Replace more usage of defaultNumericalPrecision

Author: jecisc

src/Math-Distributions/PMIncompleteBetaFunction.class.st

@@ -26,7 +26,7 @@ PMIncompleteBetaFunction >> evaluateFraction: aNumber [
 		fraction setParameter: alpha1 second: alpha2 ].
 	fraction setArgument: aNumber.
 	^ (PMContinuedFraction server: fraction)
-		  desiredPrecision: PMFloatingPointMachine new defaultNumericalPrecision;
+		  desiredPrecision: Float defaultComparisonPrecision;
 		  evaluate
 ]
 
@@ -38,7 +38,7 @@ PMIncompleteBetaFunction >> evaluateInverseFraction: aNumber [
 		inverseFraction setParameter: alpha2 second: alpha1 ].
 	inverseFraction setArgument: 1 - aNumber.
 	^ (PMContinuedFraction server: inverseFraction)
-		  desiredPrecision: PMFloatingPointMachine new defaultNumericalPrecision;
+		  desiredPrecision: Float defaultComparisonPrecision;
 		  evaluate
 ]
 

src/Math-Distributions/PMIncompleteGammaFunction.class.st

@@ -24,7 +24,7 @@ PMIncompleteGammaFunction >> evaluateFraction: aNumber [
 		fraction setParameter: alpha ].
 	fraction setArgument: aNumber.
 	^ (PMContinuedFraction server: fraction)
-		  desiredPrecision: PMFloatingPointMachine new defaultNumericalPrecision;
+		  desiredPrecision: Float defaultComparisonPrecision;
 		  evaluate
 ]
 
@@ -36,7 +36,7 @@ PMIncompleteGammaFunction >> evaluateSeries: aNumber [
 		series setParameter: alpha ].
 	series setArgument: aNumber.
 	^ (PMInfiniteSeries server: series)
-		  desiredPrecision: PMFloatingPointMachine new defaultNumericalPrecision;
+		  desiredPrecision: Float defaultComparisonPrecision;
 		  evaluate
 ]
 

src/Math-Tests-Distributions/PMStatisticsBugs.class.st

@@ -180,10 +180,10 @@ PMStatisticsBugs >> testGammaDistribution [
 
 	| dist a |
 	dist := PMGammaDistribution shape: 3.4 scale: 1.7.
-	self assert: (dist average - (3.4 * 1.7)) abs < 0.000000001.
-	self assert: (dist standardDeviation - (3.4 sqrt * 1.7)) abs < 0.000000001.
-	self assert: ((dist value: 4.5) - 0.1446067652) abs < 0.000000001.
-	self assert: ((dist distributionValue: 4.5) - 0.3982869736) abs < 0.000000001.
+	self assert: dist average - (3.4 * 1.7) closeTo: 0.
+	self assert: dist standardDeviation - (3.4 sqrt * 1.7) closeTo: 0.
+	self assert: (dist value: 4.5) - 0.1446067652 closeTo: 0.
+	self assert: (dist distributionValue: 4.5) - 0.3982869736 closeTo: 0.
 
 
 	a := PMGammaDistribution shape: 2 scale: 1.

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

@@ -102,20 +102,18 @@ PMNumericalMethodsTestCase >> testErrorFunction [
 
 { #category : #estimation }
 PMNumericalMethodsTestCase >> testFTest [
+
 	| accC accMM confidenceLevel |
 	accC := PMStatisticalMoments new.
-	#(5.56 5.89 4.66 5.69 5.34 4.79 4.80 7.86 3.64 5.70)
-		do: [ :x | accC accumulate: x ].
+	#( 5.56 5.89 4.66 5.69 5.34 4.79 4.80 7.86 3.64 5.70 ) do: [ :x | accC accumulate: x ].
 	accMM := PMStatisticalMoments new.
-	#(7.48 6.75 3.77 5.71 7.25 4.73 6.23 5.60 5.94 4.58)
-		do: [ :x | accMM accumulate: x ].
+	#( 7.48 6.75 3.77 5.71 7.25 4.73 6.23 5.60 5.94 4.58 ) do: [ :x | accMM accumulate: x ].
 	confidenceLevel := accC fConfidenceLevel: accMM.
-	self assert: (accC average - 5.393) abs < 0.000000001.
-	self
-		assert: (accC standardDeviation - 1.0990809292) abs < 0.000000001.
-	self assert: (accMM average - 5.804) abs < 0.000000001.
-	self assert: (accMM standardDeviation - 1.19415428) abs < 0.000000001.
-	self assert: (confidenceLevel - 79.8147614536) abs < 0.000000001
+	self assert: accC average - 5.393 closeTo: 0.
+	self assert: accC standardDeviation - 1.0990809292 closeTo: 0.
+	self assert: accMM average - 5.804 closeTo: 0.
+	self assert: accMM standardDeviation - 1.19415428 closeTo: 0.
+	self assert: confidenceLevel - 79.8147614536 closeTo: 0
 ]
 
 { #category : #statistics }
@@ -155,10 +153,8 @@ PMNumericalMethodsTestCase >> testIncompleteBetaFunction [
 
 { #category : #'iterative algorithms' }
 PMNumericalMethodsTestCase >> testIncompleteGammaFunction [
-	| function |
-	function := PMIncompleteGammaFunction shape: 2.
-	self
-		assert: ((function value: 2) - 0.59399414981) abs < 0.00000000001
+
+	self assert: ((PMIncompleteGammaFunction shape: 2) value: 2) - 0.59399414981 closeTo: 0
 ]
 
 { #category : #'iterative algorithms' }
@@ -819,7 +815,7 @@ PMNumericalMethodsTestCase >> testOptimizeOneDimension [
 	finder := PMOneVariableFunctionOptimizer maximizingFunction: distr.
 	finder desiredPrecision: 1.0e-6.
 	maximum := finder evaluate.
-	self assert: (maximum - 5) abs < 1.0e-6.
+	self assert: maximum - 5 closeTo: 0.
 	self assert: finder precision < 1.0e-6
 ]
 
@@ -950,20 +946,18 @@ PMNumericalMethodsTestCase >> testSymmetricMatrixAdd3 [
 
 { #category : #estimation }
 PMNumericalMethodsTestCase >> testTTest [
+
 	| accC accMM confidenceLevel |
 	accC := PMStatisticalMoments new.
-	#(5.56 5.89 4.66 5.69 5.34 4.79 4.80 7.86 3.64 5.70)
-		do: [ :x | accC accumulate: x ].
+	#( 5.56 5.89 4.66 5.69 5.34 4.79 4.80 7.86 3.64 5.70 ) do: [ :x | accC accumulate: x ].
 	accMM := PMStatisticalMoments new.
-	#(7.48 6.75 3.77 5.71 7.25 4.73 6.23 5.60 5.94 4.58)
-		do: [ :x | accMM accumulate: x ].
+	#( 7.48 6.75 3.77 5.71 7.25 4.73 6.23 5.60 5.94 4.58 ) do: [ :x | accMM accumulate: x ].
 	confidenceLevel := accC tConfidenceLevel: accMM.
-	self assert: (accC average - 5.393) abs < 0.000000001.
-	self
-		assert: (accC standardDeviation - 1.0990809292) abs < 0.000000001.
-	self assert: (accMM average - 5.804) abs < 0.000000001.
-	self assert: (accMM standardDeviation - 1.19415428) abs < 0.000000001.
-	self assert: (confidenceLevel - 56.6320739989) abs < 0.000000001
+	self assert: accC average - 5.393 closeTo: 0.
+	self assert: accC standardDeviation - 1.0990809292 closeTo: 0.
+	self assert: accMM average - 5.804 closeTo: 0.
+	self assert: accMM standardDeviation - 1.19415428 closeTo: 0.
+	self assert: confidenceLevel - 56.6320739989 closeTo: 0
 ]
 
 { #category : #'linear algebra' }