log_interpolate_1d¶
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metpy.interpolate.log_interpolate_1d(x, xp, *args, **kwargs)[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.calc.log_interp(x_interp, x_log, y_log) array([20.03438638, 24.63955657, 29.24472675])
Notes
xp and args must be the same shape.
