Skip to main content

An implementation of the Birman-Margalit-Menasco Theorem, to be used in a experimental, exploratory manner.

Project description

https://travis-ci.org/MICC/MICC.svg?branch=master

The curve complex is a simplicial complex composed of vertices representing equivalency classes of isotopic simple closed curves on a surface of fixed genus and of edges drawn between vertices if classes contain a disjoint representative. MICC is a tool designed to compute short distances between these disjoint representatives, based on an intuitive disk-with-handles represntation of a surface.

Installation

Installing through pip is recommended to use the programmatic interface:

$ pip install micc

Otherwise, the command line interface for MICC is available here.

Getting Started

Example useage of MICC:

from micc.curvepair import CurvePair

top    = [21,7,8,9,10,11,22,23,24,0,1,2,3,4,5,6,12,13,14,15,16,17,18,19,20]
bottom = [9,10,11,12,13,14,15,1,2,3,4,5,16,17,18,19,20,21,22,23,24,0,6,7,8]
test = CurvePair(top, bottom)
print test.distance

Documentation

MICC’s key interface is an abstract representation of a pair of curves a,*b* on a surace S of genus g. We present the details and nuances in our full publication <link>.

img/Birman-matrix-and-ladder.png

Define one of the two curves as a reference curve; in the above case, we choose a as our reference curve. Aftering arbitrarily labeling the arcs of b created by the removal of a, as shown above, read off the chosen identifications in the order they appear on the each side of a during an oriented traversal. Upon doing so, you will have two sequences of integer identifications. In the above example, they look like:

[1, 4, 3, 4, 1, 6]
[6, 5, 2, 3, 2, 5]

These two lists are the input to the CurvePair object, the primary interface layer for MICC. It is highly recommended that users restrict their attention to this object alone.

To compute the distance between a and b:

>>> curve = CurvePair([1, 4, 3, 4, 1, 6],[6, 5, 2, 3, 2, 5])
>>> curve.distance
3

TODO

License

Copyright 2014 Matt Morse and Paul Glenn.

MICC is licensed under the MIT License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

MICC-0.1.5.tar.gz (22.4 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page