garydoranjr

#!/usr/bin/env python
import os
import numpy as np
from scipy.io import savemat
from collections import defaultdict

def get_yields(rootdir, state, year):
    yields = {}
    yfile = 'yields-%s-%s.txt' % (state, year)
    with open(os.path.join(rootdir, yfile), 'r') as f:

garydoranjr

"""
Implements the formula to compare models with the Nemenyi test. "The performance
of two classifiers is significantly different if the corresponding average ranks
differ by at least the critical difference" from:

  Demsar, J. "Statistical comparisons of classifiers over multiple data sets."
      The Journal of Machine Learning Research 7 (2006): 1-30.

Critical values taken from:

garydoranjr

function [examples classifications] = dataset_load(dataset_name)
%  dataset_load(dataset_name)
%    Returns the example feature vectors (as rows) and corresponding
%    classifications. Automatically strips the first column (example ids).

% Load dataset into a structure array
mat_struct = load(dataset_name);

% Syntax to get the field of a structure array by name
% http://www.mathworks.com/help/matlab/ref/getfield.html

garydoranjr

#!/usr/bin/python

PAD = '.......................................................................................................................................................987654321'

if __name__ == '__main__':
    from sys import argv
    msg = argv[1]
    print '%s%s' % (msg, PAD[(len(msg) - len(PAD)):])

garydoranjr

#!/usr/bin/env python
import numpy as np
import pylab as pl
from scipy.spatial.distance import cdist

SAMPLES = 1.5e5
SIGMA = 0.2

def main():
    X = np.random.laplace(size=SAMPLES)

garydoranjr

from cvxopt import matrix as cvxmat, sparse, spmatrix
from cvxopt.solvers import qp, options
import numpy as np

def quadprog(H, f, Aeq, beq, lb, ub):
    """
    minimize:
            (1/2)*x'*H*x + f'*x
    subject to:
            Aeq*x = beq 

garydoranjr

.data
prime:     .string "Prime.\n"
p_len  = . - prime
not_prime: .string "Not Prime.\n"
np_len = . - not_prime
buffer:    .string " "
.text
.globl main
main:
    call    _getinput

garydoranjr

#!/usr/bin/python
from random import random

BE_EVIL = True
MAX_DEPTH = 20
PROB_t = 0.05
PROB_p = 0.4

def production(depth):
    depth += 1

garydoranjr

#!/usr/bin/python
# -*- coding: iso-8859-15 -*-

import string
import sys

def recurse(levels, path):
    if levels == 0:
        left  = string.uppercase[path]
        right = left + "′"