Claude 3.7 sonnet generated matlab version of the blochsim part in sims.py

[tianrluo]

I was curious, so I tried a prompt of:

please convert the following python script to matlab:
note that the γH, dt0, π imported are just three float numbers.
make sure you convert the backward method for me.

with https://github.com/tianrluo/MRphy.py/blob/master/mrphy/sims.py#L1-L315 pasted into the chatbox of Claude.

It returned me the attached file.
bloch-simulator-matlab.txt
and its response:

I'll convert this Python script to MATLAB. The script implements a Bloch simulator with explicit Jacobian operations for differentiation. Let me create the MATLAB equivalent:

I've created a complete MATLAB translation of the Python Bloch simulation code. Let me explain some of the key transformations I made:
Major Conversion Points:

    Function Organization:
        MATLAB doesn't have Python's class-based structure with forward and backward methods, so I've restructured it into multiple functions:
            blochsim (main function that users call)
            blochsim_forward (handles forward simulation)
            blochsim_backward (handles gradient calculation)
            Helper functions for relaxation
    Parameter Handling:
        Converted Python's keyword arguments to MATLAB's name-value pairs using inputParser
        Made sure optional parameters like T1/T2 are properly handled
    Tensor Operations:
        Replaced PyTorch tensor operations with MATLAB equivalents:
            torch.mul() → element-wise multiplication with .*
            torch.cross() → MATLAB's cross() function
            torch.norm() → MATLAB's vecnorm() function
    Memory Management:
        MATLAB handles memory differently, so I've structured the code to avoid unnecessary copies
        Used a cache struct to store intermediate values needed for the backward pass
    Variable Reshaping:
        MATLAB handles tensors differently than PyTorch, so I adjusted the dimension handling
        Added appropriate reshaping operations to ensure tensor dimensions match
    Function References:
        Replaced Python's lambda functions with MATLAB function handles

Specific Implementation Notes:

    The blochsim_backward function implements the same algorithm as the Python backward method, calculating gradients with respect to input magnetization and effective magnetic field.
    In place of PyTorch's automatic gradient accumulation, I've made the gradients explicit.
    Special care was taken with the relaxation functions to ensure they behave the same way in forward and backward passes.
    The mathematics of rotation and magnetization evolution is preserved exactly as in the original code.

This MATLAB implementation maintains all the functionality of the original Python code, including the crucial backward pass for gradient-based optimization. It could be integrated with MATLAB's automatic differentiation system if needed.

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NOTE that I have not tested the matlab file that was generated by Claude.
If anyone's interested, please try it yourself.