Source code for compiam.melody.tonic_identification.tonic_multipitch

import os

import numpy as np

from compiam.utils import get_logger

logger = get_logger(__name__)


[docs] class TonicIndianMultiPitch: """MultiPitch approach to extract the tonic from IAM music signals.""" def __init__( self, bin_resolution=10, frame_size=2048, harmonic_weight=0.8, hop_size=128, magnitude_compression=1, magnitude_threshold=40, max_tonic_frequency=375, min_tonic_frequency=100, num_harmonics=20, ref_frequency=55, sample_rate=44100, ): """Tonic extraction init method. For a complete and detailed list of the parameters see the documentation on the following link: https://essentia.upf.edu/reference/std_TonicIndianArtMusic.html. Naming convention of the arguments has been stadardized to compIAM-friendly format. """ ### IMPORTING OPTIONAL DEPENDENCIES try: global estd import essentia.standard as estd except: raise ImportError( "In order to use this tool you need to have essentia installed. " "Install compIAM with essentia support: pip install 'compiam[essentia]'" ) ### self.bin_resolution = bin_resolution self.frame_size = frame_size self.harmonic_weight = harmonic_weight self.hop_size = hop_size self.magnitude_compression = magnitude_compression self.magnitude_threshold = magnitude_threshold self.max_tonic_frequency = max_tonic_frequency self.min_tonic_frequency = min_tonic_frequency self.num_harmonics = num_harmonics self.ref_frequency = ref_frequency self.sample_rate = sample_rate
[docs] def extract(self, input_data, input_sr=44100): """Extract the tonic from a given file. :param input_data: path to audio file or numpy array like audio signal :param input_sr: sampling rate of the input array of data (if any). This variable is only relevant if the input is an array of data instead of a filepath. :returns: a floating point number representing the tonic of the input recording. """ if isinstance(input_data, str): if not os.path.exists(input_data): raise FileNotFoundError("Target audio not found.") audio = estd.MonoLoader(filename=input_data, sampleRate=self.sample_rate)() elif isinstance(input_data, np.ndarray): logger.warning( f"Resampling... (input sampling rate is {input_sr}Hz, make sure this is correct)" ) resampling = estd.Resample( inputSampleRate=input_sr, outputSampleRate=self.sample_rate )() audio = resampling(input_data) else: raise ValueError("Input must be path to audio signal or an audio array") extractor = estd.TonicIndianArtMusic( binResolution=self.bin_resolution, frameSize=self.frame_size, harmonicWeight=self.harmonic_weight, hopSize=self.hop_size, magnitudeCompression=self.magnitude_compression, magnitudeThreshold=self.magnitude_threshold, maxTonicFrequency=self.max_tonic_frequency, minTonicFrequency=self.min_tonic_frequency, numberHarmonics=self.num_harmonics, referenceFrequency=self.ref_frequency, sampleRate=self.sample_rate, ) return extractor(audio)