PlotDevice is a Macintosh application used for computational graphic design. It provides an interactive Python environment where you can create two-dimensional graphics and output them in a variety of vector, bitmap, and animation formats. It is meant both as a sketch environment for exploring generative design and as a general purpose graphics library for use in external Python programs.

PlotDevice scripts can create images from simple geometric primitives, text, and external vector or bitmap images. Drawing commands provide a thin abstraction over Mac OS X's Quartz graphics engine, providing high-quality rendering of 2D imagery and powerful compositing operations.

PlotDevice is a fork of the legacy NodeBox 1 application with a number of updates taking advantage of recent OS features and simplifying its build procedure. As a result it now happily runs on 64 bit systems, uses Python 2.7, and makes use of the version of PyObjC provided by the system. It requires a Macintosh running OS X 10.9 or greater.

Though Quartz is not by any means ‘slow’, its focus on rendering quality does mean that if you're interested in doing realtime or interactive work you may be better served by NodeBox GL. This project's focus is on allowing your scripts to generate ‘camera ready’ graphics and movies for use elsewhere. To that end it provides functionality to efficiently export script output as vector documents (pdf,eps), bitmap images (png,gif,jpg,tiff), or animations (mov,gif).

• Enhanced command line interface.
• Simplified api with broad support for the Python with statement
• New text editor with tab completion, syntax color themes, and emacs/vi bindings.
• Video export in H.264 or animated gif formats (with GCD-based i/o).
• Core Graphics support for gradients, shadows, blend modes, and alpha channels
• Enhanced typography with inline styles and simpler font selection.
• Added support for external editors by reloading the source when changed.
• Build system now works with Xcode or py2app for the application and pip for the module.
• Virtualenv support (for both installation of the module and running scripts with dependencies).
• External scripts can use from plotdevice import * to create a drawing environment.
• Now uses the system's Python 2.7 interpreter.

PlotDevice supports being built as either a full-fledged Cocoa application, or as a standard Python module to be installed into a virtualenv alongside your source files. In both cases it now includes a command line tool called plotdevice allowing you to run scripts and perform batch exports from the console.

The application can be built in Xcode with the PlotDevice.xcodeproj project. It can also be built from the command line by using python setup.py app (which uses Xcode) or python setup.py py2app (which uses setuptools).

The resulting binary will appear in the dist subdirectory and can be moved to your Applications folder or any other fixed directory. To install a symlink to the command line tool, launch the app from its installed location and click the Install button in the Preferences window.

Prebuilt application binaries can be downloaded from the PlotDevice site.

PlotDevice can also be built as a Python module, allowing you to rely on an external editor and launch scripts from the command line (or from a ‘shebang’ line at the top of your script invoking the plotdevice tool). To install the module and command line tool use python setup.py install

Easier still, you can install the module directly from PyPI with a simple pip install plotdevice

The PlotDevice Manual provides extensive documentation of the various drawing commands and features sample code for nearly all of them. In addition to a detailed Reference, the manual also contains a number of Tutorial chapters that explain PlotDevice's inner workings concept-by-concept.

Beyond the core API, the Manual also collects documentation for the set of third-party Libraries that were written by the NodeBox community and ported to work with PlotDevice.

Once you have installed PlotDevice and added the plotdevice command to your shell's path, it can be used to run scripts in a window or export graphics to file using one of the supported image/video formats.

plotdevice [-f] [-b] [--live] [--cmyk] [--virtualenv PATH] [--args [a [b ...]]]
           [--export FILE] [--frames N or M-N] [--fps N] [--rate N] [--loop [N]]
           file

Runtime arguments

-f run full-screen
--virtualenv PATH path to a virtualenv whose libraries you want to use (this should point to the top-level virtualenv directory)
--args [a [b ...]] arguments to be passed to the script as sys.argv

External editor integration

-b run PlotDevice in the background (i.e., don't switch apps when the script is run)
--live re-render graphics each time the file is saved

Image/animation export

--export FILE a destination filename ending in pdf, eps, png, tiff, jpg, gif, or mov
--cmyk convert colors to CMYK before generating images (colors will be RGB if omitted)

Animation options

--frames N or M-N number of frames to render or a range specifying the first and last frames (default 1-150)
--fps N frames per second in exported video (default 30)
--rate N video bitrate in megabits per second (default 1)
--loop [N] number of times to loop an exported animated gif (omit N to loop forever)

# Run a script
plotdevice script.pv

# Run fullscreen
plotdevice -f script.pv

# Save script's output to pdf
plotdevice script.pv --export output.pdf

# Create an animated gif that loops every 2 seconds
plotdevice script.pv --export output.gif --frames 60 --fps 30 --loop

# Create a sequence of numbered png files – one for each frame in the animation
plotdevice script.pv --export output.png --frames 10

# Create a 5 second long H.264 video at 2 megabits/sec
plotdevice script.pv --export output.mov --frames 150 --rate 2.0

Since PlotDevice scripts are pure Python, the entirety of the stdlib and PyPI are avaliable to you. In addition, a wide array of PlotDevice Libraries have been contributed by the community to solve more visualization-specific problems.

‘Libraries’ are Python modules that have been written specifically for PlotDevice. To install a Library, copy its folder to ~/Library/Application Support/PlotDevice and then import it from your script. Libraries can be installed individually or en masse using the archive (35 MB) from the PlotDevice website.

The easiest way to use third-party modules from a PlotDevice script is to create a virtualenv and use pip to install your dependencies. You can then launch your script with the --virtualenv option to add them to the import path:

$ virtualenv env
$ source ./env/bin/activate
(env)$ pip install redis
(env)$ plotdevice script.pv --virtualenv ./env

If you're using PlotDevice as a module rather than an application, you have the option of installing it directly into the virtualenv containing your script's other dependencies. This places the plotdevice tool at a known location relative to your script and lets you omit the --virtualenv option:

$ virtualenv env
$ source ./env/bin/activate
(env)$ pip install plotdevice
(env)$ pip install requests envoy bs4 # some other useful packages
(env)$ plotdevice script.pv # uses the tool found at ./env/bin/plotdevice

Though the plotdevice command provides a convenient way to launch scripts with the PlotDevice interpreter, you may prefer to use the module's graphics context and export functions from within your own script (and running whichever python binary your system or virtualenv provides). Importing the plotdevice module's contents initializes your script's namespace with one identical to a script running with the app or command line tool. For instance, the following will draw a few boxes:

#!/usr/bin/env python
from plotdevice import *
for x, y in grid(10,10,12,12):
    rect(x,y, 10,10)

You can then generate output files using the global export command. It takes a file path as an argument and the format will be determined by the file extension (pdf, eps, png, jpg, gif, or tiff):

export('~/Pictures/output.pdf')

If you plan to generate multiple images, be sure to call clear() to erase the canvas in between frames. Depending on the task you may also want to reset the graphics state. Use one of:

clear()    # erases the canvas
clear(all) # erases the canvas and resets colors, transforms, effects, etc.

The export function returns a context manager that encapsulates this clear/draw/save cycle for both single images and animations. By enclosing your drawing code in a with block, you can ensure that the correct sequence of clear and export calls is generated automatically. For instance these two methods of generating a png are equivalent:

from plotdevice import *

# export an image
clear(all)
... # (do some drawing)
export('output.png')

# export an image (with the context manager clearing and saving the canvas automatically)
with export('output.png'):
    ... # (do some drawing)

If you specify a filename ending in mov – or gif if you also pass a loop or fps argument – the export context manager will return a Movie object. Each time you call its add method, a new frame with the contents of the canvas will be added to the end of the animation. Once you've added the final frame, you must call finish to wait for the video encoder thread to complete its work.

As with the single-image version of the export call, you can use the with statement in your code to tidy up some of the frame-drawing boilerplate. All three examples are equivalent (note the use of a nested with statement in the final example):

# export a 100-frame movie
movie = export('anim.mov', fps=50, bitrate=1.8)
for i in xrange(100):
    clear(all)  # erase the previous frame from the canvas
    ...         # (do some drawing)
    movie.add() # add the canvas to the movie
movie.finish()  # wait for i/o to complete

# export a movie (with the context manager finishing the file when done)
with export('anim.mov', fps=50, bitrate=1.8) as movie:
    for i in xrange(100):
        clear(all)  # erase the previous frame from the canvas
        ...         # (do some drawing)
        movie.add() # add the canvas to the movie

# export a movie (with the context manager finishing the file when done)
# let the movie.frame context manager call clear() and add() for us
with export('anim.mov', fps=50, bitrate=1.8) as movie:
    for i in xrange(100):
        with movie.frame:
            ... # draw the next frame

Creating PDF documents works the same way, letting you either manually clear, add and finish the export or take advantage of the with statement to hide the repetitive bits. Note that PDF exports use the page attribute rather than frame:

# export a five-page pdf document
pdf = export('multipage.pdf')
for i in xrange(5):
    clear(all) # erase the previous page's graphics from the canvas
    ...        # (do some drawing)
    pdf.add()  # add the canvas to the pdf as a new page
pdf.finish()   # write the pdf document to disk

# export a pdf document more succinctly
with export('multipage.pdf') as pdf:
    for i in xrange(5):
        with pdf.page:
            ... # draw the next page

If you're generating a series of images, export will automatically give them consecutive names derived from the filename you pass as an argument. If the filename is a simple "name.ext" string, the sequence number will be appended with four characters of padding (yielding "name-0001.ext", "name-0002.ext", etc.).

If the filename contains a number between curly braces (e.g., "name-{4}.ext"), that substring will be replaced with the sequence number and zero padded to the specified number of digits:

# export a sequence of images to output-0001.png, output-0002.png, ...
#                                output-0099.png, output-0100.png
with export('output.png') as img:
    for i in xrange(100):
        with img.frame:
            ... # draw the next image in the sequence

# export a sequence of images to 01-img.png, 02-img.png, ...
#                                99-img.png, 100-img.png
with export('{2}-img.png') as img:
    for i in xrange(100):
        with img.frame:
            ... # draw the next image in the sequence

PlotDevice was derived from NodeBox's 1.9.7 release. Its current maintainer is Christian Swinehart.

NodeBox is a BSD-licensed graphics environment written by Frederik De Bleser.
The NodeBox manual and example code are by Tom De Smedt.

NodeBox is a fork of DrawBot by Just van Rossum.

PlotDevice is released under the MIT license. Use it as you see fit.

The PlotDevice source is available on GitHub: https://github.com/plotdevice/plotdevice