Source of image : https://math.stackexchange.com/questions/144268/is-there-a-name-for-this-type-of-plot-function-on-complex-plane-vs-time-shown
I had in one of my lectures a graph of how sin, cos and exp are related in complex domain with a figure that close to that one. I searched on-line a lot until I found that picture on Math.SE.
As per my search I found that it is only PTC mathcad that is stating it is possible to draw complex domain graphs but couldn't find any information related in mathcad manual or even in books including such graphs. Did any one managed to have such graphs drawn before. I would appreciate it as it will help me imagine graphically the circulation of complex numbers and the changes in formulas.
Can any one help?
In Mathcad, use CreateSpace with the appropriate functions of time. You'll have to open the plot dialog box to set the various axis and backplane options. You'll also need to ensure that each of the 3 plot elements is set to Data Points rather than Surface (the default display for the 3D plot component).
I typed the plot's expressions for exp, sin and cos elsewhere in the worksheet and then dragged them onto the plot.
Related
I know it is possible to create such double pie charts in excel like this:
http://chandoo.org/wp/2009/12/02/group-small-slices-in-pie-charts/
but can SPSS or R do this also?
In relation to R:
The answer to the title question is "yes" ... see ?pie
As for the second question, the one in the body - it would be possible but would involve some coding. You'd have to draw two pie charts side by side (which could be managed with two calls to pie) and use segments or arrows (and text if necessary) to do the additional components of the plot.
Here's a rough example:
That required the fig argument of par to get them side-by-side.
(That example required a little fiddling to get right, but it would be possible to write a function to automate the details.)
The main issue I can see would be 'why on earth would you do it?' -- pie charts are a poor way of conveying information of this form. There are alternatives that result in much better ability to distinguish values, and less bias (such as what you get when comparing nearly horizontal vs nearly vertical slices).
Link to sample image with tilting graph:
Link to NVD3 Streamgraph page:
The nvd3 streamgraph will descend or ascend sharply over time. I searched SO and the NVD3 documentation but didn't find a variable that controls where the zero of the y axis is at each point in time. Nor have I found discussions of this. In other words what makes the whole graph tilt in one direction or the other and how to control or turnoff this tilt.
I read a bit of the initial paper on streamgraphs by Byron but couldn't figure it out and thought I'd ask here.
Could someone please point me towards documentation on this or otherwise provide insight?
The NVD3 code for the stacked area chart accepts four possibilities for the chart style: stack, stream, stream-center, and expand. The default stream graph is the "stream" style, and this is the version that gets off-centre if you have any zero values in your data.
If you set the style explicitly to "stream-center", the chart behaves as expected. However, the radio buttons that switch between display styles switch back to the problematic algorithm, so they will need to be disabled.
chart.style('stream-center')
.showControls(false);
It's possible that the existence of this other display algorithm means that the NVD3 folks are working on it. The github issue page might be a good place to look for updates or responses from them:
https://github.com/novus/nvd3/issues/416
I'm getting familiar with Graphviz and wonder if it's doable to generate a diagram/graph like the one below (not sure what you call it). If not, does anyone know what's a good open source framework that does it? (pref, C++, Java or Python).
According to Many Eyes, this is a bubble chart. They say:
It is especially useful for data sets with dozens to hundreds of values, or with values that differ by several orders of magnitude.
...
To see the exact value of a circle on the chart, move your mouse over it. If you are charting more than one dimension, use the menu to choose which dimension to show. If your data set has multiple numeric columns, you can choose which column to base the circle sizes on by using the menu at the bottom of the chart.
Thus, any presentation with a lot of bubbles in it (especially with many small bubbles) would have to be dynamic to respond to the mouse.
My usual practice with bubble charts is to show three or four variables (x, y and another variable through the size of the bubble, and perhaps another variable with the color or shading of the bubble). With animation, you can show development over time too - see GapMinder. FlowingData provides a good example with a tutorial on how to make static bubble charts in R.
In the example shown in the question, though, the bubbles appear to be located somewhat to have similar companies close together. Even then, the exact design criteria are unclear to me. For example, I'd have expected Volkswagen to be closer to General Motors than Pfizer is (if some measure of company similarity is used to place the bubbles), but that isn't so in this diagram.
You could use Graphviz to produce a static version of a bubble chart, but there would be quite a lot of work involved to do so. You would have to preprocess the data to calculate a similarity matrix, obtain edge weights from that matrix, assign colours and sizes to each bubble and then have the preprocessing script write the Graphviz file with all edges hidden and run the Graphviz file through neato to draw it.
I recently found this web page Crime in Downtown Houston that I'm interested in reproducing. This is my first learning experience with mapping in R and thus lack the vocabulary and understanding necessary to make appropriate decisions.
At the end of the page David Kahle states:
One last point might be helpful. In making these kinds of plots, one
might tempted to use the map raster file itself as a background. This
method can be used to make map plots much more quickly than the
methods described above. However, the method has one very significant
disadvantage which, if not handled properly, can destroy the entire
purpose of using the map.
In very plain English what is the difference between the raster file
approach and his approach?
Does the RgoogleMaps package have the ability to produce these types
of high quality maps as seen on the page I referenced above that
calls a google map into R?
I ask not because I lack information but the opposite. There's too much and I want to make a good decision(s) about the approach to pursue so I'm not wasting my time on outdated or inefficient techniques.
Feel free to pass along any readings you think would benefit me.
Thank you in advance for your direction.
Basically, you had two options at the time this plot was made:
draw the map as a layer using geom_tile, where each pixel of the image is mapped onto the x,y axes (slow but accurate)
add a background image to the plot, as a purely "cosmetic" annotation. This method is faster, because you can use grid.raster which draws images more efficiently, but the image is not constrained by the axes of the plotting region. In other words, you have to manually adjust the x and y axes limits to make sure that the image corresponds to the actual positions on the plot.
Now, I would suggest you look at the new annotation_raster in ggplot2 v. 0.9.0. It should have the advantage of speed and leaner output files, and still conform to the data space of the plot. I believe that this function, as well as geom_raster and annotation_map did not exist when David made those plots.
I'm trying to make a visualization that looks like this http://www.gradient-da.com/img/temperature%20surface%20plot%20470x406.JPG http://www.gradient-da.com/img/temperature%20surface%20plot%20470x406.JPG.
The idea is to have a 3D surface plot overlapping a 2d representation of a surface.
I can build arbitrary surfaces/polygon shapes (as in http://addictedtor.free.fr/graphiques/graphcode.php?graph=135 ) and I can make the respective 2D plot. What I don't seem to be able to figure out is the way to put them together in a nice way (like the one shown in the jpg above).
I've tried googling for the answer, but I wasn't able to find anything similar done in R.
Any help would be greatly appreciated!
EDIT: The 2D portion is not a projection of the 2D one. I chose this specific picture to illustrate this. For example
Here the 2D portion is the image of the circuit and on the 3D portion is the temperature).
In 2D you can have the map of a city and in 3D the traffic
etc...
Best,
Bruno
I will give a theoretical Idea,
In the same 3D plot, select a plane perpendicular to the 3D surface (just below the 3D-surface) and project all the values to it. Instead of 2D & 3D plot, you will use only a 3D plot, which also plots your surface.
HTH
It looks like the 2D plot is a layout of a microelectronic circuit, albeit with some detail skipped, and the 3D plot is perhaps a thermal plot of the same circuit.
I don't know enough about R's capabilities, but I imagine it would be easier to generate the two plots separately with R from the same dataset which represents the layout information (but with and without the thermal data) and then combine them with a graphics manipulation program.
No help in R, but you can do something similar in ROOT as seen in this image:
taken from the THistPainter class documentation.
The code is open source and could be examined if wanted for reimplementation.
Maybe you should try to make an opengl texture out of your 2d picture and map it on a 3d polygon to be included in your scenegraph?
Don't really understand if you wish to do it with R specifically, so maybe diving in opengl is a too low level for you. In case you'd be ready for that, you may reuse a simple java library that simplify plotting 3d surface: http://code.google.com/p/jzy3d
Hope that helps,
Martin
What you're looking for is called a texture map -- and if it's not provided in the R graphics package, you may be able to do it "by hand". The suggestion below may not be fast or convenient (or even helpful, as I'm not really familiar with R), but it may actually work...
Since you know you can draw a 3D surface plot with specified colors, you can try drawing a flat 3D surface using the colors of your image.
If R also lacks methods for extracting its data from image formats, there is an image format called PPM (standing for Portable PixMap), one variant of which is basically space-separated decimal numbers. After converting your image to this format (using Photoshop, say, or some dedicated image conversion program), it should be relatively easy to input into R.