Benchmark: canvasperf - MeasureThat.net

HTML Preparation code:

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

Script Preparation code:

var canvas = document.getElementById('canvas');
var ctx = canvas.getContext("2d");

Tests:

float
ctx.beginPath(); ctx.fillStyle = '#000'; ctx.arc(70.5 + Math.random(), 70.5 + Math.random(), 6, 0, Math.PI * 2, true); ctx.fill();
int
ctx.beginPath(); ctx.fillStyle = '#000'; ctx.arc(Math.trunc(50.5 + Math.random()), Math.trunc(50.5 + Math.random()), 6, 0, Math.PI * 2, true); ctx.fill();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
float
int

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

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Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

**What is tested on the provided JSON?**

The provided JSON represents a benchmark test for measuring performance in two different ways: using floating-point numbers and integer values, specifically with the `Math.random()` function to generate random coordinates.

In the first test case (`float`), the code creates a new path, sets the fill style to black, draws an arc with a radius of 6 units centered at a random x and y coordinate between 70.5 and 120.5, and then fills the path. The `Math.PI * 2` value is used to specify the arc's angle in radians.

In the second test case (`int`), the code creates a new path, sets the fill style to black, draws an arc with a radius of 6 units centered at a random x and y coordinate between 50.5 and 100.5, and then fills the path. The `Math.trunc()` function is used to truncate the coordinates to integers.

**Options compared**

There are two main approaches being compared:

1. **Using floating-point numbers (float)**: This approach uses `Math.random()` to generate random coordinates, which allows for a wider range of possible values but may also introduce more noise and variability in the results.
2. **Using integer values (int)**: This approach uses `Math.trunc()` to truncate the generated coordinates to integers, which can reduce the range of possible values but also introduces discrete steps between valid coordinates.

**Pros and Cons**

**Float (using floating-point numbers):**

Pros:

* Allows for a wider range of possible values
* May provide more accurate results in terms of absolute performance

Cons:

* Introduces more noise and variability in the results due to randomization
* May not be suitable for applications where precision is critical

**Int (using integer values):**

Pros:

* Reduces the range of possible values, which can lead to more predictable results
* May provide better performance due to reduced overhead from floating-point arithmetic

Cons:

* Limits the range of possible coordinates
* May not be suitable for applications where high accuracy is required

**Library and purpose**

In this benchmark test, there are no specific libraries being used. However, it's worth noting that `Math.random()` and `Math.trunc()` are built-in JavaScript functions.

**Special JS features or syntax**

There are no special JS features or syntax mentioned in the benchmark test.

**Other alternatives**

If you want to measure performance in other ways or with different precision levels, you could modify the benchmark test to include additional test cases. Some alternative approaches might include:

* Using a constant radius and adjusting the center coordinates
* Drawing multiple arcs instead of one continuous arc
* Using different shapes (e.g., triangles, rectangles)
* Measuring performance under specific conditions (e.g., high latency, low bandwidth)

Overall, this benchmark test provides a good starting point for measuring performance in Canvas 2D drawing operations, and can be modified or extended to suit specific use cases or requirements.

Related benchmarks:

canvasperf (version: 0)

Comparing performance of: float vs int

Created: 8 years ago by: Guest

Jump to the latest result

float

int

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):