abarnash

//-----------------------------------
// Discrete Probability Distributions

let expectation = (xvals, pfn) => xvals.reduce((sum, x) => sum + x * pfn(x), 0)

let variance = (xvals, pfn) => {
  const expect = expectation(xvals, pfn)
  return xvals.reduce((sum, x) => sum + pfn(x) * (x - expect) ** 2, 0)
}

abarnash

With this data model, you can scroll through each interaction/source/channel demographic index directly for each demographic bucket + combination of buckets you want, without having to run through the overhead of traversing a large graph on every run.

INDEX /consumer-demo

Create an index for all consumers with all their relevant demographic attributes. Whatever process(es) that determine these values will update this index

abarnash

(ns duration-to-ms)

(defn string->millis [duration-str]
    (.getMillis (.toStandardDuration (org.joda.time.Period. duration-str))))
  
;; Example
;;=> (string->millis "PT8M56S")
;;53600
;;=>

abarnash

(defn getPromiseFn 
  [aPromise] 
  (fn [num] (Thread/sleep 10000) 
      (deliver aPromise (str num " done"))))
    
(def proms [(promise) (promise) (promise)])
(def promFns (map getPromiseFn proms))

(future (map deref proms))
(future (map promFn (range 0 (count proms))))

abarnash

var array_subtract = function(arr,values) {
  return arr.filter(function(x) {
    var remove = values.filter(function(v){
      return x == v;
    });
    return !remove.length>0;
  });
};