Random BuiltIn Function in Stella

1. Random BuiltIn Function in Stella

2. RANDOM(<min>, <max>, [<seed>]) The RANDOM builtin generates a series of uniformly distributed random numbers between min and max. RANDOM samples a new random number in each iteration of a model run. If you wish to replicate the stream of random numbers, specify seed as an integer between 1 and 32767. To replicate a simulation, all entities that use statistical functions must have seeds specified. Each entity using a statistical function should use a separate seed value.

3. Examples: RANDOM(0,1) creates a non-replicable uniformly distributed stream of numbers between 0 and 1. RANDOM(0,1,147) creates a replicable uniformly distributed stream of numbers between 0 and 1. RANDOM(0,10,12) gives a replicable uniformly distributed stream of numbers between 0 and 10. RANDOM(10,13,12) gives a replicable uniformly distributed stream of numbers between 10 and 13.

4. Build the flower model of Chapter 6 to reproduce the output shown on the next page. Or get it from http://www.atmosedu.com/WSU/esrp310-550/PP/Flowers.STM

6. Now add a new converter for temperature and connect it To the intrinsic growth rate. In the original model the intrinsic growth rate was fixed at 1.0. Here we’ll let Temperature be Random (20,30,999) and intrinsic growth rate = temperature/25.0 We added the seed here so all simulations will look the same.

7. Paste your resulting graphs of Flower area, growth, and decay here.

8. Try letting Temperature be Random (15,35,999) and intrinsic growth rate = temperature/25.0 What do you expect to be different for this new simulation? ANSWER

9. Paste your resulting graphs of Flower area, growth, and decay here.

10. NORMAL(<mean>,<std>, [<seed>]) The NORMAL builtin generates a series of normally distributed random numbers with a specified mean and std (standard deviation). NORMAL samples a new random number in each iteration of a simulation. If you wish to replicate the stream of random numbers, specify seed as an integer between 1 and 32767. To replicate a simulation, all entities that use statistical functions must have seeds specified. Each entity using a statistical function should use a separate seed value.

11. Examples: NORMAL(0,1) gives a non-replicable normally distributed stream of numbers (mean=0, standard deviation=1) NORMAL(0,1,147) gives a replicable normally distributed stream of numbers (mean=0, standard deviation=1) NORMAL(5,1,12) gives a replicable normally distributed stream of numbers (mean=5, standard deviation=1) NORMAL(10,5,102) gives a replicable normally distributed stream of numbers (mean=10, standard deviation=5)

12. Now let Temperature be Normal (25,5,999) and intrinsic growth rate = temperature/25.0 We added the seed here so all simulations will look the same and make it easier for your instructor to see if you got things set correctly.

13. Paste your resulting graphs of Flower area, growth, and decay here.

14. Now let Temperature be Normal (25,10,999) and intrinsic growth rate = temperature/25.0 What do you expect to be different for this new simulation? ANSWER

15. Paste your resulting graphs of Flower area, growth, and decay here.

16. Download the 3rd version of the MonoLake Model. http://www.atmosedu.com/WSU/esrp310-550/monoLake/MonoLake3.STM This has a comparitive graph set for volume in the lake.

17. Run the model once to get a graph of water in the lake with a fixed export of 100. Now run with export set to Normal (100,50,999) . Run this 7 times.(don’t expect big things here) Now run with export set to Normal (100,50) . Run this 7 times

18. Paste your resulting graphs of Flower area, growth, and decay here.

19. Comment on the advantages and disadvantage of the seed