Line smoothing with Numpy/SciPy

I have a line which should be smoothened by scipy.interpolate.splrep and scipy.interpolate.splev.

line = ((x1, y1), (x2, y2), ... (xn, yn))
tck = interpolate.splrep(x, y)

I need to find more values for my开发者_开发百科 x-coordinate which should be arranged evenly.

newx = numpy.XXX(x)
newy = interpolate.splev(newx, tck)

e.g. (1, 2, 4, 3) -> (1, 1.5, 2, 2.5, 3, 3.5, 4, 3.5, 3)

Is there a "simple" way to achieve this in Numpy/SciPy?

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You could do something like this:

import scipy.interpolate as interp
z = arange(0,4)
x = np.array([1,2,4,3])
f = interp.interp1d(z, x)
newx = f(np.linspace(z[0],z[-1],7))

which should give you

In [40]: print z
[0 1 2 3]

In [41]: print x
[1 2 4 3]

In [42]: print newx
[ 1.   1.5  2.   3.   4.   3.5  3. ]

which will just linearly interpolate between abscissa points in the order they are defined in the array. Is that what you were thinking of?