


How to Generate Random Numbers in Python That Sum to a Specific Value?
Generating Random Numbers Summing to a Designated Value
In Python, there exists a straightforward solution to create n pseudo-random numbers that, when summed, attain a predefined target value, while ensuring that all possible combinations are equally likely to occur.
The method involves using the random.sample function to select an ordered set of n-1 unique numbers between 1 and the target sum. The chosen numbers serve as dividers, effectively partitioning the target into n positive integers.
Consider the example of generating 4 random numbers summing to 40. The generated dividers might be [4, 11, 24] (chosen from random.sample(range(1, 40), 3)). The corresponding numbers, which sum to 40, are computed as [4, 7, 13, 6].
To ensure均匀分布, where each possible combination has an equal probability, it is crucial to select the dividers in ascending order. Further, this approach effortlessly adapts to different target values, making it versatile for various scenarios.
The above is the detailed content of How to Generate Random Numbers in Python That Sum to a Specific Value?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



Solution to permission issues when viewing Python version in Linux terminal When you try to view Python version in Linux terminal, enter python...

When using Python's pandas library, how to copy whole columns between two DataFrames with different structures is a common problem. Suppose we have two Dats...

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

Regular expressions are powerful tools for pattern matching and text manipulation in programming, enhancing efficiency in text processing across various applications.

How does Uvicorn continuously listen for HTTP requests? Uvicorn is a lightweight web server based on ASGI. One of its core functions is to listen for HTTP requests and proceed...

Fastapi ...

The article discusses the role of virtual environments in Python, focusing on managing project dependencies and avoiding conflicts. It details their creation, activation, and benefits in improving project management and reducing dependency issues.

In Python, how to dynamically create an object through a string and call its methods? This is a common programming requirement, especially if it needs to be configured or run...
