Class MultivariateRegularGrid
- java.lang.Object
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- dev.nm.analysis.curvefit.interpolation.multivariate.MultivariateRegularGrid
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- All Implemented Interfaces:
MultivariateGrid
public class MultivariateRegularGrid extends Object implements MultivariateGrid
A regular grid is a tessellation of n-dimensional Euclidean space by congruent parallelotopes (e.g. bricks), meaning that grid points are equally-spaced. This is a special case of rectilinear grid. This implementation is backed by aMultivariateArrayGrid
.- See Also:
- Wikipedia: Regular grid
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
MultivariateRegularGrid.EquallySpacedVariable
Specify the positioning and spacing along one dimension.
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Constructor Summary
Constructors Constructor Description MultivariateRegularGrid(MultiDimensionalCollection<Double> y, MultivariateRegularGrid.EquallySpacedVariable... x)
Create a new instance where the dependent variable is specified by aMultiDimensionalCollection
and the independent variables form the specified grid.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description double
deltaX(int i)
Get the distance between two adjacent points along the axis with the given index.int
dimension()
Get the total number of dimensions of the grid.int
size(int i)
Get the size of the grid in the given dimension xi.double[]
x(int i)
Get all the values of the independent variable xi as an array.double
x(int i, int j)
Get the value of the independent variable xi at the given index.double
x0(int i)
Get the value of \(\mathbf{x_i}_0\), the first value of the independent variable \(x_i\).double
y(int... indices)
Get the value of the dependent variable y at the given indices in the grid.
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Constructor Detail
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MultivariateRegularGrid
public MultivariateRegularGrid(MultiDimensionalCollection<Double> y, MultivariateRegularGrid.EquallySpacedVariable... x)
Create a new instance where the dependent variable is specified by aMultiDimensionalCollection
and the independent variables form the specified grid.- Parameters:
y
- the values of the dependent variablex
- each element specifies the independent variables along one dimension
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Method Detail
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y
public double y(int... indices)
Description copied from interface:MultivariateGrid
Get the value of the dependent variable y at the given indices in the grid.- Specified by:
y
in interfaceMultivariateGrid
- Parameters:
indices
- the indices of the independent variables in the grid- Returns:
- \(y(\mathbf{x})\), the value of the dependent variable at \(\mathbf{x}\)
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x
public double x(int i, int j)
Description copied from interface:MultivariateGrid
Get the value of the independent variable xi at the given index.- Specified by:
x
in interfaceMultivariateGrid
- Parameters:
i
- the dimension index of the independent variable xij
- the index of the value in the specified dimension xi- Returns:
- \(x_i_j\)
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x
public double[] x(int i)
Description copied from interface:MultivariateGrid
Get all the values of the independent variable xi as an array.- Specified by:
x
in interfaceMultivariateGrid
- Parameters:
i
- the dimension index of the independent variable xi- Returns:
- \(x_i\)'s
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size
public int size(int i)
Description copied from interface:MultivariateGrid
Get the size of the grid in the given dimension xi.- Specified by:
size
in interfaceMultivariateGrid
- Parameters:
i
- the dimension index of the independent variable xi- Returns:
- the size of the dimension
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dimension
public int dimension()
Description copied from interface:MultivariateGrid
Get the total number of dimensions of the grid.- Specified by:
dimension
in interfaceMultivariateGrid
- Returns:
- the number of dimensions
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x0
public double x0(int i)
Get the value of \(\mathbf{x_i}_0\), the first value of the independent variable \(x_i\). The value of \(x_i_j\) can be computed as \(x_i_0 + (j\times\delta_{x_i})\).- Parameters:
i
- the dimension index of the independent variable xi- Returns:
- \(x_i_0\)
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deltaX
public double deltaX(int i)
Get the distance between two adjacent points along the axis with the given index.- Parameters:
i
- the dimension index of the independent variable xi- Returns:
- \(\delta_{x_i}\)
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