Chris Fonnesbeck fonnesbeck

## foo.py
a=1

## gist:342992
\,{\buildrel d \over =}\,

## factor2numeric.R
as.numeric(levels(f))[f]

## cprob.tex
Y_i \sim \left\{ \begin{array}{l}
0, \text{with probability } (1-\psi) \\
\text{Poisson}(\mu), \text{with probability } \psi
\end{array} \right.

## homebrew_scipy.sh
homebrew install gfortran
homebrew install python
homebrew install distribute
homebrew install pip
pip install ipython
pip install numpy
pip install scipy
pip install -f http://downloads.sourceforge.net/project/matplotlib/matplotlib/matplotlib-1.0/matplotlib-1.0.0.tar.gz matplotlib

## Twitchimps.R
library(twitteR)
library(infochimps)
library(datamap)

infochimps('YOUR_API_KEY')

# Creates a new mapper, similar to an OO class
newMapper(type='twitchimps:influence',

    # Init is called once during newMap(). Note that

## plot2Ddist.py
"""Routines related to plotting 2D distributions of parameters.

The core of this module is plot2Ddist, which plots a two-dimensional
distribution with 1D marginal histograms along each axis and optional
features like contours and lines indicating ranges and true values.

"""

import itertools
import math

## fill_missing.py
missing = -999
filled_data = [(x, missing)[x is ''] for x in raw_data]

## least_squares.py
import numpy as np
from scipy import linalg

def lse(A, b, B, d, cond=None):
    """
    Equality-contrained least squares.

    The following algorithm minimizes ||Ax - b|| subject to the
    constrain Bx = d.


## stdout_progress.py
# this works just fine w/ multiprocess...
# now with more flushing

import sys
import time

sys.stdout.write("This is running")
sys.stdout.flush()
for i in range(5):
    sys.stdout.write(".")
	Y_i \sim \left\{ \begin{array}{l}
	0, \text{with probability } (1-\psi) \\
	\text{Poisson}(\mu), \text{with probability } \psi
	\end{array} \right.
	homebrew install gfortran
	homebrew install python
	homebrew install distribute
	homebrew install pip
	pip install ipython
	pip install numpy
	pip install scipy
	pip install -f http://downloads.sourceforge.net/project/matplotlib/matplotlib/matplotlib-1.0/matplotlib-1.0.0.tar.gz matplotlib
	library(twitteR)
	library(infochimps)
	library(datamap)

	infochimps('YOUR_API_KEY')

	# Creates a new mapper, similar to an OO class
	newMapper(type='twitchimps:influence',

	# Init is called once during newMap(). Note that
	"""Routines related to plotting 2D distributions of parameters.

	The core of this module is plot2Ddist, which plots a two-dimensional
	distribution with 1D marginal histograms along each axis and optional
	features like contours and lines indicating ranges and true values.

	"""

	import itertools
	import math
	missing = -999
	filled_data = [(x, missing)[x is ''] for x in raw_data]
	import numpy as np
	from scipy import linalg

	def lse(A, b, B, d, cond=None):
	"""
	Equality-contrained least squares.

	The following algorithm minimizes \|\|Ax - b\|\| subject to the
	constrain Bx = d.
	# this works just fine w/ multiprocess...
	# now with more flushing

	import sys
	import time

	sys.stdout.write("This is running")
	sys.stdout.flush()
	for i in range(5):
	sys.stdout.write(".")