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import breeze.linalg._
import breeze.stats._
import scala.math.sqrt


/**
 * Effecient for sparse vectors. Scales in O(activeSize)
 */
// Must take SparseVector, for implicits to be linked correctly
def pearson(a: SparseVector[Double], b: SparseVector[Double]): Double = {

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// genrate all combinations of integers in range from 0 to `len`-1
// fast as fuck
def combIdxs(len: Int, k: Int): Iterator[Array[Int]] = {
  val arr = Array.range(0, k)
  arr(k-1) -= 1
  val end = k-1
  
  Iterator.continually {
    arr(end) += 1
    if (arr(end) >= len) {

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// min-hash

val fs: Vector[Int => Int] // hash funkce

items map { it => fs map { f => f(it) } } fold (vectorPairwise(min), initialValue = Vector.fill(infinity))



// HyperLogLog

darkseed

import breeze._
import breeze.linalg._
import breeze.numerics._
import java.awt.image.BufferedImage
import javax.imageio.ImageIO

val f = ???
val img = javax.imageio.ImageIO.read(new File(f))
val gray = new BufferedImage(img.getWidth, img.getHeight, BufferedImage.TYPE_BYTE_GRAY)
val g = gray.createGraphics()

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import breeze.linalg._
import breeze.stats
import breeze.numerics._

val dataFile = new File(???)
val userItems: Array[SparseVector[Double]] = loaderUserItemsWithRatings(dataFile, """[ ,:]""".r)
val itemUsers: Array[SparseVector[Double]] = transpose(userItems) map { vec => normalize(vec, 2) }

// weights
val N = DenseVector.fill[Double](itemIndex.size)(userIndex.size) // vector where total numbers of users is repeated

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package breeze.linalg.functions

import breeze.generic.UFunc
import breeze.linalg.{SparseVector, DenseVector}
import breeze.numerics.sqrt

/**
 * A weighted Euclidean distance function implementation
 */
object weightedEuclideanDistance extends UFunc {

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#!/bin/bash
##################################################################################################################
#Gatling scale out/cluster run script:
#Before running this script some assumptions are made:
#1) Public keys were exchange inorder to ssh with no password promot (ssh-copy-id on all remotes)
#2) Check  read/write permissions on all folders declared in this script.
#3) Gatling installation (GATLING_HOME variable) is the same on all hosts
#4) Assuming all hosts has the same user name (if not change in script)
##################################################################################################################

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#!/usr/bin/env bash

# Assuming OS X Yosemite 10.10.4

# Install XCode and command line tools
# See https://itunes.apple.com/us/app/xcode/id497799835?mt=12#
# See https://developer.apple.com/library/mac/documentation/Darwin/Reference/ManPages/man1/xcode-select.1.html
xcode-select --install

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package com.agilogy.spray.cors

import spray.http.{HttpMethods, HttpMethod, HttpResponse, AllOrigins}
import spray.http.HttpHeaders._
import spray.http.HttpMethods._
import spray.routing._

// see also https://developer.mozilla.org/en-US/docs/Web/HTTP/Access_control_CORS
trait CORSSupport {
  this: HttpService =>

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plot.nnet<-function(mod.in,nid=T,all.out=T,all.in=T,bias=T,wts.only=F,rel.rsc=5,
                    circle.cex=5,node.labs=T,var.labs=T,x.lab=NULL,y.lab=NULL,
                    line.stag=NULL,struct=NULL,cex.val=1,alpha.val=1,
                    circle.col='lightblue',pos.col='black',neg.col='grey',
                    bord.col='lightblue', max.sp = F,...){

  require(scales)
  
  #sanity checks
  if('mlp' %in% class(mod.in)) warning('Bias layer not applicable for rsnns object')