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f0.def @ 1237

Last change on this file since 1237 was 1186, checked in by Maciej Komosinski, 2 years ago
For consistency with other numerical types, unlimited string length is now indicated by "-1" as the second value of the definition of the "s" property
Property svn:eol-style set to `native`
File size: 15.1 KB

Rev	Line
[952]	1	CLASS(Model,f0_model,m,Model)
[187]	2	GROUP(Properties)
	3	GROUP(Visual)
	4	PROP(se,0,1024,startenergy,f,,,,startenergy)
[1186]	5	PROP(Vstyle,1,0,Visual style,s,0,-1,,vis_style,,``See the \"Visual style definition\" context for more information'')
[187]	6	ENDCLASS
	7
[952]	8	CLASS(Part,f0_part,p,Part)
[187]	9	GROUP(Geometry)
	10	GROUP(Other properties)
	11	GROUP(Visual)
	12	PROP(x,0,1024,position.x,f,,,,p.x)
	13	PROP(y,0,1024,position.y,f,,,,p.y)
	14	PROP(z,0,1024,position.z,f,,,,p.z)
[915]	15	PROP(sh,0,0,shape,d,0,3,0,shape)
	16	PROP(s,0,0,size,f,0.1,10.0,1.0,size)
[1012]	17	PROP(sx,0,0,scale.x,f,0.05,5.0,1.0,scale.x)
	18	PROP(sy,0,0,scale.y,f,0.05,5.0,1.0,scale.y)
	19	PROP(sz,0,0,scale.z,f,0.05,5.0,1.0,scale.z)
[528]	20	XPROP(h,1,0,hollow,f,0,1,0,hollow)
[187]	21	XPROP(dn,1,0,density,f,0.2,5.0,1.0,density)
	22	XPROP(fr,1,0,friction,f,0.0,4.0,0.4,friction)
	23	XPROP(ing,1,0,ingestion,f,0.0,1.0,0.25,ingest)
	24	XPROP(as,1,0,assimilation,f,0.0,1.0,0.25,assim)
	25	PROP(rx,0,0,rot.x,f,,,,rot.x)
	26	PROP(ry,0,1024,rot.y,f,,,,rot.y)
	27	PROP(rz,0,1024,rot.z,f,,,,rot.z)
	28	PROP(i,1,0,`info',s,,,,info)
[1186]	29	PROP(Vstyle,2,0,Visual style,s,0,-1,part,vis_style,,``See the \"Visual style definition\" context for more information'')
[1142]	30	XPROP(vr,2,0,red component,f,0.0,1.0,0.5,vcolor.x)
	31	XPROP(vg,2,1024,green component,f,0.0,1.0,0.5,vcolor.y)
	32	XPROP(vb,2,1024,blue component,f,0.0,1.0,0.5,vcolor.z)
[187]	33	ENDCLASS
	34
[934]	35	CLASS(Part_MinMaxDef,f0_part_minmaxdef,p)
	36	GROUP(Geometry)
[945]	37	PROP(f,0,0,volume,f,0.83776,20.94395,4.18879,volume,,``Recommended default and min,max range for solid-shape Parts created and modified by genetic operators which are responsible for setting sizex,y,z. Default is the volume of the solid sphere (ball) with default radius=1 (radius is the same as sizex,y,z). Minimum is 5x less, maximum is 5x more.'')
[934]	38	ENDCLASS
	39
[952]	40	CLASS(Joint,f0_joint,j,Joint)
[187]	41	GROUP(Connections)
	42	GROUP(Geometry)
	43	GROUP(Other properties)
	44	GROUP(Visual)
	45	PROP(p1,0,1024,`part1 ref#',d,-1,999999,-1,p1_refno)
	46	PROP(p2,0,1024,`part2 ref#',d,-1,999999,-1,p2_refno)
	47	PROP(rx,1,0,rotation.x,f,,,,rot.x)
	48	PROP(ry,1,1024,rotation.y,f,,,,rot.y)
	49	PROP(rz,1,1024,rotation.z,f,,,,rot.z)
	50	PROP(dx,1,0,delta.x,f,-2,2,0,d.x)
	51	PROP(dy,1,1024,delta.y,f,-2,2,0,d.y)
	52	PROP(dz,1,1024,delta.z,f,-2,2,0,d.z)
[915]	53	PROP(sh,1,0,shape,d,0,3,0,shape)
	54	PROP(hx,1,0,hinge position.x,f,,,0,hinge_pos.x)
	55	PROP(hy,1,1024,hinge position.y,f,,,0,hinge_pos.y)
	56	PROP(hz,1,1024,hinge position.z,f,,,0,hinge_pos.z)
	57	PROP(hrx,1,0,hinge rotation.x,f,,,0,hinge_rot.x)
	58	PROP(hry,1,1024,hinge rotation.y,f,,,0,hinge_rot.y)
	59	PROP(hrz,1,1024,hinge rotation.z,f,,,0,hinge_rot.z)
	60	PROP(hxn,1,0,hinge x negative limit,f,-6.2832,0,-1.5708,hinge_limit_x[0])
	61	PROP(hxp,1,1024,hinge x positive limit,f,0,6.2832,1.5708,hinge_limit_x[1])
	62	PROP(hyn,1,0,hinge y negative limit,f,-6.2832,0,-1.5708,hinge_limit_y[0])
	63	PROP(hyp,1,1024,hinge y positive limit,f,0,6.2832,1.5708,hinge_limit_y[1])
[187]	64	XPROP(stif,2,0,stiffness,f,0.0,1.0,1.0,stif)
	65	XPROP(rotstif,2,0,rotation stiffness,f,0.0,1.0,1.0,rotstif)
	66	PROP(stam,2,0,stamina,f,0.0,1.0,0.25,stamina)
	67	PROP(i,2,0,`info',s,,,,info)
[1186]	68	PROP(Vstyle,3,0,Visual style,s,0,-1,joint,vis_style,,``See the \"Visual style definition\" context for more information'')
[1142]	69	XPROP(vr,3,0,red component,f,0.0,1.0,0.5,vcolor.x)
	70	XPROP(vg,3,1024,green component,f,0.0,1.0,0.5,vcolor.y)
	71	XPROP(vb,3,1024,blue component,f,0.0,1.0,0.5,vcolor.z)
[187]	72	ENDCLASS
	73
[952]	74	CLASS(Joint,f0_nodeltajoint,j,Joint,NOXML)
[187]	75	GROUP(Connections)
	76	GROUP(Geometry)
	77	GROUP(Other properties)
	78	GROUP(Visual)
	79	PROP(p1,0,1024,`part1 ref#',d,-1,999999,-1,p1_refno)
	80	PROP(p2,0,1024,`part2 ref#',d,-1,999999,-1,p2_refno)
[915]	81	PROP(sh,1,0,shape,d,0,3,0,shape)
	82	PROP(hx,1,0,hinge position.x,f,,,0,hinge_pos.x)
	83	PROP(hy,1,1024,hinge position.y,f,,,0,hinge_pos.y)
	84	PROP(hz,1,1024,hinge position.z,f,,,0,hinge_pos.z)
	85	PROP(hrx,1,0,hinge rotation.x,f,,,0,hinge_rot.x)
	86	PROP(hry,1,1024,hinge rotation.y,f,,,0,hinge_rot.y)
	87	PROP(hrz,1,1024,hinge rotation.z,f,,,0,hinge_rot.z)
	88	PROP(hxn,1,0,hinge x negative limit,f,-6.2832,0,-1.5708,hinge_limit_x[0])
	89	PROP(hxp,1,1024,hinge x positive limit,f,0,6.2832,1.5708,hinge_limit_x[1])
	90	PROP(hyn,1,0,hinge y negative limit,f,-6.2832,0,-1.5708,hinge_limit_y[0])
	91	PROP(hyp,1,1024,hinge y positive limit,f,0,6.2832,1.5708,hinge_limit_y[1])
[187]	92	XPROP(stif,2,0,stiffness,f,0.0,1.0,1.0,stif)
	93	XPROP(rotstif,2,0,rotation stiffness,f,0.0,1.0,1.0,rotstif)
	94	PROP(stam,2,0,stamina,f,0.0,1.0,0.25,stamina)
	95	PROP(i,2,0,`info',s,,,,info)
[1186]	96	PROP(Vstyle,3,0,Visual style,s,0,-1,joint,vis_style,,``See the \"Visual style definition\" context for more information'')
[1142]	97	XPROP(vr,3,0,red component,f,0.0,1.0,0.5,vcolor.x)
	98	XPROP(vg,3,1024,green component,f,0.0,1.0,0.5,vcolor.y)
	99	XPROP(vb,3,1024,blue component,f,0.0,1.0,0.5,vcolor.z)
[187]	100	ENDCLASS
	101
[952]	102	CLASS(Neuro,f0_neuro,n,Neuro)
[187]	103	GROUP(Connections)
	104	GROUP(Other)
	105	GROUP(Visual)
	106	PROP(p,0,0,`part ref#',d,-1,999999,-1,part_refno)
	107	PROP(j,0,0,`joint ref#',d,-1,999999,-1,joint_refno)
[289]	108	PROP(d,1,0,details,s,,,N,details,GETSET)
[187]	109	PROP(i,1,0,`info',s,,,,info)
[1186]	110	PROP(Vstyle,2,0,Visual style,s,0,-1,neuro,vis_style,,``See the \"Visual style definition\" context for more information'')
[187]	111	PROP(getInputCount,0,1+2,`input count',d,,,,inputCount,GETONLY)
[656]	112	PROP(getInputNeuroDef,0,0,`get input neuron',p oNeuroDef(d),,,,p_getInputNeuroDef,PROCEDURE)
	113	PROP(getInputNeuroIndex,0,0,`get input neuron index',p d(d),,,,p_getInputNeuroIndex,PROCEDURE)
	114	PROP(getInputWeight,0,0,`get input weight',p f(d),,,,p_getInputWeight,PROCEDURE)
[732]	115	PROP(classObject,0,1+2,`neuron class',oNeuroClass,,,,classObject,GETONLY)
[187]	116	ENDCLASS
	117
[952]	118	CLASS(NeuroConn,f0_neuroconn,c,Neuron connection)
[187]	119	GROUP(Connection)
	120	GROUP(Other)
	121	PROP(n1,0,1024,`this neuro ref#',d,-1,999999,-1,n1_refno)
	122	PROP(n2,0,1024,`connected neuro ref#',d,-1,999999,-1,n2_refno)
	123	PROP(w,0,1024,weight,f,-999999,999999,1.0,weight)
	124	PROP(i,1,0,`info',s,,,,info)
	125	ENDCLASS
	126
	127	NEUROCLASS(StdNeuron,N,Neuron,`Standard neuron',-1,1,0)
	128	VISUALHINTS(DontShowClass)
	129	NEUROPROP(in,1,0,Inertia,f,0.0,1.0,0.8,inertia)
	130	NEUROPROP(fo,1,0,Force,f,0.0,999.0,0.04,force)
	131	NEUROPROP(si,1,0,Sigmoid,f,-99999.0,99999.0,2.0,sigmo)
	132	NEUROPROP(s,2,0,State,f,-1.0,1.0,0.0,newstate)
	133	ENDNEUROCLASS
	134
	135	NEUROCLASS(StdUNeuron,Nu,`Unipolar neuron [EXPERIMENTAL!]',`Works like standard neuron (N) but the output value is scaled to 0...+1 instead of -1...+1.\nHaving 0 as one of the saturation states should help in \"gate circuits\", where input signal is passed through or blocked depending on the other singal.',-1,1,0)
	136	NEUROPROP(in,1,0,Inertia,f,0.0,1.0,0.8,inertia)
	137	NEUROPROP(fo,1,0,Force,f,0.0,999.0,0.04,force)
	138	NEUROPROP(si,1,0,Sigmoid,f,-99999.0,99999.0,2.0,sigmo)
	139	NEUROPROP(s,2,0,State,f,-1.0,1.0,0.0,newstate)
	140	ENDNEUROCLASS
	141
[952]	142	NEUROCLASS(Gyro,G,Gyroscope,`Tilt sensor.\nSignal is proportional to sin(angle) = most sensitive in horizontal orientation.\n0=the stick is horizontal\n+1/-1=the stick is vertical',0,1,2)
	143	SHAPETYPE(BallAndStickShapeType)
[187]	144	VISUALHINTS(ReceptorClass)
	145	SYMBOL(`8,7,100,50,90,50,90,40,70,40,80,50,70,60,90,60,90,50,12,43,24,48,24,48,19,38,19,38,24,43,24,43,54,48,54,48,64,43,69,38,64,38,54,43,54,5,63,69,58,74,48,79,38,79,28,74,23,69,1,43,79,43,74,1,23,69,26,66,1,63,69,60,66,1,55,76,53,73,1,31,75,33,72')
	146	ENDNEUROCLASS
	147
[976]	148	NEUROCLASS(GyroP,Gpart,Part Gyroscope,`Tilt sensor. Signal is directly proportional to the tilt angle.\n0=the part X axis is horizontal\n+1/-1=the axis is vertical',0,1,1)
[187]	149	VISUALHINTS(ReceptorClass)
[952]	150	SYMBOL(`8,7,100,50,90,50,90,40,70,40,80,50,70,60,90,60,90,50,12,43,24,48,24,48,19,38,19,38,24,43,24,43,54,48,54,48,64,43,69,38,64,38,54,43,54,5,63,69,58,74,48,79,38,79,28,74,23,69,1,43,79,43,74,1,23,69,26,66,1,63,69,60,66,1,55,76,53,73,1,31,75,33,72')
	151	NEUROPROP(ry,1,0,rotation.y,f,-6.282,6.282,0,ry)
	152	NEUROPROP(rz,1,0,rotation.z,f,-6.282,6.282,0,rz)
	153	ENDNEUROCLASS
	154
[1134]	155	NEUROCLASS(Touch,T,Touch,`Touch and proximity sensor (Tcontact and Tproximity combined)\n-1=no contact\n0=just touching\n>0=pressing, value depends on the force applied (not implemented in ODE mode)',0,1,1)
[952]	156	VISUALHINTS(ReceptorClass)
[187]	157	SYMBOL(`2,7,100,50,90,50,90,40,70,40,80,50,70,60,90,60,90,50,11,75,50,65,50,60,55,55,45,50,55,45,45,40,50,35,50,30,45,25,50,30,55,35,50')
	158	NEUROPROP(r,1,0,Range,f,0.0,1.0,1.0,range)
[952]	159	NEUROPROP(ry,1,0,rotation.y,f,-6.282,6.282,0,ry)
	160	NEUROPROP(rz,1,0,rotation.z,f,-6.282,6.282,0,rz)
[187]	161	ENDNEUROCLASS
	162
[976]	163	NEUROCLASS(TouchC,Tcontact,Touch contact,`Touch sensor.\n-1=no contact\n0=the Part is touching the obstacle\n>0=pressing, value depends on the force applied (not implemented in ODE mode)',0,1,1)
[952]	164	VISUALHINTS(ReceptorClass)
	165	SYMBOL(`2,7,100,50,90,50,90,40,70,40,80,50,70,60,90,60,90,50,11,75,50,65,50,60,55,55,45,50,55,45,45,40,50,35,50,30,45,25,50,30,55,35,50')
	166	ENDNEUROCLASS
	167
[1043]	168	NEUROCLASS(TouchP,Tproximity,Touch proximity,`Proximity sensor detecting obstacles along the X axis.\n-1=distance is \"r\" or more\n0=zero distance',0,1,1)
[952]	169	VISUALHINTS(ReceptorClass)
	170	SYMBOL(`2,7,100,50,90,50,90,40,70,40,80,50,70,60,90,60,90,50,11,75,50,65,50,60,55,55,45,50,55,45,45,40,50,35,50,30,45,25,50,30,55,35,50')
	171	NEUROPROP(r,1,0,Range,f,0.0,1.0,1.0,range)
	172	NEUROPROP(ry,1,0,rotation.y,f,-6.282,6.282,0,ry)
	173	NEUROPROP(rz,1,0,rotation.z,f,-6.282,6.282,0,rz)
	174	ENDNEUROCLASS
	175
[187]	176	NEUROCLASS(Smell,S,Smell,`Smell sensor. Aggregated \"smell of energy\" experienced from all energy objects (creatures and food pieces).\nClose objects have bigger influence than the distant ones: for each energy source, its partial feeling is proportional to its energy/(distance^2)',0,1,1)
	177	VISUALHINTS(ReceptorClass)
	178	SYMBOL(`5,7,100,50,90,50,90,40,70,40,80,50,70,60,90,60,90,50,3,10,40,15,45,15,55,10,60,5,20,30,25,35,30,45,30,55,25,65,20,70,4,15,35,20,40,22,50,20,60,15,65,5,75,50,50,50,45,45,40,50,45,55,50,50')
	179	ENDNEUROCLASS
	180
	181	NEUROCLASS(Const,*,Constant,Constant value,0,1,0)
	182	VISUALHINTS(Invisible)
	183	SYMBOL(`4,4,26,27,26,73,73,73,73,27,26,27,1,73,50,100,50,1,56,68,46,68,2,41,47,51,32,51,68')
	184	ENDNEUROCLASS
	185
	186	NEUROCLASS(BendMuscle,\|,Bend muscle,,1,0,2)
[932]	187	SHAPETYPE(BallAndStickShapeType)
[1134]	188	VISUALHINTS(DontShowClass+EffectorClass+IsV1BendMuscle+AtFirstPart)
[187]	189	SYMBOL(`6,5,25,40,35,40,45,50,35,60,25,60,25,40,4,65,85,65,50,75,50,75,85,65,85,3,65,56,49,29,57,24,72,50,4,68,53,70,53,70,55,68,55,68,53,5,50,21,60,15,70,14,79,15,87,20,81,10,1,86,20,77,21')
[1134]	190	NEUROPROP(p,0,0,power,f,0.0,1.0,0.25,power)
[187]	191	NEUROPROP(r,0,0,bending range,f,0.0,1.0,1.0,bendrange)
	192	ENDNEUROCLASS
	193
	194	NEUROCLASS(RotMuscle,@,Rotation muscle,,1,0,2)
[932]	195	SHAPETYPE(BallAndStickShapeType)
[1134]	196	VISUALHINTS(DontShowClass+EffectorClass+IsV1RotMuscle+AtFirstPart)
[187]	197	SYMBOL(`5,5,25,40,35,40,45,50,35,60,25,60,25,40,4,65,85,65,50,75,50,75,85,65,85,1,69,10,77,17,10,59,15,57,17,57,22,60,26,69,27,78,26,82,21,82,16,79,12,69,10,80,6,3,65,50,65,20,75,20,75,50')
[1134]	198	NEUROPROP(p,0,0,power,f,0.0,1.0,1.0,power)
[187]	199	ENDNEUROCLASS
	200
[945]	201	NEUROCLASS(SolidMuscle,M,Muscle for solids,,1,0,2)
[932]	202	SHAPETYPE(SolidsShapeType)
[975]	203	JOINTTYPE(SUPPORTED_JOINT_HINGE_X+SUPPORTED_JOINT_HINGE_XY)
[1134]	204	VISUALHINTS(EffectorClass+AtFirstPart+IsSolidMuscle)
[920]	205	SYMBOL(`6,5,25,40,35,40,45,50,35,60,25,60,25,40,4,65,85,65,50,75,50,75,85,65,85,3,65,56,49,29,57,24,72,50,4,68,53,70,53,70,55,68,55,68,53,5,50,21,60,15,70,14,79,15,87,20,81,10,1,86,20,77,21')
[1134]	206	NEUROPROP(p,0,0,power,f,0.0,1.0,1.0,power)
[920]	207	NEUROPROP(a,0,0,axis,d,0,1,0,axis)
	208	ENDNEUROCLASS
	209
[187]	210	NEUROCLASS(Diff,D,Differentiate,Calculate the difference between the current and previous input value. Multiple inputs are aggregated with respect to their weights,-1,1,0)
	211	SYMBOL(`3,3,25,0,25,100,75,50,25,0,1,75,50,100,50,3,44,42,51,57,36,57,44,42')
	212	ENDNEUROCLASS
	213
	214	NEUROCLASS(FuzzyNeuro,Fuzzy,Fuzzy system [EXPERIMENTAL!],Refer to publications to learn more about this neuron.,-1,1,0)
	215	SYMBOL(`5,2,30,65,37,37,44,65,3,37,65,44,37,51,37,58,65,2,51,65,58,37,65,65,6,100,50,70,50,70,25,25,10,25,90,70,75,70,50,1,70,65,25,65')
	216	NEUROPROP(ns,0,0,number of fuzzy sets,d,1,,,fuzzySetsNr)
	217	NEUROPROP(nr,0,0,number of rules,d,1,,,rulesNr)
[419]	218	NEUROPROP(fs,0,0,fuzzy sets,s,0,-1,,fuzzySetString)
	219	NEUROPROP(fr,0,0,fuzzy rules,s,0,-1,,fuzzyRulesString)
[187]	220	ENDNEUROCLASS
	221
	222	NEUROCLASS(VectorEye,VEye,Vector Eye [EXPERIMENTAL!],Refer to publications to learn more about this neuron.,1,1,1)
	223	SYMBOL(`11,7,100,50,90,50,90,40,70,40,80,50,70,60,90,60,90,50,14,70,50,65,40,60,35,45,30,30,30,15,35,10,40,5,50,10,60,15,65,30,70,45,70,60,65,65,60,70,50,8,38,67,28,62,23,52,28,42,38,37,48,42,53,52,48,62,38,67,4,33,52,38,47,43,52,38,57,33,52,5,70,50,60,40,45,35,30,35,15,40,5,50,1,53,33,58,22,1,62,36,68,26,1,45,30,47,19,1,35,30,35,19,1,27,31,24,20,1,18,34,12,24')
	224	NEUROPROP(tx,0,0,target.x,f,,,,target.x)
	225	NEUROPROP(ty,0,0,target.y,f,,,,target.y)
	226	NEUROPROP(tz,0,0,target.z,f,,,,target.z)
[419]	227	NEUROPROP(ts,0,0,target shape,s,0,-1,,targetShape)
[187]	228	NEUROPROP(p,0,0,perspective,f,0.1,10.0,1.0,perspz)
	229	NEUROPROP(s,0,0,scale,f,0.1,100.0,1.0,perspscale)
	230	NEUROPROP(h,0,0,show hidden lines,d,0,1,0,showhidden)
	231	NEUROPROP(o,0,0,`output lines count (each line needs four channels)',d,0,99,0,outputcount)
	232	NEUROPROP(d,0,0,debug,d,0,1,0,showdebug)
	233	ENDNEUROCLASS
	234
	235	NEUROCLASS(VisualMotorNeuron,VMotor,Visual-Motor Cortex [EXPERIMENTAL!],`Must be connected to the VEye and properly set up. Refer to publications to learn more about this neuron.',-1,1,0)
	236	NEUROPROP(noIF,0,0,number of basic features,d,,,,noIF)
	237	NEUROPROP(noDim,0,0,number of degrees of freedom,d,,,,noDim)
	238	NEUROPROP(params,0,0,parameters,s,,,,params)
	239	ENDNEUROCLASS
	240
	241	NEUROCLASS(Sticky,Sti,Sticky [EXPERIMENTAL!],,1,0,1)
[932]	242	SHAPETYPE(BallAndStickShapeType)
[187]	243	VISUALHINTS(EffectorClass)
	244	ENDNEUROCLASS
	245
	246	NEUROCLASS(LinearMuscle,LMu,Linear muscle [EXPERIMENTAL!],,1,0,2)
[932]	247	SHAPETYPE(BallAndStickShapeType)
[1134]	248	VISUALHINTS(EffectorClass+IsLinearMuscle)
[187]	249	NEUROPROP(p,0,0,power,f,0.01,1.0,1.0,power)
	250	ENDNEUROCLASS
	251
	252	NEUROCLASS(WaterDetect,Water,Water detector,`Output signal:\n0=on or above water surface\n1=under water (deeper than 1)\n0..1=in the transient area just below water surface',0,1,1)
	253	VISUALHINTS(ReceptorClass)
	254	ENDNEUROCLASS
	255
	256	NEUROCLASS(Energy,Energy,Energy level,`The current energy level divided by the initial energy level.\nUsually falls from initial 1.0 down to 0.0 and then the creature dies. It can rise above 1.0 if enough food is ingested',0,1,0)
	257	VISUALHINTS(ReceptorClass)
	258	ENDNEUROCLASS
	259
	260	NEUROCLASS(Channelize,Ch,Channelize,`Combines all input signals into a single multichannel output; Note: ChSel and ChMux are the only neurons which support multiple channels. Other neurons discard everything except the first channel.',-1,1,0)
	261	SYMBOL(`10,4,25,0,25,100,75,70,75,30,25,0,1,75,50,100,50,1,70,50,55,50,1,30,80,55,50,1,30,20,55,50,1,30,35,55,50,1,30,45,55,50,1,30,55,55,50,1,61,53,65,47,1,30,65,55,50')
	262	ENDNEUROCLASS
	263
	264	NEUROCLASS(ChMux,ChMux,Channel multiplexer,`Outputs the selected channel from the second (multichannel) input. The first input is used as the selector value (-1=select first channel, .., 1=last channel)',2,1,0)
	265	SYMBOL(`7,4,25,0,25,100,75,70,75,30,25,0,1,75,50,100,50,1,70,50,55,50,3,50,55,55,50,50,45,50,55,3,30,67,45,67,45,50,50,50,1,35,70,39,64,2,30,33,53,33,53,48')
	266	ENDNEUROCLASS
	267
	268	NEUROCLASS(ChSel,ChSel,Channel selector,`Outputs a single channel (selected by the \"ch\" parameter) from multichannel input',1,1,0)
	269	SYMBOL(`6,4,25,0,25,100,75,70,75,30,25,0,1,75,50,100,50,1,70,50,55,50,3,50,55,55,50,50,45,50,55,1,30,50,50,50,1,35,53,39,47')
	270	NEUROPROP(ch,0,0,channel,d,,,,ch)
	271	ENDNEUROCLASS
	272
	273	NEUROCLASS(Random,Rnd,Random noise,`Generates random noise (subsequent random values in the range of -1..+1)',0,1,0)
	274	ENDNEUROCLASS
	275
	276	NEUROCLASS(Sinus,Sin,Sinus generator,`Output frequency = f0+input',1,1,0)
	277	SYMBOL(`3,12,75,50,71,37,62,28,50,25,37,28,28,37,25,50,28,62,37,71,50,75,62,71,71,62,75,50,1,75,50,100,50,5,35,50,40,35,45,35,55,65,60,65,65,50')
	278	NEUROPROP(f0,0,0,base frequency,f,-1.0,1.0,0.06283185307,f0)
	279	NEUROPROP(t,0,0,time,f,0,6.283185307,0,t)
	280	ENDNEUROCLASS

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