FiniteDifferenceDerivative

Provides derivatives for a function (scalar or vector valued). Can be indexed into or the entire tensor of derivatives may be requested. The potential for optimization undoubtedly exists, but the idea is to provide as simple an interface as possible. Robustification needs to be done, but is currently used in CoordinateSystem.jacobian to good effect.

__init__(self, f, function_shape=(0, 0), parallelizer=None, logger=None, **fd_opts): 

__call__(self, *args, **opts): 

derivatives(self, center, displacement_function=None, prep=None, lazy=None, mesh_spacing=None, **fd_opts): 

Examples

FiniteDifferenceDerivative

Provides derivatives for a function (scalar or vector valued). Can be indexed into or the entire tensor of derivatives may be requested. The potential for optimization undoubtedly exists, but the idea is to provide as simple an interface as possible. Robustification needs to be done, but is currently used in CoordinateSystem.jacobian to good effect.

Properties and Methods

__init__(self, f, function_shape=(0, 0), **fd_opts): 

• f: FunctionSpec | callable

  the function we would like to take derivatives of

• function_shape: Iterable[Iterable[int] | int] | None

  the shape of the function we’d like to take the derivatives of

• fd_opts: Any

  the options to pass to the finite difference function

__call__(self, *args, **opts): 

derivatives(self, center, displacement_function=None, prep=None, lazy=None, mesh_spacing=None, **fd_opts): 

Generates a differencer object that can be used to get derivs however your little heart desires

• center: np.ndarray

  the center point around which to generate differences

• displacement_function: Any

  No description…

• mesh_spacing: Any

  No description…

• prep: Any

  No description…

• fd_opts: Any

  No description…

• :returns: _

  No description…

Examples

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