On Mon, 2013-02-25 at 10:50 -0500, Skipper Seabold wrote: > On Mon, Feb 25, 2013 at 10:43 AM, Till Stensitzki <mail.t...@gmx.de> > wrote: > > > > First, sorry that i didnt search for an old thread, but because i > disagree with > > conclusion i would at least address my reason: > > > >> I don't like > >> np.abs(arr).max() > >> because I have to concentrate to much on the braces, especially if > arr > >> is a calculation > > > > This exactly, adding an abs into an old expression is always a > little annoyance > > due to the parenthesis. The argument that np.abs() also works is > true for > > (almost?) every other method. The fact that so many methods already > exists, > > especially for most of the commonly used functions (min, max, dot, > mean, std, > > argmin, argmax, conj, T) makes me missing abs. Of course, if one > would redesign > > the api, one would drop most methods (i am looking at you ptp and > byteswap). But > > the objected is already cluttered and adding abs is imo logical > application of > > "practicality beats purity". > > > > I tend to agree here. The situation isn't all that dire for the number > of methods in an array. No scrolling at reasonably small terminal > sizes. > > [~/] > [3]: x. > x.T x.copy x.getfield x.put x.std > x.all x.ctypes x.imag x.ravel > x.strides > x.any x.cumprod x.item x.real x.sum > x.argmax x.cumsum x.itemset x.repeat > x.swapaxes > x.argmin x.data x.itemsize x.reshape x.take > x.argsort x.diagonal x.max x.resize > x.tofile > x.astype x.dot x.mean x.round > x.tolist > x.base x.dtype x.min x.searchsorted > x.tostring > x.byteswap x.dump x.nbytes x.setfield > x.trace > x.choose x.dumps x.ndim x.setflags > x.transpose > x.clip x.fill x.newbyteorder x.shape x.var > x.compress x.flags x.nonzero x.size x.view > x.conj x.flat x.prod x.sort > x.conjugate x.flatten x.ptp x.squeeze > > Two small things (not sure if it matters much). But first almost all of these methods are related to the container and not the elements. Second actually using a method arr.abs() has a tiny pitfall, since abs would work on numpy types, but not on python types. This means that:
np.array([1, 2, 3]).max().abs() works, but np.array([1, 2, 3], dtype=object).max().abs() breaks. Python has a safe name for abs already... > I find myself typing things like > > arr.abs() > > and > > arr.unique() > > quite often. > > Skipper > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
