IrregularGridFiniteDifference

Defines a finite difference over an irregular grid

Properties and Methods

finite_difference_data: method

 

__init__(self, grid, order, stencil=None, accuracy=2, end_point_accuracy=2, **kw): 
  • grid: np.ndarray

    the grid to get the weights from

  • order: int

    the order of the derivative to take

  • stencil: int | None

    the number of stencil points to add

  • accuracy: int | None

    the approximate accuracy to target with the method

  • end_point_accuracy: int | None

    the extra number of stencil points to add to the end points

  • kw: Any

    options passed through to the FiniteDifferenceMatrix

 

get_grid_slices(grid, stencil): 
  • grid: Any

    No description…

  • stencil: Any

    No description…

  • :returns: _

    No description…

 

get_weights(m, z, x): 

Extracts the grid weights for an unevenly spaced grid based off of the algorithm outlined by Fronberger in https://pdfs.semanticscholar.org/8bf5/912bde884f6bd4cfb4991ba3d077cace94c0.pdf

  • m: Any

    highest derivative order

  • z: Any

    center of the derivatives

  • X: Any

    grid of points

Examples

IrregularGridFiniteDifference

Defines a finite difference over an irregular grid

Properties and Methods

finite_difference_data: method

 

__init__(self, grid, order, stencil=None, accuracy=2, end_point_accuracy=2, **kw): 
  • grid: np.ndarray

    the grid to get the weights from

  • order: int

    the order of the derivative to take

  • stencil: int | None

    the number of stencil points to add

  • accuracy: int | None

    the approximate accuracy to target with the method

  • end_point_accuracy: int | None

    the extra number of stencil points to add to the end points

  • kw: Any

    options passed through to the FiniteDifferenceMatrix

 

get_grid_slices(grid, stencil): 
  • grid: Any

    No description…

  • stencil: Any

    No description…

  • :returns: _

    No description…

 

get_weights(m, z, x): 

Extracts the grid weights for an unevenly spaced grid based off of the algorithm outlined by Fronberger in https://pdfs.semanticscholar.org/8bf5/912bde884f6bd4cfb4991ba3d077cace94c0.pdf

  • m: Any

    highest derivative order

  • z: Any

    center of the derivatives

  • X: Any

    grid of points

Examples


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