66 lines
2.0 KiB
Markdown
66 lines
2.0 KiB
Markdown
# orx-math
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Mathematical utilities
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<!-- __demos__ -->
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## Demos
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### linearrange/DemoLinearRange02
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[source code](src/jvmDemo/kotlin/linearrange/DemoLinearRange02.kt)
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### linearrange/DemoLinearRange03
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[source code](src/jvmDemo/kotlin/linearrange/DemoLinearRange03.kt)
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### matrix/DemoLeastSquares01
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Demonstrate least squares method to find a regression line through noisy points
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Line drawn in red is the estimated line, in green is the ground-truth line
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Ax = b => x = A⁻¹b
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because A is likely inconsistent, we look for an approximate x based on AᵀA, which is consistent.
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x̂ = (AᵀA)⁻¹ Aᵀb
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[source code](src/jvmDemo/kotlin/matrix/DemoLeastSquares01.kt)
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### matrix/DemoLeastSquares02
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Demonstrate least squares method to fit a cubic bezier to noisy points
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[source code](src/jvmDemo/kotlin/matrix/DemoLeastSquares02.kt)
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### rbf/RbfInterpolation01
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[source code](src/jvmDemo/kotlin/rbf/RbfInterpolation01.kt)
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### rbf/RbfInterpolation02
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[source code](src/jvmDemo/kotlin/rbf/RbfInterpolation02.kt)
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### simplexrange/DemoSimplexRange3D01
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[source code](src/jvmDemo/kotlin/simplexrange/DemoSimplexRange3D01.kt)
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