Эффект вождения пальцем по воде

120
11 августа 2019, 12:20

Не знал, как точно сформировать вопрос, поэтому сразу прошу прощения.

У меня есть картинка (svg) с линиями, они не прямые, но это не важно. Мне нужен плагин или что то другое, который при неведении курсора будет создавать эффект, как будто водить пальцем по воде. То есть в том месте, где курсор, линии как бы расходятся, а когда убрать курсор - снова стают на место

Answer 1

Вот вариант водной поверхности на canvas, за основу взято демо от Jonas Wagner.

var floor = Math.floor; 
 
function loadImage(callback) { 
    var img = document.getElementById('bg'); 
    callback(img); 
} 
 
function getDataFromImage(img) { 
    canvas.width = img.width; 
    canvas.height = img.height; 
    ctx.clearRect(0, 0, img.width, img.height); 
    ctx.drawImage(img, 0 ,0); 
    return ctx.getImageData(0, 0, img.width, img.height); 
} 
 
function disturb(x, y, z){ 
    if(x < 2 || x > width-2 || y < 1 || y > height-2) 
        return; 
    var i = x+y*width; 
    buffer0[i] += z; 
    buffer0[i-1] -= z; 
} 
 
function process(){ 
    var img = ctx.getImageData(0, 0, width, height), 
        data = img.data, 
        i, x; 
 
    // average cells to make the surface more even 
    for(i=width+1;i<size-width-1;i+=2){ 
        for(x=1;x<width-1;x++,i++){ 
            buffer0[i] = (buffer0[i]+buffer0[i+1]+buffer0[i-1]+buffer0[i-width]+buffer0[i+width])/5; 
        } 
    } 
 
    for(i=width+1;i<size-width-1;i+=2){ 
        for(x=1;x<width-1;x++,i++){ 
            // wave propagation 
            var waveHeight = (buffer0[i-1] + buffer0[i+1] + buffer0[i+width] + buffer0[i-width])/2-buffer1[i]; 
            buffer1[i] = waveHeight; 
            // calculate index in the texture with some fake referaction 
            var ti = i+floor((buffer1[i-2]-waveHeight)*0.08)+floor((buffer1[i-width]-waveHeight)*0.08)*width; 
            // clamping 
            ti = ti < 0 ? 0 : ti > size ? size : ti; 
            // some very fake lighting and caustics based on the wave height 
            // and angle 
            var light = waveHeight*2.0-buffer1[i-2]*0.6, 
                i4 = i*4, 
                ti4 = ti*4; 
            // clamping 
            light = light < -10 ? -10 : light > 100 ? 100 : light; 
            data[i4] = texture.data[ti4]+light; 
            data[i4+1] = texture.data[ti4+1]+light; 
            data[i4+2] = texture.data[ti4+2]+light; 
        } 
    } 
    aux = buffer0; 
    buffer0 = buffer1; 
    buffer1 = aux; 
    ctx.putImageData(img, 0, 0); 
} 
var canvas = document.getElementById('c'), 
    ctx = canvas.getContext('2d'), 
    width = 320, 
    height = 240, 
    size = width*height, 
    buffer0 = [], 
    buffer1 = [], 
    aux, i, texture; 
 
for(i=0;i<size;i++){ 
    buffer0.push(0); 
    buffer1.push(0); 
} 
 
loadImage(function(img){ 
    texture = getDataFromImage(img); 
    canvas.width = width; 
    canvas.height = height; 
    ctx.fillRect(0, 0, width, height); 
    setInterval(process, 1000/60); 
    resizeBy(width-innerWidth, height-innerHeight); 
}); 
 
canvas.onmousemove = function(e){ 
    disturb( 
            floor(e.clientX/innerWidth*width), 
            floor(e.clientY/innerHeight*height), 
            15000); 
}
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Масштабируемый clipPath

Масштабируемый clipPath

Суть в том, что svg фигура в clipPath отрисовывается как есть, по тем самым размерам, с которыми создана

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использовать другой маркер

использовать другой маркер

Использую либу highchartsВстал вопрос - как вместо маркеров использовать диаграмму

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Правильный import/export React

Правильный import/export React

Подскажите как правильно експортировать и импортировать несколько const

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