README.md

# StingrayExplorer

StingrayExplorer is a data analysis tool designed for quick visualization and exploration of astronomical time series data. It leverages the Stingray library to compute power spectra, cross spectra, and more, with a user-friendly dashboard built using Panel.

## Project Structure

```
.
├── assets
│   ├── audio
│   ├── icons
│   │   └── svg.py
│   ├── images
│   ├── stylesheets
│   │   └── explorer.css
│   └── videos
├── explorer.py
├── files
│   ├── data
│   └── loaded-data
├── modules
│   ├── DataLoading
│   │   ├── DataIngestion.py
│   ├── Home
│   │   ├── HomeContent.py
│   └── QuickLook
│       ├── AverageCrossSpectrum.py
│       ├── AveragePowerSpectrum.py
│       ├── CrossSpectrum.py
│       ├── LightCurve.py
│       ├── PowerSpectrum.py
├── utils
    ├── DashboardClasses.py
    ├── globals.py
    ├── sidebar.py
    └── strings.py
```

## Installation

### Prerequisites

- Python 3.11 or above
- Panel
- Holoviews
- Stingray
- Other dependencies listed in `environment.yml`

### Setup

1. Clone the repository:

    ```
    git clone <repository_url>
    ```

2. Navigate to the project directory:

    ```
    cd StingrayExplorer
    ```

3. Create and activate the conda environment:

    ```bash
    conda env create -f environment.yml
    conda activate stingray-env
    ```
Note: In case of dependencies clashing refer to individual dependencies and see if the version is correct for Stingray installation. 
The most important dependencies are as follows:
stingray, holoviews, panel
You would need to instal the various dependencies to install all this. 

If the import errors are still persisting, see what libraries absence is causing the import and install them from pip or conda forge. 
## Usage

To run the StingrayExplorer application, execute inside StingrayExplorer:

```
panel serve explorer.py --autoreload --static-dirs assets=./assets
```

This will start a Panel server and launch the application in your default web browser.

## Modules

### `explorer.py`

The main entry point of the application. It initializes the Panel server and sets up the layout of the dashboard.

### `assets/`

Contains static assets like icons, images, stylesheets, audio, and video files used in the dashboard.

### `files/`

Contains example data files and event lists that can be loaded into the application for analysis.

### `modules/`

#### `DataLoading/`

- **DataIngestion.py**: Handles the loading and preprocessing of event list data.

#### `Home/`

- **HomeContent.py**: Contains the components and layout for the home screen of the dashboard.

#### `QuickLook/`

- **AverageCrossSpectrum.py**: Module for computing and visualizing averaged cross spectra.
- **AveragePowerSpectrum.py**: Module for computing and visualizing averaged power spectra.
- **CrossSpectrum.py**: Module for computing and visualizing cross spectra.
- **LightCurve.py**: Module for generating and displaying light curves.
- **PowerSpectrum.py**: Module for generating and displaying power spectra.

### `utils/`

- **DashboardClasses.py**: Contains reusable classes for constructing the dashboard layout and components.
- **globals.py**: Stores global variables and state used across different modules.
- **sidebar.py**: Manages the sidebar navigation and interactions.
- **strings.py**: Contains strings and messages used in the application.

## Features

- **Quick Visualization**: Easily generate and visualize light curves, power spectra, and cross spectra.
- **Data Loading**: Load and analyze different event list data sets.
- **Interactive UI**: Use a user-friendly interface to interact with the data and view results in real-time.
- **Floating Panels**: Separate panels for different plots and data frames, allowing for a customizable layout.

## Contributing

If you would like to contribute to this project, please follow the steps below:

1. Fork the repository.
2. Create a new branch (`git checkout -b feature-branch`).
3. Make your changes and commit them (`git commit -m 'Add new feature'`).
4. Push to the branch (`git push origin feature-branch`).
5. Create a new Pull Request.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Acknowledgments

- The Stingray library for providing tools for X-ray astronomy data analysis.
- Panel and Holoviews (HoloViz ecosystem) for enabling interactive data visualization in Python.