This section details the functionalities provided by the Aggregator class to an ns-3 simulation. An Aggregator object is supposed to be hooked to one or more trace sources in order to receive input. Aggregators are the end point of the data collected by the network of Probes and Collectors during the simulation. Typically, an aggregator is connected to one or more Collectors. To create a GnuplotAggregator in dynamic memory with smart pointers, one just needs to call the ns-3 method CreateObject.
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September 23rd, 5 Comments. Suppose you have a large circular container filled with sand and measure its density at different positions. Now the goal is to display your measurements as a heat map extrapolated from your measurements, but limiting that heat map to the inner part of the container as shown in Fig.
Those data points have to be extrapolated onto a grid for the heat map, which can be achieved by the following commands. The grid data is limited to the boundary given by the measurement points. In addition, the grid is always rectangular in size and not circular. To overcome the first problem you have to add four additional points to the original data in order to stretch the grid boundary to the radius of the container.
For that you have to come up with some reasonable extrapolation from the existing points. I did this in a very simple way by a mixture of linear interpolation or using the value of the nearest point. If you want to do the same with your data set you should maybe spent a little bit more effort on this.
In order to limit the heat map to a circle you first extrapolate the grid using dgrid3d and store the data in a new file. Afterwards a function is defined in order to limit the points to the inner of the circle and plot the data from the temporary file. Finally a few labels and the original measurement points are added.
The manually added points like xmin are removed by a smaller radius value. The result is then the nice circular heat map in Fig. Tags: circle , colormap , dgrid3d , grid , image.
June 21st, 7 Comments. Sometimes a classical heat map will not be the best way to visualize your data in a two dimensional plane. This is especially the case, when only a few data points on the plane have different values. For example in Fig. This is a method used in normal mode analysis of molecules to determine if two different calculations yield similar results.
As you can see only the data points near the diagonal vary, which is hard to see because of the small size of the points. In addition, points farer away from the diagonal having a small percentage value are more or less invisible — compare to Fig. In order to emphasize the data, we abounded the image plot style and use transparent circles as plotting style for visualizing the data as shown in Fig. Before plotting the data we are sorting them regarding their percentage value in order to plot the highest values above the lower ones.
Tags: circle , data , fill , image , palette , sort. June 5th, 7 Comments. If you are looking for nice color maps which are especially prepared to work with cartographic like plots you should have a look at colorbrewer2. On that site hosted by Cynthia Brewer you can pick from a large set of well balanced color maps. The maps are ordered regarding their usage. Figure 1 shows example color maps for three different use cases.
The diverging color maps are for data with extremes at both points of a neutral value, for example like the below and above sea level. The sequential color maps are for data ordered from one point to another and the qualitative color maps are for categorically-grouped data with now explicit ordering. Thanks to Anna Schneider there is an easy way to include them at least the ones with eight colors each into gnuplot. Just go to her gnuplot-colorbrewer github site and download the color maps.
Place them in the same path as your plotting file, or add the three pathes of the repository to your load pathes, for example by adding the following to your. After this you can pick the right color map for you on colorbrewer2. First we load the color map, then switch the two poles of the color map by setting the palette to negative , and finally plotting the data. The nice thing of the palettes coming with gnuplot-colorbrewer is that they also include the corresponding line colors.
In Fig. Tags: colormap , image , lines , load , palette. May 21st, 1 Comment. As you may have noted, gnuplot and Matlab have different default color maps. Designing such a default map is not easy, because they should handle a lot of different things Moreland, : — The map yields images that are aesthetically pleasing — The map has a maximal perceptual resolution — Interference with the shading of 3D surfaces is minimal — The map is not sensitive to vision deficiencies — The order of the colors should be intuitively the same for all people — The perceptual interpolation matches the underlying scalars of the map.
In his paper Moreland developed a new default color map that was mentioned already in a user comment. To use the default color map proposed by Moreland, just download default.
Figure 3 shows the jet color map from Matlab, which is a classical rainbow map with all its pros and cons. Tags: colormap , configuration , data , image , load , palette. March 12th, 12 Comments. We discussed already the plotting of heat maps at more than one occasions. Here we will add the possibility to interpolate the data in a heat map figure. But to be able to interpolate the data we have to use splot and pm3d instead. Note, that the result differs already from the plot command.
The plot command would have created six points, whereas the splot command comes up with only five different regions for every axis. Now if we want to double the number of visible points, we can tell pm3d easily to interpolate the data by the interpolate command. The two numbers 2,2 are the number of additional points along the x- and y-axis. The resulting plot can be found in Fig. In addition to explicitly setting the number of points we can tell gnuplot to choose the correct number of interpolation points by itself, by setting them to 0.
Tags: colormap , image , interpolate , matrix , pm3d , splot. March 15th, 7 Comments. Suppose you have an image and wanted to add some lines, arrows, a scale or whatever to it. Of course you can do this easily with Gnuplot as you can see in Fig. To plot the jpg image of the longnose hawkfish you have to tell the plot command that you have binary data, the filetype, and choose rgbimage as a plotting style.
Also we ensure that the image axes are in the right relation to each other by setting ratio to The scale needs a little more work, because Gnuplot can not plot a axis with tics to both directions of it.
Hence we are using a bunch of arrows to achieve the same result. The text is than set by labels to the axis. Tags: arrow , binary , image , iteration , jpg , label.
September 26th, 8 Comments. If you have not only some data points or a line to plot but a whole matrix, you could plot its values using different colors as shown in the example plot in Fig. Here a 2D slice of the 3D modulation transfer function of a digital breast tomosynthesis system is presented, thanks to Nicholas Marshall from UZ Gasthuisberg Leuven for sharing the data.
All we need to create such a plot is the image plot style, and of course the data have to be in a proper format.
Suppose the following matrix which represents z-values of a measurement. In order to plot these values in different gray color tones, we specify the corresponding palette.
In addition we apply the above mentioned image plot style and the matrix format option. The result is shown in Fig. One remaining problem with Fig. One way to get the desired values is the use command, which can also be used with image.
See Fig. Another way is to store the axes vectors together with the data. Therefore the data has to be stored as a binary matrix. The format of this matrix has to be the following:. The stored binary matrix can then be plotted by adding the binary indicator to the plot command. But if you create vector graphics with this command you will get a really big output file, because every single point will be drawn separately.
For example check the graph from Fig. Tags: binary , colormap , image , Matlab , matrix. Circular heat map. September 23rd, 5 Comments Suppose you have a large circular container filled with sand and measure its density at different positions.
Plotting sparse data. June 21st, 7 Comments Sometimes a classical heat map will not be the best way to visualize your data in a two dimensional plane. Color maps from colorbrewer. June 5th, 7 Comments If you are looking for nice color maps which are especially prepared to work with cartographic like plots you should have a look at colorbrewer2. Default color map. May 21st, 1 Comment As you may have noted, gnuplot and Matlab have different default color maps.
Designing such a default map is not easy, because they should handle a lot of different things Moreland, : — The map yields images that are aesthetically pleasing — The map has a maximal perceptual resolution — Interference with the shading of 3D surfaces is minimal — The map is not sensitive to vision deficiencies — The order of the colors should be intuitively the same for all people — The perceptual interpolation matches the underlying scalars of the map In his paper Moreland developed a new default color map that was mentioned already in a user comment.
Interpolation of heat maps. March 12th, 12 Comments We discussed already the plotting of heat maps at more than one occasions. Images within a graph. March 15th, 7 Comments Suppose you have an image and wanted to add some lines, arrows, a scale or whatever to it.
GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. Skip to content. Permalink Dismiss Join GitHub today GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. Sign up. Branch: master. Find file Copy path.
The source code license is a gratis one, but not a copyleft one; "Permission to modify the software is granted, but not the right to distribute the complete modified source code. One can plot piecewise-defined functions in gnuplot with the ternary condition operator? For instance, one can manually define the absolute value function by:. For piecewise functions, you will likely want many samples, so that discontinuities appear as vertical lines, and corners appear sharp, so:. Using instead of avoids artifacts of having a sample point appear directly on a discontinuity, which can introduce "stair steps. Better yet, switch to parametric mode, map a common t interval  to your individual t ranges, and then:.
Wendel Ricardo flag Denunciar. Hotkeys bind command are disabled if keypress is one of the end conditions. Zooming is disabled if button3 is one of the end conditions. See mouse variables p. Note: Since pause communicates with the operating system rather than the graphics, it may behave differ- ently with different device drivers depending upon how text and graphics are mixed. It offers many different graphical represen- tations for functions and data. See plotting styles p.
Official gnuplot documentation
It primarily goes over the basics of how to plot and fit simple things with Gnuplot. Most of the things here should work well with any reasonably recent version of Gnuplot, but no promises. This tutorial supposes the existance of a sparse data file with a rough decaying exponential. The one I used can be found here.