I have a small issue with Gadfly, I want to plot the tension of a sensor over the time but the scale on the y axis is too wide and I can't expaned it. Already looked through the gadfly documentation without finding an answer.
For the following julia code,
b=plot(x=time,y=lambda,Guide.xlabel("Temps"),Geom.line,Coord.Cartesian(ymin=0.28,ymax=1.0,xmin=0,xmax=150),Guide.ylabel("Lambda"),Guide.title("Evolution lambda en fonction du temps"),Scale.y_continuous(scalable=false))
I get something like this,
But here I only have on the y axis: 0.5 , 1.0 and I want more like 0.2,0.3,0.4,0.5,... because it is not readable that way.
Anyone knows how I would do that with gadfly?
Thanks by advance !
Related
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 found some posts and discussions about the above, but I'm not sure... could someone please check if I am doing anything wrong?
I have a set of N points of the form (x,y,z). The x and y coordinates are independent variables that I choose, and z is the output of a rather complicated (and of course non-analytical) function that uses x and y as input.
My aim is to find a set of values of (x,y) where z=z0.
I looked up this kind of problem in R-related forums, and it appears that I need to interpolate the points first, perhaps using a package like akima or fields.
However, it is less clear to me: 1) if that is necessary, or the basic R functions that do the same are sufficiently good; 2) how I should use the interpolated surface to generate a correct matrix of the desired (x,y,z=z0) points.
E.g. this post seems somewhat related to the problem I am describing, but it looks extremely complicated to me, so I am wondering whether my simpler approach is correct.
Please see below some example code (not the original one, as I said the generating function for z is very complicated).
I would appreciate if you could please comment / let me know if this approach is correct / suggest a better one if applicable.
df <- merge(data.frame(x=seq(0,50,by=5)),data.frame(y=seq(0,12,by=1)),all=TRUE)
df["z"] <- (df$y)*(df$x)^2
ta <- xtabs(z~x+y,df)
contour(ta,nlevels=20)
contour(ta,levels=c(1000))
#why are the x and y axes [0,1] instead of showing the original values?
#and how accurate is the algorithm that draws the contour?
li2 <- as.data.frame(contourLines(ta,levels=c(1000)))
#this extracts the contour data, but all (x,y) values are wrong
require(akima)
s <- interp(df$x,df$y,df$z)
contour(s,levels=c(1000))
li <- as.data.frame(contourLines(s,levels=c(1000)))
#at least now the axis values are in the right range; but are they correct?
require(fields)
image.plot(s)
fancier, but same problem - are the values correct? better than the akima ones?
I'm using QwtCurvePlot to plot a 2d graph. the y axis range is 0 to 100 and x axis is 0 to 60. I use SetRawSamples to initialize my data. say I want to change the colors of portion of graph that y value is between 50 and 60. is there any one can help me please?
EDIT: I want something like
you should reimplement QwtPlotZoneItem draw function in horizontal orientation.If you think you need more in-depth answer comment me.
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.