# Can anyone translate this code into simpler one?

I'm new in Mathematica, so can anyone translate the following code into a simpler form where uses more familiar syntax? my mean is #,&and /@ signs. I read about every sign individually in Mathematica documentation but this code has mixed all of them and is not clear to me. Thanks in advance.

f[n_] := Orthogonalize[r^# & /@ Range[0, n], Integrate[g*#1*#2, {r, -∞, ∞}] &]

• Why don't you ask the author of the code? – yarchik Jul 11 '20 at 15:17
• r^# & /@ Range[0, n] = r^Range[0, n]. In this case, you can replace g*#1*#2 by g * ##, but my guess is that it is not more familiar (to you). – Michael E2 Jul 11 '20 at 17:27

I think it might be helpful to evaluate the arguments on their own and see what happens.

The first argument

r^# & /@ Range[0, n]


outputs (for a specific choice of n)

With[{n = 3}, r^# & /@ Range[0, n]]
(* {1, r, r^2, r^3} *)


which generates a list that you could also get by the following

Table[r^i, {i, 0, n}]


The FullForm of the first argument would be something like

Map[Function[{x}, r^x], Range[0, n]]


note that f /@ list is a shorthand for Map[f, list] and, for the sake of a simple unrelated example, f /@ {1, 2, 3} gives {f, f, f}. Now back to the problem at hand: The syntax r^# & generates a pure (anonymous) function; you can check that r^# & [exponent] == r^exponent where on the left-hand side the function r^# & is called with the argument exponent. Note that the ampersand & simply tells Mathematica when the pure function definition is complete.

The second argument of Orthogonalize is the inner product with respect to which the vectors should be orthogonalized. It is a (pure) function that takes two arguments. When you have more than one argument in a pure function, the slots are numbered and denoted as #1, #2, etc. A silly example

Sqrt[#1 + #2] &[a, b] == Sqrt[a + b]


Now the second argument is written as

Integrate[g*#1*#2, {r, -∞, ∞}] &


If you like you can define the function explicitly

myInnerProd[v1_, v2_] := Integrate[g*v1*v2, {r, -∞, ∞}]


and then define

f[n_] := Orthogonalize[Table[r^i, {i,0, n}], myInnerProd]


If you want to understand better the syntax of pure functions read the documentation entry tutorial/FunctionalOperations#17469.

• Thanks, and how #1*#2 works? what does it mean? – Wisdom Jul 11 '20 at 14:35
• #1 and #2 are slots - anonymous arguments. When you orthogonalize, the process passes the vectors into #1, #2, just like v1*v2 above. One of the simpler ways to orthogonalize is using Gram-Schmidt and even though it's not used here, it explains it quite well. When you see $\langle \mathbf{v},\mathbf{u} \rangle$, you're doing an inner (dot) product. But since our inner product is on functions, not vectors, we do an integral of a product of polynomials over -∞, ∞ weighted by g. I hope that makes sense. – flinty Jul 11 '20 at 14:55
• These are legitimate questions. Why not properly extend the answer to explain every point? – yarchik Jul 11 '20 at 15:16
• @flinty Thanks a lot. Now tell me how Mathematica understands where to get #1 and #2? They refer to first and second terms of first argument (r^# & /@ Range[0, n])? and what is the single & at the end? – Wisdom Jul 12 '20 at 2:38
• & ends the definition of a pure function. So if I do f = # + 1 & that means define a function with an anonymous argument. I can then do f and I get result 5. You should read the tutorial Natas referenced in this answer. On the other point, Mathematica doesn't get #1 and #2 from there exactly. In this case it generates vectors during the orthogonalization process which is kind of complicated to explain here. Read the article about Gram-Schmidt in my earlier comment. It provides #1 and #2 - slots for vectors - for you to use in your own custom inner product, like the Integrate above.. – flinty Jul 12 '20 at 11:54