p[-1]`.

period : None or float, optional
    A period for the x-coordinates. This parameter allows the proper
    interpolation of angular x-coordinates. Parameters `left` and `right`
    are ignored if `period` is specified.

Returns
-------
y : float or complex (corresponding to fp) or ndarray
    The interpolated values, same shape as `x`.

Raises
------
ValueError
    If `xp` and `fp` have different length
    If `xp` or `fp` are not 1-D sequences
    If `period == 0`

See Also
--------
scipy.interpolate

Warnings
--------
The x-coordinate sequence is expected to be increasing, but this is not
explicitly enforced.  However, if the sequence `xp` is non-increasing,
interpolation results are meaningless.

Note that, since NaN is unsortable, `xp` also cannot contain NaNs.

A simple check for `xp` being strictly increasing is::

    np.all(np.diff(xp) > 0)

Examples
--------
>>> import numpy as np
>>> xp = [1, 2, 3]
>>> fp = [3, 2, 0]
>>> np.interp(2.5, xp, fp)
1.0
>>> np.interp([0, 1, 1.5, 2.72, 3.14], xp, fp)
array([3.  , 3.  , 2.5 , 0.56, 0.  ])
>>> UNDEF = -99.0
>>> np.interp(3.14, xp, fp, right=UNDEF)
-99.0

Plot an interpolant to the sine function:

>>> x = np.linspace(0, 2*np.pi, 10)
>>> y = np.sin(x)
>>> xvals = np.linspace(0, 2*np.pi, 50)
>>> yinterp = np.interp(xvals, x, y)
>>> import matplotlib.pyplot as plt
>>> plt.plot(x, y, 'o')
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.plot(xvals, yinterp, '-x')
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.show()

Interpolation with periodic x-coordinates:

>>> x = [-180, -170, -185, 185, -10, -5, 0, 365]
>>> xp = [190, -190, 350, -350]
>>> fp = [5, 10, 3, 4]
>>> np.interp(x, xp, fp, period=360)
array([7.5 , 5.  , 8.75, 6.25, 3.  , 3.25, 3.5 , 3.75])

Complex interpolation:

>>> x = [1.5, 4.0]
>>> xp = [2,3,5]
>>> fp = [1.0j, 0, 2+3j]
>>> np.interp(x, xp, fp)
array([0.+1.j , 1.+1.5j])

Nr