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This project is dual-licensed under the Apache 2.0 and MIT licenses. | ||
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You may use this code under the terms of either license. |
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# You have a numerical problem. | ||
Iterative methods and associated utilities in Rust. | ||
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## You applied an iterative method naively, now you have 10 problems that recur forever. | ||
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Suppose we have a problem, and initial solution (probably bad) and a | ||
function f such that f(x) is a better solution than x by some numeric | ||
cost measure g. Then applying f repeatedly gives us a sequence of ever | ||
better solutions, hopefully converging to an optimal solution. The | ||
most common initial "I want to see this work!" implementation looks | ||
like: | ||
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x = x0 | ||
for i in 100: | ||
x = f(x) | ||
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But as soon as you've implemented such a method, many additional | ||
considerations come up: | ||
- are 100 iterations enough? | ||
- are x actually ever improving? | ||
- how long is each iteration taking? | ||
- perhaps we want to log every 10th x for later plotting? | ||
- it crashed after 2 days of iterations, perhaps I should have saved | ||
intermediate iterations... | ||
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Following the path of least resistance, we might add `print(g(x))` at | ||
the end, move `print(g(x))` into the loop, use timers and print | ||
differences, etc. In general, we find ourselves adding a few lines of | ||
code, then moving, deleting, re-adding, commenting them out... and on | ||
the next project perhaps copy and pasting them again. | ||
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Some of the time, answering our questions require access to internal | ||
state of f, which therefore gets inlined into the loop, and now all | ||
these external concerns are mixed with the algorithm, possibly adding | ||
bugs to the very algorithm they were supposed to help understand! | ||
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Argh! | ||
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## Can't we just write the algorithm once, write each utility once, and somehow do only the wiring together we need? | ||
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Yes, kind of, but it is language specific. LT;DR: | ||
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* f should not be a black box that transforms solutions x; it should | ||
instead take and returns a struct s with all interesting state of | ||
the algorithm. | ||
* To start the sequence of states, convert a problem p into an initial | ||
state s0 | ||
* Abstract the repeated application of f as a stream of states s, | ||
assuming your language has one. | ||
* Abstract the utilities as stream adaptors. Such a utility takes a | ||
stream and applies to each a transformation (e.g., measure value), a | ||
side effect (log some states) or both. | ||
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I did not invent this approach, and will happily add further | ||
references!; briefly, this hope has a long history of programming | ||
language specific ([a Haskell mailing list circa | ||
2006](https://mail.haskell.org/pipermail/haskell-cafe/2006-August/017394.html)) | ||
answers. A recent and nice entry tackling this problem in Julia is | ||
"[Iterative methods done right (because life is too short to write | ||
for-loops)](http://lostella.github.io/2018/07/25/iterative-methods-done-right.html)" | ||
(referred to as IM below) proposes to write iterative methods as Julia | ||
iterators and various utilities for them as iterator adaptors. I | ||
recommend reading their exposition, which inspired this project! | ||
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# How deep can we follow this path in rust? | ||
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Rust seems promising for many reasons. | ||
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* Rust loves abstracting sequences; iterators are a (the?) first class | ||
citizen in, e.g., for loops. | ||
* In Rust abstraction costs are low, so won't dominate the work even | ||
when iterations are pretty cheap. | ||
* It is a language essentially optimized for writing high efficiency | ||
reusable abstractions, so when iterator is not an exact fit, we can | ||
use a variation. | ||
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## The simplest thing and how it fails | ||
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In simple cases, Rust iterators will do. We even have some nice little | ||
adaptors pre-made, like `enumerate` with annotates our state with its | ||
location in the stream, and `take` which stops after the given | ||
iteration number: | ||
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for (i, state) in convert_problem_to_iterator(problem).enumerate().take(4) { | ||
println!("Iteration {} has state {}", i, state); | ||
} | ||
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# TODO here | ||
* rework the fib example, can we actually output the state instead of | ||
the next value? | ||
* Understand rustdoc better. Link to the fib code examples? Does it | ||
make sense to make this whole essay literate code using rustdoc? | ||
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And we can go quite far with this direction, as long as state is cheap | ||
to copy. The caveat is because iterators return values, not | ||
references, and so for the iterator to own them and the loop body and | ||
down stream adaptors to have access requires copies. Some might be | ||
optimized away by a [sufficiently smart | ||
compiler](https://wiki.c2.com/?SufficientlySmartCompiler) and Rust is | ||
plenty smart, but the Rusty approach to reliable efficiency is to | ||
minimize copies and make them explicit. | ||
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Some unprocessed links: | ||
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1. https://docs.rs/streaming-iterator/0.1.5/streaming_iterator/ | ||
# Licensing | ||
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This project is dual-licensed under the [Apache](LICENSE_APACHE.md) | ||
and [MIT](LICENSE_MIT.md) licenses. You may use this code under the | ||
terms of either license. Contributing to this repo in any form | ||
constitutes agreement to license any such contributions under all | ||
licenses specified in the COPYING file at that time. |