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  • Oracle T4CPreparedStatement memory leaks?

    - by Jay
    A little background on the application that I am gonna talk about in the next few lines: XYZ is a data masking workbench eclipse RCP application: You give it a source table column, and a target table column, it would apply a trasformation (encryption/shuffling/etc) and copy the row data from source table to target table. Now, when I mask n tables at a time, n threads are launched by this app. Here is the issue: I have run into a production issue on first roll out of the above said app. Unfortunately, I don't have any logs to get to the root. However, I tried to run this app in test region and do a stress test. When I collected .hprof files and ran 'em through an analyzer (yourKit), I noticed that objects of oracle.jdbc.driver.T4CPreparedStatement was retaining heap. The analysis also tells me that one of my classes is holding a reference to this preparedstatement object and thereby, n threads have n such objects. T4CPreparedStatement seemed to have character arrays: lastBoundChars and bindChars each of size char[300000]. So, I researched a bit (google!), obtained ojdbc6.jar and tried decompiling T4CPreparedStatement. I see that T4CPreparedStatement extends OraclePreparedStatement, which dynamically manages array size of lastBoundChars and bindChars. So, my questions here are: Have you ever run into an issue like this? Do you know the significance of lastBoundChars / bindChars? I am new to profiling, so do you think I am not doing it correct? (I also ran the hprofs through MAT - and this was the main identified issue - so, I don't really think I could be wrong?) I have found something similar on the web here: http://forums.oracle.com/forums/thread.jspa?messageID=2860681 Appreciate your suggestions / advice.

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  • JVM terminates when launching eclipse with J2SE 6.0 on mac os x (need J2SE 6.0 for Oracle enterprise

    - by rooban bajwa
    I know my issue has party been addressed at this link http://stackoverflow.com/questions/245803/jvm-terminates-when-launching-eclipse-mat-on-mac-os-with-j2se-60 but it was a year+ ago.. plus the link that's provided in there http://landonf.bikemonkey.org/static/soylatte/ does not seem to be alive (i mean the download section on that link no longer provide the 32-bit port of j2se 6.0 for mac osx 10.5) I am trying to run eclipse 3.5 on mac OSX 10.5. It works fine with J2SE 5.0. But when I installed the Oracle enterprise pack for eclipse - it requires to start eclipse with J2SE 6.0 JVM otherwise it will get disabled. Here's the exact message I get from it - "You are running Eclipse on Java VM version: 1.5.0_22 Oracle Enterprise Pack for Eclipse requires Java version 6 or higher. Click next to configure a compatible Java VM." It asks me to point to J2SE 6.0 JVM, when I do that (i.e point it to "/System/Library/Frameworks/JavaVM.framework/Versions/1.6.0/Home") , it asks to restart eclipse , when I do that, eclipse just bombs .. with JVM terminated error .. SO I need to start eclipse with J2SE 6.0 JVM but eclipse needs carbon which is only available in 32 bits and hence I cann't start eclipse with J2SE 6.0 JVM which is only available in 64bit mode from mac. And the site providing 32 bit port of J2SE 6.0 JVM does not seem to be active anymore.. Can someone help me on this issue, Thanks in advance,

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  • R Random Data Sets within loops

    - by jugossery
    Here is what I want to do: I have a time series data frame with let us say 100 time-series of length 600 - each in one column of the data frame. I want to pick up 4 of the time-series randomly and then assign them random weights that sum up to one (ie 0.1, 0.5, 0.3, 0.1). Using those I want to compute the mean of the sum of the 4 weighted time series variables (e.g. convex combination). I want to do this let us say 100k times and store each result in the form ts1.name, ts2.name, ts3.name, ts4.name, weight1, weight2, weight3, weight4, mean so that I get a 9*100k df. I tried some things already but R is very bad with loops and I know vector oriented solutions are better because of R design. Thanks Here is what I did and I know it is horrible The df is in the form v1,v2,v2.....v100 1,5,6,.......9 2,4,6,.......10 3,5,8,.......6 2,2,8,.......2 etc e=NULL for (x in 1:100000) { s=sample(1:100,4)#pick 4 variables randomly a=sample(seq(0,1,0.01),1) b=sample(seq(0,1-a,0.01),1) c=sample(seq(0,(1-a-b),0.01),1) d=1-a-b-c e=c(a,b,c,d)#4 random weights average=mean(timeseries.df[,s]%*%t(e)) e=rbind(e,s,average)#in the end i get the 9*100k df } The procedure runs way to slow. EDIT: Thanks for the help i had,i am not used to think R and i am not very used to translate every problem into a matrix algebra equation which is what you need in R. Then the problem becomes a little bit complex if i want to calculate the standard deviation. i need the covariance matrix and i am not sure i can if/how i can pick random elements for each sample from the original timeseries.df covariance matrix then compute the sample variance (t(sampleweights)%*%sample_cov.mat%*%sampleweights) to get in the end the ts.weighted_standard_dev matrix Last question what is the best way to proceed if i want to bootstrap the original df x times and then apply the same computations to test the robustness of my datas thanks

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  • What influences running time of reading a bunch of images?

    - by remi
    I have a program where I read a handful of tiny images (50000 images of size 32x32). I read them using OpenCV imread function, in a program like this: std::vector<std::string> imageList; // is initialized with full path to the 50K images for(string s : imageList) { cv::Mat m = cv::imread(s); } Sometimes, it will read the images in a few seconds. Sometimes, it takes a few minutes to do so. I run this program in GDB, with a breakpoint further away than the loop for reading images so it's not because I'm stuck in a breakpoint. The same "erratic" behaviour happens when I run the program out of GDB. The same "erratic" behaviour happens with program compiled with/without optimisation The same "erratic" behaviour happens while I have or not other programs running in background The images are always at the same place in the hard drive of my machine. I run the program on a Linux Suse distrib, compiled with gcc. So I am wondering what could affect the time of reading the images that much?

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  • PostgreSQL to Data-Warehouse: Best approach for near-real-time ETL / extraction of data

    - by belvoir
    Background: I have a PostgreSQL (v8.3) database that is heavily optimized for OLTP. I need to extract data from it on a semi real-time basis (some-one is bound to ask what semi real-time means and the answer is as frequently as I reasonably can but I will be pragmatic, as a benchmark lets say we are hoping for every 15min) and feed it into a data-warehouse. How much data? At peak times we are talking approx 80-100k rows per min hitting the OLTP side, off-peak this will drop significantly to 15-20k. The most frequently updated rows are ~64 bytes each but there are various tables etc so the data is quite diverse and can range up to 4000 bytes per row. The OLTP is active 24x5.5. Best Solution? From what I can piece together the most practical solution is as follows: Create a TRIGGER to write all DML activity to a rotating CSV log file Perform whatever transformations are required Use the native DW data pump tool to efficiently pump the transformed CSV into the DW Why this approach? TRIGGERS allow selective tables to be targeted rather than being system wide + output is configurable (i.e. into a CSV) and are relatively easy to write and deploy. SLONY uses similar approach and overhead is acceptable CSV easy and fast to transform Easy to pump CSV into the DW Alternatives considered .... Using native logging (http://www.postgresql.org/docs/8.3/static/runtime-config-logging.html). Problem with this is it looked very verbose relative to what I needed and was a little trickier to parse and transform. However it could be faster as I presume there is less overhead compared to a TRIGGER. Certainly it would make the admin easier as it is system wide but again, I don't need some of the tables (some are used for persistent storage of JMS messages which I do not want to log) Querying the data directly via an ETL tool such as Talend and pumping it into the DW ... problem is the OLTP schema would need tweaked to support this and that has many negative side-effects Using a tweaked/hacked SLONY - SLONY does a good job of logging and migrating changes to a slave so the conceptual framework is there but the proposed solution just seems easier and cleaner Using the WAL Has anyone done this before? Want to share your thoughts?

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  • How to remove music/videos DRM protection and convert to Mobile Devices such as iPod, iPhone, PSP, Z

    - by tonywesley
    The music/video files you purchased from online music stores like iTunes, Yahoo Music or Wal-Mart are under DRM protection. So you can't convert them to the formats supported by your own mobile devices such as Nokia phone, Creative Zen palyer, iPod, PSP, Walkman, Zune… You also can't share your purchased music/videos with your friends. The following step by step tutorial is dedicated to instructing music lovers to how to convert your DRM protected music/videos to mobile devices. Method 1: If you only want to remove DRM protection from your protected music, this method will not spend your money. Step 1: Burn your protected music files to CD-R/RW disc to make an audio CD Step 2: Find a free CD Ripper software to convert the audio CD track back to MP3, WAV, WMA, M4A, AAC, RA… Method 2: This guide will show you how to crack drm from protected wmv, wma, m4p, m4v, m4a, aac files and convert to unprotected WMV, MP4, MP3, WMA or any video and audio formats you like, such as AVI, MP4, Flv, MPEG, MOV, 3GP, m4a, aac, wmv, ogg, wav... I have been using Media Converter software, it is the quickest and easiest solution to remove drm from WMV, M4V, M4P, WMA, M4A, AAC, M4B, AA files by quick recording. It gets audio and video stream at the bottom of operating system, so the output quality is lossless and the conversion speed is fast . The process is as follows. Step 1: Download and install the software Step 2: Run the software and click "Add…" button to load WMA or M4A, M4B, AAC, WMV, M4P, M4V, ASF files Step 3: Choose output formats. If you want to convert protected audio files, please select "Convert audio to" list; If you want to convert protected video files, please select "Convert video to" list. Step 4: You can click "Settings" button to custom preference for output files. Click "Settings" button bellow "Convert audio to" list for protected audio files Click "Settings" button bellow "Convert video to" list for protected video files Step 5: Start remove DRM and convert your DRM protected music and videos by click on "Start" button. What is DRM? DRM, which is most commonly found in movies and music files, doesn't mean just basic copy-protection of video, audio and ebooks, but it basically means full protection for digital content, ranging from delivery to end user's ways to use the content. We can remove the Drm from video and audio files legally by quick recording.

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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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  • 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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  • 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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  • Understanding the value of Customer Experience & Loyalty for the Telecommunications Industry

    - by raul.goycoolea
    Worried by economic woes and market forces, especially in mature markets, communications service providers (CSPs) increasingly focus on improving customer experience. In fact, it seems difficult to find a major message by a C-level executive in the developed world that does not include something on "meeting and exceeding customers' needs". Frequently in customer satisfaction studies by prominent firms, CSPs fall short of the leadership demonstrated by other industries that take customer-centric approaches to their bottom-line strategies. Consider the following:Despite the continued impact of global economic crisis, in July 2010, Apple Computer posted record revenue and net quarterly profit. Those who attribute the results primarily to the iPhone 4 launch should note that Apple also shipped around 30% more Macintosh computers than the same period the previous year. Even sales of the iPod line increased by 8% in a highly commoditized, shrinking media player market. Finally, Apple began selling iPads during the quarter, with total sales of more than 3 million units. What does Apple have that the others lack? Well, some great products (and services) to be sure, but it also excels at customer service and support, marketing, and distribution, and has one of the strongest brands globally. Its products are useful, simple to use, easy to acquire and augment, high quality, and considered very cool. They also evoke such an emotional response from many of Apple's customers, which they turn up their noses at competitive products.In other words, Apple appears to have mastered virtually every aspect of customer experience and the resultant loyalty of its customer base - even in difficult financial times. Through that unwavering customer focus, Apple continues to drive its revenues and profits to new heights. Other customer loyalty leaders like Wal-Mart, Google, Toyota and Honda are also doing well by focusing on customer experience as an essential driver of profitability. Service providers should note this performance and ask themselves how they might leverage the same principles to increase their own profitability. After all, that is what customer experience and loyalty are all about: profitability.To successfully manage all the critical touch points of customer experience, CSPs must shun the one-size-fits-all approach. They can no longer afford to view customer service fundamentally as an act of altruism - which mentality dates back to the industry's civil service days, when CSPs were typically government organizations that were critical to economic development and public safety.As regulators and public officials have pushed, and continue to push, service providers to new heights of reliability - using incentives and punishments - most CSPs already have some of the fundamental building blocks of customer service in place. Yet despite that history and experience, service providers still lag other industries in providing what is seen as good customer service.As we observed in the TMF's 2009 Insights Research report, Customer Experience Management: Driving Loyalty & Profitability there has been resurgence in interest by CSPs. More and more of them have stated ambitions to catch up other industries, and they are realizing that good customer service is a powerful strategy for increasing business performance and profitability, not an act of good will.CSPs are recognizing the connection between customer experience and profitability, as demonstrated in many studies. For example, according to research by Bain & Company, a 5 percent improvement in customer retention rates can yield as much as a 75 percent increase in profits for companies across a range of industries.After decades of customer experience strategy formulation, Bain partner and business author, Frederick Reichheld, considers "would you recommend us to a friend?" as the ultimate question for a customer. How many times have you or your friends recommended an iPod, iPhone or a Mac? What do your children recommend to their peers? Their peers to them?There are certain steps service providers have to take to create more personalized relationships with their customers, as well as reduce churn and increase profitability, all while becoming leaner and more agile. First, they have to define customer experience, we define it as the result of the sum of observations, perceptions, thoughts and feelings arising from interactions and relationships between customers and their service provider(s). Virtually every customer touch point - whether directly or indirectly linked to service providers and their partners - contributes to customer perception, satisfaction, loyalty, and ultimately profitability. Gaining leadership in customer experience and satisfaction will not be a simple task, as it is affected by virtually every customer-facing aspect of the service provider, and in turn impacts the service provider deeply - especially on the all-important bottom line. The scope of issues affecting customer experience is complex and dynamic.With new services, devices and applications extending the basis of customer experience to domains beyond the direct control of the service provider, it is likely to increase in complexity and dynamism.Customer loyalty = increased profitsAs stated earlier, customer experience programs are not fundamentally altruistic exercises, but a strategic means of improving competitiveness and profitability in the short and long term. Loyalty is essential to deriving long term profits from customers.Some of the earliest loyalty programs date back to the 1930s, when packaged goods companies offered embedded coupons for rewards to buyers, and eventually retail chains began offering reward programs to frequent shoppers. These programs continued for decades but were leapfrogged in the 1980s by more aggressive programs from the airlines.This movement was led by American Airlines, which launched the first full-scale loyalty marketing program of the modern era with the AAdvantage frequent flyer scheme. It was the first to reward frequent fliers with notional air miles that could be accumulated and later redeemed for free travel. Figure 1: Opportunities example of Customer loyalty driven profitOther airlines and travel providers were quick to grasp the incredible value of providing customers with an incentive to use their company exclusively. Within a few years, dozens of travel industry companies launched similar initiatives and now loyalty programs are achieving near-ubiquity in many service industries, especially those in which it is difficult to differentiate offerings by product attributes.The belief is that increased profitability will result from customer retention efforts because:•    The cost of acquisition occurs only at the beginning of a relationship: the longer the relationship, the lower the amortized cost;•    Account maintenance costs decline as a percentage of total costs, or as a percentage of revenue, over the lifetime of the relationship;•    Long term customers tend to be less inclined to switch and less price sensitive which can result in stable unit sales volume and increases in dollar-sales volume;•    Long term customers may initiate word-of-mouth promotions and referrals, which cost the company nothing and arguably are the most effective form of advertising;•    Long-term customers are more likely to buy ancillary products and higher margin supplemental products;•    Long term customers tend to be satisfied with their relationship with the company and are less likely to switch to competitors, making market entry or competitors gaining market share difficult;•    Regular customers tend to be less expensive to service, as they are familiar with the processes involved, require less 'education', and are consistent in their order placement;•    Increased customer retention and loyalty makes the employees' jobs easier and more satisfying. In turn, happy employees feed back into higher customer satisfaction in a virtuous circle. Figure 2: The virtuous circle of customer loyaltyFigure 2 represents a high-level example of a virtuous cycle driven by customer satisfaction and loyalty, depicting how superiority in product and service offerings, as well as strong customer support by competent employees, lead to higher sales and ultimately profitability. As stated above, this is not a new concept, but succeeding with it is difficult. It has eluded many a company driven to achieve profitability goals. Of course, for this circle to be virtuous, the customer relationship(s) must be profitable.Trying to maintain the loyalty of unprofitable customers is not a viable business strategy. It is, therefore, important that marketers can assess the profitability of each customer (or customer segment), and either improve or terminate relationships that are not profitable. This means each customer's 'relationship costs' must be understood and compared to their 'relationship revenue'. Customer lifetime value (CLV) is the most commonly used metric here, as it is generally accepted as a representation of exactly how much each customer is worth in monetary terms, and therefore a determinant of exactly how much a service provider should be willing to spend to acquire or retain that customer.CLV models make several simplifying assumptions and often involve the following inputs:•    Churn rate represents the percentage of customers who end their relationship with a company in a given period;•    Retention rate is calculated by subtracting the churn rate percentage from 100;•    Period/horizon equates to the units of time into which a customer relationship can be divided for analysis. A year is the most commonly used period for this purpose. Customer lifetime value is a multi-period calculation, often projecting three to seven years into the future. In practice, analysis beyond this point is viewed as too speculative to be reliable. The model horizon is the number of periods used in the calculation;•    Periodic revenue is the amount of revenue collected from a customer in a given period (though this is often extended across multiple periods into the future to understand lifetime value), such as usage revenue, revenues anticipated from cross and upselling, and often some weighting for referrals by a loyal customer to others; •    Retention cost describes the amount of money the service provider must spend, in a given period, to retain an existing customer. Again, this is often forecast across multiple periods. Retention costs include customer support, billing, promotional incentives and so on;•    Discount rate means the cost of capital used to discount future revenue from a customer. Discounting is an advanced method used in more sophisticated CLV calculations;•    Profit margin is the projected profit as a percentage of revenue for the period. This may be reflected as a percentage of gross or net profit. Again, this is generally projected across the model horizon to understand lifetime value.A strong focus on managing these inputs can help service providers realize stronger customer relationships and profits, but there are some obstacles to overcome in achieving accurate calculations of CLV, such as the complexity of allocating costs across the customer base. There are many costs that serve all customers which must be properly allocated across the base, and often a simple proportional allocation across the whole base or a segment may not accurately reflect the true cost of serving that customer;  This is made worse by the fragmentation of customer information, which is likely to be across a variety of product or operations groups, and may be difficult to aggregate due to different representations.In addition, there is the complexity of account relationships and structures to take into consideration. Complex account structures may not be understood or properly represented. For example, a profitable customer may have a separate account for a second home or another family member, which may appear to be unprofitable. If the service provider cannot relate the two accounts, CLV is not properly represented and any resultant cancellation of the apparently unprofitable account may result in the customer churning from the profitable one.In summary, if service providers are to realize strong customer relationships and their attendant profits, there must be a very strong focus on data management. This needs to be coupled with analytics that help business managers and those who work in customer-facing functions offer highly personalized solutions to customers, while maintaining profitability for the service provider. It's clear that acquiring new customers is expensive. Advertising costs, campaign management expenses, promotional service pricing and discounting, and equipment subsidies make a serious dent in a new customer's profitability. That is especially true given the rising subsidies for Smartphone users, which service providers hope will result in greater profits from profits from data services profitability in future.  The situation is made worse by falling prices and greater competition in mature markets.Customer acquisition through industry consolidation isn't cheap either. A North American service provider spent about $2,000 per subscriber in its acquisition of a smaller company earlier this year. While this has allowed it to leapfrog to become the largest mobile service provider in the country, it required a total investment of more than $28 billion (including assumption of the acquiree's debt).While many operating cost synergies clearly made this deal more attractive to the acquiring company, this is certainly an expensive way to acquire customers: the cost per subscriber in this case is not out of line with the prices others have paid for acquisitions.While growth by acquisition certainly increases overall revenues, it often creates tremendous challenges for profitability. Organic growth through increased customer loyalty and retention is a more effective driver of profit, as well as a stronger predictor of future profitability. Service providers, especially those in mature markets, are increasingly recognizing this and taking steps toward a creating a more personalized, flexible and satisfying experience for their customers.In summary, the clearest path to profitability for companies in virtually all industries is through customer retention and maximization of lifetime value. Service providers would do well to recognize this and focus attention on profitable customer relationships.

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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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  • How to tune down the Hyperic built-in postgresql database for a small setup

    - by Svish
    We are testing out Hyperic 4.5.1 in a quite small environment for now. Currently there are just 1-5 agents and there probably won't be any more than 10-15. When I run ps ax there are 20(!) postgres processes running. For a small setup like this, that can't be necessary, can it? I'm a software developer and don't have much experience with setting up servers and such though, so don't really know. Either way, what settings are appropriate for a small Hyperic setup like this? Current, default and untouched configuration file, hqdb/data/postgresql.conf: # ----------------------------- # PostgreSQL configuration file # ----------------------------- # # This file consists of lines of the form: # # name = value # # (The '=' is optional.) White space may be used. Comments are introduced # with '#' anywhere on a line. The complete list of option names and # allowed values can be found in the PostgreSQL documentation. The # commented-out settings shown in this file represent the default values. # # Please note that re-commenting a setting is NOT sufficient to revert it # to the default value, unless you restart the server. # # Any option can also be given as a command line switch to the server, # e.g., 'postgres -c log_connections=on'. Some options can be changed at # run-time with the 'SET' SQL command. # # This file is read on server startup and when the server receives a # SIGHUP. If you edit the file on a running system, you have to SIGHUP the # server for the changes to take effect, or use "pg_ctl reload". Some # settings, which are marked below, require a server shutdown and restart # to take effect. # # Memory units: kB = kilobytes MB = megabytes GB = gigabytes # Time units: ms = milliseconds s = seconds min = minutes h = hours d = days #--------------------------------------------------------------------------- # FILE LOCATIONS #--------------------------------------------------------------------------- # The default values of these variables are driven from the -D command line # switch or PGDATA environment variable, represented here as ConfigDir. #data_directory = 'ConfigDir' # use data in another directory # (change requires restart) #hba_file = 'ConfigDir/pg_hba.conf' # host-based authentication file # (change requires restart) #ident_file = 'ConfigDir/pg_ident.conf' # ident configuration file # (change requires restart) # If external_pid_file is not explicitly set, no extra PID file is written. #external_pid_file = '(none)' # write an extra PID file # (change requires restart) #--------------------------------------------------------------------------- # CONNECTIONS AND AUTHENTICATION #--------------------------------------------------------------------------- # - Connection Settings - #listen_addresses = 'localhost' # what IP address(es) to listen on; # comma-separated list of addresses; # defaults to 'localhost', '*' = all # (change requires restart) port = 9432 # (change requires restart) max_connections = 100 # (change requires restart) # Note: increasing max_connections costs ~400 bytes of shared memory per # connection slot, plus lock space (see max_locks_per_transaction). You # might also need to raise shared_buffers to support more connections. #superuser_reserved_connections = 3 # (change requires restart) #unix_socket_directory = '' # (change requires restart) #unix_socket_group = '' # (change requires restart) #unix_socket_permissions = 0777 # octal # (change requires restart) #bonjour_name = '' # defaults to the computer name # (change requires restart) # - Security & Authentication - #authentication_timeout = 1min # 1s-600s #ssl = off # (change requires restart) #password_encryption = on #db_user_namespace = off # Kerberos #krb_server_keyfile = '' # (change requires restart) #krb_srvname = 'postgres' # (change requires restart) #krb_server_hostname = '' # empty string matches any keytab entry # (change requires restart) #krb_caseins_users = off # (change requires restart) # - TCP Keepalives - # see 'man 7 tcp' for details #tcp_keepalives_idle = 0 # TCP_KEEPIDLE, in seconds; # 0 selects the system default #tcp_keepalives_interval = 0 # TCP_KEEPINTVL, in seconds; # 0 selects the system default #tcp_keepalives_count = 0 # TCP_KEEPCNT; # 0 selects the system default #--------------------------------------------------------------------------- # RESOURCE USAGE (except WAL) #--------------------------------------------------------------------------- # - Memory - shared_buffers = 64MB # min 128kB or max_connections*16kB # (change requires restart) #temp_buffers = 8MB # min 800kB #max_prepared_transactions = 5 # can be 0 or more # (change requires restart) # Note: increasing max_prepared_transactions costs ~600 bytes of shared memory # per transaction slot, plus lock space (see max_locks_per_transaction). work_mem = 2MB # min 64kB maintenance_work_mem = 32MB # min 1MB #max_stack_depth = 2MB # min 100kB # - Free Space Map - max_fsm_pages = 204800 # min max_fsm_relations*16, 6 bytes each # (change requires restart) #max_fsm_relations = 1000 # min 100, ~70 bytes each # (change requires restart) # - Kernel Resource Usage - #max_files_per_process = 1000 # min 25 # (change requires restart) #shared_preload_libraries = '' # (change requires restart) # - Cost-Based Vacuum Delay - #vacuum_cost_delay = 0 # 0-1000 milliseconds #vacuum_cost_page_hit = 1 # 0-10000 credits #vacuum_cost_page_miss = 10 # 0-10000 credits #vacuum_cost_page_dirty = 20 # 0-10000 credits #vacuum_cost_limit = 200 # 0-10000 credits # - Background writer - #bgwriter_delay = 200ms # 10-10000ms between rounds #bgwriter_lru_percent = 1.0 # 0-100% of LRU buffers scanned/round #bgwriter_lru_maxpages = 5 # 0-1000 buffers max written/round #bgwriter_all_percent = 0.333 # 0-100% of all buffers scanned/round #bgwriter_all_maxpages = 5 # 0-1000 buffers max written/round #--------------------------------------------------------------------------- # WRITE AHEAD LOG #--------------------------------------------------------------------------- # - Settings - fsync = on # turns forced synchronization on or off #wal_sync_method = fsync # the default is the first option # supported by the operating system: # open_datasync # fdatasync # fsync # fsync_writethrough # open_sync #full_page_writes = on # recover from partial page writes #wal_buffers = 64kB # min 32kB # (change requires restart) commit_delay = 100000 # range 0-100000, in microseconds #commit_siblings = 5 # range 1-1000 # - Checkpoints - checkpoint_segments = 10 # in logfile segments, min 1, 16MB each #checkpoint_timeout = 5min # range 30s-1h #checkpoint_warning = 30s # 0 is off # - Archiving - #archive_command = '' # command to use to archive a logfile segment #archive_timeout = 0 # force a logfile segment switch after this # many seconds; 0 is off #--------------------------------------------------------------------------- # QUERY TUNING #--------------------------------------------------------------------------- # - Planner Method Configuration - #enable_bitmapscan = on #enable_hashagg = on #enable_hashjoin = on #enable_indexscan = on #enable_mergejoin = on #enable_nestloop = on #enable_seqscan = on #enable_sort = on #enable_tidscan = on # - Planner Cost Constants - #seq_page_cost = 1.0 # measured on an arbitrary scale #random_page_cost = 4.0 # same scale as above #cpu_tuple_cost = 0.01 # same scale as above #cpu_index_tuple_cost = 0.005 # same scale as above #cpu_operator_cost = 0.0025 # same scale as above #effective_cache_size = 128MB # - Genetic Query Optimizer - #geqo = on #geqo_threshold = 12 #geqo_effort = 5 # range 1-10 #geqo_pool_size = 0 # selects default based on effort #geqo_generations = 0 # selects default based on effort #geqo_selection_bias = 2.0 # range 1.5-2.0 # - Other Planner Options - #default_statistics_target = 10 # range 1-1000 #constraint_exclusion = off #from_collapse_limit = 8 #join_collapse_limit = 8 # 1 disables collapsing of explicit # JOINs #--------------------------------------------------------------------------- # ERROR REPORTING AND LOGGING #--------------------------------------------------------------------------- # - Where to Log - log_destination = 'stderr' # Valid values are combinations of # stderr, syslog and eventlog, # depending on platform. # This is used when logging to stderr: redirect_stderr = on # Enable capturing of stderr into log # files # (change requires restart) # These are only used if redirect_stderr is on: log_directory = '../../logs' # Directory where log files are written # Can be absolute or relative to PGDATA log_filename = 'hqdb-%Y-%m-%d.log' # Log file name pattern. # Can include strftime() escapes #log_truncate_on_rotation = off # If on, any existing log file of the same # name as the new log file will be # truncated rather than appended to. But # such truncation only occurs on # time-driven rotation, not on restarts # or size-driven rotation. Default is # off, meaning append to existing files # in all cases. log_rotation_age = 1d # Automatic rotation of logfiles will # happen after that time. 0 to # disable. #log_rotation_size = 10MB # Automatic rotation of logfiles will # happen after that much log # output. 0 to disable. # These are relevant when logging to syslog: #syslog_facility = 'LOCAL0' #syslog_ident = 'postgres' # - When to Log - #client_min_messages = notice # Values, in order of decreasing detail: # debug5 # debug4 # debug3 # debug2 # debug1 # log # notice # warning # error #log_min_messages = notice # Values, in order of decreasing detail: # debug5 # debug4 # debug3 # debug2 # debug1 # info # notice # warning # error # log # fatal # panic #log_error_verbosity = default # terse, default, or verbose messages #log_min_error_statement = error # Values in order of increasing severity: # debug5 # debug4 # debug3 # debug2 # debug1 # info # notice # warning # error # fatal # panic (effectively off) log_min_duration_statement = 10000 # -1 is disabled, 0 logs all statements # and their durations. #silent_mode = off # DO NOT USE without syslog or # redirect_stderr # (change requires restart) # - What to Log - #debug_print_parse = off #debug_print_rewritten = off #debug_print_plan = off #debug_pretty_print = off #log_connections = off #log_disconnections = off #log_duration = off #log_line_prefix = '' # Special values: # %u = user name # %d = database name # %r = remote host and port # %h = remote host # %p = PID # %t = timestamp (no milliseconds) # %m = timestamp with milliseconds # %i = command tag # %c = session id # %l = session line number # %s = session start timestamp # %x = transaction id # %q = stop here in non-session # processes # %% = '%' # e.g. '<%u%%%d> ' #log_statement = 'none' # none, ddl, mod, all #log_hostname = off #--------------------------------------------------------------------------- # RUNTIME STATISTICS #--------------------------------------------------------------------------- # - Query/Index Statistics Collector - #stats_command_string = on #update_process_title = on stats_start_collector = on # needed for block or row stats # (change requires restart) stats_block_level = on stats_row_level = on stats_reset_on_server_start = off # (change requires restart) # - Statistics Monitoring - #log_parser_stats = off #log_planner_stats = off #log_executor_stats = off #log_statement_stats = off #--------------------------------------------------------------------------- # AUTOVACUUM PARAMETERS #--------------------------------------------------------------------------- #autovacuum = off # enable autovacuum subprocess? # 'on' requires stats_start_collector # and stats_row_level to also be on #autovacuum_naptime = 1min # time between autovacuum runs #autovacuum_vacuum_threshold = 500 # min # of tuple updates before # vacuum #autovacuum_analyze_threshold = 250 # min # of tuple updates before # analyze #autovacuum_vacuum_scale_factor = 0.2 # fraction of rel size before # vacuum #autovacuum_analyze_scale_factor = 0.1 # fraction of rel size before # analyze #autovacuum_freeze_max_age = 200000000 # maximum XID age before forced vacuum # (change requires restart) #autovacuum_vacuum_cost_delay = -1 # default vacuum cost delay for # autovacuum, -1 means use # vacuum_cost_delay #autovacuum_vacuum_cost_limit = -1 # default vacuum cost limit for # autovacuum, -1 means use # vacuum_cost_limit #--------------------------------------------------------------------------- # CLIENT CONNECTION DEFAULTS #--------------------------------------------------------------------------- # - Statement Behavior - #search_path = '"$user",public' # schema names #default_tablespace = '' # a tablespace name, '' uses # the default #check_function_bodies = on #default_transaction_isolation = 'read committed' #default_transaction_read_only = off #statement_timeout = 0 # 0 is disabled #vacuum_freeze_min_age = 100000000 # - Locale and Formatting - datestyle = 'iso, mdy' #timezone = unknown # actually, defaults to TZ # environment setting #timezone_abbreviations = 'Default' # select the set of available timezone # abbreviations. Currently, there are # Default # Australia # India # However you can also create your own # file in share/timezonesets/. #extra_float_digits = 0 # min -15, max 2 #client_encoding = sql_ascii # actually, defaults to database # encoding # These settings are initialized by initdb -- they might be changed lc_messages = 'C' # locale for system error message # strings lc_monetary = 'C' # locale for monetary formatting lc_numeric = 'C' # locale for number formatting lc_time = 'C' # locale for time formatting # - Other Defaults - #explain_pretty_print = on #dynamic_library_path = '$libdir' #local_preload_libraries = '' #--------------------------------------------------------------------------- # LOCK MANAGEMENT #--------------------------------------------------------------------------- #deadlock_timeout = 1s #max_locks_per_transaction = 64 # min 10 # (change requires restart) # Note: each lock table slot uses ~270 bytes of shared memory, and there are # max_locks_per_transaction * (max_connections + max_prepared_transactions) # lock table slots. #--------------------------------------------------------------------------- # VERSION/PLATFORM COMPATIBILITY #--------------------------------------------------------------------------- # - Previous Postgres Versions - #add_missing_from = off #array_nulls = on #backslash_quote = safe_encoding # on, off, or safe_encoding #default_with_oids = off #escape_string_warning = on #standard_conforming_strings = off #regex_flavor = advanced # advanced, extended, or basic #sql_inheritance = on # - Other Platforms & Clients - #transform_null_equals = off #--------------------------------------------------------------------------- # CUSTOMIZED OPTIONS #--------------------------------------------------------------------------- #custom_variable_classes = '' # list of custom variable class names SELECT * FROM pg_stat_activity; datid | datname | procpid | usesysid | usename | current_query | waiting | query_start | backend_start | client_addr | client_port -------+---------+---------+----------+---------+---------------------------------+---------+-------------------------------+-------------------------------+-------------+------------- 16384 | hqdb | 3267 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.036781+01 | 2011-02-08 15:51:20.02413+01 | 127.0.0.1 | 47892 16384 | hqdb | 3268 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.050994+01 | 2011-02-08 15:51:20.047393+01 | 127.0.0.1 | 47893 16384 | hqdb | 3269 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.056661+01 | 2011-02-08 15:51:20.053201+01 | 127.0.0.1 | 47894 16384 | hqdb | 3271 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.062351+01 | 2011-02-08 15:51:20.058822+01 | 127.0.0.1 | 47895 16384 | hqdb | 3272 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.068328+01 | 2011-02-08 15:51:20.064517+01 | 127.0.0.1 | 47896 16384 | hqdb | 3273 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.07444+01 | 2011-02-08 15:51:20.070755+01 | 127.0.0.1 | 47897 16384 | hqdb | 3274 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.080941+01 | 2011-02-08 15:51:20.076983+01 | 127.0.0.1 | 47898 16384 | hqdb | 3275 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.08741+01 | 2011-02-08 15:51:20.083697+01 | 127.0.0.1 | 47899 16384 | hqdb | 3276 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:20.093597+01 | 2011-02-08 15:51:20.089977+01 | 127.0.0.1 | 47900 16384 | hqdb | 3277 | 10 | hqadmin | <IDLE> in transaction | f | 2011-02-08 15:51:20.133974+01 | 2011-02-08 15:51:20.096149+01 | 127.0.0.1 | 47901 16384 | hqdb | 3308 | 10 | hqadmin | <IDLE> | f | 2011-02-09 10:49:27.402197+01 | 2011-02-08 15:51:29.826321+01 | 127.0.0.1 | 47902 16384 | hqdb | 3309 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.572395+01 | 2011-02-08 15:51:29.865243+01 | 127.0.0.1 | 47903 16384 | hqdb | 3310 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.586273+01 | 2011-02-08 15:51:29.874346+01 | 127.0.0.1 | 47904 16384 | hqdb | 3311 | 10 | hqadmin | <IDLE> | f | 2011-02-09 10:10:03.024088+01 | 2011-02-08 15:51:29.883598+01 | 127.0.0.1 | 47905 16384 | hqdb | 3312 | 10 | hqadmin | <IDLE> in transaction | f | 2011-02-08 15:51:35.804457+01 | 2011-02-08 15:51:29.892925+01 | 127.0.0.1 | 47906 16384 | hqdb | 3418 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.580207+01 | 2011-02-08 15:51:55.56911+01 | 127.0.0.1 | 47910 16384 | hqdb | 3419 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.59781+01 | 2011-02-08 15:51:55.588609+01 | 127.0.0.1 | 47911 16384 | hqdb | 3422 | 10 | hqadmin | <IDLE> | f | 2011-02-09 10:10:02.668836+01 | 2011-02-08 15:51:55.603076+01 | 127.0.0.1 | 47914 16384 | hqdb | 3421 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.770427+01 | 2011-02-08 15:51:55.603086+01 | 127.0.0.1 | 47913 16384 | hqdb | 3420 | 10 | hqadmin | <IDLE> | f | 2011-02-08 15:51:55.680785+01 | 2011-02-08 15:51:55.637058+01 | 127.0.0.1 | 47912 16384 | hqdb | 18233 | 10 | hqadmin | SELECT * FROM pg_stat_activity; | f | 2011-02-09 10:49:29.688949+01 | 2011-02-09 10:48:13.031475+01 | | -1 (21 rows)

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  • Postgres cannot connect to server

    - by user1408935
    Super stumped by why Postgres isn't working on a new app I just started. I've got it working for one app already. I'm using postgres.app, and it's running. I started a new app with rails new depot -d postgresql and then I went into the database.yml file and changed username to my $USER (which is what it is for the other app, which is working). So now my database.yml file has this development section: development: adapter: postgresql encoding: unicode database: depot_development pool: 5 username: <username> password: But when I run "rake db:create" or "rake db:create:all" I still got this error (in full, cause I don't know what's relevant): Couldn't create database for {"adapter"=>"postgresql", "encoding"=>"unicode", "database"=>"depot_development", "pool"=>5, "username"=>"<username>", "password"=>nil} could not connect to server: Permission denied Is the server running locally and accepting connections on Unix domain socket "/var/pgsql_socket/.s.PGSQL.5432"? /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/postgresql_adapter.rb:1213:in `initialize' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/postgresql_adapter.rb:1213:in `new' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/postgresql_adapter.rb:1213:in `connect' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/postgresql_adapter.rb:329:in `initialize' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/postgresql_adapter.rb:28:in `new' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/postgresql_adapter.rb:28:in `postgresql_connection' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_pool.rb:309:in `new_connection' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_pool.rb:319:in `checkout_new_connection' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_pool.rb:241:in `block (2 levels) in checkout' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_pool.rb:236:in `loop' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_pool.rb:236:in `block in checkout' /Users/<username>/.rvm/rubies/ruby-1.9.3-p194/lib/ruby/1.9.1/monitor.rb:211:in `mon_synchronize' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_pool.rb:233:in `checkout' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_pool.rb:96:in `block in connection' /Users/<username>/.rvm/rubies/ruby-1.9.3-p194/lib/ruby/1.9.1/monitor.rb:211:in `mon_synchronize' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_pool.rb:95:in `connection' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_pool.rb:404:in `retrieve_connection' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_specification.rb:170:in `retrieve_connection' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/connection_adapters/abstract/connection_specification.rb:144:in `connection' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/railties/databases.rake:107:in `rescue in create_database' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/railties/databases.rake:51:in `create_database' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/railties/databases.rake:40:in `block (3 levels) in <top (required)>' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/railties/databases.rake:40:in `each' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/gems/activerecord-3.2.8/lib/active_record/railties/databases.rake:40:in `block (2 levels) in <top (required)>' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/task.rb:205:in `call' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/task.rb:205:in `block in execute' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/task.rb:200:in `each' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/task.rb:200:in `execute' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/task.rb:158:in `block in invoke_with_call_chain' /Users/<username>/.rvm/rubies/ruby-1.9.3-p194/lib/ruby/1.9.1/monitor.rb:211:in `mon_synchronize' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/task.rb:151:in `invoke_with_call_chain' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/task.rb:144:in `invoke' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/application.rb:116:in `invoke_task' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/application.rb:94:in `block (2 levels) in top_level' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/application.rb:94:in `each' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/application.rb:94:in `block in top_level' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/application.rb:133:in `standard_exception_handling' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/application.rb:88:in `top_level' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/application.rb:66:in `block in run' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/application.rb:133:in `standard_exception_handling' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/lib/rake/application.rb:63:in `run' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/gems/rake-0.9.2.2/bin/rake:33:in `<top (required)>' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/bin/rake:19:in `load' /Users/<username>/.rvm/gems/ruby-1.9.3-p194@global/bin/rake:19:in `<main>' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/bin/ruby_noexec_wrapper:14:in `eval' /Users/<username>/.rvm/gems/ruby-1.9.3-p194/bin/ruby_noexec_wrapper:14:in `<main>' Couldn't create database for {"adapter"=>"postgresql", "encoding"=>"unicode", "database"=>"depot_test", "pool"=>5, "username"=>"<username>", "password"=>nil} I have tried createdb depot_development I have tried going into the psql environment and listing users (which included my username among them). In the same psql environment, I tried CREATE DATABASE depot; I've made sure that the pg gem is installed with bundle install, I've run "pg_ctl start", to which I got this response: pg_ctl: no database directory specified and environment variable PGDATA unset I ran "ps aux | grep postgres" to make sure postgres was running, to which I got this in return (which looks like it's doing OK, right?): <username> 10390 0.4 0.0 2425480 180 s000 R+ 6:15PM 0:00.00 grep postgres <username> 2907 0.0 0.0 2441604 464 ?? Ss 6:17PM 0:02.31 postgres: stats collector process <username> 2906 0.0 0.0 2445520 1664 ?? Ss 6:17PM 0:02.33 postgres: autovacuum launcher process <username> 2905 0.0 0.0 2445388 600 ?? Ss 6:17PM 0:09.25 postgres: wal writer process <username> 2904 0.0 0.0 2445388 1252 ?? Ss 6:17PM 0:12.08 postgres: writer process <username> 2902 0.0 0.0 2445388 3688 ?? S 6:17PM 0:00.54 /Applications/Postgres.app/Contents/MacOS/bin/postgres -D /Users/<username>/Library/Application Support/Postgres/var -p5432 The short of it, is I've been troubleshooting for a WHILE and have NO idea what's wrong. Any ideas? I'd really appreciate it, cause I'm pretty new to Rails, and this is a pretty disheartening roadblock. Thanks! EDIT -- Per request, posting the successful database.yml . It seems the difference is the inclusion of a password: development: adapter: postgresql encoding: unicode database: *******_development pool: 5 username: ******* password: ******* EDIT2 -- When I add a password to the .yml file, then run rake db:create again, I get this error. rake aborted! No Rakefile found (looking for: rakefile, Rakefile, rakefile.rb, Rakefile.rb)

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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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  • add a from to backup routine

    - by Gerard Flynn
    hi how do you put a process bar and button onto this code i have class and want to add a gui on to the code using System; using System.Collections.Generic; using System.ComponentModel; using System.Data; using System.Drawing; using System.Text; using System.Windows.Forms; using System.Data.SqlClient; using System.IO; using System.Threading; using Tamir.SharpSsh; using System.Security.Cryptography; using ICSharpCode.SharpZipLib.Checksums; using ICSharpCode.SharpZipLib.Zip; using ICSharpCode.SharpZipLib.GZip; namespace backup { public partial class Form1 : Form { public Form1() { InitializeComponent(); } /// <summary> /// Summary description for Class1. /// </summary> public class Backup { private string dbName; private string dbUsername; private string dbPassword; private static string baseDir; private string backupName; private static bool isBackup; private string keyString; private string ivString; private string[] backupDirs = new string[0]; private string[] excludeDirs = new string[0]; private ZipOutputStream zipOutputStream; private string backupFile; private string zipFile; private string encryptedFile; static void Main() { Backup.Log("BackupUtility loaded"); try { new Backup(); if (!isBackup) MessageBox.Show("Restore complete"); } catch (Exception e) { Backup.Log(e.ToString()); if (!isBackup) MessageBox.Show("Error restoring!\r\n" + e.Message); } } private void LoadAppSettings() { this.backupName = System.Configuration.ConfigurationSettings.AppSettings["BackupName"].ToString(); this.dbName = System.Configuration.ConfigurationSettings.AppSettings["DBName"].ToString(); this.dbUsername = System.Configuration.ConfigurationSettings.AppSettings["DBUsername"].ToString(); this.dbPassword = System.Configuration.ConfigurationSettings.AppSettings["DBPassword"].ToString(); //default to using where we are executing this assembly from Backup.baseDir = System.Reflection.Assembly.GetExecutingAssembly().Location.Substring(0, System.Reflection.Assembly.GetExecutingAssembly().Location.LastIndexOf("\\")) + "\\"; Backup.isBackup = bool.Parse(System.Configuration.ConfigurationSettings.AppSettings["IsBackup"].ToString()); this.keyString = System.Configuration.ConfigurationSettings.AppSettings["KeyString"].ToString(); this.ivString = System.Configuration.ConfigurationSettings.AppSettings["IVString"].ToString(); this.backupDirs = GetSetting("BackupDirs", ','); this.excludeDirs = GetSetting("ExcludeDirs", ','); } private string[] GetSetting(string settingName, char delimiter) { if (System.Configuration.ConfigurationSettings.AppSettings[settingName] != null) { string settingVal = System.Configuration.ConfigurationSettings.AppSettings[settingName].ToString(); if (settingVal.Length > 0) return settingVal.Split(delimiter); } return new string[0]; } public Backup() { this.LoadAppSettings(); if (isBackup) this.DoBackup(); else this.DoRestore(); Log("Finished"); } private void DoRestore() { System.Windows.Forms.OpenFileDialog fileDialog = new System.Windows.Forms.OpenFileDialog(); fileDialog.Title = "Choose .encrypted file"; fileDialog.Filter = "Encrypted files (*.encrypted)|*.encrypted|All files (*.*)|*.*"; fileDialog.InitialDirectory = Backup.baseDir; if (fileDialog.ShowDialog() == System.Windows.Forms.DialogResult.OK) { //string encryptedFile = GetFileName("encrypted"); string encryptedFile = fileDialog.FileName; string decryptedFile = this.GetDecryptedFilename(encryptedFile); //string originalFile = GetFileName("original"); this.Decrypt(encryptedFile, decryptedFile); //this.UnzipFile(decryptedFile, originalFile); } } //use the same filename as the backup except replace ".encrypted" with ".decrypted.zip" private string GetDecryptedFilename(string encryptedFile) { string name = encryptedFile.Substring(0, encryptedFile.LastIndexOf(".")); name += ".decrypted.zip"; return name; } private void DoBackup() { this.backupFile = GetFileName("bak"); this.zipFile = GetFileName("zip"); this.encryptedFile = GetFileName("encrypted"); this.DeleteFiles(); this.zipOutputStream = new ZipOutputStream(File.Create(zipFile)); try { //backup database first if (this.dbName.Length > 0) { this.BackupDB(backupFile); this.ZipFile(backupFile, this.GetName(backupFile)); } //zip any directories specified in config file this.ZipUserSpecifiedFilesAndDirectories(this.backupDirs); } finally { this.zipOutputStream.Finish(); this.zipOutputStream.Close(); } this.Encrypt(zipFile, encryptedFile); this.SCPFile(encryptedFile); this.DeleteFiles(); } /// <summary> /// Deletes any files created by the backup process, namely the DB backup file, /// the zip of all files backuped up, and the encrypred zip file /// </summary> private void DeleteFiles() { File.Delete(this.backupFile); File.Delete(this.zipFile); ///File.Delete(this.encryptedFile); } private void ZipUserSpecifiedFilesAndDirectories(string[] fileNames) { foreach (string fileName in fileNames) { string name = fileName.Trim(); if (name.Length > 0) { Log("Zipping " + name); this.ZipFile(name, this.GetNameFromDir(name)); } } } private void SCPFile(string inputPath) { string sshServer = System.Configuration.ConfigurationSettings.AppSettings["SSHServer"].ToString(); string sshUsername = System.Configuration.ConfigurationSettings.AppSettings["SSHUsername"].ToString(); string sshPassword = System.Configuration.ConfigurationSettings.AppSettings["SSHPassword"].ToString(); if (sshServer.Length > 0 && sshUsername.Length > 0 && sshPassword.Length > 0) { Scp scp = new Scp(sshServer, sshUsername, sshPassword); //Copy a file from local machine to remote SSH server scp.Connect(); Log("Connected to " + sshServer); //scp.Put(inputPath, "/home/wal/temp.txt"); scp.Put(inputPath, GetName(inputPath)); scp.Close(); } else { Log("Not SCP as missing login details"); } } private string GetName(string inputPath) { FileInfo info = new FileInfo(inputPath); return info.Name; } private string GetNameFromDir(string inputPath) { DirectoryInfo info = new DirectoryInfo(inputPath); return info.Name; } private static void Log(string msg) { try { string toLog = DateTime.Now.ToString() + ": " + msg; System.Diagnostics.Debug.WriteLine(toLog); System.IO.FileStream fs = new System.IO.FileStream(baseDir + "app.log", System.IO.FileMode.OpenOrCreate, System.IO.FileAccess.ReadWrite); System.IO.StreamWriter m_streamWriter = new System.IO.StreamWriter(fs); m_streamWriter.BaseStream.Seek(0, System.IO.SeekOrigin.End); m_streamWriter.WriteLine(toLog); m_streamWriter.Flush(); m_streamWriter.Close(); fs.Close(); } catch (Exception e) { Console.WriteLine(e.ToString()); } } private byte[] GetFileBytes(string path) { FileStream stream = new FileStream(path, FileMode.Open); byte[] bytes = new byte[stream.Length]; stream.Read(bytes, 0, bytes.Length); stream.Close(); return bytes; } private void WriteFileBytes(byte[] bytes, string path) { FileStream stream = new FileStream(path, FileMode.Create); stream.Write(bytes, 0, bytes.Length); stream.Close(); } private void UnzipFile(string inputPath, string outputPath) { ZipInputStream zis = new ZipInputStream(File.OpenRead(inputPath)); ZipEntry theEntry = zis.GetNextEntry(); FileStream streamWriter = File.Create(outputPath); int size = 2048; byte[] data = new byte[2048]; while (true) { size = zis.Read(data, 0, data.Length); if (size > 0) { streamWriter.Write(data, 0, size); } else { break; } } streamWriter.Close(); zis.Close(); } private bool ExcludeDir(string dirName) { foreach (string excludeDir in this.excludeDirs) { if (dirName == excludeDir) return true; } return false; } private void ZipFile(string inputPath, string zipName) { FileAttributes fa = File.GetAttributes(inputPath); if ((fa & FileAttributes.Directory) != 0) { string dirName = zipName + "/"; ZipEntry entry1 = new ZipEntry(dirName); this.zipOutputStream.PutNextEntry(entry1); string[] subDirs = Directory.GetDirectories(inputPath); //create directories first foreach (string subDir in subDirs) { DirectoryInfo info = new DirectoryInfo(subDir); string name = info.Name; if (this.ExcludeDir(name)) Log("Excluding " + dirName + name); else this.ZipFile(subDir, dirName + name); } //then store files string[] fileNames = Directory.GetFiles(inputPath); foreach (string fileName in fileNames) { FileInfo info = new FileInfo(fileName); string name = info.Name; this.ZipFile(fileName, dirName + name); } } else { Crc32 crc = new Crc32(); this.zipOutputStream.SetLevel(6); // 0 - store only to 9 - means best compression FileStream fs = null; try { fs = File.OpenRead(inputPath); } catch (IOException ioEx) { Log("WARNING! " + ioEx.Message);//might be in use, skip file in this case } if (fs != null) { byte[] buffer = new byte[fs.Length]; fs.Read(buffer, 0, buffer.Length); ZipEntry entry = new ZipEntry(zipName); entry.DateTime = DateTime.Now; // set Size and the crc, because the information // about the size and crc should be stored in the header // if it is not set it is automatically written in the footer. // (in this case size == crc == -1 in the header) // Some ZIP programs have problems with zip files that don't store // the size and crc in the header. entry.Size = fs.Length; fs.Close(); crc.Reset(); crc.Update(buffer); entry.Crc = crc.Value; this.zipOutputStream.PutNextEntry(entry); this.zipOutputStream.Write(buffer, 0, buffer.Length); } } } private void Encrypt(string inputPath, string outputPath) { RijndaelManaged rijndaelManaged = new RijndaelManaged(); byte[] encrypted; byte[] toEncrypt; //Create a new key and initialization vector. //myRijndael.GenerateKey(); //myRijndael.GenerateIV(); /*des.GenerateKey(); des.GenerateIV(); string temp1 = Convert.ToBase64String(des.Key); string temp2 = Convert.ToBase64String(des.IV);*/ //Get the key and IV. byte[] key = Convert.FromBase64String(keyString); byte[] IV = Convert.FromBase64String(ivString); //Get an encryptor. ICryptoTransform encryptor = rijndaelManaged.CreateEncryptor(key, IV); //Encrypt the data. MemoryStream msEncrypt = new MemoryStream(); CryptoStream csEncrypt = new CryptoStream(msEncrypt, encryptor, CryptoStreamMode.Write); //Convert the data to a byte array. toEncrypt = this.GetFileBytes(inputPath); //Write all data to the crypto stream and flush it. csEncrypt.Write(toEncrypt, 0, toEncrypt.Length); csEncrypt.FlushFinalBlock(); //Get encrypted array of bytes. encrypted = msEncrypt.ToArray(); WriteFileBytes(encrypted, outputPath); } private void Decrypt(string inputPath, string outputPath) { RijndaelManaged myRijndael = new RijndaelManaged(); //DES des = new DESCryptoServiceProvider(); byte[] key = Convert.FromBase64String(keyString); byte[] IV = Convert.FromBase64String(ivString); byte[] encrypted = this.GetFileBytes(inputPath); byte[] fromEncrypt; //Get a decryptor that uses the same key and IV as the encryptor. ICryptoTransform decryptor = myRijndael.CreateDecryptor(key, IV); //Now decrypt the previously encrypted message using the decryptor // obtained in the above step. MemoryStream msDecrypt = new MemoryStream(encrypted); CryptoStream csDecrypt = new CryptoStream(msDecrypt, decryptor, CryptoStreamMode.Read); fromEncrypt = new byte[encrypted.Length]; //Read the data out of the crypto stream. int bytesRead = csDecrypt.Read(fromEncrypt, 0, fromEncrypt.Length); byte[] readBytes = new byte[bytesRead]; Array.Copy(fromEncrypt, 0, readBytes, 0, bytesRead); this.WriteFileBytes(readBytes, outputPath); } private string GetFileName(string extension) { return baseDir + backupName + "_" + DateTime.Now.ToString("yyyyMMdd") + "." + extension; } private void BackupDB(string backupPath) { string sql = @"DECLARE @Date VARCHAR(300), @Dir VARCHAR(4000) --Get today date SET @Date = CONVERT(VARCHAR, GETDATE(), 112) --Set the directory where the back up file is stored SET @Dir = '"; sql += backupPath; sql += @"' --create a 'device' to write to first EXEC sp_addumpdevice 'disk', 'temp_device', @Dir --now do the backup BACKUP DATABASE " + this.dbName; sql += @" TO temp_device WITH FORMAT --Drop the device EXEC sp_dropdevice 'temp_device' "; //Console.WriteLine("sql="+sql); Backup.Log("Starting backup of " + this.dbName); ExecuteSQL(sql); } /// <summary> /// Executes the specified SQL /// Returns true if no errors were encountered during execution /// </summary> /// <param name="procedureName"></param> private void ExecuteSQL(string sql) { SqlConnection conn = new SqlConnection(this.GetDBConnectString()); try { SqlCommand comm = new SqlCommand(sql, conn); conn.Open(); comm.ExecuteNonQuery(); } finally { conn.Close(); } } private string GetDBConnectString() { StringBuilder builder = new StringBuilder(); builder.Append("Data Source=127.0.0.1; User ID="); builder.Append(this.dbUsername); builder.Append("; Password="); builder.Append(this.dbPassword); builder.Append("; Initial Catalog="); builder.Append(this.dbName); builder.Append(";Connect Timeout=30"); return builder.ToString(); } } } }

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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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