On Wed, Feb 3, 2016 at 10:18 PM, Nathaniel Smith wrote:
> On Tue, Feb 2, 2016 at 8:45 AM, Pauli Virtanen wrote:
> > 01.02.2016, 23:25, Ralf Gommers kirjoitti:
> > [clip]
> >> So: it would really help if someone could pick up the automation part of
> >> this and improve the stack testing, so the
Excellent! I was looking for nonuniform FFT as a component for the
interpolation. I am thinking of combining nufft with czt (from scipy) for the
interpolation.
Nadav
From: NumPy-Discussion on behalf of
Charles R Harris
Sent: 04 February 2016 17:17
To: Di
The test data for mpl is available as a sperate conda package,
matplotlib-tests. The reason for splitting it is 40Mb of tests images.
Tom
On Thu, Feb 4, 2016, 09:09 Pauli Virtanen wrote:
> 04.02.2016, 07:56, Nathaniel Smith kirjoitti:
> [clip]
> > Whoops, got distracted talking about the resul
On Thu, Feb 4, 2016 at 4:34 AM, Nadav Horesh wrote:
> Thank you, I'll try this.
> Interpolation by the sinc function is equivalent to what yiu get if you'll
> synthesize a smooth function by summing its Fourier component obtained via
> FFT of the data.
>
You might be interested in the NUFFT, see
On 2/4/16 02:42 , numpy-discussion-requ...@scipy.org wrote:
Date: Thu, 4 Feb 2016 09:32:36 +
From: Nadav Horesh
To: numpy-discussion
Subject: [Numpy-discussion] [OT] Interpolation of an unevently sampled
bandwidth limited signal
Message-ID:
Content-Type: text/plain;
04.02.2016, 07:56, Nathaniel Smith kirjoitti:
[clip]
> Whoops, got distracted talking about the results and forgot to say --
> I guess we should think about how to combine these? I like the
> information on warnings, because it helps gauge the impact of
> deprecations, which is a thing that takes a
Thank you, I'll try this.
Interpolation by the sinc function is equivalent to what yiu get if you'll
synthesize a smooth function by summing its Fourier component obtained via FFT
of the data.
Nadav.
From: NumPy-Discussion on behalf of Evgeni
Burovsk
> scipy:
>one new failure, in test_nanmedian_all_axis
>250 calls to np.testing.rand (wtf), 92 calls to random_integers, 3 uses
> of datetime64 with timezones. And for some reason the new numpy gives more
> "invalid value encountered in greater"-type warnings.
One limitation of this approac
On Thu, Feb 4, 2016 at 9:32 AM, Nadav Horesh wrote:
> I have several cases of hand digitized spectra that I'd like to resample
> these spectra at even spacings. My problem is that cubic or RBF splines
> often result in an unacceptible over-shooting. Is there a python module that
> provides somethi
On Wed, 3 Feb 2016 21:56:08 -0800
Nathaniel Smith wrote:
>
> An extra ~2 hours of tests / 6-way parallelism is not that big a deal
> in the grand scheme of things (and I guess it's probably less than
> that if we can take advantage of existing binary builds) -- certainly
> I can see an argument f
I have several cases of hand digitized spectra that I'd like to resample these
spectra at even spacings. My problem is that cubic or RBF splines often result
in an unacceptible over-shooting. Is there a python module that provides
something similar to sinc interpolation on unevenly space sampled
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