gradient¶
-
metpy.calc.gradient(f, **kwargs)[source]¶ Calculate the gradient of a grid of values.
Works for both regularly-spaced data, and grids with varying spacing.
Either x or deltas must be specified.
Parameters: - f (array-like) – Array of values of which to calculate the derivative
- x (array-like, optional) – Sequence of arrays containing the coordinate values corresponding to the grid points in f in axis order.
- deltas (array-like, optional) – Sequence of arrays or scalars that specify the spacing between the grid points in f in axis order. There should be one item less than the size of f along axis.
Returns: array-like – The first derivative calculated along each axis in the original array
See also
