krishnanraman

import org.jfree.chart.{ChartFactory, ChartUtilities}
import org.jfree.data.time.{Day, TimeSeries, TimeSeriesCollection}
import scala.io.Source
import java.io.File

val dow = new TimeSeries("dow")
Source.fromFile("./DJI.csv").getLines.toStream.tail.foreach{
  x:String =>
  val arr = x.split(",")
  val day = Day.parseDay(arr(0))

krishnanraman

import multiprocessing as mp
import numpy as np
import sys

def printf(format, *args):
    sys.stdout.write(format % args)

def f(x):
	sum = 0
	for i in np.arange(x, 2*x,1):

krishnanraman

import util.Random

object TalebDart extends App {
	case class Dart(x:Double, y:Double)
	
	case class Box(minx:Double, miny:Double) {
		var count = 0

		def inBox(dart:Dart):Boolean = {
			val isin = dart.x >= minx && dart.x <= minx + 0.25 &&

krishnanraman

#include "factorial.h"

int factorial(int x) {
	if (x==1) 
		return 1;
	else
		return x * factorial(x-1);
}

krishnanraman

object ucb1 extends App {
	printf("Min Bid:")
	val min = readDouble
	printf("Max Bid:")
	val max = readDouble
	printf("Number of arms:")
	val arms = readInt
	printf("Trials (say 1000):")
	val trials = readInt

krishnanraman

object variableBid extends App {
	printf("Min Bid:")
	val min = readDouble
	printf("Max Bid:")
	val max = readDouble
	printf("Number of arms:")
	val arms = readInt
	printf("Trials (say 1000):")
	val trials = readInt
	printf("Epsilon (say 0.01):")

krishnanraman

object epsilongreedy extends App {
	// cmd-line inits
	print("Run 10,000 trials with Arm Probabilities (eg. 0.3,0.7): ")
	val s = readLine
	val armprob:List[Double] = s.split(",").toList.map{ x => x.toDouble }
	val arms = armprob.size	
	val trials = 10000
	val epsAll = List(0.01,0.1,0.5,0.9,0.99).map{ eps => Eps(eps, arms)}
	val bestArm:Int = armprob.zipWithIndex.maxBy{ x=> x._1}._2

krishnanraman

/*
  Given an unsorted array/list of integers, write a function that:
  - returns True iff there are duplicate integers in the list
  - returns False otherwise
  
[-12, 32, 56, -2] -> False
[32, 23, 23, 1, 5 ] -> True
*/

// To execute Scala code, please define an object named Solution that extends App

krishnanraman

# This is selu, the best ever breakthrough activation function since sliced bread
import numpy as np
def selu(x):
    alpha = 1.67326
    scale = 1.0507
    return scale*np.where(x>=0.0, x, alpha*np.exp(x) - alpha)

# Plot it in matplot, stare at it for a while
# I figure 3 straight lines can do a decent job of interpolating it on unit interval 
from scipy import stats

krishnanraman

object foo extends App {
case class C(n:String, id:Int, pid:Int)
val l = List(C("mh", 3,6), C("sf", 1,0), C("ny", 6,0), C("ba",2,1))
def printChildren(pid:Int, l:List[C]):Unit = 
	l
	.filter{ x=> x.pid == pid}
	.sortBy{ x=> x.n}
	.foreach {x => println(x.n); printChildren(x.id, l)}
printChildren(0, l)
}