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With Update, the amended data get plotted in the Graph panel (note that in order to save the amended data, the Save option still needs to be executed).Ī movable tool bar allows quick access to frequently used graphics functions. In the table view, the user can change data entries in the first two columns.

At the bottom of these panels, two functions are provided: Close will delete this dataset from the current session, Save writes the current dataset to an ASCII file compatible with the format of the program Grace data derived from analysis in SDAR will be saved as remarks (indicated by #) at the top of the file. These latter panels show the spreadsheet format of the dataset, comprising of the x-y-data in the first columns, as well as any data derived from analysis in SDAR in the following columns. For each dataset, a new tabbed panel is added with the name of the set showing as label in the tab. The main panel tabbed Graph shows graphical x-y-plots of the current datasets.

SDAR uses tabbed panels to enable viewing of datasets. ) which also allows for generation of image files in PNG- and TIFF-format. In order to generate scalable vector graphics (SVG) images, SDAR uses the Apache Batik SVG toolkit ( These methods are implemented in SDAR as classes LevenbergMarquardt, LinearRegression and NelderMead. ) have been implemented, depending on the type of equation. ) and regression methods provided by the Flanagan library ( SDAR also uses classes for Levenberg-Marquardt minimisation (implemented by JP Lewis), linear regression and Nelder-Mead simplex non-linear regression (implemented by M Flanagan), as well as the Apache Batik SVG toolkit (grey).įor curve fitting, Levenberg-Marquardt minimisation (implemented in Java by JP Lewis The four PCSB components (white) of the program are the main class providing the GUI ( sdar), a class to describe the Dataseries objects, the JPanel class GraphPanel that provides plotting functionality, and supporting PCSB classes. Schematic composition of the SDAR Java application. Concomitantly, a class handling the 2D plotting ( GraphPanel) has also been programmed. The emphasis of this application has been intuitive usability and quick access to a variety of laboratory-derived raw data.

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, we set out to design a simple-to-use and portable Java application for Serial Data Analysis and Regression (SDAR), which enables graphical visualisation, transformation and fitting of two-dimensional data.

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update as of ), there is only one Java/Jython program listed in this context, namely jHepWork (īased on Java classes developed within our Program Collection for Structural Biology and Biophysical Chemistry

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According to a list of numerical analysis software in Wikipedia ( Despite the availability of numerical methods implementations, there is a surprising lack of interface-oriented Java software for data analysis and processing. ), and many algorithms have been made available by developers in Java, including the very extensive library of scientific and numerical classes by Flanagan ( For instance, JAMA provides classes for constructing and manipulating real matrices and their decompositions ( Numerical methods well established in the classical scientific programming languages such as Fortran and C have increasingly been developed and implemented in Java. Our lab has been developing practical Java applications focused on structural biology tasks since 2002 ), a descendant of the ACE/gr 2D plotting tool originally developed for Unix. One of the most established software in this respect is Grace ( This includes, but is not limited to, software such as Fityk

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In the last ten years, free and open source software has also been developed, mainly based on C++ and Python. Widely used software for such tasks include ubiquitous generic spreadsheet programs such as MS Excel, as well as sophisticated commercial software packages such as SigmaPlot, Origin, IGOR, etc. Data analysis and processing are tasks met in almost any experimental laboratory.

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