qumphy.data.deepbeat module

File: qumphy/data/pulsedb.py Project: 22HLT01 QUMPHY Contact: oskar.pfeffer@ptb.de Gitlab: https://gitlab.com/qumphy Description: Functions handling DeepBeat dataset.

class qumphy.data.deepbeat.DeepBeatDataModule(sampling_rate, batch_size, num_workers, pin_memory=True, prefetch_factor=8, **dskwargs)[source]

Bases: LightningDataModule

LightningDataModule implementation for the DeepBeat dataset.

setup(stage)[source]

test_dataloader()[source]

Create the test dataloader.

Returns:: Dataloader for the test dataset.
Return type:: torch.utils.data.DataLoader

train_dataloader()[source]

Create the training dataloader.

Returns:: Dataloader for the training dataset.
Return type:: torch.utils.data.DataLoader

val_dataloader()[source]

Create the validation dataloader.

Returns:: Dataloader for the validation dataset.
Return type:: torch.utils.data.DataLoader

class qumphy.data.deepbeat.DeepBeatDataset(data_directory, subset, dataset='set_revised', target_format='binary', normalize=False, dtype=torch.float32, load_data=True, data_fraction=1.0, filter_params=None, noise_params=None, input_sampling_rate=None, split_to_input_sampling_rate=None, target_sampling_rate=None)[source]

Bases: Dataset

DeepBeat dataset class.

get_data()[source]

get_labels()[source]

load_data(data_directory, filter_params=None, noise_params=None, data_fraction=1.0)[source]

normalize_data(data)[source]

Rescales the data to the range [-1, 1].

Parameters:: (array) (data)
Returns:: array: The normalized data in the range [-1, 1].

select_subset_indices(metadata, data_fraction=1.0)[source]

Set an index mask of the memmapped dataset based on the selected subset.

Return type:: Index
Parameters:: metadata (pd.core.frame.DataFrame) – The metadata dataframe.
Returns:: The index mask.
Return type:: pd.core.indexes.base.Index