create_binned_data {NeuroDecodeR}

Convert data from raster format to binned format

Description

This function takes the name of a directory that contains files in raster format and averages the data within a specified bin width at specified sampling interval increments to create data in binned format used for decoding.

Usage

create_binned_data(
  raster_dir_name,
  save_prefix_name,
  bin_width,
  sampling_interval,
  start_time = NULL,
  end_time = NULL,
  files_contain = "",
  num_parallel_cores = NULL
)

Arguments

raster_dir_name

A string that contains the path to a directory that has files in raster format. These files will be combined into binned format data.

save_prefix_name

A string with a prefix that will be used name of file that contains the saved binned format data.

bin_width

A number that has the number of data samples that data will be averaged over.

sampling_interval

A number that has the specifies the sampling interval between successive binned data points.

start_time

A number that specifies the time to start binning the data. This needs to be set to one of the start times in the raster data; i.e., if data columns are in the format time.XXX_YYY, then the start_time must be one of the XXX values. By default, the start_time is the first time in the raster data.

end_time

A number that specifies the time to end the binning of the data. This needs to be set to one of the end times in the raster data; i.e., if data columns are in the format time.XXX_YYY, then the start_time must be one of the YYY values. By default, the end_time is the last time in the raster data.

files_contain

A string that specifies that only raster files that contain this string should be included in the binned format data.

num_parallel_cores

An integer specifying the number of parallel cores to use. The default (NULL) value is to use half of the cores detected on the system. If this value is set to a value of less than 1, then the code will be run serially.

Value

Returns a string with the name of the file that was created which has the data in binnned format.

Examples

# create binned data with 150 ms bin sizes sampled at 10 ms intervals
raster_dir_name <- file.path(
  "..", "data-raw", "raster",
  "Zhang_Desimone_7objects_raster_data_rda", ""
)

raster_dir_name <- trimws(file.path(system.file("extdata", package = "NeuroDecodeR"), 
                          "Zhang_Desimone_7object_raster_data_small_rda", " "))


# The code could potentially run faster by using more parallel cores
# (e.g., by not setting the num_parallel_cores argument, half the cores available
#  will be used) 
binned_file_name <- create_binned_data(raster_dir_name, 
                                      file.path(tempdir(), "ZD"), 
                                      150, 50,
                                      num_parallel_cores = 2)