ndarray.clip only with lower or upper values?
Hi again, I noticed that clip() needs two parameters, but wouldn't it be nice and straightforward to just pass min= or max= as keyword arg? In [2]: a = arange(10) In [3]: a.clip(min = 2, max = 5) Out[3]: array([2, 2, 2, 3, 4, 5, 5, 5, 5, 5]) In [4]: a.clip(min = 2) --------------------------------------------------------------------------- exceptions.TypeError Traceback (most recent call last) /home/meine/<ipython console> TypeError: function takes at least 2 arguments (1 given) (I could simulate that by passing max = maximum_value_of(a.dtype), if that existed, see my other mail.) Ciao, / / /--/ / / ANS
On Dec 10, 2007 7:21 AM, Hans Meine <meine@informatik.uni-hamburg.de> wrote:
Hi again,
I noticed that clip() needs two parameters, but wouldn't it be nice and straightforward to just pass min= or max= as keyword arg?
In [2]: a = arange(10)
In [3]: a.clip(min = 2, max = 5) Out[3]: array([2, 2, 2, 3, 4, 5, 5, 5, 5, 5])
In [4]: a.clip(min = 2)
--------------------------------------------------------------------------- exceptions.TypeError Traceback (most recent call last)
/home/meine/<ipython console>
TypeError: function takes at least 2 arguments (1 given)
(I could simulate that by passing max = maximum_value_of(a.dtype), if that existed, see my other mail.)
Why not just use minimum or maximum as needed instead of overloading clip? -- . __ . |-\ . . tim.hochberg@ieee.org
Am Montag, 10. Dezember 2007 23:46:17 schrieb Timothy Hochberg:
TypeError: function takes at least 2 arguments (1 given)
(I could simulate that by passing max = maximum_value_of(a.dtype), if that existed, see my other mail.)
Why not just use minimum or maximum as needed instead of overloading clip?
You mean one of the following? a.clip(min = 10, max = numpy.finfo(a.dtype).max) a.clip(min = 10, max = numpy.iinfo(a.dtype).max) Three reasons: - this is not very concise - it is less efficient than specialized clip variants (not much / too important though) - I would have to discriminate integral and floating point types How is the latter done in numpy? Is there a good reason not to have numpy.rangetraits(sometype) with min/max as in iinfo/finfo? Should I use isinstance(mytype, int)? -- Ciao, / / /--/ / / ANS
On Dec 11, 2007 2:32 AM, Hans Meine <meine@informatik.uni-hamburg.de> wrote:
Am Montag, 10. Dezember 2007 23:46:17 schrieb Timothy Hochberg:
TypeError: function takes at least 2 arguments (1 given)
(I could simulate that by passing max = maximum_value_of(a.dtype), if that existed, see my other mail.)
Why not just use minimum or maximum as needed instead of overloading clip?
You mean one of the following? a.clip(min = 10, max = numpy.finfo(a.dtype).max) a.clip(min = 10, max = numpy.iinfo(a.dtype).max)
No. I mean: numpy.maximum(a, 10) To correspond to the above example.
Three reasons: - this is not very concise - it is less efficient than specialized clip variants (not much / too important though) - I would have to discriminate integral and floating point types
How is the latter done in numpy? Is there a good reason not to have numpy.rangetraits(sometype) with min/max as in iinfo/finfo? Should I use isinstance(mytype, int)?
-- Ciao, / / /--/ / / ANS _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
-- . __ . |-\ . . tim.hochberg@ieee.org
On Dienstag 11 Dezember 2007, Timothy Hochberg wrote:
You mean one of the following? a.clip(min = 10, max = numpy.finfo(a.dtype).max) a.clip(min = 10, max = numpy.iinfo(a.dtype).max)
No. I mean:
numpy.maximum(a, 10)
To correspond to the above example.
Great, thanks for the hints. That's good enough; could be pythonic to let clip() forward calls to minimum/maximum if only one bound is given though. I had a look at the code, but I am not used enough to the Python/C API, let alone to numpy's internals, to *quickly* hack this. Ciao, / / .o. /--/ ..o / / ANS ooo
Hans Meine wrote:
On Dienstag 11 Dezember 2007, Timothy Hochberg wrote:
You mean one of the following? a.clip(min = 10, max = numpy.finfo(a.dtype).max) a.clip(min = 10, max = numpy.iinfo(a.dtype).max)
No. I mean:
numpy.maximum(a, 10)
To correspond to the above example.
Great, thanks for the hints. That's good enough; could be pythonic to let clip() forward calls to minimum/maximum if only one bound is given though. I had a look at the code, but I am not used enough to the Python/C API, let alone to numpy's internals, to *quickly* hack this.
It is done, now in SVN. -Travis
participants (3)
-
Hans Meine -
Timothy Hochberg -
Travis E. Oliphant