Shawn (Yuxiang) -
The right way to compute this is using Runga-Kutta approximations. I'm not
aware if numpy supports these. -jm
______
John Mark Agosta
650 465-4707
johnmark.ago...@gmail.com *"Unpredictable consequences are the most
expected thing on earth."*
*
--- B. Latour*
On Thu, May 1, 2014 at 2:45 PM, Yuxiang Wang <yw...@virginia.edu> wrote:
> Hi all,
>
> I am trying to calculate the 2nd-order gradient numerically of an
> array in numpy.
>
> import numpy as np
> a = np.sin(np.arange(0, 10, .01))
> da = np.gradient(a)
> dda = np.gradient(da)
>
> This is what I come up. Is the the way it should be done?
>
> I am asking this, because in numpy there isn't an option saying
> np.gradient(a, order=2). I am concerned about whether this usage is
> wrong, and that is why numpy does not have this implemented.
>
> Thank you!
>
> -Shawn
> --
> Yuxiang "Shawn" Wang
> Gerling Research Lab
> University of Virginia
> yw...@virginia.edu
> +1 (434) 284-0836
> https://sites.google.com/a/virginia.edu/yw5aj/
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