Antaeus was created to be accessed by a single user who can work on individual data tables. It provides tools for looking at your data when you don’t yet know what you’re looking for, led by your intuition and knowledge about the emergent phenomena represented.
Antaeus does not use and requires no knowledge of statistics. However, it is based on the functional use of fundamental mathematical principles. The basic plot type used everywhere in Antaeus is the scatter plot, supplemented by its high-density counterpart, the sunflower plot. These plots are supported by quantile plots and histograms, which are used to see the data of a single variable.
Scatter plots are used to look for the relationship between two variables, but as the number of variables increases, more and more scatter plots become necessary to visualize all the possible interrelationships. To explore this diversity in a logical manner, something more than a “chart wizard” is needed. Antaeus uses a structure called the data cube, which is generated from a flat-file comma, tab, or semi-colon delimited data table.
A data cube (“cube” for short) is entirely independent of the data table it was created from, and these cubes can be freely exchanged between users. The cube is represented in the interface by a virtual scatter plot matrix within which you navigate the universe of possible scatter plots. The “something more” consists of supporting SVs that enable you to modify the logical structure of the data cube to provide new ways of asking questions about your data.
All the plots generated by Antaeus are very highly finished and do not require any user interaction to achieve this level of quality. You can size the plots by dragging the edges of their windows, and you have extensive control over the palettes used to color them, but all their construction details are handled proactively. Most plots may be saved to clipboard or file (when too large for the clipboard) as a Windows Enhanced Metafile.
NOTE: Free for academic and non-commercial use.
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Sunday, December 31, 2012
R is a multi-paradigm, open-source statistical software package that is widely used for data analysis, graphics and visualisation. In addition to various graphical methods, R is also a platform for developing statistical programs using the “embedded language” called S-Plus. With R, it is easy to transform raw data into graphic displays and perform statistical analyses. R is particularly used in academic research as it provides its user community with robust, high-performance statistical techniques.
Many of R’s capabilities include the following:
· Extensive data manipulation and analysis with tools including linear regression, analysis of variance, spatial statistics, time series, complex hypothesis testing, and others.
· High-level language tools that interact with R for visualization and data manipulation, including ROCR for ROC analysis, and GRACE for graphing time series data.
· General-purpose programming language extensions in the form of C, C++, and Java packages such as igraph, protap, and affy.
· Tools to convert R scripts to executable code for scientific computing systems, including Rserve and Rcompute.
· R support for other languages such as Python and Matlab.
· R integration into a variety of commonly used statistical software packages and platforms, including Microsoft Excel.
Friday, December 29, 2012
JSN Software, a product of Jakarta Software Network, is a simple, powerful and affordable administration panel for Windows Web servers.
All the features of JSN are developed to be used by system administrators, not by end users. Therefore, JSN has only limited functionality and more limited feature list.
Antaeus contains a very simple version of a quantile plot based on a sorted array. It does not need to generate the data. This is useful when the number of values are too large for your computer to process and store in memory at the same time.
This plot is a step up from a flat file or comma-delimited file because the sorting is based on the order of values within the plot.
I am intrigued by this use of Antaeus. For me, it raises an interesting question: if you do not have the resources to generate the data, and you do not have the time to investigate and analyze the data, how can you get insight into the data before you store it
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Macros are defined using a mini-language that is mainly based on the character set of the English language. They are processed in-line at a document or script level, and are executed whenever the current event passes a matching keyword. The syntax of macros is similar to that of VBA and Java, with the main difference being that macros cannot be used to manipulate the contents of the document.
Publication Date:
December 2002
File Size:
4.5 MB
Author(s):
Dino L. Cioffi, Adam G. Duff, Matthew A. D’Errico, Tim Flack
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Antaeus is created to be accessed by a single user who can work on individual data tables. It provides tools for looking at your data when you don’t yet know what you’re looking for, led by your intuition and knowledge about the emergent phenomena represented.
Antaeus does not use and requires no knowledge of statistics. However, it is based on the functional use of fundamental mathematical principles. The basic plot type used everywhere in Antaeus is the scatter plot, supplemented by its high-density counterpart, the sunflower plot. These plots are supported by quantile plots and histograms, which are used to see the data of a single variable.
Scatter plots are used to look for the relationship between two variables, but as the number of variables increases, more and more scatter plots become necessary to visualize all the possible interrelationships. To explore this diversity in a logical manner, something more than a “chart wizard” is needed. Antaeus uses a structure called the data cube, which is generated from a flat-file comma, tab, or semi-colon delimited data table.
A data cube (“cube” for short) is entirely independent of the data table it was created from, and these cubes can be freely exchanged between users. The cube is represented in the interface by a virtual scatter plot matrix within which you navigate the universe of possible scatter plots. The “something more” consists of supporting SVs that enable you to modify the logical structure of the data cube to provide new ways of asking questions about your data.
All the plots generated by Antaeus are very highly finished and do not require any user interaction to achieve this level of quality. You can size the plots by dragging the
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This is a large-scale, Java applet that serves as the user interface for the Antaeus project. It is also the largest data visualization tool that you will have come across. It allows you to select data from a comma-delimited, Excel-type data table and display in various visually interesting ways. The table may be imported directly into the applet, or it can be copied and pasted directly to the applet. The applet will allow you to set different numbers of variables and compare these different number of variables simultaneously. You can also look at specific types of data contained in a single row or column of the data table. A set of built-in SVs make it possible to think about your data in a different way.
If you have any problems or would like to provide feedback, please feel free to write to the development e-mail address: antaeus@…
Antaeus is a data exploration software application for the processing and visualization of structural biology data. It is designed to provide comprehensive and reproducible data processing for the analysis of NMR, X-ray, electron microscopy, and other data.
In particular, Antaeus is useful for the efficient processing of data obtained using high-throughput methods (NMR, X-ray, EPR, EM, AFM, and diffraction).
It provides the ability to import and export files and directories, as well as the ability to perform additional data processing tasks, such as particle counting, calculation of volumes, resolution cut-offs, and crystal averaging. Antaeus provides an intuitive graphical user interface (GUI) and various, easily used scripting languages for executing such tasks.
Antaeus runs under a variety of operating systems. It was developed with the JRE 5.0 or later. However, the user interface runs under the Java 2 Platform, Standard Edition version 7 or later, which is a subset of the Java 2 Platform, Enterprise Edition version 7 or later. The Java language is not required. It will run on both 32-bit and 64-bit Windows and Linux operating systems.
Antaeus is a data exploration software application for the processing and visualization of structural biology data. It is designed to provide comprehensive and reproducible data processing for the analysis of NMR, X-ray, electron microscopy, and other data.
In particular, Antaeus is useful for the efficient processing of data obtained using high-throughput methods (NMR, X-ray, EPR, EM, AFM, and
What’s New in the Antaeus?
Antaeus is a viewer that supports interactive visual data analysis. It is a quick and efficient tool to explore and understand large datasets. It was designed to work with data that are represented as data tables, and it is fully compatible with any external database system such as Microsoft Excel. As such, Antaeus supports the manipulation of large tables stored in Excel, ASCII or delimited text files.
Data tables in Antaeus are represented as flat-file data cubes (a list of dots) organized by variables (columns) and observations (rows). The dot size can be modified independently of the dot shape, enabling multiple visualization channels to be used to analyze the same data table. If the table is too large to fit in the viewer, it can be saved as a Windows Enhanced Metafile, allowing any software that supports the format to work with it.
Home:
License:
GNU GPL2
Bug-reports:
NEWS for 0.3.1 (2014-01-17):
– rho GUI design update for 0.3.1.
– rho 0.3.0 uses a new SV that gives the user the ability to automatically generate a new data cube from a given data table.
– rho is now distributed via CRAN. It is now the R-Forge project
– You can now download the latest development version and use Antaeus from any R-Forge CRAN mirror.
– The Antaeus logo was completely redesigned for 0.3.1. It is now based on the logo of the new Antaeus logo
– The CUSTOMIZE.R script has been removed and Antaeus now uses variables VARIABLES and USER_VARIABLES to do the same thing (when you re-open the project, Antaeus will re-create the project and its settings)
– The GUI for setting up project specific settings is now called the DEFAULT_SETTINGS.R script. This is now available from the top level of the project, not just from the man pages.
– The package manager for Antaeus will now install the rho package.
– Antaeus is now on R-Forge, so any new packages will be uploaded there as well.
NEWS for 0.3.0 (2013-10-16):
– rho GUI was replaced with a new GUI, available at
– SVs have been improved so that:
– you can manipulate a scatter plot by dragging the edges of its window.
– you can choose which palette to use for plotting
System Requirements:
Requires a supported NVIDIA GeForce GTX 580 or AMD Radeon R7 260X graphics card.
Advanced optimization is required to achieve optimal performance.
Requires a Ryzen motherboard with support for AM4 sockets.
Requires a Ryzen motherboard with support for XFR overclocking.
The user can manually set a minimum voltage for the graphics card. (–min-vdd)
To remove the limit, set the minimum voltage to the maximum. (–max-vdd)
The user can manually set a maximum frequency for the graphics
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