223b817345f40076b2ff8dd0e7e49c00e1d6c03c,nussl/separation/primitive/repet_sim.py,RepetSim,__init__,#RepetSim#,40

Before Change


                 max_repeating_frames=None, high_pass_cutoff=None, do_mono=False,
                 use_librosa_stft=constants.USE_LIBROSA_STFT, matlab_fidelity=False,
                 mask_type=mask_separation_base.MaskSeparationBase.SOFT_MASK, mask_threshold=0.5):
        super(RepetSim, self).__init__(input_audio_signal=input_audio_signal, mask_type=mask_type,
                                       mask_threshold=mask_threshold)

        self.high_pass_cutoff = 100 if high_pass_cutoff is None else high_pass_cutoff
        self.similarity_threshold = 0 if similarity_threshold is None else similarity_threshold
        self.min_distance_between_frames = 1 if min_distance_between_frames is None else min_distance_between_frames
        self.max_repeating_frames = 100 if max_repeating_frames is None else max_repeating_frames

        self._min_distance_converted_to_hops = False

        self.verbose = False
        self.similarity_matrix = None
        self.background = None
        self.foreground = None
        self.similarity_indices = None
        self.magnitude_spectrogram = None
        self.stft = None
        self.result_masks = None
        self.use_librosa_stft = use_librosa_stft
        self.matlab_fidelity = matlab_fidelity

        if self.matlab_fidelity:
            self.use_librosa_stft = False

        self.do_mono = do_mono

        if self.do_mono:
            self.audio_signal.to_mono(overwrite=True)

    def run(self):
        

After Change


    def __init__(self, input_audio_signal, similarity_threshold=0, 
                 min_distance_between_frames=1, max_repeating_frames=100, 
                 high_pass_cutoff=100, mask_type="soft", mask_threshold=0.5):
        super().__init__(
            input_audio_signal=input_audio_signal, 
            mask_type=mask_type,
            mask_threshold=mask_threshold)

        self.high_pass_cutoff = high_pass_cutoff
        self.similarity_threshold = similarity_threshold
        self.min_distance_between_frames = min_distance_between_frames
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 13

Instances


Project Name: interactiveaudiolab/nussl
Commit Name: 223b817345f40076b2ff8dd0e7e49c00e1d6c03c
Time: 2020-03-22
Author: prem@u.northwestern.edu
File Name: nussl/separation/primitive/repet_sim.py
Class Name: RepetSim
Method Name: __init__


Project Name: interactiveaudiolab/nussl
Commit Name: 223b817345f40076b2ff8dd0e7e49c00e1d6c03c
Time: 2020-03-22
Author: prem@u.northwestern.edu
File Name: nussl/separation/primitive/repet_sim.py
Class Name: RepetSim
Method Name: __init__


Project Name: interactiveaudiolab/nussl
Commit Name: 1cadb414e15dd9c65600b4432ed77428397deabc
Time: 2020-03-22
Author: prem@u.northwestern.edu
File Name: nussl/separation/factorization/rpca.py
Class Name: RPCA
Method Name: __init__


Project Name: interactiveaudiolab/nussl
Commit Name: 2ffbfa3a6bd3b8de8e21a762489346054dcd9ccc
Time: 2020-03-12
Author: prem@u.northwestern.edu
File Name: nussl/separation/deep/deep_mask_estimation.py
Class Name: DeepMaskEstimation
Method Name: __init__