Merge pull request #25 from DurieuxPol/cleanTests

Clean up tests

Author: jordanmontt

src/AI-LinearModels-Tests/AIAbstractLinearModelTest.class.st

@@ -2,38 +2,49 @@ Class {
 	#name : 'AIAbstractLinearModelTest',
 	#superclass : 'TestCase',
 	#instVars : [
-		'model'
+		'model',
+		'fixture'
 	],
 	#category : 'AI-LinearModels-Tests',
 	#package : 'AI-LinearModels-Tests'
 }
 
 { #category : 'testing' }
-AIAbstractLinearModelTest class >> isAbstract [ 
-^self == AIAbstractLinearModelTest 
+AIAbstractLinearModelTest class >> isAbstract [
+
+	^ self == AIAbstractLinearModelTest
+]
+
+{ #category : 'testing' }
+AIAbstractLinearModelTest class >> shouldInheritSelectors [
+
+	^ true
 ]
 
 { #category : 'running' }
-AIAbstractLinearModelTest >> regression [
+AIAbstractLinearModelTest >> fixtureInput [
 
-	^ self subclassResponsibility
+	^ fixture inputMatrix
 ]
 
 { #category : 'running' }
-AIAbstractLinearModelTest >> setUp [
+AIAbstractLinearModelTest >> fixtureOutput [
 
-	super setUp.
-	model := self regression
+	^ fixture outputVector
 ]
 
-{ #category : 'tests' }
-AIAbstractLinearModelTest >> testDivergingException [
+{ #category : 'running' }
+AIAbstractLinearModelTest >> regression [
+
 	^ self subclassResponsibility
 ]
 
-{ #category : 'tests' }
-AIAbstractLinearModelTest >> testExactFitSingleVariable [
-	^ self subclassResponsibility
+{ #category : 'running' }
+AIAbstractLinearModelTest >> setUp [
+
+	super setUp.
+	model := self regression.
+	fixture := AILinearRegressionFixture new
 ]
 
 { #category : 'tests' }
@@ -46,22 +57,6 @@ AIAbstractLinearModelTest >> testInconsistentFitOnDimension [
 	self should: [ model fitX: input y: output ] raise: Error
 ]
 
-{ #category : 'tests' }
-AIAbstractLinearModelTest >> testInitializeWeightsToZeroOfSize [
-
-	| expectedInitWeigths |
-	expectedInitWeigths := #(0 0 0).
-	model initializeWeightsToZeroOfSize: 3.
-	
-	self assert: model weights equals: expectedInitWeigths   
-]
-
-{ #category : 'tests' }
-AIAbstractLinearModelTest >> testPerformedIterationsIsInitialized [
-
-	self assert: model performedIterations equals: nil
-]
-
 { #category : 'tests' }
 AIAbstractLinearModelTest >> testPredictionWithNonFittedModel [
 

src/AI-LinearModels-Tests/AILinearRegressionFixture.class.st

@@ -26,15 +26,13 @@ AILinearRegressionFixture >> initialize [
 
 	| function |
 	super initialize.
-	
+
 	bias := 3.
 	inputMatrix := #( #( 2 ) #( 3 ) #( 1 ) #( 5 ) #( 2 ) #( 6 ) ).
 	weights := #( 2 ).
-	
-	function := [ :x | ( weights at: 1) * x + self bias ].
+
+	function := [ :x | weights first * x + self bias ].
 	outputVector := inputMatrix collect: [ :x | function value: x first ]
-	
-	
 ]
 
 { #category : 'accessing' }

src/AI-LinearModels-Tests/AILinearRegressionGradientDescentTest.class.st

@@ -0,0 +1,44 @@
+Class {
+	#name : 'AILinearRegressionGradientDescentTest',
+	#superclass : 'AIAbstractLinearModelTest',
+	#category : 'AI-LinearModels-Tests',
+	#package : 'AI-LinearModels-Tests'
+}
+
+{ #category : 'testing' }
+AILinearRegressionGradientDescentTest class >> isAbstract [
+
+	^ self == AILinearRegressionGradientDescentTest
+]
+
+{ #category : 'tests' }
+AILinearRegressionGradientDescentTest >> testDivergingException [
+
+	"Training the model with non-sense, completely unproportioned data and with a very high learning rate to raise the diverging exception."
+
+	|input output |
+
+	input := #( #( 13421525235235235235 ) #( 3 ) #( 0.1 ) #( 0.000005 ) #( 241241241124124124 ) #( 6412412412414 ) #(45345) #(5) #(53) #(5) #(3) #(1) #(2) #(1) #(0.09) #(0.4) #(0.0009) #(5) #(234242342423423) #(0.9888) #(0.0000009) ).
+	
+	output := (1 to: input size) collect: [ :e | 0 ].
+
+	model learningRate: 100.
+
+	self should: [model fitX: input y: output] raise: ModelStartingToDivergeException
+]
+
+{ #category : 'tests' }
+AILinearRegressionGradientDescentTest >> testInitializeWeightsToZeroOfSize [
+
+	| expectedInitWeigths |
+	expectedInitWeigths := #(0 0 0).
+	model initializeWeightsToZeroOfSize: 3.
+	
+	self assert: model weights equals: expectedInitWeigths   
+]
+
+{ #category : 'tests' }
+AILinearRegressionGradientDescentTest >> testPerformedIterationsIsInitialized [
+
+	self assert: model performedIterations equals: nil
+]

src/AI-LinearModels-Tests/AILinearRegressionLeastSquaresTest.class.st

@@ -1,42 +1,50 @@
 Class {
 	#name : 'AILinearRegressionLeastSquaresTest',
-	#superclass : 'AILinearRegressionTest',
+	#superclass : 'AIAbstractLinearModelTest',
 	#category : 'AI-LinearModels-Tests',
 	#package : 'AI-LinearModels-Tests'
 }
 
 { #category : 'running' }
-AILinearRegressionLeastSquaresTest >> regression [
+AILinearRegressionLeastSquaresTest >> fixtureInput [
 
-	^ AILinearRegressionLeastSquares new
+	^ self inputType rows: fixture inputMatrix 
 ]
 
-{ #category : 'tests' }
-AILinearRegressionLeastSquaresTest >> testInitializeWeightsToZeroOfSize [
+{ #category : 'running' }
+AILinearRegressionLeastSquaresTest >> inputType [
 
-	self skip
+	^ AIColumnMajorMatrix 
 ]
 
-{ #category : 'tests' }
-AILinearRegressionLeastSquaresTest >> testLearningRateIsInitialized [
+{ #category : 'running' }
+AILinearRegressionLeastSquaresTest >> regression [
 
-	self skip
+	^ AILinearRegressionLeastSquares new
 ]
 
 { #category : 'tests' }
-AILinearRegressionLeastSquaresTest >> testMaxIterationsIsInitialized [
+AILinearRegressionLeastSquaresTest >> testExactFitSingleVariable [
 
-	self skip
-]
+	| newInput expectedOutput actualOutput |
+	newInput := #( #( 4 ) #( 1 ) #( 7 ) #( 0 ) ).
+	expectedOutput := #( 11 5 17 3 ).
 
-{ #category : 'tests' }
-AILinearRegressionLeastSquaresTest >> testPerformedIterationsIsInitialized [
+	model fitX: self fixtureInput y: self fixtureOutput.
+	actualOutput := model predict: newInput.
 
-	self skip
+	actualOutput with: expectedOutput do: [ :actual :expected | self assert: actual closeTo: expected precision: 0.001 ]
 ]
 
 { #category : 'tests' }
-AILinearRegressionLeastSquaresTest >> testWeightDerivativeforXCostDerivative [
+AILinearRegressionLeastSquaresTest >> testPredictionWithNonFittedModel [
+
+	| input |
+	input := AIColumnMajorMatrix rows: #(
+		(1 2 3)
+   		(2 3 4)
+		(3 4 5)
+	).
 
-	self skip
+	self assert: (model predict: input) equals: Array new
 ]

src/AI-LinearModels-Tests/AILinearRegressionLeastSquaresVanillaTest.class.st

@@ -5,26 +5,39 @@ Class {
 	#package : 'AI-LinearModels-Tests'
 }
 
+{ #category : 'running' }
+AILinearRegressionLeastSquaresVanillaTest >> inputType [
+
+	^ PMMatrix
+]
+
 { #category : 'running' }
 AILinearRegressionLeastSquaresVanillaTest >> regression [
 
 	^ AILinearRegressionLeastSquaresVanilla new
 ]
 
 { #category : 'tests' }
-AILinearRegressionLeastSquaresVanillaTest >> testBiasDerivative [
+AILinearRegressionLeastSquaresVanillaTest >> testExactFitDoubleVariable [
+	"| newInput expectedOutput actualOutput initialInput initialOutput |
+	initialInput := #( #( 2 4 ) #( 3 2 ) #( 1 2 ) #( 5 1 ) #( 2 6 ) #( 6 3 ) ).
+	initialOutput := initialInput collect: [ :x | 2 + (x first * 3) + x second ].
+	newInput := #( #( 4 3 ) #( 1 2 ) #( 7 3 ) #( 0 4 ) ).
+	expectedOutput := #( 17 7 26 6 ).
 
-	self skip
-]
+	model fitX: (PMMatrix rows: initialInput) y: initialOutput asPMVector.
+	actualOutput := model predict: newInput.
 
-{ #category : 'tests' }
-AILinearRegressionLeastSquaresVanillaTest >> testCostDerivativeActual [
+	""initialInput collect: [ :x | model bias + (x first * model weights first) + (x second * model weights second) ].""
+	
+	actualOutput with: expectedOutput do: [ :actual :expected | self assert: actual closeTo: expected precision: 0.001 ]"
+	"should work but doesn't give the correct answer, vanilla needs to be fixes"
 
 	self skip
 ]
 
 { #category : 'tests' }
-AILinearRegressionLeastSquaresVanillaTest >> testWeightedSumOf [
+AILinearRegressionLeastSquaresVanillaTest >> testExactFitSingleVariable [
 
 	self skip
 ]

src/AI-LinearModels-Tests/AILinearRegressionTest.class.st

@@ -1,9 +1,6 @@
 Class {
 	#name : 'AILinearRegressionTest',
-	#superclass : 'AIAbstractLinearModelTest',
-	#instVars : [
-		'fixture'
-	],
+	#superclass : 'AILinearRegressionGradientDescentTest',
 	#category : 'AI-LinearModels-Tests',
 	#package : 'AI-LinearModels-Tests'
 }
@@ -17,21 +14,10 @@ AILinearRegressionTest >> regression [
 		yourself
 ]
 
-{ #category : 'running' }
-AILinearRegressionTest >> setUp [
-
-	super setUp.
-
-	fixture := AILinearRegressionFixture new.
-	
-]
-
 { #category : 'tests' }
 AILinearRegressionTest >> testBiasAlmostEqual [
 
-	model
-		fitX: fixture inputMatrix
-		y: fixture outputVector.
+	model fitX: self fixtureInput y: self fixtureOutput.
 
 	self assert: model bias closeTo: fixture bias precision: 0.001
 ]
@@ -56,31 +42,16 @@ AILinearRegressionTest >> testCostDerivativeActual [
 		equals: #(1 2 3)
 ]
 
-{ #category : 'tests' }
-AILinearRegressionTest >> testDivergingException [
-
-	"Training the model with non-sense, completely unproportioned data and with a very high learning rate to raise the diverging exception."
-
-	|input output |
-
-	input := #( #( 13421525235235235235 ) #( 3 ) #( 0.1 ) #( 0.000005 ) #( 241241241124124124 ) #( 6412412412414 ) #(45345) #(5) #(53) #(5) #(3) #(1) #(2) #(1) #(0.09) #(0.4) #(0.0009) #(5) #(234242342423423) #(0.9888) #(0.0000009) ).
-	
-	output := #( 4 234 523 523 5 63456346346346 636463 63463 0.253 0.84234 0.00042 243 4 2 2 5 2 5235235 0.0005 3 3 ).
-
-	model learningRate: 100.
-
-	self should: [model fitX: input y: output] raise: ModelStartingToDivergeException
-]
-
 { #category : 'tests' }
 AILinearRegressionTest >> testExactFitSingleVariable [
 
 	| newInput expectedOutput actualOutput |
 	newInput := #( #( 4 ) #( 1 ) #( 7 ) #( 0 ) ).
 	expectedOutput := #( 11 5 17 3 ).
 
-	model fitX: fixture inputMatrix y: fixture outputVector.
+	model fitX: self fixtureInput y: self fixtureOutput.
 	actualOutput := model predict: newInput.
+
 	actualOutput with: expectedOutput do: [ :actual :expected | self assert: actual closeTo: expected precision: 0.001 ]
 ]
 
@@ -95,9 +66,7 @@ AILinearRegressionTest >> testWeightDerivativeforXCostDerivative [
 { #category : 'tests' }
 AILinearRegressionTest >> testWeightsAlmostEqual [
 
-	model
-		fitX: fixture inputMatrix
-		y: fixture outputVector.
+	model fitX: self fixtureInput y: self fixtureOutput.
 
 	fixture weights with: model weights do: [ :expected :actual |
 		self assert: actual closeTo: expected precision: 0.0001 ]