class Report(BrowserView):
implements(IViewView)
template = ViewPageTemplateFile(
"templates/qualitycontrol_resultspersamplepoint.pt")
# if unsuccessful we return here:
default_template = ViewPageTemplateFile("templates/qualitycontrol.pt")
def __init__(self, context, request, report=None):
super(Report, self).__init__(context, request)
self.report = report
self.selection_macros = SelectionMacrosView(self.context, self.request)
def get_analysis_spec(self, analysis):
rr = dicts_to_dict(analysis.aq_parent.getResultsRange(), 'keyword')
return rr.get(analysis.getKeyword(), None)
def ResultOutOfRange(self, analysis):
"""Template wants to know, is this analysis out of range? We scan
IResultOutOfRange adapters, and return True if any IAnalysis adapters
trigger a result. """
adapters = getAdapters((analysis, ), IResultOutOfRange)
spec = self.get_analysis_spec(analysis)
for name, adapter in adapters:
if not spec:
return False
if adapter(specification=spec):
return True
def __call__(self):
MinimumResults = self.context.bika_setup.getMinimumResults()
warning_icon = "<img " + \
"src='" + self.portal_url + "/++resource++bika.lims.images/warning.png' " + \
"height='9' width='9'/>"
error_icon = "<img " + \
"src='" + self.portal_url + "/++resource++bika.lims.images/exclamation.png' " + \
"height='9' width='9'/>"
header = _("Results per sample point")
subheader = _(
"Analysis results for per sample point and analysis service")
self.contentFilter = {'portal_type': 'Analysis',
'review_state': ['verified', 'published']}
parms = []
titles = []
val = self.selection_macros.parse_client(self.request)
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_samplepoint(self.request)
sp_uid = val
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_sampletype(self.request)
st_uid = val
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_analysisservice(self.request)
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
else:
message = _("No analysis services were selected.")
self.context.plone_utils.addPortalMessage(message, 'error')
return self.default_template()
val = self.selection_macros.parse_daterange(self.request,
'getDateSampled',
'DateSampled')
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_state(self.request,
'bika_worksheetanalysis_workflow',
'worksheetanalysis_review_state',
'Worksheet state')
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
# Query the catalog and store analysis data in a dict
analyses = {}
out_of_range_count = 0
in_shoulder_range_count = 0
analysis_count = 0
proxies = self.bika_analysis_catalog(self.contentFilter)
if not proxies:
message = _("No analyses matched your query")
self.context.plone_utils.addPortalMessage(message, 'error')
return self.default_template()
# # Compile a list of dictionaries, with all relevant analysis data
for analysis in proxies:
analysis = analysis.getObject()
result = analysis.getResult()
client = analysis.aq_parent.aq_parent
uid = analysis.UID()
keyword = analysis.getKeyword()
service_title = "%s (%s)" % (analysis.Title(), keyword)
result_in_range = self.ResultOutOfRange(analysis)
if service_title not in analyses.keys():
analyses[service_title] = []
try:
result = float(analysis.getResult())
except:
# XXX Unfloatable analysis results should be indicated
continue
analyses[service_title].append({
# The report should not mind taking 'analysis' in place of
# 'service' - the service field values are placed in analysis.
'service': analysis,
'obj': analysis,
'Request ID': analysis.aq_parent.getId(),
'Analyst': analysis.getAnalyst(),
'Result': result,
'Sampled': analysis.getDateSampled(),
'Captured': analysis.getResultCaptureDate(),
'Uncertainty': analysis.getUncertainty(),
'result_in_range': result_in_range,
'Unit': analysis.getUnit(),
'Keyword': keyword,
'icons': '',
})
analysis_count += 1
keys = analyses.keys()
keys.sort()
parms += [
{"title": _("Total analyses"), "value": analysis_count},
]
## This variable is output to the TAL
self.report_data = {
'header': header,
'subheader': subheader,
'parms': parms,
'tables': [],
'footnotes': [],
}
plotscript = """
set terminal png transparent truecolor enhanced size 700,350 font "Verdana, 8"
set title "%(title)s"
set xlabel "%(xlabel)s"
set ylabel "%(ylabel)s"
set key off
#set logscale
set timefmt "%(date_format_long)s"
set xdata time
set format x "%(date_format_short)s\\n%(time_format)s"
set xrange ["%(x_start)s":"%(x_end)s"]
set auto fix
set offsets graph 0, 0, 1, 1
set xtics border nomirror rotate by 90 font "Verdana, 5" offset 0,-3
set ytics nomirror
f(x) = mean_y
fit f(x) 'gpw_DATAFILE_gpw' u 1:3 via mean_y
stddev_y = sqrt(FIT_WSSR / (FIT_NDF + 1))
plot mean_y-stddev_y with filledcurves y1=mean_y lt 1 lc rgb "#efefef",\
mean_y+stddev_y with filledcurves y1=mean_y lt 1 lc rgb "#efefef",\
mean_y with lines lc rgb '#ffffff' lw 3,\
"gpw_DATAFILE_gpw" using 1:3 title 'data' with points pt 7 ps 1 lc rgb '#0000ee' lw 2,\
'' using 1:3 smooth unique lc rgb '#aaaaaa' lw 2,\
'' using 1:4 with lines lc rgb '#000000' lw 1,\
'' using 1:5 with lines lc rgb '#000000' lw 1"""
## Compile plots and format data for display
for service_title in keys:
# used to calculate XY axis ranges
result_values = [int(o['Result']) for o in analyses[service_title]]
result_dates = [o['Sampled'] for o in analyses[service_title]]
parms = []
plotdata = str()
range_min = ''
range_max = ''
for a in analyses[service_title]:
a['Sampled'] = a['Sampled'].strftime(self.date_format_long) if a[
'Sampled'] else ''
a['Captured'] = a['Captured'].strftime(self.date_format_long) if \
a['Captured'] else ''
R = a['Result']
U = a['Uncertainty']
a['Result'] = a['obj'].getFormattedResult()
in_range = a['result_in_range']
# result out of range
if str(in_range) == 'False':
out_of_range_count += 1
a['Result'] = "%s %s" % (a['Result'], error_icon)
# result almost out of range
if str(in_range) == '1':
in_shoulder_range_count += 1
a['Result'] = "%s %s" % (a['Result'], warning_icon)
spec = {}
if hasattr(a["obj"], 'specification') and a["obj"].specification:
spec = a["obj"].specification
plotdata += "%s\t%s\t%s\t%s\t%s\n" % (
a['Sampled'],
R,
spec.get("min", ""),
spec.get("max", ""),
U and U or 0,
)
plotdata.encode('utf-8')
unit = analyses[service_title][0]['Unit']
if MinimumResults <= len(dict([(d, d) for d in result_dates])):
_plotscript = str(plotscript) % {
'title': "",
'xlabel': t(_("Date Sampled")),
'ylabel': unit and unit or '',
'x_start': "%s" % min(result_dates).strftime(
self.date_format_long),
'x_end': "%s" % max(result_dates).strftime(
self.date_format_long),
'date_format_long': self.date_format_long,
'date_format_short': self.date_format_short,
'time_format': self.time_format,
}
plot_png = plot(str(plotdata),
plotscript=str(_plotscript),
usefifo=False)
# Temporary PNG data file
fh, data_fn = tempfile.mkstemp(suffix='.png')
os.write(fh, plot_png)
plot_url = data_fn
self.request['to_remove'].append(data_fn)
plot_url = data_fn
else:
plot_url = ""
table = {
'title': "%s: %s" % (
t(_("Analysis Service")),
service_title),
'parms': parms,
'columns': ['Request ID',
'Analyst',
'Result',
'Sampled',
'Captured'],
'data': analyses[service_title],
'plot_url': plot_url,
}
self.report_data['tables'].append(table)
translate = self.context.translate
## footnotes
if out_of_range_count:
msgid = _("Analyses out of range")
self.report_data['footnotes'].append(
"%s %s" % (error_icon, t(msgid)))
if in_shoulder_range_count:
msgid = _("Analyses in error shoulder range")
self.report_data['footnotes'].append(
"%s %s" % (warning_icon, t(msgid)))
self.report_data['parms'].append(
{"title": _("Analyses out of range"),
"value": out_of_range_count})
self.report_data['parms'].append(
{"title": _("Analyses in error shoulder range"),
"value": in_shoulder_range_count})
title = t(header)
if titles:
title += " (%s)" % " ".join(titles)
return {
'report_title': title,
'report_data': self.template(),
}
class Report(BrowserView):
implements(IViewView)
template = ViewPageTemplateFile(
"templates/qualitycontrol_resultspersamplepoint.pt")
# if unsuccessful we return here:
default_template = ViewPageTemplateFile("templates/qualitycontrol.pt")
def __init__(self, context, request, report=None):
super(Report, self).__init__(context, request)
self.report = report
self.selection_macros = SelectionMacrosView(self.context, self.request)
def get_analysis_spec(self, analysis):
rr = dicts_to_dict(analysis.aq_parent.getResultsRange(), 'keyword')
return rr.get(analysis.getKeyword(), None)
def ResultOutOfRange(self, analysis):
""" Template wants to know, is this analysis out of range?
We scan IResultOutOfRange adapters, and return True if any IAnalysis
adapters trigger a result.
"""
adapters = getAdapters((analysis, ), IResultOutOfRange)
spec = self.get_analysis_spec(analysis)
for name, adapter in adapters:
if not spec:
return False
if adapter(specification=spec):
return True
def __call__(self):
MinimumResults = self.context.bika_setup.getMinimumResults()
warning_icon = "<img " + \
"src='" + self.portal_url + "/++resource++bika.lims.images/warning.png' " + \
"height='9' width='9'/>"
error_icon = "<img " + \
"src='" + self.portal_url + "/++resource++bika.lims.images/exclamation.png' " + \
"height='9' width='9'/>"
header = _("Results per sample point")
subheader = _(
"Analysis results for per sample point and analysis service")
self.contentFilter = {'portal_type': 'Analysis',
'review_state': ['verified', 'published']}
parms = []
titles = []
val = self.selection_macros.parse_client(self.request)
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_samplepoint(self.request)
sp_uid = val
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_sampletype(self.request)
st_uid = val
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_analysisservice(self.request)
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
else:
message = _("No analysis services were selected.")
self.context.plone_utils.addPortalMessage(message, 'error')
return self.default_template()
val = self.selection_macros.parse_daterange(self.request,
'getDateSampled',
'DateSampled')
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_state(self.request,
'bika_worksheetanalysis_workflow',
'worksheetanalysis_review_state',
'Worksheet state')
if val:
self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
# Query the catalog and store analysis data in a dict
analyses = {}
out_of_range_count = 0
in_shoulder_range_count = 0
analysis_count = 0
proxies = self.bika_analysis_catalog(self.contentFilter)
if not proxies:
message = _("No analyses matched your query")
self.context.plone_utils.addPortalMessage(message, 'error')
return self.default_template()
# # Compile a list of dictionaries, with all relevant analysis data
for analysis in proxies:
analysis = analysis.getObject()
result = analysis.getResult()
client = analysis.aq_parent.aq_parent
uid = analysis.UID()
service = analysis.getService()
keyword = service.getKeyword()
service_title = "%s (%s)" % (service.Title(), keyword)
result_in_range = self.ResultOutOfRange(analysis)
if service_title not in analyses.keys():
analyses[service_title] = []
try:
result = float(analysis.getResult())
except:
# XXX Unfloatable analysis results should be indicated
continue
analyses[service_title].append({
'service': service,
'obj': analysis,
'Request ID': analysis.aq_parent.getId(),
'Analyst': analysis.getAnalyst(),
'Result': result,
'Sampled': analysis.getDateSampled(),
'Captured': analysis.getResultCaptureDate(),
'Uncertainty': analysis.getUncertainty(),
'result_in_range': result_in_range,
'Unit': service.getUnit(),
'Keyword': keyword,
'icons': '',
})
analysis_count += 1
keys = analyses.keys()
keys.sort()
parms += [
{"title": _("Total analyses"), "value": analysis_count},
]
## This variable is output to the TAL
self.report_data = {
'header': header,
'subheader': subheader,
'parms': parms,
'tables': [],
'footnotes': [],
}
plotscript = """
set terminal png transparent truecolor enhanced size 700,350 font "Verdana, 8"
set title "%(title)s"
set xlabel "%(xlabel)s"
set ylabel "%(ylabel)s"
set key off
#set logscale
set timefmt "%(date_format_long)s"
set xdata time
set format x "%(date_format_short)s\\n%(time_format)s"
set xrange ["%(x_start)s":"%(x_end)s"]
set auto fix
set offsets graph 0, 0, 1, 1
set xtics border nomirror rotate by 90 font "Verdana, 5" offset 0,-3
set ytics nomirror
f(x) = mean_y
fit f(x) 'gpw_DATAFILE_gpw' u 1:3 via mean_y
stddev_y = sqrt(FIT_WSSR / (FIT_NDF + 1))
plot mean_y-stddev_y with filledcurves y1=mean_y lt 1 lc rgb "#efefef",\
mean_y+stddev_y with filledcurves y1=mean_y lt 1 lc rgb "#efefef",\
mean_y with lines lc rgb '#ffffff' lw 3,\
"gpw_DATAFILE_gpw" using 1:3 title 'data' with points pt 7 ps 1 lc rgb '#0000ee' lw 2,\
'' using 1:3 smooth unique lc rgb '#aaaaaa' lw 2,\
'' using 1:4 with lines lc rgb '#000000' lw 1,\
'' using 1:5 with lines lc rgb '#000000' lw 1"""
## Compile plots and format data for display
for service_title in keys:
# used to calculate XY axis ranges
result_values = [int(o['Result']) for o in analyses[service_title]]
result_dates = [o['Sampled'] for o in analyses[service_title]]
parms = []
plotdata = str()
range_min = ''
range_max = ''
for a in analyses[service_title]:
a['Sampled'] = a['Sampled'].strftime(self.date_format_long) if a[
'Sampled'] else ''
a['Captured'] = a['Captured'].strftime(self.date_format_long) if \
a['Captured'] else ''
R = a['Result']
U = a['Uncertainty']
a['Result'] = a['obj'].getFormattedResult()
in_range = a['result_in_range']
# result out of range
if str(in_range[0]) == 'False':
out_of_range_count += 1
a['Result'] = "%s %s" % (a['Result'], error_icon)
# result almost out of range
if str(in_range[0]) == '1':
in_shoulder_range_count += 1
a['Result'] = "%s %s" % (a['Result'], warning_icon)
spec = {}
if hasattr(a["obj"], 'specification') and a["obj"].specification:
spec = a["obj"].specification
plotdata += "%s\t%s\t%s\t%s\t%s\n" % (
a['Sampled'],
R,
spec.get("min", ""),
spec.get("max", ""),
U and U or 0,
)
plotdata.encode('utf-8')
unit = analyses[service_title][0]['Unit']
if MinimumResults <= len(dict([(d, d) for d in result_dates])):
_plotscript = str(plotscript) % {
'title': "",
'xlabel': t(_("Date Sampled")),
'ylabel': unit and unit or '',
'x_start': "%s" % min(result_dates).strftime(
self.date_format_long),
'x_end': "%s" % max(result_dates).strftime(
self.date_format_long),
'date_format_long': self.date_format_long,
'date_format_short': self.date_format_short,
'time_format': self.time_format,
}
plot_png = plot(str(plotdata),
plotscript=str(_plotscript),
usefifo=False)
# Temporary PNG data file
fh, data_fn = tempfile.mkstemp(suffix='.png')
os.write(fh, plot_png)
plot_url = data_fn
self.request['to_remove'].append(data_fn)
plot_url = data_fn
else:
plot_url = ""
table = {
'title': "%s: %s" % (
t(_("Analysis Service")),
service_title),
'parms': parms,
'columns': ['Request ID',
'Analyst',
'Result',
'Sampled',
'Captured'],
'data': analyses[service_title],
'plot_url': plot_url,
}
self.report_data['tables'].append(table)
translate = self.context.translate
## footnotes
if out_of_range_count:
msgid = _("Analyses out of range")
self.report_data['footnotes'].append(
"%s %s" % (error_icon, t(msgid)))
if in_shoulder_range_count:
msgid = _("Analyses in error shoulder range")
self.report_data['footnotes'].append(
"%s %s" % (warning_icon, t(msgid)))
self.report_data['parms'].append(
{"title": _("Analyses out of range"),
"value": out_of_range_count})
self.report_data['parms'].append(
{"title": _("Analyses in error shoulder range"),
"value": in_shoulder_range_count})
title = t(header)
if titles:
title += " (%s)" % " ".join(titles)
return {
'report_title': title,
'report_data': self.template(),
}
class Report(BrowserView):
implements(IViewView)
template = ViewPageTemplateFile(
"templates/qualitycontrol_resultspersamplepoint.pt")
# if unsuccessful we return here:
default_template = ViewPageTemplateFile("templates/qualitycontrol.pt")
def __init__(self, context, request, report=None):
super(Report, self).__init__(context, request)
self.report = report
self.selection_macros = SelectionMacrosView(self.context, self.request)
def __call__(self):
MinimumResults = self.context.bika_setup.getMinimumResults()
warning_icon = "<img " +\
"src='"+self.portal_url+"/++resource++bika.lims.images/warning.png' " +\
"height='9' width='9'/>"
error_icon = "<img " +\
"src='"+self.portal_url+"/++resource++bika.lims.images/exclamation.png' " +\
"height='9' width='9'/>"
header = _("Results per sample point")
subheader = _(
"Analysis results for per sample point and analysis service")
self.contentFilter = {
'portal_type': 'Analysis',
'review_state': ['verified', 'published'],
'sort_on': "getDateSampled"
}
spec = self.request.form.get('spec', 'lab')
spec_title = (spec == 'lab') and _("Lab") or _("Client")
parms = []
titles = []
val = self.selection_macros.parse_client(self.request)
if val:
self.contentFilter[val['contentFilter']
[0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_samplepoint(self.request)
sp_uid = val
if val:
self.contentFilter[val['contentFilter']
[0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_sampletype(self.request)
st_uid = val
if val:
self.contentFilter[val['contentFilter']
[0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_analysisservice(self.request)
if val:
self.contentFilter[val['contentFilter']
[0]] = val['contentFilter'][1]
parms.append(val['parms'])
else:
message = _("No analysis services were selected.")
self.context.plone_utils.addPortalMessage(message, 'error')
return self.default_template()
val = self.selection_macros.parse_daterange(self.request,
'getDateSampled',
'DateSampled')
if val:
self.contentFilter[val['contentFilter']
[0]] = val['contentFilter'][1]
parms.append(val['parms'])
titles.append(val['titles'])
val = self.selection_macros.parse_state(
self.request, 'bika_worksheetanalysis_workflow',
'worksheetanalysis_review_state', 'Worksheet state')
if val:
self.contentFilter[val['contentFilter']
[0]] = val['contentFilter'][1]
parms.append(val['parms'])
# Query the catalog and store analysis data in a dict
analyses = {}
out_of_range_count = 0
in_shoulder_range_count = 0
analysis_count = 0
proxies = self.bika_analysis_catalog(self.contentFilter)
if not proxies:
message = _("No analyses matched your query")
self.context.plone_utils.addPortalMessage(message, 'error')
return self.default_template()
cached_specs = {} # keyed by parent_folder
def lookup_spec(analysis):
# If an analysis is OUT OF RANGE, the failed spec values are passed
# back from the result_in_range function. But if the analysis resuit
# is IN RANGE, we need to look it up.
service = analysis['service']
keyword = service['Keyword']
analysis = analysis['obj']
if spec == "client":
parent = analysis.aq_parent.aq_parent
else:
parent = self.context.bika_setup.bika_analysisspecs
if not parent.UID() in cached_specs:
proxies = self.bika_setup_catalog(
portal_type='AnalysisSpec',
getSampleTypeUID=st_uid,
path={
"query": "/".join(parent.getPhysicalPath()),
"level": 0
})
if proxies:
spec_obj = proxies[0].getObject()
this_spec = spec_obj.getResultsRangeDict()
else:
this_spec = {'min': None, 'max': None}
cached_specs[parent.UID()] = this_spec
else:
this_spec = cached_specs[parent.UID()]
return this_spec
## Compile a list of dictionaries, with all relevant analysis data
for analysis in proxies:
analysis = analysis.getObject()
client = analysis.aq_parent.aq_parent
uid = analysis.UID()
service = analysis.getService()
keyword = service.getKeyword()
service_title = "%s (%s)" % (service.Title(), service.getKeyword())
result_in_range = analysis.result_in_range(specification=spec)
try:
precision = str(service.getPrecision())
except:
precision = "2"
if service_title not in analyses.keys():
analyses[service_title] = []
try:
result = float(analysis.getResult())
except:
# XXX Unfloatable analysis results should be indicated
continue
analyses[service_title].append({
'service':
service,
'obj':
analysis,
'Request ID':
analysis.aq_parent.getId(),
'Analyst':
analysis.getAnalyst(),
'Result':
result,
'precision':
precision,
'Sampled':
analysis.getDateSampled(),
'Captured':
analysis.getResultCaptureDate(),
'Uncertainty':
analysis.getUncertainty(),
'result_in_range':
result_in_range,
'Unit':
service.getUnit(),
'Keyword':
keyword,
'icons':
'',
})
analysis_count += 1
keys = analyses.keys()
keys.sort()
parms += [
{
"title": _("Total analyses"),
"value": analysis_count
},
{
"title": _("Analysis specification"),
"value": spec_title
},
]
## This variable is output to the TAL
self.report_data = {
'header': header,
'subheader': subheader,
'parms': parms,
'tables': [],
'footnotes': [],
}
plotscript = """
set terminal png transparent truecolor enhanced size 700,350 font "Verdana, 8"
set title "%(title)s"
set xlabel "%(xlabel)s"
set ylabel "%(ylabel)s"
set key off
#set logscale
set timefmt "%(date_format_long)s"
set xdata time
set format x "%(date_format_short)s\\n%(time_format)s"
set xrange ["%(x_start)s":"%(x_end)s"]
set auto fix
set offsets graph 0, 0, 1, 1
set xtics border nomirror rotate by 90 font "Verdana, 5" offset 0,-3
set ytics nomirror
f(x) = mean_y
fit f(x) 'gpw_DATAFILE_gpw' u 1:3 via mean_y
stddev_y = sqrt(FIT_WSSR / (FIT_NDF + 1))
plot mean_y-stddev_y with filledcurves y1=mean_y lt 1 lc rgb "#efefef",\
mean_y+stddev_y with filledcurves y1=mean_y lt 1 lc rgb "#efefef",\
mean_y with lines lc rgb '#ffffff' lw 3,\
"gpw_DATAFILE_gpw" using 1:3 title 'data' with points pt 7 ps 1 lc rgb '#0000ee' lw 2,\
'' using 1:3 smooth unique lc rgb '#aaaaaa' lw 2,\
'' using 1:4 with lines lc rgb '#000000' lw 1,\
'' using 1:5 with lines lc rgb '#000000' lw 1"""
## Compile plots and format data for display
for service_title in keys:
# used to calculate XY axis ranges
result_values = [int(o['Result']) for o in analyses[service_title]]
result_dates = [o['Sampled'] for o in analyses[service_title]]
parms = []
plotdata = str()
range_min = ''
range_max = ''
for a in analyses[service_title]:
a['Sampled'] = a['Sampled'].strftime(self.date_format_long)
a['Captured'] = a['Captured'].strftime(self.date_format_long)
R = a['Result']
U = a['Uncertainty']
a['Result'] = str("%." + precision + "f") % a['Result']
in_range = a['result_in_range']
# in-range: lookup spec, if possible
if in_range[1] == None:
this_spec_results = lookup_spec(a)
if this_spec_results and a['Keyword'] in this_spec_results:
this_spec = this_spec_results[a['Keyword']]
in_range[1] == this_spec
# If no specs are supplied, fake them
# and do not print specification values or errors
a['range_min'] = in_range[1] and in_range[1]['min'] or ''
a['range_max'] = in_range[1] and in_range[1]['max'] or ''
if a['range_min'] and a['range_max']:
range_min = a['range_min']
range_max = a['range_max']
# result out of range
if str(in_range[0]) == 'False':
out_of_range_count += 1
a['Result'] = "%s %s" % (a['Result'], error_icon)
# result almost out of range
if str(in_range[0]) == '1':
in_shoulder_range_count += 1
a['Result'] = "%s %s" % (a['Result'], warning_icon)
else:
a['range_min'] = min(result_values)
a['range_max'] = max(result_values)
plotdata += "%s\t%s\t%s\t%s\t%s\n" % (
a['Sampled'],
R,
range_min,
range_max,
U and U or 0,
)
plotdata.encode('utf-8')
if range_min and range_max:
spec_str = "%s: %s, %s: %s" % (
self.context.translate(_("Range min")),
range_min,
self.context.translate(_("Range max")),
range_max,
)
parms.append({
'title': _('Specification'),
'value': spec_str,
})
unit = analyses[service_title][0]['Unit']
if MinimumResults <= len(dict([(d, d) for d in result_dates])):
_plotscript = str(plotscript) % {
'title':
"",
'xlabel':
self.context.translate(_("Date Sampled")),
'ylabel':
unit and unit or '',
'x_start':
"%s" % min(result_dates).strftime(self.date_format_long),
'x_end':
"%s" % max(result_dates).strftime(self.date_format_long),
'date_format_long':
self.date_format_long,
'date_format_short':
self.date_format_short,
'time_format':
self.time_format,
}
plot_png = plot(str(plotdata),
plotscript=str(_plotscript),
usefifo=False)
# Temporary PNG data file
fh, data_fn = tempfile.mkstemp(suffix='.png')
os.write(fh, plot_png)
plot_url = data_fn
self.request['to_remove'].append(data_fn)
plot_url = data_fn
else:
plot_url = ""
table = {
'title':
"%s: %s" %
(self.context.translate(_("Analysis Service")), service_title),
'parms':
parms,
'columns':
['Request ID', 'Analyst', 'Result', 'Sampled', 'Captured'],
'data':
analyses[service_title],
'plot_url':
plot_url,
}
self.report_data['tables'].append(table)
## footnotes
if out_of_range_count:
msgid = _("Analyses out of range")
translate = self.context.translate
self.report_data['footnotes'].append(
"%s %s" % (error_icon, translate(msgid)))
if in_shoulder_range_count:
msgid = _("Analyses in error shoulder range")
self.report_data['footnotes'].append(
"%s %s" % (warning_icon, self.context.translate(msgid)))
self.report_data['parms'].append({
"title": _("Analyses out of range"),
"value": out_of_range_count
})
self.report_data['parms'].append({
"title":
_("Analyses in error shoulder range"),
"value":
in_shoulder_range_count
})
title = self.context.translate(header)
if titles:
title += " (%s)" % " ".join(titles)
return {
'report_title': title,
'report_data': self.template(),
}
class Report(BrowserView):
implements(IViewView)
template = ViewPageTemplateFile("templates/qualitycontrol_resultspersamplepoint.pt")
# if unsuccessful we return here:
default_template = ViewPageTemplateFile("templates/qualitycontrol.pt")
def __init__(self, context, request, report=None):
super(Report, self).__init__(context, request)
self.report = report
self.selection_macros = SelectionMacrosView(self.context, self.request)
def __call__(self):
MinimumResults = self.context.bika_setup.getMinimumResults()
warning_icon = (
"<img "
+ "src='"
+ self.portal_url
+ "/++resource++bika.lims.images/warning.png' "
+ "height='9' width='9'/>"
)
error_icon = (
"<img "
+ "src='"
+ self.portal_url
+ "/++resource++bika.lims.images/exclamation.png' "
+ "height='9' width='9'/>"
)
header = _("Results per sample point")
subheader = _("Analysis results for per sample point and analysis service")
self.contentFilter = {
"portal_type": "Analysis",
"review_state": ["verified", "published"],
"sort_on": "getDateSampled",
}
spec = self.request.form.get("spec", "lab")
spec_title = (spec == "lab") and _("Lab") or _("Client")
parms = []
titles = []
val = self.selection_macros.parse_client(self.request)
if val:
self.contentFilter[val["contentFilter"][0]] = val["contentFilter"][1]
parms.append(val["parms"])
titles.append(val["titles"])
val = self.selection_macros.parse_samplepoint(self.request)
sp_uid = val
if val:
self.contentFilter[val["contentFilter"][0]] = val["contentFilter"][1]
parms.append(val["parms"])
titles.append(val["titles"])
val = self.selection_macros.parse_sampletype(self.request)
st_uid = val
if val:
self.contentFilter[val["contentFilter"][0]] = val["contentFilter"][1]
parms.append(val["parms"])
titles.append(val["titles"])
val = self.selection_macros.parse_analysisservice(self.request)
if val:
self.contentFilter[val["contentFilter"][0]] = val["contentFilter"][1]
parms.append(val["parms"])
else:
message = _("No analysis services were selected.")
self.context.plone_utils.addPortalMessage(message, "error")
return self.default_template()
val = self.selection_macros.parse_daterange(self.request, "getDateSampled", "DateSampled")
if val:
self.contentFilter[val["contentFilter"][0]] = val["contentFilter"][1]
parms.append(val["parms"])
titles.append(val["titles"])
val = self.selection_macros.parse_state(
self.request, "bika_worksheetanalysis_workflow", "worksheetanalysis_review_state", "Worksheet state"
)
if val:
self.contentFilter[val["contentFilter"][0]] = val["contentFilter"][1]
parms.append(val["parms"])
# Query the catalog and store analysis data in a dict
analyses = {}
out_of_range_count = 0
in_shoulder_range_count = 0
analysis_count = 0
proxies = self.bika_analysis_catalog(self.contentFilter)
if not proxies:
message = _("No analyses matched your query")
self.context.plone_utils.addPortalMessage(message, "error")
return self.default_template()
cached_specs = {} # keyed by parent_folder
def lookup_spec(analysis):
# If an analysis is OUT OF RANGE, the failed spec values are passed
# back from the result_in_range function. But if the analysis resuit
# is IN RANGE, we need to look it up.
service = analysis["service"]
keyword = service["Keyword"]
analysis = analysis["obj"]
if spec == "client":
parent = analysis.aq_parent.aq_parent
else:
parent = self.context.bika_setup.bika_analysisspecs
if not parent.UID() in cached_specs:
proxies = self.bika_setup_catalog(
portal_type="AnalysisSpec",
getSampleTypeUID=st_uid,
path={"query": "/".join(parent.getPhysicalPath()), "level": 0},
)
if proxies:
spec_obj = proxies[0].getObject()
this_spec = spec_obj.getResultsRangeDict()
else:
this_spec = {"min": None, "max": None}
cached_specs[parent.UID()] = this_spec
else:
this_spec = cached_specs[parent.UID()]
return this_spec
## Compile a list of dictionaries, with all relevant analysis data
for analysis in proxies:
analysis = analysis.getObject()
client = analysis.aq_parent.aq_parent
uid = analysis.UID()
service = analysis.getService()
keyword = service.getKeyword()
service_title = "%s (%s)" % (service.Title(), service.getKeyword())
result_in_range = analysis.result_in_range(specification=spec)
try:
precision = str(service.getPrecision())
except:
precision = "2"
if service_title not in analyses.keys():
analyses[service_title] = []
try:
result = float(analysis.getResult())
except:
# XXX Unfloatable analysis results should be indicated
continue
analyses[service_title].append(
{
"service": service,
"obj": analysis,
"Request ID": analysis.aq_parent.getId(),
"Analyst": analysis.getAnalyst(),
"Result": result,
"precision": precision,
"Sampled": analysis.getDateSampled(),
"Captured": analysis.getResultCaptureDate(),
"Uncertainty": analysis.getUncertainty(),
"result_in_range": result_in_range,
"Unit": service.getUnit(),
"Keyword": keyword,
"icons": "",
}
)
analysis_count += 1
keys = analyses.keys()
keys.sort()
parms += [
{"title": _("Total analyses"), "value": analysis_count},
{"title": _("Analysis specification"), "value": spec_title},
]
## This variable is output to the TAL
self.report_data = {"header": header, "subheader": subheader, "parms": parms, "tables": [], "footnotes": []}
plotscript = """
set terminal png transparent truecolor enhanced size 700,350 font "Verdana, 8"
set title "%(title)s"
set xlabel "%(xlabel)s"
set ylabel "%(ylabel)s"
set key off
#set logscale
set timefmt "%(date_format_long)s"
set xdata time
set format x "%(date_format_short)s\\n%(time_format)s"
set xrange ["%(x_start)s":"%(x_end)s"]
set auto fix
set offsets graph 0, 0, 1, 1
set xtics border nomirror rotate by 90 font "Verdana, 5" offset 0,-3
set ytics nomirror
f(x) = mean_y
fit f(x) 'gpw_DATAFILE_gpw' u 1:3 via mean_y
stddev_y = sqrt(FIT_WSSR / (FIT_NDF + 1))
plot mean_y-stddev_y with filledcurves y1=mean_y lt 1 lc rgb "#efefef",\
mean_y+stddev_y with filledcurves y1=mean_y lt 1 lc rgb "#efefef",\
mean_y with lines lc rgb '#ffffff' lw 3,\
"gpw_DATAFILE_gpw" using 1:3 title 'data' with points pt 7 ps 1 lc rgb '#0000ee' lw 2,\
'' using 1:3 smooth unique lc rgb '#aaaaaa' lw 2,\
'' using 1:4 with lines lc rgb '#000000' lw 1,\
'' using 1:5 with lines lc rgb '#000000' lw 1"""
## Compile plots and format data for display
for service_title in keys:
# used to calculate XY axis ranges
result_values = [int(o["Result"]) for o in analyses[service_title]]
result_dates = [o["Sampled"] for o in analyses[service_title]]
parms = []
plotdata = str()
range_min = ""
range_max = ""
for a in analyses[service_title]:
a["Sampled"] = a["Sampled"].strftime(self.date_format_long)
a["Captured"] = a["Captured"].strftime(self.date_format_long)
R = a["Result"]
U = a["Uncertainty"]
a["Result"] = str("%." + precision + "f") % a["Result"]
in_range = a["result_in_range"]
# in-range: lookup spec, if possible
if in_range[1] == None:
this_spec_results = lookup_spec(a)
if this_spec_results and a["Keyword"] in this_spec_results:
this_spec = this_spec_results[a["Keyword"]]
in_range[1] == this_spec
# If no specs are supplied, fake them
# and do not print specification values or errors
a["range_min"] = in_range[1] and in_range[1]["min"] or ""
a["range_max"] = in_range[1] and in_range[1]["max"] or ""
if a["range_min"] and a["range_max"]:
range_min = a["range_min"]
range_max = a["range_max"]
# result out of range
if str(in_range[0]) == "False":
out_of_range_count += 1
a["Result"] = "%s %s" % (a["Result"], error_icon)
# result almost out of range
if str(in_range[0]) == "1":
in_shoulder_range_count += 1
a["Result"] = "%s %s" % (a["Result"], warning_icon)
else:
a["range_min"] = min(result_values)
a["range_max"] = max(result_values)
plotdata += "%s\t%s\t%s\t%s\t%s\n" % (a["Sampled"], R, range_min, range_max, U and U or 0)
plotdata.encode("utf-8")
if range_min and range_max:
spec_str = "%s: %s, %s: %s" % (
self.context.translate(_("Range min")),
range_min,
self.context.translate(_("Range max")),
range_max,
)
parms.append({"title": _("Specification"), "value": spec_str})
unit = analyses[service_title][0]["Unit"]
if MinimumResults <= len(dict([(d, d) for d in result_dates])):
_plotscript = str(plotscript) % {
"title": "",
"xlabel": self.context.translate(_("Date Sampled")),
"ylabel": unit and unit or "",
"x_start": "%s" % min(result_dates).strftime(self.date_format_long),
"x_end": "%s" % max(result_dates).strftime(self.date_format_long),
"date_format_long": self.date_format_long,
"date_format_short": self.date_format_short,
"time_format": self.time_format,
}
plot_png = plot(str(plotdata), plotscript=str(_plotscript), usefifo=False)
# Temporary PNG data file
fh, data_fn = tempfile.mkstemp(suffix=".png")
os.write(fh, plot_png)
plot_url = data_fn
self.request["to_remove"].append(data_fn)
plot_url = data_fn
else:
plot_url = ""
table = {
"title": "%s: %s" % (self.context.translate(_("Analysis Service")), service_title),
"parms": parms,
"columns": ["Request ID", "Analyst", "Result", "Sampled", "Captured"],
"data": analyses[service_title],
"plot_url": plot_url,
}
self.report_data["tables"].append(table)
## footnotes
if out_of_range_count:
msgid = _("Analyses out of range")
translate = self.context.translate
self.report_data["footnotes"].append("%s %s" % (error_icon, translate(msgid)))
if in_shoulder_range_count:
msgid = _("Analyses in error shoulder range")
self.report_data["footnotes"].append("%s %s" % (warning_icon, self.context.translate(msgid)))
self.report_data["parms"].append({"title": _("Analyses out of range"), "value": out_of_range_count})
self.report_data["parms"].append(
{"title": _("Analyses in error shoulder range"), "value": in_shoulder_range_count}
)
title = self.context.translate(header)
if titles:
title += " (%s)" % " ".join(titles)
return {"report_title": title, "report_data": self.template()}
class Report(BrowserView):
implements(IViewView)
template = ViewPageTemplateFile("templates/report_out.pt")
def __init__(self, context, request, report=None):
BrowserView.__init__(self, context, request)
self.report = report
self.selection_macros = SelectionMacrosView(self.context, self.request)
self.uids_map = dict()
def __call__(self):
# get all the data into datalines
catalog = api.get_tool(CATALOG_ANALYSIS_LISTING, self.context)
self.report_content = {}
parms = []
headings = {}
headings['header'] = ""
count_all = 0
query = {}
# Getting the query filters
val = self.selection_macros.parse_client(self.request)
if val:
query[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
val = self.selection_macros.parse_sampletype(self.request)
if val:
query[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
val = self.selection_macros.parse_analysisservice(self.request)
if val:
query[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
val = self.selection_macros.parse_daterange(self.request, 'created',
'Created')
if val:
query[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
val = self.selection_macros.parse_daterange(self.request,
'getDatePublished',
'Date Published')
if val:
query[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
val = self.selection_macros.parse_daterange(self.request,
'getDateReceived',
'Date Received')
if val:
query[val['contentFilter'][0]] = val['contentFilter'][1]
parms.append(val['parms'])
formats = {
'columns':
25,
'col_heads': [
_('Lab Number'),
_('Testing Lab'),
_('First Name'),
_('Middle Name'),
_('Last Name'),
_('Gender'),
_('Age'),
_('Age Type'),
_('Town'),
_('Reporting County'),
_('Reporting District'),
_('Reporting Facility'),
_('Date Onset'),
_('Date of Reporting'),
_('Was Specimen collected? '),
_('Date specimen collected'),
_('Type of Specimen'),
_('Date Specimen Sent to Lab'),
_('Date Specimen Received in Lab'),
_('Date Published'),
_('Condition of Specimen'),
_('Comment'),
_('Test Result')
],
}
# and now lets do the actual report lines
datalines = []
laboratory = self.context.bika_setup.laboratory
# Get analyses brains
logger.info("Searching Analyses: {}".format(repr(query)))
brains = catalog(query)
# Collect all AR uids and Patient UIDs so only one query to get all
# them will be needed
ar_uids = list(set([brain.getParentUID for brain in brains]))
ar_uids = filter(None, ar_uids)
self.map_uids_to_brains(ar_uids)
logger.info("Filling datalines with {} Analyses".format(len(brains)))
for analysis in brains:
# We get the AR and the patient of the
# analysis here to avoid having to get them
# inside each of the following method calls.
# If they are not found its value will be None
ar_brain = self.get_ar_brain(analysis)
patient_brain = self.get_patient_brain(analysis)
dataline = []
# Lab Number
dataitem = self.get_lab_number(analysis)
dataline.append(dataitem)
# Testing Lab
dataline.append({'value': laboratory.Title()})
#First Name
dataitem = self.get_firstname(patient_brain)
dataline.append(dataitem)
#Middle Name
dataitem = self.get_middlename(patient_brain)
dataline.append(dataitem)
#Last Name
dataitem = self.get_lastname(patient_brain)
dataline.append(dataitem)
#Gender
dataitem = self.get_gender(patient_brain)
dataline.append(dataitem)
#Age
dataitem = self.get_age(patient_brain)
dataline.append(dataitem)
#AgeType
dataitem = self.get_agetype(patient_brain)
dataline.append(dataitem)
# Facility Province
dataitem = self.get_facility_province(ar_brain)
dataline.append(dataitem)
# Facility District
dataitem = self.get_facility_district(ar_brain)
dataline.append(dataitem)
# Facility
dataitem = self.get_client_name(ar_brain)
dataline.append(dataitem)
# Date of Collection - Onset
dataitem = self.get_date_of_collection(ar_brain)
dataline.append(dataitem)
# Date Reporting
dataitem = self.get_date_of_dispatch(ar_brain)
dataline.append(dataitem)
# Specimen Collected
dataitem = self.get_date_of_collection(ar_brain)
dataline.append(dataitem)
# Date of Collection - Onset
dataitem = self.get_date_of_collection(ar_brain)
dataline.append(dataitem)
# Specimen Type
dataitem = self.get_specimentype(ar_brain)
dataline.append(dataitem)
# Date of Dispatch
dataitem = self.get_date_of_dispatch(ar_brain)
dataline.append(dataitem)
# Date of Receiving
dataitem = self.get_date_of_receiving(ar_brain)
dataline.append(dataitem)
# Date of Publication
dataitem = self.get_date_published(analysis)
dataline.append(dataitem)
# Condition of Specimen
#dataitem = self.get_date_published(analysis)
#dataline.append(dataitem)
# Comment
#dataitem = self.get_date_published(analysis)
##dataline.append(dataitem)
# Sex
#dataitem = self.get_patient_sex(patient_brain)
#dataline.append(dataitem)
# Date Of Birth
#dataitem = self.get_patient_dob(patient_brain)
#dataline.append(dataitem)
# Date of Testing
#dataitem = self.get_date_of_testing(analysis)
#dataline.append(dataitem)
#Test Result
dataitem = self.get_result(analysis)
dataline.append(dataitem)
count_all += 1
datalines.append(dataline)
logger.info("Generating output")
# footer data
footlines = []
footline = []
footitem = {'value': _('Total'), 'class': 'total_label'}
footline.append(footitem)
footitem = {'value': count_all}
footline.append(footitem)
footlines.append(footline)
self.report_content = {
'headings': headings,
'parms': parms,
'formats': formats,
'datalines': datalines,
'footings': footlines
}
if self.request.get('output_format', '') == 'CSV':
fieldnames = formats.get('col_heads')
output = StringIO.StringIO()
dw = csv.DictWriter(output,
extrasaction='ignore',
fieldnames=fieldnames)
dw.writerow(dict((fn, fn) for fn in fieldnames))
for row in datalines:
dict_row = {}
row_idx = 0
for column in fieldnames:
dict_row[column] = row[row_idx]['value']
row_idx += 1
dw.writerow(dict_row)
report_data = output.getvalue()
output.close()
date = datetime.datetime.now().strftime("%Y%m%d%H%M")
setheader = self.request.RESPONSE.setHeader
setheader('Content-Type', 'text/csv')
setheader(
"Content-Disposition",
"attachment;filename=\"analysisresultbyclient_%s.csv"
"\"" % date)
self.request.RESPONSE.write(report_data)
else:
return {
'report_title': t(headings['header']),
'report_data': self.template()
}
@viewcache.memoize
def get_brain(self, uid, catalog):
brain = self.uids_map.get(uid, None)
if brain:
return brain
logger.warning("UID not found in brains map: {}".format(uid))
cat = api.get_tool(catalog)
brain = cat(UID=uid)
if not brain or len(brain) == 0:
return None
return brain[0]
@viewcache.memoize
def get_object(self, brain_or_object_or_uid):
"""Get the full content object. Returns None if the param passed in is
not a valid, not a valid object or not found
:param brain_or_object_or_uid: UID/Catalog brain/content object
:returns: content object
"""
if api.is_uid(brain_or_object_or_uid):
brain = self.uids_map.get(brain_or_object_or_uid, None)
if brain:
return self.get_object(brain)
return api.get_object_by_uid(brain_or_object_or_uid, default=None)
if api.is_object(brain_or_object_or_uid):
return api.get_object(brain_or_object_or_uid)
return None
def get_lab_number(self, analysis):
try:
"""Client Sample ID"""
return {'value': self.context.bika_setup.laboratory.getTaxNumber()}
except:
return {'value': 'MPH'}
def get_firstname(self, patient):
if not patient:
return {'value': ''}
return {'value': patient.getFirstname}
def get_middlename(self, patient):
if not patient:
return {'value': ''}
return {'value': patient.getMiddlename}
def get_lastname(self, patient):
if not patient:
return {'value': ''}
return {'value': patient.getSurname}
def get_gender(self, patient):
if not patient:
return {'value': ''}
return {'value': patient.getGender}
def get_age(self, patient):
if not patient:
return {'value': ''}
return {'value': patient.getAgeSplittedStr}
def get_agetype(self, patient):
if not patient:
return {'value': ''}
return {'value': patient.getAgeSplittedStr}
def get_facility_province(self, ar):
"""Client province"""
if not ar:
return {'value': ''}
return {'value': ar.getProvince}
def get_facility_district(self, ar):
"""Client district"""
if not ar:
return {'value': ''}
return {'value': ar.getDistrict}
def get_client_name(self, ar):
"""Client name"""
if not ar:
return {'value': ''}
return {'value': ar.getClientTitle}
def get_patient_sex(self, patient):
"""Patient gender"""
if not patient:
return {'value': 'U'}
genders = {'male': 'M', 'female': 'F'}
return {'value': genders.get(patient.getGender, patient.getGender)}
def get_patient_dob(self, patient):
"""Patient Date Of Birth"""
if not patient:
return {'value': ''}
return {'value': self.ulocalized_time(patient.getBirthDate)}
def get_date_of_collection(self, ar):
"""Patient Date Of Collection"""
if not ar:
return {'value': ''}
return {'value': self.ulocalized_time(ar.getDateSampled)}
def get_specimentype(self, ar):
"""Specimen Type"""
if not ar:
return {'value': ''}
return {'value': ar.getSampleType}
def get_date_of_receiving(self, ar):
"""Patient Date Of Receiving"""
if not ar:
return {'value': ''}
return {'value': self.ulocalized_time(ar.getDateReceived)}
def get_date_of_dispatch(self, ar):
"""Patient Date Of Publication"""
if not ar:
return {'value': ''}
return {'value': self.ulocalized_time(ar.getDatePublished)}
def get_date_of_testing(self, analysis):
"""Date Of Testing"""
try:
date = analysis.getResultCaptureDate
date = self.ulocalized_time(date)
return {'value': date}
except:
return {'value': ''}
def get_result(self, analysis):
"""Result"""
dataitem = {
'value': analysis.getResult.replace('<',
'<').replace('>', '>')
}
return dataitem
def get_ar_brain(self, analysis_brain):
"""
Get the brain of the Analysis request the analysis
is coming from.
:param analysis_brain: The analysis brain from which
we want to get its analysis request brain
:return: Analysis Request brain if found else None
"""
ar_uid = analysis_brain.getParentUID
if not ar_uid:
return None
return self.get_brain(ar_uid, CATALOG_ANALYSIS_REQUEST_LISTING)
def get_patient_brain(self, analysis_brain):
"""
Get the brain of the patient the analysis is assigned to.
:param analysis_brain: The analysis brain from which
we want to get the patient it is assigned to
:return: Patient brain if found else None
"""
ar = self.get_ar_brain(analysis_brain)
if not ar:
return None
patient_uid = ar.getPatientUID
if not patient_uid:
return None
patient = self.get_brain(patient_uid, CATALOG_PATIENT_LISTING)
return patient
def map_uids_to_brains(self, ar_uids=None):
"""Fetches AR brains and patients and stores them in a generalist map
where the key is the brain's uid and the value is the brain"""
if not ar_uids:
return
logger.info("Mapping UIDs to brains for {} AR UIDs".format(
len(ar_uids)))
self.uids_map = dict()
pat_uids = set()
query = dict(UID=ar_uids)
ar_brains = api.search(query, CATALOG_ANALYSIS_REQUEST_LISTING)
for ar_brain in ar_brains:
pat_uid = ar_brain.getPatientUID
if pat_uid:
pat_uids.add(pat_uid)
self.uids_map[api.get_uid(ar_brain)] = ar_brain
logger.info("Mapping UIDs to brains for {} Patient UIDs".format(
len(pat_uids)))
query = dict(UID=list(pat_uids))
pat_brains = api.search(query, CATALOG_PATIENT_LISTING)
self.uids_map.update({api.get_uid(pat): pat for pat in pat_brains})
