CreateCombinationsScript.py python script is designed to enable you to perform simulations that test many different combinations of policy settings. Before you begin to work with this script, ensure that your
OuputVarsToExport.lst file is properly configured, as described in Selecting Ouput Variables for a Python Script.
CreateCombinationsScript.py file in a text editor such as Visual Studio Code.
Near the top of the script, the “File Names” section sets the filenames of various input or output files that will be used or created by the script, as well as the first year and the final year of the simulation. This section is shown in the screenshot below:
If you plan on only using this script to perform one series of runs (a “run set”), you can leave these lines alone. However, if you plan on doing more than one run set, you might wish to change the run results filename on line 19 for each version of the script, to avoid the possibility of the results from one set of runs overwriting the results from another run set. To do this, change “RunResults.tsv” (in the double quotes, colored orange in the screenshot above) to some other filename ending in .tsv, such as “RunSet1.tsv” (in one copy of the script), “RunSet2.tsv” (in another copy of the script), etc.
Below the “File Names” section of the script is the “Other Settings” section, as shown in the following screenshot:
The first setting is for the run name. This is used as the name for the
.vdfx (data) file that Vensim generates after each run, but this is not important because that
.vdfx file is over-written with every run that is part of a run set, so only the data from the final run of the run set will remain in that
.vdfx file after the script execution is complete. More important is that this value is included as a column in the output spreadsheet that contains results from all runs that are part of the run set. Therefore, if you plan on doing more than one run set (with different versions of this script), it is good practice to pick a different run name for each run set. For example, if you perform a run set where you test several different transportation sector policies, and another run set where you test several electricity sector policies, you could make the run names “Transportation Run Set” and “Electricity Run Set” respectively.
For every policy that is included in a run set, the output file will include a column specifying that policy setting for each run in the run set. The “MinPolicyCols” setting forces Vensim to include at least the specified number of policy columns, even if a smaller number of policies were enabled for this run set. The purpose of this setting is to allow all of the columns to line up correctly if you are performing multiple run sets that contain different numbers of enabled policies. For example, suppose in the “Transporation Run Set” discussed above, you are testing three policies, but in the “Electricity Run Set,” you are testing five policies. In the python script that defines the Transportaton Run Set, you should change the value for “MinPolicyCols” to 5. This will cause Vensim to add two blank columns to the policy section of the run results file for your Transportation Run Set. Now, if you ever wish to compare the runs from your Transportation Run Set against the runs from your Electricity Run Set, all you need to do is append the two files (or copy and paste the contents of one below the contents of the other in a spreadsheet program). If you do not use the MinPolicyCols setting, then the data columns would be off by two (such that year 2030 from the Transportation Run Set is in the same column as year 2028 from the Electricity Run Set).
In the “PolicySchedule” setting, specify the number of the policy implementation schedule to be used for this run set. For more details on policy implementation schedules, see Adjusting Policy Implementation Schedules.
Finally, in the “Policy Options” section, you can enable particular policies and adjust the settings at which they will be tested. For example, the following screenshot shows three of the transportation sector policies, which appear on lines 148-150:
Each policy has a list of properties:
- whether the policy is enabled (“True”) or disabled (“False”)
- the policy’s variable name in Vensim (with subscript settings if applicable)
- the policy’s name as used in the Python script itself, which is derived from the display name for this policy in WebAppData and the display names of any subscripts it may have
- a list of policy settings in square brackets
- a policy group name, which is not used in this script, and exists solely so the policy list has the same format as the one in
CreateContributionTestScript.py(for ease of updating these lists when the available policies in the EPS change with new EPS releases)
The only values you should edit are the enabled setting (changing “False” to “True”) and the policy setting values (changing or adding additional numbers to the set in square brackets). Although each policy by default only has two setting values in the script (zero and a non-zero value), there is no limit to the number of non-zero values you may include in the list. For example, to test five different settings for the “TDM” (transportation demand management) policy for passengers, change “False” to “True” and add the extra settings to the settings list for that policy, so line 149 in the Python script might change from:
(False,"Fraction of TDM Package Implemented[passenger]","Transportation Demand Management - Passengers",[0,1],"Transportation Demand Management"),
(True,"Fraction of TDM Package Implemented[passenger]","Transportation Demand Management - Passengers",[0,0.25,0.5,0.75,1],"Transportation Demand Management"),
Caution: Do not enable too many policies in a single run set. This will cause Vensim to attempt to perform so many runs that they will not be completed in a reasonable amount of time. On a typical Windows computer, the model can complete several runs per second. However, there are more than 300 listed policies (counting separate subscripted elements of a policy as their own policies) that appear in the Combinations Python script. If you enable 60 policies, with 2 settings each (namely, zero and a non-zero value), you will be performing 2^60 runs. If your computer completes 4 model runs each second, this will take over 9 billion years, roughly twice the age of the Earth. Limiting your run sets to no more than 10 enabled policies is a good guideline. (At 4 runs per second and 2 settings per policy, a run set with 10 enabled policies (2^10 or 1024 runs) would take a little over 4 minutes to complete.)
Running the Script in Vensim
Finally, save and run the Python script to generate a Vensim command script, then run the Vensim command script using Vensim DSS to perform the runs. The procedure is the same as for the Data Logging script, described here. There will only be a single tab-separated value results file for a single run set, by default named
RunResults.tsv. It will have one line per run for each variable (or each included element of a subscripted variable) in the
OutputVarsToExport.lst file. It will assign a run number to each run (counting up from 1), specify the policy settings for each run, and include the data for the selected variables in each year.
You may now open
RunResults.tsv in a spreadsheet program and perform analysis on the resulting dataset. For example, you could eliminate all scenarios with CO2e emissions in excess of a certain value (a cap) you have in mind for a particular year, then sort the rest from lowest to highest cost, to find the least-expensive way to comply with the carbon cap using the policies and settings you included in your run set.