First implementation of least squares

Author: jordanmontt

src/Math-Numerical/PMLeastSquares.class.st

@@ -0,0 +1,23 @@
+Class {
+	#name : #PMLeastSquares,
+	#superclass : #Object,
+	#category : #'Math-Numerical'
+}
+
+{ #category : #'as yet unclassified' }
+PMLeastSquares >> solveMatrixA: aPMMatrix vectorB: aPMVector [
+
+	"SVD-based implementation of a minimum-norm solution to the overdetermined least squares problem.
+	minimize || b - Ax ||"
+
+	| svd u s v pseudoinverse |
+	svd := PMSingularValueDecomposition decompose: aPMMatrix.
+
+	u := svd leftSingularMatrix.
+	s := svd diagonalSingularValueMatrix.
+	v := svd rightSingularMatrix.
+
+	pseudoinverse := s inverse.
+
+	^ v * pseudoinverse * u transpose * aPMVector
+]

src/Math-Tests-Numerical/PMLeastSquaresTest.class.st

@@ -0,0 +1,39 @@
+"
+A PMLeastSquaresTest is a test class for testing the behavior of PMLeastSquares
+"
+Class {
+	#name : #PMLeastSquaresTest,
+	#superclass : #TestCase,
+	#instVars : [
+		'matrixA',
+		'vectorB',
+		'expectedSolution'
+	],
+	#category : #'Math-Tests-Numerical'
+}
+
+{ #category : #running }
+PMLeastSquaresTest >> setUp [
+	super setUp.
+	
+	"Put here a common initialization logic for tests"
+	
+	matrixA := PMMatrix rows: #(
+		(0 1.1)
+		(1 0)
+		(0 -0.2)).
+		
+	vectorB := #(1.1 -1.1 -0.2) asPMVector.
+	expectedSolution := #(-1.1 1) asPMVector.
+]
+
+{ #category : #tests }
+PMLeastSquaresTest >> testSolve [
+
+	| leastSquares solution |
+	leastSquares := PMLeastSquares new.
+	
+	solution := leastSquares solveMatrixA: matrixA vectorB: vectorB.
+	
+	self assert: solution closeTo: expectedSolution.
+]