__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

@staticmethod
get_grid_slices(grid, stencil): 

• grid: Any

• stencil: Any

• :returns: _

@staticmethod
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

@classmethod
finite_difference_data(cls, grid, order, stencil, end_point_precision): 

Constructs a finite-difference function that computes the nth derivative with a given width

• deriv: Any

• accuracy: Any

• :returns: _