# Enhanced Automatic Shifted Log Transformer (EASLT)
Automatically transform skewed data into more normal distributions using a Monte Carlo–optimized shifted log transformation.
---
## 🚀 Features
- **Works with negative, zero, and positive values**
- **Reduces skewness and kurtosis**
- **Adaptive, data-driven transformation**
- **Multi-test normality assessment**
- **Scikit-learn compatible**
- **Numba-accelerated for speed**
---
## 📦 Installation
```bash
pip install EASLT
```
---
## ⚡ Quick Start
```python
from EASLT import AutomaticShiftedLogTransformer
import numpy as np
# Example skewed data
np.random.seed(42)
data = np.random.exponential(2, (1000, 3))
# Transform
transformer = AutomaticShiftedLogTransformer(mc_iterations=1000, random_state=42)
data_transformed = transformer.fit_transform(data)
```
---
## 📚 How It Works
EASLT:
1. **Detects data complexity** (normal, mild issues, needs transformation)
2. **Applies robust shifting** for negative/zero values
3. **Detects outliers** and optionally winsorizes
4. **Optimizes parameters** via Monte Carlo with Dirichlet sampling
5. **Applies Feng's shifted log transformation**
---
## 📝 License
MIT License © 2025 Muhammad Akmal Husain
## 🔗 Links
- **[GitHub Repository](https://github.com/AkmalHusain2003/enhanced-automatic-shifted-log)**
- **[Documentation](https://github.com/AkmalHusain2003/enhanced-automatic-shifted-log#readme)**
Raw data
{
"_id": null,
"home_page": "https://github.com/AkmalHusain2003/enhanced-automatic-shifted-log",
"name": "EASLT",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": null,
"keywords": "data-transformation, log-transformation, normality, monte-carlo-optimization, statistical-preprocessing, data-science, machine-learning, numba-acceleration, feng-transformation, adaptive-algorithms",
"author": "Muhammad Akmal Husain",
"author_email": "Muhammad Akmal Husain <akmalhusain2003@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/3c/73/40cb5f103d939405809438c7adbbb05fdb6bc998e90e97994044cf8501f5/EASLT-0.0.1.tar.gz",
"platform": null,
"description": "# Enhanced Automatic Shifted Log Transformer (EASLT)\r\n\r\nAutomatically transform skewed data into more normal distributions using a Monte Carlo\u2013optimized shifted log transformation.\r\n\r\n---\r\n\r\n## \ud83d\ude80 Features\r\n\r\n- **Works with negative, zero, and positive values**\r\n- **Reduces skewness and kurtosis**\r\n- **Adaptive, data-driven transformation**\r\n- **Multi-test normality assessment**\r\n- **Scikit-learn compatible**\r\n- **Numba-accelerated for speed**\r\n\r\n---\r\n\r\n## \ud83d\udce6 Installation\r\n\r\n```bash\r\npip install EASLT\r\n```\r\n\r\n---\r\n\r\n## \u26a1 Quick Start\r\n\r\n```python\r\nfrom EASLT import AutomaticShiftedLogTransformer\r\nimport numpy as np\r\n\r\n# Example skewed data\r\nnp.random.seed(42)\r\ndata = np.random.exponential(2, (1000, 3))\r\n\r\n# Transform\r\ntransformer = AutomaticShiftedLogTransformer(mc_iterations=1000, random_state=42)\r\ndata_transformed = transformer.fit_transform(data)\r\n```\r\n\r\n---\r\n\r\n## \ud83d\udcda How It Works\r\n\r\nEASLT:\r\n1. **Detects data complexity** (normal, mild issues, needs transformation)\r\n2. **Applies robust shifting** for negative/zero values\r\n3. **Detects outliers** and optionally winsorizes\r\n4. **Optimizes parameters** via Monte Carlo with Dirichlet sampling\r\n5. **Applies Feng's shifted log transformation**\r\n\r\n---\r\n\r\n## \ud83d\udcdd License\r\n\r\nMIT License \u00a9 2025 Muhammad Akmal Husain\r\n\r\n## \ud83d\udd17 Links\r\n\r\n- **[GitHub Repository](https://github.com/AkmalHusain2003/enhanced-automatic-shifted-log)**\r\n- **[Documentation](https://github.com/AkmalHusain2003/enhanced-automatic-shifted-log#readme)**\r\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Enhanced Automatic Shifted Log Transformer with Monte Carlo optimization",
"version": "0.0.1",
"project_urls": {
"Homepage": "https://github.com/AkmalHusain2003/enhanced-automatic-shifted-log",
"Issues": "https://github.com/AkmalHusain2003/enhanced-automatic-shifted-log/issues",
"Repository": "https://github.com/AkmalHusain2003/enhanced-automatic-shifted-log.git"
},
"split_keywords": [
"data-transformation",
" log-transformation",
" normality",
" monte-carlo-optimization",
" statistical-preprocessing",
" data-science",
" machine-learning",
" numba-acceleration",
" feng-transformation",
" adaptive-algorithms"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "0532b3adcb65e86fcfa4760a4ff4b46ac84616401ba9216e5eb3943e738f3e51",
"md5": "058ce99d702d965fef4c64d809bbd6fe",
"sha256": "11c5cfe248381e02cc9f4ce8ed18371eb4f268e99ec315c69dc26ec9d06d21ce"
},
"downloads": -1,
"filename": "EASLT-0.0.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "058ce99d702d965fef4c64d809bbd6fe",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 12857,
"upload_time": "2025-08-12T06:39:38",
"upload_time_iso_8601": "2025-08-12T06:39:38.368616Z",
"url": "https://files.pythonhosted.org/packages/05/32/b3adcb65e86fcfa4760a4ff4b46ac84616401ba9216e5eb3943e738f3e51/EASLT-0.0.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "3c7340cb5f103d939405809438c7adbbb05fdb6bc998e90e97994044cf8501f5",
"md5": "ba87e26ac1ed9d07bfc8fd31812c382e",
"sha256": "1e6db727444d633e774621c42482ac871d91adbfd58695c372fa2c8d0c70ff82"
},
"downloads": -1,
"filename": "EASLT-0.0.1.tar.gz",
"has_sig": false,
"md5_digest": "ba87e26ac1ed9d07bfc8fd31812c382e",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 15181,
"upload_time": "2025-08-12T06:39:39",
"upload_time_iso_8601": "2025-08-12T06:39:39.457215Z",
"url": "https://files.pythonhosted.org/packages/3c/73/40cb5f103d939405809438c7adbbb05fdb6bc998e90e97994044cf8501f5/EASLT-0.0.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-08-12 06:39:39",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "AkmalHusain2003",
"github_project": "enhanced-automatic-shifted-log",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "easlt"
}
JSON
