timeseries_generator: Utility function for generating batches of temporal data.
In dfalbel/keras: R Interface to 'Keras'

Utility function for generating batches of temporal data.

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

`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).