pschulam

# Simple root finding using Newton's method
#
# Function to be optimized: f(x) = x^2 - 4 * sin(x)

import math

def objfun(x):
    '''Compute the value and gradient of our function at x.'''
    f = x**2 - 4 * math.sin(x)
    fp = 2 * x - 4 * math.cos(x)

pschulam

# Script to help understanding of S3 object-oriented programming
# in R using classes and methods
 
# Constructor functions for various classes of animal
pig <- function() structure(list(), class=c("pig", "animal"))
dog <- function() structure(list(), class=c("dog", "animal"))
cat <- function() structure(list(), class=c("cat", "animal"))

makeSound <- function(x) UseMethod("makeSound")

pschulam

log.sum <- function(x) {
    m <- max(x)
    r <- sum(exp(x - m))
    return m + log(r)
}

cdist <- function(X, Z) {
    nX <- rowSums(X ** 2)
    nX <- replicate(nrow(Z))
    nZ <- rowSums(Z ** 2)

pschulam

import numpy as np

def log_sum(X):
    m = X.max(0)
    r = np.exp(X - m).sum(0)
    return m + np.log(r)

pschulam

archive: stuff you want to archive
	 $(eval DATE := $(shell date +'%F.%R'))
	 @mkdir -p .archive/$(DATE)
	 @rm -f .archive/$(DATE)/options.txt
	 @$(foreach V,$(sort $(.VARIABLES)),$(if $(filter-out environment% default automatic,$(origin $V)),echo '$V=$(value $V)' >> .archive/$(DATE)/options.txt;))
	 @cp $^ .archive/$(DATE)