I know dual-axes time series plots can be misleading. They're difficult to make in ggplot because Hadley Wickham believes they are fundamentally flawed. Others have concluded that they are ok sometimes, when axes are chosen so that the lines look as though they had been converted to indices first (even if they are given in their actual units). I'm wondering if this example is one in which dual-axes are justifiable.
This online tool is an example similar to what I want to create: https://carve.ornl.gov/visualize/
Measurements taken at the same point in time, from the same flight, are plotted over time. The user can select any two measurements to overlay, and the time matches up with a map showing flight coordinates. I think this is an elegant way for users to interact with the data, and I can't really imagine an alternative that would convey the same information.
That being said, I am interested to hear other opinions. Will this type of plot draw vitriol from other data scientists?! Do you have other ideas? And, if you have recommendations for what R tools I should turn to (since ggplot might be off the table...), I would love to hear them (I will be using Shiny). Thanks!
The debate on multiple axis on a same cartesian plane is indeed a hot one. It reminds me of the endless debates around social science´s approaches.
If you follow the orthodoxy of the Grammar of GraphicsG Gospel, then the graph you linked is flawed. To come back into the herd, you could simply map either the CO2 or the Altitude to a different plotted symbology, like the size of the dots or color. Or simply plot two different panels, aligned by the X scale.
Now, the Grammar of Graphic people have much fewer problems with multiple scales on the plotted scales than on the cartesian scales.
Yet, I think that methodological opportunism is preferable to methodological orthodoxy. Do whatever is easier for you to communicate the idea to the public.
I would like to use ggmap to plot several data points on top of a koppen-geiger climate map.
The kopper-geiger data and GIS/KMZ maps can be downloaded here:
http://koeppen-geiger.vu-wien.ac.at/present.htm
I've managed to have a code to plot the points on regular maps, obtained through the get_map function but I fail to use other maps such as koppen-geiger.
Any help will be appreaciated!
Your basic problem is that the map you are attmepting to use is an image file that is not georeferenced. So unless you want to go through the unnecessary and probably time consuming process of georeferencing this image yourself, you will be better taking an alternative approach. There are perhaps a few ways to do this. But, unless you have very few data points to overlay on the map which you can place manually using the lat-long grid of the image, then the least painful method will certainly be to redraw the map yourself using the shapefile.
This is not the right place to give you an introductory lesson on GIS, but the basic steps are to
Download shapefile (which is available at the same website as the image you linked)
Project map to desired coordinate system
Plot map, coloring by climate class
Color the ocean layer
Add labels, legend, and graticule, as desired
Overplot with your own climate data, and legend for these.
If you are unsure how to approach any of these steps, then take an introductory course on GIS, and search the Web for instructional materials. You may find this resource useful.
https://cran.r-project.org/doc/contrib/intro-spatial-rl.pdf
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.
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.
Recently a few neat uses of ggplot2 have come up, and either partial or full solutions have been posted:
ggheat
Curly braces
position_dynamic
ggheat is notable because it rather breaks the ggplot metaphor by just plotting rather than returning an object.
The curly brace solutions are notable because none really fits in the ggplot2 high-level concept (e.g. you should be specifying a range of points you want to breaks, and then somewhere else be able to specify the geom of how you want that range displayed--brace, box, purple cow, etc.).
The ggplot2 book (which I will order soon and have read the 2 online chapters) seems to be about using the grammar and functions rather than writing new ones or extensively extending existing ones.
I would like to learn to add a specific feature or develop a new geom, and do it properly. ggplot2 may not be intended as a general graphics package in the same way that grid or base graphics are, but there are a great many graphs which are only a step or two extension from an existing ggplot2 geom. When these situations come up, I can typically put together enough objects to do something once, but what if I need the same plot a few dozen times? What if other people like it and want to use it--now they have to kludge through the same process each time they want that graph. It seems to me that the proper solution is to add in a stat_heatplot and geom_heatplot, or to add a geom_Tuftebox for Tufte box plots, etc. Yet I've never seen an example of actually extending ggplot2; just examples of how to use it.
What resources exist to dig deeper into ggplot2 and start extending it? I'm particularly interested in a high-level way to specify a range on an axis as described above, but general knowledge about what makes ggplot2 tick is welcome as well.
Absent a coherent guide (which rarely exists for sufficiently advanced tinkering and therefore may not exist here), how would one go about learning about the internals? Inspecting source is obviously one way, but what functions to start with, etc.
ggplot2 is gradually becoming more and more extensible. The development version, https://github.com/hadley/ggplot2/tree/develop, uses roxygen2 (instead of two separate homegrown systems), and has begun the switch from proto to simpler S3 classes (currently complete for coords and scales). These two changes should hopefully make the source code easier to understand, and hence easier for others to extend (backup by the fact that pull request for ggplot2 are increasing).
Another big improvement that will be included in the next version is Kohske Takahashi's improvements to the guide system (https://github.com/kohske/ggplot2/tree/feature/new-guides-with-gtable). As well as improving the default guides (e.g. with elegant continuous colour bars), his changes also make it easier to override the defaults with your own custom legends and axes. This would make it possible to draw the curly braces in the axes, where they probably belong.
The next big round of changes (which I probably won't be able to tackle until summer 2012) will include a rewrite of geoms, stats and position adjustments, along the lines of the sketch in the layers package (https://github.com/hadley/layers). This should make geoms, stats and position adjustments much easier to write, and will hopefully foster more community contributions, such as a geom_tufteboxplot.
I am not certain that I agree with your analysis. I'll explain why, and will then point you to some resources for writing your own geoms.
ggheat
As far as I can tell, ggheat returns an object of class ggplot. Thus it is a convenient wrapper around ggplot, customised for a specific use case. Although qplot is far more generic, it does in principle the same thing: It is a wrapper around ggplot that makes some informed guesses about the data and chooses sensible defaults. Hadley calls this plot functions and it is described briefly on page 181 of the ggplot2 book.
curly braces
The curly brace solution does exactly what the ggplot philosophy says, i.e. separate data from presentation. In this case, the data is generated by a little custom function and is stored in a data.frame. It is then displayed using a geom that makes sense, i.e. geom_line.
quo vadis?
You have noted (in the r chat room) that you would prefer to have a more generic approach to plotting the curly braces. Something along the following lines (and I paraphrase and extend at the same time):
Supply data in the form of a bounding box coordinates (i.e. x0, x1, y0 and y1)
Specify a "statistic", such as brace, box or whatever
Specify a geom, such as geom_custom_shape
This sounds like a nice generalisation and extension of the ideas behind the curly brace solution, and would clearly require writing a new geom. There is an official ggplot wiki, where you can find instructions for creating a new geom.
Why do you want to extend it? What is the motivation? As I see it ggplot2 is meant to be a high-level graphics package designed to produce nice figures from a particular data set. And do things right and make other things easy: like scales, legends etc. ggplot2 is not meant to be a general-purpose graphics tool-kit. Like lattice it has a particular paradigm in mind and you use it for that purpose.
grid is the underlying graphical toolkit you want to use to do general purpose, customised plotting. And IIRC, it is relatively easy to add grid grobs to lattice or ggplot2 plots/objects, for this sort of arbitrary notation/annotation etc.
What doesn't make too much sense is extending ggplot2 or lattice along the lines you are thinking. I don't see why the ggplot2 can't do heatplots as it is? Or am I missing something here?
What would be very useful would be if the data processing guts of ggplot2 or lattice were available for others to write actual plotting code on top of. Hadley has mentioned this somewhere before.
ggplot2, in particular, and lattice are quite difficult codes to get into to read/understand. ggplot2 uses the proto package for a version of OOP, which means you need to understand what that is doing as well as ggplot2 semantics. lattice is similar as there is a lot of computing on the language done there that, if you are not familiar with that sort of R programming, can by quite intimidating, daunting and impenetrable!
For grid, I suggest you look at Paul Murrell's R Graphics book, a second edition of which is with the publisher: http://www.stat.auckland.ac.nz/~paul/RG2e/
Edit: The point I was intending to get across was that the interfaces provided by packages like ggplot2 and lattice are necessarily high-level. Extending them is fine as long as they stick to the paradigm/philosophy in use. Heatplots can already be made by using existing geoms; part of the philosophy of the ggplot system is to separate the data from the display/presentation, and to use geoms in interesting ways to produce the desired display.
Wrapping base ggplot + geom calls into a more user friendly function is OK as long as i) it works like ggplot already does and returns an object, and ii) it doesn't have an interface that is too different from the way ggplot works. Developers are free to write whatever code they want, it just isn't helpful to the wider community to provide wrappers that move too far away from the original's workings. That leads to confusion on the part of the user and doesn't foster learning of ggplot2 itself.
The dynamic positioning idea is interesting; you could include these ideas in all plotting packages. You could bolt this into a geom, or alternatively as an external function that modified the input coordinates to produce a new data object that could be used by the relevant geom. That same function could be used for other plotting packages - it wouldn't need to be ggplot-specific.