I have a three-dimensional vectorfield containing of coherent structures in the form of counter-rotating circles.
I would like to show these structures three-dimensionally.
So far I have used contour() in order to plot the strucutres on the y,z plane as shown in the figure below, where circles of constant magnitude are plotted.
Now I would like to plot these circles three-dimensionally, this would result in the circles being tilted in the direction of the viewer as one can see from the next plot.
How would I be able to plot such three-dimensional strucutres, where the circles are tilted in the direction of the viewer?
Functions as isosurface() do not seem to help.
I would very much appreciate any kind of help.
I have tried various functions such as isosurface(), quiver3() and streamtube() however I am not able to show the plot I am interested in: a single slice of circles being tilted in the direction of the viewer shown in a three-dimensional plot.
Related
I want to plot the recorded path of an object such as a plane or drone in 3d space using R. The plotted path should be represented by a flat “ribbon” whose orientation perpendicular to the direction of travel changes to reflect the roll of the object. In other words, I want to be able to visualize the path and orientation of the object in one "ribbon" as it banks in turns.
As far as as I can tell, a traditional ribbon plot in R won't allow you to change the orientation in a third dimension.
Matlab and Python have functionality for creating quiver plots where arrows may be placed to indicate the xyz orientation of the object at a given point in time along the path. I cannot find any R packages with similar functionality.
I have played with Plot3D, Plotrgl, Plot3Drgl and cannot find a package that has this capability.
Q1: Are there any packages in R that would support this type of plot?
Q2: If there isn't, how can I go about creating this type of plot R?
Below are examples in Python and Matlab for the 3D quiver type plots, as well as an image demonstrating the ribbon concept I am imagining.
https://medium.com/analytics-vidhya/exploring-data-acquisition-and-trajectory-tracking-with-android-devices-and-python-9fdef38f25ee
Example of 3D quiver plot in python
https://github.com/xioTechnologies/Gait-Tracking-With-x-IMU
Example of 3D quiver plot in matlab
This is an example of what the "ribbon" would look like
Thanks for any help!
I have troubles creating a ternary plot. I tried both the functions in the ggtern and Plotly package. I have a set of (x,y) coordinates, all between 0d and 1. When I just do a regular geom_point() plot, I can nicely see the results in Cartesian space.
Then I have tried the ggtern() function after converting my (x,y) coordinates to ternary space but I get a very different result and the points don't show up with a similar distribution as in Cartesian space.
Since I want to make a ternary contour plot, it seems quite necessary I get a similar distribution of points as in Cartesian space.
I tried the following conversion, with different values for 'direction' option:
Ternary_Coords<-as.data.frame(t(XYToTernary(VarX,VarY),direction=2)))
But my points never look the same as on the cartesian plot.
What could the problem be?
Many thanks in advance!
I have a set of data that I'm trying to create a surface plot of. I have an x,y point and a to colour by.
I can create a xy plot with the points coloured but I can't find a way to create a surface plot with my data. The data isn't on a normal grid and I would prefer to not normalize it if possible (or I could just use a very fine grid).
The data won't be outside the a radius=1 circle so this part would need to be blank.
The code and the plot is shown below.
I've tried using contour, filled.contour as well as surface3d (not what I wanted). I'm not real familiar with many packages in R so I'm not even sure where to begin looking for this info.
Any help in creating this plot would be appreciated.
thanks,
Gordon
dip<-data.frame(dip=seq(0,90,10))
ddr<-data.frame(ddr=seq(0,350,10))
a<-merge(dip,ddr)
a$colour<-hsv(h=runif(nrow(a)))
degrees.to.radians<-function(degrees){
radians=degrees*pi/180
radians
}
a$equal_angle_x<-sin(degrees.to.radians(a$ddr))*tan(degrees.to.radians((90-a$dip)/2))
a$equal_angle_y<-cos(degrees.to.radians(a$ddr))*tan(degrees.to.radians((90-a$dip)/2))
plot(a$equal_angle_x,a$equal_angle_y,col=a$colour,lwd=10)
With regards to the plot I was trying to create is below. I believe the link in the first comment should get me where I'm trying to go.
Here is what I need: I have an image and want to plot on specific rectangle-shaped parts of it (e.g., imagine having a picture of a chessboard and wanting to fill every square with a different color). I would like to be able to easily specify the coordinates for these parts and take these coordinates into R for plotting.
I don't have any experience with making such plots. I've thought of simply inserting an image into a plot with rasterImage (), then plotting with polygon (), but the task of setting up the coordinates for the polygon function seemed too time consuming - hence the question above.
If you have any better ideas than using a set of coordinates for the polygon function, please share. Any leads or packages suggestions would also be helpful.
thank you. Marko.
I just discovered ggmap and I've been playing around with plotting earthquake data from the USGS. I get the data in the form of Lat and Lon, depth and magnitude. I can easily plot the earthquakes as points with different colors based on depth but what I would like to do is take that depth data (just a single number) and generate contours to overlay on the map.
This seems like it should be MUCH more simple than the "Houston Crime" example I keep coming up on since I'm not doing any statistical "density" calculation or anything like that. Basically it's just a contour map on top of the google map of an area.
How do I do this (Presumably) simple, simple thing?
Thanks!
The problem of plotting a 3D surface using only a small sample of unequally spaced lat/long points and a height z (or equivalent) variable is non-trivial -- you have to estimate the values of z for all of the lat-long grid coordinates you do not have, for example using loess() or kriging to create a smooth surface.
Take a look at Methods for doing heatmaps, level / contour plots, and hexagonal binning, case #5. For a geoR example see http://www4.stat.ncsu.edu/~reich/CUSP/Ordinary_Kriging_in_R.pdf