blur

0.1

blur is a suite of tools for Python to help make using chance operations in algorithmic art easier.

>>> from blur.markov.graph import Graph
>>> word_distance_weights = {-5: 1, -1: 2, 1: 8, 3: 3}
>>> graph = Graph.from_string('blur is a suite of tools '
... 'to help make using chance operations in algorithmic '
... 'art easier', word_distance_weights)
>>> print(' '.join(graph.pick().name for i in range(8)))
using chance algorithmic in algorithmic art easier blur

Naive implementations of chance operations in algorithmic art often rely on uniform probability distributions.

# [Imaginary examples of uniform random solutions]
# The standard library random number generation module
import random
# Add oscillators with random frequencies between 220Hz and 880Hz
for i in range(100):
    add_oscillator(frequency=random.randint(220, 880))
# --------------------------------------------------------------
# Pick a random color for an object
apple.fill_color_rgb = (random.randint(200, 255),
                        random.randint(180, 230),
                        random.randint(20, 60))
# --------------------------------------------------------------
# Choose a word
print('I have {0} to say and I am saying it and that is poetry.'.format(
    random.choice(['nothing', 'something', 'everything'])))

While for many situations these types of uniform random processes are perfectly suitable, they are limited in scope and run the risk of causing chance output to feel static or arbitrarily uniform. What if you want to add a hundred oscillators whose frequencies tend toward, but aren't limited to, 440Hz? What if you want to color an apple somewhere between bright red and a natural green? What if you have a large field of words that might appear in your poem but you slightly prefer some over others?

blur allows you to easily implement complex chance generated elements in your works without getting bogged down in the boilerplate and the nitty-gritty math.

from blur import soft, rand
frequency_profile = rand.normal_distribution(mean=440, variance=50)
for i in range(100):
    add_oscillator(frequency=weighted_rand(frequency_profile))
# -----------------------------------------------------------------
color = soft.SoftColor(red=([(255, 10), (100, 0)],),
                       green=([(200, 10), (100, 0)],),
                       blue=([(0, 20), (80, 1)],))
apple.fill_color_rgb = color.get()
# -----------------------------------------------------------------
words = soft.SoftOptions([('nothing', 10),
                          ('something', 3),
                          ('everything', 1)])
print('I have {0} to say and I am saying it and that is poetry.'.format(
    words.get())

At the heart of blur is the rand module, which contains a series of functions for finding non-uniform random numbers based on customizable weights. blur also comes with a model markov graph, a tool for deriving markov graphs from text, a collection of soft objects whose values vary according to customizable weights and rules, and a model I Ching.

Besides Python (version 2.7 or 3.x), blur has no dependencies, making it easy to incorporate into your project.

To install blur use pip from the command line:

pip install blur

You can read the latest official documentation for blur online here.

---

Contributing

Feature requests, bug reports, and pull requests are all welcomed! Head on over to https://github.com/ajyoon/blur and get in touch.

Testing

The test suite is located in the tests directory. Travis has been configured to automatically run these tests on any changes in the git repository, but you can run these tests yourself as well. Travis tests run on nose, but any testing framework compatible with the built-in Python Unittest module should work. To get nose you can install it with pip:

pip install nose

To run the tests, navigate to tests and run nose:

cd blur/tests
nosetests *.py

or alternatively:

cd blur
nosetests tests/*.py

Building the documentation

To get the requirements to build the documentation, navigate to the docs folder and install from doc_requirements.txt

cd blur/doc
pip install -r doc_requirements.txt

To build, simply navigate to the doc folder and call make html

cd blur/doc
make html

TODO:

• Add examples
• Refine documentation