Using Julia 0.3.10 with Juno as IDE and Gadfly latest one. Tried running a sample code, but got stuck with add_plot_element not defined error message. The last line throws the error. Running on Win8 64bit. I'm sure I'm missing something.
using Gadfly
xs = [0:0.1:pi]
k = layer(x=xs, y=sin(xs))
p = plot(x=xs, y=sin(xs))
add_plot_element(k, Guide.title("Now it has a title"))
First, add_plot_element is modifying, so you need the ! like:
add_plot_element!(k,Guide.title(...))
This function is also not exported from Gadfly, so you would really need to write:
Gadfly.add_plot_element!(k, Guide.title("Now it has a title"))
except add_plot_element! doesn't work on Gadfly layers! It does, however, work on plots. What should work:
Gadfly.add_plot_element!(p, Guide.title("Now it has a title"))
since the layer itself doesn't have Guide.Title elements, but the plot does.
Related
I'm unable to save a plot generated by the plot.Node function in data.tree. I've tried the following:
### Create tree object and plot it
data(acme);
plot(acme);
This works fine, showing the plot, as one would expect.
### Try saving it as png
png(filename='file.png', type='cairo-png');
plot(acme);
dev.off();
This creates an empty file. ggsave does the same. Apparantly, plot.Node uses DiagrammeR under the hood, so I looked into that package. It has a function to export graphs:
export_graph(acme, file_name="file.png");
This gives the error:
Error in file.exists(diagram) : invalid 'file' argument
When I transform to GraphViz first, I get a different error:
export_graph(ToGraphViz(acme), file_name="file.png");
Error in graph$dot_code : $ operator is invalid for atomic vectors
Clearly, exporting to GraphViz doesn't quite export to what DiagrammeR expects.
I'm in RStudio and so could in theory just save the plot using the GUI, but I need this for in a script.
Apparently, plot.Node doesn't actually plot anything - instead it seems to generate html/js. Does this mean that that result cannot be stored as a graphic? Or is there some export/conversion function somewhere that I'm completely missing? it certainly feels like I'm missing something obvious - I assume the need to store plotted data.trees as images is quite common. But I have no idea which potential solutions I can still explore.
I'd be very grateful for any pointers anybody has!
As sebastian-c suggested, things work now a bit differently than suggested by Matherion, as of R 3.3.3 with data.tree 0.7.0 and DiagrammeR 0.9.0
Pre-requisite: DiagrmmeRsvg and dependencies need to be installed. Depending on your OS, for this to work you might have to install V8. For example on ubuntu:
apt-get install libv8-3.14-delibv8-3.14-dev
And then in R:
install.packages("DiagrammeRsvg")
On Windows, I didn't have to install anything (maybe because Chrome is installed?).
Once DiagrammeRsvg is available, run:
library(data.tree)
data(acme)
library(DiagrammeR)
export_graph(ToDiagrammeRGraph(acme), "export.pdf")
I've found the answer, at least, partially. There exists a package dedicated to exporting GraphViz diagrams to SVG: DiagrammeRsvg.
So this works:
treeAsSVG <- export_svg(grViz(ToGraphViz(acme)));
writeLines(treeAsSVG, "filename.svg"));
The grViz is necessary to actually convert the ToGRaphViz output to something that can be interpreted by export_svg. I'm still not really sure (yet) what all goes on under the hood - for example, this does not work:
export_graph(grViz(ToGraphViz(acme)), file_name="filename.svg");
But, if anybody else has a similar problem and stumbles upon this question, perhaps this partial answer can help them to at least export something that can then be integrated in e.g. html pages.
By converting acme with as.phylo() it works, but it looks a little boring:
plot(as.phylo(acme),
show.node.label=TRUE,
node.pos=2,
no.margin=TRUE
)
# adding edge labels
edgelabels(as.vector(acme$Get("cost"))[-1],
adj = c(0,-0.5),
frame = "none")
solution with as.phylo()
I also tried as.igraph. However, the nodes overlap and it looks even less pretty:
plot(0, type="n", ann=FALSE, axes=FALSE,
xlim=extendrange(ig[,1]),
ylim=extendrange(ig[,2]))
plot(ig,
layout=layout_as_tree(ig,root=1),
vertex.shape="rectangle",
vertex.size=(strwidth(V(ig)$name) + strwidth("oo")) * 100,
#vertex.size2=strheight("I") * 2 * 100,
edge.label=acme$Get("p",traversal = "level")[-1]
)
solution with as.igraph()
I am currently in the process of plotting a directed graphs using Julia. After some time on the internet I came across the GraphPLot package which seems to be doing an ok job.
However, I can't find out how to add node labels! Here is my code and output from the jupyter notebook.
Update:
I tried the suggested method from GitHub
nodelabel = [1:number_vertices(g)]
gplot(g, nodelabel = nodelabel)
But I get a weird error:
LoadError: Must have one label per node (or none)
while loading In[44], in expression starting on line 1
Changing
nodelabel = [1:num_vertices(g)]
To nodelabel = collect(1:num_vertices(g)) solves the issue.
If I run:
library(ggplot2)
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
bp<-ggplot(ToothGrowth, aes(x=dose, y=len, fill=dose)) +
geom_boxplot()
bp
I see the error: Error in grDevices::col2rgb(colour, TRUE) : invalid RGB specification.
If I run the identical code on my other computer, I get the expected plot. I am guessing that some plotting parameter is the culprit, but I have no idea how to find it. What's going wrong?
The computer that behaves strangely is Mac OS X 10_11_3 running R 3.2.2 via RStudio 0.99.489
Sorry I am late, but the problem is that the function alpha is masked form ggplot2, that's why if you restart R and happen to call alpha after sourcing psych but before ggplot2 it works.
Anyway, the way to solve it is to make explicit that we want the psych function:
reliability = psych::alpha(df)
Restarting R was sufficient to fix the weird behavior. Obviously should have tried that before posting...
I'm currently working through this tutorial and I'm having trouble getting the png image to display. This is my program.
using DataFrames
using Gadfly
train_df = readtable("winequality-red.csv", separator=';')
_, count = hist(train_df["quality"])
class = sort(unique(train_df["quality"]))
value_counts = DataFrame(count=count, class=class)
#value_counts
p = plot(value_counts, x="class", y="count", Geom.bar(), Guide.title("Class distributions (\"quality\")"))
draw(PNG(14cm, 10cm), p)
the error I get is
LoadError("C:/Users/John/Desktop/helloworld.jl",12,MethodError(PNG,(140.0mm,100.0mm)))
I've tried some of the things mentioned in this discussion, however I haven't made any observable progress.
I was able to solve my problem by installing Cairo.
Pkg.add("Cairo")
and changing this line
draw(PNG(14cm, 10cm), p)
to
draw(PNG("chart.png", 14cm, 10cm), p)
and then opening chart.png with Julia Studio
I have the scatterplot3d package installed in R. When I load it with library(scatterplot3d) or require(scatterplot3d) I am able to create a 3d scatter plot. However, when I try to use the points3d function I get the following error:
Error: could not find function "points3d"
I tried reinstalling the package to no avail (both inside R and as a tarball using R CMD INSTALL in the command line). I am running Xubuntu 12.10 kernel 3.8.7-030807-generic and R version 2.15.3 (2013-03-01).
Entering locate points3d in the command line gave me no results.
I also tried the par.mar default settings command as explained in the manual.
scatterplot3d does an interesting object-oriented twist on the usual R practice. The object returned from the function call includes the points3d function as built-in part of the object but it is not in the Global environment. It is intended that you add to the existing plot-object using that "attached" function that is not a free-living organism but rather a domesticated animal that only exists in the object corral, so you would use this as your syntax:
object$point3d(x,y,z)
I do "feel your pain" but can show you how to overcome the frustration, since I created a working example yesterday: Using scatterplot3d to plot a sphere
You need to intall the package plot3D in the usual way via
install.packages("plot3D")
Then you just need to import, generate the dataset and use the function points3D()
library(plot3D)
x = rnorm(100)
y = rnorm(100)
z = x + y + rnorm(100,0,1)
points3D(x, y, z, col = rainbow(1000))
This is the plot generated by the code above