I am trying to build a model that will have slightly different equations based on whether or not certain components exist (in my case, fluid ports).
A code like the following will not work:
parameter Boolean use_component=false;
Component component if use_component;
equation
if use_component then
component.x = 0;
end if;
How can I work around this?
If you want to use condition components, there are some restrictions you need to be aware of. Section 4.4.5 of the Modelica 3.3 specification sums it up nicely. It says "If the condition is false, the component, its modifiers, and any connect equations
involving the component, are removed". I'll show you how to use this to solve your problem in just a second, but first I want to explain why your solution doesn't work.
The issue has to do with checking the model. In your case, it is obvious that the equation component.x and the component component either both exist or neither exist. That is because you have tied them to the same Boolean variable. But what if you had don't this:
parameter Real some_number;
Component component if some_number*some_number>4.0;
equation
if some_number>=-2 and some_number<=2 then
component.x = 0;
end if;
We can see that this logically identical to your case. There is no chance for component.x to exist when component is absent. But can we prove such things in general? No.
So, when conditional components were introduced, conservative semantics were implemented which can always trivially ensure that the sets of variables and equations involved never get "out of sync".
Let us to return to what the specification says: "If the condition is false, the component, its modifiers, and any connect equations
involving the component, are removed"
For your case, the solution could potentially be quite simple. Depending on how you declare "x", you could just add a modification to component, i.e.
parameter Boolean use_component=false;
Component component(x=0) if use_component;
The elegance of this is that the modification only applies to component and if component isn't present, neither is the modification (equation). So the variable x and its associated equation are "in sync". But this doesn't work for all cases (IIRC, x has to have an input qualifier for this to work...maybe that is possible in your case?).
There are two remaining alternatives. First, put the equation component.x inside component. The second is to introduce a connector on component that, if connected, will generate the equation you want. As with the modification case (this is not a coincidence), you could associate x with an input connector of some kind and then do this:
parameter Boolean use_component;
Component component if use_component;
Constant zero(k=0);
equation
connect(k.y, component.x);
Now, I could imagine that after considering all three cases (modification, internalize equation and use connect), you come to the conclusion that none of them will work. If this is the case, then I would humbly suggest that you have an issue with how you have designed the component. The reason these restrictions arise is related to the necessity to check components by themselves for correctness. This requires that the component be complete ("balanced" in the terminology of the specification).
If you cannot solve the problem with approaches I mentioned above, then I suspect you really have a balancing issue and that you probably need to redefine the boundaries of your component somehow. If this is the case, I would suggest you open another question here with details of what you are trying to do.
I think that the reason why this will not work is that the parser will look for the declaration of the variable "component.x" that, if the component is not active, does not exist. It does not work even if you insert the "Evaluate=true" in the annotation.
The cleanest solution in my opinion is to work at equation level and enable different sets of equations in the same block. You can create a wrapper model with the correct connectors and paramenters, and then if it is a causal model for example you can use replaceable classes in order to parameterize the models as functions, or else, in case of acausal models, put the equations inside if statements.
Another possible workaround is to place two different models inside one block, so you can use their variables into the equation section, and then build up conditional connections that will enable the usage of the block with the choosen behaviour. In other words you can build up a "wrap model" with two blocks inside, and then place the connection equations to the connectors of the wrap model inside if statements. Remember to build up the model so that there will be a consistent system of quations even for the blocks that are not used.
But this is not the best solution, because if the blocks are big you will have to wait longer time for compilation since everything will be compiled.
I hope this will help,
Marco
You can also make a dummy component that is not visible in the graphical layer:
connector DummyHeatPort
"Dummy heatport to facilitate optional heatport. Use this with a conditional heatport by connecting it to the heatport. Then use the -DummyHeatPort.Q_flow in the thermal energy balance."
Modelica.SIunits.Temperature T "Port temperature";
flow Modelica.SIunits.HeatFlowRate Q_flow
"Heat flow rate (positive if flowing from outside into the component)";
end DummyHeatPort;
Then when this gets used in a two port model
Modelica.Thermal.HeatTransfer.Interfaces.HeatPort_a heatport if use_heat_port;
DummyHeatPort dummy_heatport;
...
equation
flowport_a.H_flow + flowport_b.H_flow - dummy_heatport.Q_flow = storage
"thermal energy balance";
connect(dummy_heatport, heatport);
This way the heatport gets used if present but does not cause an error otherwise.
Related
I'm using TF-Agents library for reinforcement learning,
and I would like to take into account that, for a given state,
some actions are invalid.
How can this be implemented?
Should I define a "observation_and_action_constraint_splitter" function when
creating the DqnAgent?
If yes: do you know any tutorial on this?
Yes you need to define the function, pass it to the agent and also appropriately change the environment output so that the function can work with it. I am not aware on any tutorials on this, however you can look at this repo I have been working on.
Note that it is very messy and a lot of the files in there actually are not being used and the docstrings are terrible and often wrong (I forked this and didn't bother to sort everything out). However it is definetly working correctly. The parts that are relevant to your question are:
rl_env.py in the HanabiEnv.__init__ where the _observation_spec is defined as a dictionary of ArraySpecs (here). You can ignore game_obs, hand_obs and knowledge_obs which are used to run the environment verbosely, they are not fed to the agent.
rl_env.py in the HanabiEnv._reset at line 110 gives an idea of how the timestep observations are constructed and returned from the environment. legal_moves are passed through a np.logical_not since my specific environment marks legal_moves with 0 and illegal ones with -inf; whilst TF-Agents expects a 1/True for a legal move. My vector when cast to bool would therefore result in the exact opposite of what it should be for TF-agents.
These observations will then be fed to the observation_and_action_constraint_splitter in utility.py (here) where a tuple containing the observations and the action constraints is returned. Note that game_obs, hand_obs and knowledge_obs are implicitly thrown away (and not fed to the agent as previosuly mentioned.
Finally this observation_and_action_constraint_splitter is fed to the agent in utility.py in the create_agent function at line 198 for example.
Enterprise Architect 13.5.
I made MDG technology extending Object metatype. I have a shape script for my stereotype working well. I need to print several predefined run-state parameters for element. Is it possible to access to run-state params within Shape ?
As Geert already commented there is no direct way to get the runstate variables from an object. You might send a feature request to Sparx. But I'm pretty sure you can't hold your breath long enough to see it in time (if at all).
So if you really need the runstate in the script the only way is to use an add-in. It's actually not too difficult to create one and Geert has a nice intro how to create it in 10 minutes. In your shape script you can print a string restult returned from an operation like
print("#addin:myAddIn,pFunc1#")
where myAddIn is the name of the registered operation and pFunc1 is a parameter you pass to it. In order to control the script flow you can use
hasproperty('addin:myAddIn,pFunc2','1')
which evaluates the returned string to match or not match the string 1.
I once got that to work with no too much hassle. But until now I never had the real need to use it somewhere in production. Know that the addin is called from the interpreted script for each shaped element on the diagram and might (dramatically) affect rendering times.
I am getting a Duplicate tag error when I try to write out histogram summaries for a multi-layer network that I generate procedurally. I think that the problem might be related to naming. Imagine code like the following:
with tf.name_scope(some_unique_name):
...
_ = tf.histogram_summary('weights', kernel_weights)
I'd naively assumed that 'weights' would be scoped to some_unique_name but I'm suspecting that it is not. Are summary names independent of name_scope?
As Dave points out, the tag argument to tf.histogram_summary(tag, ...) is indeed independent of the current name scope. Part of the reason for this is that the tag may be a string Tensor (i.e. computed by part of your graph), whereas name scopes are a purely client-side construct (i.e. Python-only), so there's no good way to make the scoping work consistently across the two modes of use.
However, if you're using TensorFlow build from source (and should be available in the next release, 0.8.0), you can use the following recipe to scope your tags (using Graph.unique_name(..., mark_as_used=False)):
with tf.name_scope(some_unique_name):
# ...
tf.histogram_summary(
tf.get_default_graph().unique_name('weights', mark_as_used=False),
kernel_weights)
Alternatively, you can do the following in the current version:
with tf.name_scope(some_unique_name) as scope:
# ...
tf.histogram_summary(scope + 'weights', kernel_weights)
They are.
I'm with you in thinking this is a bug, but I haven't run it past the designers of the op yet. Go ahead and open an issue for it on GitHub!
(I've run into this also and found it terribly annoying -- it prevents reuse of the model without deliberately parameterizing the summary op invocations.)
This might be an odd question, but I'm looking for a word to use in a function name. I'm normally good at coming up with succinct, meaningful function names, but this one has me stumped so I thought I'd appeal for help.
The function will take some desired state as an argument and compare it to the current state. If no change is needed, the function will exit normally without doing anything. Otherwise, the function will take some action to achieve the desired state.
For example, if wanted to make sure the front door was closed, i might say:
my_house.<something>_front_door('closed')
What word or term should use in place of the something? I'd like it to be short, readable, and minimize the astonishment factor.
A couple clarifying points...
I would want someone calling the function to intuitively know they didn't need to wrap the function an 'if' that checks the current state. For example, this would be bad:
if my_house.front_door_is_open():
my_house.<something>_front_door('closed')
Also, they should know that the function won't throw an exception if the desired state matches the current state. So this should never happen:
try:
my_house.<something>_front_door('closed')
except DoorWasAlreadyClosedException:
pass
Here are some options I've considered:
my_house.set_front_door('closed')
my_house.setne_front_door('closed') # ne=not equal, from the setne x86 instruction
my_house.ensure_front_door('closed')
my_house.configure_front_door('closed')
my_house.update_front_door('closed')
my_house.make_front_door('closed')
my_house.remediate_front_door('closed')
And I'm open to other forms, but most I've thought of don't improve readability. Such as...
my_house.ensure_front_door_is('closed')
my_house.conditionally_update_front_door('closed')
my_house.change_front_door_if_needed('closed')
Thanks for any input!
I would use "ensure" as its succinct, descriptive and to the point:
EnsureCustomerExists(CustomerID)
EnsureDoorState(DoorStates.Closed)
EnsureUserInterface(GUIStates.Disabled)
Interesting question!
From the info that you have supplied, it seems to me that setstate (or simply set, if you are setting other things than states) would be fine, though ensure is good if you want to really emphasize the redundancy of an if.
To me it is however perfectly intuitive that setting a state does not throw an exception, or require an if. Think of setting the state of any other variable:
In C:
int i;
i = 5; // Would you expect this to throw an exception if i was already 5?
// Would you write
if (i != 5)
i = 5;
// ?
Also it only takes about one sentence to document this behaviour:
The function does nothing if the
current state equals the requested
state.
EDIT: Actually, thinking about it, if it is really important to you (for some reason) that the user is not confused about this, I would in fact pick ensure (or some other non-standard name). Why? Because as a user, a name like that would make me scratch my head a bit and look up the documentation ("This is more than just an ordinary set-function, apparently").
EDIT 2: Only you know how you design your programs, and which function name fits in best. From what you are saying, it seems like your setting functions sometimes throw exceptions, and you need to name a setting function that doesn't - e.g. set_missile_target. If that is the case, I think you should consider the set_if, set_when, set_cond or cond_set names. Which one would kind of depend on the rest of your code. I would also add that one line of documentation (or two, if you're generous), which clarifies the whole thing.
For example:
// Sets missile target if current target is not already the requested target,
// in which case it does nothing. No exceptions are thrown.
function cond_set_missile_target ()
or function cond_set_MissileTarget ()
or function condSet_MissileTarget ()
or function condSetMissileTarget ()
ensure is not so bad, but to me it implies only that there is additional logic required to set the state (e.g. multiple states tied together, or other complications). It helps to make the user avoid adding unnecessary ifs, but it does not help much with the exception issue. I would expect an ensure function to throw an exception sooner than a set function, since the ensure function clearly has more responsibilities for, well, ensuring that this setting operation is in fact done right.
I'd go for ensure for the function you describe. I'd also use camelCase, but I suppose you may be in a language that prefers underscores.
You could always document (shock!) your API so that others don't make the mistakes you describe.
In algebra if I make the statement x + y = 3, the variables I used will hold the values either 2 and 1 or 1 and 2. I know that assignment in programming is not the same thing, but I got to wondering. If I wanted to represent the value of, say, a quantumly weird particle, I would want my variable to have two values at the same time and to have it resolve into one or the other later. Or maybe I'm just dreaming?
Is it possible to say something like i = 3 or 2;?
This is one of the features planned for Perl 6 (junctions), with syntax that should look like my $a = 1|2|3;
If ever implemented, it would work intuitively, like $a==1 being true at the same time as $a==2. Also, for example, $a+1 would give you a value of 2|3|4.
This feature is actually available in Perl5 as well through Perl6::Junction and Quantum::Superpositions modules, but without the syntax sugar (through 'functions' all and any).
At least for comparison (b < any(1,2,3)) it was also available in Microsoft Cω experimental language, however it was not documented anywhere (I just tried it when I was looking at Cω and it just worked).
You can't do this with native types, but there's nothing stopping you from creating a variable object (presuming you are using an OO language) which has a range of values or even a probability density function rather than an actual value.
You will also need to define all the mathematical operators between your variables and your variables and native scalars. Same goes for the equality and assignment operators.
numpy arrays do something similar for vectors and matrices.
That's also the kind of thing you can do in Prolog. You define rules that constraint your variables and then let Prolog resolve them ...
It takes some time to get used to it, but it is wonderful for certain problems once you know how to use it ...
Damien Conways Quantum::Superpositions might do what you want,
https://metacpan.org/pod/Quantum::Superpositions
You might need your crack-pipe however.
What you're asking seems to be how to implement a Fuzzy Logic system. These have been around for some time and you can undoubtedly pick up a library for the common programming languages quite easily.
You could use a struct and handle the operations manualy. Otherwise, no a variable only has 1 value at a time.
A variable is nothing more than an address into memory. That means a variable describes exactly one place in memory (length depending on the type). So as long as we have no "quantum memory" (and we dont have it, and it doesnt look like we will have it in near future), the answer is a NO.
If you want to program and to modell this behaviour, your way would be to use a an array (with length equal to the number of max. multiple values). With this comes the increased runtime, hence the computations must be done on each of the values (e.g. x+y, must compute with 2 different values x1+y1, x2+y2, x1+y2 and x2+y1).
In Perl , you can .
If you use Scalar::Util , you can have a var take 2 values . One if it's used in string context , and another if it's used in a numerical context .