I often need to make a linear interpolation for a single scalar value but this is not very simple with numpy.interp :

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import numpy as n n.__version__

'1.0.5.dev4420'

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xp = n.arange(10) yp = 2.5 + xp**2 -x x = 3.2 n.interp(x, xp, yp)

Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: object of too small depth for desired array

So I use the following trick (which is really ugly) :

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n.interp([x], xp, yp)[0]

7.7000000000000011

Did I miss an obvious way to do it ?

If not, I'd be tempted to patch interp to let it accept scalar values as first argument as follow :

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def interp(x, *args, **kwds):

... if type(x) in (float, int): ... return n.interp([x], *args, **kwds).item() ... else : ... return n.interp(x, *args, **kwds) ...

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interp(x, xp, yp)

7.7000000000000011

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interp([x,2*x], xp, yp)

array([ 7.7, 38.5])

-- LB