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box-least-squares

by benchflow-ai

Box Least Squares (BLS) periodogram for detecting transiting exoplanets and eclipsing binaries. Use when searching for periodic box-shaped dips in light curves. Alternative to Transit Least Squares, available in astropy.timeseries. Based on Kovács et al. (2002).

Installation

Pick a client and clone the repository into its skills directory.

Installation

Quick info

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Frontend
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About this skill

Box Least Squares (BLS) periodogram for detecting transiting exoplanets and eclipsing binaries. Use when searching for periodic box-shaped dips in light curves. Alternative to Transit Least Squares, available in astropy.timeseries. Based on Kovács et al. (2002).

How to use

  1. Zainstaluj Astropy, które zawiera moduł Box Least Squares, poleceniem pip install astropy.

  2. Przygotuj swoje dane: czas obserwacji, wartości strumienia jasności oraz błędy pomiaru. Upewnij się, że są to tablice NumPy lub obiekty Quantity z jednostkami (np. dni dla czasu).

  3. Utwórz obiekt BoxLeastSquares, przekazując czas, strumień i błędy: model = BoxLeastSquares(t, y, dy=dy), gdzie t to czas w jednostkach, y to jasność, a dy to błędy pomiaru.

  4. Uruchom automatyczne wyszukiwanie okresów za pomocą autopower(), określając oczekiwany czas trwania tranzyta: periodogram = model.autopower(duration). Metoda automatycznie ustali odpowiednią siatkę okresów do przeszukania.

  5. Wyodrębnij wyniki: znajdź okres o największej mocy w periodogramie, używając best_period = periodogram.period[np.argmax(periodogram.power)]. Wartość ta reprezentuje okres orbitalny wykrytego obiektu.

  6. Sprawdź dodatkowe parametry zwrócone przez periodogram: czas trwania tranzyta, głębokość spadku jasności oraz czas pierwszego tranzyta, aby w pełni scharakteryzować detekcję.

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