本文整理匯總了Python中xia2.Handlers.Flags.Flags.get_scale_model_absorption方法的典型用法代碼示例。如果您正苦於以下問題：Python Flags.get_scale_model_absorption方法的具體用法？Python Flags.get_scale_model_absorption怎麽用？Python Flags.get_scale_model_absorption使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類xia2.Handlers.Flags.Flags的用法示例。
在下文中一共展示了Flags.get_scale_model_absorption方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: __init__
# 需要導入模塊: from xia2.Handlers.Flags import Flags [as 別名]
# 或者: from xia2.Handlers.Flags.Flags import get_scale_model_absorption [as 別名]
def __init__(self):
super(XDSScalerA, self).__init__()
self._sweep_information = { }
self._reference = None
# spacegroup and unit cell information - these will be
# derived from an average of all of the sweeps which are
# passed in
self._xds_spacegroup = None
self._factory = CCP4Factory()
self._chef_analysis_groups = { }
self._chef_analysis_times = { }
self._chef_analysis_resolutions = { }
self._user_resolution_limits = { }
# scaling correction choices - may be set one on the command line...
if Flags.get_scale_model():
self._scalr_correct_absorption = Flags.get_scale_model_absorption()
self._scalr_correct_modulation = Flags.get_scale_model_modulation()
self._scalr_correct_decay = Flags.get_scale_model_decay()
self._scalr_corrections = True
else:
self._scalr_correct_decay = True
self._scalr_correct_modulation = True
self._scalr_correct_absorption = True
self._scalr_corrections = True
return示例2: _determine_best_scale_model_8way
# 需要導入模塊: from xia2.Handlers.Flags import Flags [as 別名]
# 或者: from xia2.Handlers.Flags.Flags import get_scale_model_absorption [as 別名]
def _determine_best_scale_model_8way(self):
'''Determine the best set of corrections to apply to the data,
testing all eight permutations.'''
# if we have already defined the best scaling model just return
if self._scalr_corrections:
return
# or see if we set one on the command line...
if Flags.get_scale_model():
self._scalr_correct_absorption = Flags.get_scale_model_absorption()
self._scalr_correct_partiality = Flags.get_scale_model_partiality()
self._scalr_correct_decay = Flags.get_scale_model_decay()
self._scalr_corrections = True
return
Debug.write('Optimising scaling corrections...')
rmerge_def = self._assess_scaling_model(
tails = False, bfactor = False, secondary = False)
results = { }
consider = []
log_results = []
for partiality in True, False:
for decay in True, False:
for absorption in True, False:
if partiality or decay or absorption:
r = self._assess_scaling_model(
tails = partiality, bfactor = decay,
secondary = absorption)
else:
r = rmerge_def
results[(partiality, decay, absorption)] = r
log_results.append((partiality, decay, absorption, r))
consider.append(
(r, partiality, decay, absorption))
Debug.write('. Tails Decay Abs R(%s)' % \
Flags.get_rmerge_target())
for result in log_results:
Debug.write('. %5s %5s %5s %.3f' % result)
consider.sort()
rmerge, partiality, decay, absorption = consider[0]
if absorption:
Debug.write('Absorption correction: on')
else:
Debug.write('Absorption correction: off')
if partiality:
Debug.write('Partiality correction: on')
else:
Debug.write('Partiality correction: off')
if decay:
Debug.write('Decay correction: on')
else:
Debug.write('Decay correction: off')
self._scalr_correct_absorption = absorption
self._scalr_correct_partiality = partiality
self._scalr_correct_decay = decay
self._scalr_corrections = True
return