read_experiment {Rtrack} | R Documentation |
Read experiment data.
Description
Reads a spreadsheet containing a description of all the files required for an experiment to allow batch execution.
Usage
read_experiment(
filename,
format = NA,
interpolate = FALSE,
project.dir = NA,
data.dir = project.dir,
author.note = "",
threads = 1,
verbose = FALSE
)
Arguments
filename |
A spreadsheet file containing a description of the experiment or a trackxf file containing an exported experiment. |
format |
An experiment description for reading raw data can be provided
as an Excel spreadsheet ("excel") or as a comma-delimited ("csv") or
tab-delimited ("tab", "tsv", "txt" or "text") text file. The value "trackxf"
indicates that the file is an archived experiment in the trackxf format (as
generated by |
interpolate |
This is passed to the |
project.dir |
A directory path specifying where the files needed for
processing the experiment are stored. Default ( |
data.dir |
A directory path specifying where the raw data are stored.
All paths specified in the experiment description spreadsheet are
interpreted as being relative to the |
author.note |
Optional text describing the experiment. This might be useful if the data is to be published or otherwise shared. Appropriate information might be author names and a link to a publication or website. |
threads |
The number of CPU threads/processes to run in parallel. The default is 1, which will use just one single thread. A value of 0 will try to use the maximum number of available cores (using multi-threading if available). Using all of the available threads/logical cores may not be sensible though, depending on your hardware. Note that for some Linux machines with multi-threading capabilities, the number of threads detected might be the same as the number of physical CPU cores. Negative values will start the default number of threads minus the given number. |
verbose |
Should feedback be printed to the console. This is only useful
for debugging and takes a little longer to run. Default is |
Details
Information about a full experiment can be assembled into a spreadsheet (
currently Excel and CSV formats are supported) and used to process large
numbers of files in one batch. The project directory (project.dir
) is
where the arena description files are found. This will typically be the same
place as the experiment description file (and is set to be this by default).
This does not need to be the same as the current working directory. An
optional data directory (data.dir
) can also be specified separately
allowing the storage-intensive raw data to be kept in a different location
(for example on a remote server). Together, these options allow for
flexibility in managing your raw data storage. Individual tracks are
associated with their raw data file, experimental group metadata, an arena
and any other parameters that the strategy-calling methods require. Required
columns are "_TrackID", "_TargetID", "_Day", "_Trial", "_Arena" "_TrackFile"
and "_TrackFileFormat" (note the leading underscore "_"). Any additional
columns (without a leading underscore) will be interpreted as user-defined
factors or other metadata and will be passed on to the final analysis objects
and thus be available for statistical analysis.
For details on how interpolation is performed (if interpolate
is set
to TRUE
), see the documentation for read_path
.
For larger experiments, it might be helpful to run the experiment processing on multiple CPU cores in parallel. To do this, simply specify the number of processes ("threads") to use.
Value
An rtrack_experiment
object containing a complete description
of the experiment.
See Also
read_path
, read_arena
,
identify_track_format
to identify the format of your raw
track files, and check_experiment
.
Examples
require(Rtrack)
experiment.description = system.file("extdata", "Minimal_experiment.xlsx",
package = "Rtrack")
experiment = read_experiment(experiment.description)