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sensitivity_analysis_toolbox_example_-_cow [2022/09/21 11:26] mina |
sensitivity_analysis_toolbox_example_-_cow [2022/09/29 12:39] mina old revision restored (2022/09/29 12:37) |
**Selection of probabilistic parameters** | **Selection of probabilistic parameters** |
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|{{:sensitivitytoolboxparameterselectiontab1.png?400|}}{{:sensitivitytoolboxparameterselectiontab2.png?400|}}|Go to Settings->Parameter selection to open the [[Parameter_selection_view|Parameter selection view]]. Here, the parameters for which the sensitivity analysis should be run are selected.\\ \\ //Select the five parameters in the table above by moving them to the right in the parameter selection view//| | |{{:sensitivitytoolboxparameterselectiontab1.png?400|}}{{:sensitivitytoolboxparameterselectiontab2.png?400|}}|Go to **Select** tab to open the [[Parameter_selection_view|Parameter selection view]]. Here, the parameters for which the sensitivity analysis should be run are selected.\\ \\ //Select the five parameters in the table above by moving them to the right in the parameter selection view//| |
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**Selection of Sensitivity analysis method** | **Selection of Sensitivity analysis method** |
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|{{:sensitivityanalysismethod.png?400|}}|Go to Settings->Method to open the [[Sensitivity_analysis_method_view|Sensitivity analysis method view]]. Here, the [[Sensitivity_analysis_methods|Sensitivity analysis method]] and its settings is selected.\\\\ \\\\ //Select the method Probabilistic with the following settings:\\ \\ Base sample size: 1000\\\\ Sampling type: Latin Hypercube\\\\ Calculate second order indices: Unchecked\\\\ Seed: Auto\\\\ //| | |{{:sensitivityanalysismethod.png?400|}}|Go to **Method** tab to open the [[Sensitivity_analysis_method_view|Sensitivity analysis method view]]. Here, the [[Sensitivity_analysis_methods|Sensitivity analysis method]] and its settings is selected.\\ \\ //Select the method Probabilistic with the following settings:\\ \\ Base sample size: 1000\\ Sampling type: Latin Hypercube\\ Calculate second order indices: Unchecked\\ Seed: Auto\\ //| |
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**Modification of parameter values (optional)** | **Modification of parameter values (optional)** |
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|{{:SensitivityToolboxParameterValuesTab.png|SensitivityToolboxParameterValuesTab}}|Go to Settings->Parameter values to open the Parameter values view. Here, the Parameter values can be reviewed and changed if necessary.\\\\ \\\\ //Keep the values set earlier.\\\\ \\\\ //| | |{{:modificationofparametervalues.png?400|}}|Go to **Values** to open the Parameter values view. Here, the Parameter values can be reviewed and changed if necessary.\\ \\ //Keep the values set earlier.\\ \\ //| |
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**Generate parameter samples** | **Generate parameter samples** |
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|{{:SensitivityToolboxInputsTab.png|SensitivityToolboxInputsTab}}|Go to Settings->Inputs to open the Input samples view. Here, samples for the selected parameters can be generated, inspected and plotted.\\\\ \\\\ //Press Generate to generate the input samples.\\\\ \\\\ // After successful generation, the tree should show the model inputs and outputs.| | |{{:sensitivitytoolboxinputstab8.png?400|}}{{:sensitivitytoolboxinputstab2.png?400|}}|Go to **Inputs** tab to open the Input samples view. Here, samples for the selected parameters can be generated, inspected and plotted.\\ \\ //Press Generate to generate the input samples.\\ \\ // After successful generation, the tree should show the model inputs and outputs.| |
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**Simulate model outputs** | **Simulate model outputs** |
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|{{:SensitivityToolboxOutputsTab.png|SensitivityToolboxOutputsTab}}|Go to Settings->Outputs to open the Output samples view. Here, samples for the model outputs can be simulated, inspected and plotted.\\\\ \\\\ //Press Simulate to generate the output samples.//\\\\ \\\\ After successful generation, the tree should show the model inputs and outputs.| | |{{:sensitivitytoolboxoutputstab1.png?400|}}{{:sensitivitytoolboxoutputstab2.png?400|}}|Go to **Outputs** tab to open the Output samples view. Here, samples for the model outputs can be simulated, inspected and plotted.\\ \\ //Press Simulate to generate the output samples.//\\ \\ After successful generation, the tree should show the model inputs and outputs.| |
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**Calculate and inspect the sensitivity analysis result** | **Calculate and inspect the sensitivity analysis result** |
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{{ :SensitivityToolboxResultsTab.png|SensitivityToolboxResultsTab}} | {{:sensitivityanalysisresultstoolbar.png?700|}} \\ |
Go to Settings->Results to open the Results view. Here, a shortcut is given to generat both inputs and outputs by clicking generate inputs & outputs. In this view, sensitivity and correlation measures can be inspected in charts and/or tables\\ | Go to the **Results** tab to show the Results view. Here, a shortcut is given to general both inputs and outputs by clicking generate inputs & outputs. In this view, sensitivity and correlation measures can be inspected in charts and/or tables\\ |
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//In the tree, select C<sub>beef</sub> and C<sub>milk</sub>//\\ | //In the tree, select C<sub>beef</sub> and C<sub>milk</sub>//\\ |
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A [[Correlation_table|Correlation table]] is created for the selected outputs, displaying the sensitivity indices calculated by the probabilistic method.\\ | A [[Correlation_table|Correlation table]] is created for the selected outputs, displaying the sensitivity indices calculated by the probabilistic method. Select the Transformation from the drop down list under the table and put it on Rank.\\ |
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//Now, select C<sub>beef</sub> and click [[Correlation_pie_chart|Correlation pie chart]]//\\ | //Now, select C<sub>beef</sub> and click [[Correlation_pie_chart|Correlation pie chart]]. Select the Transformation from the drop down list under the table and put it on Rank.//\\ |
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A [[Correlation_pie_chart|Correlation pie chart]] is created and for C<sub>milk</sub> and displays the first order sensitivity index of all parameters on the selected output. The same can be done for C<sub>beef</sub>\\ | A [[Correlation_pie_chart|Correlation pie chart]] is created and for C<sub>milk</sub> and displays the first order sensitivity index of all parameters on the selected output. The same can be done for C<sub>beef</sub>\\ |