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Setting Canvas Pixel
(version: 0)
Comparing performance of:
fillRect/concat vs fillRect/join vs 1×1 Image Data
Created:
8 years ago
by:
Guest
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HTML Preparation code:
<canvas id="c" width="800" height="800"></canvas>
Script Preparation code:
$c = document.getElementById('c'); $ctx = $c.getContext('2d'); $ctx.clearRect(0, 0, 800, 800); $px = $ctx.createImageData(1, 1); $pxls = []; for (var i=0; i<10000; ++i) $pxls.push({ x: Math.random() * 800 << 0, y: Math.random() * 800 << 0, r: 250 << 0, g: 0 << 0, b: 0, a: 1 }); $i = 0;
Tests:
fillRect/concat
for (var i=500;i--;){ var px = $pxls[$i++ % 10000]; $ctx.fillStyle = 'rgba(' + px.r + ',' + px.g + ',' + px.b + ',' + (px.a / 255) + ')'; $ctx.fillRect(px.x, px.y, 1, 1); }
fillRect/join
for (var i=500;i--;){ var px = $pxls[$i++ % 10000]; $ctx.fillStyle = 'rgba(' + [px.r,px.g,px.b,px.a/255].join() + ')'; $ctx.fillRect(px.x, px.y, 1, 1); }
1×1 Image Data
for (var i=500;i--;){ var px=$pxls[$i++ % 10000], d=$px.data; d[0] = px.r; d[1] = px.g; d[2] = px.b; d[3] = px.a; $ctx.putImageData($px, px.x, px.y); }
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (3)
Previous results
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Test case name
Result
fillRect/concat
fillRect/join
1×1 Image Data
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's dive into explaining the benchmark. **What is tested:** The provided JSON represents a JavaScript microbenchmark that tests the performance of different approaches to filling a canvas pixel with an image data object. The benchmark creates a canvas element, sets up a 2D drawing context, and then fills the pixel with an image data object using three different methods: 1. **Concise syntax**: This approach uses string concatenation to build the `rgba` color string. 2. **Join method**: This approach uses the `join()` method to concatenate the color components into a single string. 3. **Indexed array access**: This approach accesses the color components directly from the image data object. **Options compared:** The benchmark compares the performance of these three approaches, which provides insight into the optimization techniques used by different browsers and engines. **Pros and Cons:** * **Concise syntax**: Pros: + Simple and concise code. + Easy to understand and maintain. Cons: + May lead to slower performance due to string concatenation. * **Join method**: Pros: + More efficient than string concatenation for large color strings. + Can be faster in some cases. Cons: + Requires more memory accesses compared to direct array access. * **Indexed array access**: Pros: + Direct access to the color components can be faster. + May lead to better cache locality. Cons: + More complex code, which can make it harder to understand and maintain. **Library usage:** None of the benchmark scripts explicitly use any external libraries. However, some features might rely on browser-specific APIs or engine optimizations that are not explicitly mentioned in the provided JSON. **Special JS feature or syntax:** * The `<< 0` syntax is used to perform a left shift operation, which is equivalent to multiplying by 2^16 (65536). This is likely used for precision and data type optimization. * The `$pxls[$i++ % 10000]` syntax uses the variable `$pxls`, which is an array containing image data objects. The `% 10000` part ensures that the index wraps around to the beginning of the array after reaching the end, allowing for a large number of iterations. **Alternatives:** To compare the performance of these approaches, one could create more benchmark scripts using different methods, such as: * Using `rgba()` function instead of string concatenation or join method. * Implementing custom color manipulation functions for better optimization. * Testing different data types (e.g., floating-point numbers instead of integers) to observe any additional optimizations. Keep in mind that the choice of approach will depend on the specific use case, performance requirements, and personal preference.
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