I want to plot a point in the polar coordinate system using SAGE. For instance the given is cis 135°. Can somebody tell me what are the commands for this to be done?
Unfortunately it seems that the polar plotting facility and point plotting don't play well (though there is a polar_plot command if you have a function to plot). This seems to work but you might not like it so much; I would recommend turning this into a function if you have a lot to plot.
angle = 135
true_angle = 135/180*pi
point([cos(true_angle),sin(true_angle)],color='red')
Related
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 am attempting to project data onto a plot in R and see the correlation between the points. I have added a line to let the reader see the connection between these points. I am however stumped when it comes to inputting arrows to show the direction of the line. Rddproj was just an arbitrary name given to the data. Three sets of x and y coordinates are plotted x=c(-0.7159425, -0.8129311, -0.7392371); y=0.7743088, 0.7732762, 0.7490996) Here is the example below.
x<-rddproj[1:3,1]; y<-rddproj[1:3,2]
plot(x,y)
My concern is that the second group of coordinates is the greatest negative point on the x-axis. In drawing a line with arrows, the arrow will most likely point towards this point, when it should be forming a V with that point in the middle. Is it possible to plot an arrow to reflect the placement of points in a group and not just the most positive point to the most negative point or vice versa?
The arrows function ( a modified segments function) is used for this purpose (to the extent that I understand the question) in base R:
# fixed your assignment code.
plot(NA, xlim=range(x), ylim=range(y) )
arrows(head(x,-1),head(y,-1),tail(x,-1), tail(y,-1), angle=30)
An alternative reading of your question would have the glaringly obvious solution : plot(x,y) which I hope is not what you were asking since that should have been satisfactory.
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'm using plotrix package to draw circles.
And I don't get what is wrong with my code... :-(
I have three points. The first point (1,1) should be the center of the circle. The following two points (1,4) and (4,1) have the same distance/radius to the center.
So the circle in the plot should go through these points, right?
And I don't know why the circle looks wrong. Is there an explanation?
p1 <- c(1,1)
p2 <- c(4,1)
p3 <- c(1,4)
r <- sqrt(sum((p1-p2)^2))
plot(x=c(p1[1], p2[1], p3[1]),
y=c(p1[2], p2[2], p3[2]),
ylim=c(-5,5), xlim=c(-5,5))
draw.circle(x=p1[1], y=p1[2], radius=(r))
abline(v=-5:5, col="#0000FF66")
abline(h=-5:5, col="#0000FF66")
Take a look at the produced output here
As #Baptiste says above, you can use plot(...,asp=1). This will only work if your x and y ranges happen to be the same, though (because it sets the physical aspect ratio of your plot to 1). Otherwise, you probably want to use the eqscplot function from the MASS package. A similar issue arises whenever you try to do careful plots of geometric objects, e.g. Drawing non-intersecting circles
This plot is produced by substituting MASS::eqscplot for plot in your code above:
Note that depending on the details of what R thinks about your monitor configuration etc., the circle may look a bit squashed (even though it goes through the points) when you plot in R's graphics window -- it did for me -- but should look OK in the graphical output.