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https://github.com/fork123aniket/optimal-partition-search
Official Implementation of Optimal Partition Search Algorithm
https://github.com/fork123aniket/optimal-partition-search
array array-methods data-structures data-structures-and-algorithms data-structures-python python search search-algorithm search-algorithms searching searching-algorithms
Last synced: 13 days ago
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Official Implementation of Optimal Partition Search Algorithm
- Host: GitHub
- URL: https://github.com/fork123aniket/optimal-partition-search
- Owner: fork123aniket
- License: mit
- Created: 2022-12-02T17:26:07.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-08-18T10:49:36.000Z (over 1 year ago)
- Last Synced: 2023-09-19T04:10:57.979Z (over 1 year ago)
- Topics: array, array-methods, data-structures, data-structures-and-algorithms, data-structures-python, python, search, search-algorithm, search-algorithms, searching, searching-algorithms
- Language: Python
- Homepage:
- Size: 10.7 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Optimal Partition Search
[](https://www.python.org/downloads/release/python-395/)
## Overview and Functionality
- Official Implementation of the paper - "***Optimal Partition Search***" [(***IEEE Xplore***)](https://ieeexplore.ieee.org/document/8869459) [(***ResearchGate***)](https://www.researchgate.net/publication/336638736_Optimal_Partition_Search)
- Searches for the optimal number of partitions required to speed up the search process
- Works for arrays having any data type (int, float, char, long, etc.)
- Independent of the order of the elements in the array, i.e. can work for both sorted and unsorted array settings
## Usage
- Make sure you have ***Python version 3.9 or greater*** installed on your system
- Run the following command on the terminal to install this package:
```
pip install Optimal-Partition-Search
```
- More details on how to install this package and other relevant information can be found [***here***](https://pypi.org/project/Optimal-Partition-Search/0.0.1/)
## Example
```
# test.py
from Optimal_Partition_Search import optimal_partition_search
import random
import numpy as np
# Example for array having integer values
array = random.sample(range(150), 100)
print(f'array: {array}')
element = int(input("Enter the item you want to search\n"))
optimal_partition = optimal_partition_search(array, element)
print("Optimal no. of partitions", optimal_partition)
# Example for array having float values
array = np.random.uniform(low=600.5, high=705.2, size=(10,))
print(f'array: {array}')
element = float(np.random.choice(array, 1))
optimal_partition = optimal_partition_search(array, element)
print("Optimal no. of partitions", optimal_partition)
# Example for array having character and string values
array = ['a', 'c', 'q', 'l', 'h', 's', 'tr', 'input']
print(f'array: {array}')
element = input("Enter the item you want to search\n")
optimal_partition = optimal_partition_search(array, element)
print("Optimal no. of partitions", optimal_partition)
```
Use the following command to run the examples given in the `test.py` file above:
```
python test.py
```