Antaeus 2.2

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Antaeus 2.2 Ranking & Summary

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User Review: 0 (0 times)
File size: 16.3MB
Platform: Windows Vista, Windows 2000, Windows XP, Wind
License: Freeware
Price:
Downloads: 14
Date added: 2009-05-09

Antaeus 2.2 description

Antaeus 2.2 is an application for analyzing data. The fundamental tool used is the scatter plot. A single scatter plot can be used to study the relationship between two variables, but as the number of variables increases, more and more plots become necessary to visualize all the possible interrelationships.

Antaeus is built on a framework to which increasingly specialized data visualization tools will be attached. For instance, previous 2.1 release with the addition of subsystems for viewing density, sunflower, quantile, and histogram plots. As more tools and subsystems are attached to the framework, so will the depth with which Antaeus can be used to study raw data.

All the plots generated by Antaeus are very highly finished and do not require any user interaction to achieve this level of quality. Users can size the plots by dragging the edges of their windows and they have extensive control over the palettes used to color them, but all their construction details are handled proactively.

Antaeus is also a platform from which plots may be published. Any plot may be saved to file or clipboard as a Windows Enhanced Metafile (EMF), which can be embedded in reports, papers, and presentations created in Microsoft Office products such as Word, PowerPoint and Publisher. Support for EMF is also increasing among non-Microsoft publication suites. These sophisticated programs are empowered by the use of plots they cannot possibly construct themselves.

Enhancements:

  • Single scatter plot
  • Double scatter plot
  • Scatter plot matrix
  • Single density plot
  • Double density plot
  • Density plot matrix
  • Single sunflower plot
  • Double sunflower plot
  • Sunflower plot matrix
  • Single quantile plot
  • Single histogram plot
  • Quantile plot array
  • Histogram plot array
  • Color separation of dimension values
  • Creation of subsets
  • Use of subsets as active main subset
  • Use of subsets as brush in multivariate plots
  • Magnification of measures
  • Reversal of measure scale.

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