Metadata-Version: 2.4
Name: morphomeasure
Version: 0.1.1
Summary: Python package and CLI for L-Measure-based morphometric extraction
Home-page: https://github.com/Masood-Akram/MorphoMeasure
Author: Masood Akram
Author-email: masood.ahmed.akram@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
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<p align="center">
  <img src="img/MorphoMeasure.png" alt="MorphoMeasure banner" width="1000"/>
</p>

# MorphoMeasure

A Python package and command-line tool for automated extraction and summarization of morphometric features from neuron morphology files (SWC format) using [L-Measure](http://cng.gmu.edu:8080/Lm/help/index.htm). It supports batch processing, flexible feature selection, tag-based extraction, and outputs results in convenient CSV formats for downstream analysis. This package also supports the extraction of [ABEL](https://pubmed.ncbi.nlm.nih.gov/36196621/), a recently discovered morphometric feature. 


---

# Quick Install

**From PyPI (recommended):**
```bash
pip install morphomeasure
```

**Or for development:**
```bash
git clone https://github.com/Masood-Akram/MorphoMeasure.git
cd MorphoMeasure
pip install -e .
```

---

# Features

- **Python package & CLI for automated neuronal morphometric extraction using L-Measure** 
- **Batch processing of many SWC files** 
- **Outputs both branch-by-branch and summary morphometrics** 
- **Handles dendritic (3.0, 4.0) and glial (7.0) tags** 
- **Requires no Java or L-Measure installation - Lm.exe is bundled** 


---

# Requirements

- Python 3.8+
- [L-Measure](http://cng.gmu.edu:8080/Lm/help/index.htm) (`Lm.exe`) is bundled with the package
- `pandas` (auto-installed)

---

# Usage

### Python API

```bash
from morphomeasure import LMeasureWrapper

lm = LMeasureWrapper()
lm.run_batch(
    swc_dir='/path/to/swc-directory',
    output_dir='/path/to/output-directory',
    tags=['3.0'], # can be ['3.0', '4.0'] for apical & basal, and ['7.0'] for glia
    features_mode=['all']   # can be ['all', 'branch'], or ['all', 'branch', 'combined']
)

```

### As a CLI Tool

```bash
morphomeasure --tag 3.0 4.0 --features all --swc_dir /path/to/swc_files --output_dir /path/to/output
```
### All options:

```bash
morphomeasure --help
```

**Arguments:**

| Argument           | Description                                                                                  | Example                                    |
|--------------------|----------------------------------------------------------------------------------------------|--------------------------------------------|
| `--tag`            | Tags to process (e.g., 3.0 for basal, 4.0 for apical, 7.0 for glia)                         | `--tag 3.0 4.0`                            |
| `--features`       | Output type: `all`, `branch`, or `combined`                                                  | `--features all`                           |
| `--swc_dir`        | Directory containing input SWC files                                                         | `--swc_dir ./swc_files`                    |
| `--output_dir`     | Directory to save output CSVs                                                                | `--output_dir ./Measurements`              |
| `--tmp_dir`        | Temporary directory for intermediate files (default: `./tmp`)                                | `--tmp_dir ./tmp`                          |
| `--lm_exe_path`    | Path to L-Measure executable (default: bundled with package)                                 | `--lm_exe_path ./Lm/Lm.exe`                |


# Output

- **Complete structure CSVs:**  
  `Measurements/<tag_label>/All_Morphemetrics.csv`

- **Apical & Basal CSVs:**  
  `Measurements/<tag_label>/All_Morphemetrics_apical.csv`
  `Measurements/<tag_label>/All_Morphemetrics_basal.csv`

- **Branch-by-branch CSVs:**  
  `Measurements/<tag_label>/Branch_Morphometrics_<neuron>.csv`



- **Summary CSVs:**  
  - `All_Morphometrics.csv` (overall structure)
  - `All_Morphometrics_basal.csv` (basal dendrites)
  - `All_Morphometrics_apical.csv` (apical dendrites)
  - `All_Morphometrics_glia.csv` (glial processes)
- **Temporary files:**  
  Cleaned up automatically from the `tmp` directory.

---

# Customization

- **Features:**  
  Edit morphomeasure/features.py to add or remove L-Measure features.
- **Summary Logic:**  
  Update the summary_logic dictionary in features.py.
- **Tag Labels:**  
  Edit TAG_LABELS in features.py.

---

# Notes

- Temporary CSVs are cleaned up from tmp/ after processing.
- Make sure Lm.exe is compatible with your OS (bundled version is for Windows).
- For L-Measure feature details, see the [L-Measure documentation](http://cng.gmu.edu:8080/Lm/help/index.htm).

---

# Roadmap

- [ ] Extract features with tag 3 (basal) and tag 4 (apical) together and separately.
- [ ] Extract features with tag 7 (glia).
- [ ] PCA on Height, Width, and Depth.
- [ ] Pure Python feature extraction (no L-Measure dependency).
- [ ] Separate measures for apical & basal trees.

---

# License

This project is licensed under the MIT License. See the `LICENSE` file for details.

---

# Citation

If you use this repository in your research, please cite the associated papers:

```BibTex
@article{https://doi.org/10.1038/nprot.2008.51,
  author = {Scorcioni, R., Polavaram, S., & Ascoli, G. A.},
  doi = {https://doi.org/10.1038/nprot.2008.51},
  journal = {Nature protocols},
  number = {5},
  pages = {866â€“-876},
  title = {{L-Measure: a web-accessible tool for the analysis, comparison and search of digital reconstructions of neuronal morphologies}},
  volume = {3},
  year = {2008}
}

@article{https://doi.org/10.1002/jnr.25131,
  author = {Akram, M. A., Wei, Q., & Ascoli, G. A.},
  doi = {https://doi.org/10.1002/jnr.25131},
  journal = {Journal of Neuroscience Research},
  number = {1},
  pages = {112--129},
  title = {{Machine learning classification reveals robust morphometric biomarker of glial and neuronal arbors}},
  volume = {101},
  year = {2023}
}
```

---

# Acknowledgments

- L-Measure: Center for Neural Informatics, Neural Structures, & Neural Plasticity, George Mason University

---

**For questions or contributions, please open an issue or pull request!**
