def test_equality_all1():
#import score1
score1_path = Path("test_scores/multivoice_score_1a.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
#import score2
score2_path = Path("test_scores/multivoice_score_1b.mei")
with open(score2_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score2 = conv.run()
#create scores
s1 = nlin.Score(score1)
s2 = nlin.Score(score2)
#select voices1
v1 = s1.part_list[0].bar_list[0].voices_list[0]
v2 = s2.part_list[0].bar_list[0].voices_list[0]
#change the ids
for an in v1.annot_notes:
an.general_note.id = 344
for an in v2.annot_notes:
an.general_note.id = 345
assert (v1 == v2)
assert (repr(v1) == repr(v1))
assert (repr(v2) == repr(v2))
assert (repr(v1) != repr(v2))
def test_complete_scorelin_diff1():
score1_path = Path("test_scores/monophonic_score_1a.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
score2_path = Path("test_scores/monophonic_score_1b.mei")
with open(score2_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score2 = conv.run()
#build ScoreTrees
score_lin1 = nlin.Score(score1)
score_lin2 = nlin.Score(score2)
#compute the complete score diff
op_list, cost = scl.complete_scorelin_diff(score_lin1, score_lin2)
assert (cost == 8)
def test_json_production2():
score1_path = Path("test_scores/polyphonic_score_2a.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
score2_path = Path("test_scores/polyphonic_score_2b.mei")
with open(score2_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score2 = conv.run()
#build ScoreTrees
score_lin1 = nlin.Score(score1)
score_lin2 = nlin.Score(score2)
#compute the complete score diff
op_list, cost=scl.complete_scorelin_diff(score_lin1,score_lin2)
operation_json = scl.op_list2json(op_list)
assert(1==1)
def test_block_diff1():
score1_path = Path("test_scores/monophonic_score_1a.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
score2_path = Path("test_scores/monophonic_score_1b.mei")
with open(score2_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score2 = conv.run()
#build ScoreTrees
score_lin1 = nlin.Score(score1)
score_lin2 = nlin.Score(score2)
# compute the blockdiff between all the bars (just for test, in practise we will run on non common subseq)
op_list, cost = scl.block_diff_lin(score_lin1.measures_from_part(0),
score_lin2.measures_from_part(0))
assert (cost == 8)
def test_annotation_production5():
score1_path = Path("test_scores/chord_score_3a.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
score2_path = Path("test_scores/chord_score_3b.mei")
with open(score2_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score2 = conv.run()
#build ScoreTrees
score_lin1 = nlin.Score(score1)
score_lin2 = nlin.Score(score2)
#compute the complete score diff
op_list, cost=scl.complete_scorelin_diff(score_lin1,score_lin2)
ann1, ann2 = sv.oplist2annotations(op_list)
sv.setResourchesPath(Path(RESOURCES_PATH))
sv.produce_annnot_svg(score1_path,ann1,out_path=Path("output/chord_score_3a.svg"))
sv.produce_annnot_svg(score2_path,ann2,out_path=Path("output/chord_score_3b.svg"))
assert(1==1)
def test_non_common_subsequences6():
#import scores
score1_path = Path("test_scores/polyphonic_score_1a.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
score2_path = Path("test_scores/polyphonic_score_1b.mei")
with open(score2_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score2 = conv.run()
#build ScoreTrees
score_tree1 = nlin.Score(score1)
score_tree2 = nlin.Score(score2)
#compute the non common_subsequences for part 0
part = 0
non_common_subsequences = scl.non_common_subsequences(
score_tree1.part_list[part].bar_list,
score_tree2.part_list[part].bar_list)
assert (len(non_common_subsequences) == 2)
def test_non_common_subsequences7():
#import scores
score1_path = Path("test_scores/monophonic_score_1a.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
score2_path = Path("test_scores/monophonic_score_1b.mei")
with open(score2_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score2 = conv.run()
#build ScoreTrees
score_tree1 = nlin.Score(score1)
score_tree2 = nlin.Score(score2)
#compute the non common_subsequences for part 0
part = 0
non_common_subsequences = scl.non_common_subsequences(
score_tree1.part_list[part].bar_list,
score_tree2.part_list[part].bar_list)
expected_non_common1 = {
"original": [score_tree1.part_list[0].bar_list[1]],
"compare_to": [score_tree2.part_list[0].bar_list[1]]
}
expected_non_common2 = {
"original": [
score_tree1.part_list[0].bar_list[5],
score_tree1.part_list[0].bar_list[6],
score_tree1.part_list[0].bar_list[7],
score_tree1.part_list[0].bar_list[8]
],
"compare_to": [
score_tree2.part_list[0].bar_list[5],
score_tree2.part_list[0].bar_list[6],
score_tree2.part_list[0].bar_list[7]
]
}
assert (len(non_common_subsequences) == 2)
assert (non_common_subsequences[0] == expected_non_common1)
assert (non_common_subsequences[1] == expected_non_common2)
def test_scorelin2():
#import score
score1_path = Path("test_scores/monophonic_score_1a.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
#produce a ScoreTree
score_lin1 = nlin.Score(score1)
#number of parts
assert (len(score_lin1.part_list) == 1)
#number of measures for each part
assert (len(score_lin1.part_list[0].bar_list) == 11)
#number of voices for each measure in part 0
for m in score_lin1.part_list[0].bar_list:
assert (len(m.voices_list) == 1)
def test_ties1():
#import score
score1_path = Path("test_scores/tie_score_1a.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
#produce a ScoreTree
score_lin1 = nlin.Score(score1)
#number of parts
assert (len(score_lin1.part_list) == 1)
#number of measures for each part
assert (len(score_lin1.part_list[0].bar_list) == 1)
#number of voices for each measure in part 0
for m in score_lin1.part_list[0].bar_list:
assert (len(m.voices_list) == 1)
expected_tree_repr = "[[E4]4Bsr,[E4T]4Bcosr,[D4]4Bspsp,[C4,E4]4Bsr,[C4T]4Bcosr,[D4]4Bspsp,[E4,G4,C5]4,[E4]4Bsr,[F4]4Bsp]"
assert (str(score_lin1.part_list[0].bar_list[0].voices_list[0]) ==
expected_tree_repr)
assert (score_lin1.part_list[0].bar_list[0].voices_list[0].notation_size()
== 26)
def test_equality_all2():
#import score1
score1_path = Path("test_scores/polyphonic_score_2b.mei")
with open(score1_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
#create score
s = nlin.Score(score1)
#select bars
b1 = s.part_list[0].bar_list[11]
b2 = s.part_list[0].bar_list[12]
assert (b1 == b2)
assert (repr(b1) == repr(b1))
assert (repr(b2) == repr(b2))
assert (repr(b1) != repr(b2))
#select voices
v1 = s.part_list[0].bar_list[11].voices_list[0]
v2 = s.part_list[0].bar_list[12].voices_list[0]
assert (v1 == v2)
assert (repr(v1) == repr(v1))
assert (repr(v2) == repr(v2))
assert (repr(v1) != repr(v2))
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score1 = conv.run()
#load score2 in music21
score2_path = Path("test_scores/polyphonic_score_1b.mei")
with open(score2_path, 'r') as f:
mei_string = f.read()
conv = m21.mei.MeiToM21Converter(mei_string)
score2 = conv.run()
#add the correct folder for resourches. Uncomment if needed
# sv.setResourchesPath(Path("C:/Users/example/Desktop/verovio/data" ))
#build the linear representation of the score
score_lin1 = nlin.Score(score1)
score_lin2 = nlin.Score(score2)
#compute the complete score diff
op_list, cost = scl.complete_scorelin_diff(score_lin1, score_lin2)
#generate the list of annotations in json format
operation_json = scl.op_list2json(op_list)
#save them to a file
with open(Path('output/operations_test.json'), 'w') as outfile:
json.dump(operation_json, outfile)
#compute the annotations for the two scores
ann1, ann2 = sv.oplist2annotations(op_list)
#display the annotations on the scores (color the involved elements)
sv.produce_annnot_svg(score1_path, ann1, out_path=Path("output/test1.svg"))
sv.produce_annnot_svg(score2_path, ann2, out_path=Path("output/test2.svg"))
