ISAW: Integrated Spectral Analysis Workbench Technical Overview - PowerPoint PPT Presentation

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ISAW: Integrated Spectral Analysis Workbench Technical Overview

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Mouse/keyboard used to zoom/unzoom. Abridged Organization. of ISAW Source. ISAW. Command ... Zoom in on merged runs. Future Interface: Wizards. ISAW. Operators ... – PowerPoint PPT presentation

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Title: ISAW: Integrated Spectral Analysis Workbench Technical Overview


1
ISAW Integrated Spectral Analysis
WorkbenchTechnical Overview
  • ARCS Software Workshop at
  • California Institute of Technology
  • Peter F. Peterson (IPNS)

2
ISAW contributors
  • Dennis Mikkelson and Ruth MikkelsonUW-Stout
  • Alok Chatterjee (now on DAS team)
  • Peter Peterson (Post-Doc)
  • John Hammonds (DASread run file)
  • Chun Loong (scientific advisor)
  • Tom Worlton (project manager)
  • Dongfeng Chen (HRMECS functions, now in China)

3
The IPNS Web Project
  • The goal of the IPNS Web Project is to provide
    remote access to data using portable, extensible
    software
  • Integrated Spectral Analysis Workbench (ISAW)
  • ISAW can read, view, and manipulate neutron
    scattering data. It provides both a GUI for ease
    of use and a scripting language for the power of
    repetitive operations. It is written entirely in
    Java? using object-oriented programming
    techniques for ease of portability and
    maintenance.

4
ISAW Design Goals
  • Interactive environment for visualization and
    analysis of Neutron Scattering Data
  • Applicable to any instrument
  • Freely available
  • User friendly GUI
  • Programmer friendly (OOP)
  • User extensible
  • Remote data access

5
DataSet Concept
  • A DataSet holds a collection of DataBlocks
    (spectra) with same units
  • Each DataBlock can have meta-data associated with
    it stored in an extensible list of Attributes

6
DataSet Concept (cont)
  • DataBlocks (individual spectrafunctions or
    histograms)
  • Includes attributes, x-values, y-values, errors
  • DataSets (sets of spectra)
  • Includes DataBlocks, OperationLog, x-units,
    x-label, y-units, y-label, title, data ranges,
    attributes
  • Operations are DataSet dependent and can be
    performed on all spectra in DataSet
  • Datasets can be merged, summed, etc.
  • Containers (sets of DataSets)

7
ISAW data views
Table view
Tree view
8
ISAW data views
Selected graph view
Image view
Scrolled graph view
3D view
9
Views are responsive to controls
  • DataSets know which spectrum is currently pointed
    at/clicked on
  • DataSets know which spectra are selected
  • Menus know what operations can be performed on
    specified DataSets

10
Views are responsive to controls
  • Operations menu depends on DataSet pointed at by
    mouse/arrow keys
  • Attributes are listed for pointed at spectrum or
    DataSet
  • Cursor position readouts are responsive to mouse
    drag movements and arrow key movements
  • Selected graph view only shows selected spectra
  • Graph portion of Image view shows selected
    spectra plus pointed at spectrum
  • Mouse/keyboard used to zoom/unzoom

11
Abridged Organizationof ISAW Source
12
Adding New Functionality
  • End users can add new subroutines either as
    scripts or operators
  • Common subroutines can be shared in a single
    location
  • Individual users can develop code for their
    specific use

13
Operators
  • Written in java
  • Automatically located and added to menus
  • Promotes code reuse
  • Function
  • Maintains a list of parameters
  • Invoked Using getResult()

14
EXAMPLE ActivateStorage
  • Required methods
  • constructors
  • getCommand() for scripts to call the operator
  • setDefaultParameters() set up reasonable default
    values
  • getResult() perform the actual operation
  • All information is passed to the operator in
    parameters

15
Scripts
  • Simple uncompiled language to make repetitive
    tasks easier using FORTRAN/Basic-like syntax
  • Automatically added to menu system
  • GUI interface is automatically generated
  • Function
  • Provide easy user add-ons
  • Can be run inside or outside of ISAW

16
EXAMPLE merge_runs
17
Merged runs
18
Zoom in on merged runs
19
Future Interface Wizards
20
EXAMPLE MathWizard
  • Forms
  • perform one logical step
  • draw themselves
  • contain help information
  • Wizards
  • collect forms in an order
  • communicate between forms
  • allows switching between forms in order
  • contain help information

21
Future Plans for ISAW
  • Abstraction of data types allow for using model
    functions and event data
  • Viewers create custom viewers using existing
    viewer components
  • Wizards
  • Greater NeXuS support
  • XML for internal saves of data and processing
    information
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