pumpp.feature.CQT

class pumpp.feature.CQT(name, sr, hop_length, n_octaves=8, over_sample=3, fmin=None, log=False, conv=None)[source]

Constant-Q transform

Attributes

name (str) The name for this feature extractor
sr (number > 0) The sampling rate of audio
hop_length (int > 0) The number of samples between CQT frames
n_octaves (int > 0) The number of octaves in the CQT
over_sample (int > 0) The amount of frequency oversampling (bins per semitone)
fmin (float > 0) The minimum frequency of the CQT
log (boolean) If True, scale the magnitude to decibels Otherwise, use linear magnitude
__init__(name, sr, hop_length, n_octaves=8, over_sample=3, fmin=None, log=False, conv=None)[source]

Methods

__init__(name, sr, hop_length[, n_octaves, ...])
layers() Construct Keras input layers for the given transformer
merge(data) Merge an array of output dictionaries into a single dictionary with properly scoped names.
phase_diff(phase) Compute the phase differential along a given axis
pop(field)
register(key, dimension, dtype)
scope(key) Apply the name scope to a key
transform(y, sr) Transform an audio signal
transform_audio(y) Compute the CQT

Attributes

idx