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Is there a way to draw a scatter plot in Julia (preferably with gr backend), in which every point has an arrow pointing to a specified direction on it?
Specifically, my task is to create a gif image with multiple moving points with a small arrow on every point pointing to the direction of its velocity.
So, you want to plot a vector field, right?
The "arrow plot" you are looking for, is usually called quiver-plot in many programming languages. In Julia, too.
If you use Plots.jl the syntax is quiver(x,y,quiver=(u,v)), where x and y are the coordinate vectors and u and v the arrow magnitude vectors.
If you use GR or PyPlot directly the syntax is possibly a bit different.
Small Example
using Plots
gr()
N = 10
x = rand(1:10,N)
y = rand(1:10,N)
u = rand(N)
v = rand(N)
scatter(x,y)
quiver!(x,y,quiver=(u,v))
I'm trying to plot 3-dimensional vectors (x, y, z coordinates) onto a 3D coordinate system in R like in the picture below. Ideally, I would then like to construct 3d kernel density plots, also like in the image below.
Ideal result of vector plot and 3d kernel density plot
I have a matrix containing ~100 rows and one column for each coordinate (x, y , z). Initially, I tried arrow3D() from the plot3D package but I find the perspective to be sub-par, it's rather difficult to discern directions of the arrows from one perspective in the final plot. Next I tried the rgl package which gives me interactivity - great. Minimal working example:
library(rgl)
library(matlib)
data2 <- data.frame(replicate(6,rnorm(100))) #sample data set for minimum working example
colnames(data2) <- c("x_target", "y_target", "z_target", "x_start", "y_start", "z_start")
x1 <- data2$x_target - data2$x_start
y1 <- data2$y_target - data2$y_start
z1 <- data2$z_target - data2$z_start
vec <- (diag(6,3)) # coordinates for x, y and z axis
rownames(vec) <- c("X", "Y", "Z") # labels for x, y and z axis
z <- as.matrix((data.frame(x=x1, y=y1, z=z1)))
open3d()
vectors3d(vec, color=c(rep("black",3)), lwd=2, radius=1/25)
vectors3d(X=z, headlength=1/25)
(due to the random numbers generator the strange looking rods appear at different coordinates, not exactly like in the image i link to below)
The result of the code above is a version of the image link below. One set of coordinates produces a very strange looking more like rod object which is far longer then the coordinates would produce. If I plot the vectors individually, no such object is created. Anyone have any ideas why this happens? Also, if anyone has a tool (doesn't have to be R), that can create a 3D vector plot like in the first image, I'd be grateful. I find it to be very complicated in R, but I'm definitely a beginner.
Strange object to the right (long red rod that doesn't look like an arrow at all)
Thank you!
This is due to a bug in the matlib package, fixed in verson 0.9.2 of that package. I think you need to install it from Github instead of CRAN to get the bug fix:
devtools::install_github("friendly/matlib")
BTW, if you are using random numbers in a reproducible example, you can make it perfectly reproducible by something like
set.seed(123)
at the start (or some number other than 123). I saw reproducible problems with your example for set.seed(4).
I am trying to solve the following problem in R :
I have a polygon object defined by a list l with two components x and y. The order defines the edges of the polygon.
For instance :
l=list(
x=c(-1.93400738955091,0.511747161547164,1.85047596846401,-1.4963460488281,-1.31613255558929,-0.0803828876660542,1.721752044722,-0.724002506376074,-2.08847609804132,2.13366860069641),
y=c(-1.02967154136169,1.53216851658359,-1.39564869249673,-1.21266011692921,1.6419616619241,-1.87141898897228,0.946605074767527,1.49557080147009,0.324443917837958,-0.517303529772633)
)
plot(l,type="b",pch=16)
points(l$x[c(10,1)],l$y[c(10,1)],type="b",pch=16)
Now what I am interested in is to keep only the outer boundary (but not the convex hull) of this polygon. The following picture highlights the point I'd like to keep
points(
x=c(-1.13927707377209,-1.31613255249992,-1.3598262571216,0.511747159281619,0.264900107013767,0.671727215417383,-0.724002505140328,-1.93400738893304,-1.4811931364624,-1.45298543105533,-2.08847609804132,-1.40787406113029,-1.3598262571216,0.278826441754518,1.85047596733123,1.48615105742673,1.48615105742673,2.13366860069641,1.38016944537233,1.38016944537233,1.17232981688283,1.17232981688283,1.72175204307433,0.671727215417383,-1.496346, -0.08038289, -0.2824999),
y=c(1.13914087952916,1.64196166071069,0.949843643913108,1.53216851597378,1.27360509238768,1.18229006681548,1.49557080106148,-1.02967154055378,-0.972634663817139,-0.525818314106921,0.324443915423533,0.188755761926866,0.949843643913108,-1.30971824545964,-1.3956486896768,-0.59886540309968,-0.59886540309968,-0.517303527559411,-0.367082245352325,-0.367082245352325,0.0874657083966551,0.0874657083966551,0.94660507315481,1.18229006681548,-1.21266,-1.871419,-1.281255),
pch=16,
col="red",
cex=0.75
)
I am really clueless about whether there are tools to easily do that. The closest I have found is the polysimplify function in the polyclip package, which identifies all the points I need, but also outputs some points I do not need (inner points where segments intersect).
I actually found a solution (below). The following function does what I want but I am unsure why it works (and whether it may fail).
Actually the function below correctly identifies the point I want but outputs them in the wrong order, so it is still useless to me...
polygon.clean<-function(poly){
require(polyclip)
poly.cleaned=polysimplify(poly)
x=unlist(sapply(poly.cleaned,function(x)x$x))
y=unlist(sapply(poly.cleaned,function(x)x$y))
x.src=x[!x%in%x[duplicated(x)]]
y.src=y[!y%in%y[duplicated(y)]]
poly.cleaned=poly.cleaned[sapply(poly.cleaned,function(poly.sub,x,y){
any(poly.sub$x%in%x&poly.sub$y%in%y)
},x=x.src,y=y.src)]
x=unlist(sapply(poly.cleaned,function(x){
res=x$x
if(length(res)==4){
res=vector()
}
res
}))
y=unlist(sapply(poly.cleaned,function(x){
res=x$y
if(length(res)==4){
res=vector()
}
res
}))
x=c(x,x.src)
y=c(y,y.src)
tester=duplicated(x)&duplicated(y)
x=x[!tester]
y=y[!tester]
list(x=x,y=y)
}
plot(l,type="b",pch=16)
points(l$x[c(10,1)],l$y[c(10,1)],type="b",pch=16)
points(polygon.clean(l),pch=16,cex=0.75,col="red")
Using rgeos routines, you first "node" your linestring to create all the intersections, then "polygonize" it, then "union" it to dissolve its insides.
First make a SpatialLines version of your data with duplicated first/last point:
library(sp)
library(rgeos)
coords = cbind(l$x, l$y); coords=rbind(coords,coords[1,])
s = SpatialLines(list(Lines(list(Line(coords)),ID=1)))
Then:
s_outer = gUnaryUnion(gPolygonize(gNode(s)))
Plot it thus:
plot(s,lwd=5)
plot(s_outer, lwd=2,border="red",add=TRUE)
If you want the coordinates of the surrounding polygon they are in the returned object and can be extracted with:
s_outer#polygons[[1]]#Polygons[[1]]#coords
# x y
# [1,] 0.27882644 -1.30971825
# [2,] -0.08038289 -1.87141899
# [3,] -0.28886517 -1.27867953
Assuming there's only one polygon, which might not be the case - suppose your line traces a figure-of-eight - then you'll get two polygons touching at a point. We don't know how free your jaggly line is to do things like that...
t = 0:%pi/50:10*%pi;
plot3d(sin(t),cos(t),t)
When I execute this code the plot is done but the line is not visible, only the box. Any ideas which property I have to change?
Thanks
The third argument should, in this case, be a matrix of the size (length arg1) x (length arg2).
You'd expect plot3d to behave like an extension of plot and plot2d but it isn't quite the case.
The 2d plot takes a vector of x and a vector of y and plots points at (x1,y1), (x2,y2) etc., joined with lines or not as per style settings. That fits the conceptual model we usually use for 2d plots - charting the relationship of one thing as a function of another, in most cases (y = f(x)). THere are other ways to use a 2d plot: scatter graphs are common but it's easy enough to produce one using the two-rows-of-data concept.
This doesn't extend smoothly to 3d though as there are many other ways you could use a 3d plot to represent data. If you gave it three vectors of coordinates and asked it to draw a line between them all what might we want to use that for? Is that the most useful way of using a 3d plot?
Most packages give you different visualisation types for the different kinds of data. Mathematica has a lot of 3d visualisation types and Python/Scipy/Mayavi2 has even more. Matlab has a number too but Scilab, while normally mirroring Matlab, in this case prefers to handle it all with the plot3d function.
I think of it like a contour plot: you give it a vector of x and a vector of y and it uses those to create a grid of (x,y) points. The third argument is then a matrix whose dimensions match those of the (x,y) grid holding the z-coordinates of each point. The first example in the docs does what I think you're after:
t=[0:0.3:2*%pi]';
z=sin(t)*cos(t');
plot3d(t,t,z);
The first line creates a column vector of length 21
-->size(t)
ans =
21. 1.
The second line computes a 21 x 21 matrix of products of the permutations of sin(t) with cos(t) - note the transpose in the cos(t') element.
-->size(z)
ans =
21. 21.
Then when it plots them it draws (x1,y1,z11), (x1,y2,x12), (x2,y2,z22) and so on. It draws lines between adjacent points in a mesh, or no lines, or just the surface.
I have a set of 3D coordinates (below - just for a single point, in 3D space):
x <- c(-521.531433, -521.511658, -521.515259, -521.518127, -521.563416, -521.558044, -521.571228, -521.607178, -521.631165, -521.659973)
y <- c(154.499557, 154.479568, 154.438705, 154.398682, 154.580688, 154.365189, 154.3564, 154.559189, 154.341309, 154.344223)
z <- c(864.379272, 864.354675, 864.365479, 864.363831, 864.495667, 864.35498, 864.358582, 864.50415, 864.35553, 864.359863)
xyz <- data.frame(x,y,z)
I need to make a time-series plot of this point with a 3D rendering (so I can rotate the plot, etc.). The plot will visualize a trajectory of the point above in time (for example in the form of solid line). I used 'rgl' package with plot3d method, but I can't make it to plot time-series (below, just plot a single point from first frame in time-series):
require(rgl)
plot3d(xyz[1,1],xyz[1,2],xyz[1,3],axes=F,xlab="",ylab="",zlab="")
I found this post, but it doesn't really deal with a real-time rendered 3D plots. I would appreciate any suggestions. Thank you.
If you read help(plot3d) you can see how to draw lines:
require(rgl)
plot3d(xyz$x,xyz$y,xyz$z,type="l")
Is that what you want?
How about this? It uses rgl.pop() to remove a point and a line and draw them as a trail - change the sleep argument to control the speed:
ts <- function(xyz,sleep=0.3){
plot3d(xyz,type="n")
n = nrow(xyz)
p = points3d(xyz[1,])
l = lines3d(xyz[1,])
for(i in 2:n){
Sys.sleep(sleep)
rgl.pop("shapes",p)
rgl.pop("shapes",l)
p=points3d(xyz[i,])
l=lines3d(xyz[1:i,])
}
}
The solution was simpler than I thought and the problem was that I didn't use as.matrix on my data. I was getting error (list) object cannot be coerced to type 'double' when I was simply trying to plot my entire dataset using plot3d (found a solution for this here). So, if you need to plot time-series of set of coordinates (in my case motion capture data of two actors) here is my complete solution (only works with the data set below!):
download example data set
read the above data into a table:
data <- read.table("Bob12.txt",sep="\t")
extract XYZ coordinates into a separate matrixes:
x <- as.matrix(subset(data,select=seq(1,88,3)))
y <- as.matrix(subset(data,select=seq(2,89,3)))
z <- as.matrix(subset(data,select=seq(3,90,3)))
plot the coordinates on a nice, 3D rendered plot using 'rgl' package:
require(rgl)
plot3d(x[1:nrow(x),],y[1:nrow(y),],z[1:nrow(z),],axes=F,xlab="",ylab="",zlab="")
You should get something like on the image below (but you can rotate it etc.) - hope you can recognise there are joint centers for people there. I still need to tweak it to make it visually better - to have first frame as a points (to clearly see actor's joints), then a visible break, and then the rest of frames as a lines.