Ted Benson eob

## Polynomial Fitting
from scipy.optimize import curve_fit
from collections import Counter, defaultdict
import numpy as np
import time

def f(xss, a, b, c, d, e, f):
  """
  Polynomial function up to order 5
  """
  ret = []

## gist:c44bb46165af0bd0cba5
I’ve worked in an economy that rewards someone who saves the lives of others on a battlefield with a
medal, rewards a great teacher with thank-you notes from parents, but rewards those who can detect
the mispricing of securities with sums reaching into the billions. In short, fate’s distribution of long
straws is wildly capricious.

From Warren Buffett's Giving Pledge
http://givingpledge.org/pdf/letters/Buffett_Letter.pdf

## gist:d597f558890c2c05a73a
def record_poop():
  data = {
    "Timestamp": time.strftime("%Y-%m-%d %H:%M"),
    "Measurement": 'Poopy Diaper'
  }
  requests.post(MAGIC_FORM_URL, data)

## gist:80960
p (char *) [data bytes]

## gist:81427
<body>
            <table width="100%">
                <tr>
                    <td colspan=3>

                    </td>

                </tr>
                <tr valign="top">
                    <td width="15%"> <div ex:role="facet" ex:expression=".venue" ex:facetLabel="Venue"></div>

## Initialization of Y
  def initializeToCrfPotentials = {
      for (tweetIdx <- 0 until _Y.size) {
        for (tokenIdx <- 0 until _Y(tweetIdx).size) {
            for (labelIdx <- 0 until _Y(tweetIdx)(tokenIdx).size) {
                // Note: the +1 in token index is because of the <S> token at the beginning
                // of the CRF potentials.
                logger.info(tweetIdx + " " + tokenIdx + " " + labelIdx)
                _Y(tweetIdx)(tokenIdx)(labelIdx) = _crfPotentials(tweetIdx)(tokenIdx + 1)(labelIdx)
            }
        }

## gist:714195
  def initializeToCrfPosteriors = {

      _Y = emptyY // Initialize to all 0s

      require (_Y.size == _crfPotentials.size) // Santiy check: both are over tweets
      for (tweet <- 0 until _crfPotentials.size) {
          _forwardBackward.setInput(_crfPotentials(tweet))
         val nodeMarginals = _forwardBackward.getNodeMarginals()
         val nonBorderMarginals = nodeMarginals.slice(1, nodeMarginals.size - 1)

## gist:718298
  /**
   * log q(Z_i = k) less than or equal to
   *    log P(Z_i=k) (the prior)
   *  + log E_             { q(y_i),q(T_k) } Theta^T_REW f_REW(x_i,y_i,T_k)
   *  - log E_             { q(T_k) } Z_             { x_i } (Theta, T_k)
   */
  def update(td: TaggingDistribution, rd: RecordDistribution) = {

      // Initialize to all -Infinity
    _Z = logEmptyZ()

## gist:718300
  def update(td: TaggingDistribution, ad: AlignmentDistribution) = {
    /*
    * Setup: Create an empty set of records
    */
    var TPrime = List[Record]()
    for (i <- 0 until _T.size) {
      val r = new Record(i, _schema)
      r.setThetaRewrite(_T(i).thetaRewrite)
      TPrime = TPrime :+ r
    }

## gist:731611
object ListCase {
	def matcher(l:List[Int]) {
		l match {
			case List(1,3,5,7) => println("Primes")
			case List(_,_,_,3,_) => println("3 on 3")
			case 1::rest => println("List starting with 1")
			case List(_*) => println("Other list")
		}
	}
}
	from scipy.optimize import curve_fit
	from collections import Counter, defaultdict
	import numpy as np
	import time

	def f(xss, a, b, c, d, e, f):
	"""
	Polynomial function up to order 5
	"""
	ret = []
	I’ve worked in an economy that rewards someone who saves the lives of others on a battlefield with a
	medal, rewards a great teacher with thank-you notes from parents, but rewards those who can detect
	the mispricing of securities with sums reaching into the billions. In short, fate’s distribution of long
	straws is wildly capricious.

	From Warren Buffett's Giving Pledge
	http://givingpledge.org/pdf/letters/Buffett_Letter.pdf
	def record_poop():
	data = {
	"Timestamp": time.strftime("%Y-%m-%d %H:%M"),
	"Measurement": 'Poopy Diaper'
	}
	requests.post(MAGIC_FORM_URL, data)
	<body>
	<table width="100%">
	<tr>
	<td colspan=3>

	</td>

	</tr>
	<tr valign="top">
	<td width="15%"> <div ex:role="facet" ex:expression=".venue" ex:facetLabel="Venue"></div>
	def initializeToCrfPotentials = {
	for (tweetIdx <- 0 until _Y.size) {
	for (tokenIdx <- 0 until _Y(tweetIdx).size) {
	for (labelIdx <- 0 until _Y(tweetIdx)(tokenIdx).size) {
	// Note: the +1 in token index is because of the <S> token at the beginning
	// of the CRF potentials.
	logger.info(tweetIdx + " " + tokenIdx + " " + labelIdx)
	_Y(tweetIdx)(tokenIdx)(labelIdx) = _crfPotentials(tweetIdx)(tokenIdx + 1)(labelIdx)
	}
	}
	def initializeToCrfPosteriors = {

	_Y = emptyY // Initialize to all 0s

	require (_Y.size == _crfPotentials.size) // Santiy check: both are over tweets
	for (tweet <- 0 until _crfPotentials.size) {
	_forwardBackward.setInput(_crfPotentials(tweet))
	val nodeMarginals = _forwardBackward.getNodeMarginals()
	val nonBorderMarginals = nodeMarginals.slice(1, nodeMarginals.size - 1)
	/**
	* log q(Z_i = k) less than or equal to
	* log P(Z_i=k) (the prior)
	* + log E_ { q(y_i),q(T_k) } Theta^T_REW f_REW(x_i,y_i,T_k)
	* - log E_ { q(T_k) } Z_ { x_i } (Theta, T_k)
	*/
	def update(td: TaggingDistribution, rd: RecordDistribution) = {

	// Initialize to all -Infinity
	_Z = logEmptyZ()
	def update(td: TaggingDistribution, ad: AlignmentDistribution) = {
	/*
	* Setup: Create an empty set of records
	*/
	var TPrime = List[Record]()
	for (i <- 0 until _T.size) {
	val r = new Record(i, _schema)
	r.setThetaRewrite(_T(i).thetaRewrite)
	TPrime = TPrime :+ r
	}
	object ListCase {
	def matcher(l:List[Int]) {
	l match {
	case List(1,3,5,7) => println("Primes")
	case List(_,_,_,3,_) => println("3 on 3")
	case 1::rest => println("List starting with 1")
	case List(_*) => println("Other list")
	}
	}
	}