Benchmark: To fixed vs round vs to precision with float

Script Preparation code:

var someFloat = 0.123456789;

Tests:

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

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
parseFloat(someFloat.toFixed(4));
someFloat.toPrecision(4)
(Math.round(someFloat*10000)/10000)

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.

Let's break down the provided JSON and explain what's being tested.

**Benchmark Definition**

The benchmark is testing three different approaches to convert a floating-point number `someFloat` to an integer or string representation:

1. `toFixed(4)`: This method returns a string representation of the float value with a fixed number of decimal places.
2. `toPrecision(4)`: This method returns a string representation of the float value with a specified number of significant digits.
3. `(Math.round(someFloat*10000)/10000)`: This is an explicit rounding approach using multiplication, rounding, and division to achieve a similar result to `toFixed(4)` or `toPrecision(4)`.

**Options Compared**

The benchmark is comparing the performance of these three approaches across different browsers (Chrome 87 on Windows Desktop). The options being compared are:

* **Rounding**: Using an explicit rounding approach with multiplication, rounding, and division.
* **Fixed-point notation**: Using `toFixed(4)`, which converts the float value to a string representation with a fixed number of decimal places.
* **Precision-based notation**: Using `toPrecision(4)`, which returns a string representation with a specified number of significant digits.

**Pros and Cons**

Here's a brief summary of the pros and cons of each approach:

* **Rounding (explicit)**:
	+ Pros: Can be more precise, especially for large numbers or precise control over rounding.
	+ Cons: May not provide intuitive results, as it involves multiple operations.
* **Fixed-point notation (`toFixed(4)`)**:
	+ Pros: Provides a simple and well-known format, easy to read and understand.
	+ Cons: Limited to 4 decimal places; can lead to rounding errors or truncation for non-integer values.
* **Precision-based notation (`toPrecision(4)`)**:
	+ Pros: Similar to `toFixed(4)` but with more flexibility in specifying significant digits.
	+ Cons: May not be as widely supported or intuitive, especially for developers familiar with `toFixed()`.

**Library Usage**

In this benchmark, none of the libraries are explicitly used. However, it's worth noting that JavaScript engines like V8 (used by Chrome) might have some internal optimizations or heuristics that could affect performance.

**Special JS Features/Syntax**

There isn't any special JavaScript feature or syntax being tested in this benchmark. The focus is on comparing different stringification approaches for floating-point numbers.

**Alternatives**

If you're interested in testing alternative stringification approaches, here are a few options:

* `toLocaleString()`: Similar to `toFixed()` but with more flexibility and support for locale-specific formatting.
* `Number()` or `Integer()`: These methods can be used to convert float values to integers, which might provide different performance characteristics depending on the rounding strategy.

Keep in mind that these alternatives might not provide direct comparisons with the original approaches (rounding, fixed-point notation, and precision-based notation).

Related benchmarks:

To fixed vs round vs to precision with float (version: 0)

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

Created: 5 years ago by: Guest

Jump to the latest result

parseFloat(someFloat.toFixed(4));

someFloat.toPrecision(4)

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

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):