Always use an initial guess in bounds for the sources#44
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lispandfound merged 2 commits intomainfrom Jun 4, 2025
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Pull Request Overview
Addresses the issue where the default optimization starting point (0.5,0.5,…,0.5) could lie outside user-specified bounds by always initializing the solver within the provided ranges.
- Compute midpoint-based initial guesses for both source A and source B parameters.
- Replace the hardcoded default
[1/2, 1/2, 1/2, 1/2]with the newly computed initial points.
Comments suppressed due to low confidence (2)
source_modelling/sources.py:1422
- Consider adding a unit test for cases where the default (0.5, 0.5, 0.5, 0.5) lies outside the provided bounds to ensure the solver correctly uses the new midpoint-based initial guesses.
initial_point_a = (
source_modelling/sources.py:1421
- [nitpick] Add a brief comment above the initial-point computation explaining that you’re choosing the midpoint of each parameter’s bounds as the initial guess to guarantee feasibility.
res = sp.optimize.least_squares(
lispandfound
requested review from
AndrewRidden-Harper,
claudio525,
joelridden and
sungeunbae
joelridden
approved these changes
May 25, 2025
sungeunbae
reviewed
May 26, 2025
| res = sp.optimize.least_squares( | ||
| fault_coordinate_distance, | ||
| np.array([1 / 2, 1 / 2, 1 / 2, 1 / 2]), | ||
| np.array([*initial_point_a, *initial_point_b]), |
sungeunbae
approved these changes
May 26, 2025
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Default initial guess was (1/2,1/2), which doesn't work if the constraints on the optimisation are say (0.7-0.9, 0.6-1.0), as then the default optimisation point is not in the bounds for the process.