The MUSCLE configuration file, or, historically, the  Complex Automata (CxA) file specifies what code will be used in a simulation, and how its coupled together. It is actually a Ruby file, so any Ruby syntax will work inside it.

To use it, make a file and get the cxa object

cxa = Cxa.LAST

and then add kernels to it by giving a name and a Java class that has the submodel implementation

cxa.add_kernel('w', 'examples.simplejava.Sender')
cxa.add_kernel('r', 'examples.simplejava.ConsoleWriter')

When using a C++ kernel without a Java interface, use the muscle.core.standalone.NativeKernel package. For an MPI executable, on a machine where mpiexec/mpirun can be called directly, use muscle.core.standalone.MPIKernel.

To add properties, add them to the env hash of cxa:

cxa.env["max_timesteps"] = 4
cxa.env["w:dt"] = 1;
cxa.env["w:someDoubleProperty"] = 6.1;
cxa.env["w:someOtherProperty"] = "this is w text";
cxa.env["r:someOtherProperty"] = "this is r text";
cxa.env["cxa_path"] = File.dirname(__FILE__)

Properties that are only meant for a single submodel are prepended with the name and a colon (e.g., "submodelName:propertyName"). Other properties are global and will be used by all submodels.

The scale of the submodels can also be specified in the CxA file. For the timestep of a submodel, use "submodelName:dt", for the total time it will run, "submodelName:T". For the first 3 spatial dimensions, use dx, dy, dz as step size, and X, Y, Z as total size. In Java, the scale can be accessed with the getScale() method of a submodel.

The cs property of cxa is the connection scheme; it defines how submodels are coupled. In the example, submodel w is attached to submodel r by tying the conduit entrance dataOut of w to the conduit exit dataIn of r. It also ties conduit entrance otherOut of w to other of r.

cs = cxa.cs

cs.attach('w' => 'r') {
        tie('dataOut', 'dataIn')
        tie('otherOut', 'other')
}

If the conduit entrance and exit have the same name, the second argument of tie is optional.

Filters

If a conduit filter should be applied to a conduit, these can be added as a list as the last argument of tie():

cs.attach('w' => 'r') {
        tie('dataOut', 'dataIn',['muscle.core.conduit.filter.MultiplyDoubleFilter_0.5'])
}

In the example, the MUSCLE filter MultiplyDoubleFilter is applied, which multiplies each double with a value, in this case 0.5. For user defined filters, one double argument may be given, separated from the class name by an underscore. MUSCLE already supplies some custom filters, the filter package is muscle.core.conduit.filter:

Filter	Class	Arguments	Message datatype	Behavior
null	NullFilter	none	any	Removes all incoming messages
pipe	PipeFilter	none	any	Forwards all incoming messages unchanged
console	ConsoleWriterFilter	none	any	Prints all messages to console and forwards them
linearinterpolation	LinearInterpolationFilterDouble	none	double[]	Creates a double[] of length-1 of the original, and linearly interpolates between the original values: k'_i <- (k_i+k_{i+1})/2
multiply	MultiplyFilterDouble	double factor	double[]	Multiplies each value of the incoming message by factor
drop	DropFilter	int step	any	Drops messages that are not a multiple of step
timeoffset	TimeOffsetFilter	double time	any	Adds an offset time to the timestamps of messages
timefactor	TimeFactorFilter	double factor	any	Multiplies the sent timestamp of messages
blockafter	BlockAfterTimeFilter	double time	any	Drops messages with a timestamp greater than time
lineartimeinterpolation	LinearTimeInterpolationFilterDouble	int step	double[]	For step==2, forwards the first message and then sends two messages for every message received, interpolating between one message and the next.

For convenience, the MUSCLE filters may be referred to by their name instead of their class:

cs.attach('w' => 'r') {
        tie('dataOut', 'dataIn',['multiply_0.5','console'])
}

Native code

For native executables that uses the MUSCLE API, the following parameters may be set: "submodelName:command" to set the path to the executable; and "submodelName:args" to give additional command-line parameters to the executable. Suppose my executable is somewhere in my home bin directory, this could be

cxa.env["subA:command"] = ENV['HOME'] + "/bin/subA"
cxa.env["subA:args"] = "paramA paramB"

For MPI code, two additional parameters should be set: "submodelName:mpiexec_command" with the name or the path the the mpiexec/mpirun executable; and "submodelName:mpiexec_args" which are the arguments, like "-np 2", etc.

Terminals

It may be convenient to couple a submodel to dummy terminals, to evaluate its individual behavior, or to read a message from file instead of receiving it from another submodel. A terminal is initialized by calling

cxa.add_terminal('readA', 'muscle.core.conduit.terminal.DoubleFileSource')
cxa['readA:filename'] = "/path/to/some.file"
cxa['readA:suffix'] = 'dat'
cxa['readA:relative'] = false
cxa['readA:delimiter'] = ','

cs.attach('readA' => 'r') {
    tie('dataIn')
}

Here, we're reading the file /path/to/some.file.dat, and the path is not relative to the runtime path of MUSCLE. The doubles in that file are delimited by commas. Finally, a terminal port takes any name of the receiving or sending end, so only one value is given to tie. For the moment, it is not possible to apply filters to terminals.

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