hookeai.simulators.links.utilities.links_out_to_dataset.TimeSeriesDatasetInMemory

class TimeSeriesDatasetInMemory(dataset_samples)

Bases: Dataset

Time series data set (in-memory storage only).

_dataset_samples

Time series data set samples data. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

Type:

list

__len__(self):

Return size of data set (number of samples).

__getitem__(self, index)

Return data set sample from corresponding index.

get_dataset_samples(self)

Get data set samples data.

add_dataset_samples(self, samples)

Add samples to data set.

remove_dataset_samples(self, indices)

Remove samples from data set.

from_dataset(cls, dataset)

Convert data set to TimeSeriesDatasetInMemory data set.

Constructor.

Parameters:

dataset_samples (list[dict]) – Time series data set samples data. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

List of Public Methods

add_dataset_samples	Add samples to data set.
from_dataset	Convert data set to TimeSeriesDatasetInMemory data set.
get_dataset_samples	Get data set samples data.
remove_dataset_samples	Remove samples from data set.

Methods

__init__(dataset_samples)

Constructor.

Parameters:

dataset_samples (list[dict]) – Time series data set samples data. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

add_dataset_samples(samples)

Add samples to data set.

Parameters:

samples (list[dict]) – Time series samples data. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

classmethod from_dataset(dataset)

Convert data set to TimeSeriesDatasetInMemory data set.

Parameters:

dataset (torch.utils.data.Dataset) – Time series data set. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

Returns:

dataset – Time series data set. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

Return type:

TimeSeriesDatasetInMemory

get_dataset_samples()

Get data set samples data.

Returns:

dataset_samples – Time series data set samples data. Each sample is stored as a dictionary where each feature (key, str) data is a torch.Tensor(2d) of shape (sequence_length, n_features).

Return type:

list[dict]

remove_dataset_samples(indices)

Remove samples from data set.

Parameters:

indices (list[int]) – Indices of data set samples to be removed (index must be in [0, n_sample]).