interpolate_1d#
- metpy.interpolate.interpolate_1d(x, xp, *args, axis=0, fill_value=nan, return_list_always=False)#
Interpolates data with any shape over a specified axis.
Interpolation over a specified axis for arrays of any shape.
- Parameters
x (array-like) – 1-D array of desired interpolated values.
xp (array-like) – The x-coordinates of the data points.
args (array-like) – The data to be interpolated. Can be multiple arguments, all must be the same shape as xp.
axis (int, optional) – The axis to interpolate over. Defaults to 0.
fill_value (float, optional) – Specify handling of interpolation points out of data bounds. If None, will return ValueError if points are out of bounds. Defaults to nan.
return_list_always (bool, optional) – Whether to always return a list of interpolated arrays, even when only a single array is passed to args. Defaults to
False.
- Returns
array-like – Interpolated values for each point with coordinates sorted in ascending order.
Examples
>>> import metpy.interpolate >>> x = np.array([1., 2., 3., 4.]) >>> y = np.array([1., 2., 3., 4.]) >>> x_interp = np.array([2.5, 3.5]) >>> metpy.interpolate.interpolate_1d(x_interp, x, y) array([2.5, 3.5])
Notes
xp and args must be the same shape.