Astrosat Project Soft X-Ray Telescope (SXT)

Size: px
Start display at page:

Download "Astrosat Project Soft X-Ray Telescope (SXT)"

Transcription

1 Astrosat Project Soft X-Ray Telescope (SXT) SXT-SOFTWARE-SXTFLAGPIX TIFR Team Sanket Kotak Ashutosh Bajpai Kallol Mukerjee April 29, 2016 Department of Astrophysics & Astronomy Tata Institute of Fundamental Research Mumbai

2 Document Revision Status A-amend, M-modification, D-deletion Version o. Date Section ature Description 1 29/4/16 All A Initial Version

3 AME sxtflagpix Flags events for bad pixels and calibration source location. USAGE sxtflagpix [parameter = ] DESCRIPTIO 'sxtflagpix' flags events occurring in bad pixels and bad column locations, events associated with the corner calibration sources. Moreover, events whose central pixel in the 3x3 neighborhood has a PHA value (PHAS[1]) below a certain threshold are flagged. If the parameter 'thrfile' is set to CALDB, 'sxtflagpix' reads the threshold value stored in the calibration database file. By setting 'thrfile' to OE, the task allows the user to set this threshold using the parameter 'evtthr' and 'splithr'. 'sxtflagpix' allows for two different input files that identify bad pixels. These are: 1. the Bad Pixels calibration file which includes the most up to date information about known bad pixels, 2. a user supplied list of bad pixels (this file has to be of the same format as the CALDB bad pixels file). The CCD has four calibration sources located at the corners of the detector. Events coming from these positions are flagged to allow for their identification during the screening. Also the events outside of the field of view of the instrument (FOV) are flagged. The locations of the calibration sources and the geometry of the FOV are read from a CALDB file specified through the parameter 'regionfile'. The user has an option to choose which bad pixel list to use. All events are checked and flagged using the information obtained from the input bad pixels files. The bad pixels files contain a column 'TIME' at which the pixel is first considered as bad. The task reads the 'TIME' column and, for a given observation, considers only the pixels identified as bad before the observation start date. The event flag is stored as a 16 bit binary number in the column STATUS. The flag, recorded in the column STATUS, indicates if the event is considered good or bad.

4 The list of flags is the following: b Good event b Event falls in a bad pixel from CALDB b RESERVED b RESERVED b Event falls in hot bad pixel b Event falls in a user bad pixel b Event falls in flickering bad pixels b RESERVED b Event has a neighbor hot or flickering b Event falls in a bad column b Event has PHAS[1] < Event Threshold b Event has a neighbor bad from bad pixels list b Bad Event b Event from calibration source 1 b Event from calibration source 2 b Event from calibration source 3 b Event from calibration source 4 If the parameter 'owstatus' is set to 'yes' (default) the STATUS column is overwritten. To update the STATUS column, without erasing the values of the previous 'sxtflagpix' run, the user must set to 'no' the 'owstatus' parameter. All bad pixels are stored in an extension of the output file. If this already exists and the parameter 'owstatus' is set to 'no', the extension is updated with new bad pixels. The bad pixels extension or output file contains the following columns: RAWX and RAW give the raw coordinates of the pixel; TPE which identifies whether it is a single pixel (1), a column (2) or a row (3). For columns and rows of bad pixels, RAWX and RAW indicate the start pixel and EXTET the length of the set of consecutive bad pixels included in the bad pixels file; BADFLAG stores a 16 bit binary number which indicates the origin of the bad pixel.

5 PARAMETERS (infile) [filename=as1p01_044t01_ sxtpc00_level2.evt] Input Level1 Science Data File (outfile) [filename=as1p01_044t01_ sxtpc00_level2_flagpixfile.tmp] Output Level2 Unfiltered Event File (thrfile) [filename=oe / CALDB] ame of Threshold File. If set as OE 'sxtevtgen' module asks for all threshold values. (bpfile) [filename=caldb] ame of Bad Pixel File (userbpfile) [filename=oe / Filename ] ame of Input User Bad Pixel File (regionfile)[filename=oe / CALDB] ame of Region File (four corner source events are not flagged as bad if regionfile=oe) (owstatus) [string= / ] Overwrite Status Column if set as. (evtthr) [integer] Event threshold value is use for selection of events (splithr) [integer] Split Threshold Value (logpropfile) [filename=sxtflagpix.properties] LOG4CPP properties filename (logfile) [filename=sxtflagpix.log] output log filename (chatter = 2) [integer] Chatter Level (min=0, max=5). (clobber=) [string] If clobber= overwrite the output file.

6 (history=) [string] write history in output file.

7 START sxtflagpix.par file Read Input/Ouput parameter for sxtflagpix CALDB threshold file Read Threshold values from Threshold file CALDB badpix file CALDB region file Read all Bad pixel information from BadPix file Read four CornerSource and field of view regions Region file Add Status Column in Level2 Unfiltered Event File Get Total number of events in Level2 Unfiltered Event file If Row umber in Event File< Total number of Events if rawx >= 0 && rawx <= 599 && rawy >= 0 && rawy <= in STATUS Column if rawx = 0 rawx = 599 rawy = 0 rawy = 599 rawx-1 = 0 rawx+1 = 599 rawy-1 = 0 rawy+1 = in STATUS Column if (rawx - calsrc[0].rawx)*(rawx - calsrc[0].rawx) +(rawy - calsrc[0].rawy)*(rawy - calsrc[0].rawy) <= calsrc[0].radius * calsrc[0].radius

8 8192 in STATUS Column if (rawx - calsrc[1].rawx)*(rawx - calsrc[1].rawx) +(rawy - calsrc[1].rawy)*(rawy - calsrc[1].rawy) <= calsrc[1].radius * calsrc[1].radius in STATUS Column if (rawx - calsrc[2].rawx)*(rawx - calsrc[2].rawx) +(rawy - calsrc[2].rawy)*(rawy - calsrc[2].rawy) <= calsrc[2].radius * calsrc[2].radius in STATUS Column if (rawx - calsrc[3].rawx)*(rawx - calsrc[3].rawx) +(rawy - calsrc[3].rawy)*(rawy - calsrc[3].rawy) <= calsrc[3].radius * calsrc[3].radius if PHA[0] < Event Threshold in STATUS Column 2 in STATUS Column Flag status with value 256 in STATUS Column for each neighboring pixel around (RAWX,RAW) If event registered at RAWX & RAW is available in Bad Pixel table from BAD PIX File Row umber = Row umber + 1 STOP

Astrosat Project Soft X-Ray Telescope (SXT)

Astrosat Project Soft X-Ray Telescope (SXT) Astrosat Project Soft X-Ray Telescope (SXT) Standard Operating Procedure AS1SXTLevel2-1.0 Software Prepared by TIFR SXT Team 4 December 2015 Department of Astrophysics & Astronomy Tata Institute of Fundamental

More information

Astrosat Project Soft X-Ray Telescope (SXT)

Astrosat Project Soft X-Ray Telescope (SXT) Astrosat Project Soft -Ray Telescope (ST) Standard Operating Procedure AS1STLevel2-1.1 Software Prepared by TIFR ST Team 4 December 2015 Department of Astrophysics & Astronomy Tata Institute of Fundamental

More information

2. ctifile,s,h, CALDB,,, ACIS CTI ARD file (NONE none CALDB <filename>)

2. ctifile,s,h, CALDB,,, ACIS CTI ARD file (NONE none CALDB <filename>) MIT Kavli Institute Chandra X-Ray Center MEMORANDUM January 17, 2006 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: Adjusting ACIS Event Data to Compensate for CTI Revision:

More information

Weighting ARFs and RMFs: multiple sources

Weighting ARFs and RMFs: multiple sources Weighting ARFs and RMFs: multiple sources CIAO 3.4 Science Threads Weighting ARFs and RMFs: multiple sources 1 Table of Contents Weighting ARFs and RMFs: multiple sources CIAO 3.4 Get Started CALDB 3.3.0.1

More information

2. ctifile,s,h, CALDB,,, ACIS CTI ARD file (NONE none CALDB <filename>)

2. ctifile,s,h, CALDB,,, ACIS CTI ARD file (NONE none CALDB <filename>) MIT Kavli Institute Chandra X-Ray Center MEMORANDUM August 11, 2006 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: Adjusting ACIS Event Data to Compensate for CTI Revision:

More information

1 Afterglows and Hot pixels

1 Afterglows and Hot pixels MIT Kavli Institute Chandra X-Ray Center MEMORANDUM April 28, 2017 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: Afterglow and hot-pixel spec Revision: 2.11 URL: http://space.mit.edu/cxc/docs/docs.html#

More information

1 acis make bkgd. MEMORANDUM May 11, Description. 1.2 Parameters

1 acis make bkgd. MEMORANDUM May 11, Description. 1.2 Parameters MIT Kavli Institute Chandra X-Ray Center MEMORANDUM May 11, 2006 To: Jonathan McDowell, SDS Group Leader From: Glenn Allen (SDS) for the ACIS Background Working Group Subject: acis make bkgd Revision:

More information

dph/h3/cxc/icd/specs tgextract2-1.0/tgextract2.tex

dph/h3/cxc/icd/specs tgextract2-1.0/tgextract2.tex MIT Kavli Institute Chandra X-Ray Center MEMORANDUM November 16, 2015 To: From: Jonathan McDowell, SDS Group Leader; Kenny Glotfelty, DS Tools Lead David Huenemoerder, SDS Subject: tgextract2 Specifications

More information

Obtain Grating Spectra from LETG/HRC I Data

Obtain Grating Spectra from LETG/HRC I Data Obtain Grating Spectra from LETG/HRC I Data CIAO 3.4 Science Threads Obtain Grating Spectra from LETG/HRC I Data 1 Table of Contents Obtain Grating Spectra from LETG/HRC I Data CIAO 3.4 Data Preparation

More information

1 Description. MEMORANDUM February 19, 2013

1 Description. MEMORANDUM February 19, 2013 MIT Kavli Institute Chandra X-Ray Center MEMORANDUM February 19, 2013 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: DELTOCLK spec Revision: 3.2 URL: http://space.mit.edu/cxc/docs/docs.html#deltoclk

More information

Using the ACIS "Blank Sky" Background Files

Using the ACIS Blank Sky Background Files Using the ACIS "Blank Sky" Background Files CIAO 3.4 Science Threads Using the ACIS "Blank Sky" Background Files 1 Table of Contents Get Started Download the background files Download the scripts Finding

More information

Ahelp: tgdetect CIAO 3.4. Jump to: Description Examples Parameters CHANGES IN CIAO 3.3 Bugs See Also

Ahelp: tgdetect CIAO 3.4. Jump to: Description Examples Parameters CHANGES IN CIAO 3.3 Bugs See Also Ahelp: tgdetect CIAO 3.4 URL: http://cxc.harvard.edu/ciao3.4/tgdetect.html Last modified: December 2006 AHELP for CIAO 3.4 tgdetect Context: tools Jump to: Description Examples Parameters CHANGES IN CIAO

More information

1 Bias-parity errors. MEMORANDUM August 18, Description. 1.2 Input

1 Bias-parity errors. MEMORANDUM August 18, Description. 1.2 Input MIT Kavli Institute Chandra X-Ray Center MEMORANDUM August 18, 2010 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: Bias-parity error spec Revision: 0.2 URL: http://space.mit.edu/cxc/docs/docs.html#berr

More information

1 acis build chip gti

1 acis build chip gti MIT Kavli Institute Chandra X-Ray Center MEMORANDUM July 15, 2014 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: acis build chip gti Revision: 2.1 URL: http://space.mit.edu/cxc/docs/docs.html#gti

More information

Create a PSF CIAO 3.4 Science Threads

Create a PSF CIAO 3.4 Science Threads Create a PSF CIAO 3.4 Science Threads Create a PSF 1 Table of Contents Create a PSF CIAO 3.4 The PSF Libraries Get Started Characterizing the Source What is the energy of the source? (dmextract) How far

More information

Obtain Grating Spectra from HETG/ACIS S Data

Obtain Grating Spectra from HETG/ACIS S Data Obtain Grating Spectra from HETG/ACIS S Data CIAO 3.4 Science Threads Obtain Grating Spectra from HETG/ACIS S Data 1 Table of Contents Obtain Grating Spectra from HETG/ACIS S Data CIAO 3.4 Data Preparation

More information

Ahelp: tg_create_mask CIAO 3.4. tg_create_mask infile outfile input_pos_tab grating_obs [opt_parameters]

Ahelp: tg_create_mask CIAO 3.4. tg_create_mask infile outfile input_pos_tab grating_obs [opt_parameters] Ahelp: tg_create_mask CIAO 3.4 URL: http://cxc.harvard.edu/ciao3.4/tg_create_mask.html Last modified: December 2006 AHELP for CIAO 3.4 tg_create_mask Context: tools Jump to: Description Examples Parameters

More information

MIT Center for Space Research. Chandra X-Ray Center. 1 acis build mask. MEMORANDUM April 26, Description. 1.2 Input. 1.

MIT Center for Space Research. Chandra X-Ray Center. 1 acis build mask. MEMORANDUM April 26, Description. 1.2 Input. 1. MIT Center for Space Research Chandra X-Ray Center MEMORANDUM April 26, 2004 To: Martin Elvis, SDS Group Leader From: Glenn E. Allen, SDS Subject: acis build mask Revision: 3.9 URL: http://space.mit.edu/cxc/docs/docs.html#msk

More information

Eye tracking by image processing for helping disabled people. Alireza Rahimpour

Eye tracking by image processing for helping disabled people. Alireza Rahimpour An Introduction to: Eye tracking by image processing for helping disabled people Alireza Rahimpour arahimpo@utk.edu Fall 2012 1 Eye tracking system: Nowadays eye gaze tracking has wide range of applications

More information

ii ASC ACIS Tools Revision 2.0 Contents 1 Preamble iii 1.1 Document and Change Control Log iii 1.2 Applicable Documents...

ii ASC ACIS Tools Revision 2.0 Contents 1 Preamble iii 1.1 Document and Change Control Log iii 1.2 Applicable Documents... ASC Data Processing Tools for ACIS Revision 2.0 Glenn E. Allen Chandra X-ray Center Science Data Systems November 1, 1999 1 ii ASC ACIS Tools Revision 2.0 Contents 1 Preamble iii 1.1 Document and Change

More information

Extracting Extended Source Spectra and Responses

Extracting Extended Source Spectra and Responses Extracting Extended Source Spectra and Responses CIAO 3.4 Science Threads Extracting Extended Source Spectra and Responses 1 Table of Contents Getting Started CALDB 3.3.0.1 patch Using Consistent Calibration:

More information

ii CXC ACIS Tools Revision 2.1 Contents 1 Preamble iii 1.1 Document and Change Control Log iii 1.2 Applicable Documents...

ii CXC ACIS Tools Revision 2.1 Contents 1 Preamble iii 1.1 Document and Change Control Log iii 1.2 Applicable Documents... CXC Data Processing Tools for ACIS Revision 2.1 Glenn E. Allen Chandra X-ray Center Science Data Systems February 28, 2000 1 ii CXC ACIS Tools Revision 2.1 Contents 1 Preamble iii 1.1 Document and Change

More information

1 acis build chip gti

1 acis build chip gti MIT Kavli Institute Chandra X-Ray Center MEMORANDUM June 22, 2014 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: acis build chip gti Revision: 2.0 URL: http://space.mit.edu/cxc/docs/docs.html#gti

More information

Merging Data from Multiple Imaging Observations

Merging Data from Multiple Imaging Observations Merging Data from Multiple Imaging Observations CIAO 3.4 Science Threads Merging Data from Multiple Imaging Observations 1 Table of Contents Merging Data from Multiple Imaging Observations CIAO 3.4 Getting

More information

TECHNICAL REPORT. Title: The Coordinate Systems of NIRISS Doc #: Date: Rev: Authors: André R. Martel Phone:

TECHNICAL REPORT. Title: The Coordinate Systems of NIRISS Doc #: Date: Rev: Authors: André R. Martel Phone: When there is a discrepancy between the information in this technical report and information in JDox, assume JDox is correct. TECHNICAL REPORT Title: The Coordinate Systems of NIRISS Doc #: Date: Rev:

More information

XRT Data Analysis I E. Troja (NASA/GSFC/ORAU)

XRT Data Analysis I E. Troja (NASA/GSFC/ORAU) XRT Data Analysis I E. Troja (NASA/GSFC/ORAU) with thanks to Kim Page (U. Leicester) 1 Introduction to XRT Basic steps: Outline - XRT data processing (from Level 1 to Level 3) - create images, light curves

More information

Description of NOMAD Observation Types and HDF5 Datasets NOT YET COMPLETE

Description of NOMAD Observation Types and HDF5 Datasets NOT YET COMPLETE NOMAD Science Team KONINKLIJK BELGISCH INSTITUUT VOOR RUIMTE-AERONOMIE INSTITUT ROYAL D AERONOMIE SPATIALE DE BELGIQUE ROYAL BELGIAN INSTITUTE OF SPACE AERONOMY KONINKLIJK BELGISCH INSTITUUT VOOR RUIMTE-AERONOMIE

More information

OPUS Science Data Processing

OPUS Science Data Processing Science Data Processing www.stsci.edu/software/opus/ www.dpt.stsci.edu/ 1 of 13 OPUS Science Data Processing PMDB ASSIST PDB pod file Data Partitioning Support Schedule Data Validation EDT binary dataset

More information

File Operations. Lecture 16 COP 3014 Spring April 18, 2018

File Operations. Lecture 16 COP 3014 Spring April 18, 2018 File Operations Lecture 16 COP 3014 Spring 2018 April 18, 2018 Input/Ouput to and from files File input and file output is an essential in programming. Most software involves more than keyboard input and

More information

Image Processing. BITS Pilani. Dr Jagadish Nayak. Dubai Campus

Image Processing. BITS Pilani. Dr Jagadish Nayak. Dubai Campus Image Processing BITS Pilani Dubai Campus Dr Jagadish Nayak Image Segmentation BITS Pilani Dubai Campus Fundamentals Let R be the entire spatial region occupied by an image Process that partitions R into

More information

RGS data reduction and analysis of point-like sources

RGS data reduction and analysis of point-like sources 14 th ESAC SAS Workshop 2 nd 6 th June 2014 RGS data reduction and analysis of point-like sources Rosario González-Riestra XMM-Newton SOC ESAC Processing RGS data (I) from... to... FRAME Time CCD, node,

More information

Capturing, Modeling, Rendering 3D Structures

Capturing, Modeling, Rendering 3D Structures Computer Vision Approach Capturing, Modeling, Rendering 3D Structures Calculate pixel correspondences and extract geometry Not robust Difficult to acquire illumination effects, e.g. specular highlights

More information

Introduction and Scripts. Jonathan McDowell Chandra X-ray Center, SAO

Introduction and Scripts. Jonathan McDowell Chandra X-ray Center, SAO Introduction and Scripts Jonathan McDowell Chandra X-ray Center, SAO 2014 Nov CXC Scope Caveat: will cover ACIS imaging data only Basics the same for HRC and gratings, but with extra wrinkles Introduction

More information

ESAS upgrades in SAS. Carlos GABRIEL + S3MT + SAS WG XMM-Newton Science Operations Centre ESAC / ESA

ESAS upgrades in SAS. Carlos GABRIEL + S3MT + SAS WG XMM-Newton Science Operations Centre ESAC / ESA ESAS upgrades in SAS Carlos GABRIEL + S3MT + SAS WG XMM-Newton Science Operations Centre ESAC / ESA SAS development, future plans, and expected ESAS upgrades in SAS Carlos GABRIEL + S3MT + SAS WG XMM-Newton

More information

Astrosat Project Level2 Interface Control Document

Astrosat Project Level2 Interface Control Document Astrosat Project Level2 Interface Control Document Level2 Data Pipeline Software For Soft X-Ray Telescope (SXT) SAC DP Team Navita Thakkar, Arvind K Singh, T. P. Srinivasan, B. Gopala Krishna Instrument

More information

UNIVERSITY OF HAWAII AT MANOA Institute for Astrononmy

UNIVERSITY OF HAWAII AT MANOA Institute for Astrononmy Pan-STARRS Document Control PSDC-xxx-xxx-01 UNIVERSITY OF HAWAII AT MANOA Institute for Astrononmy Pan-STARRS Project Management System PS1 Postage Stamp Server System/Subsystem Description Grant Award

More information

1 Introduction. 2 Replacement. MEMORANDUM April 7, 2010

1 Introduction. 2 Replacement. MEMORANDUM April 7, 2010 MIT Kavli Institute Chandra X-Ray Center MEMORANDUM April 7, 2010 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: Bias repair Revision: 4.4 URL: http://space.mit.edu/cxc/docs/docs.html#bias

More information

XPS1 Automated Multi-Sample Run Procedure

XPS1 Automated Multi-Sample Run Procedure XPS1 Automated Multi-Sample Run Procedure Follow the XPS Operating Procedure to load samples into the SAC chamber. Once the samples are in the SAC chamber, the following procedure can be used to automate

More information

Cosmic Ray Shower Profile Track Finding for Telescope Array Fluorescence Detectors

Cosmic Ray Shower Profile Track Finding for Telescope Array Fluorescence Detectors Cosmic Ray Shower Profile Track Finding for Telescope Array Fluorescence Detectors High Energy Astrophysics Institute and Department of Physics and Astronomy, University of Utah, Salt Lake City, Utah,

More information

Relevant Documents. MEMORANDUM February 24, 2015

Relevant Documents. MEMORANDUM February 24, 2015 MIT Kavli Institute Chandra X-Ray Center MEMORANDUM February 24, 2015 To: Jonathan McDowell, SDS Group Leader From: David Huenemoerder, John Davis, SDS Subject: ACIS Dead Area Algorithm and File Specifications

More information

1 Introduction. 2 Replacement. MEMORANDUM May 13, Jonathan McDowell, SDS Group Leader Glenn E. Allen, SDS Bias repair

1 Introduction. 2 Replacement. MEMORANDUM May 13, Jonathan McDowell, SDS Group Leader Glenn E. Allen, SDS Bias repair MIT Kavli Institute Chandra X-Ray Center MEMORANDUM May 13, 2010 To: From: Subject: Revision: 5.4 URL: File: Jonathan McDowell, SDS Group Leader Glenn E. Allen, SDS Bias repair http://space.mit.edu/cxc/docs/docs.html#bias

More information

SWAP Image Calibration. Daniel B. Seaton, D. Shaun Bloomfield, ROB & TCD SWAP Teams

SWAP Image Calibration. Daniel B. Seaton, D. Shaun Bloomfield, ROB & TCD SWAP Teams SWAP Image Calibration Daniel B. Seaton, D. Shaun Bloomfield, ROB & TCD SWAP Teams Primary Image Calibration Steps Implemented Dark Subtraction Pixel Map Correction Image Scaling, Rotation, & Centering

More information

Ulrik Söderström 16 Feb Image Processing. Segmentation

Ulrik Söderström 16 Feb Image Processing. Segmentation Ulrik Söderström ulrik.soderstrom@tfe.umu.se 16 Feb 2011 Image Processing Segmentation What is Image Segmentation? To be able to extract information from an image it is common to subdivide it into background

More information

CS223b Midterm Exam, Computer Vision. Monday February 25th, Winter 2008, Prof. Jana Kosecka

CS223b Midterm Exam, Computer Vision. Monday February 25th, Winter 2008, Prof. Jana Kosecka CS223b Midterm Exam, Computer Vision Monday February 25th, Winter 2008, Prof. Jana Kosecka Your name email This exam is 8 pages long including cover page. Make sure your exam is not missing any pages.

More information

Chandra Source Catalog Quality Assurance Specifications

Chandra Source Catalog Quality Assurance Specifications I. General Chandra Source Catalog Quality Assurance Specifications August 17, 2007 Ian Evans (ievans@cfa.harvard.edu) 1. Quality Assurance Mechanisms Chandra Source Catalog quality assurance is achieved

More information

Table of Contents. Appendix. Table of Figures. Document Change Log

Table of Contents. Appendix. Table of Figures. Document Change Log Definition of the Telemetry Parameter Exchange Protocol All information is subject to change without notice and does not represent a commitment on the part of. Release 1.09 (October 1999) Table of Contents

More information

1 Description. 2 Input. 3 Output. 4 Parameters. MEMORANDUM June 15, 2011

1 Description. 2 Input. 3 Output. 4 Parameters. MEMORANDUM June 15, 2011 MIT Kavli Institute Chandra X-Ray Center MEMORANDUM June 15, 2011 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: DELTOCLK spec Revision: 1.2 URL: http://space.mit.edu/cxc/docs/docs.html#deltoclk

More information

Chromeleon software orientation

Chromeleon software orientation Chromeleon software orientation Upon opening of Chromeleon shortcut, a blue screen should appear (called control panel). If this does not occur, the green circled shortcut will open this screen. To ensure

More information

Using A Pileup Model

Using A Pileup Model Using A Pileup Model Sherpa Threads (CIAO 3.4) Using A Pileup Model 1 Table of Contents Background Information Remove the acis_detect_afterglow Correction Getting Started Reading in Data & Instrument Responses

More information

Display. Introduction page 67 2D Images page 68. All Orientations page 69 Single Image page 70 3D Images page 71

Display. Introduction page 67 2D Images page 68. All Orientations page 69 Single Image page 70 3D Images page 71 Display Introduction page 67 2D Images page 68 All Orientations page 69 Single Image page 70 3D Images page 71 Intersecting Sections page 71 Cube Sections page 72 Render page 73 1. Tissue Maps page 77

More information

Diagnostic Instrumentation

Diagnostic Instrumentation Introduction The internal workings of video compression software may be difficult to understand, especially motion estimation and mode decision. In an attempt to further the transparency within the Dirac

More information

TraceFinder Analysis Quick Reference Guide

TraceFinder Analysis Quick Reference Guide TraceFinder Analysis Quick Reference Guide This quick reference guide describes the Analysis mode tasks assigned to the Technician role in the Thermo TraceFinder 3.0 analytical software. For detailed descriptions

More information

NIR INSTRUMENT FOR GLAO. Takashi Hattori, Iwata Ikuru (Subaru Telescope)

NIR INSTRUMENT FOR GLAO. Takashi Hattori, Iwata Ikuru (Subaru Telescope) NIR INSTRUMENT FOR GLAO Takashi Hattori, Iwata Ikuru (Subaru Telescope) Instrument for GLAO Need for wide field NIR instrument GLAO : good image quality over 15 FoV cf. current Cs NIR instrument (MOIRCS)

More information

Gamma spectroscopic measurements using the PID350 pixelated CdTe radiation detector

Gamma spectroscopic measurements using the PID350 pixelated CdTe radiation detector Gamma spectroscopic measurements using the PID350 pixelated CdTe radiation detector K. Karafasoulis, K. Zachariadou, S. Seferlis, I. Papadakis, D. Loukas, C. Lambropoulos, C. Potiriadis Abstract Spectroscopic

More information

Document Number: SC2/FTS/SOF/020

Document Number: SC2/FTS/SOF/020 SCUBA-2 FTS Project Office University of Lethbridge Physics Department 4401 University Drive Lethbridge, Alberta CANADA T1K 3M4 Tel: 1-403-329-2771 Fax: 1-403-329-2057 Email: brad.gom@uleth.ca WWW: http://research.uleth.ca/scuba2/

More information

How CCD Quantum efficiency is computed?

How CCD Quantum efficiency is computed? How CCD Quantum efficiency is computed? Definition: This is the formula used in PRiSM software to compute the QE is the following : Median( Iλ( X 1, Y1, X, Y ) Bias( X1, Y1, X, Y ))* CVF QE( Tex *100 Pix

More information

RASTERIZING POLYGONS IN IMAGE SPACE

RASTERIZING POLYGONS IN IMAGE SPACE On-Line Computer Graphics Notes RASTERIZING POLYGONS IN IMAGE SPACE Kenneth I. Joy Visualization and Graphics Research Group Department of Computer Science University of California, Davis A fundamental

More information

ESAS into SAS ESAC. XMM-Newton. Carlos GABRIEL & Aitor IBARRA. XMM-Newton Science Operations Centre ESAC / ESA SAS

ESAS into SAS ESAC. XMM-Newton. Carlos GABRIEL & Aitor IBARRA. XMM-Newton Science Operations Centre ESAC / ESA SAS E into Carlos GABRIEL & Aitor IBARRA Science Operations Centre / ESA What is E? Extended Source Analysis Software (E): * package for the analysis of EPIC MOS and pn observations (by SS & KK), [suited especially

More information

Ariel Dynamics, Inc. TRIM MODULE. Revision 1.0. Ariel Dynamics, Inc. C3D TRANSFORM MODULE

Ariel Dynamics, Inc. TRIM MODULE. Revision 1.0. Ariel Dynamics, Inc. C3D TRANSFORM MODULE Ariel Dynamics, Inc. TRIM MODULE Revision 1.0 Ariel Dynamics, Inc. C3D TRANSFORM MODULE Contents i Contents ARIEL TRIM PROGRAM 1 INTRODUCTION...1 WHAT S NEW IN TRIM 1.0...1 SYSTEM REQUIREMENTS...2 TO START

More information

CIAO Exercises. Table of Contents. Introduction. Getting to know Chandra data Download dataset. Exercise 10. Review V&V report.

CIAO Exercises. Table of Contents. Introduction. Getting to know Chandra data Download dataset. Exercise 10. Review V&V report. CIAO Exercises Table of Contents Introduction Getting to know Chandra data Download dataset Exercise 1 Review V&V report Exercise 2 Display data in ds9 Exercise 3 Exercise 4 Exercise 5 Exercise 6 Inspect

More information

DETECT Talk for CIAO workshop D. Harris

DETECT Talk for CIAO workshop D. Harris DETECT Talk for CIAO workshop D. Harris 1.0 GENERAL - Philosophy...what it is, and what it isn t. 2.0 CELLDETECT 3.0 WAVDETECT 4.0 VTPDETECT 5.0 EVALUATION OF ALGORITHMS VIA DEEP FIELDS 6.0 SUMMARY 1.0

More information

Biomedical Image Analysis. Point, Edge and Line Detection

Biomedical Image Analysis. Point, Edge and Line Detection Biomedical Image Analysis Point, Edge and Line Detection Contents: Point and line detection Advanced edge detection: Canny Local/regional edge processing Global processing: Hough transform BMIA 15 V. Roth

More information

1 Introduction. 2 Replacement. MEMORANDUM November 13, 2009

1 Introduction. 2 Replacement. MEMORANDUM November 13, 2009 MIT Kavli Institute Chandra X-Ray Center MEMORANDUM November 13, 2009 To: Jonathan McDowell, SDS Group Leader From: Glenn E. Allen, SDS Subject: Bias repair Revision: 4.1 URL: http://space.mit.edu/cxc/docs/docs.html#bias

More information

CS 490: Computer Vision Image Segmentation: Thresholding. Fall 2015 Dr. Michael J. Reale

CS 490: Computer Vision Image Segmentation: Thresholding. Fall 2015 Dr. Michael J. Reale CS 490: Computer Vision Image Segmentation: Thresholding Fall 205 Dr. Michael J. Reale FUNDAMENTALS Introduction Before we talked about edge-based segmentation Now, we will discuss a form of regionbased

More information

Introduction to the Data Model

Introduction to the Data Model DM Intro CIAO 34 Introduction to the Data Model CIAO 34 Science Threads Introduction to the Data Model 1 Table of Contents DM Intro CIAO 34 Get Started Data Model Tools Running Data Model Tools Virtual

More information

Detecting Sources in Chandra Data

Detecting Sources in Chandra Data Detecting Sources in Chandra Data Goal Identify statistically significant brightness enhancements, over local background, deriving from both unresolved (point) and resolved (extended) x-ray sources. Emphasize

More information

Morphological Image Processing

Morphological Image Processing Morphological Image Processing Binary image processing In binary images, we conventionally take background as black (0) and foreground objects as white (1 or 255) Morphology Figure 4.1 objects on a conveyor

More information

Robot Vision: Camera calibration

Robot Vision: Camera calibration Robot Vision: Camera calibration Ass.Prof. Friedrich Fraundorfer SS 201 1 Outline Camera calibration Cameras with lenses Properties of real lenses (distortions, focal length, field-of-view) Calibration

More information

Solid Modeling. Thomas Funkhouser Princeton University C0S 426, Fall Represent solid interiors of objects

Solid Modeling. Thomas Funkhouser Princeton University C0S 426, Fall Represent solid interiors of objects Solid Modeling Thomas Funkhouser Princeton University C0S 426, Fall 2000 Solid Modeling Represent solid interiors of objects Surface may not be described explicitly Visible Human (National Library of Medicine)

More information

NHSC HIFI DP workshop Caltech, September A Tour of HIFI Data. - page 1

NHSC HIFI DP workshop Caltech, September A Tour of HIFI Data. - page 1 NHSC HIFI DP workshop Caltech, 12-13 September 2012 A Tour of HIFI Data - page 1 Outline Opening the observation context A casual look at the HIPE GUI presentation of your data How to plot the spectra

More information

AIA Data processing and Distribution: from Telemetry to Science data

AIA Data processing and Distribution: from Telemetry to Science data AIA Data processing and Distribution: from Telemetry to Science data AIA and HMI impose novel requirements on the data processing and distribution. The volume of data places constraints on the frequency

More information

Data transformation guide for ZipSync

Data transformation guide for ZipSync Data transformation guide for ZipSync Using EPIC ZipSync and Pentaho Data Integration to transform and synchronize your data with xmatters April 7, 2014 Table of Contents Overview 4 About Pentaho 4 Required

More information

ELEN E4830 Digital Image Processing. Homework 6 Solution

ELEN E4830 Digital Image Processing. Homework 6 Solution ELEN E4830 Digital Image Processing Homework 6 Solution Chuxiang Li cxli@ee.columbia.edu Department of Electrical Engineering, Columbia University April 10, 2006 1 Edge Detection 1.1 Sobel Operator The

More information

1 Overview. MEMORANDUM November 4, 2015

1 Overview. MEMORANDUM November 4, 2015 MIT Kavli Institute Chandra X-Ray Center MEMORANDUM November 4, 2015 To: File From: David P. Huenemoerder, Glenn E. Allen Subject: Description of enhancements to HETG/ACIS CC-mode processing Revision:

More information

ICD 2.3/4.3. Wavefront Correction Control System to Data Handling System

ICD 2.3/4.3. Wavefront Correction Control System to Data Handling System ICD 2.3/4.3 Wavefront Correction Control System to Data Handling System Version: Issued By: Erik Johansson, Keith Cummings, Kit Richards, Luke Johnson Draft 19 December 2014 Wavefront Correction Group

More information

Week 5: Files and Streams

Week 5: Files and Streams CS319: Scientific Computing (with C++) Week 5: and Streams 9am, Tuesday, 12 February 2019 1 Labs and stuff 2 ifstream and ofstream close a file open a file Reading from the file 3 Portable Bitmap Format

More information

Python Working with files. May 4, 2017

Python Working with files. May 4, 2017 Python Working with files May 4, 2017 So far, everything we have done in Python was using in-memory operations. After closing the Python interpreter or after the script was done, all our input and output

More information

Detection and Classification of Vehicles

Detection and Classification of Vehicles Detection and Classification of Vehicles Gupte et al. 2002 Zeeshan Mohammad ECG 782 Dr. Brendan Morris. Introduction Previously, magnetic loop detectors were used to count vehicles passing over them. Advantages

More information

Assignment 2: Stereo and 3D Reconstruction from Disparity

Assignment 2: Stereo and 3D Reconstruction from Disparity CS 6320, 3D Computer Vision Spring 2013, Prof. Guido Gerig Assignment 2: Stereo and 3D Reconstruction from Disparity Out: Mon Feb-11-2013 Due: Mon Feb-25-2013, midnight (theoretical and practical parts,

More information

Lobster eye X-ray optics: Data processing from two 1D modules

Lobster eye X-ray optics: Data processing from two 1D modules Contrib. Astron. Obs. Skalnaté Pleso 47, 178 183, (2017) Lobster eye X-ray optics: Data processing from two 1D modules O. Nentvich, M. Urban, V. Stehlikova, L. Sieger and R. Hudec Czech Technical University

More information

An Introduction to Images

An Introduction to Images An Introduction to Images CS6640/BIOENG6640/ECE6532 Ross Whitaker, Tolga Tasdizen SCI Institute, School of Computing, Electrical and Computer Engineering University of Utah 1 What Is An Digital Image?

More information

OU-VIS: Status. H.J. McCracken. and the OU-VIS team

OU-VIS: Status. H.J. McCracken. and the OU-VIS team OU-VIS: Status H.J. McCracken and the OU-VIS team What is OU-VIS for? From raw VIS data, create the algorithms and software to produce calibrated images suitable for cosmic shear measurement Implications:

More information

Edge and local feature detection - 2. Importance of edge detection in computer vision

Edge and local feature detection - 2. Importance of edge detection in computer vision Edge and local feature detection Gradient based edge detection Edge detection by function fitting Second derivative edge detectors Edge linking and the construction of the chain graph Edge and local feature

More information

Am29F040B. Data Sheet Supplement for PROM Programmer Manufacturers. SECTOR PROTECTION/ UNPROTECTION FOR Am29F040B. Sector Unprotection

Am29F040B. Data Sheet Supplement for PROM Programmer Manufacturers. SECTOR PROTECTION/ UNPROTECTION FOR Am29F040B. Sector Unprotection SUPPLEMENT Am29F040B Data Sheet Supplement for PROM Programmer Manufacturers This supplement is for use with the Am29F040B data sheet, publication number 21445, and describes the sector protection and

More information

GN ReSound. Personal Fine Tuning. User Interface Specifications, Version 11

GN ReSound. Personal Fine Tuning. User Interface Specifications, Version 11 GN ReSound Personal Fine Tuning User Interface Specifications, Version 11 Chris Kiess 7/23/2014 Contents Introduction... 3 1.0 Calibration Instructions... 4 1.1 Calibration... 5 1.2 Home Page... 6 1.3

More information

HCR Using K-Means Clustering Algorithm

HCR Using K-Means Clustering Algorithm HCR Using K-Means Clustering Algorithm Meha Mathur 1, Anil Saroliya 2 Amity School of Engineering & Technology Amity University Rajasthan, India Abstract: Hindi is a national language of India, there are

More information

Digital Image Processing COSC 6380/4393

Digital Image Processing COSC 6380/4393 Digital Image Processing COSC 6380/4393 Lecture 21 Nov 16 th, 2017 Pranav Mantini Ack: Shah. M Image Processing Geometric Transformation Point Operations Filtering (spatial, Frequency) Input Restoration/

More information

CSE Spring 2004 Homework 3

CSE Spring 2004 Homework 3 Overview This homework processes graphical image files. The skeleton provided to you reads and writes the files. Your task is to write several filters to modify the image content while it is in memory.

More information

ICD for REEF circular Encircled Energy calibration file. Parameter data cube HDU for PSF encircled energy. Version: 2008 Aug 25.

ICD for REEF circular Encircled Energy calibration file. Parameter data cube HDU for PSF encircled energy. Version: 2008 Aug 25. ICD for REEF circular Encircled Energy calibration file Parameter data cube HDU for PSF encircled energy Contents Version: 2008 Aug 25 1 Introduction 2 2 PSF encircled energy file 2 2.1 IMAGE HDU header.........................

More information

FPGA IMPLEMENTATION FOR REAL TIME SOBEL EDGE DETECTOR BLOCK USING 3-LINE BUFFERS

FPGA IMPLEMENTATION FOR REAL TIME SOBEL EDGE DETECTOR BLOCK USING 3-LINE BUFFERS FPGA IMPLEMENTATION FOR REAL TIME SOBEL EDGE DETECTOR BLOCK USING 3-LINE BUFFERS 1 RONNIE O. SERFA JUAN, 2 CHAN SU PARK, 3 HI SEOK KIM, 4 HYEONG WOO CHA 1,2,3,4 CheongJu University E-maul: 1 engr_serfs@yahoo.com,

More information

Multiple View Geometry

Multiple View Geometry Multiple View Geometry Martin Quinn with a lot of slides stolen from Steve Seitz and Jianbo Shi 15-463: Computational Photography Alexei Efros, CMU, Fall 2007 Our Goal The Plenoptic Function P(θ,φ,λ,t,V

More information

Chapter 11 Representation & Description

Chapter 11 Representation & Description Chain Codes Chain codes are used to represent a boundary by a connected sequence of straight-line segments of specified length and direction. The direction of each segment is coded by using a numbering

More information

COMP 175 COMPUTER GRAPHICS. Lecture 11: Recursive Ray Tracer. COMP 175: Computer Graphics April 9, Erik Anderson 11 Recursive Ray Tracer

COMP 175 COMPUTER GRAPHICS. Lecture 11: Recursive Ray Tracer. COMP 175: Computer Graphics April 9, Erik Anderson 11 Recursive Ray Tracer Lecture 11: Recursive Ray Tracer COMP 175: Computer Graphics April 9, 2018 1/40 Note on using Libraries } C++ STL } Does not always have the same performance. } Interface is (mostly) the same, but implementations

More information

ASCII American Standard Code for Information Interchange. Text file is a sequence of binary digits which represent the codes for each character.

ASCII American Standard Code for Information Interchange. Text file is a sequence of binary digits which represent the codes for each character. Project 2 1 P2-0: Text Files All files are represented as binary digits including text files Each character is represented by an integer code ASCII American Standard Code for Information Interchange Text

More information

Morphological Image Processing

Morphological Image Processing Morphological Image Processing Morphology Identification, analysis, and description of the structure of the smallest unit of words Theory and technique for the analysis and processing of geometric structures

More information

Instrument Distortion Calibration File Transformation

Instrument Distortion Calibration File Transformation Instrument Distortion Calibration File Transformation David Borncamp, Vera Kozhurina-Platais, Colin Cox, Warren Hack Space Telescope Science Institute July 1, 2014 ABSTRACT The current generation of detectors

More information

Fluke 430 Series II Firmware Upgrade

Fluke 430 Series II Firmware Upgrade Fluke 430 Series II Firmware Upgrade With this Flash Tool you can upgrade the firmware of the Fluke 430 Series II Power Quality Analyzer V03.01 and later to V05.04. It is recommended to make a copy of

More information

Chandra X-Ray Center. CIAO Workshop

Chandra X-Ray Center. CIAO Workshop Chandra X-Ray Center 1 CIAO Workshop Introduction to X-Ray Data Analysis David Huenemoerder (MIT) Randall Smith (CfA) Abstract We describe in general terms how flux incident on an X-Ray telescope observatory

More information

Data Collection Software Release Notes. Real-Time PCR Analysis Software Release Notes. SNP Genotyping Analysis Software Release Notes

Data Collection Software Release Notes. Real-Time PCR Analysis Software Release Notes. SNP Genotyping Analysis Software Release Notes PN 101-6531 D1 RELEASE NOTES Biomark/EP1 Software To download the latest version of the software for Biomark HD, Biomark, and EP1, go to fluidigm.com/software. For more information about updating the software,

More information