def fit_bazin(self, band: str):
"""Extract Bazin features for one filter.
Parameters
----------
band: str
Choice of broad band filter
Returns
-------
bazin_param: list, float
Best fit parameters for the Bazin function: [a, b, t0, tfall, trise] followed by a float corresponding to
the value of the cost function for the fit.
"""
# build filter flag
filter_flag = self.photometry['band'] == band
# get info for this filter
time = self.photometry['mjd'].values[filter_flag]
### Do we want to be subtracting off the minimum flux here?
flux = self.photometry['flux'].values[filter_flag] - np.min(
self.photometry['flux'].values)
errors = self.photometry['fluxerr'].values[filter_flag]
# fit Bazin function
bazin_param = fit_scipy(time - time[0], flux, errors)
return bazin_param
def fit_bazin(self, band: str):
"""Extract Bazin features for one filter.
Parameters
----------
band: str
Choice of broad band filter
Returns
-------
bazin_param: list
Best fit parameters for the Bazin function: [a, b, t0, tfall, trise]
"""
# build filter flag
filter_flag = self.photometry['band'] == band
# get info for this filter
time = self.photometry['mjd'].values[filter_flag]
flux = self.photometry['flux'].values[filter_flag]
# fit Bazin function
bazin_param = fit_scipy(time - time[0], flux)
return bazin_param