def calc(self, p, x, xhi=None, *args, **kwargs):
pha = self.pha
# TODO: this should probably include AREASCAL
user_grid = False
try:
if self._check_for_user_grid(x, xhi):
user_grid = True
self._startup_user_grid(x, xhi)
# Slow
if self.table is None:
# again, fit() never comes in here b/c it calls startup()
src = self.source
vals = []
for model, args in zip(self.models, self.grid):
elo, ehi = lo, hi = args
if pha.units == 'wavelength':
lo = DataPHA._hc / ehi
hi = DataPHA._hc / elo
vals.append(model(src(lo, hi)))
self.orders = vals
# Fast
else:
xlo, xhi = self.elo, self.ehi
if pha.units == 'wavelength':
xlo, xhi = self.lo, self.hi
src = self.source(xlo, xhi) # hi-res grid of all ARF grids
# Fold summed intervals through the associated response.
self.orders = \
[model(sum_intervals(src, interval[0], interval[1]))
for model, interval in zip(self.models, self.table)]
vals = sum(self.orders)
if self.mask is not None:
vals = vals[self.mask]
finally:
if user_grid:
self._teardown_user_grid()
return vals
def calc(self, p, x, xhi=None, *args, **kwargs):
pha = self.pha
user_grid = False
try:
if self._check_for_user_grid(x, xhi):
user_grid = True
self._startup_user_grid(x, xhi)
# Slow
if self.table is None:
# again, fit() never comes in here b/c it calls startup()
src = self.source
vals = []
for model, args in izip(self.models, self.grid):
elo,ehi = lo,hi = args
if pha.units == 'wavelength':
lo = DataPHA._hc / ehi
hi = DataPHA._hc / elo
vals.append(model(src(lo, hi)))
self.orders = vals
# Fast
else:
xlo,xhi = self.elo, self.ehi
if pha.units == 'wavelength':
xlo, xhi = self.lo, self.hi
src = self.source(xlo, xhi) # hi-res grid of all ARF grids
# Fold summed intervals through the associated response.
self.orders = \
[model(sum_intervals(src, interval[0], interval[1]))
for model, interval in izip(self.models, self.table)]
vals = sum(self.orders)
if self.mask is not None:
vals = vals[self.mask]
finally:
if user_grid:
self._teardown_user_grid()
return vals