The delta2d model parameters remain unchanged in a fit to 2D non-integrated data
If the delta2d model is used to fit a non-integrated data set, with an optimization method other than Nelder-Mead, the xpos and ypos model parameters will not vary in the fit. Users can work around this issue by fitting the model to 2D integrated data sets, e.g.:
sherpa> load_data("img.ccd7.0.3-7_box_0.2bin.fits", dstype=DataIMGInt)
# instead of
sherpa> load_data("img.ccd7.0.3-7_box_0.2bin.fits")
The dataspace2d, load_data, unpack_data, unpack_image, and load_image commands accept this 'dstype' specification to determine the data set type.
Workaround:
A 2D integrated data set can be specified using dataspace2d with either:
sherpa> dataspace2d([100, 100], dstype=DataIMGInt)
or
sherpa> dataspace2d([100, 100], dstype=Data2DInt)
A work-around to force the delta2d model to be integrated from a non-integrated grid is provided in the example Python script below.
from sherpa.astro.ui import * from sherpa.models import Delta2D class MyDelta2D(Delta2D): """ Force the calculation of Delta2D to be integrated from a non-integrated grid """ def calc(self, p, x0, x1, *args, **kwargs): # NOTE: image coordinates only! return Delta2D.calc(self, p, x0-0.5, x1-0.5, x0+0.5, x1+0.5, *args, **kwargs) dataspace2d([100, 100]) set_source(const2d.c2) fake() set_method("neldermead") set_stat("cash") load_psf("psf2d", gauss2d.g2) set_psf(psf2d) g2.xpos = 30 g2.ypos = 70 freeze(g2) add_model(MyDelta2D) set_source(mydelta2d.sig + const2d.bkg) sig.xpos = 50 sig.ypos = 50 sig.ampl = 1000 fake() freeze(bkg) fit() # Here the g2 model is also being fit, while it is a definition of the # psf model and it should be kept frozen. fit() sig.xpos = 49 sig.ypos = 51 fit()