Metadata-Version: 2.3
Name: identitwin
Version: 0.1.0
Summary: IdentiTwin a system for structural monitoring.
Author: Ing. Angel Navarro-Mora M.Sc
Author-email: ahnavarro@itcr.ac.cr
Requires-Python: >=3.8,<4.0
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Provides-Extra: all
Provides-Extra: hardware
Provides-Extra: performance
Requires-Dist: adafruit-blinka ; extra == "hardware" or extra == "all"
Requires-Dist: adafruit-circuitpython-ads1x15 ; extra == "hardware" or extra == "all"
Requires-Dist: colorama
Requires-Dist: gpiozero ; extra == "hardware" or extra == "all"
Requires-Dist: matplotlib
Requires-Dist: mpu6050-raspberrypi ; extra == "hardware" or extra == "all"
Requires-Dist: numpy
Requires-Dist: psutil ; extra == "performance" or extra == "all"
Requires-Dist: sphinx
Requires-Dist: sphinx-autodoc-typehints
Requires-Dist: sphinx-rtd-theme
Description-Content-Type: text/markdown

# IdentiTwin

<p align="center">
  <img src="https://github.com/estructuraPy/IdentiTwin/raw/main/identitwin.png" alt="IdentiTwin Logo" width="200"/>
</p>

## Overview

IdentiTwin is developed under the project ``Gemelo digital como herramienta de gestión del plan de conservación programada. Caso de estudio: foyer y fumadores del Teatro Nacional de Costa Rica``. The library provides comprehensive tools for structural vibration and displacement acquisition using Raspberry Pi and associated sensors.

## Core Features

### Real-time Monitoring
- Multi-threaded data acquisition system optimized for Raspberry Pi.
- Support for LVDT displacement sensors (via ADS1115 ADC) and MPU6050 accelerometers.
- Continuous performance tracking (sampling rate, jitter).
- Automated event detection based on configurable thresholds.
- Thread-safe data handling and buffering (pre-event and post-event).
- Status reporting and LED indicators.

### Event Detection & Recording
- Configurable trigger/detrigger thresholds for acceleration and displacement.
- Pre-event and post-event data buffering to capture the full event context.
- Minimum event duration setting to filter noise.
- Automated data persistence: saves event data to CSV and NPZ files.
- Background processing for saving data and generating analysis without interrupting acquisition.

### Signal Processing & Analysis
- Basic time-domain analysis (peak values).
- Fast Fourier Transform (FFT) analysis for frequency domain insights.
- Calculation of dominant frequencies.
- Automated generation of analysis plots (time series and FFT) for each event.
- Generation of summary reports for monitoring sessions and individual events.

### Hardware Support & Configuration
- Designed for Raspberry Pi with specific hardware (ADS1115, MPU6050).
- Utilizes `gpiozero` for LED indicators.
- I2C communication setup for sensors.
- Simulation mode for development and testing on non-Raspberry Pi platforms.
- Flexible configuration via Python script (`initialization.py`).

## Installation

```bash
pip install identitwin
```

### Prerequisites
- Raspberry Pi (tested on Raspberry Pi 5) with Raspberry Pi OS (or compatible Linux distribution).
- Python 3.8+
- Git

### Hardware Setup
- Connect ADS1115 ADC and MPU6050 sensors to the Raspberry Pi's I2C pins (SDA, SCL, VCC, GND). Ensure unique I2C addresses if using multiple MPU6050 sensors (e.g., 0x68, 0x69).
- Connect LVDTs to the ADS1115 analog input channels.
- Connect status and activity LEDs to the specified GPIO pins.

### Software Setup (Raspberry Pi)

1.  **Clone the Repository:**
    ```bash
    git clone https://github.com/estructuraPy/IdentiTwin.git
    cd IdentiTwin
    ```

2.  **Set up Virtual Environment (Recommended):**
    *   Give execute permissions to the setup script:
        ```bash
        chmod +x setup_env/setup_env.sh
        ```
    *   Run the setup script:
        ```bash
        ./setup_env/setup_env.sh
        ```
        This creates a virtual environment named `venv` and installs dependencies.

3.  **Activate the Virtual Environment:**
    ```bash
    source venv/bin/activate
    ```
    *(Your terminal prompt should now show `(venv)`)*

4.  **Install the Library (if not done by setup script):**
    If you didn't use the setup script or need to reinstall:
    ```bash
    pip install .
    ```
    *(The `.` refers to the current directory where `setup.py` is located)*

5.  **Configure and Run:**
    *   Navigate to the examples directory:
        ```bash
        cd examples
        ```
    *   *(Optional)* Copy the example initialization file if you want to keep the original:
        ```bash
        # cp initialization.py my_config.py
        # nano my_config.py
        ```
    *   Edit `initialization.py` (or your copy) to match your hardware setup:
        *   Set `NUM_LVDTS`, `NUM_ACCELS`.
        *   Define correct `LVDT_SLOPES` based on your sensor calibration.
        *   Adjust sampling rates (`ACCEL_SAMPLING_RATE`, `LVDT_SAMPLING_RATE`) if needed.
        *   Modify trigger/detrigger thresholds and event timing parameters as required.
        ```bash
        nano initialization.py
        ```
    *   Run the initialization script:
        ```bash
        python initialization.py
        ```
        *(Add command-line arguments if needed, e.g., `--output-dir /path/to/data`)*

6.  **Deactivate Virtual Environment (When finished):**
    ```bash
    deactivate
    ```

### Installation for Simulation/Development (Non-Raspberry Pi)

1.  **Clone the Repository:**
    ```bash
    git clone https://github.com/estructuraPy/IdentiTwin.git
    cd IdentiTwin
    ```
2.  **Create and Activate Virtual Environment:**
    ```bash
    python -m venv venv
    # On Windows:
    .\venv\Scripts\activate
    # On macOS/Linux:
    source venv/bin/activate
    ```
3.  **Install:**
    ```bash
    pip install .
    ```
    *(Hardware-specific libraries will fail to install, which is expected)*
4.  **Run in Simulation Mode:**
    The `initialization.py` script should automatically detect a non-Raspberry Pi environment and run in simulation mode.
    ```bash
    cd examples
    python initialization.py
    ```
    *(Or use the `--simulation` flag explicitly: `python initialization.py --simulation`)*

## Documentation

Full documentation is available at [Read the Docs](https://identitwin.readthedocs.io/).

Further details on configuration options, data formats, and analysis interpretation can be found in the project's technical documentation (link to be added).

## Requirements

- Python 3.8+
- numpy
- matplotlib

**Raspberry Pi Specific:**
- gpiozero
- adafruit-circuitpython-ads1x15
- mpu6050-raspberrypi
- adafruit-blinka (for CircuitPython compatibility)

## License

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

## Authors

- Ing. Angel Navarro-Mora M.Sc (ahnavarro@itcr.ac.cr / ahnavarro@anmingenieria.com)
- Alvaro Perez-Mora (alvaroenrique2001@estudiantec.cr)

## Copyright

© 2025 Instituto Tecnológico de Costa Rica (ITCR). All rights reserved.

