Martin Dengler mdengler

## demo_20news.py
import numpy as np
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer

def get_vectors(vocab_size=5000):
    newsgroups_train = fetch_20newsgroups(subset='train')
    vectorizer = CountVectorizer(max_df=.9, max_features=vocab_size)
    vecs = vectorizer.fit_transform(newsgroups_train.data)
    vocabulary = vectorizer.vocabulary
    terms = np.array(vocabulary.keys())

## gist:90e0064ea6c648f44272
#!/usr/bin/python

# to use:
# 1) git clone git@github.com:jszakmeister/nose.git nose-711
# 2) cd nose-711
# 3) python setup.py build
# 4) cd build/lib
# 5) put this file there as test.py
# 6) PYTHONPATH=$PWD python -m nose ./test.py
#    # observe the error:

## test.py
#!/usr/bin/python

# to use:
# 1) git clone git@github.com:jszakmeister/nose.git nose-711
# 2) cd nose-711
# 3) python setup.py build
# 4) cd build/lib
# 5) put this file there as test.py
# 6) PYTHONPATH=$PWD python -m nose ./test.py
#    # observe the error:

## README.md

      
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                mdengler
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              Last active
              August 29, 2015 14:02
                — forked from mbostock/.block
            
              
                Wilson's algorithm by mbostock, with quicker-completion starting conditions
              
          
    Wilson’s algorithm uses loop-erased random walks to generate a uniform spanning tree — an unbiased sample of all possible spanning trees. Most other maze generation algorithms, such as Prim’s, random traversal and randomized depth-first traversal, do not have this beautiful property.
The algorithm initializes the maze with eight arbitrary starting cells. Then, a new cell is added to the maze, initiating a random walk (shown in magenta). The random walk continues until it reconnects with the existing maze (shown in white). However, if the random walk intersects itself, the resulting loop is erased before the random walk continues.
The global structure of the maze can be more easily seen by flooding it with color.
To play with this yourself, [instructions from Uehreka on http://news.yco

  
## gist:c1e17977015325e3d084
### Keybase proof

I hereby claim:

  * I am mdengler on github.
  * I am mdengler (https://keybase.io/mdengler) on keybase.
  * I have a public key whose fingerprint is 565C 8F33 ABF7 2DAA 33DE  B9CB 81B4 44DD 75C7 D2F8

To claim this, I am signing this object:

## garch.py
#!/usr/bin/env python

# Trivial GARCH implementation in python
#
# From Peter Tessin's http://www.petertessin.com/TimeSeries.pdf
#

## gist:2817318
#!/usr/bin/env python

# See https://github.com/Elleo/gst-opencv/blob/master/examples/python/facedetect.py
# See also http://blog.mikeasoft.com/2010/06/17/gstreamer-opencv-plugins-on-the-nokia-n900/

import pygst
pygst.require("0.10")
import gst
import gtk

## csvvert.py
#!/usr/bin/env python
"""

Displays a CSV file's contents vertically.

Example:

$ cat | ~/bin/csvvert.py
Year,Make,Model,Length
1981,Ford,Capri Ghia,2.34

## html2csv.py
#!/bin/env python
# -*- coding: utf-8 -*-
"""

Examples:

%(progname)s http://en.wikipedia.org/wiki/List_of_Olympic_records_in_athletics

This is essentially this logic, done up

## pinnaclefeed.py
#!/usr/bin/env python

"""

Proof of concept scraper for pinnacle sports

"""

FEED = "http://xml.pinnaclesports.com/pinnacleFeed.aspx"
	import numpy as np
	from sklearn.datasets import fetch_20newsgroups
	from sklearn.feature_extraction.text import CountVectorizer

	def get_vectors(vocab_size=5000):
	newsgroups_train = fetch_20newsgroups(subset='train')
	vectorizer = CountVectorizer(max_df=.9, max_features=vocab_size)
	vecs = vectorizer.fit_transform(newsgroups_train.data)
	vocabulary = vectorizer.vocabulary
	terms = np.array(vocabulary.keys())
	#!/usr/bin/python

	# to use:
	# 1) git clone git@github.com:jszakmeister/nose.git nose-711
	# 2) cd nose-711
	# 3) python setup.py build
	# 4) cd build/lib
	# 5) put this file there as test.py
	# 6) PYTHONPATH=$PWD python -m nose ./test.py
	# # observe the error:
	### Keybase proof

	I hereby claim:

	* I am mdengler on github.
	* I am mdengler (https://keybase.io/mdengler) on keybase.
	* I have a public key whose fingerprint is 565C 8F33 ABF7 2DAA 33DE B9CB 81B4 44DD 75C7 D2F8

	To claim this, I am signing this object:
	#!/usr/bin/env python

	# Trivial GARCH implementation in python
	#
	# From Peter Tessin's http://www.petertessin.com/TimeSeries.pdf
	#
	#!/usr/bin/env python

	# See https://github.com/Elleo/gst-opencv/blob/master/examples/python/facedetect.py
	# See also http://blog.mikeasoft.com/2010/06/17/gstreamer-opencv-plugins-on-the-nokia-n900/

	import pygst
	pygst.require("0.10")
	import gst
	import gtk
	#!/usr/bin/env python
	"""

	Displays a CSV file's contents vertically.

	Example:

	$ cat \| ~/bin/csvvert.py
	Year,Make,Model,Length
	1981,Ford,Capri Ghia,2.34
	#!/bin/env python
	# -- coding: utf-8 --
	"""

	Examples:

	%(progname)s http://en.wikipedia.org/wiki/List_of_Olympic_records_in_athletics

	This is essentially this logic, done up
	#!/usr/bin/env python

	"""

	Proof of concept scraper for pinnacle sports

	"""

	FEED = "http://xml.pinnaclesports.com/pinnacleFeed.aspx"