shapeExperiment: This is a function used to read the SHAPE_experimentalDesign...
In rSHAPE: Simulated Haploid Asexual Population Evolution

Description Usage Arguments Value Examples

This is a function used to read the SHAPE_experimentalDesign type input file and then build a SHAPE experiment by creating all the folder structure, .R and .sh scripts required to programatically run your experiment – excluding post-analysis, that's a you problem.

shapeExperiment(func_filepath_toDesign, func_templateDir,
  func_maxGrouped_perShell = 2, func_filePath_R = NULL,
  func_baseCall = "CMD BATCH",
  func_rArgs = "\"--args shape_thisRep=1 shape_outDir='fake_serverPath/fakeDir/'\"",
  func_remoteLocation = "$TMPDISK", func_submitArgs = c(number_ofCores
  = "-c 1", memory = "--mem=8192", jobName = "-J fakeJob", wallTime =
  "-t 14-00:00:00", fileOut = "-o fakeOut"), func_processingCores = 1,
  func_suppressOld_summaryFiles = FALSE)

`func_filepath_toDesign`	This is the absolute filepath which points to the SHAPE_experimentalDesign like template you'd like used to identify parameter combinations for building your experiment.
`func_templateDir`	This is the absolute filepath to a directory on your machine where the SHAPE template scripts/files have been saved. They are used by this function to help build your experiment.
`func_maxGrouped_perShell`	Integer value defining the maximal number of jobs that an output shell script will try to have run in parallel once executed. This is related to your parallel computing potential.
`func_filePath_R`	This is the absolute path to the R application on the system where SHAPE would be run via BATCH MODE, its value is applied in shell scripts written for running the experiment. If left NULL then this function will try to use standard R install paths of which I'm aware.
`func_baseCall`	This is a string element of arguments when calling BATCH MODE if R via shell script.
`func_rArgs`	This is a character string which represent additional arguments to be passed via shell script BATCH mode call of R. I consider it most practicable to set the replicate and output directory of SHAPE.
`func_remoteLocation`	The filepath of the compute node on a remote server where your job would be run. The default is based on the environment variable value used in CAC's SLURM submission system.
`func_submitArgs`	This is information concerning sheel script lines for automatic submission of jobs to a remote server's submission system. I'm basing this off of the SLURM system of the Center for Advanced Computing Queen's University computing platform. If your system is different you may need to tweak this. Sorry? This should be a vector of arguments passed for job submissions on a remote server The example here would call 1 core with 8 Gb RAM and a wall time of 14 days and an outFile be named You can add more arguments if your server requires this, they'll get used. BUT where the job's name MUST be identified as — fakeJob —- and the output log as — fakeOut —, you can change the argument queues I also assume your remote server will create a local directory on the compute nodes whre your job once submitted, and that there will be the location defined by func_remoteLocation.
`func_processingCores`	This is the number of parallel cores you would like the summairseExperiment() to call when trying to process your experimental output.
`func_suppressOld_summaryFiles`	Logical flag controlling if your summariseExperiment() will delete old output summary files. setting to FALSE (default) is ideal if you could ever expect you might need to restart whereas TRUE becomes practical if you are worried you'd have updated output to process and you want to ensure a fresh processing start.

If no error is encountered, a message will be returned suggesting the build was successful. SHAPE makes no effort to perform validation of this effort to build the experiment and presumes no fatal errors is sufficient evidence.

# This function relies on script templates which can be found at:
# 'https://github.com/JDench/SHAPE_library/tree/master/SHAPE_templates'
# Once these have been downloaded you can pass the appropriate filepath values
# to the first two arguments. For this example, I'll assume you've installed
# them to a folder position that is now just under the root of your
# R-environment working directory.
# However, before runing the function we need to parameterise your run of SHAPE,
# here I call the default parameters:
defineSHAPE()
# Now using the default templates we design an experiment folder complete with
# shell scripts to submit our work programatically.
# NOTE: Again, this example assumes you've downloaded the templates and placed
#        them at the next filepath and directory-path locations
shapeExperiment(func_filepath_toDesign = "~/SHAPE_templates/SHAPE_experimentalDesign.v.1.r",
                             func_templateDir = "~/SHAPE_templates/")
# You should be greeted with a message suggesting your experiment is built.
# You can find the files now at that script's SHAPE workingDirectory.
list.files(getOption("shape_workDir"))
# Voila!  You can go see the spread of variable evolutionary parameters that were
# considered by looking at -- yourJob_parameterCombos.table -- which is a tab
# delimated file.
# Lastly, you may have R installed elsewhere and so want to have that noted while
# your experiment is built because the shell scripts will need to point to the correct place.
shapeExperiment(func_filepath_toDesign = "~/SHAPE_templates/SHAPE_experimentalDesign.v.1.r",
                             func_templateDir = "~/SHAPE_templates/",
                             func_filePath_R = "~/your_R_folder/R_app/bin/R")
# Now obviously the above location likely is not where you installed R,
# but ideally you get the point. The difference is in how the shell scripts were written.