pytrxmat 0.0.5
A package to easily open trx.mat files in use at the Decision & Bayesian Computation lab at the Pasteur Institute in Paris
Requires Python: >=3.8

# pytrxmat

## Overview

pytrxmat is a Python package designed to facilitate the access and manipulation of data stored in trx.mat files commonly used in behavior screens. These files contain raw tracking data and postprocessing results for multiple larvae in experimental studies.
Installation

```bash
pip install pytrxmat
```

## Usage

### TRX Class

The main component of pytrxmat is the TRX class, which provides a convenient interface to interact with trx.mat files.

#### Initialization

```python
from pytrxmat.trx import TRX

# Instantiate the TRX class with the path to your 'trx.mat' file
trx = TRX('path/to/trx.mat')
```

#### Accessing Fields

The TRX class allows you to retrieve various fields from the trx.mat file, including scalar, string, time series, and composite array fields.

#### Scalar Fields

```python
# Get a scalar field (e.g., 'numero_larva_num')
scalar_data = trx.get('numero_larva_num')
```

#### Time Series Fields

```python
# Get a time series field (e.g., 'x_tail')
time_series_data = trx.get('x_tail')
```

#### Composite Array Fields

```python
# Get a composite array field (e.g., 'duration_large')
composite_array_data = trx.get_composite_array('duration_large')
```

#### String Fields

```python
# Get string fields (e.g., 'neuron' and 'protocol')
string_data = trx.get_string(['neuron', 'protocol'])
```

### The Repository class

The class `repository.Repository` is meant to be a thin wrapper above the directory tree used to orgnaize the data.

It is initialized by providing the path to the directory containing the tracker folders, and a list of trackers to open. Once the repository is built, we can access different subsets of the data using indexing, or use iterators to loop through all the data.

```python
from repository import Repository
from pathlib import Path

repo = Repository(Path('/home/hephaistos/screen'), ['t5', 't15'])
trx = repo['t5']['FCF_attP2_1500062@NoEffector_0_9999']['p_8_45s1x30s0s#p_8_105s10x2s10s#n#n@100']['20120224_084329'].trx

protocol = repo['t5']['FCF_attP2_1500062@NoEffector_0_9999']['p_8_45s1x30s0s#p_8_105s10x2s10s#n#n@100']
for trx in protocol.trx():
    process(trx)

for trx in repo.trx():
    process(trx)

for protocol in repo.protocols():
    process(protocol)

line = repo['t5']['FCF_attP2_1500062@NoEffector_0_9999']
for protocol in line.protocols():
    process(protocol)
```

Two caveats :

1. The hierarchy goes Tracker > Line > Protocol > DateTime. This is set by the organization of the folders.

2. If you jump levels in the hierarchy by using an iterator, you won't be able to easily figure out where the data is coming from, unless you parse the `path` attribute. Instead, you could use nested `for` loops

### File Format

The trx.mat file format is a standardized way of storing experimental data in the Decision and Bayesian Computation lab at the Pasteur Institute. The file contains multiple fields, each corresponding to different aspects of the larvae's behavior. The fields include univariate and multivariate time series, classification labels and probabilities, behavior summaries, and metadata such as full paths, IDs, and neuron information.

### Contribution

Contributions to this project are welcome. Feel free to open issues for bug reports or feature requests. If you'd like to contribute code, please submit a pull request.

## License

This project is licensed under the MIT License - see the LICENSE file for details.