Category Archives: C#

Fun with Visual Studio regexp search

I only recently realized that the Visual Studio regexp feature in Search & Replace is even able to handle regexp captures. Example: In order to locate and replace all line endings in your code which exist at the end of non-empty lines, exluding lines which end at ‘/’ or with other non-alphanumeric characters one can use:

Search Pattern: ([0-9a-zA-Z)])\r\n
Replace: $1;\r\n

searchandreplacevisualstudioMatches inside () parenthesis are captured. When it comes to replacing the match the new value is created by first inserting the captured value at the position marked by ‘$1′. This way it it possible to, let’s say insert a new char in the middle of a search pattern – if it fulfills certain conditions.

There appears to be an error in the MSDN documentation, unfortunately at the point describing how to reference captures in Visual Studio regexp replace patterns. Anyway, using the ‘$’ char in conjunction with the index is the common way and it works here just fine.

Multiple captures are possible as well. Just refer to the captured content by the index according to the count of ‘()’ captures in the search pattern.

The Visual Studio regexp support is really helpful when translating huge C header files to C# – to name only one situations. It saved me a huge amount of time already. Hope you find this useful too.

HDF5 and Matlab Files – Fun with ILNumerics

Why to use HDF5 and ILNumerics?

HDF5 is a file format (Hierarchical Data Format) especially desgined to handle huge amount of numerical data. Just to mention an example,  NASA chose it to be the standard file format for storing data from the Earth Observing System (EOS).

ILNumerics easily handles HDF5 files. They can be used to exchange data with other software tools, for example Matlab mat files. In this post I will show a step by step guide – how to interface ILNumerics with Matlab.

Continue reading HDF5 and Matlab Files – Fun with ILNumerics

ILNumerics for Scientists – Going 3D

Recap

Last time I started with one of the easiest problems in quantum mechanics: the particle in a box. This time I’ll add 1 dimension and we’ll see a particle in a 2D box. To visualize its wave function and density we need 3D surface plots.

2D Box

This time we have a particle that is confined in a 2D box. The potential within the box is zero and outside the box infinity. Again the solution is well-known and can be found on Wikipedia. This time the state of the wave function is determined by two numbers. These are typically called quantum numbers and refer to the X and the Y direction, respectively.

The absolute size of the box doesn’t really matter and we didn’t worry about it in the 1D case. However, the relative size of the length and the width make a difference. The solution to our problem reads

$\Psi_{n,k}(x,y) = \sqrt{\frac{4}{L_x L_y}} \cdot \sin(n \cdot \pi \cdot x / L_x) \cdot \sin(k \cdot \pi \cdot y / L_y)$

The Math

Very similar to the 1D case I quickly coded the wave function and the density for further plotting. I had to make sure that the arrays are fit for 3D plotting, so the code looks a little bit different compared to last post’s

     public static ILArray<double> CalcWF(int EVXID, int EVYID, double LX, double LY, int MeshSize)
     {
        ILArray<double> X = linspace<double>(0, LX, MeshSize);
        ILArray<double> Y = linspace<double>(0, LY, MeshSize);

        ILArray<double> Y2d = 1;
        ILArray<double> X2d = meshgrid(X, Y, Y2d);

        ILArray<double> Z = sqrt(4.0 / LX / LY) * sin(EVXID * pi * X2d / LX) * sin(EVYID * pi * Y2d / LY);

        return Z.Concat(X2d,2).Concat(Y2d,2);
     }

Again, this took me like 10 minutes and I was done.

The Visualization

This time the user can choose the quantum numbers for X and Y direction, the ratio between the length and the width of the box and also the number of mesh points along each axis for plotting. This makes the visualization panel a little bit more involved. Nevertheless, it’s still rather simple and easy to use. This time it took me only 45 minutes – I guess I learned a lot from last time.

The result

Here is the result of my little program. You can click and play with it. If you’re interested, you can download the Particle2DBox source code. Have fun!

Particle2DBoxThis is a screenshot of the application. I chose the second quantum number along the x axis and the fourth quantum number along the y axis. The box is twice as long in y direction as it is in x direction. The mesh size is 100 in each direction. On the left hand side you see the wave function and on the right hand side the probability density.

Directions to the ILNumerics Optimization Toolbox

As of yesterday the ILNumerics Optimization Toolbox is out and online! It’s been quite a challenge to bring everything together: some of the best algorithms, the convenience you as a user of ILNumerics expect and deserve, and the high performance requirements ILNumerics sets the scale on for. We believe that all these goals could be achieved quite greatly.

Continue reading Directions to the ILNumerics Optimization Toolbox

ILNumerics for Scientists – An easy start

Motivation

I’ve been working as a scientist at universities for 10 years before deciding to go into industry. The one thing I hated most was coding. At the end of the day coding for scientists is like running for a football player. Obviously, you need it but it’s not what you’re here for.

I really dreaded the coding and the debugging. So much precious time for something that was so clear on paper and I just wanted the solution of my equations to see whether my idea made sense or not. More often than not scientists find that their idea was not so great and now they had spent so much time coding just to find out that the idea didn’t work. Continue reading ILNumerics for Scientists – An easy start

Getting to know your Scene Graph

Did you ever miss a certain feature in your ILNumerics scene graph? You probably did. But did you know, that most of the missing “features” mean nothing more than a missing “property”? Often enough, there is only a convenient access to a certain scene graph object needed in order to finalize a required configuration.

Recently, a user asked how to turn the background of a legend object in ILNumerics plots transparent. There doesn’t seem to be a straight forward way to that. One might expect code like the following to work:

var legend = new ILLegend("Line 1", "Line 2");
legend.Background.Color = Color.FromArgb(200, Color.White);

Continue reading Getting to know your Scene Graph

Uncommon data conversion with ILArray

ILNumerics Computing Engine supports the most common numeric data types out of the box: double, float, complex, fcomplex, byte, short, int, long, ulong

If you need to convert from, let’s say ushort to float, you will not find any prepared conversion function in ILMath. Luckily, it is very easy to write your own:

Here comes a method which implements the conversion from ushort -> float. A straight forward version first:

        /// <summary>
        /// Convert ushort data to ILArray&lt;float>
        /// </summary>
        /// <param name="A">Input Array</param>
        /// <returns>Array of the same size as A, single precision float elements</returns>
        public static ILRetArray<float> UShort2Single(ILInArray<ushort> A) {
            using (ILScope.Enter(A)) {
                ILArray<float> ret = ILMath.zeros<float>(A.S);
                var retArr = ret.GetArrayForWrite();
                var AArr = A.GetArrayForRead();
                int c = 0;
                foreach (ushort a in A) {
                    retArr[c++] = a;
                }
                return ret;
            }
        }

Continue reading Uncommon data conversion with ILArray

ILNumerics Language Features: Limitations for C#, Part II: Compound operators and ILArray

A while ago I blogged about why the CSharp var keyword cannot be used with local ILNumerics arrays (ILArray<T>, ILCell, ILLogical). This post is about the other one of the two main limitations on C# language features in ILNumerics: the use of compound operators in conjunction with ILArray<T>. In the online documentation we state the rule as follows:

The following features of the C# language are not compatible with the memory management of ILNumerics and its use is not supported:

  • The C# var keyword in conjunction with any ILNumerics array types, and
  • Any compound operator, like +=, -=, /=, *= a.s.o. Exactly spoken, these operators are not allowed in conjunction with the indexer on arrays. So A += 1; is allowed. A[0] += 1; is not!

Let’s take a closer look at the second rule. Most developers think of compound operators as being just syntactic sugar for some common expressions:

int i = 1;
i += 2;

… would simply expand to:

int i = 1;
i  = i + 2; 

For such simple types like an integer variable the actual effect will be indistinguishable from that expectation. However, compound operators introduce a lot more than that. Back in his times at Microsoft, Eric Lippert blogged about those subtleties. The article is worth reading for a deep understanding of all side effects. In the following, we will focus on the single fact, which becomes important in conjunction with ILNumerics arrays: when used with a compound operator, i in the example above is only evaluated once! In difference to that, in i = i + 2, i is evaluated twice.

Evaluating an int does not cause any side effects. However, if used on more complex types, the evaluation may does cause side effects. An expression like the following:

ILArray<double> A = 1;
A += 2;

… evaluates to something similiar to this:

ILArray<double> A = 1;
A = (ILArray<double>)(A + 2); 

There is nothing wrong with that! A += 2 will work as expected. Problems arise, if we include indexers on A:

ILArray<double> A = ILMath.rand(1,10);
A[0] += 2;
// this transforms to something similar to the following: 
var receiver = A; 
var index = (ILRetArray<double>)0;
receiver[index] = receiver[index] + 2; 

In order to understand what exactly is going on here, we need to take a look at the definition of indexers on ILArray:

public ILRetArray<ElementType> this[params ILBaseArray[] range] { ... 

The indexer expects a variable length array of ILBaseArray. This gives most flexibility for defining subarrays in ILNumerics. Indexers allow not only scalars of builtin system types as in our example, but arbitrary ILArray and string definitions. In the expression A[0], 0 is implicitly converted to a scalar ILNumerics array before the indexer is invoked. Thus, a temporary array is created as argument. Keep in mind, due to the memory management of ILNumerics, all such implicitly created temporary arrays are immediately disposed off after the first use.

Since both, the indexing expression 0 and the object where the indexer is defined for (i.e.: A) are evaluated only once, we run into a problem: index is needed twice. At first, it is used to acquire the subarray at receiver[index]. The indexer get { ...} function is used for that. Once it returns, all input arguments are disposed – an important foundation of ILNumerics memory efficency! Therefore, if we invoke the index setter function with the same index variable, it will find the array being disposed already – and throws an exception.

It would certainly be possible to circumvent that behavior by converting scalar system types to ILArray instead of ILRetArray:

ILArray A = ...;
A[(ILArray)0] += 2;

However, the much less expressive syntax aside, this would not solve our problem in general either. The reason lies in the flexibility required for the indexer arguments. The user must manually ensure, all arguments in the indexer argument list are of some non-volatile array type. Casting to ILArray<T> might be an option in some situations. However, in general, compound operators require much more attention due to the efficient memory management in ILNumerics. We considered the risk of failing to provide only non-volatile arguments too high. So we decided not to support compound operators at all.

See: General Rules for ILNumerics, Function Rules, Subarrays