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Improve this code that uses Nested MapThread and Map?

Jeff Burns
Posted 10 years ago
POSTED BY: Jeff Burns
6 Replies
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I like

Catenate@MapThread[Thread@*List, {l1, l2}]
POSTED BY: Szabolcs Horvát
Jeff Burns
Jeff Burns
Posted 10 years ago

This is the fastest, but I am not sure how this part work "Thread@*List". Can someone help me break it down?
POSTED BY: Jeff Burns

@* is short for Composition. Thread@*List does the same as Sander's Thread[{#1,#2}].
POSTED BY: Szabolcs Horvát
Jeff Burns
Jeff Burns
Posted 10 years ago

Thanks. That clears it up. I tried searching for “@*” in the help, but it does not return any results. Knowing the name of the command helps.

POSTED BY: Jeff Burns

Other possibilities:

Flatten[Table[{l1[[i]], l2[[i, j]]}, {i, Length[l1]}, {j,Length[l2[[i]]]}], 1]
Table[{l1[[i]], l2[[i, j]]}, {i, Length[l1]}, {j,Length[l2[[i]]]}] // Catenate
Flatten[Diagonal@Outer[List, l1, l2], 1]
Catenate@Diagonal@Outer[List, l1, l2]
POSTED BY: Valeriu Ungureanu

Many many possibilities, I give you two other ways:

Join @@ MapThread[Thread[{#1, #2}] &, {l1, l2}]
Transpose[{Join @@ MapThread[ConstantArray, {l1, Length /@ l2}], Join @@ l2}]

Depending on the types of data (all numerical, symbolic, mixed) one method will be faster than the other...

NB. Note that Flatten[...,1] is the same as Join @@ ... , but the latter is generally faster (or in the worst case, equal). I'm not sure how it compares to Catenate @ ... though, I have a feeling it is a more 'higher-level' function, and probably slower...
POSTED BY: Sander Huisman
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