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toFixed() vs String(Math.floor()) vs Math.floor().toString() 2
(version: 0)
Comparing performance of:
toFixed() vs String(Math.floor()) vs Math.floor().toString()
Created:
3 years ago
by:
Guest
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Script Preparation code:
var someFloat0 = 123.456; var someFloat1 = 123; var someFloat2 = 123.00000000000456; var someFloat3 = -123;
Tests:
toFixed()
someFloat0.toFixed(); someFloat1.toFixed(); someFloat2.toFixed(); someFloat3.toFixed();
String(Math.floor())
String(Math.floor(someFloat0)); String(Math.floor(someFloat1)); String(Math.floor(someFloat2)); String(Math.floor(someFloat3));
Math.floor().toString()
Math.floor(someFloat0).toString(); Math.floor(someFloat1).toString(); Math.floor(someFloat2).toString(); Math.floor(someFloat3).toString();
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (3)
Previous results
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Test case name
Result
toFixed()
String(Math.floor())
Math.floor().toString()
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
**Overview of the Benchmark** The provided benchmark measures the performance difference between three approaches for rounding numbers in JavaScript: `toFixed()`, `String(Math.floor())`, and `Math.floor().toString()`. **What is being tested?** * The benchmark tests how fast each approach can round a set of four numbers (`someFloat0`, `someFloat1`, `someFloat2`, and `someFloat3`) to the nearest integer. The numbers are chosen to demonstrate different rounding behaviors: * `someFloat0` is 123.456, which would be rounded to 123 using both `toFixed()` and `Math.floor().toString()`. * `someFloat1` is an exact integer, 123, so it wouldn't change with any of the tested methods. * `someFloat2` is very close to 123.00000000000456 (essentially a special floating-point value that rounds differently), which would be rounded to 123 using `toFixed()` and `Math.floor().toString()`. * `someFloat3` is -123, and it wouldn't change with any of the tested methods. **Options comparison** * **`toFixed()`**: This method returns a string representing the number as a fixed-point number with the specified number of digits after the decimal point. It's relatively simple to implement but can be slower due to string manipulation. * **`String(Math.floor())`**: This approach uses the `Math.floor()` function to round the number down to the nearest integer, and then converts the result to a string using `String()`. While this works, it may incur additional overhead due to the conversion step. * **`Math.floor().toString()`**: Similar to the previous approach, but it rounds the number first using `Math.floor()` and then immediately converts the result to a string using `toString()`. This is likely to be the fastest option since it minimizes conversions between data types. **Pros and Cons of each approach** * **`toFixed()`**: * Pros: Simple, no additional overhead from conversions. * Cons: May incur performance overhead due to string manipulation. * **`String(Math.floor())`**: * Pros: Easy to implement, avoids the need for explicit rounding. * Cons: May incur additional overhead due to the conversion step. * **`Math.floor().toString()`**: * Pros: Fastest option, minimizes conversions between data types. * Cons: Requires two function calls, which might be slower than a single `toFixed()` call. **Library usage** There is no explicit library mentioned in the benchmark. However, note that some JavaScript implementations may use specialized libraries or extensions for numerical computations or string manipulation, which could potentially impact performance. **Special JS features or syntax** The benchmark doesn't explicitly mention any special JavaScript features or syntax beyond `toFixed()`, `String()`, and `Math.floor()`. **Alternatives** Other alternatives to consider when rounding numbers in JavaScript include: * Using a library like [Decimal.js](https://mikulskil.com/decimal/) for precise arithmetic operations. * Leveraging browser-specific features or extensions, such as WebAssembly or SIMD instructions, for optimized numerical computations. * Implementing custom rounding algorithms using bitwise operations or other low-level techniques. These alternatives might offer better performance or accuracy in certain scenarios, but they also come with additional complexity and potential overhead.
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