chimeranet package

Submodules

chimeranet.models module

model module

class chimeranet.models.ChimeraNetModel(time_frames, mel_bins, n_channels, d_embeddings)[source]

Bases: object

ChimeraNetModel class

build_model(n_blstm_units=500, n_blstm_layers=4)[source]
loss_deepclustering()[source]
loss_mask()[source]
class chimeranet.models.ChimeraPPModel(time_frames, mel_bins, n_channels, d_embeddings)[source]

Bases: chimeranet.models.ChimeraNetModel

build_model(n_blstm_units=500, n_blstm_layers=4)[source]
chimeranet.models.build_chimeranet_model(T, F, C, D, n_blstm_units=500, n_blstm_layers=4)[source]
chimeranet.models.build_chimerapp_model(T, F, C, D, n_blstm_units=500, n_blstm_layers=4)[source]
chimeranet.models.from_predicted_embedding(y)[source]
chimeranet.models.from_predicted_mask(y)[source]
chimeranet.models.load_model(path)[source]
chimeranet.models.loss_deepclustering(T, F, C, D)[source]
chimeranet.models.loss_mask(T, F, C, D)[source]
chimeranet.models.probe_model_shape(path)[source]
chimeranet.models.to_prediction_data(y)[source]

chimeranet.reconstruction module

chimeranet.reconstruction.from_embedding(embedding, n_channels, n_jobs=-1)[source]
chimeranet.reconstruction.from_mask(mask)[source]

chimeranet.sampling module

class chimeranet.sampling.AggregateSampler(*samplers)[source]

Bases: chimeranet.sampling.Sampler

property amplitude_factor
property duration
property samplerate
property shift_factor
property stretch_factor
class chimeranet.sampling.AsyncSampler(*samplers)[source]

Bases: chimeranet.sampling.AggregateSampler

dataset_size()[source]
sample(n_samples=1, n_jobs=1)[source]
class chimeranet.sampling.DatasetSampler(dataset)[source]

Bases: chimeranet.sampling.Sampler

dataset_size()[source]
load(index, **kwargs)[source]
sample(n_samples=1, n_jobs=1)[source]
class chimeranet.sampling.Sampler[source]

Bases: object

property amplitude_factor
dataset_size()[source]
property duration
generate(batch_size=1, n_batch_per_round=1, n_jobs=1)[source]
sample(n_samples=1, n_jobs=1)[source]
property samplerate
property shift_factor
property stretch_factor
class chimeranet.sampling.SyncSampler(*samplers)[source]

Bases: chimeranet.sampling.AggregateSampler

property amplitude_factor
dataset_size()[source]
load(index, **kwargs)[source]
sample(n_samples=1, n_jobs=1)[source]
property shift_factor
property stretch_factor
chimeranet.sampling.normalise_amplitude(y, amplitude_factor)[source]
chimeranet.sampling.pitch_shift(y, shift_factor, sr)[source]
chimeranet.sampling.time_stretch(y, stretch_factor)[source]
chimeranet.sampling.transform(y, sr, **kwargs)[source]

chimeranet.training module

chimeranet.training.to_training_data(ys, T, F, sr=44100, n_fft=2048, hop_length=None, noise=None, threshold=None, n_jobs=1)[source]
chimeranet.training.to_training_data_single(cs, T, F, sr=44100, n_fft=2048, hop_length=None, noise=None, threshold=None)[source]

chimeranet.windowutils module

chimeranet.windowutils.merge_windows_mean(x, hop_length=None)[source]
chimeranet.windowutils.merge_windows_most_common(x, hop_length=None)[source]
chimeranet.windowutils.split_window(x, window_length, hop_length=None)[source]

Module contents