Home Backend Development Python Tutorial Example of algorithm for solving the greatest common divisor implemented in Python

Example of algorithm for solving the greatest common divisor implemented in Python

May 03, 2018 pm 01:53 PM
python greatest common divisor algorithm

This article mainly introduces the algorithm for solving the greatest common divisor implemented in Python, involving operating skills related to Python mathematical operations. Friends in need can refer to it

The example of this article describes the algorithm for solving the greatest common divisor implemented in Python . Share it with everyone for your reference, the details are as follows:

When using Python to find the greatest common divisor of two numbers, the decomposition of prime factors introduced earlier is used. In fact, when I wrote the prime factorization program, I discovered that this function was used in the process of solving the greatest common divisor.

What makes me happy is that the Python collection processing function I learned before actually comes in handy at this time. The completion of the small program makes people feel more comfortable.

The code is implemented as follows:

#!/usr/bin/python
from collections import Counter
def PrimeNum(num):
   r_value =[]
   for i inrange(2,num+1):
      for jin range(2,i):
         if i % j == 0:
            break
      else:
         r_value.append(i)
   return r_value
def PrimeFactorSolve(num,prime_list):
   for n inprime_list:
      if num % n == 0:
         return [n,num / n]
def Primepisor(num):
   num_temp =num
   prime_range= PrimeNum(num)
   ret_value =[]
   while numnot in prime_range:
      factor_list= PrimeFactorSolve(num,prime_range)
      ret_value.append(factor_list[0])
      num =factor_list[1]
   else:
      ret_value.append(num)
   return Counter(ret_value)
def Maxpisor(num1,num2):
   dict1 =Primepisor(num1)
   dict2 =Primepisor(num2)
   max_pisor= 1
   for key1 indict1:
      if key1 in dict2:
         if dict1[key1] < dict2[key1]:
            max_pisor*= (key1 ** dict1[key1])
         else:
            max_pisor*= (key1 ** dict2[key1])
   return max_pisor
print(Maxpisor(12,18))
print(Maxpisor(7,2))
print(Maxpisor(7,13))
print(Maxpisor(24,56))
print(Maxpisor(63,81))
Copy after login

The execution result of the program is as follows:

E:\WorkSpace\01 _Programming Language\03_Python\math>python max_pisor.py
6
1
1
8
9

passed the verification and the calculation result is accurate.

Related recommendations:

OpenCV cv.Mat and .txt file data reading and writing operations

The above is the detailed content of Example of algorithm for solving the greatest common divisor implemented in Python. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Article

R.E.P.O. Energy Crystals Explained and What They Do (Yellow Crystal)
1 months ago By 尊渡假赌尊渡假赌尊渡假赌
R.E.P.O. Best Graphic Settings
1 months ago By 尊渡假赌尊渡假赌尊渡假赌
Will R.E.P.O. Have Crossplay?
1 months ago By 尊渡假赌尊渡假赌尊渡假赌

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

PHP and Python: Code Examples and Comparison PHP and Python: Code Examples and Comparison Apr 15, 2025 am 12:07 AM

PHP and Python have their own advantages and disadvantages, and the choice depends on project needs and personal preferences. 1.PHP is suitable for rapid development and maintenance of large-scale web applications. 2. Python dominates the field of data science and machine learning.

Python vs. JavaScript: Community, Libraries, and Resources Python vs. JavaScript: Community, Libraries, and Resources Apr 15, 2025 am 12:16 AM

Python and JavaScript have their own advantages and disadvantages in terms of community, libraries and resources. 1) The Python community is friendly and suitable for beginners, but the front-end development resources are not as rich as JavaScript. 2) Python is powerful in data science and machine learning libraries, while JavaScript is better in front-end development libraries and frameworks. 3) Both have rich learning resources, but Python is suitable for starting with official documents, while JavaScript is better with MDNWebDocs. The choice should be based on project needs and personal interests.

How is the GPU support for PyTorch on CentOS How is the GPU support for PyTorch on CentOS Apr 14, 2025 pm 06:48 PM

Enable PyTorch GPU acceleration on CentOS system requires the installation of CUDA, cuDNN and GPU versions of PyTorch. The following steps will guide you through the process: CUDA and cuDNN installation determine CUDA version compatibility: Use the nvidia-smi command to view the CUDA version supported by your NVIDIA graphics card. For example, your MX450 graphics card may support CUDA11.1 or higher. Download and install CUDAToolkit: Visit the official website of NVIDIACUDAToolkit and download and install the corresponding version according to the highest CUDA version supported by your graphics card. Install cuDNN library:

Detailed explanation of docker principle Detailed explanation of docker principle Apr 14, 2025 pm 11:57 PM

Docker uses Linux kernel features to provide an efficient and isolated application running environment. Its working principle is as follows: 1. The mirror is used as a read-only template, which contains everything you need to run the application; 2. The Union File System (UnionFS) stacks multiple file systems, only storing the differences, saving space and speeding up; 3. The daemon manages the mirrors and containers, and the client uses them for interaction; 4. Namespaces and cgroups implement container isolation and resource limitations; 5. Multiple network modes support container interconnection. Only by understanding these core concepts can you better utilize Docker.

MiniOpen Centos compatibility MiniOpen Centos compatibility Apr 14, 2025 pm 05:45 PM

MinIO Object Storage: High-performance deployment under CentOS system MinIO is a high-performance, distributed object storage system developed based on the Go language, compatible with AmazonS3. It supports a variety of client languages, including Java, Python, JavaScript, and Go. This article will briefly introduce the installation and compatibility of MinIO on CentOS systems. CentOS version compatibility MinIO has been verified on multiple CentOS versions, including but not limited to: CentOS7.9: Provides a complete installation guide covering cluster configuration, environment preparation, configuration file settings, disk partitioning, and MinI

How to operate distributed training of PyTorch on CentOS How to operate distributed training of PyTorch on CentOS Apr 14, 2025 pm 06:36 PM

PyTorch distributed training on CentOS system requires the following steps: PyTorch installation: The premise is that Python and pip are installed in CentOS system. Depending on your CUDA version, get the appropriate installation command from the PyTorch official website. For CPU-only training, you can use the following command: pipinstalltorchtorchvisiontorchaudio If you need GPU support, make sure that the corresponding version of CUDA and cuDNN are installed and use the corresponding PyTorch version for installation. Distributed environment configuration: Distributed training usually requires multiple machines or single-machine multiple GPUs. Place

How to choose the PyTorch version on CentOS How to choose the PyTorch version on CentOS Apr 14, 2025 pm 06:51 PM

When installing PyTorch on CentOS system, you need to carefully select the appropriate version and consider the following key factors: 1. System environment compatibility: Operating system: It is recommended to use CentOS7 or higher. CUDA and cuDNN:PyTorch version and CUDA version are closely related. For example, PyTorch1.9.0 requires CUDA11.1, while PyTorch2.0.1 requires CUDA11.3. The cuDNN version must also match the CUDA version. Before selecting the PyTorch version, be sure to confirm that compatible CUDA and cuDNN versions have been installed. Python version: PyTorch official branch

How to run programs in terminal vscode How to run programs in terminal vscode Apr 15, 2025 pm 06:42 PM

In VS Code, you can run the program in the terminal through the following steps: Prepare the code and open the integrated terminal to ensure that the code directory is consistent with the terminal working directory. Select the run command according to the programming language (such as Python's python your_file_name.py) to check whether it runs successfully and resolve errors. Use the debugger to improve debugging efficiency.

See all articles