Archive for December 2008

ResolverOne: Best Spreadsheet Wins $17K

ResolverOne is one of my favorite applications in the past few years. It’s a spreadsheet powered by IronPython. Spreadsheets are among the most powerful intellectual tools ever developed: if you can solve your problem with a spreadsheet, a spreadsheet is probably the fastest way to solve it. Yet there are certain things that spreadsheets don’t do well: recursion, branching, etc.

Python is a clean, modern programming language with a large and still-growing community. It’s a language which works well for writing 10 lines of code or 1,000 lines of code. (ResolverOne itself is more than 100K of Python, so I guess it works at that level, too!)

From now (Dec 2008) to May 2009, Resolver Systems is giving away $2K per month to the best spreadsheet built in ResolverOne. The best spreadsheet received during the competition gets the grand prize of an additional $15K.

Personally, it seems to me that the great advantage of the spreadsheet paradigm is a very screen-dense way of visualizing a large amount of data and very easy access to input parameters. Meanwhile, Python can be used to create arbitrarily-complex core algorithms. The combination seems ideal for tinkering in areas such as machine learning and simulation.

I try to do some recreational programming every year between Christmas and New Year. I’m not sure I’ll have the time this year, but if I do, I may well use ResolverOne and Python to do something.

Inference for .NET: Another Option for Python-Based Inference

Inference for .NET is an alternative to Infer.NET & IronPython.

Bonus: Inference for .NET integrates with ResolverOne.

IronPython 2.0 & Microsoft Research Infer.NET 2.2

 import sys import clr sys.path.append("c:\\program files\\Microsoft Research\\Infer.NET 2.2\\bin\\debug") clr.AddReferenceToFile("Infer.Compiler.dll") clr.AddReferenceToFile("Infer.Runtime.dll") from MicrosoftResearch.Infer import * from MicrosoftResearch.Infer.Models import * from MicrosoftResearch.Infer.Distributions import *  firstCoin = Variable[bool].Bernoulli(0.5) secondCoin = Variable[bool].Bernoulli(0.5) bothHeads = firstCoin & secondCoin ie = InferenceEngine() print ie.Infer(bothHeads) --> c:\Users\Larry O'Brien\Documents\Infer.NET 2.2>ipy InferNetTest1.py Compiling model...done. Initialising...done. Iterating: .........|.........|.........|.........|.........| 50 Bernoulli(0.25) 

Sweet

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