Fix #86: Correct bounds/initial_guess passing in 5 wrapped algorithms

[Devguru-codes]

Fix #86: Correct bounds/initial_guess passing in 5 wrapped algorithms

Description

This PR addresses Issue #86, where several wrapped IVIM algorithms crashed or returned mathematically incorrect results when processing real-world MRI data (which, unlike simulated test data, heavily tests boundary validation and fallback paths).

Root Causes & Bug Fixes

During my investigation of the algorithms acting irregularly on real data, I discovered two distinct classes of Python bugs in the wrappers:

1. PV_MUMC_biexp.py — UnboundLocalError Crash

   • Bug: The ivim_fit() method had an if/else block where the local bounds variable was only assigned in the else branch. Under OsipiBase, self.bounds defaults to a Python dictionary, meaning the code executed the if branch, never created the bounds variable, and crashed.
   • Fix: Restructured the condition to always extract the self.bounds dictionary values into the ([S0_min, D_min...], [S0_max, D_max...]) array formats expected by the underlying fit_least_squares algorithm.

2. 4 IAR_LU_* Algorithms — Invalid Constraints (Dict vs List-of-Lists)

   • Bug: When bvalues were provided at init, the wrappers passed the self.bounds Python dictionary directly to the dipy IvimModel* constructors. Internally, DIPY expects arrays and indexes them via bounds[0] and bounds[1]. Indexing a dictionary by integer yields its keys ("S0", "f"), completely breaking the optimizer constraints and silently producing garbage results.
   • Fix: Explicitly convert the dictionary into a [[lower...], [upper...]] array structure whenever the IAR_algorithm is initialized.
   • Affected files: IAR_LU_biexp.py, IAR_LU_segmented_2step.py, IAR_LU_segmented_3step.py, IAR_LU_subtracted.py.

Edge Case Hardening Added

To ensure these algorithms robustly handle diverse real-world data and usage patterns, I added several layers of error handling and edge-case protection:

• Stale-Model Guard: IAR_LU algorithms now automatically detect if the bvalues array changes between init and ivim_fit(), and gracefully rebuild their internal gradient table/model to prevent silent corruption.
• Missing D_and_Ds_swap: Added the missing parameter order swap check to IAR_LU_segmented_2step.
• bvalues=None Guards: All 5 algorithms now properly fall back to self.bvalues, raising a clear error if neither is available.
• Graceful Fallbacks: Wrapped underlying scipy optimization calls in robust try/except blocks to print a warning and return default initial guesses (fail gracefully) if max evaluations are exceeded or optimization fails.

Testing & Validation

• New Regression Test: Added 4 explicit sub-tests to test_init_bvalues in tests/IVIMmodels/unit_tests/test_ivim_fit.py. It specifically catches the init failure path, the osipi_fit crash path, result key validity, and the stale-model guard.
• Test Suite Results: 1148 passed, 0 failures (Verified manually through full suite execution natively). Note: TCML_TechnionIIT_lsqBOBYQA bounds x-fails are pre-existing, tolerated algorithm limitations (strict=False) and are completely unrelated to these fixes.