This R package provides functions for creating 3D color and point plots using the rgl package, and segmentation of sonar data.
Version: 1.1 Required R version: 3.3.3
# Install the packages that cpplot3d depends on. Note that this updates all the specified packages to the latest (binary) version. To skip installing already installed packages, run install.packages(setdiff(dep.pck, installed.packages()[,"Package"]), repos="http://cran.us.r-project.org") instead: dep.pck <- c("devtools", "akima", "ccaPP", "data.table", "fBasics", "fields", "fpc", "gdata", "gsl", "pbapply", "rgl", "XML") install.packages(dep.pck, repos="http://cran.us.r-project.org") # Install cpplot3d and also the packages that cpplot3d depends on which are on GitHub (by Holmin): # On Windows you will need Rtools to complete the installations. Check if you have this by running Sys.getenv('PATH'), and go to https://cran.r-project.org/bin/windows/Rtools/ to install Rtools if not. Note that if you need to run R as administrator due to security settings, it is advised to install the pakcages in plain R, and not using Rstudio. Close Rstudio, open R and run the installation, and reopen Rstudio. dep.pck.git <- c("arnejohannesholmin/TSD", "arnejohannesholmin/SimradRaw", "arnejohannesholmin/sonR", "arnejohannesholmin/echoIBM", "arnejohannesholmin/cpplot3d") # If you want to install the lastest development versions, run devtools::install_github(dep.pck.git, ref="develop") instead: devtools::install_github(dep.pck.git)
### If an event of underwater acoustic data exists use this event. If not, generate an event from the example data in the sonR package: # Set the directory of the acoustic data, here simply as the tempdir() but preferably another location: library(sonR) dir <- tempdir() ev <- generate.event(event="Event1", cruise="Cruise1", esnm="EK60", dir.type = c("raw", "tsd"), dir.data=dir) evRaw <- ev evTSD <- ev # Add one raw file to the event: echoSounderFile <- file.path(system.file("extdata", package="sonR"), "RedSlip-D20160915-T120914.raw") file.copy(echoSounderFile, evRaw) # Generate the TSD files, which are faster to read with R: EKRaw2TSD(evRaw) # Plot an echogram of the data, which are from a netpen with herring: system.time(cplot2d.event(evTSD, t="all", xaxis="p")) # Plotting with time along the x axis is more time demanding, since image.plot() is used as opposed to grid.raster() when the x variable has fixed increments. system.time(cplot2d.event(evTSD, t="all", xaxis="t")) # Observe that the maximum absolue fractional deviation from the median of the diffs of the variable on the x axis is printed. Setting tol=0.7 allows for gaps in the x variable and still plot using grid.raster(): system.time(cplot2d.event(evTSD, t="all", tol=1))
The cpplot3d package is licensed under the LGPL-3.)
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