Add new numerical methods to solve linear system: #531
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1. Thomas method (прогонки) 2. Jacobi method (iterative) 3. Seidel method (iterative, improvement version of the Jacobi method)
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Methods should use LinearAlgebra and generalized for non-Float64 types.
Also, please add an example of usage in example module and a short markdown documentation on when those methods should be used.
| * @return vector X - solution of the system 'A*X=B'. | ||
| */ | ||
| @UnstableKMathAPI | ||
| public fun solveSystemByJacobiMethod( |
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Global namespace polution. The method must be made an extension for something. Using Double-only methods is not a KMath way, one should use Field or Ring if one does not need division for that.
| private var cachedMachineEpsilonPrecision: Double? = null | ||
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| @UnstableKMathAPI | ||
| public val machineEpsilonPrecision: Double |
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Global namespace polution. And it should be Algebra attribute.
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| var X: Point<Double> = initialApproximation |
| return X | ||
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| private fun calcNorm(x1: Point<Double>, x2: Point<Double>): Double { |
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The function could be moved inside the only function it is used in
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| norm = calcNorm(X, xTmp) | ||
| X = xTmp | ||
| } while (norm > epsilonPrecision) |
| } | ||
| } | ||
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| val X: MutableStructure1D<Double> = initialApproximation?.let { |
| return X | ||
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| private fun calcNorm(x1: Point<Double>, x2: Point<Double>): Double { |
| * @return vector X - solution of the system 'A*X=B'. | ||
| */ | ||
| @UnstableKMathAPI | ||
| public fun solveSystemByThomasMethod( |
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Global namespace pollution and unnecessary specialization. The same as above.
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| assertEquals(4, result.size) | ||
| val absoluteTolerance = 0.00000000000001 |
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There is a test method for structure equality
| */ | ||
| @Test | ||
| fun exceptionTest1() = | ||
| Double.algebra.linearSpace.run { |
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and unit tests.