New ScreenPanel

script/lscov.py

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+import org.apache.commons.math3.geometry.euclidean.twod.Vector2D as Vector2D
+import org.apache.commons.math3.linear.ArrayRealVector as ArrayRealVector
+import org.apache.commons.math3.linear.Array2DRowRealMatrix as Array2DRowRealMatrix
+import org.apache.commons.math3.linear.MatrixUtils as MatrixUtils
+import org.apache.commons.math3.util.Pair as Pair
+import org.apache.commons.math3.optimization.general.LevenbergMarquardtOptimizer as LevenbergMarquardtOptimizer
+import org.apache.commons.math3.fitting.leastsquares.MultivariateJacobianFunction as MultivariateJacobianFunction
+import org.apache.commons.math3.fitting.leastsquares.LeastSquaresBuilder as LeastSquaresBuilder
+import org.apache.commons.math3.fitting.leastsquares.LevenbergMarquardtOptimizer as LevenbergMarquardtOptimizer
+
+
+
+x = [12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0]
+y = [30.0, 21.0, 17.0, 15.0, 16.0, 19.0, 22.0, 33.0]
+v = [0.25, 0.5,  0.75, 0.33, 0.7.  0.35, 0.22, 0.35]
+
+num_samples = len(x)
+w = [1.0/i for i in v]
+
+W = MatrixUtils.createRealDiagonalMatrix(w)
+
+
+
+
+initial = [1.0, 1.0, 1.0]    #a, b, c
+
+
+class Model(MultivariateJacobianFunction):
+    def value(self, variables):
+        value = ArrayRealVector(num_samples)
+        jacobian = Array2DRowRealMatrix(num_samples, 3)        
+        for i in range(num_samples):
+            (a,b,c) = (variables.getEntry(0), variables.getEntry(1), variables.getEntry(2))   
+            model = a*x[i]*x[i] + b*x[i] + c
+            value.setEntry(i, model)  
+                      
+            # derivative with respect to a
+            jacobian.setEntry(i, 0,  x[i]*x[i])
+            # derivative with respect to b
+            jacobian.setEntry(i, 1,  x[i])
+            # derivative with respect to c
+            jacobian.setEntry(i, 2,  1.0)            
+        
+        return Pair(value, jacobian)
+
+
+model = Model()
+
+# the target is to have all points at the specified radius from the center
+target = [v for v in y]
+
+problem = LeastSquaresBuilder().start(initial).model(model).target(target).lazyEvaluation(False).maxEvaluations(1000).maxIterations(1000).weight(W).build()
+
+optimizer = LevenbergMarquardtOptimizer()
+optimum = optimizer.optimize(problem)
+optimalValues = optimum.getPoint()
+a,b,c = optimum.getPoint().getEntry(0), optimum.getPoint().getEntry(1), optimum.getPoint().getEntry(2)
+
+print "A: ",  a 
+print "B: ",  b
+print "C: ",  c
+print ""
+print "RMS: "          , optimum.getRMS()
+print "evaluations: "  , optimum.getEvaluations()
+print "iterations: "   , optimum.getIterations()
+