allenday

// cosine distance and pearson correlation
// see http://ow.ly/vtm44

package com.allenday

import com.twitter.scalding._
import com.twitter.scalding.mathematics._
import com.twitter.scalding.mathematics.Matrix._

class SimJob(args : Args) extends Job(args) {

Mortimerp9

import com.twitter.util.{Duration, Time}

/**
 * Sort of a lazy val, but that refreshes itselfs every so often; or a temporary cache for a value T,
 * will be refreshed at a minimun at the specified interval.
 * In practice, the refresh is done only when the value is accessed, so there are no guarantees
 * to when it will actually be refreshed. You can just be sure that it won't be refreshed if two calls
 * are made within `every`.
 */
class RefreshEvery[T](every: Duration)(refresh: => T) {

milessabin

scala> trait Assoc[K] { type V ; val value: V }
defined trait Assoc

scala> def mkAssoc[V0](k: String, v: V0): Assoc[k.type] { type V = V0 } =
     |   new Assoc[k.type] { type V = V0 ; val value = v }
mkAssoc: [V0](k: String, v: V0)Assoc[k.type]{type V = V0}

scala> implicit def nameAssoc = mkAssoc("Name", "Mary")
nameAssoc: Assoc[String("Name")]{type V = String}

EverythingSmartHome

{{ states.binary_sensor
   | selectattr('attributes.device_class', 'in', ['door','window'])
   | selectattr('state', 'equalto', 'on')
   | list | count }}