scientific-computing

I am working on probabilistic models, and when doing inference on those models, the estimated probabilities can become very small. In order to avoid underflow, I am currently working in the log domain (I store the log of the probabilities). Multiplying probabilities is equivalent to an addition, and summing is done by using the formula: log(exp(a) + exp(b)) = log(exp(a - m) + exp(b - m)) + m where m = max(a, b) . I use some very large matrices, and I have to take the element-wise exponential of those matrices to compute matrix-vector multiplications. This step is quite expensive, and I was

Is there a standard function for Python which outputs True or False probabilistically based on the input of a random number from 0 to 1? example of what I mean: def decision(probability): ...code goes here... return ...True or False... the above example if given an input of, say, 0.7 will return True with a 70% probability and false with a 30% probability import random def decision(probability): return random.random() < probability Blindy Given a function rand that returns a number between 0 and 1, you can define decision like this: bool decision(float probability) { return rand()<probability;

I would like to use the Windows Calculator in Scientific Mode in order solve a very basic Logarithm equation but, unfortunately, I couldn't do that. Here is the problem: log_5 125=? Thank you very much for your help... Well, I know it equals to "3", but, how can I use the Windows Calculator to get computed that equation for example? Shay You can calculate a logarithm in a given base by calculating two logarithms in an arbitrary base, using the following equation: log_b (x) = log_k (x) / log_k (b) As the windows calculator got a ln button, which stands for the natural logarithm (that is, log in

I have been looking for a python module that implements the common techniques of global optimization (finding the global minimum of a function in N dimensions) without success. If you heard about a simulated annealing or genetic algorithm implementation in python, please share. Justin Peel Scipy's optimize module has an anneal function that might fit your needs. Also, you should check out the PyEvolve module for doing a genetic algorithm. I'm not an expert, but have you looked at: Scipy's optimize: http://docs.scipy.org/doc/scipy/reference/optimize.html#global NLOpt: http://ab-initio.mit.edu

I have a project written in C# where I need to do various linear algebraic operations on matrices (like LU-factorization). Since the program is mainly a prototype created to confirm a theory, a C# implementation will suffice (compared to a possibly speedier C++ one), but I would still like a good BLAS or LAPACK library available to save me some coding. Long story short, can anybody recommend a free/open source BLAS or LAPACK library for use with .net? Best regards Egil. Update: Found Math.NET Numerics today, looks interesting, anybody have any experience with that? AMD's ACML is a free