Let us consider the following scenario .
for x in range (1,100)
for y in range (2,500)
#plot(f(x),g(y))
end
end
where f(x) and g(y) are some user defined functions.
The output must be the desired points on plane.
Is there any way in julia to do like what I need ?
In general I can do like this
for x in range (1,100)
for y in range (2,500)
push!(l,f(x))
push!(m,g(y))
end
end
and then plotting from the two lists l,m as x,y axes respectively.
But now I want to plot points while executing loop.
This is mostly supported in Plots... see https://github.com/tbreloff/Plots.jl/issues/30 for a little more information and some example usage.
use the display function:
for x in 1:100
p = plot(f(x),g(y))
display(p)
sleep(1)
end
(inspired by Andreas Peter on the Julia slack #helpdesk channel)
Related
I came across a Rose plot obtained with Plots.jl package in Julia:
https://goropikari.github.io/PlotsGallery.jl/src/rose.html
Two things are not clear to me. The first one is what is Julia doing on the line:
θ = 0:2pi/n:2pi
It seems that the output is (lower limit):(bin size):(upper limit) but I haven't seen this type of arithmetics previously where two ranges are divided. The second thing is that I would like to obtain a histogram polar plot as it was done with R (Making a polar histogram in ggplot2), but I haven't found the documentation for line styles or how to do it in Plots.jl. Thanks.
Note that start:step:end is a common syntax in creating ranges. Let's dissect the line:
# `pi` is a reserved variable name in Julia
julia> pi
π = 3.1415926535897...
# A simple division
julia> 2pi/1
6.283185307179586
# Simple multiplication
julia> 2pi
6.283185307179586
So the 0:2pi/n:2pi creates an object of type StepRange that starts from 0 up to 2pi with steps of size 2pi/n.
In the case of desired plot, you can use the PlotlyJS.jl package. As they provided an example here. (Scroll down until you see "Polar Bar Chart")
I tested the code myself, and it's reproducible expectedly. Unfortunately, I don't know anything about the R language.
julia> using RDatasets, DataFrames, PlotlyJS
julia> df = RDatasets.dataset("datasets", "iris");
julia> sepal = df.SepalWidth;
julia> plot(
barpolar(
r=sepal
)
)
Results in:
I'm trying to create an animation in Julia where a satellite orbits Earth. Earth in this case is represented by a static circle and the satellite's trajectory is a path extending from the launch point to the satellite's current position.
If I understand the process correctly, to create a gif in Julia, I need to use the #gif macro with a loop and create the next gif frame on each iteration of the loop. I've been attempting to plot Earth, then plot the launch point, then push the next position in the satellite's trajectory on each loop iteration, but it's pushing data to the Earth dataset.
I also have other plots that I would like to animate, but the animation examples that use multiple data series don't specify any x values. I need to specify x and y values for each datapoint in each series.
How can I specify the series to push a new point to?
Well, while trying to put together a small example script, I figured it out.
To begin, the conditions under which you can use push! with a plot are fairly specific. You can't use an Int64 (or any other type of integer) as an x value or push! will try to access the plot like an array at the "index" specified by your x data. This means you have to ensure every input is a Float (I didn't try this with more exotic data types for plotting like Bools, but I assume that that wouldn't go well either).
Also, the x and y (and z) data in a plot can't be something that push! doesn't work on normally, like a StepRangeLen (e.g. t = 0:10). Unfortunately this introduces an extra layer of complexity; if you need to use StepRangeLens in your plots, you'll have to convert them to Arrays: t = Array{Float64}(0:10).
Finally, it's probably good practice to pass in as many x and y values on each call to push! as you have series (if this wording is awkward, see the example below). Some of the examples for the Plots package add complexity in specifying a single x value for multiple y values, which is fine if your x values are the same for both series, but becomes a problem if they're different.
Putting all of this together, here's a minimal example of pushing to different series:
using Plots
# Let x and z be two different-valued, different-length vectors
x = Array{Float64}(range(0, stop=π, length=30))
z = Array{Float64}(range(0, stop=-π, length=20))
p = plot(x,sin.(x))
plot!(p, z, cos.(z))
# Pushing a single x,y pair goes to the first series:
push!(p, 0.0, -0.5)
# Pushing a single x value and a 2x1 Array sends the x value to
# both series, the first y value to the first series, and the
# second y value to the second series.
push!(p, -0.2, [-0.75, 0.2])
# Note: comma ^ is important
# Pushing two x values and two y values sends the first x value to
# the first series and the second x value to the second series.
# Same for the y values, which is the same as the previous example
push!(p, [-π/4, π/4], [0.1, 0.2])
# If you want to push only to one series, send a NaN to the others:
push!(p, [NaN, -3π/2], [NaN, 1.0])
display(p)
The plot is pretty incoherent if you run this as-is. I recommend commenting out each of the push! statements and uncommenting each one individually to see its effect on the plot.
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))
When plotting a function (as opposed to numerical data), how can we set the number of sample points (i.e. the number of distinct x coordinates where the function is computed)? Importantly, where can I find this information in the documentation?
Example:
plot(x -> sin(1/x), 0.001, 1)
For a useful plot in the 0–0.25 range we need many more points.
One way you can do it is:
using Gadfly;
X=1e-6:1e-6:1.0
plot(x=X, y=X .|> x -> sin(1/x), Geom.line)
or you may like this version more
using Gadfly;
X=[1/z for z=300.0:-0.05:1.0]
plot(x=X, y=X .|> x -> sin(1/x), Geom.line)
To get a docu, just do
?plot
or when you want to look at the code
methods(plot)
The number of sampling points can indeed be specified:
plot(y=[x->sin(1/x)], xmin=[0.001], xmax=[1], Stat.func(1000), Geom.line)
You can find Stat.func in the Gadfly docs here:
http://gadflyjl.org/stable/lib/statistics/#Gadfly.Stat.func.
Note you can write either Stat.func(num_samples=1000) or Stat.func(1000), since there is only one argument.
I plotted an expression curve, i.e.curve(-log((1-x)/0.9999)/x,ylim=c(0,4)).
However, I want to see the reverse relationship, i.e. y changes over x instead of x changes over y. Are there any R function can plot it automatically? Or a function that can solve the equation?
There are two obvious choices:
(i) derive the inverse function algebraically (trivial in this case),
That is, take y=-log((1-x)/0.9999) and make x the subject of the equation (which would require straightforward algebraic manipulation suitable for a question on math.SE if it's not obvious how to proceed)...
... and then use curve on the result of that, or
(ii) use plot rather than curve to plot a set of (x,y) pairs (set type="l" to get a curve), and simply interchange which is x and which is y in the call to plot.