From 2afb23928e1984d475cc460e1672e8f6fa0e4dbe Mon Sep 17 00:00:00 2001 From: Marshall Lochbaum Date: Wed, 11 Aug 2021 17:21:31 -0400 Subject: Allow clicking on header to get fragment link --- docs/doc/train.html | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) (limited to 'docs/doc/train.html') diff --git a/docs/doc/train.html b/docs/doc/train.html index b9c2f398..9675922c 100644 --- a/docs/doc/train.html +++ b/docs/doc/train.html @@ -4,10 +4,10 @@ BQN: Function trains
(github) / BQN / doc
-

Function trains

+

Function trains

Trains are an important aspect of BQN's tacit programming capabilities. In fact, a crucial one: with trains and the identity functions Left (⊣) and Right (⊢), a fully tacit program can express any explicit function whose body is a statement with 𝕨 and 𝕩 used only as arguments (that is, there are no assignments and 𝕨 and 𝕩 are not used in operands or lists. Functions with assignments may have too many variables active at once to be directly translated but can be emulated by constructing lists. But it's probably a bad idea). Without trains it isn't possible to have two different functions that each use both arguments to a dyadic function. With trains it's perfectly natural.

BQN's trains are the same as those of Dyalog APL, except that Dyalog is missing the minor convenience of BQN's Nothing (·). There are many Dyalog-based documents and videos on trains you can view on the APL Wiki.

-

2-train, 3-train

+

2-train, 3-train

Trains are an adaptation of the mathematical convention that, for example, two functions F and G can be added to get a new function F+G that applies as (F+G)(x) = F(x)+G(x). With a little change to the syntax, we can do exactly this in BQN:

↗️
    (⊢+⌽) ↕5
 ⟨ 4 4 4 4 4 ⟩
@@ -25,7 +25,7 @@
 "fcdeab"

The three functions ∾⌽, ·∾⌽, and ∾∘⌽ are completely identical: Join of Reverse. Why might we want three different ways to write the same thing? If we only want to define a function, there's hardly any difference. However, these three forms have different syntax, and might be easier or harder to use in different contexts. As we'll see, we can use ∾∘⌽ inside a train without parenthesizing it, and string ·∾⌽ but not ∾⌽ together with other trains. Let's look at how the train syntax extends to longer expressions.

-

Longer trains

+

Longer trains

Function application in trains, as in other contexts, shares the lowest precedence level with assignment. Modifiers and strands (with ‿) have higher precedence, so they are applied before forming any trains. Once this is done, an expression is a subject expression if it ends with a subject and a function expression if it ends with a function (there are also modifier expressions, which aren't relevant here). A train is any function expression with multiple functions or subjects in it: while we've seen examples with two or three functions, any number are allowed.

Subject expressions are the domain of "old-school" APL, and just apply one function after another to a subject, possibly assigning some of the results (that's the top-level picture—anything can still happen within parentheses). Subjects other than the first appear only as left arguments to functions, which means that two subjects can't appear next to each other because the one on the left would have no corresponding function. Here's an example from the compiler (at one point), with functions and assignments numbered in the order they are applied and their arguments marked with «», and a fully-parenthesized version shown below.

cn←pi∾lt←/𝕩≥ci←vi+nv
@@ -40,7 +40,7 @@
 ⊢>(¯1»⌈`)

In a train, arguments alternate strictly with combining functions between them. Arguments can be either functions or subjects, except for the rightmost one, which has to be a function to indicate that the expression is a train. Trains tend to be shorter than subject expressions partly because to keep track of this alternation in a train of all functions, you need to know where each function is relative to the end of the train (subjects like the ¯1 above only occur as left arguments, so they can also serve as anchors).

-

Practice training

+

Practice training

The train ⊢>¯1»⌈` is actually a nice trick to get the result of Mark Firsts ∊𝕩 given the result of Classify ⊐𝕩, without doing another search. Let's take a closer look, first by applying it mechanically. To do this, we apply each "argument" to the train's argument, and then combine them with the combining functions.

(⊢ > ¯1 » ⌈`) 𝕩
 (⊢𝕩) > (¯1) » (⌈`𝕩)
@@ -70,7 +70,7 @@
     (⊢>¯1»⌈`) sc
 ⟨ 1 1 1 1 0 0 1 0 0 1 1 ⟩
-

Composing trains

+

Composing trains

The example above uses a train with five functions: an odd number. Trains with an odd length are always composed of length-3 trains, and they themselves are composed the same way as subject expressions: an odd-length train can be placed in the last position of another train without parentheses, but it needs parentheses to go in any other position.

But we also saw the length-2 train ∾⌽ above. Even-length trains consist of a single function (∾) applied to a function or odd-length train (⌽); another perspective is that an even-length train is an odd-length train where the left argument of the final (leftmost) function is left out, so it's called with only a right argument. An even-length train always needs parentheses if it's used as one of the functions in another train. However, it can also be turned into an odd-length train by placing · at the left, making the implicit missing argument explicit. After this it can be used at the end of an odd-length train without parentheses. To get some intuition for even-length trains, let's look at an example of three functions used together: the unique (⍷) sorted (∧) absolute values (|) of an argument list.

↗️
    ⍷∧| 3‿4‿¯3‿¯2‿0
-- 
cgit v1.2.3