def process_form(self, instance, field, form, empty_marker = None, emptyReturnsMarker = False):
""" Return a list of dictionaries fit for AnalysisSpecsResultsField
consumption. If neither hidemin nor hidemax are specified, only
services which have float()able entries in result,min and max field
will be included. If hidemin and/or hidemax specified, results
might contain empty min and/or max fields.
"""
value = []
if 'service' in form:
for uid, keyword in form['keyword'][0].items():
hidemin = form['hidemin'][0].get(uid, '') if 'hidemin' in form else ''
hidemax = form['hidemax'][0].get(uid, '') if 'hidemax' in form else ''
mins = form['min'][0].get(uid, '') if 'min' in form else ''
maxs = form['max'][0].get(uid, '') if 'max' in form else ''
err = form['error'][0].get(uid, '') if 'error' in form else ''
rangecomment = form['rangecomment'][0].get(uid, '') if 'rangecomment' in form else ''
if not isnumber(hidemin) and not isnumber(hidemax) and \
(not isnumber(mins) or not isnumber(maxs)):
# If neither hidemin nor hidemax have been specified,
# min and max values are mandatory.
continue
value.append({'keyword': keyword,
'uid': uid,
'min': mins if isnumber(mins) else '',
'max': maxs if isnumber(maxs) else '',
'hidemin': hidemin if isnumber(hidemin) else '',
'hidemax': hidemax if isnumber(hidemax) else '',
'error': err if isnumber(err) else '0',
'rangecomment': rangecomment})
return value, {}
def _analysis_data(self, analysis, decimalmark=None):
keyword = analysis.getKeyword()
service = analysis.getService()
andict = {'obj': analysis,
'id': analysis.id,
'title': analysis.Title(),
'keyword': keyword,
'scientific_name': service.getScientificName(),
'accredited': service.getAccredited(),
'point_of_capture': to_utf8(POINTS_OF_CAPTURE.getValue(service.getPointOfCapture())),
'category': to_utf8(service.getCategoryTitle()),
'result': analysis.getResult(),
'isnumber': isnumber(analysis.getResult()),
'unit': to_utf8(service.getUnit()),
'formatted_unit': format_supsub(to_utf8(service.getUnit())),
'capture_date': analysis.getResultCaptureDate(),
'request_id': analysis.aq_parent.getId(),
'formatted_result': '',
'uncertainty': analysis.getUncertainty(),
'formatted_uncertainty': '',
'retested': analysis.getRetested(),
'remarks': to_utf8(analysis.getRemarks()),
'resultdm': to_utf8(analysis.getResultDM()),
'outofrange': False,
'type': analysis.portal_type,
'reftype': analysis.getReferenceType() \
if hasattr(analysis, 'getReferenceType')
else None,
'worksheet': None,
'specs': {},
'formatted_specs': ''}
if analysis.portal_type == 'DuplicateAnalysis':
andict['reftype'] = 'd'
ws = analysis.getBackReferences('WorksheetAnalysis')
andict['worksheet'] = ws[0].id if ws and len(ws) > 0 else None
andict['worksheet_url'] = ws[0].absolute_url if ws and len(
ws) > 0 else None
andict['refsample'] = analysis.getSample().id \
if analysis.portal_type == 'Analysis' \
else '%s - %s' % (analysis.aq_parent.id, analysis.aq_parent.Title())
# Which analysis specs must be used?
# Try first with those defined at AR Publish Specs level
if analysis.portal_type == 'ReferenceAnalysis':
# The analysis is a Control or Blank. We might use the
# reference results instead other specs
uid = analysis.getServiceUID()
specs = analysis.aq_parent.getResultsRangeDict().get(uid, {})
elif analysis.portal_type == 'DuplicateAnalysis':
specs = analysis.getAnalysisSpecs()
else:
ar = analysis.aq_parent
specs = ar.getPublicationSpecification()
if not specs or keyword not in specs.getResultsRangeDict():
specs = analysis.getAnalysisSpecs()
specs = specs.getResultsRangeDict().get(keyword, {}) \
if specs else {}
andict['specs'] = specs
scinot = self.context.bika_setup.getScientificNotationReport()
andict['formatted_result'] = analysis.getFormattedResult(
specs=specs, sciformat=int(scinot), decimalmark=decimalmark)
fs = ''
if specs.get('min', None) and specs.get('max', None):
fs = '%s - %s' % (specs['min'], specs['max'])
elif specs.get('min', None):
fs = '> %s' % specs['min']
elif specs.get('max', None):
fs = '< %s' % specs['max']
andict['formatted_specs'] = formatDecimalMark(fs, decimalmark)
andict['formatted_uncertainty'] = format_uncertainty(
analysis,
analysis.getResult(),
decimalmark=decimalmark,
sciformat=int(scinot))
# Out of range?
if specs:
adapters = getAdapters((analysis, ), IResultOutOfRange)
bsc = getToolByName(self.context, "bika_setup_catalog")
for name, adapter in adapters:
ret = adapter(specification=specs)
if ret and ret['out_of_range']:
andict['outofrange'] = True
break
return andict
def calculate(self, uid=None):
analysis = self.analyses[uid]
form_result = self.current_results[uid]['result']
service = analysis.getService()
calculation = service.getCalculation()
if analysis.portal_type == 'ReferenceAnalysis':
deps = {}
else:
deps = {}
for dep in analysis.getDependencies():
deps[dep.UID()] = dep
path = '++resource++bika.lims.images'
mapping = {}
# values to be returned to form for this UID
Result = {'uid': uid, 'result': form_result}
try:
Result['result'] = float(form_result)
except:
if form_result == "0/0":
Result['result'] = ""
if calculation:
'''
We need first to create the map of available parameters
acording to the interims, analyses and wildcards:
params = {
<as-1-keyword> : <analysis_result>,
<as-1-keyword>.<wildcard-1> : <wildcard_1_value>,
<as-1-keyword>.<wildcard-2> : <wildcard_2_value>,
<interim-1> : <interim_result>,
...
}
'''
# Get dependent analyses results and wildcard values to the
# mapping. If dependent analysis without result found,
# break and abort calculation
unsatisfied = False
for dependency_uid, dependency in deps.items():
if dependency_uid in self.ignore_uids:
unsatisfied = True
break
# LIMS-1769. Allow to use LDL and UDL in calculations.
# https://jira.bikalabs.com/browse/LIMS-1769
analysisvalues = {}
if dependency_uid in self.current_results:
analysisvalues = self.current_results[dependency_uid]
else:
# Retrieve the result and DLs from the analysis
analysisvalues = {
'keyword': dependency.getKeyword(),
'result': dependency.getResult(),
'ldl': dependency.getLowerDetectionLimit(),
'udl': dependency.getUpperDetectionLimit(),
'belowldl': dependency.isBelowLowerDetectionLimit(),
'aboveudl': dependency.isAboveUpperDetectionLimit(),
}
if analysisvalues['result']=='':
unsatisfied = True
break;
key = analysisvalues.get('keyword',dependency.getService().getKeyword())
# Analysis result
# All result mappings must be float, or they are ignored.
try:
mapping[key] = float(analysisvalues.get('result'))
mapping['%s.%s' % (key, 'RESULT')] = float(analysisvalues.get('result'))
mapping['%s.%s' % (key, 'LDL')] = float(analysisvalues.get('ldl'))
mapping['%s.%s' % (key, 'UDL')] = float(analysisvalues.get('udl'))
mapping['%s.%s' % (key, 'BELOWLDL')] = int(analysisvalues.get('belowldl'))
mapping['%s.%s' % (key, 'ABOVEUDL')] = int(analysisvalues.get('aboveudl'))
except:
# If not floatable, then abort!
unsatisfied = True
break
if unsatisfied:
# unsatisfied means that one or more result on which we depend
# is blank or unavailable, so we set blank result and abort.
self.results.append({'uid': uid,
'result': '',
'formatted_result': ''})
return None
# Add all interims to mapping
for i_uid, i_data in self.item_data.items():
for i in i_data:
# if this interim belongs to current analysis and is blank,
# return an empty result for this analysis.
if i_uid == uid and i['value'] == '':
self.results.append({'uid': uid,
'result': '',
'formatted_result': ''})
return None
# All interims must be float, or they are ignored.
try:
i['value'] = float(i['value'])
except:
pass
# all interims are ServiceKeyword.InterimKeyword
if i_uid in deps:
key = "%s.%s" % (deps[i_uid].getService().getKeyword(),
i['keyword'])
mapping[key] = i['value']
# this analysis' interims get extra reference
# without service keyword prefix
if uid == i_uid:
mapping[i['keyword']] = i['value']
# Grab values for hidden InterimFields for only for current calculation
# we can't allow non-floats through here till we change the eval's
# interpolation
hidden_fields = []
c_fields = calculation.getInterimFields()
s_fields = service.getInterimFields()
for field in c_fields:
if field.get('hidden', False):
hidden_fields.append(field['keyword'])
try:
mapping[field['keyword']] = float(field['value'])
except ValueError:
pass
# also grab stickier defaults from AnalysisService
for field in s_fields:
if field['keyword'] in hidden_fields:
try:
mapping[field['keyword']] = float(field['value'])
except ValueError:
pass
# convert formula to a valid python string, ready for interpolation
formula = calculation.getMinifiedFormula()
formula = formula.replace('[', '%(').replace(']', ')f')
try:
formula = eval("'%s'%%mapping" % formula,
{"__builtins__": None,
'math': math,
'context': self.context},
{'mapping': mapping})
# calculate
result = eval(formula)
Result['result'] = result
self.current_results[uid]['result'] = result
except TypeError as e:
# non-numeric arguments in interim mapping?
alert = {'field': 'Result',
'icon': path + '/exclamation.png',
'msg': "{0}: {1} ({2}) ".format(
t(_("Type Error")),
html_quote(str(e.args[0])),
formula)}
if uid in self.alerts:
self.alerts[uid].append(alert)
else:
self.alerts[uid] = [alert, ]
except ZeroDivisionError as e:
Result['result'] = '0/0'
Result['formatted_result'] = '0/0'
self.current_results[uid]['result'] = '0/0'
self.results.append(Result)
alert = {'field': 'Result',
'icon': path + '/exclamation.png',
'msg': "{0}: {1} ({2}) ".format(
t(_("Division by zero")),
html_quote(str(e.args[0])),
formula)}
if uid in self.alerts:
self.alerts[uid].append(alert)
else:
self.alerts[uid] = [alert, ]
return None
except KeyError as e:
alert = {'field': 'Result',
'icon': path + '/exclamation.png',
'msg': "{0}: {1} ({2}) ".format(
t(_("Key Error")),
html_quote(str(e.args[0])),
formula)}
if uid in self.alerts:
self.alerts[uid].append(alert)
else:
self.alerts[uid] = [alert, ]
# format result
belowmin = False
abovemax = False
# Some analyses will not have AnalysisSpecs, eg, ReferenceAnalysis
if hasattr(analysis, 'getAnalysisSpecs'):
specs = analysis.getAnalysisSpecs()
specs = specs.getResultsRangeDict() if specs is not None else {}
specs = specs.get(analysis.getKeyword(), {})
hidemin = specs.get('hidemin', '')
hidemax = specs.get('hidemax', '')
if Result.get('result', ''):
fresult = Result['result']
try:
belowmin = hidemin and fresult < float(hidemin) or False
except ValueError:
belowmin = False
pass
try:
abovemax = hidemax and fresult > float(hidemax) or False
except ValueError:
abovemax = False
pass
if belowmin is True:
Result['formatted_result'] = '< %s' % hidemin
elif abovemax is True:
Result['formatted_result'] = '> %s' % hidemax
else:
try:
Result['formatted_result'] = format_numeric_result(analysis,
Result['result'])
except ValueError:
# non-float
Result['formatted_result'] = Result['result']
# calculate Dry Matter result
# if parent is not an AR, it's never going to be calculable
dm = hasattr(analysis.aq_parent, 'getReportDryMatter') and \
analysis.aq_parent.getReportDryMatter() and \
analysis.getService().getReportDryMatter()
if dm:
dry_service = self.context.bika_setup.getDryMatterService()
# get the UID of the DryMatter Analysis from our parent AR
dry_analysis = [a for a in
analysis.aq_parent.getAnalyses(full_objects=True)
if a.getService().UID() == dry_service.UID()]
if dry_analysis:
dry_analysis = dry_analysis[0]
dry_uid = dry_analysis.UID()
# get the current DryMatter analysis result from the form
if dry_uid in self.current_results:
try:
dry_result = float(self.current_results[dry_uid])
except:
dm = False
else:
try:
dry_result = float(dry_analysis.getResult())
except:
dm = False
else:
dm = False
Result['dry_result'] = dm and dry_result and \
'%.2f' % ((Result['result'] / dry_result) * 100) or ''
self.results.append(Result)
# if App.config.getConfiguration().debug_mode:
# logger.info("calc.py: %s->%s %s" % (analysis.aq_parent.id,
# analysis.id,
# Result))
# LIMS-1808 Uncertainty calculation on DL
# https://jira.bikalabs.com/browse/LIMS-1808
flres = Result.get('result', None)
if flres and isnumber(flres):
flres = float(flres)
anvals = self.current_results[uid]
isldl = anvals.get('isldl', False)
isudl = anvals.get('isudl', False)
ldl = anvals.get('ldl',0)
udl = anvals.get('udl',0)
ldl = float(ldl) if isnumber(ldl) else 0
udl = float(udl) if isnumber(udl) else 10000000
belowldl = (isldl or flres < ldl)
aboveudl = (isudl or flres > udl)
unc = '' if (belowldl or aboveudl) else analysis.getUncertainty(Result.get('result'))
if not (belowldl or aboveudl):
self.uncertainties.append({'uid': uid, 'uncertainty': unc})
# maybe a service who depends on us must be recalculated.
if analysis.portal_type == 'ReferenceAnalysis':
dependents = []
else:
dependents = analysis.getDependents()
if dependents:
for dependent in dependents:
dependent_uid = dependent.UID()
# ignore analyses that no longer exist.
if dependent_uid in self.ignore_uids or \
dependent_uid not in self.analyses:
continue
self.calculate(dependent_uid)
# These self.alerts are just for the json return.
# we're placing the entire form's results in kwargs.
adapters = getAdapters((analysis, ), IFieldIcons)
for name, adapter in adapters:
alerts = adapter(result=Result['result'], form_results=self.current_results)
if alerts:
if analysis.UID() in self.alerts:
self.alerts[analysis.UID()].extend(alerts[analysis.UID()])
else:
self.alerts[analysis.UID()] = alerts[analysis.UID()]
def _analysis_data(self, analysis, decimalmark=None):
keyword = analysis.getKeyword()
service = analysis.getService()
andict = {'obj': analysis,
'id': analysis.id,
'title': analysis.Title(),
'keyword': keyword,
'scientific_name': service.getScientificName(),
'accredited': service.getAccredited(),
'point_of_capture': to_utf8(POINTS_OF_CAPTURE.getValue(service.getPointOfCapture())),
'category': to_utf8(service.getCategoryTitle()),
'result': analysis.getResult(),
'isnumber': isnumber(analysis.getResult()),
'unit': to_utf8(service.getUnit()),
'formatted_unit': format_supsub(to_utf8(service.getUnit())),
'capture_date': analysis.getResultCaptureDate(),
'request_id': analysis.aq_parent.getId(),
'formatted_result': '',
'uncertainty': analysis.getUncertainty(),
'formatted_uncertainty': '',
'retested': analysis.getRetested(),
'remarks': to_utf8(analysis.getRemarks()),
'resultdm': to_utf8(analysis.getResultDM()),
'outofrange': False,
'type': analysis.portal_type,
'reftype': analysis.getReferenceType() \
if hasattr(analysis, 'getReferenceType')
else None,
'worksheet': None,
'specs': {},
'formatted_specs': ''}
if analysis.portal_type == 'DuplicateAnalysis':
andict['reftype'] = 'd'
ws = analysis.getBackReferences('WorksheetAnalysis')
andict['worksheet'] = ws[0].id if ws and len(ws) > 0 else None
andict['worksheet_url'] = ws[0].absolute_url if ws and len(ws) > 0 else None
andict['refsample'] = analysis.getSample().id \
if analysis.portal_type == 'Analysis' \
else '%s - %s' % (analysis.aq_parent.id, analysis.aq_parent.Title())
# Which analysis specs must be used?
# Try first with those defined at AR Publish Specs level
if analysis.portal_type == 'ReferenceAnalysis':
# The analysis is a Control or Blank. We might use the
# reference results instead other specs
uid = analysis.getServiceUID()
specs = analysis.aq_parent.getResultsRangeDict().get(uid, {})
elif analysis.portal_type == 'DuplicateAnalysis':
specs = analysis.getAnalysisSpecs();
else:
ar = analysis.aq_parent
specs = ar.getPublicationSpecification()
if not specs or keyword not in specs.getResultsRangeDict():
specs = analysis.getAnalysisSpecs()
specs = specs.getResultsRangeDict().get(keyword, {}) \
if specs else {}
andict['specs'] = specs
scinot = self.context.bika_setup.getScientificNotationReport()
andict['formatted_result'] = analysis.getFormattedResult(specs=specs, sciformat=int(scinot), decimalmark=decimalmark)
fs = ''
if specs.get('min', None) and specs.get('max', None):
fs = '%s - %s' % (specs['min'], specs['max'])
elif specs.get('min', None):
fs = '> %s' % specs['min']
elif specs.get('max', None):
fs = '< %s' % specs['max']
andict['formatted_specs'] = formatDecimalMark(fs, decimalmark)
andict['formatted_uncertainty'] = format_uncertainty(analysis, analysis.getResult(), decimalmark=decimalmark, sciformat=int(scinot))
# Out of range?
if specs:
adapters = getAdapters((analysis, ), IResultOutOfRange)
bsc = getToolByName(self.context, "bika_setup_catalog")
for name, adapter in adapters:
ret = adapter(specification=specs)
if ret and ret['out_of_range']:
andict['outofrange'] = True
break
return andict
def calculate(self, uid=None):
analysis = self.analyses[uid]
form_result = self.current_results[uid]['result']
service = analysis.getService()
calculation = service.getCalculation()
if analysis.portal_type == 'ReferenceAnalysis':
deps = {}
else:
deps = {}
for dep in analysis.getDependencies():
deps[dep.UID()] = dep
path = '++resource++bika.lims.images'
mapping = {}
# values to be returned to form for this UID
Result = {'uid': uid, 'result': form_result}
try:
Result['result'] = float(form_result)
except:
if form_result == "0/0":
Result['result'] = ""
if calculation:
'''
We need first to create the map of available parameters
acording to the interims, analyses and wildcards:
params = {
<as-1-keyword> : <analysis_result>,
<as-1-keyword>.<wildcard-1> : <wildcard_1_value>,
<as-1-keyword>.<wildcard-2> : <wildcard_2_value>,
<interim-1> : <interim_result>,
...
}
'''
# Get dependent analyses results and wildcard values to the
# mapping. If dependent analysis without result found,
# break and abort calculation
unsatisfied = False
for dependency_uid, dependency in deps.items():
if dependency_uid in self.ignore_uids:
unsatisfied = True
break
# LIMS-1769. Allow to use LDL and UDL in calculations.
# https://jira.bikalabs.com/browse/LIMS-1769
analysisvalues = {}
if dependency_uid in self.current_results:
analysisvalues = self.current_results[dependency_uid]
else:
# Retrieve the result and DLs from the analysis
analysisvalues = {
'keyword': dependency.getKeyword(),
'result': dependency.getResult(),
'ldl': dependency.getLowerDetectionLimit(),
'udl': dependency.getUpperDetectionLimit(),
'belowldl': dependency.isBelowLowerDetectionLimit(),
'aboveudl': dependency.isAboveUpperDetectionLimit(),
}
if analysisvalues['result'] == '':
unsatisfied = True
break
key = analysisvalues.get('keyword',
dependency.getService().getKeyword())
# Analysis result
# All result mappings must be float, or they are ignored.
try:
mapping[key] = float(analysisvalues.get('result'))
mapping['%s.%s' % (key, 'RESULT')] = float(
analysisvalues.get('result'))
mapping['%s.%s' % (key, 'LDL')] = float(
analysisvalues.get('ldl'))
mapping['%s.%s' % (key, 'UDL')] = float(
analysisvalues.get('udl'))
mapping['%s.%s' % (key, 'BELOWLDL')] = int(
analysisvalues.get('belowldl'))
mapping['%s.%s' % (key, 'ABOVEUDL')] = int(
analysisvalues.get('aboveudl'))
except:
# If not floatable, then abort!
unsatisfied = True
break
if unsatisfied:
# unsatisfied means that one or more result on which we depend
# is blank or unavailable, so we set blank result and abort.
self.results.append({
'uid': uid,
'result': '',
'formatted_result': ''
})
return None
# Add all interims to mapping
for i_uid, i_data in self.item_data.items():
for i in i_data:
# if this interim belongs to current analysis and is blank,
# return an empty result for this analysis.
if i_uid == uid and i['value'] == '':
self.results.append({
'uid': uid,
'result': '',
'formatted_result': ''
})
return None
# All interims must be float, or they are ignored.
try:
i['value'] = float(i['value'])
except:
pass
# all interims are ServiceKeyword.InterimKeyword
if i_uid in deps:
key = "%s.%s" % (deps[i_uid].getService().getKeyword(),
i['keyword'])
mapping[key] = i['value']
# this analysis' interims get extra reference
# without service keyword prefix
if uid == i_uid:
mapping[i['keyword']] = i['value']
# Grab values for hidden InterimFields for only for current calculation
# we can't allow non-floats through here till we change the eval's
# interpolation
hidden_fields = []
c_fields = calculation.getInterimFields()
s_fields = service.getInterimFields()
for field in c_fields:
if field.get('hidden', False):
hidden_fields.append(field['keyword'])
try:
mapping[field['keyword']] = float(field['value'])
except ValueError:
pass
# also grab stickier defaults from AnalysisService
for field in s_fields:
if field['keyword'] in hidden_fields:
try:
mapping[field['keyword']] = float(field['value'])
except ValueError:
pass
# convert formula to a valid python string, ready for interpolation
formula = calculation.getMinifiedFormula()
formula = formula.replace('[', '%(').replace(']', ')f')
try:
formula = eval("'%s'%%mapping" % formula, {
"__builtins__": None,
'math': math,
'context': self.context
}, {'mapping': mapping})
# calculate
result = eval(formula)
Result['result'] = result
self.current_results[uid]['result'] = result
except TypeError as e:
# non-numeric arguments in interim mapping?
alert = {
'field':
'Result',
'icon':
path + '/exclamation.png',
'msg':
"{0}: {1} ({2}) ".format(t(_("Type Error")),
html_quote(str(e.args[0])),
formula)
}
if uid in self.alerts:
self.alerts[uid].append(alert)
else:
self.alerts[uid] = [
alert,
]
except ZeroDivisionError as e:
Result['result'] = '0/0'
Result['formatted_result'] = '0/0'
self.current_results[uid]['result'] = '0/0'
self.results.append(Result)
alert = {
'field':
'Result',
'icon':
path + '/exclamation.png',
'msg':
"{0}: {1} ({2}) ".format(t(_("Division by zero")),
html_quote(str(e.args[0])),
formula)
}
if uid in self.alerts:
self.alerts[uid].append(alert)
else:
self.alerts[uid] = [
alert,
]
return None
except KeyError as e:
alert = {
'field':
'Result',
'icon':
path + '/exclamation.png',
'msg':
"{0}: {1} ({2}) ".format(t(_("Key Error")),
html_quote(str(e.args[0])),
formula)
}
if uid in self.alerts:
self.alerts[uid].append(alert)
else:
self.alerts[uid] = [
alert,
]
# format result
belowmin = False
abovemax = False
# Some analyses will not have AnalysisSpecs, eg, ReferenceAnalysis
if hasattr(analysis, 'getAnalysisSpecs'):
specs = analysis.getAnalysisSpecs()
specs = specs.getResultsRangeDict() if specs is not None else {}
specs = specs.get(analysis.getKeyword(), {})
hidemin = specs.get('hidemin', '')
hidemax = specs.get('hidemax', '')
if Result.get('result', ''):
fresult = Result['result']
try:
belowmin = hidemin and fresult < float(hidemin) or False
except ValueError:
belowmin = False
pass
try:
abovemax = hidemax and fresult > float(hidemax) or False
except ValueError:
abovemax = False
pass
if belowmin is True:
Result['formatted_result'] = '< %s' % hidemin
elif abovemax is True:
Result['formatted_result'] = '> %s' % hidemax
else:
try:
Result['formatted_result'] = format_numeric_result(
analysis, Result['result'])
except ValueError:
# non-float
Result['formatted_result'] = Result['result']
# calculate Dry Matter result
# if parent is not an AR, it's never going to be calculable
dm = hasattr(analysis.aq_parent, 'getReportDryMatter') and \
analysis.aq_parent.getReportDryMatter() and \
analysis.getService().getReportDryMatter()
if dm:
dry_service = self.context.bika_setup.getDryMatterService()
# get the UID of the DryMatter Analysis from our parent AR
dry_analysis = [
a for a in analysis.aq_parent.getAnalyses(full_objects=True)
if a.getService().UID() == dry_service.UID()
]
if dry_analysis:
dry_analysis = dry_analysis[0]
dry_uid = dry_analysis.UID()
# get the current DryMatter analysis result from the form
if dry_uid in self.current_results:
try:
dry_result = float(self.current_results[dry_uid])
except:
dm = False
else:
try:
dry_result = float(dry_analysis.getResult())
except:
dm = False
else:
dm = False
Result['dry_result'] = dm and dry_result and \
'%.2f' % ((Result['result'] / dry_result) * 100) or ''
self.results.append(Result)
# if App.config.getConfiguration().debug_mode:
# logger.info("calc.py: %s->%s %s" % (analysis.aq_parent.id,
# analysis.id,
# Result))
# LIMS-1808 Uncertainty calculation on DL
# https://jira.bikalabs.com/browse/LIMS-1808
flres = Result.get('result', None)
if flres and isnumber(flres):
flres = float(flres)
anvals = self.current_results[uid]
isldl = anvals.get('isldl', False)
isudl = anvals.get('isudl', False)
ldl = anvals.get('ldl', 0)
udl = anvals.get('udl', 0)
ldl = float(ldl) if isnumber(ldl) else 0
udl = float(udl) if isnumber(udl) else 10000000
belowldl = (isldl or flres < ldl)
aboveudl = (isudl or flres > udl)
unc = '' if (belowldl or aboveudl) else analysis.getUncertainty(
Result.get('result'))
if not (belowldl or aboveudl):
self.uncertainties.append({'uid': uid, 'uncertainty': unc})
# maybe a service who depends on us must be recalculated.
if analysis.portal_type == 'ReferenceAnalysis':
dependents = []
else:
dependents = analysis.getDependents()
if dependents:
for dependent in dependents:
dependent_uid = dependent.UID()
# ignore analyses that no longer exist.
if dependent_uid in self.ignore_uids or \
dependent_uid not in self.analyses:
continue
self.calculate(dependent_uid)
# These self.alerts are just for the json return.
# we're placing the entire form's results in kwargs.
adapters = getAdapters((analysis, ), IFieldIcons)
for name, adapter in adapters:
alerts = adapter(result=Result['result'],
form_results=self.current_results)
if alerts:
if analysis.UID() in self.alerts:
self.alerts[analysis.UID()].extend(alerts[analysis.UID()])
else:
self.alerts[analysis.UID()] = alerts[analysis.UID()]
