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
)
Arguments
Arguments | Description |
---|---|
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). |
Value
An object that can be passed to generator based training functions (e.g. fit_generator()
).ma