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# Mathieu Blondelmblondel

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Created Apr 13, 2010
Logarithm of a sum without underflow
View logsum.py
 import numpy as np def _logsum(logx, logy): """ Return log(x+y), avoiding arithmetic underflow/overflow. logx: log(x) logy: log(y) Rationale:
Created Jun 20, 2010
TCP/IP server using a main loop
View echo_server.py
 # adapted from http://roscidus.com/desktop/node/413 import socket import gobject def server(host, port): '''Initialize server and start listening.''' sock = socket.socket() sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) sock.bind((host, port))
Created Jul 4, 2010
Python corountine examples
View coroutines.py
 def recv_count(): try: while True: n = (yield) print "T-minus", n except GeneratorExit: print "Kaboom!" def ex1(): r = recv_count()
Created Jul 12, 2010
Good-looking HMM and Lattice diagrams using TikZ
View hmm.tex
 % (C) Mathieu Blondel, July 2010 \documentclass[a4paper,10pt]{article} \usepackage[english]{babel} \usepackage[T1]{fontenc} \usepackage[ansinew]{inputenc} \usepackage{lmodern} \usepackage{amsmath}
Created Jul 23, 2010
Solve second order differential equation using the Euler and the Runge-Kutta methods
View second_order_ode.py
 #!/usr/bin/env python """ Find the solution for the second order differential equation u'' = -u with u(0) = 10 and u'(0) = -5 using the Euler and the Runge-Kutta methods.
Created Jul 23, 2010
Solve Number plate game by generating and interpreting Forth programs
View number_plate_solver.py
 #!/usr/bin/env python """ Find the operations needed to sum up to TARGET by using all 4 numbers in NUMBERS. """ from itertools import permutations, product NUMBERS = ["3","4","7","8"] TARGET = 10.0
Created Jul 25, 2010
Compute pi by MCMC
View mc_pi.py
 from random import random """ Find pi by the Monte-Carlo method. area of a circle = pi r^2 area of a square = (2r)^2 = 4 r^2 Perform random uniform sampling between -1 and 1. The proportion of points in the unit circle is:
Created Aug 14, 2010
MCMC exercises
View mcmc_exercices.py
 """ Exercises for the Markov Chain Monte-Carlo (MCMC) course available at http://users.aims.ac.za/~ioana/ """ import numpy as np import numpy.linalg as la import pylab from scipy import stats
Last active Jul 12, 2020
Latent Dirichlet Allocation with Gibbs sampler
View lda_gibbs.py
 """ (C) Mathieu Blondel - 2010 License: BSD 3 clause Implementation of the collapsed Gibbs sampler for Latent Dirichlet Allocation, as described in Finding scientifc topics (Griffiths and Steyvers) """
Last active Aug 1, 2020
Support Vector Machines
View svm.py
 # Mathieu Blondel, September 2010 # License: BSD 3 clause import numpy as np from numpy import linalg import cvxopt import cvxopt.solvers def linear_kernel(x1, x2): return np.dot(x1, x2)
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