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import jams
import tqdm
import glob
import numpy as np
import mir_eval
def quantise(beats):
return [int(round(b * 25)) / 25 for b in beats]
# simplify annotation to sevenths_inv
new_key = []
for tmp in tqdm.tqdm(glob.glob("/work/fast_data_yinghao/jjy_chord/references_v2/*.jams")):
file = jams.load(tmp)
for idx, data in enumerate(file["annotations"][0]["data"]):
# key.add(data.value.split(":")[-1])
if ":" in data.value:
new_key.append(data.value.split(":")[-1])
# else:
# new_key.append(data.value)
new_key = list(set(new_key))
map = {}
# partition = [[new_key[0]]]
target = ['maj','maj/3','maj/5',
'min' ,'min/b3','min/5',
'7' ,'7/3' ,'7/5' ,'7/b7',
'maj7', 'maj7/3','maj7/7',
'min7', 'min7/b3','min7/5' ,'min7/b7' ]
for idx, i in tqdm.tqdm(enumerate(new_key)):
for j in target:
if mir_eval.chord.sevenths_inv(["C:" + i],["C:" + j])==1:
map[i] = j
break
else:
map[i] = i
# # for j in new_key[idx+1:]:
# for j in partition:
# if mir_eval.chord.sevenths_inv([i],[j[0]])==1:
# j.append(i)
# break
# else:
# partition.append([i])
# key = set()
# ['C#:min11', 'C#:5', 'C#:5(b13)', 'C#:(1,b3)/b3', 'C#:min7', 'C#:min(*b3,9)', 'C#:5(b7)', 'C#:maj6', 'C#:maj7(*b5)', 'C#:dim', 'C#:min(*b3,*5)', 'C#:min11/b3', 'C#:min7(4)/4', 'C#:min7/4',
# 'C#:7(b9)/3', 'C#:sus4(b7)', 'C#:maj6(4)', 'C#:sus4', 'C#:min7(9)', 'C#/3', 'C#:maj', 'C#:7(b9)', 'C#:7/4', 'C#', 'C#:maj/3', 'C#:min9/b7', 'C#:min(9)', 'C#:maj(*3)', 'C#:1/1', 'C#:13', 'C#:7(#9)',
# 'C#:dim/b3', 'C#:sus2(4)', 'C#:maj/b4', 'C#:min(*b3)', 'C#:7/3', 'C#:maj7/3', 'C#:min/b7', 'C#:min7/b7', 'C#:7', 'C#:min(b13)', 'C#:7(b9,#9)', 'C#:(1,b3,b5,6)', 'C#:min9', 'C#:min7/5', 'C#:sus4(b7,9)',
# 'C#:min7/b3', 'C#:maj/5', 'C#:min/4', 'C#:dim7', 'C#:min/5', 'C#:hdim7/4', 'C#:min/3', 'C#:maj6/3', 'C#:min(11)', 'C#:hdim7', 'C#:dim7/b3', 'C#:9', 'C#:sus2(b7)', 'C#:aug', 'C#:(b3,b7,11,9)',
# 'C#:(1,b3,b5,6)/b3', 'C#:maj6(4)/3', 'C#:7(b2)', 'C#:sus2', 'C#:min', 'C#:(1,b3)']
# count = 0
for tmp in tqdm.tqdm(glob.glob("/work/fast_data_yinghao/jjy_chord/references_v2/*.jams")):
file = jams.load(tmp)
ref_intervals = np.zeros((len(file["annotations"][0]["data"]),2))
ref_labels = []
# all annotations start at 0s
# count += (file["annotations"][0]["data"][0].time==0)
annotation = ""
for idx, data in enumerate(file["annotations"][0]["data"]):
# key.add(data.value.split(":")[-1])
# key.add(data.value)
ref_intervals[idx] = [data.time, data.time + data.duration]
ref_labels.append(data.value)
if ":" in data.value:
chord = data.value.split(":")[0] + ":" + map[data.value.split(":")[-1]]
annotation +=f"{chord} {quantise(data.time + data.duration)}s,"
# break
# (est_intervals, est_labels) = (ref_intervals, ref_labels)
# est_intervals, est_labels = mir_eval.util.adjust_intervals(
# est_intervals, est_labels, ref_intervals.min(),
# ref_intervals.max(), mir_eval.chord.NO_CHORD,
# mir_eval.chord.NO_CHORD)
# (intervals, ref_labels, est_labels) = mir_eval.util.merge_labeled_intervals(
# ref_intervals, ref_labels, est_intervals, est_labels)
# durations = mir_eval.util.intervals_to_durations(intervals)
# comparisons = mir_eval.chord.sevenths_inv(ref_labels, est_labels)
# score = mir_eval.chord.weighted_accuracy(comparisons, durations)
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