/*
title: Chromies - Desperate Omnivores V24
files:
head
pointlist
point
../point_src/stage.js
mouse
dragging
stroke
---
228 colour creatures (28 large, 200 half-sized and slower) seek similar hues, blend on contact, and merge with close matches.
Drag them into each other to play genetic matchmaker. Big creatures that go 800 frames without merging burst into a random number of differently sized, random-coloured offspring while conserving mass.
*/
class MainStage extends Stage {
canvas = 'playspace'
randomGenes() {
return {
aggression: Math.random(),
fear: Math.random(),
speed: .12 + Math.pow(Math.random(),.85) * 5.1,
turnRate: .008 + Math.random() * .48,
curiosity: Math.random(),
metabolism: .25 + Math.random() * 1.85,
longevity: .45 + Math.random() * 1.65,
digestion: .55 + Math.random() * 1.45,
sociability: Math.random()
}
}
inheritGenes(parent, other, weight=1) {
const genes = {}
for (const key of ['aggression','fear','speed','turnRate','curiosity','metabolism','longevity','digestion','sociability']) {
const center = other ? parent[key]*weight + other[key]*(1-weight) : parent[key]
const variation = key==='speed' ? 1.25 : key==='turnRate' ? .085 : key==='metabolism' || key==='longevity' || key==='digestion' ? .28 : .25
const lo = key==='speed' ? .12 : key==='turnRate' ? .008 : key==='metabolism' ? .25 : key==='longevity' ? .45 : key==='digestion' ? .55 : 0
const hi = key==='speed' ? 5.2 : key==='turnRate' ? .5 : key==='metabolism' ? 2.1 : key==='longevity' ? 2.1 : key==='digestion' ? 2 : 1
const roll=Math.random()
const candidate=roll<.22 ? lo+Math.random()*(hi-lo) : center+(Math.random()+Math.random()-1)*variation*(roll<.5?2:1)
genes[key]=Math.max(lo,Math.min(hi,candidate))
}
return genes
}
initialiseLife(p) {
p.energy = 65 + Math.random() * 35
p.age = 0
p.lifespan = Math.round(3000 * p.genes.longevity)
p.maturity = 0
p.digestTimer = 0
}
makeFood(x,y,mass=.25,hue=null) {
this.nutrients.push({x,y,mass,hue,vx:(Math.random()-.5)*.32,vy:(Math.random()-.5)*.32,phase:Math.random()*6.283})
}
recycle(p) {
const count=Math.max(1,Math.min(6,Math.ceil(p.mass/.25)))
for(let i=0;i
previous && d<=wave.r+5) {
const theta=d<.001?Math.random()*Math.PI*2:Math.atan2(dy,dx);
const near=1-Math.min(1,d/wave.radius);
const shove=(5+Math.pow(near,1.2)*33)*wave.strength;
p.knockX=(p.knockX||0)+Math.cos(theta)*shove*.14;
p.knockY=(p.knockY||0)+Math.sin(theta)*shove*.14;
}
}
}
this.shockwaves=this.shockwaves.filter(w=>w.age=8 || !this.nutrients.length)return
if(this.points.length>0 && Math.random()>.04)return
const f=this.nutrients.shift()
const p=new Point({x:f.x,y:f.y,radius:Math.max(1,4*Math.sqrt(f.mass))})
p.genes=this.randomGenes()
this.initialiseLife(p)
p.energy=40
p.mass=f.mass
p.hue=Math.floor(Math.random()*12)*30
p.vx=(Math.random()-.5)*.7;p.vy=(Math.random()-.5)*.7
p.speedScale=1;p.cool=60;p.hunger=0
this.points.push(p);this.dragging.add(p)
}
addChromies() {
// Introduce genuinely new arrivals, with fresh colours and independently rolled genes.
// Stay inside the existing simulation's 400-creature population ceiling.
const available=Math.max(0,400-this.points.length);
const count=Math.min(available,3+Math.floor(Math.random()*4));
const w=this.canvas.width,h=this.canvas.height;
const newcomers=[];
for(let i=0;i 0) p.cool--
if (p.digestTimer > 0) p.digestTimer--
p.hunger = (p.hunger || 0) + 1
p.age++
const activity = Math.hypot(p.vx,p.vy)
p.energy -= (.005 + activity * .004 + p.genes.aggression * .004) * p.genes.metabolism
p.energy = Math.max(0,Math.min(150,p.energy))
const mates=[]; let friend = null, best = Infinity
let threat = null, threatScore = 0
for (const q of ps) {
if (p === q) continue
const dx=this.wrapDelta(p.x,q.x,width), dy=this.wrapDelta(p.y,q.y,height)
const dist=Math.hypot(dx,dy)||.001
const hue=this.hueDiff(p.hue,q.hue)
const danger = (q.radius / Math.max(1,p.radius)) * (q.genes ? q.genes.aggression : .5)
const range = 18 + p.radius * 4 + 50*p.genes.fear
if (danger > .45 && dist < range) {
const intensity = (range-dist)/range * danger
if (intensity > threatScore) {threatScore=intensity;threat=q}
}
const score = hue*3 + dist*.12 - p.genes.curiosity * (1 - Math.min(1,dist/180)) * 18
if (score < best) {best=score; friend=q}
if(hue<35 && dist<175 && p.genes.sociability>.12) {
mates.push({q,score:dist + hue*.7});
}
// Gently repel neighbours so the screen stays lively.
const personalSpace = 20 + p.radius + q.radius
if (dist < personalSpace && dist > 0) {
const force = (personalSpace-dist)/personalSpace*.13 * p.speedScale * (1+.6*p.genes.fear)
p.vx -= dx/dist*force
p.vy -= dy/dist*force
}
}
// Starving swimmers become opportunistic: any colour, any size.
const desperate=p.energy<35;
// Stay committed unless a clearly better-sized meal appears.
if(p.digestTimer<=0 && p.energy<90 && this.nutrients.length){
const quality=(f)=>{
const dx=this.wrapDelta(p.x,f.x,width),dy=this.wrapDelta(p.y,f.y,height);
const dist=Math.hypot(dx,dy);
return dist<=(desperate?300:160) ? (desperate ? 1/(12+dist) : Math.pow(Math.max(.02,f.mass),.65+Math.min(1.35,p.mass*.18))/(24+dist)) : 0;
};
let bestFood=null,bestScore=0;
for(const f of this.nutrients){
const score=quality(f);
if(score>bestScore){bestFood=f;bestScore=score;}
}
const current=p.foodTarget;
const currentScore=current&&this.nutrients.includes(current)?quality(current):0;
if(!currentScore || (p.foodCommit||0)<=0 ||
(bestFood!==current && bestScore>currentScore*1.65)){
p.foodTarget=bestFood;
p.foodCommit=24+Math.floor(Math.random()*17);
}
p.foodCommit--;
const food=p.foodTarget;
if(food){
const dx=this.wrapDelta(p.x,food.x,width),dy=this.wrapDelta(p.y,food.y,height);
const dist=Math.hypot(dx,dy)||1;
if(dist<(desperate?300:160)){
const hunger=(90-p.energy)/90;
const drive=desperate?.38:.14*hunger;
p.vx+=dx/dist*drive*p.speedScale;
p.vy+=dy/dist*drive*p.speedScale;
}
}
} else {
p.foodTarget=null;p.foodCommit=0;
}
if(!desperate && mates.length && p.genes.sociability>.12) {
// Duckies-style local cohesion: seek the centre of 2-3 similar neighbours.
mates.sort((a,b)=>a.score-b.score);
const n=Math.min(mates.length,p.genes.sociability>.55?3:2);
let dx=0,dy=0,ax=0,ay=0;
for(let i=0;ilimit) {p.vx*=limit/speed; p.vy*=limit/speed}
// Gene-limited steering: smooth, individual turns.
if (Math.hypot(p.vx,p.vy) > .03) {
const target=Math.atan2(p.vy,p.vx)
if (!Number.isFinite(p.radians)) p.radians=target
const delta=Math.atan2(Math.sin(target-p.radians),Math.cos(target-p.radians))
p.radians+=Math.max(-p.genes.turnRate,Math.min(p.genes.turnRate,delta))
const magnitude=Math.hypot(p.vx,p.vy)
p.vx=Math.cos(p.radians)*magnitude
p.vy=Math.sin(p.radians)*magnitude
}
p.x+=p.vx+(p.knockX||0);
p.y+=p.vy+(p.knockY||0);
p.knockX=(p.knockX||0)*.88;
p.knockY=(p.knockY||0)*.88;
if(Math.abs(p.knockX)<.015)p.knockX=0;
if(Math.abs(p.knockY)<.015)p.knockY=0
// Toroidal screen wrap. Reset the visual tail at the seam so it
// doesn't draw a long line across the canvas.
let wrapped = false
if(p.x < -p.radius) {p.x=width+p.radius;wrapped=true}
if(p.x > width+p.radius) {p.x=-p.radius;wrapped=true}
if(p.y < -p.radius) {p.y=height+p.radius;wrapped=true}
if(p.y > height+p.radius) {p.y=-p.radius;wrapped=true}
if(wrapped) p.tail = null
}
const eaten = new Set()
for(const p of ps){
if(p.digestTimer > 0)continue
for(const f of this.nutrients){
if(eaten.has(f))continue
const dx=Math.abs(f.x-p.x),dy=Math.abs(f.y-p.y)
if(Math.hypot(Math.min(dx,width-dx),Math.min(dy,height-dy))!eaten.has(f))
const gone = new Set()
for (let i=0;i= a.radius+b.radius)continue
const difference=this.hueDiff(a.hue,b.hue)
if(difference < 18 && ps.length-gone.size>3) {
const total=a.mass+b.mass
a.x=(a.x*a.mass+b.x*b.mass)/total
a.y=(a.y*a.mass+b.y*b.mass)/total
a.vx=(a.vx*a.mass+b.vx*b.mass)/total
a.vy=(a.vy*a.mass+b.vy*b.mass)/total
a.radians=Math.atan2(a.vy,a.vx)
a.hue=this.mixHue(a.hue,b.hue)
a.genes=this.inheritGenes(a.genes,b.genes,a.mass/total)
a.energy=Math.min(150,a.energy+b.energy*.65)
a.lifespan=Math.round(3000*a.genes.longevity)
a.mass=total
a.speedScale=1
a.radius=Math.min(17,4*Math.sqrt(total))
a.cool=25
a.hunger=0
a.digestTimer=Math.max(a.digestTimer||0,b.digestTimer||0)
gone.add(b)
} else {
const blended=this.mixHue(a.hue,b.hue)
a.hue=(a.hue*.7+blended*.3)%360
b.hue=(b.hue*.7+blended*.3)%360
a.cool=b.cool=22
const nx=dx/(dist||1),ny=dy/(dist||1)
a.vx-=nx*.7*a.speedScale;a.vy-=ny*.7*a.speedScale
b.vx+=nx*.7*b.speedScale;b.vy+=ny*.7*b.speedScale
}
}
}
// Starved adults burst into a random number of unequal pieces.
// Offspring masses sum to the parent's mass (last takes the remainder).
const newborns = []
let population = ps.length - gone.size
for (const p of ps) {
if (gone.has(p) || p.mass < 1.5 || p.hunger < 800 || p.energy < 25) continue
const maxPieces = Math.min(10, Math.floor(p.mass / .20), 400 - population + 1)
if (maxPieces < 2) continue
const baseCount = 2 + Math.floor(Math.random()*Math.max(1,Math.min(7,Math.floor(p.mass/.25))-1))
const count = Math.max(2,Math.min(maxPieces,Math.round(baseCount*1.3)))
const weights = Array.from({length: count}, () => .3 + Math.random() * 2)
const weightSum = weights.reduce((a,b) => a+b,0)
let remaining = p.mass
const baseAngle = Math.random() * Math.PI * 2
const offspring = []
for (let i = 0; i < count; i++) {
const childMass = i === count - 1 ? remaining : p.mass * weights[i] / weightSum
remaining -= childMass
// Radius represents mass, not a mass deduction.
const childRadius = Math.max(1, Math.min(17, 4 * Math.sqrt(childMass)))
const theta = baseAngle + i * 2 * Math.PI / count
const offset = p.radius + childRadius + 2
const child = new Point({
x: Math.max(childRadius, Math.min(width-childRadius, p.x + Math.cos(theta)*offset)),
y: Math.max(childRadius, Math.min(height-childRadius, p.y + Math.sin(theta)*offset)),
radius: childRadius
})
child.genes = this.inheritGenes(p.genes)
this.initialiseLife(child)
child.energy = Math.max(10, p.energy/count)
child.mass = childMass
child.hue = Math.random()<.24 ? Math.random()*360 : this.wheelStep(p.hue,(p.hue+(Math.random()+Math.random()-1)*210+360)%360,.65)
child.vx = p.vx + Math.cos(theta) * .7
child.vy = p.vy + Math.sin(theta) * .7
child.speedScale = 1
child.cool = 45
child.hunger = 0
child.radians = Math.atan2(child.vy, child.vx)
offspring.push(child)
}
this.popShockwave(p,Math.min(1.35,.7+p.mass*.09))
gone.add(p)
newborns.push(...offspring)
population += count - 1
}
// Older creatures gradually fade; exhaustion slows movement rather than
// instantly deleting the entire population.
for(const p of ps) {
if(gone.has(p))continue
if(p.age > p.lifespan) {
p.energy -= .035 * p.genes.metabolism
}
if(p.energy <= 0 && p.age > 500) {this.popShockwave(p,.65);gone.add(p);this.recycle(p)}
}
if(gone.size || newborns.length) {
// Keep the surviving Point objects and re-register dragging.
const survivors=Array.from(ps).filter(p=>!gone.has(p))
this.points=new PointList(...survivors, ...newborns)
this.dragging.add(...newborns)
}
this.germinate()
}
updateTail(p) {
const count=7, spacing=Math.max(1.1,p.radius*.48)
if(!p.tail) {
const angle=p.radians||0
p.tail=Array.from({length:count},(_,i)=>({x:p.x-Math.cos(angle)*spacing*(i+1),y:p.y-Math.sin(angle)*spacing*(i+1)}))
p.swimPhase=Math.random()*Math.PI*2
}
const v=Math.hypot(p.vx,p.vy)
p.swimPhase+=.09+Math.min(.22,v*.055)
let leader=p
const angle=p.radians||0
for(let i=0;ir.life>0)
ctx.restore()
ctx.save()
for(const f of this.nutrients){
const r=Math.max(1.2,Math.min(3,2*Math.sqrt(f.mass/.25)))
ctx.fillStyle=Number.isFinite(f.hue)?`hsla(${f.hue} 65% 35% / .85)`:'rgba(32,40,53,.8)'
ctx.beginPath();ctx.arc(f.x,f.y,r,0,Math.PI*2);ctx.fill()
ctx.fillStyle=Number.isFinite(f.hue)?`hsla(${f.hue} 80% 70% / .65)`:'rgba(95,107,120,.55)'
ctx.beginPath();ctx.arc(f.x-.35,f.y-.45,.5,0,Math.PI*2);ctx.fill()
}
ctx.restore()
for(const p of this.points) {
this.updateTail(p)
this.drawTail(ctx,p)
ctx.beginPath()
ctx.arc(p.x,p.y,Math.max(.8,p.radius*.66),0,Math.PI*2)
ctx.fillStyle=`hsl(${p.hue} 85% ${Math.max(33,65-(p.age/p.lifespan)*18)}%)`
ctx.fill()
}
}
}
const stage=MainStage.go()