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General and Advanced Pure and Applied Mathematics Use SAGE for studying a huge range of mathematics, including algebra, calculus, elementary to very advanced number theory, cryptography, numerical computation, commutative algebra, group theory, combinatorics, graph theory, and exact linear algebra.

Python library for arbitrary-precision floating-point arithmetic

Mpmath is a pure-Python library for multiprecision floating-point arithmetic. It provides an extensive set of transcendental functions, unlimited exponent sizes, complex numbers, interval arithmetic, numerical integration and differentiation, root-finding, linear algebra, and much more. Almost any calculation can be performed just as well at 10-digit or 1000-digit precision, and in many cases mpmath implements asymptotically fast algorithms that scale well for extremely high precision work. If available, mpmath will (optionally) use gmpy to speed up high precision operations.

For example edge labels can be added using matplotlib "text" objects like this: import networkx as nx import pylab as plot K=nx.XGraph(name="Konigsberg", multiedges=True, selfloops=False) K.add_edges_from([("A","B","Honey Bridge"),     ("A","B","Blacksmith's Bridge"),     ("A","C","Green Bridge"),     ("A","C","Connecting Bridge"),     ("A","D","Merchant's Bridge"),     ("C","D","High Bridge"),     ("B","D","Wooden Bridge")]) pos=nx.spring_layout(K) nx.draw_nx(K,pos) xa,ya=pos['A'] xb,yb=pos['B'] plot.text((xa+xb)/2,(ya+yb)/2,"Blacksmith's Bridge") plot.show() With a little work you can get the label rotated and exactly how you want it positioned.  You can also set the node positions directly in the "pos" dictionary above.

For drawing you can use pygraphviz (also available at networkx.lanl.gov) or the built-in drawing tools.

SVGMath is written in pure Python, with neither extension modules nor external dependencies. It runs on any platform where a modern Python environment (version 2.4 or higher) is available. It can be used either as a command-line script for batch-mode file conversion, or as a component to process MathML data in other Python applications.

StatPy: Statistical Computing with Python Welcome to StatPy, a collection of resources to help you do statistical computing with Python, with a special emphasis on astrostatistics (statistics in astronomy). This web site is brand-spanking-new, and still very much under construction; please be patient with our "dust" and check back again frequently as building continues.