def analyze(cls, events: List[CorpusEvent],
metadata: Metadata) -> List[CorpusEvent]:
if not FeatureUtils.is_valid_audio(events, metadata):
raise FeatureError(
f"Feature '{cls.__name__}' does not support content of "
f"type {metadata.content_type.__class__.__name__}")
metadata: AudioMetadata = typing.cast(AudioMetadata, metadata)
# TODO: Pass rather than hard-code
yin_frames: np.ndarray = librosa.yin(metadata.foreground_data,
fmin=50,
fmax=4186,
sr=metadata.sr,
frame_length=2048,
hop_length=metadata.hop_length)
yin_midipitches: np.ndarray = np.round(
12 * np.log2(yin_frames / 8.175798915643707))
for event in events:
onset_frame: int = librosa.time_to_frames(
event.onset, sr=metadata.sr, hop_length=metadata.hop_length)
end_frame: int = librosa.time_to_frames(
event.onset + event.duration,
sr=metadata.sr,
hop_length=metadata.hop_length)
hist, _ = np.histogram(yin_midipitches[onset_frame:end_frame],
bins=128,
range=(0, 128))
pitch: int = int(np.argmax(hist))
event.set_feature(cls(value=pitch))
return events
def analyze(cls, events: List[MidiCorpusEvent],
metadata: MidiMetadata) -> List[MidiCorpusEvent]:
if FeatureUtils.is_valid_midi(events, metadata):
for event in events:
event.set_feature(cls(value=len(event.notes)))
return events
raise FeatureError(
f"Feature '{cls.__name__}' does not support content of "
f"type {metadata.content_type.__class__.__name__}")
def analyze(cls, events: List[MidiCorpusEvent],
metadata: MidiMetadata) -> List[MidiCorpusEvent]:
""" raises: FeatureError if invalid MIDI content """
if FeatureUtils.is_valid_midi(events, metadata):
for event in events:
event.set_feature(cls(int(min([n.pitch
for n in event.notes]))))
return events
raise FeatureError(
f"Feature '{cls.__name__}' does not support content of "
f"type {metadata.content_type.__class__.__name__}")
def analyze(cls, events: List[CorpusEvent], metadata: Metadata) -> List[CorpusEvent]:
if FeatureUtils.is_valid_midi(events, metadata):
events: List[MidiCorpusEvent]
metadata: MidiMetadata
cls._analyze_midi(events, metadata)
elif FeatureUtils.is_valid_audio(events, metadata):
events: List[AudioCorpusEvent]
metadata: AudioMetadata
cls._analyze_audio(events, metadata)
else:
raise FeatureError(f"Feature '{cls.__name__}' does not support content of type {metadata.content_type}")
return events
def analyze(cls, events: List[MidiCorpusEvent],
metadata: MidiMetadata) -> List[MidiCorpusEvent]:
if FeatureUtils.is_valid_midi(events, metadata):
for event in events:
band_distribution: np.ndarray = np.zeros(OctaveBands.NUM_BANDS,
dtype=float)
octaves: List[int] = [
int(note.pitch // 12) for note in event.notes
]
for octave in octaves:
band_distribution[octave] += 1.0
max_val: float = np.max(band_distribution)
if max_val > 0:
band_distribution /= max_val
event.set_feature(cls(value=band_distribution))
return events
raise FeatureError(
f"Feature '{cls.__name__}' does not support content of "
f"type {metadata.content_type.__class__.__name__}")
def get_feature(self, feature_type: Type[FeatureValue]) -> FeatureValue:
"""Raises KeyError"""
try:
return self.features[feature_type]
except ValueError as e:
raise FeatureError(f"Corpus does not have feature of type '{feature_type}'") from e