Re: [Numpy-discussion] Cython-based OpenMP-accelerated quartic polynomial solver
Personally I like atleast_1d, which will convert a scalar into a 1d array but will leave arrays untouched (i.e. won't change the dimensions. Not sure what the advantages/disadvantages are relative to asarray. Jon On Fri, Oct 2, 2015 at 7:05 AM, <numpy-discussion-request@scipy.org> wrote:
From: Juha Jeronen <juha.jeronen@jyu.fi> To: Discussion of Numerical Python <numpy-discussion@scipy.org> Cc: Date: Fri, 2 Oct 2015 13:31:47 +0300 Subject: Re: [Numpy-discussion] Cython-based OpenMP-accelerated quartic polynomial solver On 02.10.2015 13:07, Daπid wrote:
On 2 October 2015 at 11:58, Juha Jeronen <juha.jeronen@jyu.fi> wrote:
First version done and uploaded:
https://yousource.it.jyu.fi/jjrandom2/miniprojects/trees/master/misc/polysol...
Small comment: now you are checking if the input is a scalar or a ndarray, but it should also accept any array-like. If I pass a list, I expect it to work, internally converting it into an array.
Good catch.
Is there an official way to test for array-likes? Or should I always convert with asarray()? Or something else?
-J
-- ________________________________________________________ Jonathan D. Slavin Harvard-Smithsonian CfA jslavin@cfa.harvard.edu 60 Garden Street, MS 83 phone: (617) 496-7981 Cambridge, MA 02138-1516 cell: (781) 363-0035 USA ________________________________________________________
numpy.asanyarray() would be my preferred goto, as it will leave subclasses of ndarray untouched; asarray() and atleast_1d() force ndarray. It's nice to do the whenever possible. Ryan On Fri, Oct 2, 2015 at 6:52 AM, Slavin, Jonathan <jslavin@cfa.harvard.edu> wrote:
Personally I like atleast_1d, which will convert a scalar into a 1d array but will leave arrays untouched (i.e. won't change the dimensions. Not sure what the advantages/disadvantages are relative to asarray.
Jon
On Fri, Oct 2, 2015 at 7:05 AM, <numpy-discussion-request@scipy.org> wrote:
From: Juha Jeronen <juha.jeronen@jyu.fi> To: Discussion of Numerical Python <numpy-discussion@scipy.org> Cc: Date: Fri, 2 Oct 2015 13:31:47 +0300 Subject: Re: [Numpy-discussion] Cython-based OpenMP-accelerated quartic polynomial solver
On 02.10.2015 13:07, Daπid wrote:
On 2 October 2015 at 11:58, Juha Jeronen <juha.jeronen@jyu.fi> wrote:
First version done and uploaded:
https://yousource.it.jyu.fi/jjrandom2/miniprojects/trees/master/misc/polysol...
Small comment: now you are checking if the input is a scalar or a ndarray, but it should also accept any array-like. If I pass a list, I expect it to work, internally converting it into an array.
Good catch.
Is there an official way to test for array-likes? Or should I always convert with asarray()? Or something else?
-J
-- ________________________________________________________ Jonathan D. Slavin Harvard-Smithsonian CfA jslavin@cfa.harvard.edu 60 Garden Street, MS 83 phone: (617) 496-7981 Cambridge, MA 02138-1516 cell: (781) 363-0035 USA ________________________________________________________
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
-- Ryan May
Hi all, Thanks Jon and Ryan for the suggestions. Both asanyarray() or atleast_1d() sound good. There's the technical detail that Cython needs to know the object type (e.g. in the parameters to quartic_z_array()), so I think atleast_1d() may be safer. I've taken this option for now. This simplified the code somewhat. The *_scalar() functions have been removed, as they are no longer needed. The *_array() versions have been renamed, removing the _array suffix. The return values have stayed as they were - if there is only one problem to solve, the singleton dimension is dropped, and otherwise a 2D array is returned. (The exception is linear(), which does not need the second dimension, since the solution for each problem is unique. It will return a scalar in the case of a single problem, or a 1D array in the case of multiple problems.) I've pushed the new version. It's available from the same repository: https://yousource.it.jyu.fi/jjrandom2/miniprojects/trees/master/misc/polysol... Other comments? The next step? -J P.S.: I'm not sure how exact the object type must be - i.e. whether Cython wants to know that the object stores its data somewhat like an ndarray, or that its C API exactly matches that of an ndarray. In Cython there are some surprising details regarding this kind of things, such as the ctypedef'ing of scalar types. For example, see the comments about complex support near the beginning of polysolve2.pyx, and the commented-out SSE2 intrinsics experiment in https://yousource.it.jyu.fi/jjrandom2/miniprojects/blobs/master/misc/tworods... . In the latter, it was somewhat tricky to get Cython to recognize __m128d - turns out it's close enough for Cython to know that it behaves like a double, although it actually contains two doubles. (Note that these ctypedefs never end up in the generated C code; Cython uses them as extra context information when mapping the Python code into C.) (And no need to worry, I'm not planning to put any SSE into polysolve2 :) ) On 02.10.2015 17:18, Ryan May wrote:
numpy.asanyarray() would be my preferred goto, as it will leave subclasses of ndarray untouched; asarray() and atleast_1d() force ndarray. It's nice to do the whenever possible.
Ryan
On Fri, Oct 2, 2015 at 6:52 AM, Slavin, Jonathan <jslavin@cfa.harvard.edu <mailto:jslavin@cfa.harvard.edu>> wrote:
Personally I like atleast_1d, which will convert a scalar into a 1d array but will leave arrays untouched (i.e. won't change the dimensions. Not sure what the advantages/disadvantages are relative to asarray.
Jon
On Fri, Oct 2, 2015 at 7:05 AM, <numpy-discussion-request@scipy.org <mailto:numpy-discussion-request@scipy.org>> wrote:
From: Juha Jeronen <juha.jeronen@jyu.fi <mailto:juha.jeronen@jyu.fi>> To: Discussion of Numerical Python <numpy-discussion@scipy.org <mailto:numpy-discussion@scipy.org>> Cc: Date: Fri, 2 Oct 2015 13:31:47 +0300 Subject: Re: [Numpy-discussion] Cython-based OpenMP-accelerated quartic polynomial solver
On 02.10.2015 13:07, Daπid wrote:
On 2 October 2015 at 11:58, Juha Jeronen <juha.jeronen@jyu.fi <mailto:juha.jeronen@jyu.fi>> wrote:
First version done and uploaded:
https://yousource.it.jyu.fi/jjrandom2/miniprojects/trees/master/misc/polysol...
Small comment: now you are checking if the input is a scalar or a ndarray, but it should also accept any array-like. If I pass a list, I expect it to work, internally converting it into an array.
Good catch.
Is there an official way to test for array-likes? Or should I always convert with asarray()? Or something else?
-J
-- ________________________________________________________ Jonathan D. Slavin Harvard-Smithsonian CfA jslavin@cfa.harvard.edu <mailto:jslavin@cfa.harvard.edu> 60 Garden Street, MS 83 phone: (617) 496-7981 <tel:%28617%29%20496-7981> Cambridge, MA 02138-1516 cell: (781) 363-0035 <tel:%28781%29%20363-0035> USA ________________________________________________________
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org <mailto:NumPy-Discussion@scipy.org> https://mail.scipy.org/mailman/listinfo/numpy-discussion
-- Ryan May
_______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org https://mail.scipy.org/mailman/listinfo/numpy-discussion
participants (3)
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Juha Jeronen -
Ryan May -
Slavin, Jonathan