Reactions

I got a lot of emails after the last two posts (first, second) of people that liked the post and are interested in learning more. Most emails asked me to go into more details about how I did all that. Obviously, not too many people are interested in implementing the particle in a box, so the “what” is not as interesting as the “how”.

In this post I want to focus on the visualization part of the previous two examples and how ILNumerics helped me. As many of our users are scientists and engineers they are typically experts in the computation part but appreciate a little help in the visualization. If you’re interested in the computation part, please be patient until the next post.

The Form

I started by creating a new project in Visual Studio and chose Windows Forms Application. This gives me a vanilla Form1.cs. That’s the basis of all the visualization and helps me – being a scientist and not a coder – a lot, because I couldn’t do all that without the help of Visual Studio in the background.

On the left-hand side in the Toolbox panel I picked TableLayoutPanel under Containers and dragged it into Form1.cs.

I adjusted the table to have three rows and a single column. In the Properties section under Dock I chose Fill so that everything scales when scaling the window later on.

A right click on Table -> Edit Rows and Columns allows you to change the behavior of the three rows. I wanted the first and last row not to scale when changing the window. This is what I chose here.

In the middle row we would like to see two ILNumerics panels. So I dragged another TableLayoutPanel in the middle row and chose two columns and one row. Choosing Dock = Fill for the new table and dragging two ILPanels into the respective columns (again with Dock = Fill) gives us the layout for our final Windows Form.

In the header (the first row) I inserted a FlowLayoutPanel that makes sure that everything in there will be displayed rather neatly. Then I added the labels and the NumericUpDown according to my needs. Please make sure that you go through the properties of every item and choose the values according to your needs. In my case, for instance, the minimum value for the state is 1, since 0 would mean that there is no particle present. Here is the final picture of the form for the 1D particle in a box:

The Wiring

After having the layout ready the interactivity needs to be implemented. In this case there is only one point of user interaction. The user can choose which eigenvector to display. Double-clicking on the NumericUpDown control opens a new tab with a predefined class and a function handling the event when a user changes the value of the eigenvector.

All that’s needed now is to implement the function numericUpDown1_ValueChanged. This is particularly simple in our case. We just call the Update function (still to be implemented) with the new value for the eigenvector.

In the case of the 2D particle in a box we have, in fact, four events that should trigger the Update function. This is easily done by introducing these lines of code in the public function Form1():

     numericUpDown1.ValueChanged += Update;
     numericUpDown2.ValueChanged += Update;
     numericUpDown3.ValueChanged += Update;
     textBox1.TextChanged += Update;

The Implementation

Now, all we need to do is to implement the Update function and the initialization. The initialization makes sure that all the plotting objects are created when starting the program.

     public Form1()
     {
        InitializeComponent();

        var EVID = 1;
        var MeshSize = 1000;

        InitializePanel1(EVID, MeshSize);
        InitializePanel2(EVID, MeshSize);

        label2.Text = string.Format("In appropriate units the energy is {0}", EVID * EVID);
     }

     private void InitializePanel1(int EVID, int MeshSize)
     {
        ILArray<float> XY = ILMath.tosingle(Computing_Module1.CalcWF(EVID, MeshSize));
        var color = Color.Black;
        ilPanel1.Scene =
          new ILScene {
            new ILPlotCube {
              new ILLinePlot (XY, lineColor : color)
            }
          };
     }

The call to Computing_Module1.CalcWF will be explained in the next post. The piece of code above initializes the wave function plot and the density plot in their respective panels with the first eigenvector and a mesh size of 1000.

Finally, the Update function is implemented.

     private void Update(int EVID, int MeshSize = 1000)
     {
       ILArray<float> XY = ILMath.tosingle(Computing_Module1.CalcWF(EVID, MeshSize));
       ilPanel1.Scene.First<ILLinePlot>().Update(XY);
       ilPanel1.Scene.First<ILPlotCube>().Reset();
       ilPanel1.Refresh();

       ILArray<float> XD = ILMath.tosingle(Computing_Module1.CalcDensity(EVID, MeshSize));
       ilPanel2.Scene.First<ILLinePlot>().Update(XD);
       ilPanel2.Scene.First<ILPlotCube>().Reset();
       ilPanel2.Refresh();
       label2.Text = string.Format("In appropriate units the energy is {0}", EVID * EVID);
     }

Again, the CalcWF and CalcDensity calls will be explained in the next post. The Reset() function rescales the axes and the Refresh() function finally puts the new plot on screen.

The post ILNumerics for Science – How did you do the Visualization? appeared first on The ILNumerics Blog.

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.

To make things worse even in the case that the idea was good the code was typically in a scripted language like Python or Matlab and now needed to be rewritten in Fortran or C++. Isn’t there a better way of doing things? Isn’t there a way where the idea creation and the formulation is the bottle neck and not the coding? I could’ve spent so much more time on valuable thinking instead of senseless coding.

Now, obviously, I’m going to tell you how ILNumerics does exactly that. And, obviously, I do that because I work for them. Still, this is my experience and this is how easy it was. And at the end of the day, you’re not going to buy our product because of this blog post, rather because you downloaded our free trial and convinced yourself.

The Problem

Let’s start with one of the simplest problems in quantum mechanics – the particle in a box. This is a quantum mechanical particle in a potential-free box with an infinite potential outside the box. In other words, the particle is forced to stay within the box. Anybody unfamiliar with this problem can read the Wikipedia article about this.

The solution to this problem is well-known and can be found analytically. As always in quantum mechanics, the solution is quantized with infinitely many solutions – also known as states. Each of the solutions consists of a wave function associated with a corresponding energy.

$\Psi_n(x) = \sqrt{\frac{2}{L}} \sin(n \cdot \pi \cdot  x)$

In the equation above $n$ designates the $n^{th}$ state and $L$ is the length of the box, set to 1 in our case.

The Goal

My goal is to display the wave function and the probability density of a user-chosen state. I choose a simple problem and a simple goal because I’m just getting started. Obviously, this is not one of the problems I faced as a scientist in my earlier life, but it is a nice example.

The Solution

Let’s start with the mathematical part. First I implemented the wave function for a given state. As the wave function is supposed to be plotted it is discretized over a mesh. Here is my body of my function:

     ILArray<double> X = linspace<double>(0,1,MeshSize);
     ILArray<double> Y = sqrt(2.0)*sin(EVID*pi*X);
     return vertcat(X,Y);

The parameter EVID is the eigenvector ID, i.e. an integer greater than 0 to identify which state should be calculated. I coded the same for the density, which basically means squaring the wave function stored in vector Y.

Done in less than 10 minutes!!!

The Graphs

The rest is all about the presentation to the user. So I created a simple Windows Form with a numeric up/down counter (to allow the user to choose the state) and two panels for simple line plots. I just needed to wire all the components to make sure that the plots were rescaled and updated after the user changes the state. This took me some more time, because it was the first time for me. Still it took me only 60 minutes and done.

The Result

Here you can find the result of my simple little program. You can download the source code and play with it. Have fun!

The post ILNumerics for Scientists – An easy start appeared first on The ILNumerics Blog.

And here comes the code used to create this example:

private void ilPanel1_Load(object sender, EventArgs e) {
    // create some test data
    ILArray<float> A = ILSpecialData.torus(1.3f, 0.6f);

    // create the plot: a simple surface
    ilPanel1.Scene.Add(new ILPlotCube(twoDMode: false) {
        new ILSurface(A, colormap: Colormaps.Summer) {
            // we also want a colorbar
            new ILColorbar() {
                Background = {
                    Color = Color.DarkGray
                }
            }
        }
    });

    // set the backcolor of the scene to black
    ilPanel1.BackColor = Color.Black; 

    // set labels color
    foreach (var label in ilPanel1.Scene.Find<ILLabel>()) {
        label.Color = Color.White;
        label.Fringe.Width = 0;
    }

    // set the color of the default labels for axis ticks
    foreach (var axis in ilPanel1.Scene.Find<ILAxis>()) {
        axis.Ticks.DefaultLabel.Color = Color.White;
        axis.Ticks.DefaultLabel.Fringe.Width = 0;
    }

    // some more configuration: the view limits
    ilPanel1.Scene.First<ILPlotCube>().Limits.Set(
        new Vector3(0, 0, 1), new Vector3(2, 2, -1));

}

In line 4 we use the ILSpecialData class to create some test data. torus() creates the X, Y and Z values which eventually assemble a torus when used in ILSurface. The next line creates and adds a new plot cube to the scene. We set its two2Mode property to false, so we can rotate the torus with the mouse.

The next line creates a new surface and provides the torus data to it. As colormap ‘Colormaps.Summer’ is configured. Most surfaces need a colorbar in order to help mapping colors to actual values. We add a new colorbar below the surface and set its background color to some dark value.

Next, the BackColor of the main panel is set to black. Note, that setting the background color of a panel must be done in code in the current version (3.3.3). This is due to a bug in ILPanel which causes settings made in the designer to be ignored!

Now we have a dark background color but the labels still remain black. So let’s fix this: all labels which are part of the regular scene graph can easily be set at once. We simply use the ILGroup.Find() function to enumerate all labels and set their color to white. Also, we remove the fringe around them. Alternatively we could have set the fringe color to some dark color.

The last issue remaining is caused by the fact that labels for ticks cannot be configured here. The reason is, that tick labels are created dynamically. they don’t even exist at the time of execution of this code. So we must configure a thing called ‘DefaultLabel‘ instead. DefaultLabel is a member of the ticks collection of every axis object and used at runtime to provide default properties for all tick labels in auto mode.

This gives a nice dark color scheme. Keep in mind that the default color values for all scene-/plot objects are currently optimized for light background colors. Using dark backgrounds, therefore requires one to adjust the color on all plot objects accordingly.

The post Dark color schemes with ILPanel appeared first on The ILNumerics Blog.

ILView: a simple way to create interactive 3d visualizations

We have created ILView as an extension to our interactive web component: It allows you to simply try out ILNumerics’ 2d and 3d visualization features by chosing the output format .exe in our visualization examples. But that’s not all: ILView is also a general REPL for the evaluation of computational expressions using C# language. ILView is Open Source – find it on GitHub!

ILNumerics Scene Graph: realize complex visualizations in .NET

The ILNumeric’s scene graph is the core of ILNumerics’ visualization engine. No matter if you want to create complex interactive 3D visualizations, or if you aim at enhancing and re-configuring existing scenes in .NET: The ILNumerics scene graph offers a convenient way to realize stunning graphics with C#. It uses OpenGL, GDI, and it’s possible to export scenes into vector and pixel graphics.

Scientific Plotting: visualize your data using C#

With ILNumerics’ visualization capabilities, C# becomes the language of choice for scientists, engineers and developers who need to visualize data: Our plotting API and different kinds of plotting types (contour plots, surface plots etc.) make easy work of creating beautiful scientific visualizations.

The post C# for 3D visualizations and Plotting in .NET appeared first on The ILNumerics Blog.

There are two other web applications that cause a lot of excitement in the scientific community at the moment: The IPython Notebook and Shiny, a tool for creating web applications in R. Let’s have a closer look…

IPython Notebook: “Interactive Computational Environment”

The IPython Notebook adresses the huge amount of Python users in the scientific community. It basically offers a new way for writing papers: It’s a web based editor for code execution, math, text and visualization. Because the IPython Notebook combines all parts you normally need to write a scientific paper, you won’t have to import / export different elements from several domain specific software applications: “Everything related to my analysis is located in one unified place”, explains Philip J. Guo in his blog (http://www.pgbovine.net/ipython-notebook-first-impressions.htm). Once you have finished your paper, you can share your IPython Notebook as HTML and PDF with your colleagues, your professor etc.

Shiny: “Easy web applications in R”

Shiny stands for a different approach: It allows you to implement own analysis into web applications. While IPython obviously adresses Python users, Shiny is based on R, a still very popular programming language among statisticians. What makes Shiny interesting are its interactivity features: Most demos on the Shiny website offer the opportunity to choose input parameters from text fields or drop-downs to dynamically change the output visualization. The code seems to be quite similar to R, so users who are familiar with that language will easily be able to create interactive data visualization applications for their websites using Shiny.

Disadvantages: Performance does matter

Both approaches make web browsers accesable for specific needs of scientific visualization: The IPython Notebook offers a convenient tool to share the results of analytics related research; Shiny allows R developers to publish particular interactive plots on the web.

However, both projects are limited – namely because of technological issues. The level of performance that can be realized with both platforms is restricted: You’ll face that at the latest when you start creating complex 3d scenes with either Python or R. This holds true for the platforms’ web applications, too…

Outlook: Scientific Computing online

For certain purposes web based scientific computing software offers new convenient solutions. But if you want to realize complex interactive 3d visualizations, you still won’t use any of them but an application on your local machine instead.

Our interactive web examples point the direction we want to go. In order to make scientific computing more powerful, we’re working on the next step of our approach: a full WebGL support for ILNumerics. Stay tuned…

The post Scientific Computing Online: IPython Notebook, Shiny (R) and ILNumerics appeared first on The ILNumerics Blog.