def guess(self, dep, *args, **kwargs):
ampl = guess_amplitude(dep, *args)
pos = get_position(dep, *args)
fwhm = guess_fwhm(dep, *args)
param_apply_limits(pos, self.pos, **kwargs)
norm = fwhm['val'] * numpy.sqrt(numpy.pi) * \
numpy.exp(lgam(self.index.val - 0.5) - lgam(self.index.val))
for key in ampl.keys():
ampl[key] *= norm
param_apply_limits(ampl, self.ampl, **kwargs)
def guess(self, dep, *args, **kwargs):
xpos, ypos = guess_position(dep, *args)
norm = guess_amplitude2d(dep, *args)
rad = guess_radius(*args)
param_apply_limits(xpos, self.xpos, **kwargs)
param_apply_limits(ypos, self.ypos, **kwargs)
param_apply_limits(norm, self.ampl, **kwargs)
param_apply_limits(rad, self.r0, **kwargs)
def guess(self, dep, *args, **kwargs):
vmax = get_peak(dep, *args)
tMax = vmax / 5.88e+10
t = {'val': tMax,
'min': tMax / _guess_ampl_scale,
'max': tMax * _guess_ampl_scale}
norm = guess_amplitude(dep, *args)
c_cm = 2.99792458e+10
h_erg = 6.6260693e-27
factor = numpy.exp(2.82) * numpy.square(c_cm) / h_erg / 2.
modampl = norm['val'] * factor / numpy.power(vmax, 3.)
mod = {'val': modampl,
'min': modampl / _guess_ampl_scale,
'max': modampl * _guess_ampl_scale}
param_apply_limits(mod, self.ampl, **kwargs)
param_apply_limits(t, self.t, **kwargs)
def guess(self, dep, *args, **kwargs):
if args[0][0] > args[0][-1]:
self.space.val = 1
Emax = get_peak(dep, *args)
tMax = Emax / 1.594
kt = {'val': tMax,
'min': tMax / _guess_ampl_scale,
'max': tMax * _guess_ampl_scale}
param_apply_limits(kt, self.kt, **kwargs)
norm = guess_amplitude(dep, *args)
modampl = norm['val'] * (numpy.exp(Emax / tMax) - 1) / \
numpy.square(Emax)
mod = {'val': modampl,
'min': modampl / _guess_ampl_scale,
'max': modampl * _guess_ampl_scale}
param_apply_limits(mod, self.ampl, **kwargs)
def guess(self, dep, *args, **kwargs):
pos = get_position(dep, *args)
fwhm = guess_fwhm(dep, *args)
param_apply_limits(pos, self.pos, **kwargs)
param_apply_limits(fwhm, self.fwhm, **kwargs)
norm = guess_amplitude(dep, *args)
if fwhm != 10:
aprime = norm['val'] * self.fwhm.val * numpy.pi / 2.
ampl = {'val': aprime,
'min': aprime / _guess_ampl_scale,
'max': aprime * _guess_ampl_scale}
param_apply_limits(ampl, self.ampl, **kwargs)
else:
param_apply_limits(norm, self.ampl, **kwargs)
def guess(self, dep, *args, **kwargs):
pos = get_position(dep, *args)
param_apply_limits(pos, self.eb, **kwargs)
ref = guess_reference(self.ref.min, self.ref.max, *args)
param_apply_limits(ref, self.ref, **kwargs)
norm = guess_amplitude_at_ref(self.ref.val, dep, *args)
param_apply_limits(norm, self.ampl, **kwargs)
def guess(self, dep, *args, **kwargs):
ref = guess_reference(self.rest.min, self.rest.max, *args)
param_apply_limits(ref, self.rest, **kwargs)
norm = guess_amplitude_at_ref(self.rest.val, dep, *args)
fwhm = get_fwhm(dep, *args)
c_km = 2.99792458e+5
if self.rest.val != 0:
vsini = 2. * fwhm * c_km / numpy.sqrt(3.) / self.rest.val
vs = {'val': vsini,
'min': vsini / _guess_ampl_scale,
'max': vsini * _guess_ampl_scale }
param_apply_limits(vs, self.vsini, **kwargs)
modampl = norm['val'] * numpy.pi * self.vsini.val * \
self.rest.val / 2. / c_km
mod = {'val': modampl,
'min': modampl / _guess_ampl_scale,
'max': modampl * _guess_ampl_scale}
param_apply_limits(mod, self.ampl, **kwargs)
def guess(self, dep, *args, **kwargs):
norm = guess_amplitude(dep, *args)
param_apply_limits(norm, self.norm, **kwargs)
