JS 는 Sketch.js 를 바탕 으로 무 리 를 지어 움 직 이 는 올챙이 운동 애니메이션 효 과 를 실현 합 니 다[데모 소스 다운로드 첨부]
Sketch.js 를 바탕 으로 물체 터치 검 측(올챙이 가 장애물 에 부 딪 히 고 똑똑 하 게 마 우 스 를 피 하 는 클릭),랜 덤 운동,집적 알고리즘 등 을 실현 했다.
이미 게임 의 기본 요 소 를 갖 추고 있어 서 확장 하면 괜 찮 은 HTML 5 게임 이 될 수 있다.
데모 효 과 는 다음 과 같 습 니 다.
전체 코드 는 다음 과 같 습 니 다:
<!DOCTYPE html>
<html class=" -webkit- js flexbox canvas canvastext webgl no-touch geolocation postmessage websqldatabase indexeddb hashchange history draganddrop websockets rgba hsla multiplebgs backgroundsize borderimage borderradius boxshadow textshadow opacity cssanimations csscolumns cssgradients cssreflections csstransforms csstransforms3d csstransitions fontface generatedcontent video audio localstorage sessionstorage webworkers applicationcache svg inlinesvg smil svgclippaths">
<head>
<meta charset="UTF-8">
<title>HTML5 Preview Panel</title>
<script src="prefixfree.min.js"></script>
<script src="modernizr.js"></script>
<style>
body {
background-color: #222;
}
</style>
</head>
<body>
<script src="sketch.min.js"></script>
<div id="container">
<canvas class="sketch" id="sketch-0" height="208" width="607"></canvas>
</div>
<script>
var calculateDistance = function(object1, object2) {
x = Math.abs(object1.x - object2.x);
y = Math.abs(object1.y - object2.y);
return Math.sqrt((x * x) + (y * y));
};
var calcMagnitude = function(x, y) {
return Math.sqrt((x * x) + (y * y));
};
var calcVectorAdd = function(v1, v2) {
return {
x: v1.x + v2.x,
y: v1.y + v2.y
};
};
var random = function(min, max) {
return min + Math.random() * (max - min);
};
var getRandomItem = function(list, weight) {
var total_weight = weight.reduce(function(prev, cur, i, arr) {
return prev + cur;
});
var random_num = random(0, total_weight);
var weight_sum = 0;
//console.log(random_num)
for (var i = 0; i < list.length; i++) {
weight_sum += weight[i];
weight_sum = +weight_sum.toFixed(2);
if (random_num <= weight_sum) {
return list[i];
}
}
// end of function
};
/***********************
BOID
***********************/
function Boid(x, y) {
this.init(x, y);
}
Boid.prototype = {
init: function(x, y) {
//body
this.type = "boid";
this.alive = true;
this.health = 1;
this.maturity = 4;
this.speed = 6;
this.size = 5;
this.hungerLimit = 12000;
this.hunger = 0;
this.isFull = false;
this.digestTime = 400;
this.color = 'rgb(' + ~~random(0, 100) + ',' + ~~random(50, 220) + ',' + ~~random(50, 220) + ')';
//brains
this.eyesight = 100; //range for object dectection
this.personalSpace = 20; //distance to avoid safe objects
this.flightDistance = 60; //distance to avoid scary objects
this.flockDistance = 100; //factor that determines how attracted the boid is to the center of the flock
this.matchVelFactor = 6; //factor that determines how much the flock velocity affects the boid. less = more matching
this.x = x || 0.0;
this.y = y || 0.0;
this.v = {
x: random(-1, 1),
y: random(-1, 1),
mag: 0
};
this.unitV = {
x: 0,
y: 0,
};
this.v.mag = calcMagnitude(this.v.x, this.v.y);
this.unitV.x = (this.v.x / this.v.mag);
this.unitV.y = (this.v.y / this.v.mag);
},
wallAvoid: function(ctx) {
var wallPad = 10;
if (this.x < wallPad) {
this.v.x = this.speed;
} else if (this.x > ctx.width - wallPad) {
this.v.x = -this.speed;
}
if (this.y < wallPad) {
this.v.y = this.speed;
} else if (this.y > ctx.height - wallPad) {
this.v.y = -this.speed;
}
},
ai: function(boids, index, ctx) {
percievedCenter = {
x: 0,
y: 0,
count: 0
};
percievedVelocity = {
x: 0,
y: 0,
count: 0
};
mousePredator = {
x: ((typeof ctx.touches[0] === "undefined") ? 0 : ctx.touches[0].x),
y: ((typeof ctx.touches[0] === "undefined") ? 0 : ctx.touches[0].y)
};
for (var i = 0; i < boids.length; i++) {
if (i != index) {
dist = calculateDistance(this, boids[i]);
//Find all other boids close to it
if (dist < this.eyesight) {
//if the same species then flock
if (boids[i].type == this.type) {
//Alignment
percievedCenter.x += boids[i].x;
percievedCenter.y += boids[i].y;
percievedCenter.count++;
//Cohesion
percievedVelocity.x += boids[i].v.x;
percievedVelocity.y += boids[i].v.y;
percievedVelocity.count++;
//Separation
if (dist < this.personalSpace + this.size + this.health) {
this.avoidOrAttract("avoid", boids[i]);
}
} else {
//if other species fight or flight
if (dist < this.size + this.health + boids[i].size + boids[i].health) {
this.eat(boids[i]);
} else {
this.handleOther(boids[i]);
}
}
} //if close enough
} //dont check itself
} //Loop through boids
//Get the average for all near boids
if (percievedCenter.count > 0) {
percievedCenter.x = ((percievedCenter.x / percievedCenter.count) - this.x) / this.flockDistance;
percievedCenter.y = ((percievedCenter.y / percievedCenter.count) - this.y) / this.flockDistance;
this.v = calcVectorAdd(this.v, percievedCenter);
}
if (percievedVelocity.count > 0) {
percievedVelocity.x = ((percievedVelocity.x / percievedVelocity.count) - this.v.x) / this.matchVelFactor;
percievedVelocity.y = ((percievedVelocity.y / percievedVelocity.count) - this.v.y) / this.matchVelFactor;
this.v = calcVectorAdd(this.v, percievedVelocity);
}
//Avoid Mouse
if (calculateDistance(mousePredator, this) < this.eyesight) {
var mouseModifier = 20;
this.avoidOrAttract("avoid", mousePredator, mouseModifier);
}
this.wallAvoid(ctx);
this.limitVelocity();
},
setUnitVector: function() {
var magnitude = calcMagnitude(this.v.x, this.v.y);
this.v.x = this.v.x / magnitude;
this.v.y = this.v.y / magnitude;
},
limitVelocity: function() {
this.v.mag = calcMagnitude(this.v.x, this.v.y);
this.unitV.x = (this.v.x / this.v.mag);
this.unitV.y = (this.v.y / this.v.mag);
if (this.v.mag > this.speed) {
this.v.x = this.unitV.x * this.speed;
this.v.y = this.unitV.y * this.speed;
}
},
avoidOrAttract: function(action, other, modifier) {
var newVector = {
x: 0,
y: 0
};
var direction = ((action === "avoid") ? -1 : 1);
var vModifier = modifier || 1;
newVector.x += ((other.x - this.x) * vModifier) * direction;
newVector.y += ((other.y - this.y) * vModifier) * direction;
this.v = calcVectorAdd(this.v, newVector);
},
move: function() {
this.x += this.v.x;
this.y += this.v.y;
if (this.v.mag > this.speed) {
this.hunger += this.speed;
} else {
this.hunger += this.v.mag;
}
},
eat: function(other) {
if (!this.isFull) {
if (other.type === "plant") {
other.health--;
this.health++;
this.isFull = true;
this.hunger = 0;
}
}
},
handleOther: function(other) {
if (other.type === "predator") {
this.avoidOrAttract("avoid", other);
}
},
metabolism: function() {
if (this.hunger >= this.hungerLimit) {
this.health--;
this.hunger = 0;
}
if (this.hunger >= this.digestTime) {
this.isFull = false;
}
if (this.health <= 0) {
this.alive = false;
}
},
mitosis: function(boids) {
if (this.health >= this.maturity) {
//reset old boid
this.health = 1;
birthedBoid = new Boid(
this.x + random(-this.personalSpace, this.personalSpace),
this.y + random(-this.personalSpace, this.personalSpace)
);
birthedBoid.color = this.color;
boids.push(birthedBoid);
}
},
draw: function(ctx) {
drawSize = this.size + this.health;
ctx.beginPath();
ctx.moveTo(this.x + (this.unitV.x * drawSize), this.y + (this.unitV.y * drawSize));
ctx.lineTo(this.x + (this.unitV.y * drawSize), this.y - (this.unitV.x * drawSize));
ctx.lineTo(this.x - (this.unitV.x * drawSize * 2), this.y - (this.unitV.y * drawSize * 2));
ctx.lineTo(this.x - (this.unitV.y * drawSize), this.y + (this.unitV.x * drawSize));
ctx.lineTo(this.x + (this.unitV.x * drawSize), this.y + (this.unitV.y * drawSize));
ctx.fillStyle = this.color;
ctx.shadowBlur = 20;
ctx.shadowColor = this.color;
ctx.fill();
}
};
Predator.prototype = new Boid();
Predator.prototype.constructor = Predator;
Predator.constructor = Boid.prototype.constructor;
function Predator(x, y) {
this.init(x, y);
this.type = "predator";
//body
this.maturity = 6;
this.speed = 6;
this.hungerLimit = 25000;
this.color = 'rgb(' + ~~random(100, 250) + ',' + ~~random(10, 30) + ',' + ~~random(10, 30) + ')';
//brains
this.eyesight = 150;
this.flockDistance = 300;
}
Predator.prototype.eat = function(other) {
if (!this.isFull) {
if (other.type === "boid") {
other.health--;
this.health++;
this.isFull = true;
this.hunger = 0;
}
}
};
Predator.prototype.handleOther = function(other) {
if (other.type === "boid") {
if (!this.isFull) {
this.avoidOrAttract("attract", other);
}
}
};
Predator.prototype.mitosis = function(boids) {
if (this.health >= this.maturity) {
//reset old boid
this.health = 1;
birthedBoid = new Predator(
this.x + random(-this.personalSpace, this.personalSpace),
this.y + random(-this.personalSpace, this.personalSpace)
);
birthedBoid.color = this.color;
boids.push(birthedBoid);
}
};
Plant.prototype = new Boid();
Plant.prototype.constructor = Plant;
Plant.constructor = Boid.prototype.constructor;
function Plant(x, y) {
this.init(x, y);
this.type = "plant";
//body
this.speed = 0;
this.size = 10;
this.health = ~~random(1, 10);
this.color = 'rgb(' + ~~random(130, 210) + ',' + ~~random(40, 140) + ',' + ~~random(160, 220) + ')';
//brains
this.eyesight = 0;
this.flockDistance = 0;
this.eyesight = 0; //range for object dectection
this.personalSpace = 100; //distance to avoid safe objects
this.flightDistance = 0; //distance to avoid scary objects
this.flockDistance = 0; //factor that determines how attracted the boid is to the center of the flock
this.matchVelFactor = 0; //factor that determines how much the flock velocity affects the boid
}
Plant.prototype.ai = function(boids, index, ctx) {};
Plant.prototype.move = function() {};
Plant.prototype.mitosis = function(boids) {
var growProbability = 1,
maxPlants = 40,
plantCount = 0;
for (m = boids.length - 1; m >= 0; m--) {
if (boids[m].type === "plant") {
plantCount++;
}
}
if (plantCount <= maxPlants) {
if (random(0, 100) <= growProbability) {
birthedBoid = new Plant(
this.x + random(-this.personalSpace, this.personalSpace),
this.y + random(-this.personalSpace, this.personalSpace)
);
birthedBoid.color = this.color;
boids.push(birthedBoid);
}
}
};
Plant.prototype.draw = function(ctx) {
var drawSize = this.size + this.health;
ctx.fillStyle = this.color;
ctx.shadowBlur = 40;
ctx.shadowColor = this.color;
ctx.fillRect(this.x - drawSize, this.y + drawSize, drawSize, drawSize);
};
/***********************
SIM
***********************/
var boids = [];
var sim = Sketch.create({
container: document.getElementById('container')
});
sim.setup = function() {
for (i = 0; i < 50; i++) {
x = random(0, sim.width);
y = random(0, sim.height);
sim.spawn(x, y);
}
};
sim.spawn = function(x, y) {
var predatorProbability = 0.1,
plantProbability = 0.3;
switch (getRandomItem(['boid', 'predator', 'plant'], [1 - predatorProbability - plantProbability, predatorProbability, plantProbability])) {
case 'predator':
boid = new Predator(x, y);
break;
case 'plant':
boid = new Plant(x, y);
break;
default:
boid = new Boid(x, y);
break;
}
boids.push(boid);
};
sim.update = function() {
for (i = boids.length - 1; i >= 0; i--) {
if (boids[i].alive) {
boids[i].ai(boids, i, sim);
boids[i].move();
boids[i].metabolism();
boids[i].mitosis(boids);
} else {
//remove dead boid
boids.splice(i, 1);
}
}
};
sim.draw = function() {
sim.globalCompositeOperation = 'lighter';
for (i = boids.length - 1; i >= 0; i--) {
boids[i].draw(sim);
}
sim.fillText(boids.length, 20, 20);
};
</script>
</body>
</html>
자 바스 크 립 트 관련 내용 에 관심 이 있 는 독자 들 은 본 사이트 의 주 제 를 볼 수 있다.
본 고 에서 말 한 것 이 여러분 의 자 바스 크 립 트 프로 그래 밍 에 도움 이 되 기 를 바 랍 니 다.
이 내용에 흥미가 있습니까?
현재 기사가 여러분의 문제를 해결하지 못하는 경우 AI 엔진은 머신러닝 분석(스마트 모델이 방금 만들어져 부정확한 경우가 있을 수 있음)을 통해 가장 유사한 기사를 추천합니다:
JS 판단 수조 네 가지 실현 방법 상세그러면 본고는 주로 몇 가지 판단 방식과 방식 판단의 원리를 바탕으로 문제가 있는지 토론하고자 한다. 예를 들어 html에 여러 개의 iframe 대상이 있으면 instanceof의 검증 결과가 기대에 부합되지 않을...
텍스트를 자유롭게 공유하거나 복사할 수 있습니다.하지만 이 문서의 URL은 참조 URL로 남겨 두십시오.
CC BY-SA 2.5, CC BY-SA 3.0 및 CC BY-SA 4.0에 따라 라이센스가 부여됩니다.
좋은 웹페이지 즐겨찾기
