stats-base-ndarray-dcumax
Compute the cumulative maximum value of a one-dimensional double-precision floating-point ndarray.
Science Score: 44.0%
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Repository
Compute the cumulative maximum value of a one-dimensional double-precision floating-point ndarray.
Basic Info
- Host: GitHub
- Owner: SaraStojanova
- License: apache-2.0
- Language: JavaScript
- Default Branch: main
- Size: 47.9 KB
Statistics
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 1
Topics
Metadata Files
README.md
📊 Stats Base: Cumulative Maximum for Ndarrays
Welcome to the Stats Base Ndarray Dcumax repository! This library computes the cumulative maximum value of a one-dimensional double-precision floating-point ndarray. You can find the latest releases here.
Table of Contents
Introduction
The Stats Base Ndarray Dcumax library provides a simple and efficient way to compute the cumulative maximum of a one-dimensional array. It is designed for developers and data scientists who need a reliable tool for statistical analysis in JavaScript.
With this library, you can easily manage large datasets and perform complex calculations with minimal effort.
Features
- Easy to Use: Simple API for quick implementation.
- Performance: Optimized for speed and efficiency.
- Compatibility: Works seamlessly with Node.js and JavaScript environments.
- Lightweight: Minimal dependencies for a clean setup.
- Versatile: Suitable for a variety of applications in statistics and data analysis.
Installation
To install the library, use npm:
bash
npm install stats-base-ndarray-dcumax
You can also clone the repository directly:
bash
git clone https://github.com/SaraStojanova/stats-base-ndarray-dcumax.git
cd stats-base-ndarray-dcumax
npm install
Usage
To use the library, first require it in your JavaScript file:
javascript
const dcumax = require('stats-base-ndarray-dcumax');
Then, you can compute the cumulative maximum of your ndarray:
javascript
const ndarray = require('ndarray');
const data = ndarray(new Float64Array([1.0, 2.5, 3.1, 2.0, 5.5]), [5]);
const result = dcumax(data);
console.log(result);
Examples
Basic Example
Here's a simple example to demonstrate how to use the library:
```javascript const dcumax = require('stats-base-ndarray-dcumax'); const ndarray = require('ndarray');
const data = ndarray(new Float64Array([4.0, 2.0, 5.0, 1.0, 3.0]), [5]); const result = dcumax(data); console.log(result); // Output: [4.0, 4.0, 5.0, 5.0, 5.0] ```
Working with Larger Datasets
For larger datasets, the library remains efficient:
```javascript const dcumax = require('stats-base-ndarray-dcumax'); const ndarray = require('ndarray');
const largeData = ndarray(new Float64Array(1000000).fill(0).map((_, i) => Math.random() * 100), [1000000]); const result = dcumax(largeData); console.log(result); ```
API Documentation
dcumax(data)
Parameters:
data: A one-dimensional ndarray of double-precision floating-point numbers.
Returns: An ndarray containing the cumulative maximum values.
Example:
javascript
const result = dcumax(ndarray(new Float64Array([1.0, 3.0, 2.0]), [3]));
console.log(result); // Output: [1.0, 3.0, 3.0]
Contributing
We welcome contributions! To contribute:
- Fork the repository.
- Create a new branch (
git checkout -b feature/YourFeature). - Make your changes.
- Commit your changes (
git commit -m 'Add new feature'). - Push to the branch (
git push origin feature/YourFeature). - Create a pull request.
Please ensure that your code follows the project's coding standards and includes appropriate tests.
License
This project is licensed under the MIT License. See the LICENSE file for details.
Contact
For any questions or feedback, please reach out:
- Author: Sara Stojanova
- Email: sara@example.com
- GitHub: SaraStojanova
Thank you for using Stats Base Ndarray Dcumax! Check out the Releases section for updates and new features.
Owner
- Login: SaraStojanova
- Kind: user
- Repositories: 1
- Profile: https://github.com/SaraStojanova
Citation (CITATION.cff)
cff-version: 1.2.0
title: stdlib
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- name: The Stdlib Authors
url: https://github.com/stdlib-js/stdlib/graphs/contributors
repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io
abstract: |
Standard library for JavaScript and Node.js.
keywords:
- JavaScript
- Node.js
- TypeScript
- standard library
- scientific computing
- numerical computing
- statistical computing
license: Apache-2.0 AND BSL-1.0
date-released: 2016
GitHub Events
Total
- Release event: 1
- Push event: 745
- Create event: 3
Last Year
- Release event: 1
- Push event: 745
- Create event: 3
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Last synced: 10 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| stdlib-bot | n****y@s****o | 1 |
| SaraStojanova | 1****a | 1 |
Committer Domains (Top 20 + Academic)
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Last synced: 10 months ago
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- Total pull requests: 0
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- Average comments per issue: 0
- Average comments per pull request: 0
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- Bot issues: 0
- Bot pull requests: 0
Past Year
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Dependencies
- @stdlib/array-float64 ^0.2.2 development
- @stdlib/array-zeros ^0.2.2 development
- @stdlib/assert-is-same-float64array ^0.2.2 development
- @stdlib/bench-harness ^0.2.2 development
- @stdlib/math-base-assert-is-nan ^0.2.2 development
- @stdlib/math-base-special-pow ^0.3.0 development
- @stdlib/ndarray-base-ctor ^0.2.2 development
- @stdlib/ndarray-data-buffer ^0.2.2 development
- @stdlib/ndarray-to-array ^0.2.1 development
- @stdlib/ndarray-zeros-like ^0.3.0 development
- @stdlib/random-array-discrete-uniform ^0.2.1 development
- @stdlib/random-array-uniform ^0.2.1 development
- istanbul ^0.4.1 development
- tap-min git+https://github.com/Planeshifter/tap-min.git development
- tape git+https://github.com/kgryte/tape.git#fix/globby development
- @stdlib/ndarray-base-data-buffer ^0.2.2
- @stdlib/ndarray-base-numel-dimension ^0.3.2
- @stdlib/ndarray-base-offset ^0.2.2
- @stdlib/ndarray-base-stride ^0.2.2
- @stdlib/stats-strided-dcumax github:stdlib-js/stats-strided-dcumax#main
- @stdlib/types ^0.4.3