def test_good_rules():
parncutt = Parncutt()
parncutt.segment_combiner(method="cost")
for id in subcosts:
d_corpus = DCorpus(corpus_str=TestConstant.PARNCUTT_HUMAN_FRAGMENT[id])
parncutt.load_corpus(d_corpus=d_corpus)
if id == 'B':
suggestions, costs, details = parncutt.generate_advice(staff="upper", cycle=4, k=20)
else:
suggestions, costs, details = parncutt.generate_advice(staff="upper", last_digit=last_digit[id], k=30)
details_for_sugg = dict()
for i in range(len(details)):
details_for_sugg[suggestions[i]] = details[i][0] # 0 index because we only have one segment
# parncutt.report_on_advice(suggestions, costs, details)
for gold_sugg in subcosts[id]:
assert gold_sugg in details_for_sugg, \
"Missing suggestion {0} in {1}".format(gold_sugg, id)
for rule in subcosts[id][gold_sugg]:
# if rule == 'bl1':
# continue
gold_cost = subcosts[id][gold_sugg][rule]
cost = details_for_sugg[gold_sugg][rule]
assert cost == gold_cost, \
"Bad {0} cost for {1} in {2}: {3} should be {4}".format(rule, gold_sugg, id, cost, gold_cost)
def test_cycles():
parncutt = Parncutt()
parncutt.segment_combiner(method="cost")
d_corpus = DCorpus(corpus_str=TestConstant.FOUR_NOTES)
parncutt.load_corpus(d_corpus=d_corpus)
suggestions, costs, details = parncutt.generate_advice(staff="upper", cycle=4, k=2)
assert len(suggestions) == 2, "No loops in that dog in top ten"
# parncutt.report_on_advice(suggestions, costs, details)
d_corpus = DCorpus(corpus_str=TestConstant.PARNCUTT_HUMAN_FRAGMENT['B'])
parncutt.load_corpus(d_corpus=d_corpus)
suggestions, costs, details = parncutt.generate_advice(staff="upper", cycle=4, k=16)
assert len(suggestions) == 16, "There should be 16 cyclic fingerings!"
def test_fingering_counts():
parncutt = Parncutt(pruning_method="none")
parncutt.segment_combiner(method="cost")
d_corpus = DCorpus(corpus_str=TestConstant.FOUR_NOTES)
parncutt.load_corpus(d_corpus=d_corpus)
suggestions, costs, details = parncutt.generate_advice(staff="upper", k=2)
assert parncutt.last_segment_pruned_count() == 320, "Bad none pruning on open-ended problem"
def test_four_note_example(self):
parncutt = Parncutt(segmenter=ManualDSegmenter(), segment_combiner="cost")
# parncutt.segment_combiner(method="cost")
d_corpus = DCorpus(corpus_str=TestConstant.FOUR_NOTES)
parncutt.load_corpus(d_corpus=d_corpus)
suggestions, costs, details = parncutt.generate_advice(staff="upper", k=2)
self.assertEqual(len(suggestions), 2, "No loops in that dog in top ten")
def test_sma_lar():
parncutt = Parncutt()
parncutt.segment_combiner(method="cost")
for id in sma_lar_sums:
d_corpus = DCorpus(corpus_str=TestConstant.PARNCUTT_HUMAN_FRAGMENT[id])
parncutt.load_corpus(d_corpus=d_corpus)
if id == 'B':
suggestions, costs, details = parncutt.generate_advice(staff="upper", cycle=4, k=20)
else:
suggestions, costs, details = parncutt.generate_advice(staff="upper", last_digit=last_digit[id], k=20)
details_for_sugg = dict()
for i in range(len(details)):
details_for_sugg[suggestions[i]] = details[i][0] # 0 index because we only have one segment
# parncutt.report_on_advice(suggestions, costs, details)
for gold_sugg in sma_lar_sums[id]:
assert gold_sugg in details_for_sugg,\
"Missing suggestion {0} in {1}".format(gold_sugg, id)
sma = details_for_sugg[gold_sugg]['sma']
lar = details_for_sugg[gold_sugg]['lar']
assert sma + lar == sma_lar_sums[id][gold_sugg],\
"Bad sma + lar total for {0} in {1}".format(gold_sugg, id)
def get_fingered_system_scores(self, loaded_model: Parncutt, model_name, version=None, score_count=5, weights=None):
advice = loaded_model.generate_advice(staff=STAFF, score_index=0, k=score_count)
# print(advice)
authority = model_name
if version:
authority = model_name + '_' + version
base_score = loaded_model.score_by_index(0)
sys_scores = []
for i in range(score_count):
sys_score = copy.deepcopy(base_score)
sys_score.remove_annotations()
abcdf = advice[0][i]
ann = DAnnotation(abcdf=abcdf, authority=authority)
sys_score.annotate(d_annotation=ann)
PianoFingering.finger_score(d_score=sys_score, staff=STAFF)
sys_scores.append(sys_score)
return sys_scores
#!/usr/bin/env python3
import pprint
from pydactyl.dactyler.Parncutt import Parncutt
from pydactyl.dcorpus.DCorpus import DCorpus
from pydactyl.dcorpus.ManualDSegmenter import ManualDSegmenter
model = Parncutt(segmenter=ManualDSegmenter(), segment_combiner="cost")
# d_corpus = DCorpus(paths=["/Users/dave/malody.abcd"])
d_corpus = DCorpus(paths=["/tmp/malody.abcd"])
model.load_corpus(d_corpus=d_corpus)
advice = model.advise()
print("Best advice: {0}".format(advice))
# Gold-standard embedded in input file.
hamming_dists = model.evaluate_strike_distance()
print("Hamming distance from gold standard: {0}".format(hamming_dists[0]))
suggestions, costs, details = model.generate_advice(staff="upper", k=9)
print("Ranked advice:\n\t{0}".format("\n\t".join(suggestions)))
print("Ranked costs :\n\t{0}".format("\n\t".join(str(x) for x in costs)))
# pp = pprint.PrettyPrinter(width=120)
# pp.pprint(details)
# HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, # WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING # FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR # OTHER DEALINGS IN THE SOFTWARE. import copy import re import sys from pydactyl.dcorpus.DCorpus import DCorpus, DAnnotation from pydactyl.dactyler.Parncutt import Parncutt from pydactyl.dcorpus.PigIn import PigIn # import scamp # s = scamp.Session() # print(s.get_available_midi_output_devices()) # exit(0) ## pig_eater = PigIn() ## pig_eater.transform() staff = 'upper' k = 5 corpus_dir = "/Users/dave/tb2/didactyl/dd/corpora/pig/PianoFingeringDataset_v1.00/abcd/" d_corpus = DCorpus() d_corpus.append_dir(corpus_dir=corpus_dir, split_header_extension='abcd') model = Parncutt() model.load_corpus(d_corpus=d_corpus) advice = model.generate_advice(staff=staff, score_index=0, k=k) print(advice)