I was wondering if there already exists a possibility to extract from flat Modelica code all variables AND their corresponding types (classnames respectively).
For example:
Given an extract from a flattened Modelica model:
constant Integer nSurfaces = 8;
constant Integer construction1.nLayers(min = 1.0) = 2 "Number of layers of the construction";
parameter Modelica.SIunits.Length construction1.thickness[construction1.nLayers]= {0.2, 0.1} "Thickness of each construction layer";
Here, the wanted output would be something like:
nSurfaces, Integer, constant;
construction1.nLayers, Integer, constant;
construction1.thickness[construction1.nLayers], Modelica.SIunits.Length, parameter
Ideally, for construction1.thickness there would be two lines (=number of construction1.nLayers).
I know, that it is possible to get a list of used variables from the dsin.txt, which is produced while translating a model. But until now I did not find an already existing way to get the corresponding types. And I really would like to avoid writing an own parser :-).
You could try to generate the file modelDescription.xml as defined by the FMI standard. It contains a ton of information and XML should be easier to parse, e.g. python has a couple of xml parsing/reading packages.
If you are using Dymola you just set the flag Advanced.FMI.GenerateModelDescriptionInterface2 = true to generate the model description file.
The second idea could be to let the compiler/tool parse the Modelica file for you as they need to do that anyway, try searching for AST (abstract syntax tree). In Dymola, this is available through the ModelManagement library, and also through the Python interface.
Third idea could be to use one of the Modelica parsers available, e.g. have a look at:
https://github.com/lbl-srg/modelica-json
https://hackage.haskell.org/package/modelicaparser
https://github.com/xie-dongping/modparc
https://github.com/pymoca/pymoca
https://github.com/pymola/pymola/tree/master/src/pymola
Fourth, if all that did not work, you still do not have to write a full parser, you could use ANTLR, then use an existing grammar file (look for e.g. modelica.g4).
Related
I'm working with scalax to generate a graph of my Spark operationS. So, I have a custom library that generates my graph. So, let me show a sample:
val DAGWithoutGet = createGraphFromOps(ops)
val DAGWithGet = createGraphFromOps(ops).get
The return type of DAGWithoutGet is
scala.util.Try[scalax.collection.Graph[typeA, scalax.collection.GraphEdge.DiEdge]],
and, for DAGWithGet is
scalax.collection.Graph[typeA, scalax.collection.GraphEdge.DiEdge].
Here, typeA is a project related class representing a single Spark operation, not relevant for the context of this question. (for context only: What my custom library does is, essentially, generate a map of dependencies between those operations, creating a big Map object, and calling Graph(myBigMap: _*) to generate the graph).
As far as I know, calling the .get command on this point of my code or later should not make any difference, but that is not what I'm seeing.
Calling DAGWithoutGet.get.nodes has a return type of scalax.collection.Graph[typeA,DiEdge]#NodeSetT,
while calling DAGWithGet.nodes returns DAGWithGet.NodeSetT.
When I extract one of those nodes (using the .find method), I receive scalax.collection.Graph[typeA,DiEdge]#NodeT and DAGWithGet.NodeT types, respectively. Much to my dismay, even the methods available in each case are different - I cannot use pathTo (which happens to be what I want) or withSubgraph on the former, only on the latter.
My doubt is, then, after this relatively complex example: what is going on here? Why extracting the value from the Try construct on different moments leads to different types, one path dependent, and the other not - or, if that isn't correct, what may I be missing here?
In my Simulink Model I have a MATLAB function, this_function, which uses as one parameter the name of the Simulink Model, modelname. The name is defined in an extra parameter file with all other parameters needed. Loading the parameter file loads modelname into the workspace. The problem is now, that this_function can't access modelname in the workspace and therefore the model doesn't run.
I tried to use modelname as a constant input source for this_function, which I used as a work-around previously, but Simulink doesn't accept chars/strings as signals. Furthermore does setting modelname to global not work as well.
Is there a way to keep modelname in the parameter file instead of writing it directly into this_function?
Simulink does not support strings. Like, anywhere. It really sucks and I don't know why this limitation exists - it seems like a pretty horrible design choice to me.
I've found the following workarounds for this limitation:
Dirty Casting
Let
function yourFun(num_param1, num_param2, ..., str_param);
be your MATLAB function inside the Simulink block, with str_param the parameter you want to be a string, and num_param[X] any other parameters. Then pass the string signal to the function like so:
yourFun(3, [4 5], ..., 'the_string'+0);
Note that '+0' at the end; that is shorthand for casting a string to an array of integers, corresponding to the ASCII codes of each character in the string. Then, inside the function, you could get the string back by doing the inverse:
model = char(str_param);
but usually that results in problems later on (strcmp not supported, upper/lower not supported, etc.). So, you could do string comparisons (and similar operations) in a similar fashion:
isequal(str_param, 'comparison'+0);
This has all the benefits of strings, without actually using strings.
Of course, the '+0' trick can be used inside constant blocks as well, model callbacks to convert workspace variables on preLoad, etc.
Note that support for variable size arrays must be enabled in the MATLAB function.
Fixed Option Set
Instead of passing in a string, you can pass a numeric scalar, which corresponds to a selection in a list of fixed, hardcoded options:
function yourFun(..., option)
...
switch (option)
case 1
model = 'model_idealised';
case 2
model = 'model_with_drag';
case 3
model = 'model_fullscale';
otherwise
error('Invalid option.');
end
...
end
Both alternatives are not ideal, both are contrived, and both are prone to error and/or have reusability and scalability problems. It's pretty hopeless.
Simulink should start supporting strings natively, I mean, come on.
I am writing a signal processing program using matlab. I know there are two types of float-pointing variables, single and double. Considering the memory usage, I want my code to work with only single type variable when the system's memory is not large, while it can also be adapted to work with double type variables when necessary, without significant modification (simple and light modification before running is OK, i.e., I don't need runtime-check technique). I know this can be done by macro in C and by template in C++. I don't find practical techniques which can do this in matlab. Do you have any experience with this?
I have a simple idea that I define a global string containing "single" or "double", then I pass this string to any memory allocation method called in my code to indicate what type I need. I think this can work, I just want to know which technique you guys use and is widely accepted.
I cannot see how a template would help here. The type of c++ templates are still determined in compile time (std::vector vec ...). Also note that Matlab defines all variables as double by default unless something else is stated. You basically want runtime checks for your code. I can think of one solution as using a function with a persistent variable. The variable is set once per run. When you generate variables you would then have to generate all variables you want to have as float through this function. This will slow down assignment though, since you have to call a function to assign variables.
This example is somehow an implementation of the singleton pattern (but not exactly). The persistent variable type is set at the first use and cannot change later in the program (assuming that you do not do anything stupid as clearing the variable explicitly). I would recommend to go for hardcoding single in case performance is an issue, instead of having runtime checks or assignment functions or classes or what you can come up with.
function c = assignFloat(a,b)
persistent type;
if (isempty(type) & nargin==2)
type = b;
elseif (isempty(type))
type = 'single';
% elseif(nargin==2), error('Do not set twice!') % Optional code, imo unnecessary.
end
if (strcmp(type,'single'))
c = single(a);
return;
end
c = double(a);
end
In the syntax analysis phase, an imperative compiler can build an AST out of nodes that already contain a type field that is set to null during construction, and then later, in the semantic analysis phase, fill in the types by assigning the declared/inferred types into the type fields.
How do purely functional languages handle this, where you do not have the luxury of assignment? Is the type-less AST mapped to a different kind of type-enriched AST? Does that mean I need to define two types per AST node, one for the syntax phase, and one for the semantic phase?
Are there purely functional programming tricks that help the compiler writer with this problem?
I usually rewrite a source (or an already several steps lowered) AST into a new form, replacing each expression node with a pair (tag, expression).
Tags are unique numbers or symbols which are then used by the next pass which derives type equations from the AST. E.g., a + b will yield something like { numeric(Tag_a). numeric(Tag_b). equals(Tag_a, Tag_b). equals(Tag_e, Tag_a).}.
Then types equations are solved (e.g., by simply running them as a Prolog program), and, if successful, all the tags (which are variables in this program) are now bound to concrete types, and if not, they're left as type parameters.
In a next step, our previous AST is rewritten again, this time replacing tags with all the inferred type information.
The whole process is a sequence of pure rewrites, no need to replace anything in your AST destructively. A typical compilation pipeline may take a couple of dozens of rewrites, some of them changing the AST datatype.
There are several options to model this. You may use the same kind of nullable data fields as in your imperative case:
data Exp = Var Name (Maybe Type) | ...
parse :: String -> Maybe Exp -- types are Nothings here
typeCheck :: Exp -> Maybe Exp -- turns Nothings into Justs
or even, using a more precise type
data Exp ty = Var Name ty | ...
parse :: String -> Maybe (Exp ())
typeCheck :: Exp () -> Maybe (Exp Type)
I cant speak for how it is supposed to be done, but I did do this in F# for a C# compiler here
The approach was basically - build an AST from the source, leaving things like type information unconstrained - So AST.fs basically is the AST which strings for the type names, function names, etc.
As the AST starts to be compiled to (in this case) .NET IL, we end up with more type information (we create the types in the source - lets call these type-stubs). This then gives us the information needed to created method-stubs (the code may have signatures that include type-stubs as well as built in types). From here we now have enough type information to resolve any of the type names, or method signatures in the code.
I store that in the file TypedAST.fs. I do this in a single pass, however the approach may be naive.
Now we have a fully typed AST you could then do things like compile it, fully analyze it, or whatever you like with it.
So in answer to the question "Does that mean I need to define two types per AST node, one for the syntax phase, and one for the semantic phase?", I cant say definitively that this is the case, but it is certainly what I did, and it appears to be what MS have done with Roslyn (although they have essentially decorated the original tree with type info IIRC)
"Are there purely functional programming tricks that help the compiler writer with this problem?"
Given the ASTs are essentially mirrored in my case, it would be possible to make it generic and transform the tree, but the code may end up (more) horrendous.
i.e.
type 'type AST;
| MethodInvoke of 'type * Name * 'type list
| ....
Like in the case when dealing with relational databases, in functional programming it is often a good idea not to put everything in a single data structure.
In particular, there may not be a data structure that is "the AST".
Most probably, there will be data structures that represent parsed expressions. One possible way to deal with type information is to assign a unique identifier (like an integer) to each node of the tree already during parsing and have some suitable data structure (like a hash map) that associates those node-ids with types. The job of the type inference pass, then, would be just to create this map.
In fortran I can use Class (*) in a subroutine and use
Select Type (ir)
Type Is (Integer (Int8))
Type Is (Integer (Int16))
End Select
Does there exist any way to pass a numeric value rather than using Class (*), by using Class (Integer) for example or something similar.
Intrinsic types are not extended types, they have no common ancestor, nothing like that exist. You can use the unlimited polymorphism (class(*)) or you must indicate exact type and kind (real(dp)). You can also write type(real) in Fortran 2008, but that does not change anything, it is just a different syntax for the same.
Have a look at some common techniques for generic programming with different kinds like, for example, How to make some generic programming in fortran 90/95 working with intrinsic types , STL analogue in Fortran and others. You normally make a separate procedure for each kind and paste the code body from an include file.