Refine lake_model.md: Remove redundant decorators and improve organization #664
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
…ation
This commit improves the Lake Model lecture with several refinements:
**Code improvements:**
- Remove redundant `@jax.jit` decorators from `compute_matrices`, `stock_update`, `rate_update`, and `markov_update` (these functions are only called from within jitted functions, so the decorators are unnecessary and can inhibit compiler optimization)
- Refactor aggregate dynamics plot to use a for loop instead of repetitive code
- Remove hardcoded colors ('r') from plots to use matplotlib's default color cycle
**Content organization:**
- Move rate definitions ($e_t$, $u_t$) to "Laws of motion for rates" section where they logically belong
- Relocate Exercise 1 to appear immediately before "Dynamics of an individual worker" section for better flow
- Simplify Exercise 1 to focus on the pedagogically interesting `vmap` usage, removing less interesting parameter comparison parts
These changes improve code clarity, performance, and pedagogical flow without changing functionality.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
|
📖 Netlify Preview Ready! Preview URL: https://pr-664--sunny-cactus-210e3e.netlify.app (27bb29b) 📚 Changed Lecture Pages: lake_model |
Major improvements:
- Added create_lake_model() function to generate model instances with precomputed matrices A, R, and g
- Replaced A_hat notation with R throughout (code and LaTeX) for cleaner notation
- Updated LakeModel NamedTuple to store computed matrices A and R
- Modified all functions to unpack model using tuple unpacking for efficiency
- Added type hints to stock_update(), rate_update(), and create_lake_model()
- Simplified generate_path() function by removing unused time parameter
- Updated rate_steady_state() to use Perron-Frobenius theorem (argmax instead of searching for eigenvalue near 1)
- Converted all LakeModel() instantiations to use create_lake_model()
- Updated markov simulation to use dedicated simulate_markov() function
Benefits:
- Matrices computed once at model creation instead of repeatedly
- Cleaner mathematical notation using R instead of \hat{A}
- More efficient code with direct tuple unpacking
- Better type safety with added annotations
- More mathematically rigorous using Perron-Frobenius theorem
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
|
📖 Netlify Preview Ready! Preview URL: https://pr-664--sunny-cactus-210e3e.netlify.app (8a84067) 📚 Changed Lecture Pages: lake_model |
Contributor
Author
Additional Refactoring: Improved Model Structure and NotationI've made additional improvements to Key Changes:
All code has been tested and verified to work correctly. ✅ |
|
📖 Netlify Preview Ready! Preview URL: https://pr-664--sunny-cactus-210e3e.netlify.app (8cce1a7) 📚 Changed Lecture Pages: lake_model |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary
This PR refines the Lake Model lecture with several improvements to code quality, performance, and pedagogical flow:
Code improvements:
@jax.jitdecorators from helper functions (compute_matrices,stock_update,rate_update,markov_update)Content organization:
vmapfunctionality, removing less pedagogically interesting parameter comparisonsTest plan
🤖 Generated with Claude Code