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 coordinates.
- 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.
