I apologize for this super basic question, but I am not experienced in plotting, and a lot of the documentation for Julia plotting assumes more knowledge than I have!
I am creating a scatter plot, using Plots, where each marker is plotted based on spatial position, and I want to scale the color by magnitude of value that each marker holds. I created a color gradient as such:
C(g::ColorGradient) = RGB[g[z] for z = LinRange(0,1,M)]
g = :inferno
cgrad(g,[0.01,0.99]) |> C
M is related to the number of markers, this way I create a suitable scale of colors based on the number of markers I have.
I assumed I was creating some kind of structure that would assign a color from this gradient based off a value ranging from 0.01 to 0.99. However, I guess I don't understand what the structure C is. When I assign color = C(v), where v is between 0 and 1.00, I get an error saying that C does not accept type Float64.
Is there a way I can assign a marker some color from this gradient based off its value? I have all of the values for each location stored in another array.
UPDATE: I have also tried indexing into C. I turned my values into Int64 ranging from 1-99, and tried to set color=C[v], but C also does not take Type Int64.
UPDATE 2: Ok, so i realized my issue was I did not understand the |> functionality, So i rewrote the code to look like:
C(g::ColorGradient) = RGB[g[z] for z = LinRange(0,1,M)]
g = :inferno
myGrad = (cgrad(g,[0.00,1.00]) |> C)
and now I can index into my color gradiant! However I still am having an issue setting the color equal to the value stored in the myGradient array.
for i = 1:M
X,Y = find_coords(i,pd)
colors = myGrad[c_index[i]]
outline = rand(Float64,3)
plt = plot!(X,Y,colors, markerstrokecolor = outline)
end
When I type myGrad[c_index[i]] into REPL it plots a color. However I am getting an error from the above code which states
"Cannot convert RGB{Float64} to series data for plotting"
If i change the plot line as follows I get a slightly different error:
plt = plot!(X,Y,markercolor = colors, markerstrokecolor = outline)
ERROR: LoadError: MethodError: no method matching plot_color(::Float64)
So for some reason I cant store this color, as a color variable for my plot.
There are a few different issues at play here. Firstly, if you want to create a scatter plot, you should probably use scatter. It also doesn't seem necessary to plot things in a loop here, although it's hard to tell as your code isn't a minimum working example (MWE), as it relies on things defined somewhere else in your code.
Here's an example of how this might work:
using Plots
# Create a discrete color gradient with 20 points
my_colors = [cgrad(:inferno, [0.01, 0.99])[z] for z ∈ range(0.0, 1.0, length = 20)]
# Draw some random data points
x, y = sort(rand(100)), rand(100)
# Assign a color between 1 and 20 on the color grid to each point
z = sort(rand(1:20, 100))
# Plot
scatter(x, y, color = my_colors[z], markerstrokecolor = "white", label = "",
markersize = [10 for _ ∈ 1:100])
gives:
Related
I want create a scatter plot. I have point size and colour in additional variables (vectors).
x = Float64.(1:10)
y = Float64.(1:10)
c = Float64.(1:10)
s = Float64.(1:10)
scatter(x,y)
I've been googling very long now and could not find the right answer. What I am looking for is this:
This should get you part of the way there:
x = 1.0:10.0
y = 1.0:10.0
c = 1.0:10.0
s = 1.0:10.0
theme(:ggplot2)
scatter(x, y; zcolor=c, markersize=s, color=:oslo)
I didn't have time to try to figure out the legends.
There are a nearly unlimited number of colorschemes, have a look here if this one isn't exactly right: https://docs.juliaplots.org/latest/generated/colorschemes/
Two questions in one: Given a line plotted in Julia, how can I
delete it from the plot and legend (without clearing the whole plot)
change its properties (such as color, thickness, opacity)
As a concrete example in the code below, how can I 1. delete previous regression lines OR 2. change their opacity to 0.1?
using Plots; gr()
f = x->.3x+.2
g = x->f(x)+.2*randn()
x = rand(2)
y = g.(x)
plt = scatter(x,y,c=:orange)
plot!(0:.1:1, f, ylim=(0,1), c=:green, alpha=.3, linewidth=10)
anim = Animation()
for i=1:200
r = rand()
x_new, y_new = r, g(r)
push!(plt, x_new, y_new)
push!(x, x_new)
push!(y, y_new)
A = hcat(fill(1., size(x)), x)
coefs = A\y
plot!(0:.1:1, x->coefs[2]*x+coefs[1], c=:blue) # plot new regression line
# 1. delete previous line
# 2. set alpha of previous line to .1
frame(anim)
end
gif(anim, "regression.gif", fps=5)
I tried combinations of delete, pop! and remove but without success.
A related question in Python can be found here: How to remove lines in a Matplotlib plot
Here is a fun and illustrative example of how you can use pop!() to undo plotting in Julia using Makie. Note that you will see this goes back in the reverse order that everything was plotted (think, like adding and removing from a stack), so deleteat!(scene.plots, ind) will still be necessary to remove a plot at a specific index.
using Makie
x = range(0, stop = 2pi, length = 80)
f1(x) = sin.(x)
f2(x) = exp.(-x) .* cos.(2pi*x)
y1 = f1(x)
y2 = f2(x)
scene = lines(x, y1, color = :blue)
scatter!(scene, x, y1, color = :red, markersize = 0.1)
lines!(scene, x, y2, color = :black)
scatter!(scene, x, y2, color = :green, marker = :utriangle, markersize = 0.1)
display(scene)
sleep(10)
pop!(scene.plots)
display(scene)
sleep(10)
pop!(scene.plots)
display(scene)
You can see the images above that show how the plot progressively gets undone using pop(). The key idea with respect to sleep() is that if we were not using it (and you can test this on your own by running the code with it removed), the fist and only image shown on the screen will be the final image above because of the render time.
You can see if you run this code that the window renders and then sleeps for 10 seconds (in order to give it time to render) and then uses pop!() to step back through the plot.
Docs for sleep()
I have to say that I don't know what the formal way is to accomplish them.
There is a cheating method.
plt.series_list stores all the plots (line, scatter...).
If you have 200 lines in the plot, then length(plt.series_list) will be 200.
plt.series_list[1].plotattributes returns a dictionary containing attributes for the first line(or scatter plot, depends on the order).
One of the attributes is :linealpha, and we can use it to modify the transparency of a line or let it disappear.
# your code ...
plot!(0:.1:1, x->coefs[2]*x+coefs[1], c=:blue) # plot new regression line
# modify the alpha value of the previous line
if i > 1
plt.series_list[end-1][:linealpha] = 0.1
end
# make the previous line invisible
if i > 2
plt.series_list[end-2][:linealpha] = 0.0
end
frame(anim)
# your code ...
You cannot do that with the Plots package. Even the "cheating" method in the answer by Pei Huang will end up with the whole frame getting redrawn.
You can do this with Makie, though - in fact the ability to interactively change plots was one of the reasons for creating that package (point 1 here http://makie.juliaplots.org/dev/why-makie.html)
Not sure about the other popular plotting packages for Julia.
Let's say that I have a DataFrame which contains a Cufflinks heatmap (like this one).
Normally, I plot it in the following way. Notice that I specified a preset colorscale by the name 'spectral'.
heatmap.iplot(kind='heatmap', title='title', colorscale='spectral', xTitle='xTitle', yTitle='yTitle')
It shows me a heatmap, but the value range of the colorscale (not the color, but the min/max values the colorscale is mapped to) is auto-decided.
I want to be able to specify the min/max value so that the coldest color maps to the min value, and the hottest color maps to the max value. My use case is that I have multiple color maps to compare to each other, and I need them to have the same value<->colorscale mapping so that the value difference across these heatmaps are obvious from the colors.
BTW, I don't want to manually specify all the color mappings inside the colorscale, since that means I need to first dig out how the colorscale 'spectral' maps which values to what colors.
The short answer: You can't do it directly with cufflinks because zmin and zmax are no keyword arguments.
The long answer: Transforming your DataFrame is simple but getting the same color scale as cufflinks is a bit trickier (isn't it fun when two identically named colorscales have different mappings?)
df.iplot(kind='heatmap')
is identical to
plotly.offline.iplot([go.Heatmap(z=df.transpose().values)])
So now we can set the upper and lower range of the colorscale via zmin and zmax
plotly.offline.iplot([go.Heatmap(z=df.transpose().values, zmin=0, zmax=40)])
Now let's extract the colorscale from cufflinks and feed it to our heatmap
scale = cf.get_scales()['spectral']
l = len(scale) - 1
spectral = [[i / l, s] for i, s in enumerate(scale)]
plotly.offline.iplot([go.Heatmap(z=df.transpose().values,
zmin=0,
zmax=40,
colorscale=spectral
)])
The complete code
import cufflinks as cf
import plotly
plotly.offline.init_notebook_mode()
import plotly.graph_objs as go
cf.go_offline()
df = cf.datagen.heatmap(20,20)
df.iplot(kind='heatmap', colorscale='spectral')
scale = cf.get_scales()['spectral']
l = len(scale) - 1
spectral = [[i / l, s] for i, s in enumerate(scale)]
plotly.offline.iplot([go.Heatmap(z=df.transpose().values, zmin=0, zmax=40, colorscale=spectral)])
Does anyone have an idea how is this kind of chart plotted? It seems like heat map. However, instead of using color, size of each cell is used to indicate the magnitude. I want to plot a figure like this but I don't know how to realize it. Can this be done in R or Matlab?
Try scatter:
scatter(x,y,sz,c,'s','filled');
where x and y are the positions of each square, sz is the size (must be a vector of the same length as x and y), and c is a 3xlength(x) matrix with the color value for each entry. The labels for the plot can be input with set(gcf,properties) or xticklabels:
X=30;
Y=10;
[x,y]=meshgrid(1:X,1:Y);
x=reshape(x,[size(x,1)*size(x,2) 1]);
y=reshape(y,[size(y,1)*size(y,2) 1]);
sz=50;
sz=sz*(1+rand(size(x)));
c=[1*ones(length(x),1) repmat(rand(size(x)),[1 2])];
scatter(x,y,sz,c,'s','filled');
xlab={'ACC';'BLCA';etc}
xticks(1:X)
xticklabels(xlab)
set(get(gca,'XLabel'),'Rotation',90);
ylab={'RAPGEB6';etc}
yticks(1:Y)
yticklabels(ylab)
EDIT: yticks & co are only available for >R2016b, if you don't have a newer version you should use set instead:
set(gca,'XTick',1:X,'XTickLabel',xlab,'XTickLabelRotation',90) %rotation only available for >R2014b
set(gca,'YTick',1:Y,'YTickLabel',ylab)
in R, you should use ggplot2 that allows you to map your values (gene expression in your case?) onto the size variable. Here, I did a simulation that resembles your data structure:
my_data <- matrix(rnorm(8*26,mean=0,sd=1), nrow=8, ncol=26,
dimnames = list(paste0("gene",1:8), LETTERS))
Then, you can process the data frame to be ready for ggplot2 data visualization:
library(reshape)
dat_m <- melt(my_data, varnames = c("gene", "cancer"))
Now, use ggplot2::geom_tile() to map the values onto the size variable. You may update additional features of the plot.
library(ggplot2)
ggplot(data=dat_m, aes(cancer, gene)) +
geom_tile(aes(size=value, fill="red"), color="white") +
scale_fill_discrete(guide=FALSE) + ##hide scale
scale_size_continuous(guide=FALSE) ##hide another scale
In R, corrplotpackage can be used. Specifically, you have to use method = 'square' when creating the plot.
Try this as an example:
library(corrplot)
corrplot(cor(mtcars), method = 'square', col = 'red')
I'm attempting to set manual colors for Dimple dPlot line values and having some trouble.
d1 <- dPlot(
x="Date",
y="Count",
groups = "Category",
data = AB_DateCategory,
type = 'line'
)
d1$xAxis(orderRule = "Date")
d1$yAxis(type = "addMeasureAxis")
d1$xAxis(
type = "addTimeAxis",
inputFormat = "%Y-%m-%d",
outputFormat = "%Y-%m-%d",
)
The plot comes out looking great, but I would like to manually set the "Category" colors. Right now, it's set to the defaults and I cannot seem to find a method of manually setting a scale.
I have been able to set the defaults using brewer.pal, but I want to match other colors in my report:
d1$defaultColors(brewer.pal(n=4,"Accent"))
Ideally, these are my four colors - the category values I'm grouping on are R, D, O and U.
("#377EB8", "#4DAF4A", "#E41A1C", "#984EA3"))
If I understand correctly, you want to make sure R is #377EB8, etc. To match R, D, O, U consistently to the colors especially across multiple charts, you will need to do something like this.
d1$defaultColors = "#!d3.scale.ordinal().range(['#377EB8', '#4DAF4A', '#E41A1C', '#984EA3']).domain(['R','D','O','U'])!#"
This is on my list of things to make easier.
Let me know if this doesn't work.
The issue with the accepted answer above is that defining an ordinal scale will not guarantee that specific colors are bound to specific categories R, D, O and U. The color mapping will change depending on the input data. To assign each color specifically you can use assignColor like this
d1$setTemplate(afterScript = '<script>
myChart.assignColor("R","#377EB8");
myChart.draw();
</script>')