Benchmark: save/restore vs manual - shadow

HTML Preparation code:

<canvas id="canvasOne" width="400" height="400"></canvas>
<canvas id="canvasTwo" width="400" height="400"></canvas>

Script Preparation code:

var canvasOne = document.getElementById('canvasOne');
var ctxOne = canvasOne.getContext("2d");

var canvasTwo = document.getElementById('canvasTwo');
var ctxTwo = canvasTwo.getContext("2d");

Tests:

manual
ctxOne.beginPath(); ctxOne.moveTo(20, 20); ctxOne.lineTo(40, 40); ctxOne.shadowBlur = 20; ctxOne.shadowOffsetX = 10; ctxOne.shadowOffsetY = 10; ctxOne.shadowColor = '#f62459'; ctxOne.strokeStyle = '#f62459'; ctxOne.stroke(); ctxOne.shadowBlur = 0; ctxOne.shadowOffsetX = 0; ctxOne.shadowOffsetY = 0; ctxOne.shadowColor = 'rgba(0, 0, 0, 0)';
save/restore
ctxTwo.save(); ctxTwo.beginPath(); ctxTwo.moveTo(20, 20); ctxTwo.lineTo(40, 40); ctxTwo.shadowBlur = 20; ctxTwo.shadowOffsetX = 10; ctxTwo.shadowOffsetY = 10; ctxTwo.shadowColor = '#f62459'; ctxTwo.strokeStyle = '#f62459'; ctxTwo.stroke(); ctxTwo.restore();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
manual
save/restore

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases.

**Benchmark Definition**

The website uses JSON to define a benchmark. In this case, it's testing two approaches for applying shadows to a 2D context in JavaScript: manual vs save/restore.

**Script Preparation Code**

Before running each test, the script preparation code sets up two canvas elements (`canvasOne` and `canvasTwo`) and gets their respective 2D drawing contexts (`ctxOne` and `ctxTwo`). This ensures that both canvases have the same initial state.

**Html Preparation Code**

The HTML preparation code generates a simple HTML page with two canvas elements, each with an ID of either "canvasOne" or "canvasTwo".

**Test Cases**

There are two individual test cases:

1. **Manual**: The benchmark definition contains a script that manually applies shadows to the 2D context (`ctxOne`). Specifically, it:
	* Sets the shadow blur radius (20) and offset coordinates (10, 10).
	* Sets the stroke color and style.
	* Draws a line from (20, 20) to (40, 40).
	* Restores the original state of `ctxOne` by setting the shadow blur radius, offset coordinates, and stroke color to their default values.
2. **Save/Restore**: The benchmark definition contains another script that uses the save/restore feature of the 2D context (`ctxTwo`). Specifically, it:
	* Saves the current state of `ctxTwo`.
	* Applies shadows (similar to manual) on a new path.
	* Restores the original state of `ctxTwo`.

**Pros and Cons**

Here are some general pros and cons of each approach:

Manual:
Pros: Easy to understand and implement. No dependency on external libraries or features.
Cons: Requires explicit restoration of the original state, which can be error-prone.

Save/Restore:
Pros: Convenient and efficient way to apply shadows without manual restoration. Can be less error-prone than manual.
Cons: Requires an additional function call (`save()` and `restore()`) to manage the context's state.

**Library**

In this benchmark, there is no explicit library used. The save/restore feature is a built-in part of the 2D drawing context in most JavaScript engines (e.g., Gecko, Blink).

**Special JS Features or Syntax**

This benchmark uses special features of the 2D drawing context, specifically:

* Shadow blur radius and offset coordinates.
* Stroke color and style.

No other special features or syntax are used.

**Other Alternatives**

If you wanted to implement a similar benchmark without using save/restore, you could consider alternative approaches, such as:

* Using a library like Canvas.js or Pixi.js, which provide more advanced 2D drawing capabilities.
* Implementing custom rendering algorithms or techniques (e.g., pixel-perfect rendering).
* Using Web Workers or other parallel computing techniques to accelerate rendering.

Keep in mind that these alternatives may require additional setup and expertise.

Latest run results:

Run details: (Test run date: 6 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3321.0 Safari/537.36

Browser/OS: Chrome 65 on Mac OS X 10.10.1

View result in a separate tab

Test name	Executions per second
manual	10519.8 Ops/sec
save/restore	10410.1 Ops/sec

Related benchmarks:

save/restore vs manual - shadow (version: 0)

Comparing performance of: manual vs save/restore

Created: 6 years ago by: Guest

Jump to the latest result

manual

save/restore

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 26 days ago):