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ENH: Monte Carlo Analysis Enhancements #269
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EnhancementNew feature or request, including adjustments in current codesNew feature or request, including adjustments in current codesMonte CarloMonte Carlo and related contentsMonte Carlo and related contents
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EnhancementNew feature or request, including adjustments in current codesNew feature or request, including adjustments in current codesMonte CarloMonte Carlo and related contentsMonte Carlo and related contents
Everyone loves the fact that RocketPy can be quite easily wrapped to run Monte Carlo simulations to carry on dispersion analysis.
However, this experience quickly becomes hard as the analysis complexity increases. Usually, lack of a good stopping criteria combined with long simulation times are the main issues.
Therefore, the following requirements are specified to improve general Monte Carlo simulations with RocketPy.
Requirements
New features
Corrections:
export_ellipses_to_kmlfunctiontimezone,number_of_grains,nose_kindto be variedStochasticFlight.create_objectto avoid unnecessary calls.StochasticModel.__init__()method_validate_airfoilmethod to a child classProposed Milestone
v1.X (This means we will avoid breaking changes as much as possible)
Additional comments
Ref.1 -> There are certain quantities, e.g. wind speed, that the user might have a more accurate distribution (maybe built empirically) that does not fit Numpy's provided distributions. The user could provide a "sampler," i.e. a function that takes an integer sample_size as input and outputs that amount of samples according to his distribution.)