Derivative

Derivative()

An unevaluated Derivative, which carries metadata (Dimensions, derivative order, etc) describing how the derivative will be expanded upon evaluation.

Parameters

Name	Type	Description	Default
expr	expr - like	Expression for which the Derivative is produced.	required
dims	Dimension or tuple of Dimension	Dimensions w.r.t. which to differentiate.	required
fd_order	int or tuple of int	Coefficient discretization order. Note: this impacts the width of the resulting stencil.	1
deriv_order		Derivative order.	required
side	Side or tuple of Side	Side of the finite difference location, centered (at x), left (at x - 1) or right (at x +1).	centered
transpose	Transpose	Forward (matvec=direct) or transpose (matvec=transpose) mode of the finite difference.	direct
subs	dict	Substitutions to apply to the finite-difference expression after evaluation.	required
x0	dict	Origin (where the finite-difference is evaluated at) for the finite-difference scheme, e.g. {x: x, y: y + h_y/2}.	required

Examples

Creation

>>> from devito import Function, Derivative, Grid
>>> grid = Grid((10, 10))
>>> x, y = grid.dimensions
>>> u = Function(name="u", grid=grid, space_order=2)
>>> Derivative(u, x)
Derivative(u(x, y), x)

This can also be obtained via the differential shortcut

>>> u.dx
Derivative(u(x, y), x)

You can also specify the order as a keyword argument

>>> Derivative(u, x, deriv_order=2)
Derivative(u(x, y), (x, 2))

Or as a tuple

>>> Derivative(u, (x, 2))
Derivative(u(x, y), (x, 2))

Once again, this can be obtained via shortcut notation

>>> u.dx2
Derivative(u(x, y), (x, 2))

Derivative object are also callable to change default setup:

>>> u.dx2(x0=x + x.spacing)
Derivative(u(x, y), (x, 2))

will create the second derivative at x=x + x.spacing. Accepted arguments for dynamic evaluation are x0, fd_order and side.

Attributes

Name	Description
T	Transpose of the Derivative.