ENH: support for ND arithmetical operations for Function.

[phmbressan]

Pull request type

• Code changes (bugfix, features)

Checklist

• Tests for the changes have been added (if needed)
• Docs have been reviewed and added / updated
• All tests (pytest tests -m slow --runslow) have passed locally
• CHANGELOG.md has been updated (if relevant)

Current behavior

PR #785 introduced the possibility of 2D Function multiplication. The intent of this PR is to generalize this to the other arithmetical operations and to ND Functions for better scalability (e.g. so as not keep adding if blocks for every dimension, like 3D, 4D etc).

New behavior

The generalization is done with the following changes:

• Use the self._domain and self._image for array manipulation, instead of unidimensional self.x_array and self.y_array;
• Multivariate lambda expressions are generated to allow callable operations:
  • The implementation is less trivial, requiring dynamically building a multivariate lambda;
  • This PR implementation worked very well on testing, but, if it does not hold review scrutinity due the use of eval, it can easily be converted into an exception and disallowing it.

Tests were introduced for both existing 2D operations and for the new generalized ones.

Overall the structure of the arithmetic methods of Function got a bit simpler and more regular. Another important notice, is that the current multivariable implementation of mul from #785 is non commutative when dealing with 1D*2D, which is fixed by this PR.

Breaking change

• Yes
• No

[codecov]

Codecov Report

Attention: Patch coverage is 93.13305% with 16 lines in your changes missing coverage. Please review.

Project coverage is 80.14%. Comparing base (4df0b38) to head (01d0f9d).
Report is 20 commits behind head on develop.

Files with missing lines	Patch %	Lines
rocketpy/mathutils/function.py	93.13%	16 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff             @@
##           develop     #810      +/-   ##
===========================================
+ Coverage    79.11%   80.14%   +1.02%     
===========================================
  Files           96       98       +2     
  Lines        11575    12030     +455     
===========================================
+ Hits          9158     9641     +483     
+ Misses        2417     2389      -28     

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[MateusStano]

Can you check execution speed of the code? With Monte Carlo sims especially

The operations seems different so I just want to make sure it is close to how it was before

[phmbressan]

Can you check execution speed of the code? With Monte Carlo sims especially

The operations seems different so I just want to make sure it is close to how it was before

Performance Benchmarks

Function Composition (f + g) and Evaluation (h(x))

Test	Before	After
f + g (lambda)	16.2 μs ± 1.24 μs	17.5 μs ± 0.41 μs
h(3) (lambda eval)	1.59 μs ± 0.013 μs	725 ns ± 5.47 ns
f + g (array function)	110 μs ± 0.82 μs	102 μs ± 1.01 μs
h(2.5) (array eval)	3.85 μs ± 0.045 μs	3.74 μs ± 0.068 μs

Monte Carlo Simulation

Metric	Before	After
Avg Time per Iteration	1.337 s	1.276 s
Total Simulations	250	250
Total Wall Time	334.3 s	319.0 s

Overall the results are about the same speed, mostly within run to run variance. The exception is the Function lambda evaluation that is now consistently faster and I don't know why, still checking.

[Copilot]

Pull Request Overview

This PR generalizes arithmetical operations for the Function class from 2D to ND and improves internal consistency by using the set_source method.

• Refactors source setting by replacing direct assignment with set_source.
• Adds extensive parametrized tests covering add, sub, mul, div, pow, and mod operations for both 2D and ND functions.
• Updates CHANGELOG.md to reflect the new ND arithmetic support.

Reviewed Changes

Copilot reviewed 3 out of 3 changed files in this pull request and generated 1 comment.

File	Description
tests/unit/test_function.py	Updates to test cases including replacing source assignment with set_source and adding parametrized tests for ND arithmetic operations.
CHANGELOG.md	Added an entry for ND arithmetic support in the Function class.

Comments suppressed due to low confidence (1)

tests/unit/test_function.py:907

• [nitpick] When using lambda functions in ND arithmetic tests, ensure that the lambda and other operand functions have matching arity and consistent naming conventions to avoid ambiguity in multi-dimensional operations.

func_lambda = Function(lambda x, y, z: x + y + z)