def interp(x, xp, fp, left=None, right=None):
if isinstance(x, (float, int, number)):<EOL><INDENT>return compiled_interp([x], xp, fp, left, right).item()<EOL><DEDENT>elif isinstance(x, np.ndarray) and x.ndim == <NUM_LIT:0>:<EOL><INDENT>return compiled_interp([x], xp, fp, left, right).item()<EOL><DEDENT>else:<EOL><INDENT>return compiled_interp(x, xp, fp, left, right)<EOL><DEDENT>
One-dimensional linear interpolation.

Returns the one-dimensional piecewise linear interpolant to a function
with given values at discrete data-points.

Parameters
----------
x : array_like
    The x-coordinates of the interpolated values.

xp : 1-D sequence of floats
    The x-coordinates of the data points, must be increasing.

fp : 1-D sequence of floats
    The y-coordinates of the data points, same length as `xp`.

left : float, optional
    Value to return for `x < xp[0]`, default is `fp[0]`.

right : float, optional
    Value to return for `x > xp[-1]`, default is `fp[-1]`.

Returns
-------
y : {float, ndarray}
    The interpolated values, same shape as `x`.

Raises
------
ValueError
    If `xp` and `fp` have different length

Notes
-----
Does not check that the x-coordinate sequence `xp` is increasing.
If `xp` is not increasing, the results are nonsense.
A simple check for increasing is::

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


Examples
--------
>>> 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()