log_interpolate_1d

metpy.interpolate.log_interpolate_1d(x, xp, *args, axis=0, fill_value=nan)[source]

Interpolates data with logarithmic x-scale over a specified axis.

Interpolation on a logarithmic x-scale for interpolation values in pressure coordintates.

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.

Returns

array-like – Interpolated values for each point with coordinates sorted in ascending order.

Examples

>>> x_log = np.array([1e3, 1e4, 1e5, 1e6])
>>> y_log = np.log(x_log) * 2 + 3
>>> x_interp = np.array([5e3, 5e4, 5e5])
>>> metpy.interpolate.log_interpolate_1d(x_interp, x_log, y_log)
array([20.03438638, 24.63955657, 29.24472675])

Notes

xp and args must be the same shape.

Examples using metpy.interpolate.log_interpolate_1d

inverse_distance_to_points natural_neighbor_to_grid