def testExecute(self):
self.run()
plugin = self.getPlugin()
output = plugin.dataOutput
reference = XSDataResCutoffResult.parseFile(self.getReferenceDataOutputFile())
EDAssert.strAlmostEqual(output.marshal(),
reference.marshal(),
"output looks good")
def testExecute(self):
self.run()
plugin = self.getPlugin()
output = plugin.dataOutput
reference = XSDataResCutoffResult.parseFile(
self.getReferenceDataOutputFile())
EDAssert.strAlmostEqual(output.marshal(), reference.marshal(),
"output looks good")
def process(self, _edObject=None):
EDPlugin.process(self)
detector_max_res = self.dataInput.detector_max_res
if detector_max_res is not None:
detector_max_res = detector_max_res.value
completeness_cutoff_param = self.dataInput.completeness_cutoff
if completeness_cutoff_param is None:
completeness_cutoff = 80
else:
completeness_cutoff = completeness_cutoff_param.value
isig_cutoff_param = self.dataInput.isig_cutoff
if isig_cutoff_param is None:
isig_cutoff = 3
else:
isig_cutoff = isig_cutoff_param.value
cc_half_cutoff_param = self.dataInput.cc_half_cutoff
if cc_half_cutoff_param is not None:
cc_half_cutoff = cc_half_cutoff_param.value
else:
cc_half_cutoff = 30
res_override = self.dataInput.res_override
bins = list()
# for the first iteration
# comment from max's code: "less stringent at low res"
local_completeness_cutoff = 70
# declared but not initialized in the perl code
prev_isig = prev_res = 0
# XXX: if res is still not defined at the end it is set to
# detector_max_res, which we should somehow defined (in the
# data model?) and used as the default value before we start
# the processing
res = detector_max_res
for entry in self.dataInput.completeness_entries:
current_res = entry.res.value
complete = entry.complete.value
rfactor = entry.rfactor.value
isig = entry.isig.value
cc_half = entry.half_dataset_correlation.value
# isig < isig_cutoff or \
if cc_half < cc_half_cutoff or \
(res_override is not None and current_res < res_override.value):
continue
else:
bins.append(current_res)
# Now the implementation of what max does when he encouters
# the total values, which are conveniently already parsed in
# our case
if len(bins) < 2:
strErrorMessage = "No bins with CC1/2 greater than %s" % cc_half_cutoff
self.ERROR(strErrorMessage)
self.addErrorMessage(strErrorMessage)
self.ERROR(
"Something could be wrong, or the completeness could be too low!"
)
self.ERROR(
"bravais lattice/SG could be incorrect or something more insidious like"
)
self.ERROR(
"incorrect parameters in XDS.INP like distance, X beam, Y beam, etc."
)
self.ERROR("Stopping")
self.setFailure()
return
if res is None:
res = sorted(bins)[0]
if res_override is not None:
res = res_override.value
retbins = [XSDataDouble(x) for x in bins]
data_output = XSDataResCutoffResult()
data_output.res = XSDataDouble(res)
data_output.bins = retbins
totals = self.dataInput.total_completeness
data_output.total_complete = totals.complete
data_output.total_rfactor = totals.rfactor
data_output.total_isig = totals.isig
self.dataOutput = data_output
def __init__(self):
EDPlugin.__init__(self)
self.setXSDataInputClass(XSDataResCutoff)
self.setDataOutput(XSDataResCutoffResult())
def process(self, _edObject=None):
EDPlugin.process(self)
detector_max_res = self.dataInput.detector_max_res
if detector_max_res is not None:
detector_max_res = detector_max_res.value
completeness_cutoff_param = self.dataInput.completeness_cutoff
if completeness_cutoff_param is None:
completeness_cutoff = 80
else:
completeness_cutoff = completeness_cutoff_param.value
isig_cutoff_param = self.dataInput.isig_cutoff
if isig_cutoff_param is None:
isig_cutoff = 3
else:
isig_cutoff = isig_cutoff_param.value
cc_half_cutoff_param = self.dataInput.cc_half_cutoff
if cc_half_cutoff_param is not None:
cc_half_cutoff = cc_half_cutoff_param.value
else:
cc_half_cutoff = 30
res_override = self.dataInput.res_override
bins = list()
# for the first iteration
# comment from max's code: "less stringent at low res"
local_completeness_cutoff = 70
# declared but not initialized in the perl code
prev_isig = prev_res = 0
# XXX: if res is still not defined at the end it is set to
# detector_max_res, which we should somehow defined (in the
# data model?) and used as the default value before we start
# the processing
res = detector_max_res
for entry in self.dataInput.completeness_entries:
current_res = entry.res.value
complete = entry.complete.value
rfactor = entry.rfactor.value
isig = entry.isig.value
cc_half = entry.half_dataset_correlation.value
# isig < isig_cutoff or \
if cc_half < cc_half_cutoff or \
(res_override is not None and current_res < res_override.value):
continue
else:
bins.append(current_res)
# Now the implementation of what max does when he encouters
# the total values, which are conveniently already parsed in
# our case
if len(bins) < 2:
strErrorMessage = "No bins with CC1/2 greater than %s" % cc_half_cutoff
self.ERROR(strErrorMessage)
self.addErrorMessage(strErrorMessage)
self.ERROR("Something could be wrong, or the completeness could be too low!")
self.ERROR("bravais lattice/SG could be incorrect or something more insidious like")
self.ERROR("incorrect parameters in XDS.INP like distance, X beam, Y beam, etc.")
self.ERROR("Stopping")
self.setFailure()
return
if res is None:
res = sorted(bins)[0]
if res_override is not None:
res = res_override.value
retbins = [XSDataDouble(x) for x in bins]
data_output = XSDataResCutoffResult()
data_output.res = XSDataDouble(res)
data_output.bins = retbins
totals = self.dataInput.total_completeness
data_output.total_complete = totals.complete
data_output.total_rfactor = totals.rfactor
data_output.total_isig = totals.isig
self.dataOutput = data_output
