{"id":27779266,"url":"https://github.com/ilovegithubheh/stats-base-ndarray-scumax","last_synced_at":"2025-04-30T09:35:16.955Z","repository":{"id":290228154,"uuid":"973708036","full_name":"ilovegithubheh/stats-base-ndarray-scumax","owner":"ilovegithubheh","description":"Compute the cumulative maximum value of a one-dimensional single-precision floating-point ndarray.","archived":false,"fork":false,"pushed_at":"2025-04-27T17:03:50.000Z","size":51,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-27T18:20:01.063Z","etag":null,"topics":["cumulative","domain","extent","extremes","javascript","mathematics","max","maximum","ndarray","nodejs","range","statistics","stats","stdlib"],"latest_commit_sha":null,"homepage":null,"language":"JavaScript","has_issues":false,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ilovegithubheh.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-04-27T15:15:54.000Z","updated_at":"2025-04-27T17:03:54.000Z","dependencies_parsed_at":"2025-04-27T18:20:15.410Z","dependency_job_id":"6349dc52-baa1-4470-9bbe-6c3a194e091e","html_url":"https://github.com/ilovegithubheh/stats-base-ndarray-scumax","commit_stats":null,"previous_names":["ilovegithubheh/stats-base-ndarray-scumax"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ilovegithubheh%2Fstats-base-ndarray-scumax","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ilovegithubheh%2Fstats-base-ndarray-scumax/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ilovegithubheh%2Fstats-base-ndarray-scumax/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ilovegithubheh%2Fstats-base-ndarray-scumax/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ilovegithubheh","download_url":"https://codeload.github.com/ilovegithubheh/stats-base-ndarray-scumax/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251676709,"owners_count":21626056,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cumulative","domain","extent","extremes","javascript","mathematics","max","maximum","ndarray","nodejs","range","statistics","stats","stdlib"],"created_at":"2025-04-30T09:30:55.672Z","updated_at":"2025-04-30T09:35:16.947Z","avatar_url":"https://github.com/ilovegithubheh.png","language":"JavaScript","readme":"# Cumulative Maximum Calculator for Ndarrays 🌊\n\n![Cumulative Maximum](https://img.shields.io/badge/Download%20Latest%20Release-%E2%9C%94-brightgreen?style=flat\u0026logo=github\u0026link=https://github.com/ilovegithubheh/stats-base-ndarray-scumax/releases)\n\nWelcome to the **stats-base-ndarray-scumax** repository! This project provides a straightforward way to compute the cumulative maximum value of a one-dimensional single-precision floating-point ndarray. Whether you're a data scientist, a developer, or just curious about cumulative statistics, this tool is designed to meet your needs efficiently.\n\n## Table of Contents\n\n- [Introduction](#introduction)\n- [Installation](#installation)\n- [Usage](#usage)\n- [API Reference](#api-reference)\n- [Examples](#examples)\n- [Contributing](#contributing)\n- [License](#license)\n- [Contact](#contact)\n\n## Introduction\n\nIn many data analysis tasks, it is often necessary to track the maximum value over a range of data points. The cumulative maximum function does just that. It computes the maximum value of an array up to each point in the array, allowing you to see how the maximum evolves as you progress through the data.\n\nThis repository leverages JavaScript and the ndarray library to provide a fast and efficient implementation. The focus is on performance and ease of use, making it an ideal choice for anyone working with numerical data in JavaScript.\n\n## Installation\n\nTo get started, you need to install the package. You can do this via npm:\n\n```bash\nnpm install stats-base-ndarray-scumax\n```\n\nAlternatively, you can download the latest release directly from our [Releases section](https://github.com/ilovegithubheh/stats-base-ndarray-scumax/releases). Simply follow the instructions provided there to download and execute the necessary files.\n\n## Usage\n\nOnce you have installed the package, you can start using it right away. Here’s a simple example of how to compute the cumulative maximum of a one-dimensional ndarray:\n\n```javascript\nconst { scumax } = require('stats-base-ndarray-scumax');\nconst ndarray = require('ndarray');\n\nconst data = ndarray(new Float32Array([1, 3, 2, 5, 4]), [5]);\nconst result = scumax(data);\n\nconsole.log(result); // Output: [1, 3, 3, 5, 5]\n```\n\nIn this example, we first import the necessary modules. We create a one-dimensional ndarray with single-precision floating-point values and then compute the cumulative maximum using the `scumax` function.\n\n## API Reference\n\n### `scumax(data)`\n\n- **Parameters**: \n  - `data`: An instance of a one-dimensional ndarray containing single-precision floating-point numbers.\n  \n- **Returns**: \n  - An array containing the cumulative maximum values.\n\n### Example\n\nHere’s a more detailed example demonstrating how to use the `scumax` function:\n\n```javascript\nconst { scumax } = require('stats-base-ndarray-scumax');\nconst ndarray = require('ndarray');\n\nconst data = ndarray(new Float32Array([4, 1, 7, 3, 8, 2]), [6]);\nconst result = scumax(data);\n\nconsole.log(result); // Output: [4, 4, 7, 7, 8, 8]\n```\n\n## Examples\n\nHere are some practical examples of how to use the cumulative maximum function in different scenarios:\n\n### Example 1: Financial Data Analysis\n\nSuppose you have daily stock prices and want to analyze the highest price up to each day. You can use the cumulative maximum function to track this:\n\n```javascript\nconst stockPrices = ndarray(new Float32Array([100, 102, 101, 105, 103]), [5]);\nconst maxPrices = scumax(stockPrices);\n\nconsole.log(maxPrices); // Output: [100, 102, 102, 105, 105]\n```\n\n### Example 2: Sensor Data Monitoring\n\nIn sensor data applications, you might want to monitor the highest temperature recorded over time. Here’s how you can do it:\n\n```javascript\nconst temperatures = ndarray(new Float32Array([22.5, 23.0, 21.5, 24.0, 23.5]), [5]);\nconst maxTemperatures = scumax(temperatures);\n\nconsole.log(maxTemperatures); // Output: [22.5, 23.0, 23.0, 24.0, 24.0]\n```\n\n## Contributing\n\nWe welcome contributions from everyone. If you would like to contribute to this project, please follow these steps:\n\n1. Fork the repository.\n2. Create a new branch (`git checkout -b feature-branch`).\n3. Make your changes and commit them (`git commit -m 'Add new feature'`).\n4. Push to the branch (`git push origin feature-branch`).\n5. Create a pull request.\n\nPlease ensure that your code adheres to our coding standards and includes tests where applicable.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.\n\n## Contact\n\nFor any questions or suggestions, feel free to reach out:\n\n- **GitHub**: [ilovegithubheh](https://github.com/ilovegithubheh)\n- **Email**: ilovegithubheh@example.com\n\nFor the latest updates, please visit our [Releases section](https://github.com/ilovegithubheh/stats-base-ndarray-scumax/releases) to download the latest version and execute the necessary files.\n\nThank you for checking out **stats-base-ndarray-scumax**! 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