I have a simulation with a lot of random components, so I would like to run many simulations and average the results (the result is determined by a variable called score).
How would you do this in Netlogo?
Currently I'm working on a program that will export the results to csv, then I plan to use python/excel to average them. I don't like this because I want to run 100+ simulations (so there will be 100+ files)... I'm hoping there is a better solution
EDIT or an implementation of what I described (I have to relearn enough python/vba to solve this, so it's going to take me some time)
This should be simple enough if you use BehaviorSpace.
In your experiment definition, put score in the Measure runs using these reporters textbox and uncheck Measure run at every step.
When you run your experiment, save your results using Table output. It will produce a csv that you can open in your spreadsheet application. From there, producing an average of the score column should be trivial.
Related
Is there any way in Modelica, to reduce the sampeling during simulations? I have a DCDC converter with high frequency, consequently generating huge dataset. I am wondering, if there is any way to reduce the size of the dataset during simulation/exportation?
Thanks
Trying to create smaller dataset from models that generate huge ones (models with high frequencies).
Basically when you simulate, do not press the -> press the S on the toolbar and you get several tabs and the ones you care about are General and Output.
In General you can specify the number of intervals to reduce the data stored. It will only be stored at each interval.
In the Output you can say not to store events for example. You can also filter out variables that you are not interested in to reduce the result file size. Note that "Equidistant Time Grid" is activated by default, if not this would generate quite a lot of output maybe even several times per interval.
See more here about the things you have in General/Output:
https://openmodelica.org/doc/OpenModelicaUsersGuide/1.20/omedit.html#simulating-a-model
By including our desired variables in the Variable Filter in Output tab one can reduce the size of the output file without compromising the interval points. Each entry follows a POSIX EXTENDED regular expression format, say:
for a list of x,y,z it is ^x|y|z$. Another best practice could be unchecking the flag Store variables at Events. The best answer for this question is already answered by Adrian Pop.
I am having trouble with the coding process or steps to extract data from the main and onto the parameter variation experiment in anylogic. I am currently working on total evacuation time due to random fire obstruction.
For now I have successfully obtained the total max evacuation time for 100 runs in my study but I also need another set of data for the number of exits obstructed during each run. My main has the collection (of 3 exits) availableExits and I can see what is obstructed during the simulation.
Furthermore, I would like to obtain data for the number of people evacuating at a particular time (for example number of pedestrians using exit at 120 seconds). I can see this in main from timeMeasureEnd and creating a histogram distribution graph, which shows number of pedestrians escaping at each time. I've managed to create one in parameter variation but when I run the experiment, I am unable to store or view the data as it keeps changing after every run.
Here is the code from analysis Histogram Data which is entered in after simulation run
data = root.timeMeasureEnd.distribution;
i would recommend to add a dataset to your main which would store all the values you want to keep in parameter variation. Dataset differs from histogram data in a way that it doesnt aggregate, it is just a raw array of values, and later you will not have a problem of "aggregating aggregated data".
So, after each simulation run you can access your dataset in main via "root" reference (as you are already doing it) and loop through it to store all the values one by one.
I wish to store record the output of a NetLogo simulation run in two ways:
Output of some functions at the end of the simulation creating a single .csv for all simulation runs.(This is fairly easy to accomplish)
Output of some variables of an agentset at the end of each tick and store the values in a separate .csv for each simulation.
I don't know how to create a separate .csv for each simulation run and also accomplish the two at the same time.
In terms of the efficiency, while recording the data at each tick, does NetLogo write to .csv directly or stores in memory and writes once in the end?
Note: I run the simulations on HPC using behavior space.
Tries:
Using RNetLogo I can accomplish this, but it is too slow due to the inherent time in data transfer between R and NetLogo. Also, running NetLogo in parallel from R seems difficult to do
Tried writing an if condition in reporter tab in behavior space GUI, doesn't work. It seems allow only reporters.
EDIT:
Link same question asked at d-level
I want to run a simulation which includes SimEvent blocks (thus only Normal option is available for sim run) for a large number of times, like at least 1000. When I use sim it compiles the program every time and I wonder if there is any other solution which just run the simulation repeatedly in a faster way. I disabled Rebuild option from Configuration Parameter and it does make it faster but still takes ages to run for around 100 times.
And single simulation time is not long at all.
Thank you!
It's difficult to say why the model compiles every time without actually seeing the model and what's inside it. However, the Parallel Computing Toolbox provides you with the ability to distribute the iterations of your model across several cores, or even several machines (with the MATLAB Distributed Computing Server). See Run Parallel Simulations in the documentation for more details.
I have a set of data for the past 5 years. Approx 7000 rows of data with features that are binary {yes/no} or are multi-classed {product A, B, C} A total of about 20+ features.
I am trying to make a program (or one time analysis project) to determine (predict) the product shipdate(shipping delay days) based on this historical data. I have 2 columns that indicate when a product was planned to be shipped and another column of when it was actually shipped! Currently.
I'm wondering how I can make a prediction program that determines based on the historic data when new data input of a product will expect to ship. I don't care about a getting a specific date but even just a program that can tell me number of delay days to add...
I took an ML class a while back and I wasn't sure how to start something like this. Any advice? Plus the closest thing to this I can think of is an image recognition assignment using NN. but that was too easy here I have to deal with a date instead of pixel white/black.... I used Matlab back in the day (I still know how to use it) but I just downloaded Weka data mining tool.
I was thinking of a neural network but I'm not sure how to set it up to have my program give me a the expected delay time (# of days/month) from the inputed ship date.
Basically,
I want to input (size = 5, prod = A, ....,expected ship date = jan 1st)
and the program returns the number of days to add as a delay onto my expected ship date given the historical trends...
Would appreciate any any help on how start something like this the correct/easiest/best way... Thanks in advance.
If you use weka, then get your input/label data into the arff format and then you try out all the different regressors (this is a regression problem after all). To avoid having to do too much programming quite yet (if you are just in an exploratory phase), use the weka experimenter which has a GUI for trying out a whole bunch of regressors on your dataset.
Then when you find one that does something expected and you want to do some more data analysis using MATLAB, then you can use a weka/matlab interface.