I have a code to plot a world map with a meteorological field for one moment (or one measure).
Is it possible to successively plot the map for different moments (for i from 1 to 125) in order to view a sort of video when we run the code?
Yes, look at the animation package.
It can creates an animated gif for you (as well as other tricks). There are live examples you can look at as eg Buffon's needle, a CLT demo and much more.
The package abstracts away some of the OS-dependent layers. If you know the basics, you can of course just call the corresponding tool from the imagemagick project which is likely to be available on OS of choice too.
Related
I was trying to allow the user to give a curve as input for some analysis. Is there a package that can be used in this regard? Basically, a GUI like paint wherein the user can draw a simple curve and which would be stored in R as a set of data points or as an equation if its a simple curve.
Thanks
Gopher
Reading mouse input
Below is a list of sample approaches to first the problem, from the most complex to simplest (IMHO).
I would recommend that you have a look at the
qtpaint
package.
Less laborious solution may involve looking at the way interactive
plots in Shiny are handled. Using the click option would
enable you to get the mouse cursor position. Together with the Shiny
framework this would provide a convenient wrapper to get mouse input
from a user.
Finally, third approach could rely on making use of the locator function available in the graphics package. Depending on what you intend to do, this may be the simplest solution as you could then use read values to inform generation of your graphic.
Generating graphics
Assuming that you got your values via the locator functionality you could attempt to draw your line using segments. It would be a little fiddly as you would have to translate your coordinates to some placement of the dot in your desired chart but this wouldn't computationally too taxing, just a matter of bring mouse pointer values to some x/y values on the chart.
If you care to update your post with a sample code and reproducible attempts of your previous work, I bet the question will receive more replies. You may find this discussion on making a reproducible example in R helpful.
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'd like to create a heat map in R that I want to use on a website. I stumbled upon the SVGAnnotation package which seems to be very nice to process SVG graphics in R to make them more interactive. First, I was planning to add tool tips for each cell in the heatmap - if the user hovers over the cell, the value of this cell should pop up. However, I am fighting with SVGAnnotation for more than 3 hours now, reading and trying things, and I can't get it to work.
I would appreciate any help on the SVGAnnotation tool tip function. But I would also very much appreciate alternatives to SVGAnnotation to add some activity to my R SVG heatmap.
So, what I have got so far looks like this:
library(SVGAnnotation)
data(mtcars)
cars <- as.matrix(mtcars)
map <- svgPlot(heatmap(cars))
addToolTips(map, ...) # problem
saveXML(map, "cars.svg")
My problem is the addToolTips function itself, I guess. Intuitively, I would simply insert the data matrix, i.e., cars, but this does not work and R gets stuck (it's calculating, but doesn't return anything, I waited 50 minutes)
EDIT:
After some more online research, I found a good example of what I want to achieve: http://online.wsj.com/article/SB125993225142676615.html#articleTabs=interactive
This heat map looks really great, and the interactive features (tool tips) work very well. I am wondering how they did that. To me, it looks like the graphic was done in R using the ggplot package.
I wrote a command line tool that can do exactly that if you are still interested to add tool tips to your heat map. It runs in Windows/Linux/MacOS terminals. All you need as input is the heat map as svg file and the data table/matrix that you used as input to create your heat map as csv or other text file.
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 have a large directed acyclic graph that I would like to visualize in a bitmap image.
Ideally I'd like to have all the root nodes at the top of the image, and all of the leaf nodes at the bottom, i.e. the graph edges are all pointing in a downwards direction.
Is there a good algorithm for working out the coordinates of all the nodes that meets these constraints and will produce a good visualization?
I advise you to use Gephi.
This soft is able to do all the things you want to, especially graph layouts !
Look at the Graphviz software collection. It contains several programs to render graphs.
The most simple way is to write your graph to disk, in one of Graphviz's text formats. Then execute one of the render programs, and load the resulting image into your application.
Bayesian Networks have similar requirements. You might look for algorithms for Bayesian Networks. This paper for example might be helpful.
If the graph is fairly simply then bitmaps will serve you fairly well. For very dense graphs however you'll want something with vector graphics, such as a SVG file that will support zooming in and out of fine details in a more friendly manner. Better yet is to use an interactive tool dedicated to navigating a graph such as gephi like someone mentioned above or yED
If you're trying to visualize a software dependency graph the best tool I've found for navigating is the DGML tools that are part of Visual Studio. They use a very powerful Sugiyama tree layout that does a fine job of making the flow of the graph directional. They have powerful interactive features with these edge hopping links that are bar none. You can also organize subgraphs and collapse them down, etc.
There's several graph description languages covered in Wikipedia with checking out
https://en.wikipedia.org/wiki/Category:Graph_description_languages. If you have a good chunk of RAM the DGML tools can render very pleasantly and make the interaction and exploration of the graph very intuitive.
There's a decent overview of layout techniques to be seen here particularly #2 Layered Graph Drawing from Kozo Sugiyama.
You might be interested in layered graph drawing (also known as "hierarchical graph drawing" or "Sugiyama-style graph drawing"). The algorithm is too long to describe here, but Google searches bring up many reliable explanations.
You can try this Go package I wrote: https://github.com/h8liu/e8tools/tree/master/dagvis
An example: http://lonnie.io/gostd/dagvis/