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Busko, I. 2000, in ASP Conf. Ser., Vol. 216, Astronomical Data Analysis Software and Systems IX, eds. N. Manset, C. Veillet, D. Crabtree (San Francisco: ASP), 79

SPECVIEW: An Interactive Java Tool for Visualization and Analysis of Spectral Data

I. Busko
Space Telescope Science Institute, Baltimore, MD 21218

Abstract:

This paper presents the general design concepts used in the development of specview, a Java 1-D spectrum visualization program capable of handling, among others, the data formats generated by Hubble Space Telescope instruments. In the design process, particular emphasis was given to the set of classes that define and handle spectral data, so they can be used not only for building the initial visualization tool, but could serve as well as a foundation stone for a more capable application enhanced with data analysis abilities.

1. Introduction

The specview Java tool was conceived as a testbed for evaluating the use of Object Oriented programming techniques and the Java language to solve astronomical data analysis problems. Its first inception was as a 1-D spectrum visualization tool. However simple the initial requirements were, considerable effort was put into designing a comprehensive set of classes to describe spectral data and its properties. The goal was to produce a set of classes that would support the future upgrade to a full blown data analysis application with minimal recoding.

Usual OO practice mandates that one should strive for the highest degree of encapsulation. That is, an object should not expose its contents to the public, but rather should expose an interface that describes the object's capabilities, including e.g. the ability to create a screen depiction of itself. Thus in specview's case one should require that objects that store spectral data should be able to drawn themselves on screen. In other words, the simplest design would require graphics code that is buried inside these spectrum-holding objects.

On the other hand, another requirement of specview was that it should be able to handle spectral data from different instruments and wavelength regimes in a uniform way. That is, no matter where the data comes from, its screen depiction should be the same. Conversely, a single spectrum could have more than one simultaneous screen representation. This suggests that the graphics code should be independent of the particular details of the spectrum holding classes.

These two conflicting requirements led to a mixed design based on the Model-View-Controller (MVC) paradigm, where objects have screen depictions that are entirely independent from their other attributes. This however applies only to classes that require a common view for subclasses, such as spectrum-holding classes. Other types of objects in specview can have internal GUI code and be truly encapsulated.

Several concepts presented in the Design Patterns book (Gamma et al. 1994) were extensively exploited in specview's design. Design patterns such as Composite, Decorator, Command, Singleton, Observer and Abstract Factory in fact make the backbone of specview's design.

2. Main MVC Design

Figure 1 depicts the MVC relationships that exist in between the main elements of specview.

Figure 1: The MVC structure of specview. See text.
\begin{figure}
\epsscale{.7}
\plotone{P3-03a.eps}
\end{figure}

The Model consists basically of server methods that access a storage area where instances of a Spectrum class are kept. Upon receiving a command for creating a new spectrum, the server resorts to native methods in a factory class. These were presented in previous work (Busko 1999). Spectrum is an abstract class and appropriate subclasses are created by the factory depending on the file structure and/or instrument type. Except for the native code in the factory, and the subclass declaration files, the remaining code in specview can be made entirely unaware of the internal storage details in each Spectrum object, such as an echelle or multi-instrument structure.

The Controller and View are depicted close together in Figure 1, as in most MVC implementations the boundary between these two realms is quite fuzzy. The Controller object keeps the main GUI, but the plotting widgets (windows) have their own set of lower-level controlling elements (such as zoom controls). The plotting widgets are made generic and unaware of the existence of a Spectrum class by means of the Plottable interface. Any object that implements this interface can be rendered by the plotting widgets. Plottable attributes can be dynamically attached to Spectrum objects by the way of a Decorator pattern, thus making possible the rendering of any Spectrum object created by the factory. This design approach allows more code reuse since the plotting code in its entirety can be reused to depict other unrelated objects (such as tables), as long as they can be decorated with Plottable attributes.

The View and Model are linked together by an Observer pattern. When the Controller creates a plotting widget associated with a given Spectrum instance, this instance is informed that it has that particular widget as an observer. From then on, whenever the Spectrum object changes its internal contents, the widget is automatically notified and can perform some action such as refreshing the plot. This mechanism ensures that the View is always in synch with the Model. It also allows more than one observer per observable, thus multiple views of the same spectrum can be kept in synch on screen.

3. Graphics

Graphics support is not directly related to the MVC architecture but is the single most important element of specview, which is basically a plotting application. The initial idea was to resort to existing scientific graphics packages written in Java. A quick survey showed that the few available were basically either literal translations of older, procedural code, or where developed in procedural style, making their adaptation to specview's needs labor-intensive. Additionally, they did not exploit at all the new powerful resources available in Java's Swing and 2D packages.

Thus an effort was made to design and code from scratch a scientific plotting package that would at first satisfy the needs of the project, but then would provide capabilities to support other projects as well. The resulting work showed to be comparable, or even less, than the work that would be necessary to adapt any of the existing, older packages.

The graphics package design is based on two design patterns: Decorator and Singleton. It also uses Observer links for handling the cross-hair cursor.

Figure 2 represents the assembly process used to create a plot. Individual graphics elements such as the data plot, axis, labels, cursor, are plotted by separate objects whose classes implement a basic GraphicCanvas interface. The individual elements are stacked together using a dynamically-defined Decorator pattern. The pattern exploits the transparency and containment capability of Swing components, as well as the internal mechanism used by Java's Abstract Window Toolkit to refresh widgets on screen. This results in very compact and modular code. Decorators can be combined at will for creating customized plots on the fly.

Figure 2: Building a plot using graphics elements. See text.
\begin{figure}
\epsscale{.7}
\plotone{P3-03b.eps}
\end{figure}

The cross-hair cursor is handled by a GraphicsCursor class implemented as a Singleton, that is, only one instance of the class can exist at any time. The GraphicsCursor object tracks the on-screen mouse pointer and uses Observer links to notify interested listeners of the current cursor position in world coordinates and of mouse/key events. Listeners can include the application code, which automatically gets notified of any cursor action and can listen to specific mouse/key presses. Special listeners are CursorCanvas objects, that use the notifications sent by the GraphicsCursor object to update the cross-hair position on screen. In this way multiple windows can handle copies of the cross-hair that move in synch in WCS space, helping the user to relate features displayed in separate windows.

4. Lessons Learned

The work done so far enables us to draw a few conclusions about the OO methodology:

References

Busko, I. 1999, in ASP Conf. Ser., Vol. 172, Astronomical Data Analysis Software and Systems VIII, ed. D. M. Mehringer, R. L. Plante, & D. A. Roberts (San Francisco: ASP), 417

Gamma, E., Helm, R., Johnson, R., Vlissides, J. 1994, Design Patterns, Addison-Wesley Professional Computing Series


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