ZooScatR is an implementation of the Distorted Wave Born Approximation (DWBA) model for the simulation of acoustic scattering by weak scattering targets inside a fluid.
It includes a shiny web application called DWBAapp for easy model parametrisation and result visualisation as well as the option to run the DWBA model from the command line. Additional functions to compute soundspeed in water, water density and Spherical Bessel functions with their derivatives (as needed in the analytical solution of a weakly scattering sphere, e.g. Neumann and Hankel functions).
Copyright (C) 2018 Sven Gastauer, Dezhang Chu, Martin Cox.
This file is part of ZooScatR.
ZooScatR is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
ZooScatR is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with ZooScatR. If not, see <http://www.gnu.org/licenses/>.
This package is open for community development and we encourage users to extend the package as they need. We are not liable for any losses when using ZooScatR.
If using ZooScatR, please cite as:
citation('ZooScatR')ZooScatR can be instaled from binary or source files found here and will be updated regularly.
ZooScatR can be installed form GitHub. This requires the devtools package.
# The package can be installed from Github:
# install.packages("devtools")
#Install the package from github with vignettes
devtools::install_github("AustralianAntarcticDivision/ZooScatR", build_vignettes = TRUE, force_deps=TRUE)
# if the above fails, try the alternative devtools syntax
# devtools::install_github("AustralianAntarcticDivision/ZooScatR", build_opts = c("--no-resave-data", "--no-manual"))
ZooScatR currently depends on:
- shiny - to build the shiny app
- shinyjs - for some features like showing/hiding tabs inside the shiny app
- ggplot2 - for nicer plots
- reshape2 - for easy reshaping of datframes to be plotted in ggplot2
- pracma - for some Matlab-like mathematical operations
- doSNOW - for running the model in Parallel (multiple cores)
- tcltk2 - got system independent progressbar window
- viridis - For improved colour scheme
- plotly - For 3D plotting
These dependencies should be installed automatically, if unavailable when ZooScatR is installed. If not, the missing libraries can be installed through:
packages <- c("shiny","shinyjs","ggplot2", "reshape2","pracma","doSNOW","tcltk2","viridis", "plotly")
if (length(setdiff(packages, rownames(installed.packages()))) > 0) {
install.packages(setdiff(packages, rownames(installed.packages())))}If you get a message such as:
WARNING: Rtools is required to build R packages, but is not currently installed.
Install Rtools by downloading the required binary package from cran:
For a quick start, a minimal example:
library(ZooScatR)
fname <- paste0(system.file(package="ZooScatR"),"/extdata/configs/config_0.dat") #Loacation of the parameters file
para = read_para(fname) #Read parameters file
#Create list with soundspeed info
misc <- list(cw=1500)
#Run DWBA based on config file
res <- bscat(para=para, misc=misc) #Target strength vs Frequency
res$rplot #Show the result plot
#Target strength vs angular position
para$simu$var_indx <- 2 #Set output variable to Angular position
#Run DWBA based on config file
res <- bscat(para=para, misc=misc)
res$rplot #Show the result plot
#Backscattering amplitude vs ka (Wavenumber x width)
para$simu$out_indx <- 1 #Set output to Backscattering amplitude
para$simu$var_indx <- 3 #Set output variable to ka
#Run DWBA based on config file
res <- bscat(para=para, misc=misc)
res$rplot #Show the result plot
#Reduced Target Strength vs Frequency (Wavenumber x width)
para$simu$out_indx <- 4 #Set output to Reduced Target Strength
para$simu$var_indx <- 1 #Set output variable to Frequency
#Run DWBA based on config file
res <- bscat(para=para, misc=misc)
res$rplot #Show the result plot
#Run the DWBA shiny app
DWBAapp()It is recommended to view the app in a browser like Chromium, Chrome or Firefox for better visualisation and user experience, rather than the R preview window.
We are constantly workin on new examples and vignettes.
A list of all currently integrated vignettes can be obtained through:
vignette(package="ZooScatR")The best way to view vignettes is in your web browse:
browseVignettes("ZooScatR")Currently the following vignettes are available:
- A general introduction to the DWBA model, with examples on how to run the DWBA model inside ZooScatR from the command
vignette("DwbaCommand", package="ZooScatR") - A description of the DWBA web application
vignette("DWBAapp_vignette", package="ZooScatR") - A validation of the model implication within ZooScatR through comparison with an analytical solution of the sphere case
vignette("CompareToAnalyticalSolution", package="ZooScatR") - An a bit more advanced tutorial on how to run multiple DWBA instance in parallel using multiple cores
vignette("DWBAParallel", package="ZooScatR")
All vignettes are located in the vignettes folder in the package folder, available after isntallation of ZooScatR. If you don't know the location of the package folder, this can be obtained through system.file(package="ZooScatR"). It is recommended to open the html files directly in a browser, rather than through the R preview, as formulas and otherfeatures might not be rendered correctly in the R preview window.
For ZooScatR specific questions make a feature request or post an issue on GitHub.
For general R questions visit Stack Overflow.
If none of those options seem appropriate and you are getting really desperate, contact one the authors.