PyX Graphics for Julia ============================================================================= This is a Julia wrapper of the PyX plotting and TeX graphics library from Python. It is a work in progress, broken, and will set your computer on fire. See also the TODO file. **Source Code:** https://github.com/bnewbold/PyX.jl **Travis CI:** https://travis-ci.org/bnewbold/PyX.jl ## Example ``` using PyX g = graph.graphxy(width=8) plot(g, graph_data_function("y(x)=sin(x)/x", min=-15, max=15)) writePDFfile(g, "example_graph.pdf") ``` Plotting works automagically from within Jupyter and other graphic interfaces: ![Jupyter Example Image](examples/jupyter_example_graph.png "Jupyter Example Image") There are many (ported) examples in the ./examples/ directory of this repository. See the Python PyX upstream documentation for example outputs: For pipeGS (ghostscript file conversion) output "device" options, see: ## Dependencies and Python Version You'll obviously need the underlying Python PyX library installed, plus any dependencies (eg, LaTeX and Ghostscript). These are pretty huge and complex packages to install! Use something like Debian's `apt` or Homebrew on OS X. No idea how to get this set up on Windows or other platforms. *NOTE:* PyX versions starting with 0.13 are Python3-only. PyX versions 0.12.1 and earlier are Python2-only. This split happened back in 2013. This wrapper will work with versions on either side of the split, but the newer versions (starting with PyX 0.14) support SVG and newer features. Unfortunately, switching Julia's PyCall wrapper from Python2 to Python3 is all or nothing. Careful! If you decide to do this, run: julia> ENV["PYTHON"] = "/usr/bin/python3" # Or your local full path julia> Pkg.build("PyCall") ## Installation This package is not (yet) listed in the official Julia MANIFEST.jl index, so you'll need to install it "unregistered" style: julia> Pkg.clone("https://github.com/bnewbold/PyX.jl") julia> using PyX To run tests, do something like: JULIA_LOAD_PATH=src julia test/runtests.jl ## Differences from Python All the expected [Julia/Python differences][1] apply: * use Julia's `nothing` instead of Python's `None` * use 1-indexing instead of 0-indexing, and require `end` in slice syntax * function calls like `writeEPSfile(c, filename)` instead of object method calls like `c.writeEPSfile(filename)`. Note that the string code snippets that go into `graph_data_function` are still Python code, not Julia. There doesn't seem to be an easy way to handle nested Python modules as nested modules in Julia, so there can only be a single `.` separator in variable and function names. This has been worked around by using the underscore character (`_`) instead of `.` for all but the last separator. So, eg, `graph_axis.split()` instead of `graph.axis.split()` and `color_rgb.red` instead of `color.rgb.red`. To avoid namespace collisions or confusion with built-in Julia functions the following functions (only) have `pyx_` preprended to the function name: pyx_fill, pyx_append, pyx_insert, pyx_text `function` is also a reserved keyword in Julia, so use `graph_data_function` instead of `graph_data.function`. [1]: http://docs.julialang.org/en/stable/manual/noteworthy-differences/#noteworthy-differences-from-python) ## License Following the license of the underlying PyX python library, this wrapper is licensed under the GNU GPL Version 2 (or later). See the LICENSE file, and the upstream licensing note: