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# Lightkurve
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A comprehensive Python library for analyzing time series data from NASA's Kepler and TESS space telescopes. Lightkurve provides user-friendly tools for downloading, processing, analyzing, and visualizing astronomical flux data, enabling both basic exploratory analysis and sophisticated automated pipelines for exoplanet detection and stellar variability studies.
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## Package Information
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- **Package Name**: lightkurve
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- **Package Type**: pypi
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- **Language**: Python
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- **Installation**: `pip install lightkurve`
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## Core Imports
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```python
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import lightkurve as lk
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```
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For specific functionality:
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```python
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from lightkurve import LightCurve, TargetPixelFile, search_lightcurve, read, open
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```
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## Basic Usage
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```python
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import lightkurve as lk
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import astropy.units as u
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# Search for Kepler data
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search_result = lk.search_lightcurve('Kepler-10')
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# Download the first light curve
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lc = search_result[0].download()
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# Basic processing
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lc = lc.remove_nans().normalize()
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# Create a periodogram to find planets
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periodogram = lc.to_periodogram()
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# Plot the light curve
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lc.plot()
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# Fold the light curve at a specific period
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folded_lc = lc.fold(period=0.84 * u.day)
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folded_lc.plot()
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```
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## Architecture
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Lightkurve is built around several core data containers and analysis tools:
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- **Data Containers**: `LightCurve` and `TargetPixelFile` classes represent time series and pixel-level data respectively
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- **Collections**: Group multiple data files together for batch processing
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- **Search Functions**: Query and download data from MAST archives
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- **Analysis Tools**: Periodograms, correctors, and specialized analysis classes
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- **Utilities**: Time formats, quality flags, and helper functions designed for space telescope data
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The library integrates seamlessly with the scientific Python ecosystem, building on NumPy, SciPy, Matplotlib, and Astropy.
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## Capabilities
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### Data Search and Access
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Search and download time series data from NASA's space telescope archives, including Kepler, K2, and TESS missions with support for multiple data products and pipelines.
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```python { .api }
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def search_lightcurve(target, **kwargs):
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    """Search for light curve files in MAST archives"""
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def search_targetpixelfile(target, **kwargs):
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    """Search for target pixel files in MAST archives"""
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def search_tesscut(target, size, **kwargs):
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    """Search for TESS full frame image cutouts"""
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class SearchResult:
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    """Container for search results with download capabilities"""
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    def download(self, **kwargs): ...
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    def download_all(self, **kwargs): ...
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```
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[Data Search and Access](./data-search.md)
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### Core Data Objects
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Light curves and target pixel files are the fundamental data containers, providing rich functionality for time series analysis and visualization.
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```python { .api }
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class LightCurve:
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    """Time series data with time, flux, and flux_err columns"""
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    def __init__(self, time=None, flux=None, flux_err=None, **kwargs): ...
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    def plot(self, **kwargs): ...  
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    def remove_outliers(self, **kwargs): ...
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    def normalize(self, **kwargs): ...
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    def fold(self, period, **kwargs): ...
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class TargetPixelFile:
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    """Pixel-level time series data from space telescopes"""
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    def to_lightcurve(self, **kwargs): ...
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    def plot(self, **kwargs): ...
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    def interact(self, **kwargs): ...
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```
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[Core Data Objects](./core-data.md)
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### Time Series Analysis  
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Comprehensive periodogram analysis for detecting periodic signals, including specialized algorithms for transit detection and stellar oscillations.
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```python { .api }
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class Periodogram:
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    """Power spectrum representation with peak detection"""
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    def plot(self, **kwargs): ...
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    def show_properties(self): ...
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class LombScarglePeriodogram(Periodogram):
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    """Lomb-Scargle periodogram for unevenly sampled data"""
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class BoxLeastSquaresPeriodogram(Periodogram):
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    """Box Least Squares periodogram for transit detection"""
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```
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[Time Series Analysis](./time-series-analysis.md)
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### Systematics Correction
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Advanced algorithms for removing instrumental systematics and improving photometric precision, essential for detecting small astrophysical signals.
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```python { .api }
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class PLDCorrector:
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    """Pixel Level Decorrelation for removing systematic noise"""
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    def correct(self, **kwargs): ...
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class CBVCorrector:
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    """Cotrending Basis Vector correction using pre-computed vectors"""
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    def correct(self, **kwargs): ...
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class SFFCorrector:
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    """Self Flat Fielding for K2 data correction"""
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    def correct(self, **kwargs): ...
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```
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[Systematics Correction](./systematics-correction.md)
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### Point Spread Function Modeling
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Sophisticated PSF modeling and photometry for extracting precise light curves from pixel data, particularly useful for crowded fields and faint targets.
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```python { .api }
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class KeplerPRF:
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    """Kepler Point Response Function model"""
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    def evaluate(self, **kwargs): ...
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class PRFPhotometry:
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    """High-level interface for PRF photometry analysis"""
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    def fit(self, **kwargs): ...
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```
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[Point Spread Function Modeling](./prf-modeling.md)
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### Asteroseismology
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Specialized tools for analyzing stellar oscillations and deriving fundamental stellar properties from seismic parameters.
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```python { .api }
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class Seismology:
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    """Asteroseismology analysis for stellar oscillations"""
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    def estimate_numax(self, **kwargs): ...
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    def estimate_deltanu(self, **kwargs): ...
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def estimate_radius(numax, deltanu, teff): ...
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def estimate_mass(numax, deltanu, teff): ...
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```
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[Asteroseismology](./asteroseismology.md)
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## Types
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```python { .api }
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# Time formats for space telescope data
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class TimeBKJD:
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    """Barycentric Kepler Julian Date"""
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class TimeBTJD:
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    """Barycentric TESS Julian Date"""
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# Quality flag decoders
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class KeplerQualityFlags:
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    """Decoder for Kepler data quality flags"""
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class TessQualityFlags:
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    """Decoder for TESS data quality flags"""
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# Configuration
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class Conf:
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    """Configuration parameters for lightkurve"""
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    cache_dir: str
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    search_result_display_extra_columns: list
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```