围绕给定坐标旋转像素
Rotate the pixels around a given coordinate
前段时间做了一个太阳系动画，现在正在重写。我将为质量添加重力效果，为了使效果可见，我将背景变成了网格。
我将添加两种不同的效果；捏和旋转。我正在学习 Geek Office Dog: Hello swirl! (A swirl effect tutorial in javascript) 上的教程。循序渐进，首先，我想了解旋转是如何工作的。
这是从站点摘录的简单旋转演示：jsFiddle. The code seemed chaotic to me, so I modified and simplified it: jsFiddle。
var canvas = document.getElementById("canvas");
var context = canvas.getContext("2d");
var img = new Image();
img.src = document.getElementById("test-image").src;
img.onload = function () {
context.drawImage(img, 0, 0);
originalImageData = context.getImageData(0, 0, canvas.width, canvas.height);
originalPixels = originalImageData.data;
transformedImageData = context.createImageData(originalImageData);
transformedPixels = transformedImageData.data;
originX = 100;
originY = 100;
radius = 50;
// copying the original pixels into transformed pixels
for (var y = 0; y < originalImageData.height; y++) {
for (var x = 0; x < originalImageData.width; x++) {
var position = (y * originalImageData.width + x) * 4;
transformedPixels[position + 0] = originalPixels[position + 0];
transformedPixels[position + 1] = originalPixels[position + 1];
transformedPixels[position + 2] = originalPixels[position + 2];
transformedPixels[position + 3] = originalPixels[position + 3];
}
}
// Iterate over the interest square region
for (var y = -radius; y < radius; y++) {
for (var x = -radius; x < radius; x++) {
// Check if the pixel is inside the effect circle
if (x * x + y * y <= radius * radius) {
// Get the pixel array position
var sourcePosition = (y + originY) * originalImageData.width + x + originX;
sourcePosition *= 4;
// Transform the pixel cartesian coordinates (x, y) to polar coordinates (r, angle)
var r = Math.sqrt(x * x + y * y);
var angle = Math.atan2(y, x);
// convert the angle from radian to degree
var degrees = (angle * 180.0) / Math.PI;
// rotate the pixels
degrees -= 30.0;
// Transform back from polar coordinates to cartesian
angle = (degrees * Math.PI) / 180.0;
var newY = Math.floor(r * Math.sin(angle));
var newX = Math.floor(r * Math.cos(angle));
// Get the new pixel location
var destPosition = (newY + originY) * originalImageData.width + newX + originX;
destPosition *= 4;
transformedPixels[destPosition + 0] = originalPixels[sourcePosition + 0];
transformedPixels[destPosition + 1] = originalPixels[sourcePosition + 1];
transformedPixels[destPosition + 2] = originalPixels[sourcePosition + 2];
transformedPixels[destPosition + 3] = originalPixels[sourcePosition + 3];
}
}
}
context.putImageData(transformedImageData, 0, 0);
};
<table>
<tr>
<td>image</td>
<td>image</td>
<td>canvas</td>
</tr>
<tr>
<td><img id="test-image" border="1" src="data:image/png;base64,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"></td>
<td><img id="image-area" border="1" src="http://i1115.photobucket.com/albums/k544/akinuri/download%201.png"></td>
<td><canvas id="canvas" style="border: 1px solid blue" width="227" height="213"></canvas></td>
</tr>
</table>
我没看懂 // Iterate over the interest square region 部分。为什么它在 -radius 和 radius 之间循环以及 x * x + y * y <= radius * radius 究竟如何检查像素是否在圆圈内？
我无法想象那部分代码在我脑海中发生了什么。然而
更新： 好的，所以在考虑了一下之后，我认为在循环中：
// Iterate over the interest square region
for (var y = -radius; y < radius; y++) {
for (var x = -radius; x < radius; x++) {
// Check if the pixel is inside the effect circle
if (x * x + y * y <= radius * radius) {
我们实际上不是在迭代图像上的区域，而是一个理论区域。
并检查当前 (x,y) 是否在圆圈内。如果是，在下一行代码中，我们计算 (x,y) 在图像上的实际位置：
// Get the pixel array position
var sourcePosition = (y + originY) * originalImageData.width + x + originX;
sourcePosition *= 4;
Loops (+ if) 只是给我们圆内每个像素的坐标，然后我们将这些 (x,y) 坐标移动 (originX, originY) 值，这样我们就可以得到实际坐标图片。
我说的对吗？我是吗？ （请原谅我的激动:)
首先是简单的部分:)
x * x + y * y <= radius * radius
这就是毕达哥拉斯：
现在，如果您看那张图片，也很明显 x 和 y 在 -r 和 r 之间摆动，对吗？ :) 想象一下那些坐标在每个最左上角的...圆圈的点:)
前段时间做了一个太阳系动画，现在正在重写。我将为质量添加重力效果，为了使效果可见，我将背景变成了网格。
我将添加两种不同的效果；捏和旋转。我正在学习 Geek Office Dog: Hello swirl! (A swirl effect tutorial in javascript) 上的教程。循序渐进，首先，我想了解旋转是如何工作的。
这是从站点摘录的简单旋转演示：jsFiddle. The code seemed chaotic to me, so I modified and simplified it: jsFiddle。
var canvas = document.getElementById("canvas");
var context = canvas.getContext("2d");
var img = new Image();
img.src = document.getElementById("test-image").src;
img.onload = function () {
context.drawImage(img, 0, 0);
originalImageData = context.getImageData(0, 0, canvas.width, canvas.height);
originalPixels = originalImageData.data;
transformedImageData = context.createImageData(originalImageData);
transformedPixels = transformedImageData.data;
originX = 100;
originY = 100;
radius = 50;
// copying the original pixels into transformed pixels
for (var y = 0; y < originalImageData.height; y++) {
for (var x = 0; x < originalImageData.width; x++) {
var position = (y * originalImageData.width + x) * 4;
transformedPixels[position + 0] = originalPixels[position + 0];
transformedPixels[position + 1] = originalPixels[position + 1];
transformedPixels[position + 2] = originalPixels[position + 2];
transformedPixels[position + 3] = originalPixels[position + 3];
}
}
// Iterate over the interest square region
for (var y = -radius; y < radius; y++) {
for (var x = -radius; x < radius; x++) {
// Check if the pixel is inside the effect circle
if (x * x + y * y <= radius * radius) {
// Get the pixel array position
var sourcePosition = (y + originY) * originalImageData.width + x + originX;
sourcePosition *= 4;
// Transform the pixel cartesian coordinates (x, y) to polar coordinates (r, angle)
var r = Math.sqrt(x * x + y * y);
var angle = Math.atan2(y, x);
// convert the angle from radian to degree
var degrees = (angle * 180.0) / Math.PI;
// rotate the pixels
degrees -= 30.0;
// Transform back from polar coordinates to cartesian
angle = (degrees * Math.PI) / 180.0;
var newY = Math.floor(r * Math.sin(angle));
var newX = Math.floor(r * Math.cos(angle));
// Get the new pixel location
var destPosition = (newY + originY) * originalImageData.width + newX + originX;
destPosition *= 4;
transformedPixels[destPosition + 0] = originalPixels[sourcePosition + 0];
transformedPixels[destPosition + 1] = originalPixels[sourcePosition + 1];
transformedPixels[destPosition + 2] = originalPixels[sourcePosition + 2];
transformedPixels[destPosition + 3] = originalPixels[sourcePosition + 3];
}
}
}
context.putImageData(transformedImageData, 0, 0);
};
<table>
<tr>
<td>image</td>
<td>image</td>
<td>canvas</td>
</tr>
<tr>
<td><img id="test-image" border="1" 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"></td>
<td><img id="image-area" border="1" src="http://i1115.photobucket.com/albums/k544/akinuri/download%201.png"></td>
<td><canvas id="canvas" style="border: 1px solid blue" width="227" height="213"></canvas></td>
</tr>
</table>
我没看懂 // Iterate over the interest square region 部分。为什么它在 -radius 和 radius 之间循环以及 x * x + y * y <= radius * radius 究竟如何检查像素是否在圆圈内？
我无法想象那部分代码在我脑海中发生了什么。然而
更新： 好的，所以在考虑了一下之后，我认为在循环中：
// Iterate over the interest square region
for (var y = -radius; y < radius; y++) {
for (var x = -radius; x < radius; x++) {
// Check if the pixel is inside the effect circle
if (x * x + y * y <= radius * radius) {
我们实际上不是在迭代图像上的区域，而是一个理论区域。
并检查当前 (x,y) 是否在圆圈内。如果是，在下一行代码中，我们计算 (x,y) 在图像上的实际位置：
// Get the pixel array position
var sourcePosition = (y + originY) * originalImageData.width + x + originX;
sourcePosition *= 4;
Loops (+ if) 只是给我们圆内每个像素的坐标，然后我们将这些 (x,y) 坐标移动 (originX, originY) 值，这样我们就可以得到实际坐标图片。
我说的对吗？我是吗？ （请原谅我的激动:)
首先是简单的部分:)
x * x + y * y <= radius * radius
这就是毕达哥拉斯：
现在，如果您看那张图片，也很明显 x 和 y 在 -r 和 r 之间摆动，对吗？ :) 想象一下那些坐标在每个最左上角的...圆圈的点:)