As a result of the last UseR conference and some great spatial workshops and talks where I participated I decided to rework the selection dialog for the upcoming Bio7 2.3 to transfer ImageJ selection data as ‘Spatial Objects’ with the help of the package ‘sp‘ and the Java GDAL binding (version 1.7.1).
One reason to add this functionality is the great improvement for the use of the ‘spatstat’ package which I will present as part of a workshop at the next Imagej conference 2015 (I already gave a short overview of R and spatial packages in the 2012 conference).
In additon the supplied actions can help scientists which work with georeferenced data to profit from the wealth of ImageJ analyze methods and vice versa brings new maybe unknown GIS methods in the focus of microscopists.
The transferred objects can be converted easily to spatstat objects (ppp, psp, owin, etc.) and if equipped with a data frame converted to a marked point pattern.
Though it is already easy to convert ImageJ selections and image pixel data to spatstat objects in 2d and in 3d from ImageJ measurements with Bio7 the new actions make it easy to georeference the data (probably with some data dependent unknown limitations of projections of course – the Java API of GDAL emphasizes that for the used transform method) and add data frames to the spatial shapes (transferred ImageJ measurements data, created spreadsheet data, etc., available in the R workspace).
Below you can see a result of a dummy transfer of point data from a 7000*7000 georeferenced geotiff image where I selected and transferred points from a highly zoomed tiny region.
The right site of the image shows the selected (x,y) ImageJ selection. The left site shows the final converted (Lat, Lon) data loaded in the GIS software QGIS to control the pixel precision.
At all the georeferenced results seems to be exact in all test so far.
I think the new methods are a great help to transfer image measurements and selections to R ready for postprocessing with powerful spatial packages like, e.g., ‘spatstat’.
I released a new version of Bio7 for Windows, Linux and MacOSX simultaneously. This release is based on Eclipse 4.5 which was published on Wednesday.
It comes bundled with the latest ImageJ version (1.49u) and the latest R version (bundled with Windows and Mac).
HTML editor has now an enabled “Outline” view (with the help of a HTML parser)
New feature and action (main toolbar) to create knitr HTML reports easily (just add R commands in a HTML div layer which can be created with the knitr action in the GUI HTML editor toolbar – see screenshot below)
Added default knitr HTML preferences
Added more R editor preferences
Improved the MacOSX GUI
Updated all scientific libraries for Java (Commons Math, etc.)
Improved the dynamic invocation of the Java main method (now an empty string is passed)
I published a MacOSX release candidate for Bio7 2.1 based on Eclipse 4.5 RC2. This release was tested on MacOSX 10.10. The final release will be published after the official Eclipse 4.5 release.
Bio7 2.1 comes as a regular *.dmg installation package. Just drag the Bio7.app to the Applications folder.
Bio7 2.1 comes with a bundled jre 1.8.45. No need to install an extra Java Runtime Environment.
Bio7 2.1 comes bundled with R 3.2.0 and Rserve 1.8.2 installed.
Eventually XQuartz has to be installed to use the default custom R plotting device of Bio7 on MacOSX. If you plot the first time with R and XQuartz is not available a dialog will inform about the missing package.
After the 64-bit release of Windows the Linux 64-bit and Windows 32-bit release can be downloaded at: http://bio7.org
The installation of Bio7 is similar to the installation of the Eclipse environment. Simply decompress the downloaded *.zip file in a preferred location on your file system. After decompressing with a standard zip-tool (like WinZip, Win Rar) the typical file structure of an Eclipse based application will be created. To start the application simply double click on the Bio7 binary file.
R and Rserve installation:
To use R from within Bio7 please install R with a Linux R package manager.
Also the installation of the Rserve library is required. Rserve hast be compiled and installed in the local R application with the shell command:
sudo PKG_CPPFLAGS=-DCOOPERATIVE R CMD INSTALL Rserve_1.8-2.tar.gz
The flag before R CMD INSTALL… is necessary to enable a shared workspace when switching from a local Rserve connection to the native Bio7 R console and conversely. After the installation of R the path to the R (if not using the default path!) application has to be adjusted inside of Bio7 (Preferences- ▷ Preferences Bio7). In addition the path to the (add-on) packages install location has to be adjusted, too (Preferences ▷ Preferences Bio7 ▷ RServe Preferences).
Please also set the user rights for the folder. This is sometimes necessary if you would like to install packages with the Bio7 interface and you don’t have the user rights. Since Bio7 1.4 default R paths are set which are usually correct for a Linux distribution!