I have a model in my Modelica and I use Dymola to compile this model. In my model I need the simulation information "Output Interval length". I have searched for it but I could not get the useful information. Is there any other possible way we could access simulation information.
If you are simply trying to get the results reported at specific intervals, you can use a sample operator to achieve that. That would force the solution to be computed at specific times without directly specifying something like the time step.
The important point to understand here is that a model where the behavior of the model depends on the numerical integration is highly suspect and I've never seen a case where the behavior couldn't be described without knowledge of the solution method. Said another way, "mother nature" doesn't know anything about "time steps". :-)
You could use a clocked system with an integrator.
For an Example, see File -->Libraries-->Modelica_Synchronous --> Examples --> Systems --> Controlled_mixing_unit in Dymola
There the period (i.e. in this case the timestep of the explicit Euler method) is a parameter of the periodic clock)
Modelica by design prohibits accessing any numerical solver internals, so you cannot access it. The output interval length also cannot be determined by the model in any reliable way since the solver will take internal steps longer than the output interval and then interpolate values for the result file.
You could create a function that reads the dsin.txt file and extracts that information.
Related
i'm using Epsilon Comparison Language for the first time. I am writing a code in order to compare two models, in particular i want to show some information on the default output stream console when the code finds differences between the models. I want to visualize, for example, the name of the involved rule and the differences between the fields under investigation. When the comparison ends without differences i can visualize, for example, all that i need using the matchInfo variable in a "do" block. How can i solve the problem when the code find some differences? Thanks.
ECL does not provide any built-in differencing or difference visualisation capabilities. If you need such capabilities my suggestion would be to consider using EMFCompare.
My team has a plan to apply optaplanner to existing system.
Existing system has its own rule-sets.
it tries own rule-sets one by one and pick the one as best result.
We want to start from its result as heuristics
and start to solve the problem as meta-heuristics.
We have reviewed optaplanner manual especially in repeated planning section.
but we can't find the way.
Is there a way to accept existing system's result?
your cooperation would be highly appreciated
Best regards.
For OptaPlanner, it makes no difference where the input solution comes from. Consider the following code:
MyPlanningSolution solution = readSolution();
Solver<MyPlanningSolution> solver = SolverFactory.create(...)
.buildSolver();
solver.solve(solution);
Notice how solution comes from a custom method, readSolution(). Whether that method generates the initial solution randomly, reads it from a file, from a database etc., that does not matter to the solver. It also does not matter if it is initialized or not - construction heuristic, if configured, will just skip the initialized entities.
That means you have absolute freedom in how you create your initial solution and, to the solver, they all look the same.
In:
https://docs.omnetpp.org/tutorials/tictoc/part5/
and
https://doc.omnetpp.org/omnetpp/manual/#sec:simple-modules:declaring-statistics
it's shown how network statistics can be processed after a simulation.
Is it possible to get network parameters dynamically?
TL;DR: Use signals (not statistics) and hook up your own simple module on these signals and compute the required statistics in that module.
You cannot access the value of #statistics in your code, and there is a reason for this as this would be an anti pattern. NED based statistics were introduced as a method to add calculations and measurements to your model without modifying your models behavior and code. This means that statistics are NOT considered part of a model, but rather they are considered as a configuration. Changing a statistics (i.e. deciding that you want to measure something else) should never change the behavior of your model. That's why the actual value of a given statistic is not exposed (easily) to the C++ code. You could dig them out, but it is highly discouraged.
Now, this does not mean that what you want to achieve is not legitimate but the actual statistics gathering must be an integral part of your model. I.e. you should not aim for using built-in statistics, but rather create an explicit statistics gathering submodule that should hook up on the necessary signals (https://doc.omnetpp.org/omnetpp/manual/#sec:simple-modules:subscribing-to-signals) and do the actual statistics computation you need in its C++ code. After that, other modules are free to access this information and make decisions based on that.
I read about how FoundationDB does its network testing/simulation here: http://www.slideshare.net/FoundationDB/deterministic-simulation-testing
I would like to implement something very similar, but cannot figure out how they actually did implement it. How would one go about writing, for example, a C++ class that does what they do. Is it possible to do the kind of simulation they do without doing any code generation (as they presumeably do)?
Also: How can a simulation be repeated, if it contains random events?? Each time the simulation would require to choose a new random value and thus be not the same run as the one before. Maybe I am missing something here...hope somebody can shed a bit of light on the matter.
You can find a little bit more detail in the talk that went along with those slides here: https://www.youtube.com/watch?v=4fFDFbi3toc
As for the determinism question, you're right that a simulation cannot be repeated exactly unless all possible sources of randomness and other non-determinism are carefully controlled. To that end:
(1) Generate all random numbers from a PRNG that you seed with a known value.
(2) Avoid any sort of branching or conditionals based on facts about the world which you don't control (e.g. the time of day, the load on the machine, etc.), or if you can't help that, then pseudo-randomly simulate those things too.
(3) Ensure that whatever mechanism you pick for concurrency has a mode in which it can guarantee a deterministic execution order.
Since it's easy to mess all those things up, you'll also want to have a way of checking whether determinism has been violated.
All of this is covered in greater detail in the talk that I linked above.
In the sims I've built the biggest issue with repeatability ends up being proper seed management (as per the previous answer). You want your simulations to give different results only when you supply a different seed to your random number generators than before.
After that the biggest issue I've seen seems tends to be making sure you don't iterate over collections with nondeterministic ordering. For instance, in Java, you'd use a LinkedHashMap instead of a HashMap.
In official documentation I can't find any information how to write conditional statements for java.util.Date type fact fields in guided rules. For example how to compare such field to current date, check if it is equal omitting time, or check if it is date before some time from now?
Drools isn't a real-time program and it doesn't have an innate idea of Time or Now. If you need to investigate relations of some fact property w.r.t. some point of time X, you'll have to establish a fact carrying X as its data, and write your rules based on that.
A more or less coarse approximation of a fact representing Now can be made using timers. You can implement a rule that modifies a fact containing a value representing Time (e.g. java.util.Date) every second, or less frequently.
Blending out the time of the day is something you'll have to do using Java or DRL functions. Alternatively, if it is days you are interested in, use some custom class representing days, with some suitable day 1 defined by you.
you can give like
inputDate>=11-Nov-2014
provide your current date to inputDate rule input Fact variable.