jamesthompson

{
    // You probably want to configure this to something of your own
    // ${home}, ${env:<variable>}, ${project_path:} and ${folder:} tokens can be used in the sublimejava_classpath option.
    //
    // ${home} is replaced with the value of the HOME environment variable.
    //
    // ${env:<variable>} is replaced with the "variable" environment variable.
    //
    // ${project_path:} tries to find a file with the given name in all the registered project folders and
    // returns the first file found, or the original file name if none is found.

jamesthompson

apply plugin: 'java'

sourceCompatibility=1.6
targetCompatibility=1.6

dependencies {
	compile files("/Users/James/Desktop/GUVJesper/lib/ij.jar", "/Users/James/Desktop/GUVJesper/lib/loci_tools.jar")
}

mainClass = 'ND2_GUVPlugin'

jamesthompson

group = 'com.malmstadt'
version = 1.0               

apply plugin: 'scala'

apply from: 'https://repository-javafx-gradle-plugin.forge.cloudbees.com/release/javafx.plugin'

repositories {
    mavenCentral()
}

jamesthompson

implicit class Timer[T](f: => T) {
  def timems = {
    val before = System.currentTimeMillis
    val result = f
    val end = System.currentTimeMillis
    println(s"Operation elapsed time = ${end - before} ms >>> Result = $result")
  }
  def timens = {
    val before = System.nanoTime
    val result = f

jamesthompson

implicit class Meter(val num: Double) extends AnyVal {
  def m  : Double = num
  def mm : Double = num / 1e3
  def um : Double = num / 1e6
  def nm : Double = num / 1e9
}

jamesthompson

import scala.collection.generic.CanBuildFrom
import scala.collection.TraversableLike
implicit class Normalizer[N:Numeric, M[+_]](xs:M[N]) {
  def normalize(implicit bf: CanBuildFrom[M[N], Double, M[Double]], 
                ev: M[N] => TraversableLike[N, M[N]], 
                eb: M[Double] => TraversableLike[Double, M[Double]]) = {
    val n = implicitly[Numeric[N]]
    val mind = n.toDouble(xs.min)
    val maxd = n.toDouble(xs.max)
    xs.map(v => (n.toDouble(v) - mind) * (1 / (maxd - mind)))

jamesthompson

implicit class LinearRegression[NA: Numeric, NB: Numeric, M[+_]](pts: (M[NA], M[NB])) {
    def getVector[A: Numeric](in: M[A]) : Vector[Double] = {
      val n = implicitly[Numeric[A]]
      in.asInstanceOf[TraversableLike[A, Traversable[A]]].map(n.toDouble(_)).toVector
    }
    def lnfit = {
      val xpts = getVector(pts._1)
      val ypts = getVector(pts._2)
      xpts.isEmpty match {
        case true => None

jamesthompson

def legendres(i: Int) : List[Polynomial[Rational]] = {
	val one = Polynomial(0 -> r"1/1")
	val x = Polynomial(1 -> r"1/1")
	lazy val leg : Stream[Polynomial[Rational]] = {
	  def loop(pnm1: Polynomial[Rational], pn: Polynomial[Rational], n: Int = 1) : Stream[Polynomial[Rational]] = {
	  	pn #:: loop(pn, Polynomial(0 -> Numeric[Rational].fromInt(n + 1).reciprocal) * (
	  				      (Polynomial(1 -> Numeric[Rational].fromInt(2 * n + 1)) * pn) + 
                  (Polynomial(0 -> Numeric[Rational].fromInt(n).unary_-) * pnm1)), n + 1)
	  }
	  one #:: loop(one, x)

jamesthompson

find regex: ^(.*)$

where: *.scala, *.java etc etc...

jamesthompson

scala> p
res6: spire.math.poly.MultivariatePolynomial[Double] = (2.0x + 5.0 + 3.0y)

scala> q
res7: spire.math.poly.MultivariatePolynomial[Double] = (xy + 2.0x + 1.0 + 5.0y)

scala> p * q
res8: spire.math.poly.MultivariatePolynomial[Double] = (2.0x^2y + 4.0x^2 + 3.0xy^2 + 21.0xy + 12.0x + 28.0y + 5.0 + 15.0y^2)

scala> p + q