On Fri, Jul 17, 2009 at 9:51 AM, Tony Yu <tsy...@gmail.com> wrote: > > Date: Thu, 16 Jul 2009 23:37:58 -0400 > From: Ralf Gommers <ralf.gomm...@googlemail.com> > > It seems to me that there are quite a few other functions that will give > errors with 0-D arrays (apply_along/over_axis are two that come to mind). > There is nothing to interpolate so I'm not surprised. > > > Hmm, I don't quite understand. In the example below, the 0-D array (`x0`) > gives the x-value(s) where you want interpolated values. This shouldn't > require a non-scalar, and in fact, interp currently accepts python scalars > (but not Numpy scalars). >
> If the 0-D array replaced `x` and `y`---the known data points--- then, I > agree there would be nothing to interpolate. I believe the example functions > you cite are similar to replacing `x` and `y` below with scalar values. > You're right, sorry for the confusion, i did swap the roles of x/y with that of x0 in my mind. That's what I get for writing emails at midnight. If it works with scalars it should work with 0-D arrays I think. So you should probably open a ticket and attach your patch. Cheers, Ralf > ... or am I just missing something? > > Thanks, > -Tony > > > When using interpolate with a zero-rank array, I get "ValueError: > > object of too small depth for desired array". The following code > > reproduces this issue > > > import numpy as np > > x0 = np.array(0.1) > > x = np.linspace(0, 1) > > y = np.linspace(0, 1) > > np.interp(x0, x, y) > > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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