YPlot.jl

A very simple plotting package for Julia. For now, the backend is PyPlot, the syntax is somewhat reminiscent of Yorick.

The initial objective was to cope with the displaying 2D Julia arrays with axes orientation and extent suitable for matrix (that is A[i,j] is indexed by row i and column j) or image (that is A[x,y] is indexed by abscissa index x and ordinate index y) conventions.

Example:

using YPlot
A = randn(4,7)
plmat(A, "As a matrix", "row index", "column index"; fig=1)
plimg(A, "As an image", "x", "y"; cbar=true, fig=2)

will display the 2D array 4×7 array A as a matrix in figure 1 and as an image (with a color bar) in figure 2.

Wish List

• Add a database of preferences (using a dictionary) which can be optionaly saved to the disk. The backend should be part of the preferences.

• Add plc for plotting contours.

Installation

using Pkg
Pkg.add("https://github.com/emmt/YPlot.jl")

Using PyPlot with system MatPlotLib on Ubuntu

When installing PyCall which is required by PyPlot, if environment variable PYTHON is set to an empty string, a custom Python installation based on Conda.jl is installed. This can take quite a bit of disk space (4-5 Gb in my case per version of Julia) and you may prefer to use a version of MatPlotLib already installed on your system. I explain below how to do that on Ubuntu (or similar like Linux-Mint) Linux distribution.

Important As of Julia 1.0 and PyPlot 2.2.2, interaction with Python3 is broken (it freezes the REPL until mouse moves into the graphic window) and Gtk3Agg backend is broken with Python2.7 even with the python-cairocffi Debian package (error message: TypeError: Couldn't find foreign struct converter for 'cairo.Context'). Hence, my recommandation is to use Python 2.7 with Qt5Agg or Tk frontends. Perhaps Qt4Agg or WXAgg work but I did not tried.

Install packages (depending on which version of Python you want to use, the two can coexist but see my recommandations above):

sudo apt-get install python-matplotlib libpython-dev python-pyqt5

or

sudo apt-get install python3-matplotlib libpython3-dev python3-pyqt5

depending on which version of Python you want to use.

Instead of python-pyqt5 (resp. python3-pyqt5), alternative Debian packages are python-qt4 (resp. python3-pyqt4) for using with QT4 toolkit and/or python-tk (resp. python3-tk) to use Tcl/Tk. The *-dev packages are needed to have symbolic links libpython*.so in /usr/lib/x86_64-linux-gnu. If symbolic links libpython*.so do not exists in /usr/lib, create them (needed for PyCall build to find the Python library):

cd /usr/lib
sudo ln -s x86_64-linux-gnu/libpython*.so .

Now, in Julia install PyCall and PyPlot (see here for the different Python versions on Ubuntu):

ENV["PYTHON"] = "/usr/bin/python2.7" # or "/usr/bin/python3.6m" or "/usr/bin/python3.6"
ENV["MPLBACKEND"] = "Qt5Agg"
using Pkg
Pkg.add("PyCall")
Pkg.add("PyPlot")

You can also define ENV["PYTHON"] and ENV["MPLBACKEND"] in ~/.juliarc.jl or in ~/.Julia/config/startup.jl (depending on Julia version) to start Julia with the correct Python path and MatPlotLib backend.

My own ~/.Julia/config/startup.jl has the following lines:

ENV["PYTHON"] = "/usr/bin/python2.7"
ENV["MPLBACKEND"] = "Qt5Agg"

If you change ENV["PYTHON"], re-build PyCall. Remember that defining ENV["PYTHON"]="", will install a custom Conda environment (which may be huge, 4-5 Gb for me). If you change ENV["MPLBACKEND"], just restart Julia (or make the change before your first import/using of PyPlot).

In case of problems, to check which backend you are using:

using PyPlot
PyPlot.backend # yields backend name
PyPlot.gui     # yields toolkit name

MatPlotLib backends (see file init.jl in PyPlot/src directory, "Agg" means anti-aliasing and case does not matter) are:

• WX, WXAgg
• GTK, GTKAgg, GTKCairo
• GTK3, GTK3Agg, GTK3Cairo
• Qt4Agg, QT5Agg
• TkAgg