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I think the idea is that you performed the exercise to create stress that you want your body to respond to by getting stronger / more aerobically fit etc in some way. So by icing, yes, you recover better, but by reducing the stress you reduce the adaptations.

Imagine you could perfectly recover with some intervention. Then weight lifting no longer works!

For examples like the ones you listed, peak performances where you’re not concerned about gainz and maybe even have to perform again soon after, it makes a lot of sense to do anything to recover quickly.


I find I need two different modes:

- hypertrophy to actually gain strength and muscle (ie. longer recovery time)

- maximum recovery to heal from a strenuous exercise and be ready for more the next day (ie. shortest possible recovery time)

In the second scenario, I don't care about gaining strength at all, and the recovery is the only important aspect.


Yep, this is exactly the point I was getting to.

The stress response is literally the point of working out, you won’t get adaptation without stress.

Sometimes that’s undesirable, ie if you’re in the middle of a competitive league and need to reduce stress post-game. In which case, ice away.


> and maybe even have to perform again soon after, it makes a lot of sense to do anything to recover quickly

For running specifically I’m not trying to make my legs stronger, I’m improving cardio. I need the legs to be in good shape for tomorrow’s hard run :)


In running specifically you need the stress to drive adaptation in the muscle such as capillarisation.

If you’re icing after you run you’re missing out on the benefits of the run.


Not MIT scheme, and there are no proper ports of scmutils to other Scheme dialects that I know of.


Interesting, looks like Ben Greenman started work on a port to Racket, but it does appear that that work is still firmly WIP: https://github.com/bennn/mechanics


That note in the docs is from a time when Emmy only ran on the JVM. Now Emmy runs in JS in a browser (see my top level comment for demo links) which I would argue is even easier.

Also the MIT scheme install was historically quite hairy and not supported on M1 Macs, for example.

I’ll update the docs here. Thanks!


Hey Taylor, thanks for posting these!! I'm still working on the airplane... it's a Vans RV-10, and now out at the hangar and maybe 98% complete, one more full-time month of work that I need to carve out so I can fly it by this summer.


Co-author of Emmy here, happy to answer any questions!

Point well taken from tonyarkles that on-boarding and docs need work. My big goals for this project were:

1. finish a 100% port of Gerald Sussman's scmutils algebra system into the browser via ClojureScript (I'm at ~98% or so?)

2. attach a 2D and 3D visualization system, and use the very-high-level physics abstractions to generate fast, interactive animations

3. make this all editable in the browser

4. write a ton of physics lessons and essays using the system

1-3 are all done, 4 is going to happen, but job + young twins are slowing me down now.

The easiest way to play with 1-3 is via the demos I shared at Strange Loop this past year, all of which run in the browser.

The first two live in Maria.cloud, which has all of Emmy available on any page. So fork these, play and share:

- First-Class Visualizations: https://2.maria.cloud/gist/30dbb25a2d2eb7324e0aad1097c459ae

- MathBox + Emmy at Strange Loop: https://2.maria.cloud/gist/0405c3427c88326a181b307371f939bc

These live in an editable version of a Clerk notebook with a less-polished UI:

- Taylor Series: https://sritchie.github.io/strange-loop-2023/notebooks/stl/t...

- Dual Number Visualization: https://sritchie.github.io/strange-loop-2023/notebooks/stl/d...

- (p, q) torus knot: https://sritchie.github.io/strange-loop-2023/notebooks/stl/p...

- Phase Portrait of the Pendulum: https://sritchie.github.io/strange-loop-2023/notebooks/stl/p...

- Geodesics of a Torus: https://sritchie.github.io/strange-loop-2023/notebooks/stl/t...

- Geodesics Klein bottles: https://sritchie.github.io/strange-loop-2023/notebooks/stl/k...

- Animated Particle on an Ellipsoid: https://sritchie.github.io/strange-loop-2023/notebooks/stl/e...


Simply want to say thank you and you're awesome. I'm looking forward to the physics lessons.


Thank you for the kind words :)


I used tons of lash splices while building an RV-10 airplane but didn’t know the name until now. Thank you!


I have reverse-mode (purely functional reverse mode at that!) sitting in a branch, and will get this going at some point soon. Even more fun will be compilation down to XLA, like JAX does in Python.


Yes, if you get to automatic differentiation by overloading your operators to also take a “differential” type, you can further overload them to do symbolic arithmetic and then symbolic differentiation falls out for free.

See https://sritchie.github.io/emmy/src/emmy/differential.html for detail!


What would you build / create / write if you had a web-enabled build of SICM (well, scmutils I guess) in hand? I'd love to hear more about your thoughts on how to build a community around these tools and ideas.


I would love to explore statistical mechanics, quantum field theory, and/or general relativity through a similar lens.

But I am also quite interested in learning more about the "under the hood" workings and software craftsmanship of scmutils. The textbook _uses_ scmutils to explore classical mechanics.

But it does not delve into the implementation details of scmutils itself, which interest me.


It's fully rejuvenated in Clojure as "Emmy", with Sussman's support and a bunch of 2D and 3D graphing extensions. See Emmy-Viewers: https://emmy-viewers.mentat.org/ and Emmy: https://emmy.mentat.org/

Thanks to https://2.maria.cloud, everything in SICM and FDG works in the browser as well: https://2.maria.cloud/gist/d3c76ee5e9eaf6b3367949f43873e8b2


Wow, thanks for this!


Of course! And referencing your other comment, during the ~2 year period I've been working on Emmy (on top of work by Colin Smith), I was keen to make the implementation more accessible and well-documented than the original.

There's still not a great map of the project (from primitives to general relativity), but many of the namespaces are written as literate programming explorations: https://emmy.mentat.org/#explore-the-project

Here's the automatic differentiation implementation/essay, for example: https://sritchie.github.io/emmy/src/emmy/differential.html

A rough sketch of the tower is:

- `emmy.value` and `emmy.generic` implement the extensible generic operations

- `emmy.ratio`, `emmy.complex` and `emmy.numbers` fleshes out the numeric tower

- `emmy.expression` and `emmy.abstract.number` add support for symbolic literals

Next we need an algebraic simplifier...

- `emmy.pattern.{match,rule,syntax} give us a pattern matching language

- `emmy.simplify.rules` adds a ton of simplification rules, out of which

- `emmy.simplify` builds a simplification engine

Actually the simplifier has three parts... the first two start in `emmy.rational-function` and `emmy.polynomial` and involve converting an expression into either a polynomial or a rational function and then back out, putting them into "canonical form" in the process. That will send you down the rabbit hole of polynomial GCD etc...

And on and on! I'm happy to facilitate any code reading journey you go on or chat about Emmy or the original scmutils, feel free to write at sam [at] mentat.org, or else visit the Discord I run for the project at https://discord.gg/hsRBqGEeQ4.


This is an absolute triumph. Over the course of several years (starting about 15 years ago) I've been looking for a way to go through SICM and FDG without dredging up an MIT scheme that's useful for nothing else, or dealing with a partial reimplementation in a language with much less expressive power.


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