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Java DRA Algorithm Library

For Opal Neutron Scattering. Java DRA Algorithm Library. Data Analysis Team Jian Wang, Yang Fei, Paul Hathaway contribute to this library. Outline. Introduction Data Reduction and analysis Library Design for DRA Global View of DRA Library Class UML Diagram and Control

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Java DRA Algorithm Library

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  1. For Opal Neutron Scattering Java DRA Algorithm Library Data Analysis Team Jian Wang, Yang Fei, Paul Hathaway contribute to this library

  2. Outline Introduction Data Reduction and analysis Library Design for DRA Global View of DRA Library Class UML Diagram and Control Summery

  3. Introduction • Provide data reduction capability and support for data analysis tools to the users of the OPAL neutron beam instruments • DRA library contains data reduction and analysis algorithm modules • Provide graphic and non-graphic access interface • Java is employed for working language. XML is used for configuration • DRA visualisation is developed depending upon openGL. • Data analysis package will offer various functions based on user’s inquiry • Image process on two dimensional graphic environment.

  4. Experiment Review

  5. DRA Requirements • Collected raw data should be corrected with detection efficiency due to detector and electronics sensitivity, • Background should also be removed from data sample, • Multiple scan data sample treatment in same experiment, • Geometry should be corrected for difference type of detector. • Mask process to reject bad regional data • Should be easily to process regular and generic mask shape. • Multiple masks can be applied in same data sample. • Data integration in different 2theta region, also can be easily convert between 2theta and Q neutron wavelets. • Curve fitting can be applied to selected distribution function.

  6. Detector and Data Sample 512 pixels in vertical Horizontal with 128 corrected Scattering pattern geometry correction Data sets stitching 128*nScan x 512

  7. Algorithm Library design • Data Reduction Algorithm • Efficiency correction can be different with different detectors, • Backgrounds should be considered all possible sources, • Data set stitch is quite different for different instruments, • Geometry correction is applied for pixel by pixel correction depending upon scattering theoretical prediction. • Data Analysis Algorithm • Multiple functions should be applied for curve fitting, • Various data region shape integrations are considered, • Wavelets Q and 2theta can be converted through graphic and non-graphic • Visualisation should be applied at the any stage of DRA. • Data integration with required region can be applied at the any stage

  8. Active Algorithm Diagram Data in Efficiency Correction BG subtraction Multi-Data sets stitching Geometry correction Mask process Math Library Stat Library Vis Library Multiple integrations Meta para Ctr para Library

  9. Developing Status We have developed (or developing) algorithm for 6 instruments. • HRPD 12 algorithms have been full developed and tested • Efficiency correction • Background subtraction (simplified) • Multiple data stitching • Geometry correction • Mask processor • Integration multiple functions • Regular data region integration, such as horizontal, vertical, box shape, oval … • Special data region integration, complex data region. • Curve fitting • Visualisation • HIPD, RSD, TAS and SANS are full developed. HIPD and RSD are tested, TAS and SANS need slightly modification and discussion. • Reflectometer are partly developed, need to discuss new requirement.

  10. Summery • With Java platform independent characteristic, Java algorithm library can be applied to any platform. • Library is designed module by module. It can be easily used. • Graphic function is depend on openGL. This design offers good functionality to process mask application and data visualisation. • Fitting is designed to use though graphic and non-graphic access. This is easy to use for any application • Library modules can be full controlled by process manager input control parameters.

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