Metadata-Version: 2.1
Name: Deep-Lightcurve
Version: 0.1.0
Summary: A general Light curve classification framework based on deep learning
Author-email: Kaiming Cui <cuikaiming@sjtu.edu.cn>
License: MIT License
        
        Copyright (c) 2023 Kaiming Cui
        
        MIT License
        
        NTS-Net
        
        Copyright (c) 2020 Ze Yang
        
        MIT License
        
        conformal_classification
        
        Copyright (c) 2020 Anastasios Angelopoulos
        
        MIT License
        
        Lightkurve_ext
        
        Copyright (c) 2022 Kaiming Cui
        
        MIT License
        
        Lightkurve
        
        Copyright (c) 2018-2021 The Authors
        
        MIT License
        
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Project-URL: Homepage, https://github.com/ckm3/Deep-LC
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch
Requires-Dist: torchvision
Requires-Dist: gatspy
Requires-Dist: lightkurve>=2.0
Provides-Extra: dev
Requires-Dist: black; extra == "dev"
Requires-Dist: bumpver; extra == "dev"
Requires-Dist: isort; extra == "dev"
Requires-Dist: pip-tools; extra == "dev"
Requires-Dist: pytest; extra == "dev"

# Deep-LC

``Deep-LC``  is open-source and intended for the classification of light curves (LCs) in a gernaral purpose. It utilizes a weakly supervised object detection algorithm to automatically zoom in on the LC and power spectrum (PS) to extract local features. This eliminates the need for manual feature extraction and allows it to be applied to both space- and ground-based observations, as well as multiband LCs with large gaps and nonuniform sampling.

The implenmentaion and performace detail can be found in our paper.

LC component processing animation of TIC 470109695, which is a rotating variable star. Our model can automatically zoom in on the LC and PS to extract local features.

![LC component processing](docs/source/lc.gif)

PS component processing animation of KIC 12268220, which is an eclipsing bianry with a $\delta$ Scuti pulsating primary star.

![PS component processing](docs/source/ps.gif)

## Introduction

``Deep-LC`` is easy to install with pip:
```
pip install deep-lc
```

Or install the development version from source:
```
git clone https://github.com/ckm3/Deep-LC.git
cd Deep-LC
pip install -e .
```

## Quickstart

```python
from deep_lc import DeepLC

# Load model
dl_combined = DeepLC(combined_model="model_path")

# Load light curve
lc = np.load("your_light_curve_path")

# Predict as show intermediate results
prediction, figs = dl_combined.predict(lc, show_intermediate_results=True)

```

Please visit the [quickstart page](https://deep-lc.readthedocs.io/en/latest/Quickstart.html) for details.

## Citing

If you are using Deep-LC in your research, please cite our paper and add a footnote of this Github project.
