @@ def escore_notes_pitches_range(escore_notes,
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else:
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return [ -1] * 6
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###################################################################################
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#
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# This is the end of the TMIDI X Python module
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import tqdm
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+
import multiprocessing
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+
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from itertools import zip_longest
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from itertools import groupby
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from collections import Counter
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for e in enhanced_melody_score_notes:
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dtime = max(0, min(max_score_time, e[1]-pe[1]))
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if dtime > stime:
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if chu:
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mel_chunks.append(chu)
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chu = []
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all_patches = [e[6] for e in escore_notes]
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patches = ordered_set(all_patches)[:16]
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instruments = [alpha_str(Number2patch[p]) for p in patches if p < 128]
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description += 'This ' + mood + ' melody has '
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else:
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description += 'TThis drum track has '
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if instruments:
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if comp_type not in ['monophonic melody', 'drum track']:
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+
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description += 'The song '
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if len(instruments) > 1:
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description += 'features ' + NUMERALS[max(0, min(15, len(instruments)-1))] + ' instruments: '
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description += ', '.join(instruments[:-1]) + ' and ' + instruments[-1] + '.'
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else:
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description += 'features one instrument: ' + instruments[0] + '.'
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description += '\n'
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description += 'The song has ' + NUMERALS[len(lead_melodies)-1] + ' distinct lead ' + mword + ' played on '
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if len(lead_melodies) > 1:
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description += ', '.join([l[0] for l in lead_melodies[:-1]]) + ' and ' + lead_melodies[-1][0] + '.'
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else:
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description += lead_melodies[0][0] + '.'
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description += 'The song has ' + NUMERALS[len(base_melodies)-1] + ' distinct base ' + mword + ' played on '
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if len(base_melodies) > 1:
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description += ', '.join([b[0] for b in base_melodies[:-1]]) + ' and ' + base_melodies[-1][0] + '.'
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else:
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description += base_melodies[0][0] + '.'
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description += 'The song has ' + NUMERALS[len(lead_melodies)-1] + ' distinct lead ' + lmword + ' played on '
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if len(lead_melodies) > 1:
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description += ', '.join([l[0] for l in lead_melodies[:-1]]) + ' and ' + lead_melodies[-1][0] + '.'
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else:
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description += lead_melodies[0][0] + '.'
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description += ' And ' + NUMERALS[len(base_melodies)-1] + ' distinct base ' + bmword + ' played on '
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if len(base_melodies) > 1:
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description += ', '.join([b[0] for b in base_melodies[:-1]]) + ' and ' + base_melodies[-1][0] + '.'
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else:
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description += base_melodies[0][0] + '.'
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8, 9, 10, 11, 12, 13, 14, 15, # Chromatic Percussion
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16, 17, 18, 19, 20, 21, 22, 23, # Organ
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24, 25, 26, 27, 28, 29, 30, 31, # Guitar
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+
40, 41, 46, # Strings
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52, 53, 54, # Ensemble
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56, 57, 59, 60, # Brass
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64, 65, 66, 67, 68, 69, 70, 71, # Reed
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else:
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return [ -1] * 6
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###################################################################################
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def escore_notes_core(escore_notes, core_len=128):
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cscore = chordify_score([1000, escore_notes])
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chords = []
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chords_idxs = []
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for i, c in enumerate(cscore):
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pitches = [e[4] for e in c if e[3] != 9]
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if pitches:
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tones_chord = sorted(set([p % 12 for p in pitches]))
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if tones_chord not in ALL_CHORDS_SORTED:
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tones_chord = check_and_fix_tones_chord(tones_chord)
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chords.append(ALL_CHORDS_SORTED.index(tones_chord))
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chords_idxs.append(i)
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mid = len(chords_idxs) // 2
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clen = core_len // 2
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sidx = chords_idxs[mid-clen]
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eidx = chords_idxs[mid+clen]
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core_chords = chords[mid-clen:mid+clen]
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core_score = flatten(cscore[sidx:eidx])
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return core_score, core_chords
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###################################################################################
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def multiprocessing_wrapper(function, data_list):
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with multiprocessing.Pool() as pool:
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results = []
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for result in tqdm.tqdm(pool.imap_unordered(function, data_list), total=len(data_list)):
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results.append(result)
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return results
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###################################################################################
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def rle_encode_ones(matrix, div_mod=-1):
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flat_list = [val for row in matrix for val in row]
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encoding = []
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i = 0
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while i < len(flat_list):
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if flat_list[i] == 1:
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start_index = i
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count = 1
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i += 1
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while i < len(flat_list) and flat_list[i] == 1:
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count += 1
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i += 1
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if div_mod > 0:
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encoding.append((start_index // div_mod, start_index % div_mod))
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else:
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encoding.append(start_index)
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else:
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i += 1
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return encoding
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###################################################################################
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def rle_decode_ones(encoding, size=(128, 128)):
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flat_list = [0] * (size[0] * size[1])
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for start_index in encoding:
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flat_list[start_index] = 1
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matrix = [flat_list[i * size[1]:(i + 1) * size[1]] for i in range(size[0])]
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return matrix
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###################################################################################
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#
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# This is the end of the TMIDI X Python module
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