Fixing an issue with time domain bootstrapped uncertanties#487
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Reduces uncertainty calculation for bootstrapped uncertainties. Previously it was always 1000 samples. This saves around 4s, when using <100 samples.
-`test_fit_model_confidence_intervals` increased the number of bootstraps so it passes -`test_fit_modelUncert` expanded to test the bootstrapped
stestoll
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Jan 9, 2025
HKaras
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Mar 18, 2026
* Added modelUncert for bootstrapped * Remove unused input * Always create modelUncert quantification * Allow bootstrap resampling to be variable in propagation * Update examples * Add test for modelUncert output * Minor docstring update * Bootrstap Uncertainty sampling reduction Reduces uncertainty calculation for bootstrapped uncertainties. Previously it was always 1000 samples. This saves around 4s, when using <100 samples. * Add model copying * General improvemements * Fixes issues with functions being deep copyied * Test update -`test_fit_model_confidence_intervals` increased the number of bootstraps so it passes -`test_fit_modelUncert` expanded to test the bootstrapped * Correct number of bootstrap samples * Fix gaussian normalisation issues * Bug fix in test * multi-guass_background fix removal * Fix example for latest matplotlib
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