In R package,
is there any way to smoothen the polygon in a polar.plot?
I tried to use the splines, but could not find a way to insert the curved line in the polar.plot..
(I am a begginer in R programming)
I know that mathematically with polar plotting you can get smoothed polygons. An example here is for the square if you plot: 1 + Sin[4*x]/20 from 0 to 2 $\pi$ you will get a smoothed square. Change 4 to 5 and adjust the other constants by interpolation and you may find yourself happy.
Related
I am looking for a way to plot a wind 3D direction in R or MATLAB.
There are 3 given vector components:
u : x-axis (horizontal)
v : y-axis (horizontal)
w : z-axis (vertical)
For plotting wind directions in 2D, there is the traditional way of using a rose plot like this: https://commons.wikimedia.org/wiki/File:Wind_rose_plot.jpg
Do you have any idea, how I can plot this in 3D using the R statistic engine or MATLAB, by using the additional w vector?
Thanks a lot!
In MATLAB quiver3 will be the most relevant to your case. More information and examples here.
I have been searching for this quite a while, but cannot find an answer to my problem or a minimum example. I would like to make a 3D-plot of a matrix.
An extract of my data looks like this. There are the years, which I would like to use as X-Axis. There is Y, which I would like to use as Y and I would like to plot z.
Year y z
2000 1 467
2000 2 10678
2000 2 25
...
How can I make this a surface plot?
Best
Have you tried searching for how to plot a surface plot in R? It turns out there's at least a persp function, a package called plot3D, wireframe in lattice and plotly.
For starters, try (from the plot3D package vignette)
library(plot3D)
example(persp3D)
example(surf3D)
example(slice3D)
example(scatter3D)
example(segments3D)
example(image2D)
example(image3D)
example(contour3D)
example(colkey)
example(jet.col)
example(perspbox)
example(mesh)
example(trans3D)
example(plot.plist)
example(ImageOcean)
example(Oxsat)
I cannot find a straightforward way to make a nice image plot in R, but in polar coordinates. I'm basically attempting to find a R equivalent for the 'polarplot3d' function in MATLAB. I've been playing around with ggplot2 package but without much luck. Am I missing a package that contains functionality for what I'm attempting? thanks in advance for any pointers.
Ok, I'm trying to be more clear about what I'm trying to do. Lets say I want to define a polar coordinate grid, increments in the radial direction are 50m and 2.5 degrees in theta. This should look like a dartboard.
My data (r and angle in below code) are correspond to a radial distance measure and an angle. My desired z-value is the counts of a bivariate histogram between r and angle within the increments described above defining the grid.
My data is like the following:
# synthetic data for angle and distance #
angle <- rnorm(500,mean=90,sd=15)
r <- rnorm(500,mean=700,sd=200)
# bivariate histogram #
observations <- table(cut(angle,breaks=c(seq(0,360,by=2.5))),cut(r,breaks=c(seq(0,1400,by=50))))
# the 'z' data are in observations for each bin of bivariate histogram #
# hot to plot a polar coord image? #
It's very slow to render on my system, but
library(reshape2)
library(ggplot2)
mm <- melt(counts)
ggplot(mm,aes(Var1,Var2,fill=value))+geom_tile()+coord_polar()
ggsave("polar1.png")
appears to work.
I think the following could work. Use mapproject() from the maproj library to transform my xy coordinates acording to a polar projection (or another), Then use as.image() (from fields package) function to build a image object from my new coordiantes and my Z values. Eventually use image.plot().
library("mapproj")
xyProj <- mapproject(x, y, projection="conic", parameters=-90)
library("fields")
im <- as.image(z, x=xyProj)
image.plot(im)
I have a set of data, looks like:
x y z
1 1 2 1
2 3 5 7
3 -3 2 4
4 -2 1 1
so each row record the dot coordinate in a 3-D space. I want to plot all the dot as points except for one, say no.15 as a translucent sphere, with radius I can set. Then I can see from the plot that which of those points in the data are included in the sphere. I'm using RGL package right now and did the following:
> open3d()
> plot3d(readin,col=3,type="p")
> plot3d(readin[15,],col=2,add=T,type="s",radius=0.1)
So the first plot command plotted the whole set as scatter plots and the second plot command picked the 15th row of the data and plot it as a sphere and add it to the previous canvas. I just wondering if I can make the sphere translucent so that I can see which dots a included in the sphere which means those dots are very near to the one I select.
Is there a way to do this by RGL Or you can provide me another ways to complete this task?
Thanks!
I think what you are looking for is the argument alpha.
Example
df <- data.frame(x=c(1,3,-3,-2), y=c(2,5,2,1),z=c(1,7,4,1))
library(rgl)
open3d()
plot3d(df,col=3,type="p", radius=0.5)
plot3d(df,col=rgb(1,0,0.3),alpha=0.5, add=T,type="s",radius=1)
You can plot transparent spheres using the alpha argument to spheres3d. You can rotate the plot to move the box line behind the sphere to prove it's transparent.
spheres3d(dat[4,],col=rgb(1,0,0), alpha=0.9) # transparent red.
(I tried to do it with the alpha argument to rgb but it failed.)
If you just want to find out which points are within a certain radius of point 15 then you can calculate the Euclidean distance from each point to point 15 and see which of those distances are less than the radius. No plotting needed (though you could plot those points as a different color to highlight them. The dist function is one way to compute the distances, or it is simple to program yourself.
I am writing an regression algorithm which tries to "capture" points inside boxes. The algorithm tries to keep the boxes as small as possible, so usually the edges/corners of the boxes go through points, which determines the size of the box.
Problem: I need graphical output of the boxes in R. In 2D it is easy to draw boxes with segments(), which draws a line between two points. So, with 4 segments I can draw a box:
plot(x,y,type="p")
segments(x1,y1,x2,y2)
I then tried both the scatterplot3d and plot3d package for 3D plotting. In 3D the segments() command is not working, as there is no additional z-component. I was surprised that apparently (to me) there is no adequate replacement in 3D for segments()
Is there an easy way to draw boxes / lines between two points when plotting in three dimensions ?
The scatterplot3d function returns information that will allow you to project (x,y,z) points into the relevant plane, as follows:
library(scatterplot3d)
x <- c(1,4,3,6,2,5)
y <- c(2,2,4,3,5,9)
z <- c(1,3,5,9,2,2)
s <- scatterplot3d(x,y,z)
## now draw a line between points 2 and 3
p2 <- s$xyz.convert(x[2],y[2],z[2])
p3 <- s$xyz.convert(x[3],y[3],z[3])
segments(p2$x,p2$y,p3$x,p3$y,lwd=2,col=2)
The rgl package is another way to go, and perhaps even easier (note that segments3d takes points in pairs from a vector)
plot3d(x,y,z)
segments3d(x[2:3],y[2:3],z[2:3],col=2,lwd=2)