threeML.utils.time_series.polynomial module¶
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class
threeML.utils.time_series.polynomial.
Polynomial
(coefficients: Iterable[float], is_integral: bool = False)[source]¶ Bases:
object
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property
coefficients
¶ Gets or sets the coefficients of the polynomial.
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property
covariance_matrix
¶
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property
degree
¶ the polynomial degree :return:
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property
error
¶ the error on the polynomial coefficients :return:
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classmethod
from_previous_fit
(coefficients, covariance) → threeML.utils.time_series.polynomial.Polynomial[source]¶
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property
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threeML.utils.time_series.polynomial.
polyfit
(x: Iterable[float], y: Iterable[float], grade: int, exposure: Iterable[float], bayes: bool = False) → Tuple[threeML.utils.time_series.polynomial.Polynomial, float][source]¶ function to fit a polynomial to data. not a member to allow parallel computation
- Parameters
x – the x coord of the data
y – teh y coord of the data
grade – the polynomical order or grade
expousure – the exposure of the interval
bayes – to do a bayesian fit or not
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threeML.utils.time_series.polynomial.
unbinned_polyfit
(events: Iterable[float], grade: int, t_start: float, t_stop: float, exposure: float, bayes: bool) → Tuple[threeML.utils.time_series.polynomial.Polynomial, float][source]¶ function to fit a polynomial to unbinned event data. not a member to allow parallel computation
- Parameters
events – the events to fit
grade – the polynomical order or grade
t_start – the start time to fit over
t_stop – the end time to fit over
expousure – the exposure of the interval
bayes – to do a bayesian fit or not