implemented random number generation

integration/code/pn_interface.alc

@@ -510,8 +510,76 @@ Element function rhs_rewrite(final_matches : Element,plabel_to_rhsnode:Element,
 				log("unsupported metatype in rhs")
 	return 0
 	
-Element function tf_executeRule(tf_er_transformation: Element,tf_er_rule: Element, tf_er_model: Element, pivots : Element):
-	//TODO support for multiple ruleTypes
+Element function tf_executeFRule(tf_er_transformation: Element,tf_er_rule: Element, tf_er_model: Element, pivots : Element):
+	
+	//find LHS
+	//TODO if no lhs (is this allowed to happen?) // or empty lhs
+	Element tf_er_lhs
+	tf_er_lhs = allOutgoingAssociationInstances(tf_er_transformation, tf_er_rule, dict_read(dict_read(dict_read(tf_er_transformation, "metamodel"), "model"), "lhs"))
+	tf_er_lhs = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_lhs)), tf_er_model, pivots)
+	Integer nr_of_lhs_matches
+	nr_of_lhs_matches = list_len(tf_er_lhs)
+	
+	//find NACs if at least one lhs is found (otherwise not needed)
+	Integer nr_of_nac_matches
+	nr_of_nac_matches = 0
+	Element tf_er_nac
+	tf_er_nac = create_node()
+	if(nr_of_lhs_matches > 0):
+		Element tf_er_nac_
+		tf_er_nac_ = allOutgoingAssociationInstances(tf_er_transformation, tf_er_rule, dict_read(dict_read(dict_read(tf_er_transformation, "metamodel"), "model"), "nac"))
+		Element partial_nac_matches
+		while (read_nr_out(tf_er_nac_) > 0):
+			partial_nac_matches = tf_matchAll(tf_er_transformation, read_edge_dst(set_pop(tf_er_nac_)), tf_er_model, pivots)
+			while (read_nr_out(partial_nac_matches)>0):
+				list_append(tf_er_nac, set_pop(partial_nac_matches))
+		nr_of_nac_matches = list_len(tf_er_nac)
+		
+	//remove from lhs matches that share a node with a nac match
+	//TODO if nac is not related to match (no plabels match)
+	Element final_matches
+	final_matches = mergeLHSNAC(tf_er_lhs, tf_er_nac)
+	
+	//extract pivots from the matches
+	extractPivots(final_matches, pivots, tf_er_transformation, tf_er_model)
+
+	//rhs part
+	
+	//create plabel_to_rhsnode
+	Element RHS
+	RHS = allOutgoingAssociationInstances(tf_er_transformation, tf_er_rule, tf_er_transformation["metamodel"]["model"]["rhs"])
+	if(read_nr_out(RHS) > 0):
+		RHS = read_edge_dst(set_pop(RHS))
+		Element metamodelTransf //transformation metamodel
+		metamodelTransf = tf_er_transformation["metamodel"]["model"]
+		Element post2ram // type of the post2ram edge
+		post2ram = dict_read(metamodelTransf, "post2ram")
+		post2ram = allOutgoingAssociationInstances(tf_er_transformation, RHS, post2ram)
+		Element plabel_to_rhsnode //dict in the form plabel->node
+		plabel_to_rhsnode = create_node()
+		Element rhs_node
+		Integer rhs_plabel
+		while (integer_lt(0, list_len(post2ram))):
+			rhs_node = read_edge_dst(set_pop(post2ram))
+			rhs_plabel = read_attribute(tf_er_transformation, getName(tf_er_transformation, rhs_node), "plabel")
+			dict_add(plabel_to_rhsnode,rhs_plabel, rhs_node)
+		
+		rhs_rewrite(final_matches ,plabel_to_rhsnode, tf_er_transformation, tf_er_model )
+		
+	return pivots
+
+Integer function modulo(a:Integer,b:Integer):
+	return a - integer_division(a,b)*b
+
+Integer RandomNumberState
+Integer function getRandomNumber(min:Integer, max:Integer):
+	if( bool_not(is_physical_int(RandomNumberState))):
+		RandomNumberState = 4 // xkcd.com/221/
+	RandomNumberState = modulo((8121*RandomNumberState) + 28411, 134456)
+	return modulo(RandomNumberState , (max-min)+1)+min
+
+
+Element function tf_executeARule(tf_er_transformation: Element,tf_er_rule: Element, tf_er_model: Element, pivots : Element):
 	
 	//find LHS
 	//TODO if no lhs (is this allowed to happen?) // or empty lhs
@@ -585,13 +653,13 @@ Element function executeRuleBlock(transformation_model : Element,hostmodel:Eleme
 		log("running arule")
 		Rule = read_edge_dst(set_pop(allOutgoingAssociationInstances(transformation_model, ruleblock, transformation_model["metamodel"]["model"]["getrule"])))
 		log(getName(transformation_model, Rule))
-		pivots = tf_executeRule(transformation_model, Rule, hostmodel, pivots)
+		pivots = tf_executeARule(transformation_model, Rule, hostmodel, pivots)
 		succes = True
 	elif (typename == "FRule"):
 		log("running frule")
 		Rule = read_edge_dst(set_pop(allOutgoingAssociationInstances(transformation_model, ruleblock, transformation_model["metamodel"]["model"]["getrule"])))
 		log(getName(transformation_model, Rule))
-		pivots = tf_executeRule(transformation_model, Rule, hostmodel, pivots)
+		pivots = tf_executeFRule(transformation_model, Rule, hostmodel, pivots)
 		succes = True
 	else:
 		log("RuleType is not supported yet")