import scipy.interpolate as si
[docs]def splinterp(x2, x, y):
"""This function implements the methods splrep and splev of the
module scipy.interpolate
Parameters
----------
x2 : 1D array_like
array of points at which to return the value of the
smoothed spline or its derivatives
x : array_like
The x data points defining a curve y = f(x).
y : array_like
The y data points defining a curve y = f(x).
Returns
-------
array_like
An array of values representing the spline function or curve.
If tck was returned from splrep, then this is a list of arrays
representing the curve in N-dimensional space.
Examples
--------
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> x = np.arange(21)/20.0 * 2.0 * np.pi
>>> y = np.sin(x)
>>> x2 = np.arange(41)/40.0 *2.0 * np.pi
>>> y2 = splinterp(x2, x, y)
>>> plt.plot(x2,y2)
"""
tck = si.splrep(x, y)
y2 = si.splev(x2, tck)
return y2