mrocklin

import theano
import theano.tensor as T
import pickle
import numpy as np

# Create a simple example
x   = T.matrix('x')
y   = x + x
env = theano.Env([x], [y])

mrocklin

def shape_of_variables(env, input_shapes):
    """
    Inputs:
        env - the theano.Env in question
        input_shapes - a dict mapping input to shape

    Outputs:
        shapes - a dict mapping variable to shape

    WARNING : This modifies the env! Not pure!

mrocklin

#!/usr/bin/python

import re
import networkx as nx
import os

prog = re.compile("class (?P<subclass>\w+)\((?P<superclasses>[\s\w,]+)\):")

def grep_stream(location):
    return os.popen(

mrocklin

import theano
import theano.sandbox.linalg as linalg

mu = theano.tensor.matrix('mu')
Sigma = theano.tensor.matrix('Sigma')
H = theano.tensor.matrix('H')
R = theano.tensor.matrix('R')
data = theano.tensor.matrix('data')

dot = theano.tensor.dot

mrocklin

import theano
from theano.tensor.io import send, recv, mpi_cmps
import theano.sandbox.linalg as linalg
from theano.gof.sched import sort_schedule_fn
from time import time

dot = theano.tensor.dot
dtype = 'float32'
n = 500
run = False

mrocklin

#include <stdio.h>
#include <sys/time.h>

const int n = 16000000;

// Print number of milliseconds between timevals
void printDuration(timeval a, timeval b, char* message)
{
    double elapsedTime = (b.tv_sec - a.tv_sec) * 1000.0;
    elapsedTime += (b.tv_usec - a.tv_usec) / 1000.0;

mrocklin

! Answers discussion in the following SO question
! http://stackoverflow.com/questions/4637888/where-can-i-find-blas-example-code-in-fortran/

! Author: Matthew Rocklin
! Disclaimer: This is my first Fortran program. Please do not judge.

implicit none

integer, parameter :: N=2

mrocklin

In [1]: from sympy.stats import *

In [2]: x0 = Symbol('x0', real=True, bounded=True)

In [3]: gamma = Symbol('gamma', positive=True)

In [4]: X = Cauchy('X', x0, gamma)

In [5]: density(X)(x)
Out[5]: 

mrocklin

In [1]: from sympy.stats import *

In [2]: nu = Symbol("nu", positive=True)

In [3]: X = StudentT("x", nu)

In [4]: density(X)(x)
Out[4]: 
          ν   1         
        - ─ - ─         

mrocklin

from numpy import linspace, sin
from pylab import plot, figure, show

def plotFunction(f):
    """ Plot a function on the domain x in (-10, 10) """
    xs = linspace(-10, 10, 100)
    ys = map(f, xs)
    plot(xs, ys)

def derivative(f, dx=.00001):