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  • SDL_image/C++ OpenGL Program: IMG_Load() produces fuzzy images

    - by Kami
    I'm trying to load an image file and use it as a texture for a cube. I'm using SDL_image to do that. I used this image because I've found it in various file formats (tga, tif, jpg, png, bmp) The code : SDL_Surface * texture; //load an image to an SDL surface (i.e. a buffer) texture = IMG_Load("/Users/Foo/Code/xcode/test/lena.bmp"); if(texture == NULL){ printf("bad image\n"); exit(1); } //create an OpenGL texture object glGenTextures(1, &textureObjOpenGLlogo); //select the texture object you need glBindTexture(GL_TEXTURE_2D, textureObjOpenGLlogo); //define the parameters of that texture object //how the texture should wrap in s direction glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_S, GL_REPEAT); //how the texture should wrap in t direction glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_WRAP_T, GL_REPEAT); //how the texture lookup should be interpolated when the face is smaller than the texture glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_LINEAR); //how the texture lookup should be interpolated when the face is bigger than the texture glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_LINEAR); //send the texture image to the graphic card glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, texture->w, texture->h, 0, GL_RGB, GL_UNSIGNED_BYTE, texture-> pixels); //clean the SDL surface SDL_FreeSurface(texture); The code compiles without errors or warnings ! I've tired all the files formats but this always produces that ugly result : I'm using : SDL_image 1.2.9 & SDL 1.2.14 with XCode 3.2 under 10.6.2 Does anyone knows how to fix this ?

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  • Fuzzy Regex, Text Processing, Lexical Analysis?

    - by justinzane
    I'm not quite sure what terminology to search for, so my title is funky... Here is the workflow I've got: Semi-structured documents are scanned to file. The files are OCR'd to text. The text is parsed into Python objects The objects are serialized (to SQL, JSON, whatever) for use. The documents are structures like this: HEADER blah blah, Page ### blah Garbage text... 1. Question Text... continued until now. A. Choice text... adsadsf. B. Another Choice... 2. Another Question... I need to extract the questions and choices. The problem is that, because the text is OCR output, there are occasional strange substitutions like '2' - 'Z' which makes ordinary regular expressions useless. I've tried the Levenshtein module and it helps, but it requires prior knowledge of what edit distance is to be expected. I don't know whether I'm looking to create a parser? a lexer? something else? This has lead me down all kinds of interesting but nonrelevant paths. Guidance would be greatly appreciated. Oh, also, the text is generally from specific technical domains, so general spelling tools are not so helpful. Regarding the structure of the documents, there is no clear visual pattern -- like line breaks or indentation -- with the exception of the fact that "questions" usually begin a line. Crap on the document can cause characters to appear before the actual beginning of the line, which means that something along the lines of r'^[0-9]+' does not reliably work. Though the "questions" always begin with an int, a period and a space; the OCR can substitute other characters or skip characters. This is not so much a problem with Tesseract or Cunieform, rather with the poor quality of the paper documents. # Note: for the project in question, it was decided that having a human prep the OCR'd text was better that spending the time coding a solution. I'd still love good pointers, however.

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  • Using cascade in NHibernate

    - by Tyler
    I have two classes, call them Monkey and Banana, with a one-to-many bidirectional relationship. Monkey monkey = new Monkey(); Banana banana = new Banana(); monkey.Bananas.Add(banana); banana.Monkey = monkey; hibernateService.Save(banana); When I run that chunk of code, I want both monkey and banana to be persisted. However, it's only persisting both when I explicitly save the monkey and not vice versa. Initially, this made sense since only my Monkey.hbm.xml had a mapping with cascade="all". <set name="Bananas" inverse="true" cascade="all"> <key column="Id"/> <one-to-many class="Banana"/> </set> I figured I just needed to add the following to my Banana.hbm.xml file: <many-to-one name="Monkey" column="Id" cascade="all" /> Unfortunately, this resulted in a Parameter index is out of range error when I tried to run the snippet of code. I investigated this error and found this post, but I still don't see what I'm doing wrong. I have the relationship mapped once on each side as far as I can tell. For full disclosure, here are the two mapping files: Monkey.hbm.xml <class name="Monkey" table="monkies" lazy="true"> <id name="Id"> <generator class="increment" /> </id> <property name="Name" /> <set name="Bananas" inverse="true" cascade="all"> <key column="Id"/> <one-to-many class="Banana"/> </set> </class> Banana.hbm.xml <class name="Banana" table="bananas" lazy="true"> <id name="Id"> <generator class="increment" /> </id> <property name="Name" /> <many-to-one name="Monkey" column="Id" cascade="all" /> </class>

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  • fuzzy DISTINCT Values

    - by user982853
    I have a database of real estate listings and need to return a list of neighborhoods. Right now I am using mysql DISTINCT which returns all of the distinct values. My probelm is that there is a lot of neighborhoods that have similar names: example: Park View Sub 1 Park View Park View Sub 2 Park View Sub 3 Great Lake Sub 1 Great Lake Sub 2 Great Lake Great Lake Sub 3 I am looking for an easy php or mysql solution that would recognize that "Park View" and "Great Lake" already exists and ONLY return "Park View" and "Great Lake". My initial thought is to some how get the sort order by length so that the short values are at the top and then loop through using strstr. This sound like a large task I am wondering if there is a function either in mysql or php that would easily do this.

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  • algorithm q: Fuzzy matching of structured data

    - by user86432
    I have a fairly small corpus of structured records sitting in a database. Given a tiny fraction of the information contained in a single record, submitted via a web form (so structured in the same way as the table schema), (let us call it the test record) I need to quickly draw up a list of the records that are the most likely matches for the test record, as well as provide a confidence estimate of how closely the search terms match a record. The primary purpose of this search is to discover whether someone is attempting to input a record that is duplicate to one in the corpus. There is a reasonable chance that the test record will be a dupe, and a reasonable chance the test record will not be a dupe. The records are about 12000 bytes wide and the total count of records is about 150,000. There are 110 columns in the table schema and 95% of searches will be on the top 5% most commonly searched columns. The data is stuff like names, addresses, telephone numbers, and other industry specific numbers. In both the corpus and the test record it is entered by hand and is semistructured within an individual field. You might at first blush say "weight the columns by hand and match word tokens within them", but it's not so easy. I thought so too: if I get a telephone number I thought that would indicate a perfect match. The problem is that there isn't a single field in the form whose token frequency does not vary by orders of magnitude. A telephone number might appear 100 times in the corpus or 1 time in the corpus. The same goes for any other field. This makes weighting at the field level impractical. I need a more fine-grained approach to get decent matching. My initial plan was to create a hash of hashes, top level being the fieldname. Then I would select all of the information from the corpus for a given field, attempt to clean up the data contained in it, and tokenize the sanitized data, hashing the tokens at the second level, with the tokens as keys and frequency as value. I would use the frequency count as a weight: the higher the frequency of a token in the reference corpus, the less weight I attach to that token if it is found in the test record. My first question is for the statisticians in the room: how would I use the frequency as a weight? Is there a precise mathematical relationship between n, the number of records, f(t), the frequency with which a token t appeared in the corpus, the probability o that a record is an original and not a duplicate, and the probability p that the test record is really a record x given the test and x contain the same t in the same field? How about the relationship for multiple token matches across multiple fields? Since I sincerely doubt that there is, is there anything that gets me close but is better than a completely arbitrary hack full of magic factors? Barring that, has anyone got a way to do this? I'm especially keen on other suggestions that do not involve maintaining another table in the database, such as a token frequency lookup table :). This is my first post on StackOverflow, thanks in advance for any replies you may see fit to give.

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  • Resolving Assemblies, the fuzzy way

    - by David Rutten
    Here's the setup: A pure DotNET class library is loaded by an unmanaged desktop application. The Class Library acts as a plugin. This plugin loads little baby plugins of its own (all DotNET Class Libraries), and it does so by reading the dll into memory as a byte-stream, then Assembly asm = Assembly.Load(COFF_Image); The problem arises when those little baby plugins have references to other dlls. Since they are loaded via the memory rather than directly from the disk, the framework often cannot find these referenced assemblies and is thus incapable of loading them. I can add an AssemblyResolver handler to my project and I can see these referenced assemblies drop past. I have a reasonably good idea about where to find these referenced assemblies on the disk, but how can I make sure that the Assmebly I load is the correct one? In short, how do I reliably go from the System.ResolveEventArgs.Name field to a dll file path, presuming I have a list of all the folders where this dll could be hiding)?

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  • One page of responsive site is blurry/fuzzy on iphone

    - by Gwendydd
    Here's a weird one. I'm developing a responsive site here: http://74.209.178.54:3000/index.html There are three pages built so far: the home page, the "Why" page, and the "Pricing" page. The Home and Why pages are just fine on my iPhone 4. The "Pricing" page is really blurry. And I don't just mean the images are blurry - absolutely everything is blurry: text, borders, backgrounds... Has anyone seen this before? Do you know what's happening?

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  • Any way to use a class extension method to support an interface method in C#?

    - by dudeNumber4
    Console app below compiles, but the interface cast fails at run time. Is there an easy way to make this work? namespace ConsoleApplication1 { class Monkey { public string Shock { get { return "Monkey has been shocked."; } } } static class MonkeyExtensionToSupportIWombat { public static string ShockTheMonkey( this Monkey m ) { return m.Shock; } } interface IWombat { string ShockTheMonkey(); } class Program { static void Main( string[] args ) { var monkey = new Monkey(); Console.WriteLine( "Shock the monkey without the interface: {0}", monkey.Shock ); IWombat wombat = monkey as IWombat; Console.WriteLine( "Shock the monkey with the interface: {0}", wombat.ShockTheMonkey() ); Console.ReadLine(); } } }

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  • Search Lucene with precise edit distances

    - by askullhead
    I would like to search a Lucene index with edit distances. For example, say, there is a document with a field FIRST_NAME; I want all documents with first names that are 1 edit distance away from, say, 'john'. I know that Lucene supports fuzzy searches (FIRST_NAME:john~) and takes a number between 0 and 1 to control the fuzziness. The problem (for me) is this number does not directly translate to an edit distance. And when the values in the documents are short strings (less than 3 characters) the fuzzy search has difficulty finding them. For example if there is a document with FIRST_NAME 'J' and I search for FIRST_NAME:I~0.0 I don't get anything back.

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  • How would you start automating my job?

    - by Jurily
    At my new job, we sell imported stuff. In order to be able to sell said stuff, currently the following things need to happen for every incoming shipment: Invoice arrives, in the form of an email attachment, Excel spreadsheet Monkey opens invoice, copy-pastes the relevant part of three columns into the relevant parts of a spreadsheet template, where extremely complex calculations happen, like =B2*550 Monkey sends this new spreadsheet to boss (email if lucky, printer otherwise), who sets the retail price Monkey opens the reply, then proceeds to input the data into the production database using a client program that is unusable on so many levels it's not even worth detailing Monkey fires up HyperTerminal, types in "AT", disconnect Monkey sends text messages and emails to customers using another part of the horrible client program, one at a time I want to change Monkey from myself to software wherever possible. I've never written anything that interfaces with email, Excel, databases or SMS before, but I'd be more than happy to learn if it saves me from this. Here's my uneducated wishlist: Monkey asks Thunderbird (mail server perhaps?) for the attachment Monkey tells Excel to dump the spreadsheet into a more Jurily-friendly format, like CSV or something Monkey parses the output, does the complex calculations // TODO: find a way to get the boss-generated prices with minimal manual labor involved Monkey connects to the database, inserts data Monkey spams costumers Is all this feasible? If yes, where do I start reading? How would you improve it? What language/framework do you think would be ideal for this? What would you do about the boss?

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  • Why won't Media Monkey add one particular folder of mp3's?

    - by ChrisF
    I'm using the latest and greatest version on Media Monkey (free version) and it won't find the mp3's in one particular folder in my music tree. It can see all the other files in the tree and the folder shows up when I click Add/Rescan files to the library... I have full control over the folder and all the files in the folder. The files play in Windows Media Player. The files play in Media Monkey if I right click and play from the context menu. All the tracks are at least 2 minutes long and over 5MB long and Media Monkey is set to ignore files shorter than 20KB and include all files regardless of length. There was an issue in that the that the genre of the tracks was set to "Classical" and the option that allows you to browse the classical music independently of the other music isn't enabled in the free version. It's a Gold version option only. I hadn't spotted that my other classical music was also missing from the library (I have rather a large library). Once I retagged the music with a different tag and tried to add the files again it reported that it added the tracks, but they still didn't show up in the library.

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  • after Bios screen appears, the purple screen appears with a red circle and a white line through it, saying cannot load Ubuntu 2D

    - by Felix
    After the Bios screen appears, the purple screen appears and says, "cannot load Ubuntu2D" Log off. Logging off is my only option. I am operating on a Dell Insoirion 11.10 Ubuntu system. I deleted the gnome because I read in the forum it slowed down the computer and I wanted to watch movies. I deleted Unity as well because I read terrible things about it and that it was not necessary for me. I realize my experimention in learning by adding and deleting things were not proper. I was just trying to learn and fix my sound. Please help. Thanks.

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  • Inverse Logistic Function / Reverse Sigmoid Function

    - by Chanq
    I am currently coding up a fuzzy logic library in java. I have found the equations for all the standard functions - Grade, inverseGrade, Triangle, Trapezoid, Gaussian. However, I can't find the inverse of the sigmoid/ logistic function. The way I have written the logistic function is java is : //f(x) = 1/(1+e(-x)) public double logistic(double x){ return (1/(1+(Math.exp(-x))); } But I can't work out or find the inverse anywhere. My algebraic/calculus abilities are fairly limited, hence why I haven't been able to work out the inverse of the function. Any hints or pointers would be a big help. Thanks

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  • What free expert system can You recommend (with higher functionality then CLIPS)?

    - by Martin
    Hi, I'm trying to find best free expert system, with the highest functionality. I know about CLIPS, but is there another system, for example being able to accept percent of confidence for each rule (fuzzy logic). I need it to know will I be able to do fast a short project using expert system, with highest functionality. But anyways, it's interesting is there an open source program that aims to gather different AI methods (whitch there are plenty of), and use them together. So I would be extremely thankeful for any info about more robust CLIPS, or similar programs. Thanks!

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  • Algorithm detect repeating/similiar strings in a corpus of data -- say email subjects, in Python

    - by RizwanK
    I'm downloading a long list of my email subject lines , with the intent of finding email lists that I was a member of years ago, and would want to purge them from my Gmail account (which is getting pretty slow.) I'm specifically thinking of newsletters that often come from the same address, and repeat the product/service/group's name in the subject. I'm aware that I could search/sort by the common occurrence of items from a particular email address (and I intend to), but I'd like to correlate that data with repeating subject lines.... Now, many subject lines would fail a string match, but "Google Friends : Our latest news" "Google Friends : What we're doing today" are more similar to each other than a random subject line, as is: "Virgin Airlines has a great sale today" "Take a flight with Virgin Airlines" So -- how can I start to automagically extract trends/examples of strings that may be more similar. Approaches I've considered and discarded ('because there must be some better way'): Extracting all the possible substrings and ordering them by how often they show up, and manually selecting relevant ones Stripping off the first word or two and then count the occurrence of each sub string Comparing Levenshtein distance between entries Some sort of string similarity index ... Most of these were rejected for massive inefficiency or likelyhood of a vast amount of manual intervention required. I guess I need some sort of fuzzy string matching..? In the end, I can think of kludgy ways of doing this, but I'm looking for something more generic so I've added to my set of tools rather than special casing for this data set. After this, I'd be matching the occurring of particular subject strings with 'From' addresses - I'm not sure if there's a good way of building a data structure that represents how likely/not two messages are part of the 'same email list' or by filtering all my email subjects/from addresses into pools of likely 'related' emails and not -- but that's a problem to solve after this one. Any guidance would be appreciated.

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  • Simplifying a four-dimensional rule table in Matlab: addressing rows and columns of each dimension

    - by Cate
    Hi all. I'm currently trying to automatically generate a set of fuzzy rules for a set of observations which contain four values for each observation, where each observation will correspond to a state (a good example is with Fisher's Iris Data). In Matlab I am creating a four dimensional rule table where a single cell (a,b,c,d) will contain the corresponding state. To reduce the table I am following the Hong and Lee method of row and column similarity checking but I am having difficulty understanding how to address the third and fourth dimensions' rows and columns. From the method it is my understanding that each dimension is addressed individually and if the rule is true, the table is simplified. The rules for merging are as follows: If all cells in adjacent columns or rows are the same. If two cells are the same or if either of them is empty in adjacent columns or rows and at least one cell in both is not empty. If all cells in a column or row are empty and if cells in its two adjacent columns or rows are the same, merge the three. If all cells in a column or row are empty and if cells in its two adjacent columns or rows are the same or either of them is empty, merge the three. If all cells in a column or row are empty and if all the non-empty cells in the column or row to its left have the same region, and all the non-empty cells in the column or row to its right have the same region, but one different from the previously mentioned region, merge these three columns into two parts. Now for the confusing bit. Simply checking if the entire row/column is the same as the adjacent (rule 1) seems simple enough: if (a,:,:,:) == (a+1,:,:,:) (:,b,:,:) == (:,b+1,:,:) (:,:,c,:) == (:,:,c+1,:) (:,:,:,d) == (:,:,:,d+1) is this correct? but to check if the elements in the row/column match, or either is zero (rules 2 and 4), I am a bit lost. Would it be something along these lines: for a = 1:20 for i = 1:length(b) if (a+1,i,:,:) == (a,i,:,:) ... else if (a+1,i,:,:) == 0 ... else if (a,i,:,:) == 0 etc. and for the third and fourth dimensions: for c = 1:20 for i = 1:length(a) if (i,:,c,:) == (i,:,c+1,:) ... else if (i,:,c+1,:) == 0 ... else if (i,:,c,:) == 0 etc. for d = 1:20 for i = 1:length(a) if (i,:,:,d) == (i,:,:,d+1) ... else if (i,:,:,d+1) == 0 ... else if (i,:,:,d) == 0 etc. even any help with four dimensional arrays would be useful as I'm so confused by the thought of more than three! I would advise you look at the paper to understand my meaning - they themselves have used the Iris data but only given an example with a 2D table. Thanks in advance, hopefully!

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  • Sync Your Pidgin Profile Across Multiple PCs with Dropbox

    - by Matthew Guay
    Pidgin is definitely our favorite universal chat client, but adding all of your chat accounts to multiple computers can be frustrating.  Here’s how you can easily transfer your Pidgin settings to other computers and keep them in sync using Dropbox. Getting Started Make sure you have both Pidgin and Dropbox installed on any computers you want to sync.  To sync Pidgin, you need to: Move your Pidgin profile folder on your first computer to Dropbox Create a symbolic link from the new folder in Dropbox to your old profile location Delete the default pidgin profile on your other computer, and create a symbolic link from your Dropbox Pidgin profile to the default Pidgin profile location This sounds difficult, but it’s actually easy if you follow these steps.  Here we already had all of our accounts setup in Pidgin in Windows 7, and then synced this profile with an Ubuntu and a XP computer with fresh Pidgin installs.  Our instructions for each OS are based on this, but just swap the sync order if your main Pidgin install is in XP or Ubuntu. Please Note:  Please make sure Pidgin isn’t running on your computer while you are making the changes! Sync Your Pidgin Profile from Windows 7 Here is Pidgin with our accounts already setup.  Our Pidgin profile has a Gtalk, MSN Messenger, and Facebook Chat account, and lots of log files. Let’s move this profile to Dropbox to keep it synced.  Exit Pidgin, and then enter %appdata% in the address bar in Explorer or press Win+R and enter %appdata%.  Select the .purple folder, which is your Pidgin profiles and settings folder, and press Ctrl+X to cut it. Browse to your Dropbox folder, and press Ctrl+V to paste the .purple folder there. Now we need to create the symbolic link.  Enter  “command” in your Start menu search, right-click on the Command Prompt shortcut, and select “Run as administrator”. We can now use the mklink command to create a symbolic link to the .purple folder.  In Command Prompt, enter the following and substitute username for your own username. mklink /D “C:\Users\username\Documents\My Dropbox\.purple” “C:\Users\username\AppData\Roaming\.purple” And that’s it!  You can open Pidgin now to make sure it still works as before, with your files being synced with Dropbox. Please Note:  These instructions work the same for Windows Vista.  Also, if you are syncing settings from another computer to Windows 7, then delete the .purple folder instead of cutting and pasting it, and reverse the order of the file paths when creating the symbolic link. Add your Pidgin Profile to Ubuntu Our Ubuntu computer had a clean install of Pidgin, so we didn’t need any of the information in its settings.  If you’ve run Pidgin, even without creating an account, you will need to first remove its settings folder.  Open your home folder, and click View, and then “Show Hidden Files” to see your settings folders. Select the .purple folder, and delete it. Now, to create the symbolic link, open Terminal and enter the following, substituting username for your username: ln –s /home/username/Dropbox/.purple /home/username/ Open Pidgin, and you will see all of your accounts that were on your other computer.  No usernames or passwords needed; everything is setup and ready to go.  Even your status is synced; we had our status set to Away in Windows 7, and it automatically came up the same in Ubuntu. Please Note: If your primary Pidgin account is in Ubuntu, then cut your .purple folder and paste it into your Dropbox folder instead.  Then, when creating the symbolic link, reverse the order of the folder paths. Add your Pidgin Profile to Windows XP In XP we also had a clean install of Pidgin.  If you’ve run Pidgin, even without creating an account, you will need to first remove its settings folder.  Click Start, the Run, and enter %appdata%. Delete your .purple folder. XP does not include a way to create a symbolic link, so we will use the free Junction tool from Sysinternals.  Download Junction (link below) and unzip the folder. Open Command Prompt (click Start, select All Programs, then Accessories, and select Command Prompt), and enter cd followed by the path of the folder where you saved Junction.   Now, to create the symbolic link, enter the following in Command Prompt, substituting username with your username. junction –d “C:\Documents and Settings\username\Application Data\.purple” “C:\Documents and Settings\username\My Documents\My Dropbox\.purple” Open Pidgin, and you will see all of your settings just as they were on your other computer.  Everything’s ready to go.   Please Note: If your primary Pidgin account is in Windows XP, then cut your .purple folder and paste it into your Dropbox folder instead.  Then, when creating the symbolic link, reverse the order of the folder paths. Conclusion This is a great way to keep all of your chat and IM accounts available from all of your computers.  You can easily access logs from chats you had on your desktop from your laptop, or if you add a chat account on your work computer you can use it seamlessly from your home computer that evening.  Now Pidgin is the universal chat client that is always ready whenever and wherever you need it! Links Downlaod Pidgin Download and signup for Dropbox Download Junction for XP Similar Articles Productive Geek Tips Add "My Dropbox" to Your Windows 7 Start MenuUse Multiple Firefox Profiles at the Same TimeEasily Add Facebook Chat to PidginPut Your Pidgin Buddy List into the Windows Vista SidebarBackup and Restore Firefox Profiles Easily TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 Download Free iPad Wallpapers at iPad Decor Get Your Delicious Bookmarks In Firefox’s Awesome Bar Manage Photos Across Different Social Sites With Dropico Test Drive Windows 7 Online Download Wallpapers From National Geographic Site Spyware Blaster v4.3

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  • Java code optimization leads to numerical inaccuracies and errors

    - by rano
    I'm trying to implement a version of the Fuzzy C-Means algorithm in Java and I'm trying to do some optimization by computing just once everything that can be computed just once. This is an iterative algorithm and regarding the updating of a matrix, the clusters x pixels membership matrix U, this is the update rule I want to optimize: where the x are the element of a matrix X (pixels x features) and v belongs to the matrix V (clusters x features). And m is a parameter that ranges from 1.1 to infinity. The distance used is the euclidean norm. If I had to implement this formula in a banal way I'd do: for(int i = 0; i < X.length; i++) { int count = 0; for(int j = 0; j < V.length; j++) { double num = D[i][j]; double sumTerms = 0; for(int k = 0; k < V.length; k++) { double thisDistance = D[i][k]; sumTerms += Math.pow(num / thisDistance, (1.0 / (m - 1.0))); } U[i][j] = (float) (1f / sumTerms); } } In this way some optimization is already done, I precomputed all the possible squared distances between X and V and stored them in a matrix D but that is not enough, since I'm cycling througn the elements of V two times resulting in two nested loops. Looking at the formula the numerator of the fraction is independent of the sum so I can compute numerator and denominator independently and the denominator can be computed just once for each pixel. So I came to a solution like this: int nClusters = V.length; double exp = (1.0 / (m - 1.0)); for(int i = 0; i < X.length; i++) { int count = 0; for(int j = 0; j < nClusters; j++) { double distance = D[i][j]; double denominator = D[i][nClusters]; double numerator = Math.pow(distance, exp); U[i][j] = (float) (1f / (numerator * denominator)); } } Where I precomputed the denominator into an additional column of the matrix D while I was computing the distances: for (int i = 0; i < X.length; i++) { for (int j = 0; j < V.length; j++) { double sum = 0; for (int k = 0; k < nDims; k++) { final double d = X[i][k] - V[j][k]; sum += d * d; } D[i][j] = sum; D[i][B.length] += Math.pow(1 / D[i][j], exp); } } By doing so I encounter numerical differences between the 'banal' computation and the second one that leads to different numerical value in U (not in the first iterates but soon enough). I guess that the problem is that exponentiate very small numbers to high values (the elements of U can range from 0.0 to 1.0 and exp , for m = 1.1, is 10) leads to ver y small values, whereas by dividing the numerator and the denominator and THEN exponentiating the result seems to be better numerically. The problem is it involves much more operations. Am I doing something wrong? Is there a possible solution to get both the code optimized and numerically stable? Any suggestion or criticism will be appreciated.

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  • Eculidean space and vector magnitude

    - by Starkers
    Below we have distances from the origin calculated in two different ways, giving the Euclidean distance, the Manhattan distance and the Chebyshev distance. Euclidean distance is what we use to calculate the magnitude of vectors in 2D/3D games, and that makes sense to me: Let's say we have a vector that gives us the range a spaceship with limited fuel can travel. If we calculated this with Manhattan metric, our ship could travel a distance of X if it were travelling horizontally or vertically, however the second it attempted to travel diagonally it could only tavel X/2! So like I say, Euclidean distance does make sense. However, I still don't quite get how we calculate 'real' distances from the vector's magnitude. Here are two points, purple at (2,2) and green at (3,3). We can take two points away from each other to derive a vector. Let's create a vector to describe the magnitude and direction of purple from green: |d| = purple - green |d| = (purple.x, purple.y) - (green.x, green.y) |d| = (2, 2) - (3, 3) |d| = <-1,-1> Let's derive the magnitude of the vector via Pythagoras to get a Euclidean measurement: euc_magnitude = sqrt((x*x)+(y*y)) euc_magnitude = sqrt((-1*-1)+(-1*-1)) euc_magnitude = sqrt((1)+(1)) euc_magnitude = sqrt(2) euc_magnitude = 1.41 Now, if the answer had been 1, that would make sense to me, because 1 unit (in the direction described by the vector) from the green is bang on the purple. But it's not. It's 1.41. 1.41 units is the direction described, to me at least, makes us overshoot the purple by almost half a unit: So what do we do to the magnitude to allow us to calculate real distances on our point graph? Worth noting I'm a beginner just working my way through theory. Haven't programmed a game in my life!

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  • As a code monkey, how to discuss programming with a guy who almost has a doctorate in computer science

    - by Peter Turner
    A friend of my wife's is coming over for dinner tonight and he is a lot smarter than me. What do we have in common, well... A Bachelor's in Computer Science, and that should be enough of a conversation starter. But he's nearly completed his doctoral studies and is light years ahead of me in his particular area, which I find fascinating but don't have any legit reason to care about (except for maybe a better way through heavy traffic - he's a combinatorics guy specializing in that I think) and I got married and had some kids and am a professional programmer for medical records software. We've got a lot in common, but there's a point where neither of us care or understand each other - although I really want to learn from him and I'm not certain he'd even want to talk about his work. So for all you doctors or code monkeys, what's a good conversation starter!

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  • What are the maths behind 'Raiden 2' purple laser?

    - by Aybe
    The path of the laser is affected by user input and enemies present on the screen. Here is a video, at 5:00 minutes the laser in question is shown : Raiden II (PS) - 1 Loop Clear - Part 2 UPDATE Here is a test using Inkscape, ship is at bottom, the first 4 enemies are targeted by the plasma. There seems to be a sort of pattern. I moved the ship first, then the handle from it to form a 45° angle, then while trying to fit the curve I found a pattern of parallel handles and continued so until I reached the last enemy. Update, 5/26/2012 : I started an XNA project using beziers, there is still some work needed, will update the question next week. Stay tuned ! Update : 5/30/2012 : It really seems that they are using Bézier curves, I think I will be able to replicate/imitate a plasma of such grade. There are two new topics I discovered since last time : Arc length, Runge's phenomenon, first one should help in having a linear movement possible over a Bézier curve, second should help in optimizing the number of vertices. Next time I will put a video so you can see the progress 8-)

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  • Using MinHash to find similiarities between 2 images

    - by Sung Meister
    I am using MinHash algorithm to find similar images between images. I have run across this post, How can I recognize slightly modified images? which pointed me to MinHash algorithm. Being a bit mathematically challenged, I was using a C# implementation from this blog post, Set Similarity and Min Hash. But while trying to use the implementation, I have run into 2 problems. What value should I set universe value to? When passing image byte array to HashSet, it only contains distinct byte values; thus comparing values from 1 ~ 256. What is this universe in MinHash? And what can I do to improve the C# MinHash implementation? Since HashSet<byte> contains values upto 256, similarity value always come out to 1. Here is the source that uses the C# MinHash implementation from Set Similarity and Min Hash: class Program { static void Main(string[] args) { var imageSet1 = GetImageByte(@".\Images\01.JPG"); var imageSet2 = GetImageByte(@".\Images\02.TIF"); //var app = new MinHash(256); var app = new MinHash(Math.Min(imageSet1.Count, imageSet2.Count)); double imageSimilarity = app.Similarity(imageSet1, imageSet2); Console.WriteLine("similarity = {0}", imageSimilarity); } private static HashSet<byte> GetImageByte(string imagePath) { using (var fs = new FileStream(imagePath, FileMode.Open, FileAccess.Read)) using (var br = new BinaryReader(fs)) { //List<int> bytes = br.ReadBytes((int)fs.Length).Cast<int>().ToList(); var bytes = new List<byte>(br.ReadBytes((int) fs.Length).ToArray()); return new HashSet<byte>(bytes); } } }

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  • Is this a variation of the traveling salesman problem?

    - by Ville Koskinen
    I'm interested in a function of two word lists, which would return an order agnostic edit distance between them. That is, the arguments would be two lists of (let's say space delimited) words and return value would be the minimum sum of the edit (or Levenshtein) distances of the words in the lists. Distance between "cat rat bat" and "rat bat cat" would be 0. Distance between "cat rat bat" and "fat had bad" would be the same as distance between "rat bat cat" and "had fat bad", 4. In the case the number of words in the lists are not the same, the shorter list would be padded with 0-length words. My intuition (which hasn't been nurtured with computer science classes) does not find any other solution than to use brute force: |had|fat|bad| a solution ---+---+---+---+ +---+---+---+ cat| 2 | 1 | 2 | | | 1 | | ---+---+---+---+ +---+---+---+ rat| 2 | 1 | 2 | | 3 | | | ---+---+---+---+ +---+---+---+ bat| 2 | 1 | 1 | | | | 4 | ---+---+---+---+ +---+---+---+ Starting from the first row, pick a column and go to the next rows without ever revisiting a column you have already visited. Do this over and over again until you've tried all combinations. To me this sounds a bit like the traveling salesman problem. Is it, and how would you solve my particular problem?

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  • How to calculate this string-dissimilarity function efficiently?

    - by ybungalobill
    Hello, I was looking for a string metric that have the property that moving around large blocks in a string won't affect the distance so much. So "helloworld" is close to "worldhello". Obviously Levenshtein distance and Longest common subsequence don't fulfill this requirement. Using Jaccard distance on the set of n-grams gives good results but has other drawbacks (it's a pseudometric and higher n results in higher penalty for changing single character). [original research] As I thought about it, what I'm looking for is a function f(A,B) such that f(A,B)+1 equals the minimum number of blocks that one have to divide A into (A1 ... An), apply a permutation on the blocks and get B: f("hello", "hello") = 0 f("helloworld", "worldhello") = 1 // hello world -> world hello f("abba", "baba") = 2 // ab b a -> b ab a f("computer", "copmuter") = 3 // co m p uter -> co p m uter This can be extended for A and B that aren't necessarily permutations of each other: any additional character that can't be matched is considered as one additional block. f("computer", "combuter") = 3 // com uter -> com uter, unmatched: p and b. Observing that instead of counting blocks we can count the number of pairs of indices that are taken apart by a permutation, we can write f(A,B) formally as: f(A,B) = min { C(P) | P:|A|?|B|, P is bijective, ?i?dom(P) A[P(i)]=B[P(i)] } C(P) = |A| + |B| - |dom(P)| - |{ i | i,i+1?dom(P) and P(i)+1=P(i+1) }| - 1 The problem is... guess what... ... that I'm not able to calculate this in polynomial time. Can someone suggest a way to do this efficiently? Or perhaps point me to already known metric that exhibits similar properties?

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