On Sat, Feb 02, 2019 at 03:22:12PM -0800, Christopher Barker wrote:
[This bit was me]
Even numpy supports inhomogeneous data:
py> a = np.array([1, 'spam']) py> a array(['1', 'spam'], dtype='|S4')
well, no -- it doesn't -- look carefully, that is an array or type '!S4' -- i,e, a 4 element long string --every element in that array is that same type.
So it is. I wondered what the cryptic '|S4' symbol meant, and I completely missed the '' quotes around the 1.
Thanks for the correction.
c = np.sqrt(a**2 + b**2)
is a heck of a lot easer to read, write, and get correct than:
c = list(map(math.sqrt, map(lambda x, y: x + y, map(lambda x: x**2, a), map(lambda x: x**2, b) )))
Indeed. This hypothetical syntax brings the readability advantages of infix operators to code that operates on iterables, without requiring every iterable to support arbitrary functions and methods.