Hi Chris,
Thank you! This is useful information. Unfortunately, I am doing this
on data from a sensor and would be hard to fit to a simple polynomial
while avoiding overfitting.
Thanks again!
Shawn
On Thu, May 1, 2014 at 7:01 PM, Chris Barker chris.bar...@noaa.gov wrote:
On Thu, May 1, 2014
Hi Christian,
Thank you for your input! I prefer np.gradient because it takes
mid-point finite difference estimation instead of one-sided estimates,
but np.diff() is also a good idea. Just wondering why np.gradient does
not have something similar, being curious :)
Shawn
On Thu, May 1, 2014 at
Hi,
On Tue, Apr 22, 2014 at 6:25 AM, Andrew Collette
andrew.colle...@gmail.com wrote:
Announcing HDF5 for Python (h5py) 2.3.0
===
The h5py team is happy to announce the availability of h5py 2.3.0 (final).
Thanks to everyone who provided beta feedback!
On Thu, May 1, 2014 at 6:00 PM, Yuxiang Wang yw...@virginia.edu wrote:
Thank you for your input! I prefer np.gradient because it takes
mid-point finite difference estimation instead of one-sided estimates,
but np.diff() is also a good idea. Just wondering why np.gradient does
not have
Shawn (Yuxiang) -
The right way to compute this is using Runga-Kutta approximations. I'm not
aware if numpy supports these. -jm
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John Mark Agosta
650 465-4707
johnmark.ago...@gmail.com *Unpredictable consequences are the most
expected thing on earth.*
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