timeseries_generator: Utility function for generating batches of temporal data.

Description

Utility function for generating batches of temporal data.

Usage

timeseries_generator(
  data,
  targets,
  length,
  sampling_rate = 1,
  stride = 1,
  start_index = 0,
  end_index = NULL,
  shuffle = FALSE,
  reverse = FALSE,
  batch_size = 128
)

Value

An object that can be passed to generator based training functions (e.g. fit_generator()).ma

Arguments

data: Object containing consecutive data points (timesteps). The data should be 2D, and axis 1 is expected to be the time dimension.
targets: Targets corresponding to timesteps in data. It should have same length as data.
length: Length of the output sequences (in number of timesteps).
sampling_rate: Period between successive individual timesteps within sequences. For rate r, timesteps data[i], data[i-r], ... data[i - length] are used for create a sample sequence.
stride: Period between successive output sequences. For stride s, consecutive output samples would be centered around data[i], data[i+s], data[i+2*s], etc.
start_index, end_index: Data points earlier than start_index or later than end_index will not be used in the output sequences. This is useful to reserve part of the data for test or validation.
shuffle: Whether to shuffle output samples, or instead draw them in chronological order.
reverse: Boolean: if true, timesteps in each output sample will be in reverse chronological order.
batch_size: Number of timeseries samples in each batch (except maybe the last one).