Benchmark: toFixed vs toPrecision vs Math.round() with num > 0

Script Preparation code:

var someFloat = 1234.123456789;

Tests:

toFixed(4)
someFloat.toFixed(4);
toPrecision(4).toString()
someFloat.toPrecision(4).toString();
(Math.round(*10000)/10000).toString()
(Math.round(someFloat*10000)/10000).toString();

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
toFixed(4)
toPrecision(4).toString()
(Math.round(*10000)/10000).toString()

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/118.0

Browser/OS: Firefox 118 on Windows

View result in a separate tab

Test name	Executions per second
toFixed(4)	21916862.0 Ops/sec
toPrecision(4).toString()	15628011.0 Ops/sec
(Math.round(*10000)/10000).toString()	1713118976.0 Ops/sec

Autogenerated LLM Summary (model llama3.1:latest, generated 2 months ago):

LLMs can make mistakes. Check important info.

Let's break down what's happening in this benchmark.

**Benchmark Overview**

This benchmark tests the performance of three different approaches to rounding numbers with four decimal places:

1. `toFixed(4)`: using the `toFixed()` method of a number object
2. `toPrecision(4).toString()`: using the `toPrecision()` method followed by `toString()` to get a string representation with four decimal places
3. `(Math.round(someFloat*10000)/10000).toString()`: using the `Math.round()` function to round the number, multiplying it by 10,000 to avoid decimal issues, and then dividing back down to get the desired precision

**Individual Test Cases**

Each test case is a separate benchmark that runs one of these three approaches on the same input value (`someFloat = 1234.123456789`).

* `toFixed(4)`: Simply calls `someFloat.toFixed(4)` to round the number to four decimal places.
* `toPrecision(4).toString()`: Calls `someFloat.toPrecision(4)` to get a string representation of the number with four decimal places, and then immediately converts it back to a string using `toString()`.
* `(Math.round(someFloat*10000)/10000).toString()`: Multiplies the input value by 10,000, rounds it using `Math.round()`, divides the result back down by 10,000, and finally converts the result to a string.

**Pros/Cons and Considerations**

Here are some pros and cons of each approach:

* **toFixed(4)**:
	+ Pros: Simple and concise code.
	+ Cons: May be slower than other methods due to the overhead of calling `toFixed()`.
* **toPrecision(4).toString()**:
	+ Pros: Avoids decimal issues by using `toPrecision()` instead of `toFixed()`. Can also provide more flexibility in terms of rounding precision.
	+ Cons: More verbose code, and may incur additional performance overhead due to the extra method calls.
* `(Math.round(someFloat*10000)/10000).toString()`:
	+ Pros: Avoids decimal issues by multiplying the number, but is a bit contrived and harder to read. May be faster than `toFixed()` or `toPrecision()`.
	+ Cons: More complex code, and may not be immediately clear what's happening.

**Library Usage**

There's no external library usage in this benchmark.

**Special JS Features or Syntax**

None.

**Alternatives**

Other alternatives for rounding numbers with four decimal places include:

* Using a dedicated rounding library like [decimal.js](https://github.com/MahdiYaghoubi/decimal.js).
* Implementing your own custom rounding function using bitwise operations (e.g., `Math.round()`).
* Using a more advanced library or framework that provides built-in support for high-precision arithmetic, such as [BigDecimal.js](https://github.com/visionn/BigDecimal.js).

Hope this explanation helps!

Related benchmarks:

toFixed vs toPrecision vs Math.round() with num > 0 (version: 0)

Comparing performance of: toFixed(4) vs toPrecision(4).toString() vs (Math.round(*10000)/10000).toString()

Created: one year ago by: Guest

Jump to the latest result

toFixed(4)

toPrecision(4).toString()

(Math.round(*10000)/10000).toString()

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.1:latest, generated 2 months ago):