xarray.DataArray.differentiate

DataArray.differentiate(coord, edge_order=1, datetime_unit=None)

Differentiate the array with the second order accurate central differences.

Note

This feature is limited to simple cartesian geometry, i.e. coord must be one dimensional.

Parameters:

coord: str

The coordinate to be used to compute the gradient.

edge_order: 1 or 2. Default 1

N-th order accurate differences at the boundaries.

datetime_unit: None or any of {‘Y’, ‘M’, ‘W’, ‘D’, ‘h’, ‘m’, ‘s’, ‘ms’,

‘us’, ‘ns’, ‘ps’, ‘fs’, ‘as’} Unit to compute gradient. Only valid for datetime coordinate.

Returns:

differentiated: DataArray

See also

numpy.gradient

corresponding numpy function

Examples

>>> da = xr.DataArray(np.arange(12).reshape(4, 3), dims=['x', 'y'],
...                   coords={'x': [0, 0.1, 1.1, 1.2]})
>>> da
<xarray.DataArray (x: 4, y: 3)>
array([[ 0,  1,  2],
       [ 3,  4,  5],
       [ 6,  7,  8],
       [ 9, 10, 11]])
Coordinates:
  * x        (x) float64 0.0 0.1 1.1 1.2
Dimensions without coordinates: y
>>>
>>> da.differentiate('x')
<xarray.DataArray (x: 4, y: 3)>
array([[30.      , 30.      , 30.      ],
       [27.545455, 27.545455, 27.545455],
       [27.545455, 27.545455, 27.545455],
       [30.      , 30.      , 30.      ]])
Coordinates:
  * x        (x) float64 0.0 0.1 1.1 1.2
Dimensions without coordinates: y