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• New Replication, Optimizer and High Availability features in MySQL 5.6.5!

  - by Rob Young

  As the Product Manager for the MySQL database it is always great to announce when the MySQL Engineering team delivers another great product release.  As a field DBA and developer it is even better when that release contains improvements and innovation that I know will help those currently using MySQL for apps that range from modest intranet sites to the most highly trafficked web sites on the web.  That said, it is my pleasure to take my hat off to MySQL Engineering for today's release of the MySQL 5.6.5 Development Milestone Release ("DMR"). The new highlighted features in MySQL 5.6.5 are discussed here: New Self-Healing Replication ClustersThe 5.6.5 DMR improves MySQL Replication by adding Global Transaction Ids and automated utilities for self-healing Replication clusters.  Prior to 5.6.5 this has been somewhat of a pain point for MySQL users with most developing custom solutions or looking to costly, complex third-party solutions for these capabilities.  With 5.6.5 these shackles are all but removed by a solution that is included with the GPL version of the database and supporting GPL tools.  You can learn all about the details of the great, problem solving Replication features in MySQL 5.6 in Mat Keep's Developer Zone article.  New Replication Administration and Failover UtilitiesAs mentioned above, the new Replication features, Global Transaction Ids specifically, are now supported by a set of automated GPL utilities that leverage the new GTIDs to provide administration and manual or auto failover to the most up to date slave (that is the default, but user configurable if needed) in the event of a master failure. The new utilities, along with links to Engineering related blogs, are discussed in detail in the DevZone Article noted above. Better Query Optimization and ThroughputThe MySQL Optimizer team continues to amaze with the latest round of improvements in 5.6.5. Along with much refactoring of the legacy code base, the Optimizer team has improved complex query optimization and throughput by adding these functional improvements: Subquery Optimizations - Subqueries are now included in the Optimizer path for runtime optimization.  Better throughput of nested queries enables application developers to simplify and consolidate multiple queries and result sets into a single unit or work. Optimizer now uses CURRENT_TIMESTAMP as default for DATETIME columns - For simplification, this eliminates the need for application developers to assign this value when a column of this type is blank by default. Optimizations for Range based queries - Optimizer now uses ready statistics vs Index based scans for queries with multiple range values. Optimizations for queries using filesort and ORDER BY.  Optimization criteria/decision on execution method is done now at optimization vs parsing stage. Print EXPLAIN in JSON format for hierarchical readability and Enterprise tool consumption. You can learn the details about these new features as well all of the Optimizer based improvements in MySQL 5.6 by following the Optimizer team blog. You can download and try the MySQL 5.6.5 DMR here. (look under "Development Releases")  Please let us know what you think!  The new HA utilities for Replication Administration and Failover are available as part of the MySQL Workbench Community Edition, which you can download here .Also New in MySQL LabsAs has become our tradition when announcing DMRs we also like to provide "Early Access" development features to the MySQL Community via the MySQL Labs.  Today is no exception as we are also releasing the following to Labs for you to download, try and let us know your thoughts on where we need to improve:InnoDB Online OperationsMySQL 5.6 now provides Online ADD Index, FK Drop and Online Column RENAME.  These operations are non-blocking and will continue to evolve in future DMRs.  You can learn the grainy details by following John Russell's blog.InnoDB data access via Memcached API ("NotOnlySQL") - Improved refresh of an earlier feature releaseSimilar to Cluster 7.2, MySQL 5.6 provides direct NotOnlySQL access to InnoDB data via the familiar Memcached API. This provides the ultimate in flexibility for developers who need fast, simple key/value access and complex query support commingled within their applications.Improved Transactional Performance, ScaleThe InnoDB Engineering team has once again under promised and over delivered in the area of improved performance and scale.  These improvements are also included in the aggregated Spring 2012 labs release:InnoDB CPU cache performance improvements for modern, multi-core/CPU systems show great promise with internal tests showing:    2x throughput improvement for read only activity 6x throughput improvement for SELECT range Read/Write benchmarks are in progress More details on the above are available here. You can download all of the above in an aggregated "InnoDB 2012 Spring Labs Release" binary from the MySQL Labs. You can also learn more about these improvements and about related fixes to mysys mutex and hash sort by checking out the InnoDB team blog.MySQL 5.6.5 is another installment in what we believe will be the best release of the MySQL database ever.  It also serves as a shining example of how the MySQL Engineering team at Oracle leads in MySQL innovation.You can get the overall Oracle message on the MySQL 5.6.5 DMR and Early Access labs features here. As always, thanks for your continued support of MySQL, the #1 open source database on the planet!

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• MySQL Connect Only 10 Days Away - Focus on InnoDB Sessions

  - by Bertrand Matthelié

  Time flies and MySQL Connect is only 10 days away! You can check out the full program here as well as in the September edition of the MySQL newsletter. Mat recently blogged about the MySQL Cluster sessions you’ll have the opportunity to attend, and below are those focused on InnoDB. Remember you can plan your schedule with Schedule Builder. Saturday, 1.00 pm, Room Golden Gate 3: 10 Things You Should Know About InnoDB—Calvin Sun, Oracle InnoDB is the default storage engine for Oracle’s MySQL as of MySQL Release 5.5. It provides the standard ACID-compliant transactions, row-level locking, multiversion concurrency control, and referential integrity. InnoDB also implements several innovative technologies to improve its performance and reliability. This presentation gives a brief history of InnoDB; its main features; and some recent enhancements for better performance, scalability, and availability. Saturday, 5.30 pm, Room Golden Gate 4: Demystified MySQL/InnoDB Performance Tuning—Dimitri Kravtchuk, Oracle This session covers performance tuning with MySQL and the InnoDB storage engine for MySQL and explains the main improvements made in MySQL Release 5.5 and Release 5.6. Which setting for which workload? Which value will be better for my system? How can I avoid potential bottlenecks from the beginning? Do I need a purge thread? Is it true that InnoDB doesn't need thread concurrency anymore? These and many other questions are asked by DBAs and developers. Things are changing quickly and constantly, and there is no “silver bullet.” But understanding the configuration setting’s impact is already a huge step in performance improvement. Bring your ideas and problems to share them with others—the discussion is open, just moderated by a speaker. Sunday, 10.15 am, Room Golden Gate 4: Better Availability with InnoDB Online Operations—Calvin Sun, Oracle Many top Web properties rely on Oracle’s MySQL as a critical piece of infrastructure for serving millions of users. Database availability has become increasingly important. One way to enhance availability is to give users full access to the database during data definition language (DDL) operations. The online DDL operations in recent MySQL releases offer users the flexibility to perform schema changes while having full access to the database—that is, with minimal delay of operations on a table and without rebuilding the entire table. These enhancements provide better responsiveness and availability in busy production environments. This session covers these improvements in the InnoDB storage engine for MySQL for online DDL operations such as add index, drop foreign key, and rename column. Sunday, 11.45 am, Room Golden Gate 7: Developing High-Throughput Services with NoSQL APIs to InnoDB and MySQL Cluster—Andrew Morgan and John Duncan, Oracle Ever-increasing performance demands of Web-based services have generated significant interest in providing NoSQL access methods to MySQL (MySQL Cluster and the InnoDB storage engine of MySQL), enabling users to maintain all the advantages of their existing relational databases while providing blazing-fast performance for simple queries. Get the best of both worlds: persistence; consistency; rich SQL queries; high availability; scalability; and simple, flexible APIs and schemas for agile development. This session describes the memcached connectors and examines some use cases for how MySQL and memcached fit together in application architectures. It does the same for the newest MySQL Cluster native connector, an easy-to-use, fully asynchronous connector for Node.js. Sunday, 1.15 pm, Room Golden Gate 4: InnoDB Performance Tuning—Inaam Rana, Oracle The InnoDB storage engine has always been highly efficient and includes many unique architectural elements to ensure high performance and scalability. In MySQL 5.5 and MySQL 5.6, InnoDB includes many new features that take better advantage of recent advances in operating systems and hardware platforms than previous releases did. This session describes unique InnoDB architectural elements for performance, new features, and how to tune InnoDB to achieve better performance. Sunday, 4.15 pm, Room Golden Gate 3: InnoDB Compression for OLTP—Nizameddin Ordulu, Facebook and Inaam Rana, Oracle Data compression is an important capability of the InnoDB storage engine for Oracle’s MySQL. Compressed tables reduce the size of the database on disk, resulting in fewer reads and writes and better throughput by reducing the I/O workload. Facebook pushes the limit of InnoDB compression and has made several enhancements to InnoDB, making this technology ready for online transaction processing (OLTP). In this session, you will learn the fundamentals of InnoDB compression. You will also learn the enhancements the Facebook team has made to improve InnoDB compression, such as reducing compression failures, not logging compressed page images, and allowing changes of compression level. Not registered yet? You can still save US$ 300 over the on-site fee – Register Now!

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• C++ vs Matlab vs Python as a main language for Computer Vision Postgraduate

  - by Hough

  Hi all, Firstly, sorry for a somewhat long question but I think that many people are in the same situation as me and hopefully they can also gain some benefit from this. I'll be starting my PhD very soon which involve the fields of computer vision, pattern recognition and machine learning. Currently, I'm using opencv (2.1) C++ interface and I especially like its powerful Mat class and the overloaded operations available for matrix and image seamless operations and transformations. I've also tried (and implemented many small vision projects) using opencv python interface (new bindings; opencv 2.1) and I really enjoy python's ability to integrate opencv, numpy, scipy and matplotlib. But recently, I went back to opencv C++ interface because I felt that the official python new bindings were not stable enough and no overloaded operations are available for matrices and images, not to mention the lack of machine learning modules and slow speeds in certain operations. I've also used Matlab extensively in the past and although I've used mex files and other means to speed up the program, I just felt that Matlab's performance was inadequate for real-time vision tasks, be it for fast prototyping or not. When the project becomes larger and larger, many tasks have to be re-written in C and compiled into Mex files increasingly and Matlab becomes nothing more than a glue language. Here comes the sub-questions: For postgrad studies in these fields (machine learning, vision, pattern recognition), what is your main or ideal programming language for rapid prototyping of ideas and testing algorithms contained in papers? For postgrad studies, can you list down the pros and cons of using the following languages? C++ (with opencv + gsl + svmlib + other libraries) vs Matlab (with all its toolboxes) vs python (with the imcomplete opencv bindings + numpy + scipy + matplotlib). Are there computer vision PhD/postgrad students here who are using only C++ (with all its availabe libraries including opencv) without even needing to resort to Matlab or python? In other words, given the current existing computer vision or machine learning libraries, is C++ alone sufficient for fast prototyping of ideas? If you're currently using Java or C# for your postgrad work, can you list down the reasons why they should be used and how they compare to other languages in terms of available libraries? What is the de facto vision/machine learning programming language and its associated libraries used in your university research group? Thanks in advance.

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• AutoIt scripts runs without error but I can't see archive?

  - by Scott

  #include <File.au3> #include <Zip.au3> ; bad file extensions Local $extData="ade|adp|app|asa|ashx|asp|bas|bat|cdx|cer|chm|class|cmd|com|cpl|crt|csh|der|exe|fxp|gadget|hlp|hta|htr|htw|ida|idc|idq|ins|isp|its|jse|ksh|lnk|mad|maf|mag|mam|maq|mar|mas|mat|mau|mav|maw|mda|mdb|mde|mdt|mdw|mdz|msc|msh|msh1|msh1xml|msh2|msh2xml|mshxml|msi|msp|mst|ops|pcd|pif|prf|prg|printer|pst|reg|rem|scf|scr|sct|shb|shs|shtm|shtml|soap|stm|url|vb|vbe|vbs|ws|wsc|wsf|wsh" Local $extensions = StringSplit($extData, "|") ; What is the root directory? $rootDirectory = InputBox("Root Directory", "Please enter the root directory...") archiveDir($rootDirectory) Func archiveDir($dir) $goDirs = True $goFiles = True ; Get all the files under the current dir $allOfDir = _FileListToArray($dir) Local $countDirs = 0 Local $countFiles = 0 $imax = UBound($allOfDir) For $i = 0 to $imax - 1 If StringInStr(FileGetAttrib($dir & "\" & $allOfDir[$i]),"D") Then $countDirs = $countDirs + 1 ElseIf StringInStr(($allOfDir[$i]),".") Then $countFiles = $countFiles + 1 EndIf Next MsgBox(0, "Value of $countDirs in " & $dir, $countDirs) MsgBox(0, "Value of $countFiles in " & $dir, $countFiles) If ($countDirs > 0) Then Local $allDirs[$countDirs] $goDirs = True Else $goDirs = False EndIf If ($countFiles > 0) Then Local $allFiles[$countFiles] $goFiles = True Else $goFiles = False EndIf $dirCount = 0 $fileCount = 0 For $i = 0 to $imax - 1 If (StringInStr(FileGetAttrib($dir & "\" & $allOfDir[$i]),"D")) And ($goDirs == True) Then $allDirs[$dirCount] = $allOfDir[$i] $dirCount = $dirCount + 1 ElseIf (StringInStr(($allOfDir[$i]),".")) And ($goFiles == True) Then $allFiles[$fileCount] = $allOfDir[$i] $fileCount = $fileCount + 1 EndIf Next ; Zip them if need be in current spot using 'ext_zip.zip' as file name, loop through each file ext. If ($goFiles == True) Then $emax = UBound($extensions) $fmax = UBound($allFiles) For $e = 0 to $emax - 1 For $f = 0 to $fmax - 1 $currentExt = getExt($allFiles[$f]) If ($currentExt == $extensions[$e]) Then $zip = _Zip_Create($dir & "\" & $currentExt & "_zip.zip") _Zip_AddFile($zip, $allFiles[$f]) EndIf Next Next EndIf ; Get all dirs under current DirCopy ; For each dir, recursive call from step 2 If ($goDirs == True) Then $dmax = UBound($allDirs) $rootDirectory = $rootDirectory & "\" For $d = 0 to $dmax - 1 archiveDir($rootDirectory & $allDirs[$d]) Next EndIf EndFunc Func getExt($filename) $pos = StringInStr($filename, ".") $retval = StringTrimLeft($filename, $pos + 1) Return $retval EndFunc This should output the .zip archives in the directories it finds the files that it needs to zip but it doesn't. Is there something I have to do after I create and add files to the archive within the code to put this created archive in the directory?

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• AutoIt scripts runs without error but I can't see archive? - UPDATE

  - by Scott

  #include <File.au3> #include <Zip.au3> #include <Array.au3> ; bad file extensions Local $extData="ade|adp|app|asa|ashx|asp|bas|bat|cdx|cer|chm|class|cmd|com|cpl|crt|csh|der|exe|fxp|gadget|hlp|hta|htr|htw|ida|idc|idq|ins|isp|its|jse|ksh|lnk|mad|maf|mag|mam|maq|mar|mas|mat|mau|mav|maw|mda|mdb|mde|mdt|mdw|mdz|msc|msh|msh1|msh1xml|msh2|msh2xml|mshxml|msi|msp|mst|ops|pcd|pif|prf|prg|printer|pst|reg|rem|scf|scr|sct|shb|shs|shtm|shtml|soap|stm|url|vb|vbe|vbs|ws|wsc|wsf|wsh" Local $extensions = StringSplit($extData, "|") ; What is the root directory? $rootDirectory = InputBox("Root Directory", "Please enter the root directory...") archiveDir($rootDirectory) Func archiveDir($dir) $goDirs = True $goFiles = True ; Get all the files under the current dir $allOfDir = _FileListToArray($dir) $tmax = UBound($allOfDir) For $t = 0 to $tmax - 1 Next Local $countDirs = 0 Local $countFiles = 0 $imax = UBound($allOfDir) For $i = 0 to $imax - 1 If StringInStr(FileGetAttrib($dir & "\" & $allOfDir[$i]),"D") Then $countDirs = $countDirs + 1 ElseIf StringInStr(($allOfDir[$i]),".") Then $countFiles = $countFiles + 1 EndIf Next If ($countDirs > 0) Then Local $allDirs[$countDirs] $goDirs = True Else $goDirs = False EndIf If ($countFiles > 0) Then Local $allFiles[$countFiles] $goFiles = True Else $goFiles = False EndIf $dirCount = 0 $fileCount = 0 For $i = 0 to $imax - 1 If (StringInStr(FileGetAttrib($dir & "\" & $allOfDir[$i]),"D")) And ($goDirs == True) Then $allDirs[$dirCount] = $allOfDir[$i] $dirCount = $dirCount + 1 ElseIf (StringInStr(($allOfDir[$i]),".")) And ($goFiles == True) Then $allFiles[$fileCount] = $allOfDir[$i] $fileCount = $fileCount + 1 EndIf Next ; Zip them if need be in current spot using 'ext_zip.zip' as file name, loop through each file ext. If ($goFiles == True) Then $fmax = UBound($allFiles) For $f = 0 to $fmax - 1 $currentExt = getExt($allFiles[$f]) $position = _ArraySearch($extensions, $currentExt) If @error Then MsgBox(0, "Not Found", "Not Found") Else $zip = _Zip_Create($dir & "\" & $currentExt & "_zip.zip") _Zip_AddFile($zip, $dir & "\" & $allFiles[$f]) EndIf Next EndIf ; Get all dirs under current DirCopy ; For each dir, recursive call from step 2 If ($goDirs == True) Then $dmax = UBound($allDirs) $rootDirectory = $rootDirectory & "\" For $d = 0 to $dmax - 1 archiveDir($rootDirectory & $allDirs[$d]) Next EndIf EndFunc Func getExt($filename) $pos = StringInStr($filename, ".") $retval = StringTrimLeft($filename, $pos - 1) Return $retval EndFunc Updated, fixed a lot of bugs. Still not working. Like I said I have a list of 'bad' file extensions, this script should go through a directory of files (and subdirectories), and zip up (in separate zip files for each bad extension), all files WITH those bad extensions in the directories it finds them. What is wrong???

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• imagick showing script url instead of image

  - by Raz

  Hi, currently i'm trying to use imagick to generate some images without saving them on the server and then outputting to the browser, my method of choice was image magic with the imagick extension for php. I read the documentation, and i'm sure the package is installed on my machine (windows xp, with xampp). the class is installed imagick module enabled imagick module version 2.0.0-alpha imagick classes Imagick, ImagickDraw, ImagickPixel, ImagickPixelIterator ImageMagick version ImageMagick 6.3.3 04/21/07 Q16 http://www.imagemagick.org ImageMagick release date 04/21/07 ImageMagick Number of supported formats: 164 ImageMagick Supported formats A, ART, AVI, AVS, B, BIE, BMP, BMP2, BMP3, C, CACHE, CAPTION, CIN, CIP, CLIP, CLIPBOARD, CMYK, CMYKA, CUR, CUT, DCM, DCX, DFONT, DPS, DPX, EMF, EPDF, EPI, EPS, EPS2, EPS3, EPSF, EPSI, EPT, EPT2, EPT3, FAX, FITS, FRACTAL, FTS, G, G3, GIF, GIF87, GRADIENT, GRAY, HISTOGRAM, HTM, HTML, ICB, ICO, ICON, INFO, JBG, JBIG, JNG, JP2, JPC, JPEG, JPG, JPX, K, LABEL, M, M2V, MAP, MAT, MATTE, MIFF, MNG, MONO, MPC, MPEG, MPG, MSL, MSVG, MTV, MVG, NULL, O, OTB, OTF, PAL, PALM, PAM, PATTERN, PBM, PCD, PCDS, PCL, PCT, PCX, PDB, PDF, PFA, PFB, PGM, PGX, PICON, PICT, PIX, PJPEG, PLASMA, PNG, PNG24, PNG32, PNG8, PNM, PPM, PREVIEW, PS, PS2, PS3, PSD, PTIF, PWP, R, RAS, RGB, RGBA, RGBO, RLA, RLE, SCR, SCT, SFW, SGI, SHTML, STEGANO, SUN, SVG, SVGZ, TEXT, TGA, THUMBNAIL, TIFF, TILE, TIM, TTC, TTF, TXT, UIL, UYVY, VDA, VICAR, VID, VIFF, VST, WBMP, WMF, WMFWIN32, WMZ, WPG, X, XBM, XC, XCF, XPM, XV, XWD, Y, YCbCr, YCbCrA, YUV this is from the phpinfo so i know i have it installed, the thing is when i try to generate an image and save it, it works flawlessly, but when i try to output the image directly, i get the script url as an image $draw = new ImagickDraw(); $draw->setFont('AnkeCalligraph.TTF'); $draw->setFontSize(52); $draw->annotation(110, 110, "Hello World!"); $draw->annotation(50, 220, "Hello World!"); $canvas = new Imagick('./pictures/test_live.PNG'); $canvas->drawImage($draw); $canvas->setImageFormat('png'); header("Content-Type: image/png"); echo $canvas; this is the code used. if i use writeimage, then the file on the server is created with no problems. does anyone have any ideas what i'm doing wrong ?

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• C++ vs Matlab vs Python as a main language for Computer Vision Research

  - by Hough

  Hi all, Firstly, sorry for a somewhat long question but I think that many people are in the same situation as me and hopefully they can also gain some benefit from this. I'll be starting my PhD very soon which involves the fields of computer vision, pattern recognition and machine learning. Currently, I'm using opencv (2.1) C++ interface and I especially like its powerful Mat class and the overloaded operations available for matrix and image operations and seamless transformations. I've also tried (and implemented many small vision projects) using opencv python interface (new bindings; opencv 2.1) and I really enjoy python's ability to integrate opencv, numpy, scipy and matplotlib. But recently, I went back to opencv C++ interface because I felt that the official python new bindings were not stable enough and no overloaded operations are available for matrices and images, not to mention the lack of machine learning modules and slow speeds in certain operations. I've also used Matlab extensively in the past and although I've used mex files and other means to speed up the program, I just felt that Matlab's performance was inadequate for real-time vision tasks, be it for fast prototyping or not. When the project becomes larger and larger, many tasks have to be re-written in C and compiled into Mex files increasingly and Matlab becomes nothing more than a glue language. Here comes the sub-questions: For carrying out research in these fields (machine learning, vision, pattern recognition), what is your main or ideal programming language for rapid prototyping of ideas and testing algorithms contained in papers? For computer vision research work, can you list down the pros and cons of using the following languages? C++ (with opencv + gsl + svmlib + other libraries) vs Matlab (with all its toolboxes) vs python (with the imcomplete opencv bindings + numpy + scipy + matplotlib). Are there computer vision PhD/postgrad students here who are using only C++ (with all its availabe libraries including opencv) without even needing to resort to Matlab or python? In other words, given the current existing computer vision or machine learning libraries, is C++ alone sufficient for fast prototyping of ideas? If you're currently using Java or C# for your research, can you list down the reasons why they should be used and how they compare to other languages in terms of available libraries? What is the de facto vision/machine learning programming language and its associated libraries used in your research group? Thanks in advance. Edit: As suggested, I've opened the question to both academic and non-academic computer vision/machine learning/pattern recognition researchers and groups.

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• Prolog: Sentence Parser Problem

  - by Devon

  Hey guys, Been sat here for hours now just staring at this code and have no idea what I'm doing wrong. I know what's happening from tracing the code through (it is going on an eternal loop when it hits verbPhrase). Any tips are more then welcome. Thank you. % Knowledge-base det(the). det(a). adjective(quick). adjective(brown). adjective(orange). adjective(sweet). noun(cat). noun(mat). noun(fox). noun(cucumber). noun(saw). noun(mother). noun(father). noun(family). noun(depression). prep(on). prep(with). verb(sat). verb(nibbled). verb(ran). verb(looked). verb(is). verb(has). % Sentece Structures sentence(Phrase) :- append(NounPhrase, VerbPhrase, Phrase), nounPhrase(NounPhrase), verbPhrase(VerbPhrase). sentence(Phrase) :- verbPhrase(Phrase). nounPhrase([]). nounPhrase([Head | Tail]) :- det(Head), nounPhrase2(Tail). nounPhrase(Phrase) :- nounPhrase2(Phrase). nounPhrase(Phrase) :- append(NP, PP, Phrase), nounPhrase(NP), prepPhrase(PP). nounPhrase2([]). nounPhrase2(Word) :- noun(Word). nounPhrase2([Head | Tail]) :- adjective(Head), nounPhrase2(Tail). prepPhrase([]). prepPhrase([Head | Tail]) :- prep(Head), nounPhrase(Tail). verbPhrase([]). verbPhrase(Word) :- verb(Word). verbPhrase([Head | Tail]) :- verb(Head), nounPhrase(Tail). verbPhrase(Phrase) :- append(VP, PP, Phrase), verbPhrase(VP), prepPhrase(PP).

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• UpdatePanel Full Postback

  - by Korivo

  Greetings, here is the scenario. I have and .aspx page with and updatepanel like this <asp:UpdatePanel id="uPanelMain" runat="server"> <ContentTemplate> <uc:Calendar id="ucCalendar" runat="server" Visible="true" /> <uc:Scoring id="ucScoring" runat="server" Visible="false" /> </ContentTemplate> The control ucCalendar is loaded first and it contains a grid like this <asp:DataGrid CssClass="grid" ID="gridGames" runat="server" AutoGenerateColumns="False" HeaderStyle-CssClass="gridHeader" ItemStyle-CssClass="gridScoringRow" GridLines="None" ItemStyle-BackColor="#EEEEEE" AlternatingItemStyle-BackColor="#F5F5F5" OnEditCommand="doScoreGame" OnDeleteCommand="doEditGame" OnCancelCommand="printLineup" OnItemDataBound="gridDataBound"> <Columns> <asp:TemplateColumn > <ItemTemplate> <asp:CheckBox ID="chkDelete" runat="server" /> </ItemTemplate> </asp:TemplateColumn> <asp:BoundColumn DataField="idGame" Visible="false" /> <asp:BoundColumn DataField="isClose" Visible="false" /> <asp:TemplateColumn HeaderText="Status"> <ItemTemplate> <asp:Image ID="imgStatus" runat="server" ImageUrl="~/img/icoX.png" alt="icoStatus" /> </ItemTemplate> </asp:TemplateColumn> <asp:TemplateColumn> <ItemTemplate> <asp:LinkButton ID="linkScore" runat="server" CommandName="Edit" Text="Score" /> </ItemTemplate> </asp:TemplateColumn> </Columns> </asp:DataGrid> So when i click the "linkButton", the codebehind of the userControl calls a public method in the .aspx as this: From the userControl protected void doScoreGame(object sender, DataGridCommandEventArgs e) { ((GM)this.Page).showScoring(null, null); } From the .aspx page public void showScoring(object sender, EventArgs e) { removeLastLoadedControl(); ucScoring.Visible = true; } So, here comes the problem: There are two postbacks taking place when I change the visible attribute of the ucScoring control. The first postback is fine, it's handled by the updatePanel. The second postback is a full postback, and i really don't understand why it is happening. I'm really lost here, please help! Thanks Mat

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• SQLAuthority News – SQLPASS Nov 8-11, 2010-Seattle – An Alternative Look at Experience

  - by pinaldave

  I recently attended most prestigious SQL Server event SQLPASS between Nov 8-11, 2010 at Seattle. I have only one expression for the event - Best Summit Ever This year the summit was at its best. Instead of writing about my usual routine or the event, I am going to write about the interesting things I did and how I felt about it! Best Summit Ever Trip to Seattle! This was my second trip to Seattle this year and the journey is always long. Here is the travel stats on how long it takes to get to Seattle: 24 hours official air time 36 hours total travel time (connection waits and airport commute) Every time I travel to USA I gain a day and when I travel back to home, I lose a day. However, the total traveling time is around 3 days. The journey is long and very exhausting. However, it is all worth it when you’re attending an event like SQLPASS. Here are few things I carry when I travel for a long journey: Dry Snack packs – I like to have some good Indian Dry Snacks along with me in my backpack so I can have my own snack when I want Amazon Kindle – Loaded with 80+ books A physical book – This is usually a very easy to read book I do not watch movies on the plane and usually spend my time reading something quick and easy. If I can go to sleep, I go for it. I prefer to not to spend time in conversation with the guy sitting next to me because usually I end up listening to their biography, which I cannot blog about. Sheraton Seattle SQLPASS In any case, I love to go to Seattle as the city is great and has everything a brilliant metropolis has to offer. The new Light Train is extremely convenient, and I can take it directly from the airport to the city center. My hotel, the Sheraton, was only few meters (in the USA people count in blocks – 3 blocks) away from the train station. This time I saved USD 40 each round trip due to the Light Train. Sessions I attended! Well, I really wanted to attend most of the sessions but there was great dilemma of which ones to choose. There were many, many sessions to be attended and at any given time there was more than one good session being presented. I had decided to attend sessions in area performance tuning and I attended quite a few sessions this year, compared to what I was able to do last year. Here are few names of the speakers whose sessions I attended (please note, following great speakers are not listed in any order. I loved them and I enjoyed their sessions): Conor Cunningham Rushabh Mehta Buck Woody Brent Ozar Jonathan Kehayias Chris Leonard Bob Ward Grant Fritchey I had great fun attending their sessions. The sessions were meaningful and enlightening. It is hard to rate any session but I have found that the insights learned in Conor Cunningham’s sessions are the highlight of the PASS Summit. Rushabh Mehta at Keynote SQLPASS   Bucky Woody and Brent Ozar I always like the sessions where the speaker is much closer to the audience and has real world experience. I think speakers who have worked in the real world deliver the best content and most useful information. Sessions I did not like! Indeed there were few sessions I did not like it and I am not going to name them here. However, there were strong reasons I did not like their sessions, and here is why: Sessions were all theory and had no real world connections. All technical questions ended with confusing answers (lots of “I will get back to you on it,” “it depends,” “let us take this offline” and many more…) “I am God” kind of attitude in the speakers For example, I attended a session of one very well known speaker who is a specialist for one particular area. I was bit late for the session and was surprised to see that in a room that could hold 350 people there were only 30 attendees. After sitting there for 15 minutes, I realized why lots of people left. Very soon I found I preferred to stare out the window instead of listening to that particular speaker. One on One Talk! Many times people ask me what I really like about PASS. I always say the experience of meeting SQL legends and spending time with them one on one and LEARNING! Here is the quick list of the people I met during this event and spent more than 30 minutes with each of them talking about various subjects: Pinal Dave and Brad Shulz Pinal Dave and Rushabh Mehta Michael Coles and Pinal Dave Rushabh Mehta – It is always pleasure to meet with him. He is a man with lots of energy and a passion for community. He recently told me that he really wanted to turn PASS into resource for learning for every SQL Server Developer and Administrator in the world. I had great in-depth discussion regarding how a single person can contribute to a community. Michael Coles – I consider him my best friend. It is always fun to meet him. He is funny and very knowledgeable. I think there are very few people who are as expert as he is in encryption and spatial databases. Worth meeting him every single time. Glenn Berry – A real friend of everybody. He is very a simple person and very true to his heart. I think there is not a single person in whole community who does not like him. He is a friends of all and everybody likes him very much. I once again had time to sit with him and learn so much from him. As he is known as Dr. DMV, I can be his nurse in the area of DMV. Brad Schulz – I always wanted to meet him but never got chance until today. I had great time meeting him in person and we have spent considerable amount of time together discussing various T-SQL tricks and tips. I do not know where he comes up with all the different ideas but I enjoy reading his blog and sharing his wisdom with me. Jonathan Kehayias – He is drill sergeant in US army. If you get the impression that he is a giant with very strong personality – you are wrong. He is very kind and soft spoken DBA with strong performance tuning skills. I asked him how he has kept his two jobs separate and I got very good answer – just work hard and have passion for what you do. I attended his sessions and his presentation style is very unique.  I feel like he is speaking in a language I understand. Louis Davidson – I had never had a chance to sit with him and talk about technology before. He has so much wisdom and he is very kind. During the dinner, I had talked with him for long time and without hesitation he started to draw a schema for me on the menu. It was a wonderful experience to learn from a master at the dinner table. He explained to me the real and practical differences between third normal form and forth normal form. Honestly I did not know earlier, but now I do. Erland Sommarskog – This man needs no introduction, he is very well known and very clear in conveying his ideas. I learned a lot from him during the course of year. Every time I meet him, I learn something new and this time was no exception. Joe Webb – Joey is all about community and people, we had interesting conversation about community, MVP and how one can be helpful to community without losing passion for long time. It is always pleasant to talk to him and of course, I had fun time. Ross Mistry – I call him my brother many times because he indeed looks like my cousin. He provided me lots of insight of how one can write book and how he keeps his books simple to appeal to all the readers. A wonderful person and great friend. Ola Hallgren - I did not know he was coming to the summit. I had great time meeting him and had a wonderful conversation with him regarding his scripts and future community activities. Blythe Morrow – She used to be integrated part of SQL Server Community and PASS HQ. It was wonderful to meet her again and re-connect. She is wonderful person and I had a great time talking to her. Solid Quality Mentors – It is difficult to decide who to mention here. Instead of writing all the names, I am going to include a photo of our meeting. I had great fun meeting various members of our global branches. This year I was sitting with my Spanish speaking friends and had great fun as Javier Loria from Solid Quality translated lots of things for me. Party, Party and Parties Every evening there were various parties. I did attend almost all of them. Every party had different theme but the goal of all the parties the same – networking. Here are the few parties where I had lots of fun: Dell Reception Party Exhibitor Party Solid Quality Fun Party Red Gate Friends Party MVP Dinner Microsoft Party MVP Dinner Quest Party Gameworks PASS Party Volunteer Party at Garage Solid Quality Mentors (10 Members out of 120) They were all great networking opportunities and lots of fun. I really had great time meeting people at the various parties. There were few people everywhere – well, I will say I am among them – who hopped parties. NDA – Not Decided Agenda During the event there were few meetings marked “NDA.” Someone asked me “why are these things NDA?”  My response was simple: because they are not sure themselves. NDA stands for Not Decided Agenda. Toys, Giveaways and Luggage I admit, I was like child in Gameworks and was playing to win soft toys. I was doing it for my daughter. I must thank all of the people who gave me their cards to try my luck. I won 4 soft-toys for my daughter and it was fun. Also, thanks to Angel who did a final toy swap with me to get the desired toy for my daughter. I also collected ducks from Idera, as my daughter really loves them. Solid Quality Booth Each of the exhibitors was giving away something and I got so much stuff that my luggage got quite a bit bigger when I returned. Best Exhibitor Idera had SQLDoctor (a real magician and fun guy) to promote their new tool SQLDoctor. I really had a great time participating in the magic myself. At one point, the magician made my watch disappear.  I have seen better magic before, but this time it caught me unexpectedly and I was taken by surprise. I won many ducks again. The Common Question I heard the following common questions: I have seen you somewhere – who are you? – I am Pinal Dave. I did not know that Pinal is your first name and Dave is your last name, how do you pronounce your last name again? – Da-way How old are you? – I am as old as I can be. Are you an Indian because you look like one? – I did not answer this one. Where are you from? This question was usually asked after looking at my badge which says India. So did you really fly from India? – Yes, because I have seasickness so I do not prefer the sea journey. How long was the journey? – 24/36/12 (air travel time/total travel time/time zone difference) Why do you write on SQLAuthority.com? – Because I want to. I remember your daughter looks like you. – Is this even a question? Of course, she is daddy’s little girl. There were so many other questions, I will have to write another blog post about it. SQLPASS Again, Best Summit Ever! Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: About Me, Pinal Dave, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, T SQL, Technology Tagged: SQLPASS

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• The Changing Face of PASS

  - by Bill Graziano

  I’m starting my sixth year on the PASS Board.  I served two years as the Program Director, two years as the Vice-President of Marketing and I’m starting my second year as the Executive Vice-President of Finance.  There’s a pretty good chance that if PASS has done something you don’t like or is doing something you don’t like, that I’m involved in one way or another. Andy Leonard asked in a comment on his blog if the Board had ever reversed itself based on community input.  He asserted that it hadn’t.  I disagree.  I’m not going to try and list all the changes we make inside portfolios based on feedback from and meetings with the community.  I’m going to focus on major governance issues since I was elected to the Board. Management Company The first big change was our management company.  Our old management company had a standard approach to running a non-profit.  It worked well when PASS was launched.  Having a ready-made structure and process to run the organization enabled the organization to grow quickly.  As time went on we were limited in some of the things we wanted to do.  The more involved you were with PASS, the more you saw these limitations.  Key volunteers were regularly providing feedback that they wanted certain changes that were difficult for us to accomplish.  The Board at that time wanted changes that were difficult or impossible to accomplish under that structure. This was not a simple change.  Imagine a $2.5 million dollar company letting all its employees go on a Friday and starting with a new staff on Monday.  We also had a very narrow window to accomplish that so that we wouldn’t affect the Summit – our only source of revenue.  We spent the year after the change rebuilding processes and putting on the Summit in Denver.  That’s a concrete example of a huge change that PASS made to better serve its members.  And it was a change that many in the community were telling us we needed to make. Financials We heard regularly from our members that they wanted our financials posted.  Today on our web site you can find audited financials going back to 2004.  We publish our budget at the start of each year.  If you ask a question about the financials on the PASS site I do my best to answer it.  I’m also trying to do a better job answering financial questions posted in other locations.  (And yes, I know I owe a few of you some blog posts.) That’s another concrete example of a change that our members asked for that the Board agreed was a good decision. Minutes When I started on the Board the meeting minutes were very limited.  The minutes from a two day Board meeting might fit on one page.  I think we did the bare minimum we were legally required to do.  Today Board meeting minutes run from 5 to 12 pages and go into incredible detail on what we talk about.  There are certain topics that are NDA but where possible we try to list the topic we discussed but that the actual discussion was under NDA.  We also publish the agenda of Board meetings ahead of time. This is another specific example where input from the community influenced the decision.  It was certainly easier to have limited minutes but I think the extra effort helps our members understand what’s going on. Board Q&A At the 2009 Summit the Board held its first public Q&A with our members.  We’d always been available individually to answer questions.  There’s a benefit to getting us all in one room and asking the really hard questions to watch us squirm.  We learn what questions we don’t have good answers for.  We get to see how many people in the crowd look interested in the various questions and answers. I don’t recall the genesis of how this came about.  I’m fairly certain there was some community pressure though. Board Votes Until last November, the Board only reported the vote totals and not how individual Board members voted.  That was one of the topics at a great lunch I had with Tim Mitchell and Kendal van Dyke at the Summit.  That was also the topic of the first question asked at the Board Q&A by Kendal.  Kendal expressed his opposition to to anonymous votes clearly and passionately and without trying to paint anyone into a corner.  Less than 24 hours later the PASS Board voted to make individual votes public unless the topic was under NDA.  That’s another area where the Board decided to change based on feedback from our members. Summit Location While this isn’t actually a governance issue it is one of the more public decisions we make that has taken some public criticism.  There is a significant portion of our members that want the Summit near them.  There is a significant portion of our members that like the Summit in Seattle.  There is a significant portion of our members that think it should move around the country.  I was one that felt strongly that there were significant, tangible benefits to our attendees to being in Seattle every year.  I’m also one that has been swayed by some very compelling arguments that we need to have at least one outside Seattle and then revisit the decision.  I can’t tell you how the Board will vote but I know the opinion of our members weighs heavily on the decision. Elections And that brings us to the grand-daddy of all governance issues.  My thesis for this blog post is that the PASS Board has implemented policy changes in response to member feedback.  It isn’t to defend or criticize our election process.  It’s just to say that is has been under going continuous change since I’ve been on the Board.  I ran for the Board in the fall of 2005.  I don’t know much about what happened before then.  I was actively volunteering for PASS for four years prior to that as a chapter leader and on the program committee.  I don’t recall any complaints about elections but that doesn’t mean they didn’t occur.  The questions from the Nominating Committee (NomCom) were trivial and the selection process rudimentary (For example, “Tell us about your accomplishments”).  I don’t even remember who I ran against or how many other people ran.  I ran for the VP of Marketing in the fall of 2007.  I don’t recall any significant changes the Board made in the election process for that election.  I think a lot of the changes in 2007 came from us asking the management company to work on the election process.  I was expecting a similar set of puff ball questions from my previous election.  Boy, was I in for a shock.  The NomCom had found a much better set of questions and really made the interview portion difficult.  The questions were much more behavioral in nature.  I’d already written about my vision for PASS and my goals.  They wanted to know how I handled adversity, how I handled criticism, how I handled conflict, how I handled troublesome volunteers, how I motivated people and how I responded to motivation. And many, many other things. They grilled me for over an hour.  I’ve done a fair bit of technical sales in my time.  I feel I speak well under pressure addressing pointed questions.  This interview intentionally put me under pressure.  In addition to wanting to know about my interpersonal skills, my work experience, my volunteer experience and my supervisory experience they wanted to see how I’d do under pressure.  They wanted to see who would respond under pressure and who wouldn’t.  It was a bit of a shock. That was the first big change I remember in the election process.  I know there were other improvements around the process but none of them stick in my mind quite like the unexpected hour-long grilling. The next big change I remember was after the 2009 elections.  Andy Warren was unhappy with the election process and wanted to make some changes.  He worked with Hannes at HQ and they came up with a better set of processes.  I think Andy moved PASS in the right direction.  Nonetheless, after the 2010 election even more people were very publicly clamoring for changes to our election process.  In August of 2010 we had a choice to make.  There were numerous bloggers criticizing the Board and our upcoming election.  The easy change would be to announce that we were changing the process in a way that would satisfy our critics.  I believe that a knee-jerk response to criticism is seldom correct. Instead the Board spent August and September and October and November listening to the community.  I visited two SQLSaturdays and asked questions of everyone I could.  I attended chapter meetings and asked questions of as many people as they’d let me.  At Summit I made it a point to introduce myself to strangers and ask them about the election.  At every breakfast I’d sit down at a table full of strangers and ask about the election.  I’m happy to say that I left most tables arguing about the election.  Most days I managed to get 2 or 3 breakfasts in. I spent less time talking to people that had already written about the election.  They were already expressing their opinion.  I wanted to talk to people that hadn’t spoken up.  I wanted to know what the silent majority thought.  The Board all attended the Q&A session where our members expressed their concerns about a variety of issues including the election. The PASS Board also chose to create the Election Review Committee.  We wanted people from the community that had been involved with PASS to look at our election process with fresh eyes while listening to what the community had to say and give us some advice on how we could improve the process.  I’m a part of this as is Andy Warren.  None of the other members are on the Board.  I’ve sat in numerous calls and interviews with this group and attended an open meeting at the Summit.  We asked anyone that wanted to discuss the election to come speak with us.  The ERC held an open meeting at the Summit and invited anyone to attend.  There are forums on the ERC web site where we’ve invited people to participate.  The ERC has reached to key people involved in recent elections.  The years that I haven’t mentioned also saw minor improvements in the election process.  Off the top of my head I don’t recall what exact changes were made each year.  Specifically since the 2010 election we’ve gone out of our way to seek input from the community about the process.  I’m not sure what more we could have done to invite feedback from the community. I think to say that we haven’t “fixed” the election process isn’t a fair criticism at this time.  We haven’t rushed any changes through the process.  If you don’t see any changes in our election process in July or August then I think it’s fair to criticize us for ignoring the community or ask for an explanation for what we’ve done. In Summary Andy’s main point was that the PASS Board hasn’t changed in response to our members wishes.  I think I’ve shown that time and time again the PASS Board has changed in response to what our members want.  There are only two outstanding issues: Summit location and elections.  The 2013 Summit location hasn’t been decided yet.  Our work on the elections is also in progress.  And at every step in the election review we’ve gone out of our way to listen to the community and incorporate their feedback on the process. I also hope I’m not encouraging everyone that wants some change in the organization to organize a “blog rush” against the Board.  We take public suggestions very seriously but we also take the time to evaluate those suggestions and learn what the rest of our members think and make a measured decision.

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• I am getting error when using Attributes in Rcpp and have RcppArmadillo code

  - by howard123

  I am trying to create a package with RcppArmadillo. The code uses the new attributes methodology of Rcpp. The sourceCpp works fine and compiles the code, but when I build a package I get errors when I use RcppArmadillo code. Without the RcppArmadillo code and using regulare C++, I do not get these errors. The C++ code (it is essentially the fastLm sample code) is: // [[Rcpp::depends(RcppArmadillo)]] #include <Rcpp.h> #include <RcppArmadillo.h> using namespace Rcpp; // [[Rcpp::depends(RcppArmadillo)]] #include <RcppArmadillo.h> // [[Rcpp::export]] List fastLm(NumericVector yr, NumericMatrix Xr) { int n = Xr.nrow(), k = Xr.ncol(); arma::mat X(Xr.begin(), n, k, false); arma::colvec y(yr.begin(), yr.size(), false); arma::colvec coef = arma::solve(X, y); arma::colvec resid = y - X*coef; double sig2 = arma::as_scalar(arma::trans(resid)*resid/(n-k)); arma::colvec stderrest = arma::sqrt( sig2 * arma::diagvec( arma::inv(arma::trans(X)*X)) ); return List::create(Named("coefficients") = coef, Named("stderr") = stderrest); } Here is the compilation error, after I execute "R Rcpp::compileAttributes() * Updated src/RcppExports.cpp == Rcmd.exe INSTALL --no-multiarch NewPackage * installing to library 'C:/Users/Howard/Documents/R/win-library/2.15' * installing *source* package 'NewPackage' ... ** libs g++ -m64 -I"C:/R/R-2-15-2/include" -DNDEBUG -I"C:/Users/Howard/Documents/R/win-library/2.15/Rcpp/include" -I"C:/Users/Howard/Documents/R/win-library/2.15/RcppArmadillo/include" -I"d:/RCompile/CRANpkg/extralibs64/local/include" -O2 -Wall -mtune=core2 -c RcppExports.cpp -o RcppExports.o g++ -m64 -I"C:/R/R-2-15-2/include" -DNDEBUG -I"C:/Users/Howard/Documents/R/win-library/2.15/Rcpp/include" -I"C:/Users/Howard/Documents/R/win-library/2.15/RcppArmadillo/include" -I"d:/RCompile/CRANpkg/extralibs64/local/include" -O2 -Wall -mtune=core2 -c test_arma3.cpp -o test_arma3.o g++ -m64 -shared -s -static-libgcc -o NewPackage.dll tmp.def RcppExports.o test_arma3.o C:/Users/Howard/Documents/R/win-library/2.15/Rcpp/lib/x64/libRcpp.a -Ld:/RCompile/CRANpkg/extralibs64/local/lib/x64 -Ld:/RCompile/CRANpkg/extralibs64/local/lib -LC:/R/R-2-15-2/bin/x64 -lR test_arma3.o:test_arma3.cpp:(.text+0xae4): undefined reference to `dgemm_' test_arma3.o:test_arma3.cpp:(.text+0x19db): undefined reference to `dgemm_' test_arma3.o:test_arma3.cpp:(.text+0x1b0c): undefined reference to `dgemv_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma6auxlib8solve_odIdNS_3MatIdEEEEbRNS2_IT_EES6_RKNS_4BaseIS4_T0_EE[_ZN4arma6auxlib8solve_odIdNS_3MatIdEEEEbRNS2_IT_EES6_RKNS_4BaseIS4_T0_EE]+0x702): undefined reference to `dgels_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma6auxlib8solve_udIdNS_3MatIdEEEEbRNS2_IT_EES6_RKNS_4BaseIS4_T0_EE[_ZN4arma6auxlib8solve_udIdNS_3MatIdEEEEbRNS2_IT_EES6_RKNS_4BaseIS4_T0_EE]+0x51c): undefined reference to `dgels_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma6auxlib10det_lapackIdEET_RKNS_3MatIS2_EEb[_ZN4arma6auxlib10det_lapackIdEET_RKNS_3MatIS2_EEb]+0x14b): undefined reference to `dgetrf_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma6auxlib5solveIdNS_3MatIdEEEEbRNS2_IT_EES6_RKNS_4BaseIS4_T0_EEb[_ZN4arma6auxlib5solveIdNS_3MatIdEEEEbRNS2_IT_EES6_RKNS_4BaseIS4_T0_EEb]+0x375): undefined reference to `dgesv_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma4gemvILb1ELb0ELb0EE15apply_blas_typeIdEEvPT_RKNS_3MatIS3_EEPKS3_S3_S3_[_ZN4arma4gemvILb1ELb0ELb0EE15apply_blas_typeIdEEvPT_RKNS_3MatIS3_EEPKS3_S3_S3_]+0x17d): undefined reference to `dgemv_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma27glue_times_redirect2_helperILb1EE5applyINS_2OpINS_3MatIdEENS_9op_htransEEES5_EEvRNS4_INT_9elem_typeEEERKNS_4GlueIS8_T0_NS_10glue_timesEEE[_ZN4arma27glue_times_redirect2_helperILb1EE5applyINS_2OpINS_3MatIdEENS_9op_htransEEES5_EEvRNS4_INT_9elem_typeEEERKNS_4GlueIS8_T0_NS_10glue_timesEEE]+0x37a): undefined reference to `dgemm_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE[_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE]+0x2c1): undefined reference to `dgetrf_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE[_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE]+0x322): undefined reference to `dgetri_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE[_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE]+0x398): undefined reference to `dgetri_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE[_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE]+0x775): undefined reference to `dgetrf_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE[_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE]+0x7d6): undefined reference to `dgetri_' test_arma3.o:test_arma3.cpp:(.text$_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE[_ZN4arma10op_diagvec5applyINS_2OpINS_4GlueINS2_INS_3MatIdEENS_9op_htransEEES5_NS_10glue_timesEEENS_6op_invEEEEEvRNS4_INT_9elem_typeEEERKNS2_ISC_S0_EE]+0x892): undefined reference to `dgetri_' collect2: ld returned 1 exit status ERROR: compilation failed for package 'NewPackage' * removing 'C:/Users/Howard/Documents/R/win-library/2.15/NewPackage' * restoring previous 'C:/Users/Howard/Documents/R/win-library/2.15/NewPackage' Exited with status 1.

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• image processing algorithm in MATLAB

  - by user261002

  I am trying to reconstruct an algorithm belong to this paper: Decomposition of biospeckle images in temporary spectral bands Here is an explanation of the algorithm: We recorded a sequence of N successive speckle images with a sampling frequency fs. In this way it was possible to observe how a pixel evolves through the N images. That evolution can be treated as a time series and can be processed in the following way: Each signal corresponding to the evolution of every pixel was used as input to a bank of filters. The intensity values were previously divided by their temporal mean value to minimize local differences in reflectivity or illumination of the object. The maximum frequency that can be adequately analyzed is determined by the sampling theorem and s half of sampling frequency fs. The latter is set by the CCD camera, the size of the image, and the frame grabber. The bank of filters is outlined in Fig. 1. In our case, ten 5° order Butterworth11 filters were used, but this number can be varied according to the required discrimination. The bank was implemented in a computer using MATLAB software. We chose the Butter-worth filter because, in addition to its simplicity, it is maximally flat. Other filters, an infinite impulse response, or a finite impulse response could be used. By means of this bank of filters, ten corresponding signals of each filter of each temporary pixel evolution were obtained as output. Average energy Eb in each signal was then calculated: where pb(n) is the intensity of the filtered pixel in the nth image for filter b divided by its mean value and N is the total number of images. In this way, en values of energy for each pixel were obtained, each of hem belonging to one of the frequency bands in Fig. 1. With these values it is possible to build ten images of the active object, each one of which shows how much energy of time-varying speckle there is in a certain frequency band. False color assignment to the gray levels in the results would help in discrimination. and here is my MATLAB code base on that : clear all for i=0:39 str = num2str(i); str1 = strcat(str,'.mat'); load(str1); D{i+1}=A; end new_max = max(max(A)); new_min = min(min(A)); for i=20:180 for j=20:140 ts = []; for k=1:40 ts = [ts D{k}(i,j)]; %%% kth image pixel i,j --- ts is time series end ts = double(ts); temp = mean(ts); ts = ts-temp; ts = ts/temp; N = 5; % filter order W = [0.00001 0.05;0.05 0.1;0.1 0.15;0.15 0.20;0.20 0.25;0.25 0.30;0.30 0.35;0.35 0.40;0.40 0.45;0.45 0.50]; N1 = 5; for ind = 1:10 Wn = W(ind,:); [B,A] = butter(N1,Wn); ts_f(ind,:) = filter(B,A,ts); end for ind=1:10 imag_test1{ind}(i,j) =sum((ts_f(ind,:)./mean(ts_f(ind,:))).^2); end end end for i=1:10 temp_imag = imag_test1{i}(:,:); x=isnan(temp_imag); temp_imag(x)=0; temp_imag=medfilt2(temp_imag); t_max = max(max(temp_imag)); t_min = min(min(temp_imag)); temp_imag = (temp_imag-t_min).*(double(new_max-new_min)/double(t_max-t_min))+double(new_min); imag_test2{i}(:,:) = temp_imag; end for i=1:10 A=imag_test2{i}(:,:); B=A/max(max(A)); B=histeq(B); figure,imshow(B) colorbar end but I am not getting the same result as paper. has anybody has aby idea why? or where I have gone wrong? Refrence Link to the paper

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• A Taxonomy of Numerical Methods v1

  - by JoshReuben

  Numerical Analysis – When, What, (but not how) Once you understand the Math & know C++, Numerical Methods are basically blocks of iterative & conditional math code. I found the real trick was seeing the forest for the trees – knowing which method to use for which situation. Its pretty easy to get lost in the details – so I’ve tried to organize these methods in a way that I can quickly look this up. I’ve included links to detailed explanations and to C++ code examples. I’ve tried to classify Numerical methods in the following broad categories: Solving Systems of Linear Equations Solving Non-Linear Equations Iteratively Interpolation Curve Fitting Optimization Numerical Differentiation & Integration Solving ODEs Boundary Problems Solving EigenValue problems Enjoy – I did ! Solving Systems of Linear Equations Overview Solve sets of algebraic equations with x unknowns The set is commonly in matrix form Gauss-Jordan Elimination http://en.wikipedia.org/wiki/Gauss%E2%80%93Jordan_elimination C++: http://www.codekeep.net/snippets/623f1923-e03c-4636-8c92-c9dc7aa0d3c0.aspx Produces solution of the equations & the coefficient matrix Efficient, stable 2 steps: · Forward Elimination – matrix decomposition: reduce set to triangular form (0s below the diagonal) or row echelon form. If degenerate, then there is no solution · Backward Elimination –write the original matrix as the product of ints inverse matrix & its reduced row-echelon matrix à reduce set to row canonical form & use back-substitution to find the solution to the set Elementary ops for matrix decomposition: · Row multiplication · Row switching · Add multiples of rows to other rows Use pivoting to ensure rows are ordered for achieving triangular form LU Decomposition http://en.wikipedia.org/wiki/LU_decomposition C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-lu-decomposition-for-solving.html Represent the matrix as a product of lower & upper triangular matrices A modified version of GJ Elimination Advantage – can easily apply forward & backward elimination to solve triangular matrices Techniques: · Doolittle Method – sets the L matrix diagonal to unity · Crout Method - sets the U matrix diagonal to unity Note: both the L & U matrices share the same unity diagonal & can be stored compactly in the same matrix Gauss-Seidel Iteration http://en.wikipedia.org/wiki/Gauss%E2%80%93Seidel_method C++: http://www.nr.com/forum/showthread.php?t=722 Transform the linear set of equations into a single equation & then use numerical integration (as integration formulas have Sums, it is implemented iteratively). an optimization of Gauss-Jacobi: 1.5 times faster, requires 0.25 iterations to achieve the same tolerance Solving Non-Linear Equations Iteratively find roots of polynomials – there may be 0, 1 or n solutions for an n order polynomial use iterative techniques Iterative methods · used when there are no known analytical techniques · Requires set functions to be continuous & differentiable · Requires an initial seed value – choice is critical to convergence à conduct multiple runs with different starting points & then select best result · Systematic - iterate until diminishing returns, tolerance or max iteration conditions are met · bracketing techniques will always yield convergent solutions, non-bracketing methods may fail to converge Incremental method if a nonlinear function has opposite signs at 2 ends of a small interval x1 & x2, then there is likely to be a solution in their interval – solutions are detected by evaluating a function over interval steps, for a change in sign, adjusting the step size dynamically. Limitations – can miss closely spaced solutions in large intervals, cannot detect degenerate (coinciding) solutions, limited to functions that cross the x-axis, gives false positives for singularities Fixed point method http://en.wikipedia.org/wiki/Fixed-point_iteration C++: http://books.google.co.il/books?id=weYj75E_t6MC&pg=PA79&lpg=PA79&dq=fixed+point+method++c%2B%2B&source=bl&ots=LQ-5P_taoC&sig=lENUUIYBK53tZtTwNfHLy5PEWDk&hl=en&sa=X&ei=wezDUPW1J5DptQaMsIHQCw&redir_esc=y#v=onepage&q=fixed%20point%20method%20%20c%2B%2B&f=false Algebraically rearrange a solution to isolate a variable then apply incremental method Bisection method http://en.wikipedia.org/wiki/Bisection_method C++: http://numericalcomputing.wordpress.com/category/algorithms/ Bracketed - Select an initial interval, keep bisecting it ad midpoint into sub-intervals and then apply incremental method on smaller & smaller intervals – zoom in Adv: unaffected by function gradient à reliable Disadv: slow convergence False Position Method http://en.wikipedia.org/wiki/False_position_method C++: http://www.dreamincode.net/forums/topic/126100-bisection-and-false-position-methods/ Bracketed - Select an initial interval , & use the relative value of function at interval end points to select next sub-intervals (estimate how far between the end points the solution might be & subdivide based on this) Newton-Raphson method http://en.wikipedia.org/wiki/Newton's_method C++: http://www-users.cselabs.umn.edu/classes/Summer-2012/csci1113/index.php?page=./newt3 Also known as Newton's method Convenient, efficient Not bracketed – only a single initial guess is required to start iteration – requires an analytical expression for the first derivative of the function as input. Evaluates the function & its derivative at each step. Can be extended to the Newton MutiRoot method for solving multiple roots Can be easily applied to an of n-coupled set of non-linear equations – conduct a Taylor Series expansion of a function, dropping terms of order n, rewrite as a Jacobian matrix of PDs & convert to simultaneous linear equations !!! Secant Method http://en.wikipedia.org/wiki/Secant_method C++: http://forum.vcoderz.com/showthread.php?p=205230 Unlike N-R, can estimate first derivative from an initial interval (does not require root to be bracketed) instead of inputting it Since derivative is approximated, may converge slower. Is fast in practice as it does not have to evaluate the derivative at each step. Similar implementation to False Positive method Birge-Vieta Method http://mat.iitm.ac.in/home/sryedida/public_html/caimna/transcendental/polynomial%20methods/bv%20method.html C++: http://books.google.co.il/books?id=cL1boM2uyQwC&pg=SA3-PA51&lpg=SA3-PA51&dq=Birge-Vieta+Method+c%2B%2B&source=bl&ots=QZmnDTK3rC&sig=BPNcHHbpR_DKVoZXrLi4nVXD-gg&hl=en&sa=X&ei=R-_DUK2iNIjzsgbE5ID4Dg&redir_esc=y#v=onepage&q=Birge-Vieta%20Method%20c%2B%2B&f=false combines Horner's method of polynomial evaluation (transforming into lesser degree polynomials that are more computationally efficient to process) with Newton-Raphson to provide a computational speed-up Interpolation Overview Construct new data points for as close as possible fit within range of a discrete set of known points (that were obtained via sampling, experimentation) Use Taylor Series Expansion of a function f(x) around a specific value for x Linear Interpolation http://en.wikipedia.org/wiki/Linear_interpolation C++: http://www.hamaluik.com/?p=289 Straight line between 2 points à concatenate interpolants between each pair of data points Bilinear Interpolation http://en.wikipedia.org/wiki/Bilinear_interpolation C++: http://supercomputingblog.com/graphics/coding-bilinear-interpolation/2/ Extension of the linear function for interpolating functions of 2 variables – perform linear interpolation first in 1 direction, then in another. Used in image processing – e.g. texture mapping filter. Uses 4 vertices to interpolate a value within a unit cell. Lagrange Interpolation http://en.wikipedia.org/wiki/Lagrange_polynomial C++: http://www.codecogs.com/code/maths/approximation/interpolation/lagrange.php For polynomials Requires recomputation for all terms for each distinct x value – can only be applied for small number of nodes Numerically unstable Barycentric Interpolation http://epubs.siam.org/doi/pdf/10.1137/S0036144502417715 C++: http://www.gamedev.net/topic/621445-barycentric-coordinates-c-code-check/ Rearrange the terms in the equation of the Legrange interpolation by defining weight functions that are independent of the interpolated value of x Newton Divided Difference Interpolation http://en.wikipedia.org/wiki/Newton_polynomial C++: http://jee-appy.blogspot.co.il/2011/12/newton-divided-difference-interpolation.html Hermite Divided Differences: Interpolation polynomial approximation for a given set of data points in the NR form - divided differences are used to approximately calculate the various differences. For a given set of 3 data points , fit a quadratic interpolant through the data Bracketed functions allow Newton divided differences to be calculated recursively Difference table Cubic Spline Interpolation http://en.wikipedia.org/wiki/Spline_interpolation C++: https://www.marcusbannerman.co.uk/index.php/home/latestarticles/42-articles/96-cubic-spline-class.html Spline is a piecewise polynomial Provides smoothness – for interpolations with significantly varying data Use weighted coefficients to bend the function to be smooth & its 1st & 2nd derivatives are continuous through the edge points in the interval Curve Fitting A generalization of interpolating whereby given data points may contain noise à the curve does not necessarily pass through all the points Least Squares Fit http://en.wikipedia.org/wiki/Least_squares C++: http://www.ccas.ru/mmes/educat/lab04k/02/least-squares.c Residual – difference between observed value & expected value Model function is often chosen as a linear combination of the specified functions Determines: A) The model instance in which the sum of squared residuals has the least value B) param values for which model best fits data Straight Line Fit Linear correlation between independent variable and dependent variable Linear Regression http://en.wikipedia.org/wiki/Linear_regression C++: http://www.oocities.org/david_swaim/cpp/linregc.htm Special case of statistically exact extrapolation Leverage least squares Given a basis function, the sum of the residuals is determined and the corresponding gradient equation is expressed as a set of normal linear equations in matrix form that can be solved (e.g. using LU Decomposition) Can be weighted - Drop the assumption that all errors have the same significance –-> confidence of accuracy is different for each data point. Fit the function closer to points with higher weights Polynomial Fit - use a polynomial basis function Moving Average http://en.wikipedia.org/wiki/Moving_average C++: http://www.codeproject.com/Articles/17860/A-Simple-Moving-Average-Algorithm Used for smoothing (cancel fluctuations to highlight longer-term trends & cycles), time series data analysis, signal processing filters Replace each data point with average of neighbors. Can be simple (SMA), weighted (WMA), exponential (EMA). Lags behind latest data points – extra weight can be given to more recent data points. Weights can decrease arithmetically or exponentially according to distance from point. Parameters: smoothing factor, period, weight basis Optimization Overview Given function with multiple variables, find Min (or max by minimizing –f(x)) Iterative approach Efficient, but not necessarily reliable Conditions: noisy data, constraints, non-linear models Detection via sign of first derivative - Derivative of saddle points will be 0 Local minima Bisection method Similar method for finding a root for a non-linear equation Start with an interval that contains a minimum Golden Search method http://en.wikipedia.org/wiki/Golden_section_search C++: http://www.codecogs.com/code/maths/optimization/golden.php Bisect intervals according to golden ratio 0.618.. Achieves reduction by evaluating a single function instead of 2 Newton-Raphson Method Brent method http://en.wikipedia.org/wiki/Brent's_method C++: http://people.sc.fsu.edu/~jburkardt/cpp_src/brent/brent.cpp Based on quadratic or parabolic interpolation – if the function is smooth & parabolic near to the minimum, then a parabola fitted through any 3 points should approximate the minima – fails when the 3 points are collinear , in which case the denominator is 0 Simplex Method http://en.wikipedia.org/wiki/Simplex_algorithm C++: http://www.codeguru.com/cpp/article.php/c17505/Simplex-Optimization-Algorithm-and-Implemetation-in-C-Programming.htm Find the global minima of any multi-variable function Direct search – no derivatives required At each step it maintains a non-degenerative simplex – a convex hull of n+1 vertices. Obtains the minimum for a function with n variables by evaluating the function at n-1 points, iteratively replacing the point of worst result with the point of best result, shrinking the multidimensional simplex around the best point. Point replacement involves expanding & contracting the simplex near the worst value point to determine a better replacement point Oscillation can be avoided by choosing the 2nd worst result Restart if it gets stuck Parameters: contraction & expansion factors Simulated Annealing http://en.wikipedia.org/wiki/Simulated_annealing C++: http://code.google.com/p/cppsimulatedannealing/ Analogy to heating & cooling metal to strengthen its structure Stochastic method – apply random permutation search for global minima - Avoid entrapment in local minima via hill climbing Heating schedule - Annealing schedule params: temperature, iterations at each temp, temperature delta Cooling schedule – can be linear, step-wise or exponential Differential Evolution http://en.wikipedia.org/wiki/Differential_evolution C++: http://www.amichel.com/de/doc/html/ More advanced stochastic methods analogous to biological processes: Genetic algorithms, evolution strategies Parallel direct search method against multiple discrete or continuous variables Initial population of variable vectors chosen randomly – if weighted difference vector of 2 vectors yields a lower objective function value then it replaces the comparison vector Many params: #parents, #variables, step size, crossover constant etc Convergence is slow – many more function evaluations than simulated annealing Numerical Differentiation Overview 2 approaches to finite difference methods: · A) approximate function via polynomial interpolation then differentiate · B) Taylor series approximation – additionally provides error estimate Finite Difference methods http://en.wikipedia.org/wiki/Finite_difference_method C++: http://www.wpi.edu/Pubs/ETD/Available/etd-051807-164436/unrestricted/EAMPADU.pdf Find differences between high order derivative values - Approximate differential equations by finite differences at evenly spaced data points Based on forward & backward Taylor series expansion of f(x) about x plus or minus multiples of delta h. Forward / backward difference - the sums of the series contains even derivatives and the difference of the series contains odd derivatives – coupled equations that can be solved. Provide an approximation of the derivative within a O(h^2) accuracy There is also central difference & extended central difference which has a O(h^4) accuracy Richardson Extrapolation http://en.wikipedia.org/wiki/Richardson_extrapolation C++: http://mathscoding.blogspot.co.il/2012/02/introduction-richardson-extrapolation.html A sequence acceleration method applied to finite differences Fast convergence, high accuracy O(h^4) Derivatives via Interpolation Cannot apply Finite Difference method to discrete data points at uneven intervals – so need to approximate the derivative of f(x) using the derivative of the interpolant via 3 point Lagrange Interpolation Note: the higher the order of the derivative, the lower the approximation precision Numerical Integration Estimate finite & infinite integrals of functions More accurate procedure than numerical differentiation Use when it is not possible to obtain an integral of a function analytically or when the function is not given, only the data points are Newton Cotes Methods http://en.wikipedia.org/wiki/Newton%E2%80%93Cotes_formulas C++: http://www.siafoo.net/snippet/324 For equally spaced data points Computationally easy – based on local interpolation of n rectangular strip areas that is piecewise fitted to a polynomial to get the sum total area Evaluate the integrand at n+1 evenly spaced points – approximate definite integral by Sum Weights are derived from Lagrange Basis polynomials Leverage Trapezoidal Rule for default 2nd formulas, Simpson 1/3 Rule for substituting 3 point formulas, Simpson 3/8 Rule for 4 point formulas. For 4 point formulas use Bodes Rule. Higher orders obtain more accurate results Trapezoidal Rule uses simple area, Simpsons Rule replaces the integrand f(x) with a quadratic polynomial p(x) that uses the same values as f(x) for its end points, but adds a midpoint Romberg Integration http://en.wikipedia.org/wiki/Romberg's_method C++: http://code.google.com/p/romberg-integration/downloads/detail?name=romberg.cpp&can=2&q= Combines trapezoidal rule with Richardson Extrapolation Evaluates the integrand at equally spaced points The integrand must have continuous derivatives Each R(n,m) extrapolation uses a higher order integrand polynomial replacement rule (zeroth starts with trapezoidal) à a lower triangular matrix set of equation coefficients where the bottom right term has the most accurate approximation. The process continues until the difference between 2 successive diagonal terms becomes sufficiently small. Gaussian Quadrature http://en.wikipedia.org/wiki/Gaussian_quadrature C++: http://www.alglib.net/integration/gaussianquadratures.php Data points are chosen to yield best possible accuracy – requires fewer evaluations Ability to handle singularities, functions that are difficult to evaluate The integrand can include a weighting function determined by a set of orthogonal polynomials. Points & weights are selected so that the integrand yields the exact integral if f(x) is a polynomial of degree <= 2n+1 Techniques (basically different weighting functions): · Gauss-Legendre Integration w(x)=1 · Gauss-Laguerre Integration w(x)=e^-x · Gauss-Hermite Integration w(x)=e^-x^2 · Gauss-Chebyshev Integration w(x)= 1 / Sqrt(1-x^2) Solving ODEs Use when high order differential equations cannot be solved analytically Evaluated under boundary conditions RK for systems – a high order differential equation can always be transformed into a coupled first order system of equations Euler method http://en.wikipedia.org/wiki/Euler_method C++: http://rosettacode.org/wiki/Euler_method First order Runge–Kutta method. Simple recursive method – given an initial value, calculate derivative deltas. Unstable & not very accurate (O(h) error) – not used in practice A first-order method - the local error (truncation error per step) is proportional to the square of the step size, and the global error (error at a given time) is proportional to the step size In evolving solution between data points xn & xn+1, only evaluates derivatives at beginning of interval xn à asymmetric at boundaries Higher order Runge Kutta http://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods C++: http://www.dreamincode.net/code/snippet1441.htm 2nd & 4th order RK - Introduces parameterized midpoints for more symmetric solutions à accuracy at higher computational cost Adaptive RK – RK-Fehlberg – estimate the truncation at each integration step & automatically adjust the step size to keep error within prescribed limits. At each step 2 approximations are compared – if in disagreement to a specific accuracy, the step size is reduced Boundary Value Problems Where solution of differential equations are located at 2 different values of the independent variable x à more difficult, because cannot just start at point of initial value – there may not be enough starting conditions available at the end points to produce a unique solution An n-order equation will require n boundary conditions – need to determine the missing n-1 conditions which cause the given conditions at the other boundary to be satisfied Shooting Method http://en.wikipedia.org/wiki/Shooting_method C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-shooting-method-for-solving.html Iteratively guess the missing values for one end & integrate, then inspect the discrepancy with the boundary values of the other end to adjust the estimate Given the starting boundary values u1 & u2 which contain the root u, solve u given the false position method (solving the differential equation as an initial value problem via 4th order RK), then use u to solve the differential equations. Finite Difference Method For linear & non-linear systems Higher order derivatives require more computational steps – some combinations for boundary conditions may not work though Improve the accuracy by increasing the number of mesh points Solving EigenValue Problems An eigenvalue can substitute a matrix when doing matrix multiplication à convert matrix multiplication into a polynomial EigenValue For a given set of equations in matrix form, determine what are the solution eigenvalue & eigenvectors Similar Matrices - have same eigenvalues. Use orthogonal similarity transforms to reduce a matrix to diagonal form from which eigenvalue(s) & eigenvectors can be computed iteratively Jacobi method http://en.wikipedia.org/wiki/Jacobi_method C++: http://people.sc.fsu.edu/~jburkardt/classes/acs2_2008/openmp/jacobi/jacobi.html Robust but Computationally intense – use for small matrices < 10x10 Power Iteration http://en.wikipedia.org/wiki/Power_iteration For any given real symmetric matrix, generate the largest single eigenvalue & its eigenvectors Simplest method – does not compute matrix decomposition à suitable for large, sparse matrices Inverse Iteration Variation of power iteration method – generates the smallest eigenvalue from the inverse matrix Rayleigh Method http://en.wikipedia.org/wiki/Rayleigh's_method_of_dimensional_analysis Variation of power iteration method Rayleigh Quotient Method Variation of inverse iteration method Matrix Tri-diagonalization Method Use householder algorithm to reduce an NxN symmetric matrix to a tridiagonal real symmetric matrix vua N-2 orthogonal transforms     Whats Next Outside of Numerical Methods there are lots of different types of algorithms that I’ve learned over the decades: Data Mining – (I covered this briefly in a previous post: http://geekswithblogs.net/JoshReuben/archive/2007/12/31/ssas-dm-algorithms.aspx ) Search & Sort Routing Problem Solving Logical Theorem Proving Planning Probabilistic Reasoning Machine Learning Solvers (eg MIP) Bioinformatics (Sequence Alignment, Protein Folding) Quant Finance (I read Wilmott’s books – interesting) Sooner or later, I’ll cover the above topics as well.

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• Sorting linked lists in Pascal

  - by user3712174

  I'm doing my final project for Informatics class and I can't get my sorting procedure to work. Have a look at my program, specifically the bolded part (some things are in Croatian. - if you need something translated, let me know): type pokazivac=^slog; slog=record prezime_ime:string[30]; redni_broj:string[2]; fakultet:string[50]; bodovi:integer; sljedeci:pokazivac; end; var pocetni, trenutni, prethodni:pokazivac; i:integer; procedure racunaj; var i,a,c:integer; b,d,e,f,g,h,j:real; begin write('Postotak bodova (u decimalnom zapisu) koje ucenik ostvaruje na temelju prosjeka ocjena - '); readln(e); e:=e*1000/4; write('Prosjek ocjena u prvom razredu : '); readln(f); f:=f/5*e; write('Prosjek ocjena u drugom razredu : '); readln(g); g:=g/5*e; write('Prosjek ocjena u trecem razredu : '); readln(h); h:=h/5*e; write('Prosjek ocjena u cetvrtom razredu : '); readln(j); j:=j/5*e; d:=f+g+h+j; write('Broj predmeta (ne racunajuci hrvatski jezik, strani jezik i matematiku) koju je ucenik/ca polagao na maturi - '); readln(a); write('Postotak rijesnosti ispita iz hrvatskog jezika te zatim maksimum bodova koje je ucenik/ca mogao ostvariti - '); readln(b); readln(c); d:=d+b*c; write('Postotak rijesnosti ispita iz stranog jezika te zatim maksimum bodova koje je ucenik/ca mogao ostvariti - '); readln(b); readln(c); d:=d+(b*c); write('Postotak rijesnosti ispita iz matematike te zatim maksimum bodova koje je ucenik/ca mogao ostvariti - '); readln(b); readln(c); d:=d+(b*c); for i:=1 to a do begin writeln('Postotak rijesnosti dodatnog predmeta te zatim maksimum bodova koje je ucenik/ca mogao ostvariti - '); readln(b); readln(c); d:=d+(b*c); end; d:=round(d); writeln('Vas broj bodova je: ', d:4:2); write('Za nastavak pritisnite ENTER..'); readln; end; procedure unos; begin new(trenutni); write('Redni broj ucenika - ');readln(trenutni^.redni_broj); write('Prezime i ime - ');readln(trenutni^.prezime_ime); write('Naziv fakultet - ');readln(trenutni^.fakultet); write('Bodovi - ');readln(trenutni^.bodovi); trenutni^.sljedeci:=pocetni; pocetni:=trenutni; end; procedure ispis; begin writeln(); writeln('Lista popisanih ucenika:'); writeln(); trenutni:=pocetni; while trenutni<>NIL do begin with trenutni^do begin writeln('IME: ',prezime_ime); writeln('FAKULTET: ',fakultet); writeln('BODOVI: ',bodovi); writeln(); end; trenutni:=trenutni^.sljedeci; end; writeln(); write('Za nastavak pritisnite ENTER..'); readln; end; procedure brisi; var s:string; begin trenutni:= pocetni; prethodni:=pocetni; write('Redni broj ucenika kojeg zelite izbrisati - '); readln(s); while trenutni<>NIL do begin if trenutni^.redni_broj=s then begin prethodni^.sljedeci:=trenutni^.sljedeci; dispose(trenutni); break; end; trenutni:=trenutni^.sljedeci; end; end; procedure izmjeni; var s:string; begin trenutni:=pocetni; write('Redni broj ucenika cije podatke zelite izmijeniti - '); readln(s); while trenutni<> NIL do begin if trenutni^.redni_broj=s then begin write(trenutni^.prezime_ime, ' - '); readln(trenutni^.prezime_ime); write(trenutni^.fakultet, ' - '); readln(trenutni^.fakultet); write(trenutni^.bodovi, ' - '); readln(trenutni^.bodovi); break; end; trenutni:=trenutni^.sljedeci; end; end; **procedure sortiraj; var t1,t2,t:pokazivac; begin t1:=pocetni; while t1 <> NIL do begin t2:=t1^.sljedeci; while t2<>NIL do if t2^.bodovi<t1^.bodovi then begin new(t); t^.redni_broj:=t1^.redni_broj; t^.prezime_ime:=t1^.prezime_ime; t^.fakultet:=t1^.fakultet; t^.bodovi:=t1^.bodovi; t1^.redni_broj:=t2^.redni_broj; t1^.prezime_ime:=t2^.prezime_ime; t1^.fakultet:=t2^.fakultet; t1^.bodovi:=t2^.bodovi; t2^.redni_broj:=t^.redni_broj; t2^.prezime_ime:=t^.prezime_ime; t2^.fakultet:=t^.fakultet; t2^.bodovi:=t^.bodovi; dispose(t); end; t2:=t2^.sljedeci; end; t1:=t1^.sljedeci; write('Za nastavak pritisnite ENTER..'); readln; end;** begin pocetni:=NIL; trenutni:=NIL; writeln('******************************************'); writeln('**********DOBRODOSLI U FAX-O-MAT**********'); writeln('******************************************'); repeat writeln('1 - Racunaj broj bodova'); writeln('2 - Dodaj ucenika'); writeln('3 - Brisi ucenika'); writeln('4 - Ispis liste'); writeln('5 - Izmjeni podatke'); writeln('6 - Sortiraj listu prema broju bodova'); writeln('0 - Kraj'); readln(i); case i of 1:racunaj; 2:unos; 3:brisi; 4:ispis; 5:izmjeni; 6:sortiraj; end; until i=0; end. Either it crashes with a fatal error, or when I press the number 6, nothing happens. The pointer keeps blinking and I can't enter any more numbers.

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• Database Tutorial: The method open() is undefined for the type MainActivity.DBAdapter

  - by user2203633

  I am trying to do this database tutorial on SQLite Eclipse: https://www.youtube.com/watch?v=j-IV87qQ00M But I get a few errors at the end.. at db.ppen(); i get error: The method open() is undefined for the type MainActivity.DBAdapter and similar for insert record and close. MainActivity: package com.example.studentdatabase; import java.io.File; import java.io.FileNotFoundException; import java.io.FileOutputStream; import java.io.IOException; import java.io.InputStream; import java.io.OutputStream; import android.app.Activity; import android.app.ListActivity; import android.content.Intent; import android.database.Cursor; import android.os.Bundle; import android.util.Log; import android.view.LayoutInflater; import android.view.View; import android.view.ViewGroup; import android.widget.BaseAdapter; import android.widget.Button; import android.widget.Toast; public class MainActivity extends Activity { /** Called when the activity is first created. */ //DBAdapter db = new DBAdapter(this); @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.activity_main); Button addBtn = (Button)findViewById(R.id.add); addBtn.setOnClickListener(new View.OnClickListener() { @Override public void onClick(View v) { Intent i = new Intent(MainActivity.this, addassignment.class); startActivity(i); } }); try { String destPath = "/data/data/" + getPackageName() + "/databases/AssignmentDB"; File f = new File(destPath); if (!f.exists()) { CopyDB( getBaseContext().getAssets().open("mydb"), new FileOutputStream(destPath)); } } catch (FileNotFoundException e) { e.printStackTrace(); } catch (IOException e) { e.printStackTrace(); } DBAdapter db = new DBAdapter(); //---add an assignment--- db.open(); long id = db.insertRecord("Hello World", "2/18/2012", "DPR 224", "First Android Project"); id = db.insertRecord("Workbook Exercises", "3/1/2012", "MAT 100", "Do odd numbers"); db.close(); //---get all Records--- /* db.open(); Cursor c = db.getAllRecords(); if (c.moveToFirst()) { do { DisplayRecord(c); } while (c.moveToNext()); } db.close(); */ /* //---get a Record--- db.open(); Cursor c = db.getRecord(2); if (c.moveToFirst()) DisplayRecord(c); else Toast.makeText(this, "No Assignments found", Toast.LENGTH_LONG).show(); db.close(); */ //---update Record--- /* db.open(); if (db.updateRecord(1, "Hello Android", "2/19/2012", "DPR 224", "First Android Project")) Toast.makeText(this, "Update successful.", Toast.LENGTH_LONG).show(); else Toast.makeText(this, "Update failed.", Toast.LENGTH_LONG).show(); db.close(); */ /* //---delete a Record--- db.open(); if (db.deleteRecord(1)) Toast.makeText(this, "Delete successful.", Toast.LENGTH_LONG).show(); else Toast.makeText(this, "Delete failed.", Toast.LENGTH_LONG).show(); db.close(); */ } private class DBAdapter extends BaseAdapter { private LayoutInflater mInflater; //private ArrayList<> @Override public int getCount() { return 0; } @Override public Object getItem(int arg0) { return null; } @Override public long getItemId(int arg0) { return 0; } @Override public View getView(int arg0, View arg1, ViewGroup arg2) { return null; } } public void CopyDB(InputStream inputStream, OutputStream outputStream) throws IOException { //---copy 1K bytes at a time--- byte[] buffer = new byte[1024]; int length; while ((length = inputStream.read(buffer)) > 0) { outputStream.write(buffer, 0, length); } inputStream.close(); outputStream.close(); } public void DisplayRecord(Cursor c) { Toast.makeText(this, "id: " + c.getString(0) + "\n" + "Title: " + c.getString(1) + "\n" + "Due Date: " + c.getString(2), Toast.LENGTH_SHORT).show(); } public void addAssignment(View view) { Intent i = new Intent("com.pinchtapzoom.addassignment"); startActivity(i); Log.d("TAG", "Clicked"); } } DBAdapter code: package com.example.studentdatabase; public class DBAdapter { public static final String KEY_ROWID = "id"; public static final String KEY_TITLE = "title"; public static final String KEY_DUEDATE = "duedate"; public static final String KEY_COURSE = "course"; public static final String KEY_NOTES = "notes"; private static final String TAG = "DBAdapter"; private static final String DATABASE_NAME = "AssignmentsDB"; private static final String DATABASE_TABLE = "assignments"; private static final int DATABASE_VERSION = 2; private static final String DATABASE_CREATE = "create table if not exists assignments (id integer primary key autoincrement, " + "title VARCHAR not null, duedate date, course VARCHAR, notes VARCHAR );"; private final Context context; private DatabaseHelper DBHelper; private SQLiteDatabase db; public DBAdapter(Context ctx) { this.context = ctx; DBHelper = new DatabaseHelper(context); } private static class DatabaseHelper extends SQLiteOpenHelper { DatabaseHelper(Context context) { super(context, DATABASE_NAME, null, DATABASE_VERSION); } @Override public void onCreate(SQLiteDatabase db) { try { db.execSQL(DATABASE_CREATE); } catch (SQLException e) { e.printStackTrace(); } } @Override public void onUpgrade(SQLiteDatabase db, int oldVersion, int newVersion) { Log.w(TAG, "Upgrading database from version " + oldVersion + " to " + newVersion + ", which will destroy all old data"); db.execSQL("DROP TABLE IF EXISTS contacts"); onCreate(db); } } //---opens the database--- public DBAdapter open() throws SQLException { db = DBHelper.getWritableDatabase(); return this; } //---closes the database--- public void close() { DBHelper.close(); } //---insert a record into the database--- public long insertRecord(String title, String duedate, String course, String notes) { ContentValues initialValues = new ContentValues(); initialValues.put(KEY_TITLE, title); initialValues.put(KEY_DUEDATE, duedate); initialValues.put(KEY_COURSE, course); initialValues.put(KEY_NOTES, notes); return db.insert(DATABASE_TABLE, null, initialValues); } //---deletes a particular record--- public boolean deleteContact(long rowId) { return db.delete(DATABASE_TABLE, KEY_ROWID + "=" + rowId, null) > 0; } //---retrieves all the records--- public Cursor getAllRecords() { return db.query(DATABASE_TABLE, new String[] {KEY_ROWID, KEY_TITLE, KEY_DUEDATE, KEY_COURSE, KEY_NOTES}, null, null, null, null, null); } //---retrieves a particular record--- public Cursor getRecord(long rowId) throws SQLException { Cursor mCursor = db.query(true, DATABASE_TABLE, new String[] {KEY_ROWID, KEY_TITLE, KEY_DUEDATE, KEY_COURSE, KEY_NOTES}, KEY_ROWID + "=" + rowId, null, null, null, null, null); if (mCursor != null) { mCursor.moveToFirst(); } return mCursor; } //---updates a record--- public boolean updateRecord(long rowId, String title, String duedate, String course, String notes) { ContentValues args = new ContentValues(); args.put(KEY_TITLE, title); args.put(KEY_DUEDATE, duedate); args.put(KEY_COURSE, course); args.put(KEY_NOTES, notes); return db.update(DATABASE_TABLE, args, KEY_ROWID + "=" + rowId, null) > 0; } } addassignment code: package com.example.studentdatabase; public class addassignment extends Activity { DBAdapter db = new DBAdapter(this); @Override protected void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.add); } public void addAssignment(View v) { Log.d("test", "adding"); //get data from form EditText nameTxt = (EditText)findViewById(R.id.editTitle); EditText dateTxt = (EditText)findViewById(R.id.editDuedate); EditText courseTxt = (EditText)findViewById(R.id.editCourse); EditText notesTxt = (EditText)findViewById(R.id.editNotes); db.open(); long id = db.insertRecord(nameTxt.getText().toString(), dateTxt.getText().toString(), courseTxt.getText().toString(), notesTxt.getText().toString()); db.close(); nameTxt.setText(""); dateTxt.setText(""); courseTxt.setText(""); notesTxt.setText(""); Toast.makeText(addassignment.this,"Assignment Added", Toast.LENGTH_LONG).show(); } public void viewAssignments(View v) { Intent i = new Intent(this, MainActivity.class); startActivity(i); } } What is wrong here? Thanks in advance.

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