I want to plot a 3D array M where
M <- array(runif(64),dim=c(4,4,4))
A similar question is here with comments that this can be done using a common 3D plot in R, but I could find no such function in R which can be used to plot multidimensional arrays (say, a 3D array as in the above example). Any suggestion how to do it? Thanks.
Use melt to create a table of x,y,z,value, and then rgl to do a 3d plot:
library(reshape2)
library(rgl)
M=melt(M)
points3d(M$Var1,M$Var2,M$Var3)
That's just 64 points in a cube. You can scale and colour them:
points3d(M$Var1,M$Var2,M$Var3,size=10,color=rainbow(10)[M$value*10])
Use whatever method of mapping M$value to colour you prefer. Don't use rainbow palettes for real!
Related
I am using the contour function from Julia's Plots to plot level curves. I want to extract a list of x coordinates and a list of y coordinates corresponding to the level curves from the plot, e.g., something like this. Is there a way to do it in Julia?
Not for contour, unfortunately. For most plot types you can extract the input data of, e.g. the first series in the first subplot, with p[1][1][:x]. But for contour in particular Plots does not generate the level curves, it simply passes the matrix to the backend that then does the computation and display.
I'm trying to figure out how to create surface plots with Plots.jl. I can create a spherical surface from a 2-d mesh like below:
using Plots
plotlyjs()
# Read the theta and phi angles from file...
x2d = sind(theta2d).*cosd(phi2d)
y2d = sind(theta2d).*sind(phi2d)
z2d = cosd(theta2d)
surface(x2d,y2d,z2d)
However, I want to have the surface color be controlled by a separate matrix like the plot below (made with Python).
from mayavi import mlab
# Create/read plot data...
mlab.figure(bgcolor=(1,1,1), fgcolor=(0.,0.,0.))
mlab.mesh(x2d, y2d, z2d, scalars=p2d, colormap='jet', vmax=5, vmin=-35)
Perhaps I should just use the Python plotting functions directly? Or maybe GLVisualize directly?
Thanks!
You can supply the matrix controlling the colors as the fill_z keyword. It doesn't work on all backends, but try plotljys and pyplot.
I'm new to R so please bear with me; I have six 3D arrays (c0, ..., c5) and I need to overlap the individual arrays into one 3D scatter plot. I have one scatter plot using the c0 array with...
library(scatterplot3d) ; scatterplot3d(c0)
... and get the following plot:
Any idea how to add on the other five arrays, with different colors & shapes?
Also, any other suggestion for interactive use? Like python's 3D plots allow for zooming, rotating plot for different views, etc.
UPDATE:
The c0 array is as follows (used read.table('...')); there are 1000 elements, but this will give an idea.
> c0
C4_1548 Mg2_2796 Si4_1393
1 0.703216519 0.611332440 0.715913967
4 -0.073868874 0.333571615 0.174178337
5 0.584873346 -0.398325128 -0.038525721
I have a function z=f(x,y) and want to plot it using octave, but don't want the plot to be in 3d, as in
octave:1> x=(1:300);
octave:2> y=(1:300);
octave:3> [xx,yy]=meshgrid(x,y);
octave:4> A=sin(xx/100).*yy;
octave:5> mesh(x,y,A)
but rather in 2d using colors for the values of z, like what you get using the gnuplot instruction
gnuplot> plot 'a.txt' matrix w image
if I save the matrix A in the file a.txt. The closest I have found is the command contourf, but the as you can see if you try it,
octave:7> contourf(xx,yy,A)
the result is far from optimal... Any suggestion?
Thanks
imagesc will plot a matrix of your "z" values using colors:
> imagesc(x, y, A)
This will be inverted vertically compared to contourf, but that's easily fixed:
> imagesc(x, flipud(y), flipud(A))
And in your example you don't even need to provide the variables x and y:
> imagesc(A)
> imagesc(flipud(A))
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)