ConvergenceException on SimpleCurveFitter in Scala










1














I'm trying to fit a curve with SimpleCurveFitter of commons.math3.fitting in Scala but I catch an exception :



org.apache.commons.math3.exception.ConvergenceException : Unable to permorm 
Qr decomposition on jacobian


However, I have checked my gradient calculations.... I still don't see why the exception is raised.
See the code by yourself



 def main(args: Array[String]): Unit = 
var xv: DenseVector[Double] = linspace(0, 3, 300)
var yv: DenseVector[Double] = DenseVector.zeros(300)


for (i <- xv.findAll(x => x < 1.0)) yv.update(i, 1)
for (i <- xv.findAll(x => x >= 1.0)) yv.update(i, exp(-(xv(i) - 1.0)/1))

val wop: Array[WeightedObservedPoint] = new Array[WeightedObservedPoint](xv.length)

for (i <- 0 to xv.length - 1) wop.update(i, new WeightedObservedPoint(1, xv(i), yv(i)))

val f: ParametricUnivariateFunction = new ParametricUnivariateFunction
override def value(x: Double, parameters: Double*): Double =
val a = parameters(0)
val b = parameters(1)

1.0 / (1.0 + a * pow(x, 2 * b))


override def gradient(x: Double, parameters: Double*): Array[Double] =
val a = parameters(0)
val b = parameters(1)
val ga = - pow(x, 2 * b) / pow(1 + a * pow(x, 2 * b), 2)
val gb = - (2 * a * pow(x, 2 * b) * log(x)) / pow(1 + a * pow(x, 2 * b), 2)
val grad = Array(ga, gb)
grad



val wopc = JavaConverters.asJavaCollection(wop)
val cf = SimpleCurveFitter.create(f, Array(1, 1))
val param = cf.fit(wopc)
println(param(0), param(1))



Thank you for your help :)










share|improve this question




























    1














    I'm trying to fit a curve with SimpleCurveFitter of commons.math3.fitting in Scala but I catch an exception :



    org.apache.commons.math3.exception.ConvergenceException : Unable to permorm 
    Qr decomposition on jacobian


    However, I have checked my gradient calculations.... I still don't see why the exception is raised.
    See the code by yourself



     def main(args: Array[String]): Unit = 
    var xv: DenseVector[Double] = linspace(0, 3, 300)
    var yv: DenseVector[Double] = DenseVector.zeros(300)


    for (i <- xv.findAll(x => x < 1.0)) yv.update(i, 1)
    for (i <- xv.findAll(x => x >= 1.0)) yv.update(i, exp(-(xv(i) - 1.0)/1))

    val wop: Array[WeightedObservedPoint] = new Array[WeightedObservedPoint](xv.length)

    for (i <- 0 to xv.length - 1) wop.update(i, new WeightedObservedPoint(1, xv(i), yv(i)))

    val f: ParametricUnivariateFunction = new ParametricUnivariateFunction
    override def value(x: Double, parameters: Double*): Double =
    val a = parameters(0)
    val b = parameters(1)

    1.0 / (1.0 + a * pow(x, 2 * b))


    override def gradient(x: Double, parameters: Double*): Array[Double] =
    val a = parameters(0)
    val b = parameters(1)
    val ga = - pow(x, 2 * b) / pow(1 + a * pow(x, 2 * b), 2)
    val gb = - (2 * a * pow(x, 2 * b) * log(x)) / pow(1 + a * pow(x, 2 * b), 2)
    val grad = Array(ga, gb)
    grad



    val wopc = JavaConverters.asJavaCollection(wop)
    val cf = SimpleCurveFitter.create(f, Array(1, 1))
    val param = cf.fit(wopc)
    println(param(0), param(1))



    Thank you for your help :)










    share|improve this question


























      1












      1








      1







      I'm trying to fit a curve with SimpleCurveFitter of commons.math3.fitting in Scala but I catch an exception :



      org.apache.commons.math3.exception.ConvergenceException : Unable to permorm 
      Qr decomposition on jacobian


      However, I have checked my gradient calculations.... I still don't see why the exception is raised.
      See the code by yourself



       def main(args: Array[String]): Unit = 
      var xv: DenseVector[Double] = linspace(0, 3, 300)
      var yv: DenseVector[Double] = DenseVector.zeros(300)


      for (i <- xv.findAll(x => x < 1.0)) yv.update(i, 1)
      for (i <- xv.findAll(x => x >= 1.0)) yv.update(i, exp(-(xv(i) - 1.0)/1))

      val wop: Array[WeightedObservedPoint] = new Array[WeightedObservedPoint](xv.length)

      for (i <- 0 to xv.length - 1) wop.update(i, new WeightedObservedPoint(1, xv(i), yv(i)))

      val f: ParametricUnivariateFunction = new ParametricUnivariateFunction
      override def value(x: Double, parameters: Double*): Double =
      val a = parameters(0)
      val b = parameters(1)

      1.0 / (1.0 + a * pow(x, 2 * b))


      override def gradient(x: Double, parameters: Double*): Array[Double] =
      val a = parameters(0)
      val b = parameters(1)
      val ga = - pow(x, 2 * b) / pow(1 + a * pow(x, 2 * b), 2)
      val gb = - (2 * a * pow(x, 2 * b) * log(x)) / pow(1 + a * pow(x, 2 * b), 2)
      val grad = Array(ga, gb)
      grad



      val wopc = JavaConverters.asJavaCollection(wop)
      val cf = SimpleCurveFitter.create(f, Array(1, 1))
      val param = cf.fit(wopc)
      println(param(0), param(1))



      Thank you for your help :)










      share|improve this question















      I'm trying to fit a curve with SimpleCurveFitter of commons.math3.fitting in Scala but I catch an exception :



      org.apache.commons.math3.exception.ConvergenceException : Unable to permorm 
      Qr decomposition on jacobian


      However, I have checked my gradient calculations.... I still don't see why the exception is raised.
      See the code by yourself



       def main(args: Array[String]): Unit = 
      var xv: DenseVector[Double] = linspace(0, 3, 300)
      var yv: DenseVector[Double] = DenseVector.zeros(300)


      for (i <- xv.findAll(x => x < 1.0)) yv.update(i, 1)
      for (i <- xv.findAll(x => x >= 1.0)) yv.update(i, exp(-(xv(i) - 1.0)/1))

      val wop: Array[WeightedObservedPoint] = new Array[WeightedObservedPoint](xv.length)

      for (i <- 0 to xv.length - 1) wop.update(i, new WeightedObservedPoint(1, xv(i), yv(i)))

      val f: ParametricUnivariateFunction = new ParametricUnivariateFunction
      override def value(x: Double, parameters: Double*): Double =
      val a = parameters(0)
      val b = parameters(1)

      1.0 / (1.0 + a * pow(x, 2 * b))


      override def gradient(x: Double, parameters: Double*): Array[Double] =
      val a = parameters(0)
      val b = parameters(1)
      val ga = - pow(x, 2 * b) / pow(1 + a * pow(x, 2 * b), 2)
      val gb = - (2 * a * pow(x, 2 * b) * log(x)) / pow(1 + a * pow(x, 2 * b), 2)
      val grad = Array(ga, gb)
      grad



      val wopc = JavaConverters.asJavaCollection(wop)
      val cf = SimpleCurveFitter.create(f, Array(1, 1))
      val param = cf.fit(wopc)
      println(param(0), param(1))



      Thank you for your help :)







      scala curve-fitting






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      edited Nov 12 '18 at 14:24







      Adlane LADJAL

















      asked Nov 12 '18 at 5:33









      Adlane LADJALAdlane LADJAL

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