Multiband features

These experimental features work with multi-band light curves.

light_curve.ColorOfMedian

Bases: light_curve.light_curve_py.features._base.BaseMultiBandFeature

Difference of median magnitudes in two bands.

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light_curve.RainbowFit

Bases: light_curve.light_curve_py.features.rainbow._base.BaseRainbowFit

Multiband blackbody fit to the light curve using functions to be chosen by the user Note, that m and corresponded sigma are assumed to be flux densities. Based on Russeil et al. 2023, arXiv:2310.02916.

Parameters:

Name	Type	Description	Default
band_wave_cm	dict	Dictionary of band names and their effective wavelengths in cm.	required
with_baseline	bool	Whether to include an offset in the fit, individual for each band. If it is true, one more fit paramter per passband is added - the additive constant with the same units as input flux.	True
bolometric	str or BaseBolometricTerm subclass	The shape of bolometric term. Default is 'bazin'. Other options are: 'sigmoid'	'bazin'
temperature	str or BaseTemperatureTerm subclass	The shape of temperature term. Default is 'sigmoid'. Other options are: 'constant', 'delayed_sigmoid'	'sigmoid'

Methods:

Name	Description
__call__	Evaluate the feature. Positional arguments are numpy arrays of the same length, band must consist of the same strings as keys in band_wave_cm. If sorted is True, t must be sorted in ascending order. If check is True, the input is checked for NaNs and Infs. If fill_value is not None, it is used to fill the output array if the feature cannot be evaluated.
model	Evaluate Rainbow model on the given arrays of times and bands. *params are fit parameters, basically the output of __call__ method but without the last parameter (reduced Chi^2 of the fit). See parameter names in the .name attribute.
peak_time	Return bolometric peak time for given set of parameters
fit_and_get_errors	The same as __call__ but also returns the parameter errors. Optionally sets the print_level (verbosity) for Minuit fitter. If get_initial is True, returns the initial parameters instead of fitted ones (useful for debugging)

bolometric = 'bazin' class-attribute

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.

temperature = 'sigmoid' class-attribute

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.

peak_time

Returns true bolometric peak position for given parameters