"""Simple examples of using the "frams" module to communicate directly with the Framsticks library (dll/so). For an introduction to Framsticks, its usage and scripting, see https://www.youtube.com/playlist?list=PLkPlXm7pOPatTl3_Gecx8ZaCVGeH4UV1L For a list of available classes, objects, methods and fields, see http://www.framsticks.com/files/classdoc/ For a number of examples of scripting, see the "scripts" directory in Framsticks distribution. """ import sys import frams frams.init(*(sys.argv[1:])) # pass whatever args we have, init() is the right place to deal with different scenarios: # frams.init() - should try to figure out everything (and might fail) # frams.init('path/to/lib') - load the library from the specified directory and configure Framsticks path as "data" inside this directory # frams.init('path/to/lib','-d/tmp/workdir/data') - as above, but set the working (writable) directory somewhere else (see also -D) # frams.init('path/to/lib','-Lframs-objects-alt.dll') - use specified library location and non-default file name print('Available objects:', dir(frams)) print() def extValueDetails(v): """A helper function to display basic information about a variable of type ExtValue.""" return '\t"' + str(v) + '" frams type=' + str(v._type()) + ' frams class=' + str(v._class()) + ' python type=' + str(type(v._value())) dic_as_string = '[100,2.2,"abc",[null,[],{}],XYZ[9,8,7]]' print("We have the following string:\n\t'%s'" % dic_as_string) print("Looks like a serialized dictionary, let's ask Framsticks String.deserialize() to do its job.") v = frams.String.deserialize(dic_as_string) print("Framsticks String.deserialize() returned\n\t", type(v)) print("More specifically, it is:") print(extValueDetails(v)) print("Even though it is ExtValue (Framsticks' Vector), it supports iteration like a python vector, so let's inspect its elements:") for e in v: print(extValueDetails(e)) print("Now let's play with the Framsticks simulator. Let's create a Genotype object and set fields in its custom 'data' dictionary.") g = frams.GenePools[0].add('X') g.name = "Snakis Py" g.data['custom'] = 123.456 g.data['a'] = 'b' # implicit conversion, looks like python dictionary but still converts '3' and '4' to ExtValue dic = frams.Dictionary.new() # let's create a Dictionary object from Framsticks dic.set('1', '2') # calling set() from Framsticks Dictionary dic['3'] = '4' # implicit conversion, looks like python dictionary but still converts '3' and '4' to ExtValue g.data['d'] = dic print(extValueDetails(g)) print("Let's add a few mutants and display their data:") for more in range(5): frams.GenePools[0].add(frams.GenMan.mutate(g.geno)) for g in frams.GenePools[0]: print("\t%d. name='%s'\tgenotype='%s'\tdata=%s" % (g.index._value(), str(g.name), str(g.genotype), str(g.data))) print("Let's now change some property of the simulation. Current water level is", frams.World.wrldwat) frams.World.wrldwat = 0.5 print("Now water level is", frams.World.wrldwat) frams.World.wrldwat = frams.World.wrldwat._value() + 0.7 print("Now water level is", frams.World.wrldwat) initial_genotype = 'X(X,RX(X[T],X[G]))' # simple body with touch and gyroscope sensors print("Let's perform a few simulation steps of the initial genotype:", initial_genotype) frams.ExpProperties.initialgen = initial_genotype frams.ExpProperties.p_mut = 0 # no mutation (the selection procedure will clone our initial genotype) frams.ExpProperties.p_xov = 0 # no crossover (the selection procedure will clone our initial genotype) frams.Populations[0].initial_nn_active = 1 # immediate simulation of neural network - no "waiting for stabilization" period frams.World.wrldg = 5 # gravity=5x default, let it fall quickly frams.Simulator.init() # adds initial_genotype to gene pool (calls onInit() from standard.expdef) frams.Simulator.start() # this does not actually start the simulation, just sets the "Simulator.running" status variable step = frams.Simulator.step # cache reference to avoid repeated lookup in the loop (just for performance) for s in range(15): step() # first step performs selection and revives one genotype according to standard.expdef rules creature = frams.Populations[0][0] # FramScript Creature object mechpart0 = creature.getMechPart(0) print('Step# = %d' % frams.Simulator.stepNumber._value(), '\tSimulated_creatures =', frams.Populations[0].size._value(), "\tpart0_xyz = (% .2f,% .2f,% .2f)" % (mechpart0.x._value(), mechpart0.y._value(), mechpart0.z._value()), "\ttouch = % .3f\tgyro = % .3f" % (creature.getNeuro(0).state._value(), creature.getNeuro(1).state._value())) frams.Simulator.stop() # Note that implementing a complete expdef, especially a complex one, entirely in python may be inconvenient or impractical # because you do not have access to "event handlers" like you have in FramScript - onStep(), onBorn(), onDied(), onCollision() etc., # so you would have to check various conditions in python in each simulation step to achieve the same effect.