def createActualModuleFromTemplate(self, template_module, isPredecessor = False):
"""
Creates a normal ParametricModule out of a GenerationTemplateModule.
If this is a predecessor module (isPredecessor is True), then the module is created with variables (e.g. x,y,z) as parameters.
"""
module = ParametricModule(template_module.letter)
#print("Gen module has n params: " + str(len(template_module.params)))
if self.parameterized:
param_index = 0
for param in template_module.params:
value = 1 # Default value
if isPredecessor == True:
if param_index == 0: value = "x"
if param_index == 1: value = "y"
if param_index == 2: value = "z"
elif self.constantsProbability > 0.0:
if self.rnd.random() < self.constantsProbability:
# Set a constant value as parameter
value = template_module.generateConstantParameterValue(self.rnd)
elif self.definesProbability > 0.0:
if self.rnd.random() < self.definesProbability:
# Select an existing define, or add a new one
nCurrentDefines = len(self.generator.lsystem.globalDefines)
if nCurrentDefines > 0 and (self.rnd.random() > 0.5 or nCurrentDefines == ModulesTemplateLibrary.MAX_DEFINES):
defname = "d"+str(self.rnd.randint(0,len(self.generator.lsystem.globalDefines)-1))
else:
defname, defvalue = self.generator.generateRandomDefine()
value = defname
module.appendParameter(value)
param_index += 1
#print("New Module: " + str(module))
return module
def copyFrom(other_pString):
"""
Copies a ParametricString and returns the copy.
"""
new_pString = ParametricString()
new_pString.setGlobals(other_pString.globalDefines)
new_pString.modulesList = []
for m in other_pString.modulesList:
new_pString.modulesList.append(ParametricModule.copyFrom(m))
return new_pString
def appendCloseBranch(self):
self.modulesList.append(ParametricModule.fromTextString("]"))
def appendOpenBranch(self):
self.modulesList.append(ParametricModule.fromTextString("["))
def __init__(self,letter,params=[]):
ParametricModule.__init__(self, letter, params)
v1 = op(v1,v2)
return v1
if __name__ == "__main__":
print("Start testing ParametricProduction")
print("\nCreation")
pp = ParametricProduction(verbose=True)
pp.setGlobals({"p":1.0}) # TODO: Must this be before? Or not?
pp.parseString('F:*->FF') # TODO: add a ParametricProduction.fromTextString LIKE THE REST!
#print(pp)
print("\nChange predecessor: parametric")
pm = ParametricModule.fromTextString("A(x)")
pp.setPredecessorModule(pm)
print(pp)
print(pm.letter)
print("\nChange condition: probability")
pp.setConditionFromString("0.8")
print(pp)
print("\nChange condition: parametric")
pp.setConditionFromString("x>0.9")
print(pp)
print("\nChange successor: parametric")
ps = ParametricString.fromTextString('F(x)A(p)')
pp.setSuccessorPstring(ps)
def __str__(self):
s = ParametricModule.__str__(self)
s += "(W: " + str(self.weight) + ")"
return s
def __init__(self,letter,params=[],weight=1,scale_min=0,scale_max=1):
ParametricModule.__init__(self, letter, params)
self.weight = weight # Must be [1,100]. The higher, the more likely this will appear in the generation
self.scale_min = scale_min # Determines the minimum random value that this module can have as a single parameter
self.scale_max = scale_max # Determines the maximum random value that this module can have as a single parameter
