add readme.md file

README.md

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----
-license: mit
----
+---
+pretty_name: LightModulation
+license: mit
+task_categories:
+- other
+tags:
+- polymer-electronics
+- simulation
+- light-modulation
+- organic-photovoltaics
+- current-density
+- fft-analysis
+size_categories:
+- 1K<n<10K
+---
+
+# Light Modulation Analysis Dataset
+[![Code](https://img.shields.io/badge/GitHub-Code-black?logo=github)](https://github.com/baskargroup/LightModulation)
+
+## Dataset Description
+
+This dataset contains current-time curve data, extracted features, and analysis outputs from light modulation simulations of organic photovoltaic devices. The dataset includes both raw JT curves and processed features from FFT (Fast Fourier Transform) and JT cycle analysis.
+
+### Dataset Summary
+
+- **Total Files**: ~5,000 files
+- **Dataset Size**: ~436 MB (compressed: ~XXX MB)
+- **Modulation Types**: Sinusoidal and Square waveforms
+- **Data Types**: 
+  - Raw JT curve time-series data (.txt files)
+  - Extracted JT cycle features (CSV)
+  - FFT spectral analysis features (CSV)
+  - GRASPI morphological features (CSV)
+  - Analysis plots and visualizations (PNG)
+
+## Dataset Structure
+
+```
+data/
+├── modulation_profile/          # Light modulation waveform definitions
+│   ├── LM_sinusoidal.txt
+│   └── LM_square.txt
+├── all_jt_curves/               # Raw JT curve time-series data
+│   ├── sinusoidal/             # Sinusoidal modulation JT curves
+│   └── square/                 # Square modulation JT curves
+├── sample_jt_curves/           # Sample subset of JT curves
+├── morph_images/               # Morphology images
+├── jt_features_out/             # Extracted JT cycle features
+│   ├── jt_features_sinusoidal.csv
+│   ├── jt_features_square.csv
+│   └── figs_*/                 # Analysis plots
+├── fft_features_out/           # FFT spectral analysis features
+│   ├── fft_features_sinusoidal.csv
+│   ├── fft_features_square.csv
+│   └── */                      # FFT spectrum plots
+├── features_data.csv           # Merged feature dataset
+├── graspi_features.csv         # GRASPI morphological features
+└── figures/                    # Publication-quality figures
+```
+
+## Data Fields
+
+### JT Curve Files (.txt)
+Each JT curve file contains time-series data with the following columns:
+- `time(sec)`: Time in seconds
+- `J`: Current density in mA/cm²
+
+### JT Features 
+Extracted features from JT cycle analysis:
+- **Peak Features**: `peak_value`, `peak_time`, `left_min_value`, `right_min_value`
+- **Amplitude Features**: `left_amplitude`, `right_amplitude`, `avg_amplitude`
+- **Temporal Features**: `rise_time_ps`, `fall_time_ps`, `cycle_time_ps`, `time_avg_value`
+- **Phase Features**: `phase_shift_ps`
+- **Shape Features**: `skewness`, `skewness_2`, `asymmetry`
+- **Metadata**: `filename`, `modulation_type`
+
+### FFT Features
+Spectral analysis features:
+- `f1_Hz`: Fundamental frequency (Hz)
+- `H1_amp`: Fundamental harmonic amplitude
+- `THD_ratio`: Total Harmonic Distortion
+- `OER_odd_over_even`: Odd-to-even harmonic ratio
+- `harmonic_decay_slope_per_k`: Harmonic amplitude decay slope
+- `sampling_jitter`: Temporal sampling jitter
+- `filename`, `modulation_type`
+
+
+## Usage
+
+### Download the Dataset
+
+#### Option 1: Using the provided script (Recommended)
+
+1. Clone the Light Modulation Analysis repository:
+   ```bash
+   git clone https://github.com/baskargroup/LightModulation.git
+   cd LightModulation
+   ```
+
+2. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+3. Download the data:
+   ```bash
+   python download_data_from_hf.py --repo-id BGlab/light-modulation-data
+   ```
+
+The script will automatically:
+- Download the compressed archive
+- Extract to `data/` folder in the git root
+- Verify the extraction
+
+#### Option 2: Using Hugging Face Hub
+
+```python
+from huggingface_hub import hf_hub_download
+import tarfile
+
+# Download the archive
+archive_path = hf_hub_download(
+    repo_id="BGlab/light-modulation-data",
+    filename="data.tar.gz",
+    repo_type="dataset"
+)
+
+# Extract to current directory
+with tarfile.open(archive_path, 'r:gz') as tar:
+    tar.extractall()
+```
+
+### Using the Data
+
+Once downloaded, you can load the feature datasets:
+
+```python
+import pandas as pd
+
+# Load merged features
+features = pd.read_csv('data/features_data.csv')
+
+# Load GRASPI features
+graspi = pd.read_csv('data/graspi_features.csv', delimiter=' ')
+```
+
+## Dataset Creation
+
+### Source Data
+The dataset was generated from light modulation simulations of organic photovoltaic devices. JT curves were collected from simulation outputs and processed using the Light Modulation Analysis pipeline.
+
+### Preprocessing
+1. **JT Cycle Analysis**: Extracted temporal and amplitude features from current-time cycles
+2. **FFT Analysis**: Performed spectral decomposition to extract harmonic content
+3. **Feature Merging**: Combined JT, FFT, and GRASPI features into unified dataset
+
+### Analysis Windows
+- **Sinusoidal modulation**: Analysis window [0.89e-9, 0.96e-9] seconds
+- **Square modulation**: Analysis window [0.8e-9, 0.9e-9] seconds
+
+## Citation
+
+If you use this dataset in your research, please cite:
+
+```bibtex
+@dataset{light_modulation_2024,
+  title={Light Modulation Analysis Dataset},
+  author={BGlab},
+  year={2024},
+  url={https://huggingface.co/datasets/BGlab/light-modulation-data}
+}
+```
+
+## License
+
+This dataset is released under the MIT License.
+
+## Contact
+
+For questions or issues, please contact the maintainers.
+
+## Acknowledgments
+
+This dataset was created as part of research on light modulation effects in organic photovoltaic devices.
+