Presenters-0423: Difference between revisions
From CSDMS
m Add youtube views template if missing |
m Text replacement - "\|CSDMS meeting youtube views=\{\{(Youtube_[^}]+)\}\}" to "|CSDMS meeting youtube views={{#explode:{{$1}}| |0}} |CSDMS meeting youtube AverageViews={{#explode:{{$1}}| |1}}" |
||
Line 14: | Line 14: | ||
|CSDMS meeting abstract presentation=Interested in which variables influence your model outcome? SALib (Sensitivity Analysis Library) provides commonly used sensitivity analysis methods implemented in a Python programming language package. In this clinic we will use these methods with example models to apportion uncertainty in model output to model variables. We will use models built with the Landlab Earth-surface dynamics framework, but the analyses can be easily adapted for other model software. No prior experience with Landlab or Python is necessary. | |CSDMS meeting abstract presentation=Interested in which variables influence your model outcome? SALib (Sensitivity Analysis Library) provides commonly used sensitivity analysis methods implemented in a Python programming language package. In this clinic we will use these methods with example models to apportion uncertainty in model output to model variables. We will use models built with the Landlab Earth-surface dynamics framework, but the analyses can be easily adapted for other model software. No prior experience with Landlab or Python is necessary. | ||
|CSDMS meeting youtube code=0 | |CSDMS meeting youtube code=0 | ||
|CSDMS meeting youtube views={{Youtube_0}} | |CSDMS meeting youtube views={{#explode:{{Youtube_0}}| |0}} | ||
|CSDMS meeting youtube AverageViews={{#explode:{{Youtube_0}}| |1}} | |||
|CSDMS meeting participants=0 | |CSDMS meeting participants=0 | ||
}} | }} |
Latest revision as of 16:33, 11 June 2025
CSDMS3.0 - Bridging Boundaries
Model sensitivity analysis using SALib
Abstract
Interested in which variables influence your model outcome? SALib (Sensitivity Analysis Library) provides commonly used sensitivity analysis methods implemented in a Python programming language package. In this clinic we will use these methods with example models to apportion uncertainty in model output to model variables. We will use models built with the Landlab Earth-surface dynamics framework, but the analyses can be easily adapted for other model software. No prior experience with Landlab or Python is necessary.
Please acknowledge the original contributors when you are using this material. If there are any copyright issues, please let us know (CSDMSweb@colorado.edu) and we will respond as soon as possible.
Of interest for: