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• black and white pages not recognized by printer

  - by user46627

  I have a document which has color on about 25% of its pages. When I print it in the copy shop, the printer's technically supposed to recognize the b/w pages. However, all pages are registered as colored, i.e. the pages are color-enabled pages which happen to not have any colors on them (but I'm paying for the color-enabled-ness). Regrettably, the staff have to charge me for color because the printer's leased and they have to pay for color pages, so showing them that there's no color doesn't help me. What are possible sources for b/w pages showing up like that?

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• How do I add color syntax highlighting to GNU emacs?

  - by Alex Reynolds

  I have two versions of emacs available to me on a locked workstation: $ /usr/local/bin/emacs --version GNU Emacs 22.3.1 $ /usr/bin/emacs --version GNU Emacs 21.4.1 In both cases, my terminal type is xterm when I run either version of emacs. When I run the v21 version of emacs, I get syntax coloring for Perl, HTML, and other modes. When I run the v22 version, I do not get syntax coloring. I would like to migrate from the v21 version because the combination of v21 emacs, GNOME Terminal and GNU Screen is eating Ctrl-arrow key chords, which prevents me from moving quickly between words. (OS X Terminal and GNU Screen do not have this issue.) The v22 version allows use of Ctrl-arrow key combinations with GNOME Terminal and GNU Screen. How do I fix the v22 version (or ask my sys admin to fix) so that it once again highlights syntax and allows me to use Ctrl-arrow key combinations?

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• Convert color photos of documents to good black-and-white images?

  - by Norman Ramsey

  Since I don't have a copier or scanner, I'm using an 8 megapixel camera to copy documents. This works pretty well except they need a lot of processing afterward. I'd like to get from a photo to a bitmap, but using djpeg -grayscale -pnm photo.jpg | pgmtopbm -threshold -value XXX does not work so well, for two reasons: It's hard to guess what XXX should be, and XXX is different for different photos. Illumination varies, and sometimes a single threshold isn't what's right for the image. How can I do better? The ideal solution will be fully automatic command-line program that I can run on Linux. (I have already written a program to remove dark pixels from the edges of images.)

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• Where is a reputable place to buy ink refills for my color laser printer?

  - by FooBook

  I was looking around for a place to buy a refill kit for my laser printer. Of course, there are thousands of websites that are selling these kits. The problem is that I can't tell which one is a good one to buy from. How can I tell if the store has a good reputation. I don't want to pay, and then not receive the item. This has happened to me before (IvySkin). Or get conned some other way. One place I found is printerinkcartridge.us. But again, I can't find any independent information from people that they have successfully ordered products from there, and that they received what they expected. Are there any reliable sites you can suggest where I may order a kit from? Is the one I found good enough? Thanks guys.

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• Color drop down in Excel cell (with no text)? e.g. bgcolor = Red-Green-Amber-unknown

  - by adolf garlic

  I have an Excel sheet that I'm using to keep track of the status of certain things. I want to have a column which consists of cells containing a repeated drop down that allows you to select (as background) red amber green unknown I don't want any text in this cell, I just want a coloured block. Is this possible? I've tried playing around with data-validation-list (based on range containing all of said colours but to no avail)

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• How do i change color vibrance/saturation with intel graphics on my laptop?

  - by neelts

  like in the nvidia control panel laptop model is lenovo u350

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• How do I find all text with particular background color?

  - by Dave M G

  I have a LibreOffice Writer document that has undergone a process of editing, and sections of the text that needed to be rewritten were highlighted in yellow. As I fixed those sections, I removed the yellow highlight. Now, I want to make sure there are no remaining areas of highlighted text that have not been fixed or possibly the highlight was not removed. It's many hundreds of pages, so a manual scan is unfeasible. Also, it might be that one space or one character got accidentally left highlighted, and I want to ensure I've accounted for them all. How can I search the document to find all instances where text has been highlighted?

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• Parallelism in .NET – Part 3, Imperative Data Parallelism: Early Termination

  - by Reed

  Although simple data parallelism allows us to easily parallelize many of our iteration statements, there are cases that it does not handle well.  In my previous discussion, I focused on data parallelism with no shared state, and where every element is being processed exactly the same. Unfortunately, there are many common cases where this does not happen.  If we are dealing with a loop that requires early termination, extra care is required when parallelizing. Often, while processing in a loop, once a certain condition is met, it is no longer necessary to continue processing.  This may be a matter of finding a specific element within the collection, or reaching some error case.  The important distinction here is that, it is often impossible to know until runtime, what set of elements needs to be processed. In my initial discussion of data parallelism, I mentioned that this technique is a candidate when you can decompose the problem based on the data involved, and you wish to apply a single operation concurrently on all of the elements of a collection.  This covers many of the potential cases, but sometimes, after processing some of the elements, we need to stop processing. As an example, lets go back to our previous Parallel.ForEach example with contacting a customer.  However, this time, we’ll change the requirements slightly.  In this case, we’ll add an extra condition – if the store is unable to email the customer, we will exit gracefully.  The thinking here, of course, is that if the store is currently unable to email, the next time this operation runs, it will handle the same situation, so we can just skip our processing entirely.  The original, serial case, with this extra condition, might look something like the following: foreach(var customer in customers) { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { // Exit gracefully if we fail to email, since this // entire process can be repeated later without issue. if (theStore.EmailCustomer(customer) == false) break; customer.LastEmailContact = DateTime.Now; } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Here, we’re processing our loop, but at any point, if we fail to send our email successfully, we just abandon this process, and assume that it will get handled correctly the next time our routine is run.  If we try to parallelize this using Parallel.ForEach, as we did previously, we’ll run into an error almost immediately: the break statement we’re using is only valid when enclosed within an iteration statement, such as foreach.  When we switch to Parallel.ForEach, we’re no longer within an iteration statement – we’re a delegate running in a method. This needs to be handled slightly differently when parallelized.  Instead of using the break statement, we need to utilize a new class in the Task Parallel Library: ParallelLoopState.  The ParallelLoopState class is intended to allow concurrently running loop bodies a way to interact with each other, and provides us with a way to break out of a loop.  In order to use this, we will use a different overload of Parallel.ForEach which takes an IEnumerable<T> and an Action<T, ParallelLoopState> instead of an Action<T>.  Using this, we can parallelize the above operation by doing: Parallel.ForEach(customers, (customer, parallelLoopState) => { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { // Exit gracefully if we fail to email, since this // entire process can be repeated later without issue. if (theStore.EmailCustomer(customer) == false) parallelLoopState.Break(); else customer.LastEmailContact = DateTime.Now; } }); There are a couple of important points here.  First, we didn’t actually instantiate the ParallelLoopState instance.  It was provided directly to us via the Parallel class.  All we needed to do was change our lambda expression to reflect that we want to use the loop state, and the Parallel class creates an instance for our use.  We also needed to change our logic slightly when we call Break().  Since Break() doesn’t stop the program flow within our block, we needed to add an else case to only set the property in customer when we succeeded.  This same technique can be used to break out of a Parallel.For loop. That being said, there is a huge difference between using ParallelLoopState to cause early termination and to use break in a standard iteration statement.  When dealing with a loop serially, break will immediately terminate the processing within the closest enclosing loop statement.  Calling ParallelLoopState.Break(), however, has a very different behavior. The issue is that, now, we’re no longer processing one element at a time.  If we break in one of our threads, there are other threads that will likely still be executing.  This leads to an important observation about termination of parallel code: Early termination in parallel routines is not immediate.  Code will continue to run after you request a termination. This may seem problematic at first, but it is something you just need to keep in mind while designing your routine.  ParallelLoopState.Break() should be thought of as a request.  We are telling the runtime that no elements that were in the collection past the element we’re currently processing need to be processed, and leaving it up to the runtime to decide how to handle this as gracefully as possible.  Although this may seem problematic at first, it is a good thing.  If the runtime tried to immediately stop processing, many of our elements would be partially processed.  It would be like putting a return statement in a random location throughout our loop body – which could have horrific consequences to our code’s maintainability. In order to understand and effectively write parallel routines, we, as developers, need a subtle, but profound shift in our thinking.  We can no longer think in terms of sequential processes, but rather need to think in terms of requests to the system that may be handled differently than we’d first expect.  This is more natural to developers who have dealt with asynchronous models previously, but is an important distinction when moving to concurrent programming models. As an example, I’ll discuss the Break() method.  ParallelLoopState.Break() functions in a way that may be unexpected at first.  When you call Break() from a loop body, the runtime will continue to process all elements of the collection that were found prior to the element that was being processed when the Break() method was called.  This is done to keep the behavior of the Break() method as close to the behavior of the break statement as possible. We can see the behavior in this simple code: var collection = Enumerable.Range(0, 20); var pResult = Parallel.ForEach(collection, (element, state) => { if (element > 10) { Console.WriteLine("Breaking on {0}", element); state.Break(); } Console.WriteLine(element); }); If we run this, we get a result that may seem unexpected at first: 0 2 1 5 6 3 4 10 Breaking on 11 11 Breaking on 12 12 9 Breaking on 13 13 7 8 Breaking on 15 15 What is occurring here is that we loop until we find the first element where the element is greater than 10.  In this case, this was found, the first time, when one of our threads reached element 11.  It requested that the loop stop by calling Break() at this point.  However, the loop continued processing until all of the elements less than 11 were completed, then terminated.  This means that it will guarantee that elements 9, 7, and 8 are completed before it stops processing.  You can see our other threads that were running each tried to break as well, but since Break() was called on the element with a value of 11, it decides which elements (0-10) must be processed. If this behavior is not desirable, there is another option.  Instead of calling ParallelLoopState.Break(), you can call ParallelLoopState.Stop().  The Stop() method requests that the runtime terminate as soon as possible , without guaranteeing that any other elements are processed.  Stop() will not stop the processing within an element, so elements already being processed will continue to be processed.  It will prevent new elements, even ones found earlier in the collection, from being processed.  Also, when Stop() is called, the ParallelLoopState’s IsStopped property will return true.  This lets longer running processes poll for this value, and return after performing any necessary cleanup. The basic rule of thumb for choosing between Break() and Stop() is the following. Use ParallelLoopState.Stop() when possible, since it terminates more quickly.  This is particularly useful in situations where you are searching for an element or a condition in the collection.  Once you’ve found it, you do not need to do any other processing, so Stop() is more appropriate. Use ParallelLoopState.Break() if you need to more closely match the behavior of the C# break statement. Both methods behave differently than our C# break statement.  Unfortunately, when parallelizing a routine, more thought and care needs to be put into every aspect of your routine than you may otherwise expect.  This is due to my second observation: Parallelizing a routine will almost always change its behavior. This sounds crazy at first, but it’s a concept that’s so simple its easy to forget.  We’re purposely telling the system to process more than one thing at the same time, which means that the sequence in which things get processed is no longer deterministic.  It is easy to change the behavior of your routine in very subtle ways by introducing parallelism.  Often, the changes are not avoidable, even if they don’t have any adverse side effects.  This leads to my final observation for this post: Parallelization is something that should be handled with care and forethought, added by design, and not just introduced casually.

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• Parallelism in .NET – Part 7, Some Differences between PLINQ and LINQ to Objects

  - by Reed

  In my previous post on Declarative Data Parallelism, I mentioned that PLINQ extends LINQ to Objects to support parallel operations.  Although nearly all of the same operations are supported, there are some differences between PLINQ and LINQ to Objects.  By introducing Parallelism to our declarative model, we add some extra complexity.  This, in turn, adds some extra requirements that must be addressed. In order to illustrate the main differences, and why they exist, let’s begin by discussing some differences in how the two technologies operate, and look at the underlying types involved in LINQ to Objects and PLINQ . LINQ to Objects is mainly built upon a single class: Enumerable.  The Enumerable class is a static class that defines a large set of extension methods, nearly all of which work upon an IEnumerable<T>.  Many of these methods return a new IEnumerable<T>, allowing the methods to be chained together into a fluent style interface.  This is what allows us to write statements that chain together, and lead to the nice declarative programming model of LINQ: double min = collection .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Other LINQ variants work in a similar fashion.  For example, most data-oriented LINQ providers are built upon an implementation of IQueryable<T>, which allows the database provider to turn a LINQ statement into an underlying SQL query, to be performed directly on the remote database. PLINQ is similar, but instead of being built upon the Enumerable class, most of PLINQ is built upon a new static class: ParallelEnumerable.  When using PLINQ, you typically begin with any collection which implements IEnumerable<T>, and convert it to a new type using an extension method defined on ParallelEnumerable: AsParallel().  This method takes any IEnumerable<T>, and converts it into a ParallelQuery<T>, the core class for PLINQ.  There is a similar ParallelQuery class for working with non-generic IEnumerable implementations. This brings us to our first subtle, but important difference between PLINQ and LINQ – PLINQ always works upon specific types, which must be explicitly created. Typically, the type you’ll use with PLINQ is ParallelQuery<T>, but it can sometimes be a ParallelQuery or an OrderedParallelQuery<T>.  Instead of dealing with an interface, implemented by an unknown class, we’re dealing with a specific class type.  This works seamlessly from a usage standpoint – ParallelQuery<T> implements IEnumerable<T>, so you can always “switch back” to an IEnumerable<T>.  The difference only arises at the beginning of our parallelization.  When we’re using LINQ, and we want to process a normal collection via PLINQ, we need to explicitly convert the collection into a ParallelQuery<T> by calling AsParallel().  There is an important consideration here – AsParallel() does not need to be called on your specific collection, but rather any IEnumerable<T>.  This allows you to place it anywhere in the chain of methods involved in a LINQ statement, not just at the beginning.  This can be useful if you have an operation which will not parallelize well or is not thread safe.  For example, the following is perfectly valid, and similar to our previous examples: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); However, if SomeOperation() is not thread safe, we could just as easily do: double min = collection .Select(item => item.SomeOperation()) .AsParallel() .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .Min(item => item.PerformComputation()); In this case, we’re using standard LINQ to Objects for the Select(…) method, then converting the results of that map routine to a ParallelQuery<T>, and processing our filter (the Where method) and our aggregation (the Min method) in parallel. PLINQ also provides us with a way to convert a ParallelQuery<T> back into a standard IEnumerable<T>, forcing sequential processing via standard LINQ to Objects.  If SomeOperation() was thread-safe, but PerformComputation() was not thread-safe, we would need to handle this by using the AsEnumerable() method: double min = collection .AsParallel() .Select(item => item.SomeOperation()) .Where(item => item.SomeProperty > 6 && item.SomeProperty < 24) .AsEnumerable() .Min(item => item.PerformComputation()); Here, we’re converting our collection into a ParallelQuery<T>, doing our map operation (the Select(…) method) and our filtering in parallel, then converting the collection back into a standard IEnumerable<T>, which causes our aggregation via Min() to be performed sequentially. This could also be written as two statements, as well, which would allow us to use the language integrated syntax for the first portion: var tempCollection = from item in collection.AsParallel() let e = item.SomeOperation() where (e.SomeProperty > 6 && e.SomeProperty < 24) select e; double min = tempCollection.AsEnumerable().Min(item => item.PerformComputation()); This allows us to use the standard LINQ style language integrated query syntax, but control whether it’s performed in parallel or serial by adding AsParallel() and AsEnumerable() appropriately. The second important difference between PLINQ and LINQ deals with order preservation.  PLINQ, by default, does not preserve the order of of source collection. This is by design.  In order to process a collection in parallel, the system needs to naturally deal with multiple elements at the same time.  Maintaining the original ordering of the sequence adds overhead, which is, in many cases, unnecessary.  Therefore, by default, the system is allowed to completely change the order of your sequence during processing.  If you are doing a standard query operation, this is usually not an issue.  However, there are times when keeping a specific ordering in place is important.  If this is required, you can explicitly request the ordering be preserved throughout all operations done on a ParallelQuery<T> by using the AsOrdered() extension method.  This will cause our sequence ordering to be preserved. For example, suppose we wanted to take a collection, perform an expensive operation which converts it to a new type, and display the first 100 elements.  In LINQ to Objects, our code might look something like: // Using IEnumerable<SourceClass> collection IEnumerable<ResultClass> results = collection .Select(e => e.CreateResult()) .Take(100); If we just converted this to a parallel query naively, like so: IEnumerable<ResultClass> results = collection .AsParallel() .Select(e => e.CreateResult()) .Take(100); We could very easily get a very different, and non-reproducable, set of results, since the ordering of elements in the input collection is not preserved.  To get the same results as our original query, we need to use: IEnumerable<ResultClass> results = collection .AsParallel() .AsOrdered() .Select(e => e.CreateResult()) .Take(100); This requests that PLINQ process our sequence in a way that verifies that our resulting collection is ordered as if it were processed serially.  This will cause our query to run slower, since there is overhead involved in maintaining the ordering.  However, in this case, it is required, since the ordering is required for correctness. PLINQ is incredibly useful.  It allows us to easily take nearly any LINQ to Objects query and run it in parallel, using the same methods and syntax we’ve used previously.  There are some important differences in operation that must be considered, however – it is not a free pass to parallelize everything.  When using PLINQ in order to parallelize your routines declaratively, the same guideline I mentioned before still applies: Parallelization is something that should be handled with care and forethought, added by design, and not just introduced casually.

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• Parallelism in .NET – Part 9, Configuration in PLINQ and TPL

  - by Reed

  Parallel LINQ and the Task Parallel Library contain many options for configuration.  Although the default configuration options are often ideal, there are times when customizing the behavior is desirable.  Both frameworks provide full configuration support. When working with Data Parallelism, there is one primary configuration option we often need to control – the number of threads we want the system to use when parallelizing our routine.  By default, PLINQ and the TPL both use the ThreadPool to schedule tasks.  Given the major improvements in the ThreadPool in CLR 4, this default behavior is often ideal.  However, there are times that the default behavior is not appropriate.  For example, if you are working on multiple threads simultaneously, and want to schedule parallel operations from within both threads, you might want to consider restricting each parallel operation to using a subset of the processing cores of the system.  Not doing this might over-parallelize your routine, which leads to inefficiencies from having too many context switches. In the Task Parallel Library, configuration is handled via the ParallelOptions class.  All of the methods of the Parallel class have an overload which accepts a ParallelOptions argument. We configure the Parallel class by setting the ParallelOptions.MaxDegreeOfParallelism property.  For example, let’s revisit one of the simple data parallel examples from Part 2: Parallel.For(0, pixelData.GetUpperBound(0), row => { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } }); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Here, we’re looping through an image, and calling a method on each pixel in the image.  If this was being done on a separate thread, and we knew another thread within our system was going to be doing a similar operation, we likely would want to restrict this to using half of the cores on the system.  This could be accomplished easily by doing: var options = new ParallelOptions(); options.MaxDegreeOfParallelism = Math.Max(Environment.ProcessorCount / 2, 1); Parallel.For(0, pixelData.GetUpperBound(0), options, row => { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } }); Now, we’re restricting this routine to using no more than half the cores in our system.  Note that I included a check to prevent a single core system from supplying zero; without this check, we’d potentially cause an exception.  I also did not hard code a specific value for the MaxDegreeOfParallelism property.  One of our goals when parallelizing a routine is allowing it to scale on better hardware.  Specifying a hard-coded value would contradict that goal. Parallel LINQ also supports configuration, and in fact, has quite a few more options for configuring the system.  The main configuration option we most often need is the same as our TPL option: we need to supply the maximum number of processing threads.  In PLINQ, this is done via a new extension method on ParallelQuery<T>: ParallelEnumerable.WithDegreeOfParallelism. Let’s revisit our declarative data parallelism sample from Part 6: double min = collection.AsParallel().Min(item => item.PerformComputation()); Here, we’re performing a computation on each element in the collection, and saving the minimum value of this operation.  If we wanted to restrict this to a limited number of threads, we would add our new extension method: int maxThreads = Math.Max(Environment.ProcessorCount / 2, 1); double min = collection .AsParallel() .WithDegreeOfParallelism(maxThreads) .Min(item => item.PerformComputation()); This automatically restricts the PLINQ query to half of the threads on the system. PLINQ provides some additional configuration options.  By default, PLINQ will occasionally revert to processing a query in parallel.  This occurs because many queries, if parallelized, typically actually cause an overall slowdown compared to a serial processing equivalent.  By analyzing the “shape” of the query, PLINQ often decides to run a query serially instead of in parallel.  This can occur for (taken from MSDN): Queries that contain a Select, indexed Where, indexed SelectMany, or ElementAt clause after an ordering or filtering operator that has removed or rearranged original indices. Queries that contain a Take, TakeWhile, Skip, SkipWhile operator and where indices in the source sequence are not in the original order. Queries that contain Zip or SequenceEquals, unless one of the data sources has an originally ordered index and the other data source is indexable (i.e. an array or IList(T)). Queries that contain Concat, unless it is applied to indexable data sources. Queries that contain Reverse, unless applied to an indexable data source. If the specific query follows these rules, PLINQ will run the query on a single thread.  However, none of these rules look at the specific work being done in the delegates, only at the “shape” of the query.  There are cases where running in parallel may still be beneficial, even if the shape is one where it typically parallelizes poorly.  In these cases, you can override the default behavior by using the WithExecutionMode extension method.  This would be done like so: var reversed = collection .AsParallel() .WithExecutionMode(ParallelExecutionMode.ForceParallelism) .Select(i => i.PerformComputation()) .Reverse(); Here, the default behavior would be to not parallelize the query unless collection implemented IList<T>.  We can force this to run in parallel by adding the WithExecutionMode extension method in the method chain. Finally, PLINQ has the ability to configure how results are returned.  When a query is filtering or selecting an input collection, the results will need to be streamed back into a single IEnumerable<T> result.  For example, the method above returns a new, reversed collection.  In this case, the processing of the collection will be done in parallel, but the results need to be streamed back to the caller serially, so they can be enumerated on a single thread. This streaming introduces overhead.  IEnumerable<T> isn’t designed with thread safety in mind, so the system needs to handle merging the parallel processes back into a single stream, which introduces synchronization issues.  There are two extremes of how this could be accomplished, but both extremes have disadvantages. The system could watch each thread, and whenever a thread produces a result, take that result and send it back to the caller.  This would mean that the calling thread would have access to the data as soon as data is available, which is the benefit of this approach.  However, it also means that every item is introducing synchronization overhead, since each item needs to be merged individually. On the other extreme, the system could wait until all of the results from all of the threads were ready, then push all of the results back to the calling thread in one shot.  The advantage here is that the least amount of synchronization is added to the system, which means the query will, on a whole, run the fastest.  However, the calling thread will have to wait for all elements to be processed, so this could introduce a long delay between when a parallel query begins and when results are returned. The default behavior in PLINQ is actually between these two extremes.  By default, PLINQ maintains an internal buffer, and chooses an optimal buffer size to maintain.  Query results are accumulated into the buffer, then returned in the IEnumerable<T> result in chunks.  This provides reasonably fast access to the results, as well as good overall throughput, in most scenarios. However, if we know the nature of our algorithm, we may decide we would prefer one of the other extremes.  This can be done by using the WithMergeOptions extension method.  For example, if we know that our PerformComputation() routine is very slow, but also variable in runtime, we may want to retrieve results as they are available, with no bufferring.  This can be done by changing our above routine to: var reversed = collection .AsParallel() .WithExecutionMode(ParallelExecutionMode.ForceParallelism) .WithMergeOptions(ParallelMergeOptions.NotBuffered) .Select(i => i.PerformComputation()) .Reverse(); On the other hand, if are already on a background thread, and we want to allow the system to maximize its speed, we might want to allow the system to fully buffer the results: var reversed = collection .AsParallel() .WithExecutionMode(ParallelExecutionMode.ForceParallelism) .WithMergeOptions(ParallelMergeOptions.FullyBuffered) .Select(i => i.PerformComputation()) .Reverse(); Notice, also, that you can specify multiple configuration options in a parallel query.  By chaining these extension methods together, we generate a query that will always run in parallel, and will always complete before making the results available in our IEnumerable<T>.

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• Parallelism in .NET – Part 2, Simple Imperative Data Parallelism

  - by Reed

  In my discussion of Decomposition of the problem space, I mentioned that Data Decomposition is often the simplest abstraction to use when trying to parallelize a routine.  If a problem can be decomposed based off the data, we will often want to use what MSDN refers to as Data Parallelism as our strategy for implementing our routine.  The Task Parallel Library in .NET 4 makes implementing Data Parallelism, for most cases, very simple. Data Parallelism is the main technique we use to parallelize a routine which can be decomposed based off data.  Data Parallelism refers to taking a single collection of data, and having a single operation be performed concurrently on elements in the collection.  One side note here: Data Parallelism is also sometimes referred to as the Loop Parallelism Pattern or Loop-level Parallelism.  In general, for this series, I will try to use the terminology used in the MSDN Documentation for the Task Parallel Library.  This should make it easier to investigate these topics in more detail. Once we’ve determined we have a problem that, potentially, can be decomposed based on data, implementation using Data Parallelism in the TPL is quite simple.  Let’s take our example from the Data Decomposition discussion – a simple contrast stretching filter.  Here, we have a collection of data (pixels), and we need to run a simple operation on each element of the pixel.  Once we know the minimum and maximum values, we most likely would have some simple code like the following: for (int row=0; row < pixelData.GetUpperBound(0); ++row) { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This simple routine loops through a two dimensional array of pixelData, and calls the AdjustContrast routine on each pixel. As I mentioned, when you’re decomposing a problem space, most iteration statements are potentially candidates for data decomposition.  Here, we’re using two for loops – one looping through rows in the image, and a second nested loop iterating through the columns.  We then perform one, independent operation on each element based on those loop positions. This is a prime candidate – we have no shared data, no dependencies on anything but the pixel which we want to change.  Since we’re using a for loop, we can easily parallelize this using the Parallel.For method in the TPL: Parallel.For(0, pixelData.GetUpperBound(0), row => { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } }); Here, by simply changing our first for loop to a call to Parallel.For, we can parallelize this portion of our routine.  Parallel.For works, as do many methods in the TPL, by creating a delegate and using it as an argument to a method.  In this case, our for loop iteration block becomes a delegate creating via a lambda expression.  This lets you write code that, superficially, looks similar to the familiar for loop, but functions quite differently at runtime. We could easily do this to our second for loop as well, but that may not be a good idea.  There is a balance to be struck when writing parallel code.  We want to have enough work items to keep all of our processors busy, but the more we partition our data, the more overhead we introduce.  In this case, we have an image of data – most likely hundreds of pixels in both dimensions.  By just parallelizing our first loop, each row of pixels can be run as a single task.  With hundreds of rows of data, we are providing fine enough granularity to keep all of our processors busy. If we parallelize both loops, we’re potentially creating millions of independent tasks.  This introduces extra overhead with no extra gain, and will actually reduce our overall performance.  This leads to my first guideline when writing parallel code: Partition your problem into enough tasks to keep each processor busy throughout the operation, but not more than necessary to keep each processor busy. Also note that I parallelized the outer loop.  I could have just as easily partitioned the inner loop.  However, partitioning the inner loop would have led to many more discrete work items, each with a smaller amount of work (operate on one pixel instead of one row of pixels).  My second guideline when writing parallel code reflects this: Partition your problem in a way to place the most work possible into each task. This typically means, in practice, that you will want to parallelize the routine at the “highest” point possible in the routine, typically the outermost loop.  If you’re looking at parallelizing methods which call other methods, you’ll want to try to partition your work high up in the stack – as you get into lower level methods, the performance impact of parallelizing your routines may not overcome the overhead introduced. Parallel.For works great for situations where we know the number of elements we’re going to process in advance.  If we’re iterating through an IList<T> or an array, this is a typical approach.  However, there are other iteration statements common in C#.  In many situations, we’ll use foreach instead of a for loop.  This can be more understandable and easier to read, but also has the advantage of working with collections which only implement IEnumerable<T>, where we do not know the number of elements involved in advance. As an example, lets take the following situation.  Say we have a collection of Customers, and we want to iterate through each customer, check some information about the customer, and if a certain case is met, send an email to the customer and update our instance to reflect this change.  Normally, this might look something like: foreach(var customer in customers) { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } } Here, we’re doing a fair amount of work for each customer in our collection, but we don’t know how many customers exist.  If we assume that theStore.GetLastContact(customer) and theStore.EmailCustomer(customer) are both side-effect free, thread safe operations, we could parallelize this using Parallel.ForEach: Parallel.ForEach(customers, customer => { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } }); Just like Parallel.For, we rework our loop into a method call accepting a delegate created via a lambda expression.  This keeps our new code very similar to our original iteration statement, however, this will now execute in parallel.  The same guidelines apply with Parallel.ForEach as with Parallel.For. The other iteration statements, do and while, do not have direct equivalents in the Task Parallel Library.  These, however, are very easy to implement using Parallel.ForEach and the yield keyword. Most applications can benefit from implementing some form of Data Parallelism.  Iterating through collections and performing “work” is a very common pattern in nearly every application.  When the problem can be decomposed by data, we often can parallelize the workload by merely changing foreach statements to Parallel.ForEach method calls, and for loops to Parallel.For method calls.  Any time your program operates on a collection, and does a set of work on each item in the collection where that work is not dependent on other information, you very likely have an opportunity to parallelize your routine.

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• Parallelism in .NET – Part 4, Imperative Data Parallelism: Aggregation

  - by Reed

  In the article on simple data parallelism, I described how to perform an operation on an entire collection of elements in parallel.  Often, this is not adequate, as the parallel operation is going to be performing some form of aggregation. Simple examples of this might include taking the sum of the results of processing a function on each element in the collection, or finding the minimum of the collection given some criteria.  This can be done using the techniques described in simple data parallelism, however, special care needs to be taken into account to synchronize the shared data appropriately.  The Task Parallel Library has tools to assist in this synchronization. The main issue with aggregation when parallelizing a routine is that you need to handle synchronization of data.  Since multiple threads will need to write to a shared portion of data.  Suppose, for example, that we wanted to parallelize a simple loop that looked for the minimum value within a dataset: double min = double.MaxValue; foreach(var item in collection) { double value = item.PerformComputation(); min = System.Math.Min(min, value); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This seems like a good candidate for parallelization, but there is a problem here.  If we just wrap this into a call to Parallel.ForEach, we’ll introduce a critical race condition, and get the wrong answer.  Let’s look at what happens here: // Buggy code! Do not use! double min = double.MaxValue; Parallel.ForEach(collection, item => { double value = item.PerformComputation(); min = System.Math.Min(min, value); }); This code has a fatal flaw: min will be checked, then set, by multiple threads simultaneously.  Two threads may perform the check at the same time, and set the wrong value for min.  Say we get a value of 1 in thread 1, and a value of 2 in thread 2, and these two elements are the first two to run.  If both hit the min check line at the same time, both will determine that min should change, to 1 and 2 respectively.  If element 1 happens to set the variable first, then element 2 sets the min variable, we’ll detect a min value of 2 instead of 1.  This can lead to wrong answers. Unfortunately, fixing this, with the Parallel.ForEach call we’re using, would require adding locking.  We would need to rewrite this like: // Safe, but slow double min = double.MaxValue; // Make a "lock" object object syncObject = new object(); Parallel.ForEach(collection, item => { double value = item.PerformComputation(); lock(syncObject) min = System.Math.Min(min, value); }); This will potentially add a huge amount of overhead to our calculation.  Since we can potentially block while waiting on the lock for every single iteration, we will most likely slow this down to where it is actually quite a bit slower than our serial implementation.  The problem is the lock statement – any time you use lock(object), you’re almost assuring reduced performance in a parallel situation.  This leads to two observations I’ll make: When parallelizing a routine, try to avoid locks. That being said: Always add any and all required synchronization to avoid race conditions. These two observations tend to be opposing forces – we often need to synchronize our algorithms, but we also want to avoid the synchronization when possible.  Looking at our routine, there is no way to directly avoid this lock, since each element is potentially being run on a separate thread, and this lock is necessary in order for our routine to function correctly every time. However, this isn’t the only way to design this routine to implement this algorithm.  Realize that, although our collection may have thousands or even millions of elements, we have a limited number of Processing Elements (PE).  Processing Element is the standard term for a hardware element which can process and execute instructions.  This typically is a core in your processor, but many modern systems have multiple hardware execution threads per core.  The Task Parallel Library will not execute the work for each item in the collection as a separate work item. Instead, when Parallel.ForEach executes, it will partition the collection into larger “chunks” which get processed on different threads via the ThreadPool.  This helps reduce the threading overhead, and help the overall speed.  In general, the Parallel class will only use one thread per PE in the system. Given the fact that there are typically fewer threads than work items, we can rethink our algorithm design.  We can parallelize our algorithm more effectively by approaching it differently.  Because the basic aggregation we are doing here (Min) is communitive, we do not need to perform this in a given order.  We knew this to be true already – otherwise, we wouldn’t have been able to parallelize this routine in the first place.  With this in mind, we can treat each thread’s work independently, allowing each thread to serially process many elements with no locking, then, after all the threads are complete, “merge” together the results. This can be accomplished via a different set of overloads in the Parallel class: Parallel.ForEach<TSource,TLocal>.  The idea behind these overloads is to allow each thread to begin by initializing some local state (TLocal).  The thread will then process an entire set of items in the source collection, providing that state to the delegate which processes an individual item.  Finally, at the end, a separate delegate is run which allows you to handle merging that local state into your final results. To rewriting our routine using Parallel.ForEach<TSource,TLocal>, we need to provide three delegates instead of one.  The most basic version of this function is declared as: public static ParallelLoopResult ForEach<TSource, TLocal>( IEnumerable<TSource> source, Func<TLocal> localInit, Func<TSource, ParallelLoopState, TLocal, TLocal> body, Action<TLocal> localFinally ) The first delegate (the localInit argument) is defined as Func<TLocal>.  This delegate initializes our local state.  It should return some object we can use to track the results of a single thread’s operations. The second delegate (the body argument) is where our main processing occurs, although now, instead of being an Action<T>, we actually provide a Func<TSource, ParallelLoopState, TLocal, TLocal> delegate.  This delegate will receive three arguments: our original element from the collection (TSource), a ParallelLoopState which we can use for early termination, and the instance of our local state we created (TLocal).  It should do whatever processing you wish to occur per element, then return the value of the local state after processing is completed. The third delegate (the localFinally argument) is defined as Action<TLocal>.  This delegate is passed our local state after it’s been processed by all of the elements this thread will handle.  This is where you can merge your final results together.  This may require synchronization, but now, instead of synchronizing once per element (potentially millions of times), you’ll only have to synchronize once per thread, which is an ideal situation. Now that I’ve explained how this works, lets look at the code: // Safe, and fast! double min = double.MaxValue; // Make a "lock" object object syncObject = new object(); Parallel.ForEach( collection, // First, we provide a local state initialization delegate. () => double.MaxValue, // Next, we supply the body, which takes the original item, loop state, // and local state, and returns a new local state (item, loopState, localState) => { double value = item.PerformComputation(); return System.Math.Min(localState, value); }, // Finally, we provide an Action<TLocal>, to "merge" results together localState => { // This requires locking, but it's only once per used thread lock(syncObj) min = System.Math.Min(min, localState); } ); Although this is a bit more complicated than the previous version, it is now both thread-safe, and has minimal locking.  This same approach can be used by Parallel.For, although now, it’s Parallel.For<TLocal>.  When working with Parallel.For<TLocal>, you use the same triplet of delegates, with the same purpose and results. Also, many times, you can completely avoid locking by using a method of the Interlocked class to perform the final aggregation in an atomic operation.  The MSDN example demonstrating this same technique using Parallel.For uses the Interlocked class instead of a lock, since they are doing a sum operation on a long variable, which is possible via Interlocked.Add. By taking advantage of local state, we can use the Parallel class methods to parallelize algorithms such as aggregation, which, at first, may seem like poor candidates for parallelization.  Doing so requires careful consideration, and often requires a slight redesign of the algorithm, but the performance gains can be significant if handled in a way to avoid excessive synchronization.

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• Parallelism in .NET – Part 11, Divide and Conquer via Parallel.Invoke

  - by Reed

  Many algorithms are easily written to work via recursion.  For example, most data-oriented tasks where a tree of data must be processed are much more easily handled by starting at the root, and recursively “walking” the tree.  Some algorithms work this way on flat data structures, such as arrays, as well.  This is a form of divide and conquer: an algorithm design which is based around breaking up a set of work recursively, “dividing” the total work in each recursive step, and “conquering” the work when the remaining work is small enough to be solved easily. Recursive algorithms, especially ones based on a form of divide and conquer, are often a very good candidate for parallelization. This is apparent from a common sense standpoint.  Since we’re dividing up the total work in the algorithm, we have an obvious, built-in partitioning scheme.  Once partitioned, the data can be worked upon independently, so there is good, clean isolation of data. Implementing this type of algorithm is fairly simple.  The Parallel class in .NET 4 includes a method suited for this type of operation: Parallel.Invoke.  This method works by taking any number of delegates defined as an Action, and operating them all in parallel.  The method returns when every delegate has completed: Parallel.Invoke( () => { Console.WriteLine("Action 1 executing in thread {0}", Thread.CurrentThread.ManagedThreadId); }, () => { Console.WriteLine("Action 2 executing in thread {0}", Thread.CurrentThread.ManagedThreadId); }, () => { Console.WriteLine("Action 3 executing in thread {0}", Thread.CurrentThread.ManagedThreadId); } ); .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } Running this simple example demonstrates the ease of using this method.  For example, on my system, I get three separate thread IDs when running the above code.  By allowing any number of delegates to be executed directly, concurrently, the Parallel.Invoke method provides us an easy way to parallelize any algorithm based on divide and conquer.  We can divide our work in each step, and execute each task in parallel, recursively. For example, suppose we wanted to implement our own quicksort routine.  The quicksort algorithm can be designed based on divide and conquer.  In each iteration, we pick a pivot point, and use that to partition the total array.  We swap the elements around the pivot, then recursively sort the lists on each side of the pivot.  For example, let’s look at this simple, sequential implementation of quicksort: public static void QuickSort<T>(T[] array) where T : IComparable<T> { QuickSortInternal(array, 0, array.Length - 1); } private static void QuickSortInternal<T>(T[] array, int left, int right) where T : IComparable<T> { if (left >= right) { return; } SwapElements(array, left, (left + right) / 2); int last = left; for (int current = left + 1; current <= right; ++current) { if (array[current].CompareTo(array[left]) < 0) { ++last; SwapElements(array, last, current); } } SwapElements(array, left, last); QuickSortInternal(array, left, last - 1); QuickSortInternal(array, last + 1, right); } static void SwapElements<T>(T[] array, int i, int j) { T temp = array[i]; array[i] = array[j]; array[j] = temp; } Here, we implement the quicksort algorithm in a very common, divide and conquer approach.  Running this against the built-in Array.Sort routine shows that we get the exact same answers (although the framework’s sort routine is slightly faster).  On my system, for example, I can use framework’s sort to sort ten million random doubles in about 7.3s, and this implementation takes about 9.3s on average. Looking at this routine, though, there is a clear opportunity to parallelize.  At the end of QuickSortInternal, we recursively call into QuickSortInternal with each partition of the array after the pivot is chosen.  This can be rewritten to use Parallel.Invoke by simply changing it to: // Code above is unchanged... SwapElements(array, left, last); Parallel.Invoke( () => QuickSortInternal(array, left, last - 1), () => QuickSortInternal(array, last + 1, right) ); } This routine will now run in parallel.  When executing, we now see the CPU usage across all cores spike while it executes.  However, there is a significant problem here – by parallelizing this routine, we took it from an execution time of 9.3s to an execution time of approximately 14 seconds!  We’re using more resources as seen in the CPU usage, but the overall result is a dramatic slowdown in overall processing time. This occurs because parallelization adds overhead.  Each time we split this array, we spawn two new tasks to parallelize this algorithm!  This is far, far too many tasks for our cores to operate upon at a single time.  In effect, we’re “over-parallelizing” this routine.  This is a common problem when working with divide and conquer algorithms, and leads to an important observation: When parallelizing a recursive routine, take special care not to add more tasks than necessary to fully utilize your system. This can be done with a few different approaches, in this case.  Typically, the way to handle this is to stop parallelizing the routine at a certain point, and revert back to the serial approach.  Since the first few recursions will all still be parallelized, our “deeper” recursive tasks will be running in parallel, and can take full advantage of the machine.  This also dramatically reduces the overhead added by parallelizing, since we’re only adding overhead for the first few recursive calls.  There are two basic approaches we can take here.  The first approach would be to look at the total work size, and if it’s smaller than a specific threshold, revert to our serial implementation.  In this case, we could just check right-left, and if it’s under a threshold, call the methods directly instead of using Parallel.Invoke. The second approach is to track how “deep” in the “tree” we are currently at, and if we are below some number of levels, stop parallelizing.  This approach is a more general-purpose approach, since it works on routines which parse trees as well as routines working off of a single array, but may not work as well if a poor partitioning strategy is chosen or the tree is not balanced evenly. This can be written very easily.  If we pass a maxDepth parameter into our internal routine, we can restrict the amount of times we parallelize by changing the recursive call to: // Code above is unchanged... SwapElements(array, left, last); if (maxDepth < 1) { QuickSortInternal(array, left, last - 1, maxDepth); QuickSortInternal(array, last + 1, right, maxDepth); } else { --maxDepth; Parallel.Invoke( () => QuickSortInternal(array, left, last - 1, maxDepth), () => QuickSortInternal(array, last + 1, right, maxDepth)); } We no longer allow this to parallelize indefinitely – only to a specific depth, at which time we revert to a serial implementation.  By starting the routine with a maxDepth equal to Environment.ProcessorCount, we can restrict the total amount of parallel operations significantly, but still provide adequate work for each processing core. With this final change, my timings are much better.  On average, I get the following timings: Framework via Array.Sort: 7.3 seconds Serial Quicksort Implementation: 9.3 seconds Naive Parallel Implementation: 14 seconds Parallel Implementation Restricting Depth: 4.7 seconds Finally, we are now faster than the framework’s Array.Sort implementation.

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• Building and Deploying Windows Azure Web Sites using Git and GitHub for Windows

  - by shiju

  Microsoft Windows Azure team has released a new version of Windows Azure which is providing many excellent features. The new Windows Azure provides Web Sites which allows you to deploy up to 10 web sites  for free in a multitenant shared environment and you can easily upgrade this web site to a private, dedicated virtual server when the traffic is grows. The Meet Windows Azure Fact Sheet provides the following information about a Windows Azure Web Site: Windows Azure Web Sites enable developers to easily build and deploy websites with support for multiple frameworks and popular open source applications, including ASP.NET, PHP and Node.js. With just a few clicks, developers can take advantage of Windows Azure’s global scale without having to worry about operations, servers or infrastructure. It is easy to deploy existing sites, if they run on Internet Information Services (IIS) 7, or to build new sites, with a free offer of 10 websites upon signup, with the ability to scale up as needed with reserved instances. Windows Azure Web Sites includes support for the following: Multiple frameworks including ASP.NET, PHP and Node.js Popular open source software apps including WordPress, Joomla!, Drupal, Umbraco and DotNetNuke Windows Azure SQL Database and MySQL databases Multiple types of developer tools and protocols including Visual Studio, Git, FTP, Visual Studio Team Foundation Services and Microsoft WebMatrix Signup to Windows and Enable Azure Web Sites You can signup for a 90 days free trial account in Windows Azure from here. After creating an account in Windows Azure, go to https://account.windowsazure.com/ , and select to preview features to view the available previews. In the Web Sites section of the preview features, click “try it now” which will enables the web sites feature Create Web Site in Windows Azure To create a web sites, login to the Windows Azure portal, and select Web Sites from and click New icon from the left corner  Click WEB SITE, QUICK CREATE and put values for URL and REGION dropdown. You can see the all web sites from the dashboard of the Windows Azure portal Set up Git Publishing Select your web site from the dashboard, and select Set up Git publishing To enable Git publishing , you must give user name and password which will initialize a Git repository Clone Git Repository We can use GitHub for Windows to publish apps to non-GitHub repositories which is well explained by Phil Haack on his blog post. Here we are going to deploy the web site using GitHub for Windows. Let’s clone a Git repository using the Git Url which will be getting from the Windows Azure portal. Let’s copy the Git url and execute the “git clone” with the git url. You can use the Git Shell provided by GitHub for Windows. To get it, right on the GitHub for Windows, and select open shell here as shown in the below picture. When executing the Git Clone command, it will ask for a password where you have to give password which specified in the Windows Azure portal. After cloning the GIT repository, you can drag and drop the local Git repository folder to GitHub for Windows GUI. This will automatically add the Windows Azure Web Site repository onto GitHub for Windows where you can commit your changes and publish your web sites to Windows Azure. Publish the Web Site using GitHub for Windows We can add multiple framework level files including ASP.NET, PHP and Node.js, to the local repository folder can easily publish to Windows Azure from GitHub for Windows GUI. For this demo, let me just add a simple Node.js file named Server.js which handles few request handlers. 1: var http = require('http'); 2: var port=process.env.PORT; 3: var querystring = require('querystring'); 4: var utils = require('util'); 5: var url = require("url"); 6:   7: var server = http.createServer(function(req, res) { 8: switch (req.url) { //checking the request url 9: case '/': 10: homePageHandler (req, res); //handler for home page 11: break; 12: case '/register': 13: registerFormHandler (req, res);//hamdler for register 14: break; 15: default: 16: nofoundHandler (req, res);// handler for 404 not found 17: break; 18: } 19: }); 20: server.listen(port); 21: //function to display the html form 22: function homePageHandler (req, res) { 23: console.log('Request handler home was called.'); 24: res.writeHead(200, {'Content-Type': 'text/html'}); 25: var body = '<html>'+ 26: '<head>'+ 27: '<meta http-equiv="Content-Type" content="text/html; '+ 28: 'charset=UTF-8" />'+ 29: '</head>'+ 30: '<body>'+ 31: '<form action="/register" method="post">'+ 32: 'Name:<input type=text value="" name="name" size=15></br>'+ 33: 'Email:<input type=text value="" name="email" size=15></br>'+ 34: '<input type="submit" value="Submit" />'+ 35: '</form>'+ 36: '</body>'+ 37: '</html>'; 38: //response content 39: res.end(body); 40: } 41: //handler for Post request 42: function registerFormHandler (req, res) { 43: console.log('Request handler register was called.'); 44: var pathname = url.parse(req.url).pathname; 45: console.log("Request for " + pathname + " received."); 46: var postData = ""; 47: req.on('data', function(chunk) { 48: // append the current chunk of data to the postData variable 49: postData += chunk.toString(); 50: }); 51: req.on('end', function() { 52: // doing something with the posted data 53: res.writeHead(200, "OK", {'Content-Type': 'text/html'}); 54: // parse the posted data 55: var decodedBody = querystring.parse(postData); 56: // output the decoded data to the HTTP response 57: res.write('<html><head><title>Post data</title></head><body><pre>'); 58: res.write(utils.inspect(decodedBody)); 59: res.write('</pre></body></html>'); 60: res.end(); 61: }); 62: } 63: //Error handler for 404 no found 64: function nofoundHandler(req, res) { 65: console.log('Request handler nofound was called.'); 66: res.writeHead(404, {'Content-Type': 'text/plain'}); 67: res.end('404 Error - Request handler not found'); 68: } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } If there is any change in the local repository folder, GitHub for Windows will automatically detect the changes. In the above step, we have just added a Server.js file so that GitHub for Windows will detect the changes. Let’s commit the changes to the local repository before publishing the web site to Windows Azure. After committed the all changes, you can click publish button which will publish the all changes to Windows Azure repository. The following screen shot shows deployment history from the Windows Azure portal.   GitHub for Windows is providing a sync button which can use for synchronizing between local repository and Windows Azure repository after making any commit on the local repository after any changes. Our web site is running after the deployment using Git Summary Windows Azure Web Sites lets the developers to easily build and deploy websites with support for multiple framework including ASP.NET, PHP and Node.js and can easily deploy the Web Sites using Visual Studio, Git, FTP, Visual Studio Team Foundation Services and Microsoft WebMatrix. In this demo, we have deployed a Node.js Web Site to Windows Azure using Git. We can use GitHub for Windows to publish apps to non-GitHub repositories and can use to publish Web SItes to Windows Azure.

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• Stencil mask with AlphaTestEffect

  - by Brendan Wanlass

  I am trying to pull off the following effect in XNA 4.0: http://eng.utah.edu/~brendanw/question.jpg The purple area has 50% opacity. I have gotten pretty close with the following code: public static DepthStencilState AlwaysStencilState = new DepthStencilState() { StencilEnable = true, StencilFunction = CompareFunction.Always, StencilPass = StencilOperation.Replace, ReferenceStencil = 1, DepthBufferEnable = false, }; public static DepthStencilState EqualStencilState = new DepthStencilState() { StencilEnable = true, StencilFunction = CompareFunction.Equal, StencilPass = StencilOperation.Keep, ReferenceStencil = 1, DepthBufferEnable = false, }; ... if (_alphaEffect == null) { _alphaEffect = new AlphaTestEffect(_spriteBatch.GraphicsDevice); _alphaEffect.AlphaFunction = CompareFunction.LessEqual; _alphaEffect.ReferenceAlpha = 129; Matrix projection = Matrix.CreateOrthographicOffCenter(0, _spriteBatch.GraphicsDevice.PresentationParameters.BackBufferWidth, _spriteBatch.GraphicsDevice.PresentationParameters.BackBufferHeight, 0, 0, 1); _alphaEffect.Projection = world.SystemManager.GetSystem<RenderSystem>().Camera.View * projection; } _mask = new RenderTarget2D(_spriteBatch.GraphicsDevice, _spriteBatch.GraphicsDevice.PresentationParameters.BackBufferWidth, _spriteBatch.GraphicsDevice.PresentationParameters.BackBufferHeight, false, SurfaceFormat.Color, DepthFormat.Depth24Stencil8); _spriteBatch.GraphicsDevice.SetRenderTarget(_mask); _spriteBatch.GraphicsDevice.Clear(ClearOptions.Target | ClearOptions.Stencil, Color.Transparent, 0, 0); _spriteBatch.Begin(SpriteSortMode.Immediate, null, null, AlwaysStencilState, null, _alphaEffect); _spriteBatch.Draw(sprite.Texture, position, sprite.SourceRectangle,Color.White, 0f, sprite.Origin, 1f, SpriteEffects.None, 0); _spriteBatch.End(); _spriteBatch.Begin(SpriteSortMode.Immediate, null, null, EqualStencilState, null, null); _spriteBatch.Draw(_maskTex, new Vector2(x * _maskTex.Width, y * _maskTex.Height), null, Color.White, 0f, Vector2.Zero, 1f, SpriteEffects.None, 0); _spriteBatch.End(); _spriteBatch.GraphicsDevice.SetRenderTarget(null); _spriteBatch.GraphicsDevice.Clear(Color.Black); _spriteBatch.Begin(); _spriteBatch.Draw((Texture2D)_mask, Vector2.Zero, null, Color.White, 0f, Vector2.Zero, 1f, SpriteEffects.None, layer/max_layer); _spriteBatch.End(); My problem is, I can't get the AlphaTestEffect to behave. I can either mask over the semi-transparent purple junk and fill it in with the green design, or I can draw over the completely opaque grassy texture. How can I specify the exact opacity that needs to be replace with the green design?

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• Weird CSS-behaviour [migrated]

  - by WMRKameleon

  <!DOCTYPE html> <html> <head> <title>PakHet</title> <link rel="stylesheet" type="text/css" href="css/basis.css" /> </head> <body> <div class="wrapper"> <div id='cssmenu'> <ul> <li class="active"><a href='index.html'><span>Start</span></a></li> <li><a href='pakhet.html'><span>Over PakHet</span></a></li> <li><a href='overons.html'><span>Over Ons</span></a></li> <li class='has-sub '><a href='#'><span>Uw pakket</span></a> <ul> <li><a href='aanmelden.php'><span>Aanmelden</span></a></li> <li><a href='traceren.php'><span>Traceren</span></a></li> </ul> </li> </ul> </div> <div class="header"> <h1>Hier komt de titel van de website</h1> </div> <div class="content"> <p>Dit is de tekst van de content. Dit is de indexpagina.</p> </div> </div> </body> </html> And this is the CSS: /* CSS RESET */ html, body, div, span, applet, object, iframe, h1, h2, h3, h4, h5, h6, p, blockquote, pre, a, abbr, acronym, address, big, cite, code, del, dfn, em, img, ins, kbd, q, s, samp, small, strike, strong, sub, sup, tt, var, b, u, i, center, dl, dt, dd, ol, ul, li, fieldset, form, label, legend, table, caption, tbody, tfoot, thead, tr, th, td, article, aside, canvas, details, embed, figure, figcaption, footer, header, hgroup, menu, nav, output, ruby, section, summary, time, mark, audio, video, *{ margin: 0; padding: 0; border: 0; vertical-align: baseline; } table { border-collapse: collapse; border-spacing: 0; } /* Einde CSS RESET, nu echte code */ html, body{ background:url(../images/bg_picture.jpg) fixed no-repeat; } .wrapper{ margin:0 auto; } .header{ margin:0 auto; background-color:rgba(0, 0, 0, 0.4); } .content{ background-color:rgba(0, 0, 0, 0.4); width:600px; margin:0 auto; margin-top:50px; } .content p{ color:white; text-shadow:1px 1px 0 rgba(0,0,0, 0.5); font-family:"Lucida Grande", sans-serif; } #cssmenu{ height:37px; display:block; padding:0; margin: 0; border:1px solid; } #cssmenu > ul {list-style:inside none; padding:0; margin:0;} #cssmenu > ul > li {list-style:inside none; padding:0; margin:0; float:left; display:block; position:relative;} #cssmenu > ul > li > a{ outline:none; display:block; position:relative; padding:12px 20px; font:bold 13px/100% "Lucida Grande", Helvetica, sans-serif; text-align:center; text-decoration:none; text-shadow:1px 1px 0 rgba(0,0,0, 0.4); } #cssmenu > ul > li:first-child > a{border-radius:5px 0 0 5px;} #cssmenu > ul > li > a:after{ content:''; position:absolute; border-right:1px solid; top:-1px; bottom:-1px; right:-2px; z-index:99; } #cssmenu ul li.has-sub:hover > a:after{top:0; bottom:0;} #cssmenu > ul > li.has-sub > a:before{ content:''; position:absolute; top:18px; right:6px; border:5px solid transparent; border-top:5px solid #fff; } #cssmenu > ul > li.has-sub:hover > a:before{top:19px;} #cssmenu ul li.has-sub:hover > a{ background:#3f3f3f; border-color:#3f3f3f; padding-bottom:13px; padding-top:13px; top:-1px; z-index:999; } #cssmenu ul li.has-sub:hover > ul, #cssmenu ul li.has-sub:hover > div{display:block;} #cssmenu ul li.has-sub > a:hover{background:#3f3f3f; border-color:#3f3f3f;} #cssmenu ul li > ul, #cssmenu ul li > div{ display:none; width:auto; position:absolute; top:38px; padding:10px 0; background:#3f3f3f; border-radius:0 0 5px 5px; z-index:999; } #cssmenu ul li > ul{width:200px;} #cssmenu ul li > ul li{display:block; list-style:inside none; padding:0; margin:0; position:relative;} #cssmenu ul li > ul li a{ outline:none; display:block; position:relative; margin:0; padding:8px 20px; font:10pt "Lucida Grande", Helvetica, sans-serif; color:#fff; text-decoration:none; text-shadow:1px 1px 0 rgba(0,0,0, 0.5); } #cssmenu, #cssmenu > ul > li > ul > li a:hover{ background:#333333; background:-moz-linear-gradient(top, #333333 0%, #222222 100%); background:-webkit-gradient(linear, left top, left bottom, color-stop(0%,#333333), color-stop(100%,#222222)); background:-webkit-linear-gradient(top, #333333 0%,#222222 100%); background:-o-linear-gradient(top, #333333 0%,#222222 100%); background:-ms-linear-gradient(top, #333333 0%,#222222 100%); background:linear-gradient(top, #333333 0%,#222222 100%); filter:progid:DXImageTransform.Microsoft.gradient( startColorstr='#333333', endColorstr='#222222',GradientType=0 ); } #cssmenu{border-color:#000;} #cssmenu > ul > li > a{border-right:1px solid #000; color:#fff;} #cssmenu > ul > li > a:after{border-color:#444;} #cssmenu > ul > li > a:hover{background:#111;} #cssmenu > ul > li.active > a{ color:orange; } .header{ clear:both; } The problem is that, whenever I hover on the dropdown-menu, that a 1px margin appears in between the menu and the header. Can I solve that? I can't seem to find the solution.

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• Optimization ended up in casting an object at each method call

  - by Aybe

  I've been doing some optimization for the following piece of code : public void DrawLine(int x1, int y1, int x2, int y2, int color) { _bitmap.DrawLineBresenham(x1, y1, x2, y2, color); } After profiling it about 70% of the time spent was in getting a context for drawing and disposing it. I ended up sketching the following overload : public void DrawLine(int x1, int y1, int x2, int y2, int color, BitmapContext bitmapContext) { _bitmap.DrawLineBresenham(x1, y1, x2, y2, color, bitmapContext); } Until here no problems, all the user has to do is to pass a context and performance is really great as a context is created/disposed one time only (previously it was a thousand times per second). The next step was to make it generic in the sense it doesn't depend on a particular framework for rendering (besides .NET obvisouly). So I wrote this method : public void DrawLine(int x1, int y1, int x2, int y2, int color, IDisposable bitmapContext) { _bitmap.DrawLineBresenham(x1, y1, x2, y2, color, (BitmapContext)bitmapContext); } Now every time a line is drawn the generic context is casted, this was unexpected for me. Are there any approaches for fixing this design issue ? Note : _bitmap is a WriteableBitmap from WPF BitmapContext is from WriteableBitmapEx library DrawLineBresenham is an extension method from WriteableBitmapEx

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• How can I find unused/unapplied CSS rules in a stylesheet?

  - by liori

  Hello, I've got a huge CSS file and an HTML file. I'd like to find out which rules are not used while displaying a HTML file. Are there tools for this? The CSS file has evolved over few years and from what I know no one has ever removed anything from it--people just wrote new overriding rules again and again. EDIT: It was suggested to use Dust-Me Selectors or Chrome's Web Page Performance tool. But they both work on level of selectors, and not individual rules. I've got lots of cases where a rule inside a selector is always overridden--and this is what I mostly want to get rid of. For example: body { color: white; padding: 10em; } h1 { color: black; } p { color: black; } ... ul { color: black; } All the text in my HTML is inside some wrapper element, so it is never white. body's padding always works, so of course the whole body selector cannot be removed. And I'd like to get rid of such useless rules too. EDIT: And another case of useless rule: when it duplicates existing one without changing anything: a { margin-left: 5px; color: blue; } a:hover { margin-left: 5px; color: red; } I'd happily get rid of the second margin-left... again it seems to me that those tools does not find such things. Thank you,

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• Repurposing CSS Class Selectors

  - by limefartlek

  I don't know what this technique is called, I've only seen it used. It's a way to repurpose the same selectors with CSS. For example if I create h1 { font-size:18px; color:#FFFFFF; font-family:Arial, Helvetica;margin:0; padding:0; } h2 { font-size:18px; color:#000000; font-family:Arial, Helvetica; font-weight:normal;margin:0; padding:0; } I can repurpose the h selectors with something like .whatever h1 { color: #000; font: 2.0em arial, sans-serif; background-color: #fff3ea; margin: 50px 0px 0px 50px; } .whatever h2 { color: #000; font: 1.7em bold arial, sans-serif; background-color: #fff3ea; margin: 25px 0px 25px 75px; } If h1 and h2 appear inside of a div called whatever, then they will assume those properties. You can do this with ID tags and class tags but I can't for the life of me remember how this is done. Any thoughts?

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• A couple of pattern matching issues with pattern matching in Lua

  - by Josh

  I'm fairly new to lua programming, but I'm also a quick study. I've been working on a weather forecaster for a program that I use, and it's working well, for the most part. Here is what I have so far. (Pay no attention to the zs.stuff. That is program specific and has no bearing on the lua coding.) if not http then http = require("socket.http") end local locale = string.gsub(zs.params(1),"%s+","%%20") local page = http.request("http://www.wunderground.com/cgi-bin/findweather/getForecast?query=" .. locale .. "&wuSelect=WEATHER") local location = string.match(page,'title="([%w%s,]+) RSS"') --print("Gathering weather information for " .. location .. ".") --local windspeed = string.match(page,'<span class="nobr"><span class="b">([%d.]+)</span>&nbsp;mph</span>') --print(windspeed) local condition = string.match(page, '<td class="vaM taC"><img src="http://icons-ecast.wxug.com/i/c/a/[%w_]+.gif" width="42" height="42" alt="[%w%s]+" class="condIcon" />') --local image = string.match(page, '<img src="http://icons-ecast.wxug.com/i/c/a/(.+).gif" width="42" height="42" alt="[%w%s]+" class="condIcon" />') local temperature = string.match(page,'pwsvariable="tempf" english="&deg;F" metric="&deg;C" value="([%d.]+)">') local humidity = string.match(page,'pwsvariable="humidity" english="" metric="" value="(%d+)"') zs.say(location) --zs.say("image ./Images/" .. image .. ".gif") zs.say("<color limegreen>Condition:</color> <color white>" .. condition .. "</color>") zs.say("<color limegreen>Temperature: </color><color white>" .. temperature .. "F</color>") zs.say("<color limegreen>Humidity: </color><color white>" .. humidity .. "%</color>") My main issue is this: I changed the 'condition' and added the 'image' variables to what they are now. Even though the line it's supposed to be matching comes directly from the webpage, it fails to match at all. So I'm wondering what it is I'm missing that's preventing this code from working. If I take out the <td class="vaM taC">< img src="http://icons-ecast.wxug.com/i/c/a/[%w_]+.gif" it'll match condition flawlessly. (For whatever reason, I can't get the above line to display correctly, but there is no space between the `< and img) Can anyone point out what is wrong with it? Aside from the pattern matching, I assure you the line is verbatim from the webpage. Another question I had is the ability to match across line breaks. Is there any possible way to do this? The reason why I ask is because on that same page, a few of the things I need to match are broken up on separate lines, and since the actual pattern I'm wanting to match shows up in other places on the page, I need to be able to match across line breaks to get the exact pattern. I appreciate any help in this matter!

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• Animate button on MouseOver and MouseDown

  - by haagel

  I'm making my own ControlTemplate for a standard Button in WPF. I want to change the background of my button when the user hovers over the button with the mouse, but also when the user presses the button (to yet another color). This seems like a common behavior, but I can't get it to work. My template consists of a Border with an Image inside. It is the background color (a gradient really) of the Border that I want to animate. I have triggers in my template that activates animations (storyboards). The MouseOver/Out works just fine. My problem occurs when I press the button. The Press animation runs as it should, and so does the Release animation. But after this the MouseOut will never run. The button gets stuck in the MouseOver state. What am I doing wrong? <ControlTemplate TargetType="{x:Type Button}"> <ControlTemplate.Resources> <Storyboard x:Key="MouseOverAnimation"> <ColorAnimation Storyboard.TargetName="ButtonBorderGradientStop1" Storyboard.TargetProperty="Color" To="#ffefefff" Duration="0:0:0.2" /> <ColorAnimation Storyboard.TargetName="ButtonBorderGradientStop2" Storyboard.TargetProperty="Color" To="#ffc7c7ff" Duration="0:0:0.2" /> </Storyboard> <Storyboard x:Key="MouseOutAnimation"> <ColorAnimation Storyboard.TargetName="ButtonBorderGradientStop1" Storyboard.TargetProperty="Color" To="#ffeeeeee" Duration="0:0:0.2" /> <ColorAnimation Storyboard.TargetName="ButtonBorderGradientStop2" Storyboard.TargetProperty="Color" To="#ffcccccc" Duration="0:0:0.2" /> </Storyboard> <Storyboard x:Key="MouseDownAnimation"> <ColorAnimation Storyboard.TargetName="ButtonBorderGradientStop1" Storyboard.TargetProperty="Color" To="#ffc7c7ff" Duration="0:0:0.1" /> <ColorAnimation Storyboard.TargetName="ButtonBorderGradientStop2" Storyboard.TargetProperty="Color" To="#ff9a9aff" Duration="0:0:0.1" /> </Storyboard> <Storyboard x:Key="MouseUpAnimation"> <ColorAnimation Storyboard.TargetName="ButtonBorderGradientStop1" Storyboard.TargetProperty="Color" To="#ffefefff" Duration="0:0:0.1" /> <ColorAnimation Storyboard.TargetName="ButtonBorderGradientStop2" Storyboard.TargetProperty="Color" To="#ffc7c7ff" Duration="0:0:0.1" /> </Storyboard> </ControlTemplate.Resources> <Border x:Name="ButtonBorder" CornerRadius="0" BorderBrush="#55aaaaaa" BorderThickness="1" Width="23" Height="22"> <Border.Background> <LinearGradientBrush StartPoint="0,0" EndPoint="0,1"> <GradientBrush.GradientStops> <GradientStop x:Name="ButtonBorderGradientStop1" Color="#ffeeeeee" Offset="0.0" /> <GradientStop x:Name="ButtonBorderGradientStop2" Color="#ffcccccc" Offset="1.0" /> </GradientBrush.GradientStops> </LinearGradientBrush> </Border.Background> <Image x:Name="ButtonIcon" Source="icons/searchicon_bw.png" Width="16" Height="16" /> </Border> <ControlTemplate.Triggers> <Trigger Property="IsMouseOver" Value="True"> <Trigger.EnterActions> <BeginStoryboard Storyboard="{StaticResource MouseOverAnimation}" /> </Trigger.EnterActions> <Trigger.ExitActions> <BeginStoryboard Storyboard="{StaticResource MouseOutAnimation}" /> </Trigger.ExitActions> </Trigger> <Trigger Property="IsPressed" Value="True"> <Trigger.EnterActions> <BeginStoryboard Storyboard="{StaticResource MouseDownAnimation}" /> </Trigger.EnterActions> <Trigger.ExitActions> <BeginStoryboard Storyboard="{StaticResource MouseUpAnimation}" /> </Trigger.ExitActions> </Trigger> </ControlTemplate.Triggers> </ControlTemplate>

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• [Java] Cannot draw pixels

  - by Wilhelm

  Hello everyone. I want to print each digit of pi number as a colored pixel, so, I get na input, with the pi number, then parse it into a list, each node containing a digit (I know, I'll use an array later), but I never get this painted to screen... Can someone help me to see where I'm wrong? package edu.pi.view; import java.awt.Graphics; import java.awt.Image; import java.awt.image.MemoryImageSource; import java.io.BufferedReader; import java.io.File; import java.io.FileReader; import java.util.ArrayList; import java.util.List; import javax.swing.JFrame; import javax.swing.JPanel; public class Main extends JPanel { private static final long serialVersionUID = 6416932054834995251L; private static int pixels[]; private static List<Integer> pi; public static void readFile(String name) { File file = new File(name); BufferedReader reader = null; pi = new ArrayList<Integer>(); char[] digits; try { reader = new BufferedReader(new FileReader(file)); String text = null; while((text = reader.readLine()) != null) { digits = text.toCharArray(); for(char el : digits) if(el != ' ') pi.add(Character.getNumericValue(el)); } } catch (Exception e) { e.printStackTrace(); } } public void paint(Graphics gg) { readFile("c:\\pi.txt"); int h = 5; int w = 2; int color = 0xffffff; int digit; int i = 0; pixels = new int[w * h]; for (int y = 0; y < h; y++) { for (int x = 0; x < h; x++) { digit = pi.get(i); if(digit == 0) color = 0x000000; else if(digit == 1) color = 0x787878; else if(digit == 2) color = 0x008B00; else if(digit == 3) color = 0x00008B; else if(digit == 4) color = 0x008B8B; else if(digit == 5) color = 0x008B00; else if(digit == 6) color = 0xCDCD00; else if(digit == 7) color = 0xFF4500; else if(digit == 8) color = 0x8B0000; else if(digit == 9) color = 0xFF0000; pixels[i] = color; i++; } } Image art = createImage(new MemoryImageSource(w, h, pixels, 0, w)); gg.drawImage(art, 0, 0, this); } public static void main(String[] args) { JFrame frame = new JFrame(); frame.getContentPane().add(new Main()); frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE); frame.setSize(300,300); frame.setVisible(true); } }

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• LUA: A couple of pattern matching issues

  - by Josh

  I'm fairly new to lua programming, but I'm also a quick study. I've been working on a weather forecaster for a program that I use, and it's working well, for the most part. Here is what I have so far. (Pay no attention to the zs.stuff. That is program specific and has no bearing on the lua coding.) if not http then http = require("socket.http") end local locale = string.gsub(zs.params(1),"%s+","%%20") local page = http.request("http://www.wunderground.com/cgi-bin/findweather/getForecast?query=" .. locale .. "&wuSelect=WEATHER") local location = string.match(page,'title="([%w%s,]+) RSS"') --print("Gathering weather information for " .. location .. ".") --local windspeed = string.match(page,'<span class="nobr"><span class="b">([%d.]+)</span>&nbsp;mph</span>') --print(windspeed) local condition = string.match(page, '<td class="vaM taC"><img src="http://icons-ecast.wxug.com/i/c/a/[%w_]+.gif" width="42" height="42" alt="[%w%s]+" class="condIcon" />') --local image = string.match(page, '<img src="http://icons-ecast.wxug.com/i/c/a/(.+).gif" width="42" height="42" alt="[%w%s]+" class="condIcon" />') local temperature = string.match(page,'pwsvariable="tempf" english="&deg;F" metric="&deg;C" value="([%d.]+)">') local humidity = string.match(page,'pwsvariable="humidity" english="" metric="" value="(%d+)"') zs.say(location) --zs.say("image ./Images/" .. image .. ".gif") zs.say("<color limegreen>Condition:</color> <color white>" .. condition .. "</color>") zs.say("<color limegreen>Temperature: </color><color white>" .. temperature .. "F</color>") zs.say("<color limegreen>Humidity: </color><color white>" .. humidity .. "%</color>") My main issue is this: I changed the 'condition' and added the 'image' variables to what they are now. Even though the line it's supposed to be matching comes directly from the webpage, it fails to match at all. So I'm wondering what it is I'm missing that's preventing this code from working. If I take out the <td class="vaM taC">< img src="http://icons-ecast.wxug.com/i/c/a/[%w_]+.gif" it'll match condition flawlessly. (For whatever reason, I can't get the above line to display correctly, but there is no space between the `< and img) Can anyone point out what is wrong with it? Aside from the pattern matching, I assure you the line is verbatim from the webpage. Another question I had is the ability to match across line breaks. Is there any possible way to do this? The reason why I ask is because on that same page, a few of the things I need to match are broken up on separate lines, and since the actual pattern I'm wanting to match shows up in other places on the page, I need to be able to match across line breaks to get the exact pattern. I appreciate any help in this matter!

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• Wrong background colors in Swing ListCellRenderer

  - by Johannes Rössel

  I'm currently trying to write a custom ListCellRenderer for a JList. Unfortunately, nearly all examples simply use DefaultListCellRenderer as a JLabel and be done with it; I needed a JPanel, however (since I need to display a little more info than just an icon and one line of text). Now I have a problem with the background colors, specifically with the Nimbus PLAF. Seemingly the background color I get from list.getBackground() is white, but paints as a shade of gray (or blueish gray). Outputting the color I get yields the following: Background color: DerivedColor(color=255,255,255 parent=nimbusLightBackground offsets=0.0,0.0,0.0,0 pColor=255,255,255 However, as can be seen, this isn't what gets painted. It obviously works fine for the selected item. Currently I even have every component I put into the JPanel the cell renderer returns set to opaque and with the correct foreground and background colors—to no avail. Any ideas what I'm doing wrong here? ETA: Example code which hopefully runs. public class ParameterListCellRenderer implements ListCellRenderer { @Override public Component getListCellRendererComponent(JList list, Object value, int index, boolean isSelected, boolean cellHasFocus) { // some values we need Border border = null; Color foreground, background; if (isSelected) { background = list.getSelectionBackground(); foreground = list.getSelectionForeground(); } else { background = list.getBackground(); foreground = list.getForeground(); } if (cellHasFocus) { if (isSelected) { border = UIManager.getBorder("List.focusSelectedCellHighlightBorder"); } if (border == null) { border = UIManager.getBorder("List.focusCellHighlightBorder"); } } else { border = UIManager.getBorder("List.cellNoFocusBorder"); } System.out.println("Background color: " + background.toString()); JPanel outerPanel = new JPanel(new BorderLayout()); setProperties(outerPanel, foreground, background); outerPanel.setBorder(border); JLabel nameLabel = new JLabel("Factory name here"); setProperties(nameLabel, foreground, background); outerPanel.add(nameLabel, BorderLayout.PAGE_START); Box innerPanel = new Box(BoxLayout.PAGE_AXIS); setProperties(innerPanel, foreground, background); innerPanel.setAlignmentX(Box.LEFT_ALIGNMENT); innerPanel.setBorder(BorderFactory.createEmptyBorder(0, 10, 0, 0)); JLabel label = new JLabel("param: value"); label.setFont(label.getFont().deriveFont( AffineTransform.getScaleInstance(0.95, 0.95))); setProperties(label, foreground, background); innerPanel.add(label); outerPanel.add(innerPanel, BorderLayout.CENTER); return outerPanel; } private void setProperties(JComponent component, Color foreground, Color background) { component.setOpaque(true); component.setForeground(foreground); component.setBackground(background); } } The weird thing is, if I do if (isSelected) { background = new Color(list.getSelectionBackground().getRGB()); foreground = new Color(list.getSelectionForeground().getRGB()); } else { background = new Color(list.getBackground().getRGB()); foreground = new Color(list.getForeground().getRGB()); } it magically works. So maybe the DerivedColor with nimbusLightBackground I'm getting there may have trouble?

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• C# Accessing controls from an outside class without "public"

  - by Kurt W

  I know this has been asked before but I believe my situation is a bit different -- or I don't understand the answers given. I have spent about 4 hours working on this solidly and finally realized, I just don't know what to do. I have 2 Forms (Form1, Settings) and a class I created called Themes. I have get/set properties that currently work but are all within Form1 and I would like to move as much code related to themeing as I can OUTSIDE of Form1 and into Themes.cs. Changing Theme: To change the theme, the user opens up the Settings form and selects a theme from the dropdown menu and presses the 'Set' button -- this all works, but now I want to move it into my own class and I can't get the code to compile. Here is example code that works before moving -- note that this is only 2 different controls I want to modify but there are about 30 total. I am abridging the code: Form 1: public partial class Form1 : Form { public Form1() { InitializeComponent(); } private void btnSettings_Click(object sender, EventArgs e) { Settings frm = new Settings(this); frm.Show(); } private Color txtRSSURLBGProperty; private Color txtRSSURLFGProperty; public Color TxtRSSURLBGProperty { get { return txtRSSURLBGProperty; } set { txtRSSURL.BackColor = value; } } public Color TxtRSSURLFGProperty { get { return txtRSSURLFGProperty; } set { txtRSSURL.ForeColor = value; } } Settings Form: public partial class Settings : Form { public Settings() { InitializeComponent(); } private Form1 rssReaderMain = null; public Settings(Form requestingForm) { rssReaderMain = requestingForm as Form1; InitializeComponent(); } private void button2_Click(object sender, EventArgs args) { // Appearence settings for DEFAULT THEME if (cbThemeSelect.SelectedIndex == 1) { this.rssReaderMain.TxtRSSURLBGProperty = Color.DarkSeaGreen; this.rssReaderMain.TxtRSSURLFGProperty = Color.White; [......about 25 more of these....] } The theme class is currently empty. Again, the goal is to move as much code into the themes class (specifically the get/set statements if at all possible!) and hopefully just use a method similar to this within the Settings form once the proper drowndown item is selected: SetTheme(Default); I hope someone can help, and I hope I explained it right! I have been racking my brain and I need to have this done fairly soon! Much thanks in advance as I'm sure everyone says. I have teamviewer or logmein if someone wants to remote in -- that is just as easy. I can also send my project as a zip if needed. Thanks so much, Kurt Modified code for review: Form1 form: public partial class Form1 : ThemeableForm { public Form1() { InitializeComponent(); } ThemeableForm form: internal abstract class ThemeableForm : Form { private Color rssLabelBGProperty; private Color rssLabelFGProperty; public Color RssLabelBGProperty { get { return rssLabelBGProperty; } set { lRSS.BackColor = value; } } public Color RssLabelFGProperty { get { return rssLabelFGProperty; } set { lRSS.ForeColor = value; } } Settings form: public Settings(ThemeableForm requestingForm) { rssReaderMain = requestingForm as ThemeableForm; InitializeComponent(); } private ThemeableForm rssReaderMain = null; private void button2_Click(object sender, EventArgs args) { // Appearence settings for DEFAULT THEME if (cbThemeSelect.SelectedIndex == 1) { this.rssReaderMain.LRSSBGProperty = Color.DarkSeaGreen; this.rssReaderMain.LRSSFGProperty = Color.White; } Now the all the controls in my get/set (lRSS in the example code above) error out with does not exist in the current context. I also get the warning: Warning 1The designer could not be shown for this file because none of the classes within it can be designed. The designer inspected the following classes in the file: Form1 --- The base class 'RSSReader_BKRF.ThemeableForm' could not be loaded. Ensure the assembly has been referenced and that all projects have been built. 0 0

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