*3.2.1. Example of basic data plotting*

In this section we shall extract data from a simulation which has setup according to the Figure 3. Please note that this is just an example without any practical use, it serves only as an illustration.

**Figure 3.** Model Setup and Its Voxel Representation (waveguide section with excitation probe at 2.45 GHz, voxels shown in section)

We simulated simple section of a waveguide (inner dimensions 100x50x200 mm) with one side shorted (there is an excitation probe in form of a cylinder in the distance of 17 mm from the shorted end) and the other side open (absorbing boundary condition – absorbs 99.9% of incident power). We extracted the data and plotted them using Matlab.

As you can see (Fig 4ab.) we used several colormaps which enable us to highlight different aspects in our results interpretation. Sometimes it is needed to have contrast colormap (jet, lines – for more information see Product Help of Matlab), at other circumstances you may need to use fine and moderate colormaps (hot, gray, bone, pink – for more information see Product Help of Matlab). In the fourth graph in Fig. 4 we used different shading – faceted. This enables us to highlight structure of computational grid. In many commercial simulators of EM field parts of a model need to be meshed finer than others (e.g. in our case the excitation probe needs to be meshed four times more than the rest of the waveguide to be voxeled sufficiently). In other examples we used shading interp to get more clear view.

electric field *E*, because it is the source of heat generation in exposed samples.)

how the results can be viewed and interpreted.

*3.2.1. Example of basic data plotting* 

an illustration.

GHz, voxels shown in section)

2 *E*

This can be again obtained very simply from amplitude of intensity of electric field. (Note that this same procedure can be used also in the case of intensity of magnetic field *H*, usually in applications involving heating and/or drying we deal only with intensity of

Now that we have three dimensional matrix of values of *RMS|E|* we can plot it to see what our results look like. In the following section there is an example we prepared to illustrate

In this section we shall extract data from a simulation which has setup according to the Figure 3. Please note that this is just an example without any practical use, it serves only as

**Figure 3.** Model Setup and Its Voxel Representation (waveguide section with excitation probe at 2.45

We simulated simple section of a waveguide (inner dimensions 100x50x200 mm) with one side shorted (there is an excitation probe in form of a cylinder in the distance of 17 mm from the shorted end) and the other side open (absorbing boundary condition – absorbs 99.9% of

As you can see (Fig 4ab.) we used several colormaps which enable us to highlight different aspects in our results interpretation. Sometimes it is needed to have contrast colormap (jet, lines – for more information see Product Help of Matlab), at other circumstances you may need to use fine and moderate colormaps (hot, gray, bone, pink – for more information see Product Help of Matlab). In the fourth graph in Fig. 4 we used different shading – faceted. This enables us to highlight structure of computational grid. In many commercial simulators of EM field parts of a model need to be meshed finer than others (e.g. in our case the excitation probe needs to be meshed four times more than the rest of the waveguide to be voxeled sufficiently). In other examples we used shading interp to get more clear view.

incident power). We extracted the data and plotted them using Matlab.

*RMS E* (3)

a - Interpretation of Extracted Data (Y-plane, middle section of the waveguide) [dB]

b - Interpretation of Extracted Data (Y-plane, middle section of the waveguide) [dB]

**Figure 4.** a - (*RMS|E|* colormap-Custom, real modulus E in phase 0° colormap-Hot) b - (from left upper corner to right lower corner: *RMS|E|* colormap-Hot, *RMS|E|* colormap-Jet, *RMS|E|* colormap-Gray, *RMS|E|* shading faceted)

We can also utilize custom colormaps. This can be exceptionally beneficial in applications where we need to find out where values are at some critical level or higher. We illustrated this feature in the first image in Fig. 4a. In Fig. 5. there is an Colormap Editor which can be accessed through: Figure – Edit – Figure Properties – Colormap pull-down menu – Custom.

In our example we set segment in the middle to black colour and segment next to it to white colour. This resulted in the graph as seen in Fig. 4a. For more information on colormaps please refer to the Product Help of Matlab.


**Figure 5.** Colormap Editor Window

Furthermore, we illustrated how real modulus of vector of intensity of electric field at phase 0° is interpreted using Matlab (second image in Fig. 4a.). This is the most basic interpretation of obtained data we can do.

Note that this kind of results interpretation is much more flexible than the interpretation allowed by post processing tools in commercial EM simulators. In the following example we shall show how to work with time dependency of phasors. Since the results of EM field simulator are extracted when the steady state is reached time dependency is reduced to angle of phasors depicting the field of vectors. Through the following method we can alter phase of those phasors and show real part and imaginary part through one period. The results can be seen in Fig. 6. Figure 7. shows example of data processing to achieve this.

**Figure 6.** Phase Shifted Data – real part of vector *E* [dB] (left phase = 0°, right phase = 90°)

Note: In many EM field simulators you may encounter various errors. Pay special attention to the data structure of your exported data since it may not be useful in the way we have shown here (e.g. real and imaginary parts are exported as absolute values so the vital information about phase is lost).

Note: In the part of the script (Fig. 7.) where lowerThan variable is used we are changing the range of values. Since there are parts of model where values of intensity of electric or magnetic field are very near to zero, minimum of these values in dB would be around -400 dB. This renders produced images useless (value range is huge but most of the relevant values are in the region <-50,0>). Using function find we identify indexes of elements with values lower than -50 dB and we replace those elements with value -50 dB. For more information on function find please refer to the Product Help of Matlab.

Note: In this example we use function subaxis which has similar usage as function subplot but allows users to set the layout of plots in the figure more accurately (options Padding, Spacing, Margin etc.). For more information on subaxis please see internet documentation.
