I am trying to change the number of breaks in the legend of a heatmap. I am using the example from docs to make it reproducible:
using Unitful, Plots
xs = [string("x", i) for i = 1:10]
ys = [string("y", i) for i = 1:4]
z = float((1:4) * reshape(1:10, 1, :)) * u"km"
heatmap(xs, ys, z, aspect_ratio=1)
Output:
Imagine I want for example only 4 breaks so: 5, 15, 25, 35. How can we change the number of breaks in a heatmap in Julia?
You can use colorbar_ticks but they are not supported by gr() so you will need to switch to pyplot() backend:
pyplot()
heatmap(xs, ys, z, aspect_ratio=1, colorbar_ticks=[5, 15, 25, 35] .* u"km")
Related
I would like to have a double y-axis in one of my subplots; however, it seems like I am missing something about twinx() and link = :x, but I couldn't figure out what..
Plotting double y-axis using twinx() works fine in a standard plotting frame. However, it creates the following problem when I try to link the x-axes. What am I missing here?
using Plots
x = [3, 5, 7, 9];
y = [10, 20, 30 , 40];
z = [-10, -20, -30, -40];
a = plot(1:10, color = :black, legend = false)
b = plot(x, y, color = :green, legend = false)
b = scatter!(twinx(), x, z, color = :orange, legend = false)
plot(a, b, layout = (2, 1), link= :x)
Output:
Thank you very much!
What are the alternatives for drawing a simple curve for a function like
eq = function(x){x*x}
in R?
It sounds such an obvious question, but I could only find these related questions on stackoverflow, but they are all more specific
Plot line function in R
Plotting functions on top of datapoints in R
How can I plot a function in R with complex numbers?
How to plot a simple piecewise linear function?
Draw more than one function curves in the same plot
I hope I didn't write a duplicate question.
I did some searching on the web, and this are some ways that I found:
The easiest way is using curve without predefined function
curve(x^2, from=1, to=50, , xlab="x", ylab="y")
You can also use curve when you have a predfined function
eq = function(x){x*x}
curve(eq, from=1, to=50, xlab="x", ylab="y")
If you want to use ggplot,
library("ggplot2")
eq = function(x){x*x}
ggplot(data.frame(x=c(1, 50)), aes(x=x)) +
stat_function(fun=eq)
You mean like this?
> eq = function(x){x*x}
> plot(eq(1:1000), type='l')
(Or whatever range of values is relevant to your function)
plot has a plot.function method
plot(eq, 1, 1000)
Or
curve(eq, 1, 1000)
Here is a lattice version:
library(lattice)
eq<-function(x) {x*x}
X<-1:1000
xyplot(eq(X)~X,type="l")
Lattice solution with additional settings which I needed:
library(lattice)
distribution<-function(x) {2^(-x*2)}
X<-seq(0,10,0.00001)
xyplot(distribution(X)~X,type="l", col = rgb(red = 255, green = 90, blue = 0, maxColorValue = 255), cex.lab = 3.5, cex.axis = 3.5, lwd=2 )
If you need your range of values for x plotted in increments different from 1, e.g. 0.00001 you can use:
X<-seq(0,10,0.00001)
You can change the colour of your line by defining a rgb value:
col = rgb(red = 255, green = 90, blue = 0, maxColorValue = 255)
You can change the width of the plotted line by setting:
lwd = 2
You can change the size of the labels by scaling them:
cex.lab = 3.5, cex.axis = 3.5
As sjdh also mentioned, ggplot2 comes to the rescue. A more intuitive way without making a dummy data set is to use xlim:
library(ggplot2)
eq <- function(x){sin(x)}
base <- ggplot() + xlim(0, 30)
base + geom_function(fun=eq)
Additionally, for a smoother graph we can set the number of points over which the graph is interpolated using n:
base + geom_function(fun=eq, n=10000)
Function containing parameters
I had a function (emax()) involving 3 parameters (a, b & h) whose line I wanted to plot:
emax = function(x, a, b, h){
(a * x^h)/(b + x^h)
}
curve(emax, from = 1, to = 40, n=40 a = 1, b = 2, h = 3)
which errored with Error in emax(x) : argument "a" is missing, with no default error.
This is fixed by putting the named arguments within the function using this syntax:
curve(emax(x, a = 1, b = 2, h = 3), from = 1, to = 40, n = 40)
which is contrary to the documentation which writes curve(expr, from, to, n, ...) rather than curve(expr(x,...), from, to, n).
I have a plot(x, y) and I want to add a vertical line at x = 2 ONLY from y = 1 to 4. I want to use the lines() function but I'm having trouble limiting the y-range.
What's an easy way to do this?
Here's a simple example of using plot and lines. To draw a line from (2, 1) to (2, 4), you have to provide the x coordinates and y coordinates as (2, 2) and (1, 4):
plot(1:5)
lines(c(2, 2), c(1, 4))
ggplot2 offers a very simple solution, too!
library(ggplot2)
set.seed(1)
# Create some dummy data
data.frame(X = rpois(n = 10, lambda = 3),
Y = rpois(n = 10, lambda = 2)) %>%
# Pipe to ggplot
ggplot(aes(X, Y)) +
geom_point() +
geom_segment(aes(x = 1, xend = 1, y = 1, yend = 4), color = "red")
Within the aesthetics call to geom_segment() you can select the start and end points for your x and y parameters. You can then easily add multiple segments by simply adding + geom_segment(aes(...)) to the end of the code above.
For completeness, there is also a base graphics function in R that will do this: segments(x0,y0,x1,y1):
plot(1:5)
segments(2,1,2,4)
I am having extreme difficulty in making my axes logarithmic/have custom tick marks in plot3d using the rgl package. I've tried using the "log='xy'" command in my code just like you would in the basic plot function, and I have tried to create custom tick marks using rgl.bbox. My y axis is plotting fine but my x and z are not cooperating. I cannot get anything to work. Any ideas? Below is my data, code, and a picture of the result I'm getting. I should also add that I'm basically plotting multiple 2d scatterplots in 3d using an arbitrary z value to separate the individual 2d plots.
https://www.dropbox.com/s/wv24rmnyalm3vvc/scattertest.csv?dl=0
#!/usr/bin/env Rscript
library("rgl")
data <- read.csv("~/Desktop/scattertest.csv", header=TRUE, fill=TRUE, sep=',')
x <- names(data[2])
y <- names(data[3])
z <- names(data[4])
plot3d(data[[x]], data[[z]], data[[y]], type="s", size=0.75, lit=FALSE, axes=FALSE,
xlab="rpmn", ylab="round", zlab="rpmt", log="xz",
xmin=c(0.1, 10^6), ymin=c(1,4), zmin=c(0.1, 10^6))
rgl.bbox(color="grey50", emission="grey50",
xat = c(0.1, 1, 10, 100, 10^3, 10^4, 10^5, 10^6), yat = c(1, 2, 3, 4), zat = c(0.1, 1, 10, 100, 10^3, 10^4, 10^5, 10^6),
xlen=8, ylen=4, zlen=8)
There's no support for log="xy" in plot3d(), you'll need to do the transformation yourself.
Your code asks for logarithmic labels, but you aren't doing the logarithmic transformation, so it's not working. You need to rescale the data as well.
You didn't post a reproducible example, but it's easy to create one:
x <- rlnorm(20, 2, 6)
y <- runif(20, 1, 4)
z <- rlnorm(20, 2, 6)
xyz <- cbind(log(x), y, log(z))
plot3d(xyz, axes = FALSE)
ticks <- 10^((-1):6)
bbox3d(xat = log(ticks), xlab = ticks, yat = pretty(1:4),
zat = log(ticks), zlab = ticks,
color="grey50", emission="grey50")
What are the alternatives for drawing a simple curve for a function like
eq = function(x){x*x}
in R?
It sounds such an obvious question, but I could only find these related questions on stackoverflow, but they are all more specific
Plot line function in R
Plotting functions on top of datapoints in R
How can I plot a function in R with complex numbers?
How to plot a simple piecewise linear function?
Draw more than one function curves in the same plot
I hope I didn't write a duplicate question.
I did some searching on the web, and this are some ways that I found:
The easiest way is using curve without predefined function
curve(x^2, from=1, to=50, , xlab="x", ylab="y")
You can also use curve when you have a predfined function
eq = function(x){x*x}
curve(eq, from=1, to=50, xlab="x", ylab="y")
If you want to use ggplot,
library("ggplot2")
eq = function(x){x*x}
ggplot(data.frame(x=c(1, 50)), aes(x=x)) +
stat_function(fun=eq)
You mean like this?
> eq = function(x){x*x}
> plot(eq(1:1000), type='l')
(Or whatever range of values is relevant to your function)
plot has a plot.function method
plot(eq, 1, 1000)
Or
curve(eq, 1, 1000)
Here is a lattice version:
library(lattice)
eq<-function(x) {x*x}
X<-1:1000
xyplot(eq(X)~X,type="l")
Lattice solution with additional settings which I needed:
library(lattice)
distribution<-function(x) {2^(-x*2)}
X<-seq(0,10,0.00001)
xyplot(distribution(X)~X,type="l", col = rgb(red = 255, green = 90, blue = 0, maxColorValue = 255), cex.lab = 3.5, cex.axis = 3.5, lwd=2 )
If you need your range of values for x plotted in increments different from 1, e.g. 0.00001 you can use:
X<-seq(0,10,0.00001)
You can change the colour of your line by defining a rgb value:
col = rgb(red = 255, green = 90, blue = 0, maxColorValue = 255)
You can change the width of the plotted line by setting:
lwd = 2
You can change the size of the labels by scaling them:
cex.lab = 3.5, cex.axis = 3.5
As sjdh also mentioned, ggplot2 comes to the rescue. A more intuitive way without making a dummy data set is to use xlim:
library(ggplot2)
eq <- function(x){sin(x)}
base <- ggplot() + xlim(0, 30)
base + geom_function(fun=eq)
Additionally, for a smoother graph we can set the number of points over which the graph is interpolated using n:
base + geom_function(fun=eq, n=10000)
Function containing parameters
I had a function (emax()) involving 3 parameters (a, b & h) whose line I wanted to plot:
emax = function(x, a, b, h){
(a * x^h)/(b + x^h)
}
curve(emax, from = 1, to = 40, n=40 a = 1, b = 2, h = 3)
which errored with Error in emax(x) : argument "a" is missing, with no default error.
This is fixed by putting the named arguments within the function using this syntax:
curve(emax(x, a = 1, b = 2, h = 3), from = 1, to = 40, n = 40)
which is contrary to the documentation which writes curve(expr, from, to, n, ...) rather than curve(expr(x,...), from, to, n).