Convert The Temperature

Problem Description

You are given a non-negative floating point number rounded to two decimal places celsius, that denotes the temperature in Celsius.

You should convert Celsius into Kelvin and Fahrenheit and return it as an array ans = [kelvin, fahrenheit].

Return the array ans. Answers within 10^(-5) of the actual answer will be accepted.

Example

Example 1:

Input: celsius = 36.50
Output: [309.65000,97.70000]
Explanation: Temperature at 36.50 Celsius converted in Kelvin is 309.65 and converted in Fahrenheit is 97.70.

Example 2:

Input: celsius = 122.11
Output: [395.26000,251.79800]
Explanation: Temperature at 122.11 Celsius converted in Kelvin is 395.26 and converted in Fahrenheit is 251.798.

Constraints

• 0 <= celsius <= 1000

Solution Approach

Intuition:

To efficiently determine the Kelvin and Farenheit temperature.

Solution Implementation

Code In Different Languages:

JavaScript

Written by @Ishitamukherjee2004

 
class Solution {
convertTemperature(celsius) {
 const kelvin = celsius + 273.15;
 const farenheit = (celsius * 1.80) + 32.00;
 return [kelvin, farenheit];
}
}

TypeScript

Written by @Ishitamukherjee2004

 class Solution {
convertTemperature(celsius: number): number[] {
 const kelvin: number = celsius + 273.15;
 const farenheit: number = (celsius * 1.80) + 32.00;
 return [kelvin, farenheit];
}
}

Python

Written by @Ishitamukherjee2004

 class Solution:
 def convertTemperature(self, celsius: float) -> list[float]:
     kelvin = celsius + 273.15
     farenheit = (celsius * 1.80) + 32.00
     return [kelvin, farenheit]

Java

Written by @Ishitamukherjee2004

 public class Solution {
 public double[] convertTemperature(double celsius) {
     double kelvin = celsius + 273.15;
     double farenheit = (celsius * 1.80) + 32.00;
     return new double[]{kelvin, farenheit};
 }
}

C++

Written by @Ishitamukherjee2004

class Solution {
public:
 vector<double> convertTemperature(double celsius) {
      double kelvin = celsius+273.15;
      double farenheit = (celsius*1.80)+32.00;

     return {kelvin, farenheit};
 }
};

Complexity Analysis

• Time Complexity: $O(1)$
• Space Complexity: $O(1)$
• The time complexity is $O(2*n)$ because the function performs a fixed number of operations, regardless of the input size.
• The space complexity is $O(1)$ because we are not using any extra space.