From 4cfeb0f2a9c040e85f67a8d78e8a40de68530e46 Mon Sep 17 00:00:00 2001 From: Marshall Lochbaum Date: Wed, 1 Jun 2022 16:06:28 -0400 Subject: Consistently use the name Reorder Axes, not dyadic Transpose --- docs/doc/indices.html | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'docs/doc/indices.html') diff --git a/docs/doc/indices.html b/docs/doc/indices.html index 8ed4317e..36bf279c 100644 --- a/docs/doc/indices.html +++ b/docs/doc/indices.html @@ -85,7 +85,7 @@ -

In Dyadic Transpose (), 𝕨 is made up of indices into axes of 𝕩. Since array shape is 1-dimensional, there is only one sensible choice for these elements, a single number each.

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In Reorder Axes (), 𝕨 is made up of indices into axes of 𝕩. Since array shape is 1-dimensional, there is only one sensible choice for these elements, a single number each.

Element indices

In general, the index of an element of an array is a list whose length matches the array rank. It is also possible to use a number for an index into a list, as the list index is a singleton, but this must be kept consistent with the rest of the language. NARS-family APLs make the Index Generator ( in BQN) return a numeric list when the argument has length 1 but a nested array otherwise. This means that the depth of the result depends on the shape of the argument, inverting the typical hierarchy. BQN shouldn't have such an inconsistency.

Functions Range (), Indices (/), Group (), and Pick () naturally deal with element indices. Each of these can be defined to use list indices. However, this usually rules out the possibility of using atomic indices, which makes these functions harder to use both with generic array manipulation and with the major cell indices discussed in the next section. For this reason BQN restricts and / to use atomic indices, which comes with the requirement that the arguments to Group and Indices, and the result of Group Indices, must be lists. For dyadic Group the depth-1 elements of 𝕨 are arrays of indices along axes of the result (multi-axis documentation). This means each axis of 𝕩 can only be related to one axis of the result.

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