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)
    default_template = ViewPageTemplateFile("templates/productivity.pt")
    template = ViewPageTemplateFile(
        "templates/productivity_analysesperdepartment.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):

        parms = []
        titles = []

        # Apply filters
        self.contentFilter = {'portal_type': 'Analysis'}
        val = self.selection_macros.parse_daterange(self.request,
                                                    'getDateRequested',
                                                    _('Date Requested'))
        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_analysis_workflow',
                                                'getAnalysisState',
                                                _('Analysis State'))
        if val:
            self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
            parms.append(val['parms'])
            titles.append(val['titles'])

        # Query the catalog and store results in a dictionary
        analyses = self.bika_analysis_catalog(self.contentFilter)
        if not analyses:
            message = _("No analyses matched your query")
            self.context.plone_utils.addPortalMessage(message, "error")
            return self.default_template()

        groupby = self.request.form.get('GroupingPeriod', '')
        if (groupby != ''):
            parms.append({"title": _("Grouping period"), "value": _(groupby)})

        datalines = {}
        footlines = {}
        totalcount = len(analyses)
        totalpublishedcount = 0
        totalperformedcount = 0
        for analysis in analyses:
            analysis = analysis.getObject()
            analysisservice = analysis.getService()
            department = analysisservice.getDepartment()
            department = department.Title() if department else ''
            daterequested = analysis.created()

            group = ''
            if groupby == 'Day':
                group = self.ulocalized_time(daterequested)
            elif groupby == 'Week':
                group = daterequested.strftime(
                    "%Y") + ", " + daterequested.strftime("%U")
            elif groupby == 'Month':
                group = daterequested.strftime(
                    "%B") + " " + daterequested.strftime("%Y")
            elif groupby == 'Year':
                group = daterequested.strftime("%Y")
            else:
                group = ''

            dataline = {'Group': group, 'Requested': 0, 'Performed': 0,
                        'Published': 0, 'Departments': {}}
            deptline = {'Department': department, 'Requested': 0, 'Performed': 0,
                        'Published': 0}
            if (group in datalines):
                dataline = datalines[group]
                if (department in dataline['Departments']):
                    deptline = dataline['Departments'][department]

            grouptotalcount = dataline['Requested'] + 1
            groupperformedcount = dataline['Performed']
            grouppublishedcount = dataline['Published']

            depttotalcount = deptline['Requested'] + 1
            deptperformedcount = deptline['Performed']
            deptpubishedcount = deptline['Published']

            workflow = getToolByName(self.context, 'portal_workflow')
            arstate = workflow.getInfoFor(analysis.aq_parent, 'review_state', '')
            if (arstate == 'published'):
                deptpubishedcount += 1
                grouppublishedcount += 1
                totalpublishedcount += 1

            if (analysis.getResult()):
                deptperformedcount += 1
                groupperformedcount += 1
                totalperformedcount += 1

            group_performedrequested_ratio = float(groupperformedcount) / float(
                grouptotalcount)
            group_publishedperformed_ratio = groupperformedcount > 0 and float(
                grouppublishedcount) / float(groupperformedcount) or 0

            anl_performedrequested_ratio = float(deptperformedcount) / float(
                depttotalcount)
            anl_publishedperformed_ratio = deptperformedcount > 0 and float(
                deptpubishedcount) / float(deptperformedcount) or 0

            dataline['Requested'] = grouptotalcount
            dataline['Performed'] = groupperformedcount
            dataline['Published'] = grouppublishedcount
            dataline['PerformedRequestedRatio'] = group_performedrequested_ratio
            dataline['PerformedRequestedRatioPercentage'] = ('{0:.0f}'.format(
                group_performedrequested_ratio * 100)) + "%"
            dataline['PublishedPerformedRatio'] = group_publishedperformed_ratio
            dataline['PublishedPerformedRatioPercentage'] = ('{0:.0f}'.format(
                group_publishedperformed_ratio * 100)) + "%"

            deptline['Requested'] = depttotalcount
            deptline['Performed'] = deptperformedcount
            deptline['Published'] = deptpubishedcount
            deptline['PerformedRequestedRatio'] = anl_performedrequested_ratio
            deptline['PerformedRequestedRatioPercentage'] = ('{0:.0f}'.format(
                anl_performedrequested_ratio * 100)) + "%"
            deptline['PublishedPerformedRatio'] = anl_publishedperformed_ratio
            deptline['PublishedPerformedRatioPercentage'] = ('{0:.0f}'.format(
                anl_publishedperformed_ratio * 100)) + "%"

            dataline['Departments'][department] = deptline
            datalines[group] = dataline

        # Footer total data
        total_performedrequested_ratio = float(totalperformedcount) / float(
            totalcount)
        total_publishedperformed_ratio = totalperformedcount > 0 and float(
            totalpublishedcount) / float(totalperformedcount) or 0

        footline = {'Requested': totalcount,
                    'Performed': totalperformedcount,
                    'Published': totalpublishedcount,
                    'PerformedRequestedRatio': total_performedrequested_ratio,
                    'PerformedRequestedRatioPercentage': ('{0:.0f}'.format(
                        total_performedrequested_ratio * 100)) + "%",
                    'PublishedPerformedRatio': total_publishedperformed_ratio,
                    'PublishedPerformedRatioPercentage': ('{0:.0f}'.format(
                        total_publishedperformed_ratio * 100)) + "%"}

        footlines['Total'] = footline

        self.report_data = {'parameters': parms,
                            'datalines': datalines,
                            'footlines': footlines}

        if self.request.get('output_format', '') == 'CSV':
            import csv
            import StringIO
            import datetime

            fieldnames = [
                'Group',
                'Department',
                'Requested',
                'Performed',
                'Published',
            ]
            output = StringIO.StringIO()
            dw = csv.DictWriter(output, extrasaction='ignore',
                                fieldnames=fieldnames)
            dw.writerow(dict((fn, fn) for fn in fieldnames))
            for group_name, group in datalines.items():
                for dept_name, dept in group['Departments'].items():
                    dw.writerow({
                        'Group': group_name,
                        'Department': dept_name,
                        'Requested': dept['Requested'],
                        'Performed': dept['Performed'],
                        'Published': dept['Published'],
                    })
            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=\"analysesperdepartment_%s.csv\"" % date)
            self.request.RESPONSE.write(report_data)
        else:
            return {'report_title': _('Analyses summary per department'),
                    'report_data': self.template()}
Exemple #3
0
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(),
        }
Exemple #4
0
class Report(BrowserView):
    implements(IViewView)
    default_template = ViewPageTemplateFile("templates/productivity.pt")
    template = ViewPageTemplateFile(
        "templates/productivity_analysesperdepartment.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):

        parms = []
        titles = []

        # Apply filters
        self.contentFilter = {'portal_type': 'Analysis'}
        val = self.selection_macros.parse_daterange(self.request,
                                                    'getDateRequested',
                                                    _('Date Requested'))
        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_analysis_workflow',
                                                'getAnalysisState',
                                                _('Analysis State'))
        if val:
            self.contentFilter[val['contentFilter']
                               [0]] = val['contentFilter'][1]
            parms.append(val['parms'])
            titles.append(val['titles'])

        # Query the catalog and store results in a dictionary
        analyses = self.bika_analysis_catalog(self.contentFilter)
        if not analyses:
            message = _("No analyses matched your query")
            self.context.plone_utils.addPortalMessage(message, "error")
            return self.default_template()

        groupby = self.request.form.get('GroupingPeriod', '')
        if (groupby != ''):
            parms.append({"title": _("Grouping period"), "value": _(groupby)})

        datalines = {}
        footlines = {}
        totalcount = len(analyses)
        totalpublishedcount = 0
        totalperformedcount = 0
        for analysis in analyses:
            analysis = analysis.getObject()
            analysisservice = analysis.getService()
            department = analysisservice.getDepartment()
            department = department.Title() if department else ''
            daterequested = analysis.created()

            group = ''
            if groupby == 'Day':
                group = self.ulocalized_time(daterequested)
            elif groupby == 'Week':
                group = daterequested.strftime(
                    "%Y") + ", " + daterequested.strftime("%U")
            elif groupby == 'Month':
                group = daterequested.strftime(
                    "%B") + " " + daterequested.strftime("%Y")
            elif groupby == 'Year':
                group = daterequested.strftime("%Y")
            else:
                group = ''

            dataline = {
                'Group': group,
                'Requested': 0,
                'Performed': 0,
                'Published': 0,
                'Departments': {}
            }
            deptline = {
                'Department': department,
                'Requested': 0,
                'Performed': 0,
                'Published': 0
            }
            if (group in datalines):
                dataline = datalines[group]
                if (department in dataline['Departments']):
                    deptline = dataline['Departments'][department]

            grouptotalcount = dataline['Requested'] + 1
            groupperformedcount = dataline['Performed']
            grouppublishedcount = dataline['Published']

            depttotalcount = deptline['Requested'] + 1
            deptperformedcount = deptline['Performed']
            deptpubishedcount = deptline['Published']

            workflow = getToolByName(self.context, 'portal_workflow')
            arstate = workflow.getInfoFor(analysis.aq_parent, 'review_state',
                                          '')
            if (arstate == 'published'):
                deptpubishedcount += 1
                grouppublishedcount += 1
                totalpublishedcount += 1

            if (analysis.getResult()):
                deptperformedcount += 1
                groupperformedcount += 1
                totalperformedcount += 1

            group_performedrequested_ratio = float(
                groupperformedcount) / float(grouptotalcount)
            group_publishedperformed_ratio = groupperformedcount > 0 and float(
                grouppublishedcount) / float(groupperformedcount) or 0

            anl_performedrequested_ratio = float(deptperformedcount) / float(
                depttotalcount)
            anl_publishedperformed_ratio = deptperformedcount > 0 and float(
                deptpubishedcount) / float(deptperformedcount) or 0

            dataline['Requested'] = grouptotalcount
            dataline['Performed'] = groupperformedcount
            dataline['Published'] = grouppublishedcount
            dataline[
                'PerformedRequestedRatio'] = group_performedrequested_ratio
            dataline['PerformedRequestedRatioPercentage'] = ('{0:.0f}'.format(
                group_performedrequested_ratio * 100)) + "%"
            dataline[
                'PublishedPerformedRatio'] = group_publishedperformed_ratio
            dataline['PublishedPerformedRatioPercentage'] = ('{0:.0f}'.format(
                group_publishedperformed_ratio * 100)) + "%"

            deptline['Requested'] = depttotalcount
            deptline['Performed'] = deptperformedcount
            deptline['Published'] = deptpubishedcount
            deptline['PerformedRequestedRatio'] = anl_performedrequested_ratio
            deptline['PerformedRequestedRatioPercentage'] = ('{0:.0f}'.format(
                anl_performedrequested_ratio * 100)) + "%"
            deptline['PublishedPerformedRatio'] = anl_publishedperformed_ratio
            deptline['PublishedPerformedRatioPercentage'] = ('{0:.0f}'.format(
                anl_publishedperformed_ratio * 100)) + "%"

            dataline['Departments'][department] = deptline
            datalines[group] = dataline

        # Footer total data
        total_performedrequested_ratio = float(totalperformedcount) / float(
            totalcount)
        total_publishedperformed_ratio = totalperformedcount > 0 and float(
            totalpublishedcount) / float(totalperformedcount) or 0

        footline = {
            'Requested':
            totalcount,
            'Performed':
            totalperformedcount,
            'Published':
            totalpublishedcount,
            'PerformedRequestedRatio':
            total_performedrequested_ratio,
            'PerformedRequestedRatioPercentage':
            ('{0:.0f}'.format(total_performedrequested_ratio * 100)) + "%",
            'PublishedPerformedRatio':
            total_publishedperformed_ratio,
            'PublishedPerformedRatioPercentage':
            ('{0:.0f}'.format(total_publishedperformed_ratio * 100)) + "%"
        }

        footlines['Total'] = footline

        self.report_data = {
            'parameters': parms,
            'datalines': datalines,
            'footlines': footlines
        }

        if self.request.get('output_format', '') == 'CSV':
            import csv
            import StringIO
            import datetime

            fieldnames = [
                'Group',
                'Department',
                'Requested',
                'Performed',
                'Published',
            ]
            output = StringIO.StringIO()
            dw = csv.DictWriter(output,
                                extrasaction='ignore',
                                fieldnames=fieldnames)
            dw.writerow(dict((fn, fn) for fn in fieldnames))
            for group_name, group in datalines.items():
                for dept_name, dept in group['Departments'].items():
                    dw.writerow({
                        'Group': group_name,
                        'Department': dept_name,
                        'Requested': dept['Requested'],
                        'Performed': dept['Performed'],
                        'Published': dept['Published'],
                    })
            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=\"analysesperdepartment_%s.csv\"" % date)
            self.request.RESPONSE.write(report_data)
        else:
            return {
                'report_title': _('Analyses summary per department'),
                'report_data': self.template()
            }
Exemple #5
0
class Report(BrowserView):
    implements(IViewView)
    default_template = ViewPageTemplateFile("templates/productivity.pt")
    template = ViewPageTemplateFile(
        "templates/productivity_analysesperdepartment.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):

        parms = []
        titles = []

        # Apply filters
        self.contentFilter = {'portal_type': 'Analysis'}
        val = self.selection_macros.parse_daterange(self.request,
                                                    'getDateRequested',
                                                    _('Date Requested'))
        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_analysis_workflow',
                                                'getAnalysisState',
                                                _('Analysis State'))
        if val:
            self.contentFilter[val['contentFilter']
                               [0]] = val['contentFilter'][1]
            parms.append(val['parms'])
            titles.append(val['titles'])

        # Query the catalog and store results in a dictionary
        analyses = self.bika_analysis_catalog(self.contentFilter)
        if not analyses:
            message = _("No analyses matched your query")
            self.context.plone_utils.addPortalMessage(message, "error")
            return self.default_template()

        groupby = self.request.form.get('GroupingPeriod', '')
        if (groupby != ''):
            parms.append({"title": _("Grouping period"), "value": _(groupby)})

        datalines = {}
        footlines = {}
        totalcount = len(analyses)
        totalpublishedcount = 0
        totalperformedcount = 0
        for analysis in analyses:
            analysis = analysis.getObject()
            analysisservice = analysis.getService()
            department = analysisservice.getDepartment().Title()
            daterequested = analysis.created()

            group = ''
            if groupby == 'Day':
                group = self.ulocalized_time(daterequested)
            elif groupby == 'Week':
                group = daterequested.strftime(
                    "%Y") + ", " + daterequested.strftime("%U")
            elif groupby == 'Month':
                group = daterequested.strftime(
                    "%B") + " " + daterequested.strftime("%Y")
            elif groupby == 'Year':
                group = daterequested.strftime("%Y")
            else:
                group = ''

            dataline = {
                'Group': group,
                'Requested': 0,
                'Performed': 0,
                'Published': 0,
                'Departments': {}
            }
            deptline = {
                'Department': department,
                'Requested': 0,
                'Performed': 0,
                'Published': 0
            }
            if (group in datalines):
                dataline = datalines[group]
                if (department in dataline['Departments']):
                    deptline = dataline['Departments'][department]

            grouptotalcount = dataline['Requested'] + 1
            groupperformedcount = dataline['Performed']
            grouppublishedcount = dataline['Published']

            depttotalcount = deptline['Requested'] + 1
            deptperformedcount = deptline['Performed']
            deptpubishedcount = deptline['Published']

            workflow = getToolByName(self.context, 'portal_workflow')
            arstate = workflow.getInfoFor(analysis.aq_parent, 'review_state',
                                          '')
            if (arstate == 'published'):
                deptpubishedcount += 1
                grouppublishedcount += 1
                totalpublishedcount += 1

            if (analysis.getResult()):
                deptperformedcount += 1
                groupperformedcount += 1
                totalperformedcount += 1

            group_performedrequested_ratio = float(
                groupperformedcount) / float(grouptotalcount)
            group_publishedperformed_ratio = groupperformedcount > 0 and float(
                grouppublishedcount) / float(groupperformedcount) or 0

            anl_performedrequested_ratio = float(deptperformedcount) / float(
                depttotalcount)
            anl_publishedperformed_ratio = deptperformedcount > 0 and float(
                deptpubishedcount) / float(deptperformedcount) or 0

            dataline['Requested'] = grouptotalcount
            dataline['Performed'] = groupperformedcount
            dataline['Published'] = grouppublishedcount
            dataline[
                'PerformedRequestedRatio'] = group_performedrequested_ratio
            dataline['PerformedRequestedRatioPercentage'] = ('{0:.0f}'.format(
                group_performedrequested_ratio * 100)) + "%"
            dataline[
                'PublishedPerformedRatio'] = group_publishedperformed_ratio
            dataline['PublishedPerformedRatioPercentage'] = ('{0:.0f}'.format(
                group_publishedperformed_ratio * 100)) + "%"

            deptline['Requested'] = depttotalcount
            deptline['Performed'] = deptperformedcount
            deptline['Published'] = deptpubishedcount
            deptline['PerformedRequestedRatio'] = anl_performedrequested_ratio
            deptline['PerformedRequestedRatioPercentage'] = ('{0:.0f}'.format(
                anl_performedrequested_ratio * 100)) + "%"
            deptline['PublishedPerformedRatio'] = anl_publishedperformed_ratio
            deptline['PublishedPerformedRatioPercentage'] = ('{0:.0f}'.format(
                anl_publishedperformed_ratio * 100)) + "%"

            dataline['Departments'][department] = deptline
            datalines[group] = dataline

        # Footer total data
        total_performedrequested_ratio = float(totalperformedcount) / float(
            totalcount)
        total_publishedperformed_ratio = totalperformedcount > 0 and float(
            totalpublishedcount) / float(totalperformedcount) or 0

        footline = {
            'Requested':
            totalcount,
            'Performed':
            totalperformedcount,
            'Published':
            totalpublishedcount,
            'PerformedRequestedRatio':
            total_performedrequested_ratio,
            'PerformedRequestedRatioPercentage':
            ('{0:.0f}'.format(total_performedrequested_ratio * 100)) + "%",
            'PublishedPerformedRatio':
            total_publishedperformed_ratio,
            'PublishedPerformedRatioPercentage':
            ('{0:.0f}'.format(total_publishedperformed_ratio * 100)) + "%"
        }

        footlines['Total'] = footline

        self.report_data = {
            'parameters': parms,
            'datalines': datalines,
            'footlines': footlines
        }

        return {
            'report_title': _('Analyses summary per department'),
            '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)
    default_template = ViewPageTemplateFile("templates/productivity.pt")
    template = ViewPageTemplateFile("templates/productivity_analysesperdepartment.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):

        parms = []
        titles = []

        # Apply filters
        self.contentFilter = {'portal_type': 'Analysis'}
        val = self.selection_macros.parse_daterange(self.request,
                                                    'getDateRequested',
                                                    _('Date Requested'))
        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_analysis_workflow',
                                                'getAnalysisState',
                                                _('Analysis State'))
        if val:
            self.contentFilter[val['contentFilter'][0]] = val['contentFilter'][1]
            parms.append(val['parms'])
            titles.append(val['titles'])

        # Query the catalog and store results in a dictionary
        analyses = self.bika_analysis_catalog(self.contentFilter)
        if not analyses:
            message = _("No analyses matched your query")
            self.context.plone_utils.addPortalMessage(message, "error")
            return self.default_template()

        groupby = self.request.form.get('GroupingPeriod', '')
        if (groupby != ''):
            parms.append({"title": _("Grouping period"), "value": _(groupby)})

        datalines = {}
        footlines = {}
        totalcount = len(analyses)
        totalpublishedcount = 0
        totalperformedcount = 0
        for analysis in analyses:
            analysis = analysis.getObject()
            analysisservice = analysis.getService()
            department = analysisservice.getDepartment().Title()
            daterequested = analysis.created()

            group = ''
            if groupby == 'Day':
                group = self.ulocalized_time(daterequested)
            elif groupby == 'Week':
                group = daterequested.strftime("%Y") + ", " + daterequested.strftime("%U")
            elif groupby == 'Month':
                group = daterequested.strftime("%B") + " " + daterequested.strftime("%Y")
            elif groupby == 'Year':
                group = daterequested.strftime("%Y")
            else :
                group = ''

            dataline = {'Group': group, 'Requested': 0, 'Performed': 0, 'Published': 0, 'Departments': {} }
            deptline = {'Department':department, 'Requested':0, 'Performed': 0, 'Published': 0 }
            if (group in datalines):
                dataline = datalines[group]
                if (department in dataline['Departments']):
                    deptline = dataline['Departments'][department]

            grouptotalcount = dataline['Requested']+1
            groupperformedcount = dataline['Performed']
            grouppublishedcount = dataline['Published']

            depttotalcount = deptline['Requested']+1
            deptperformedcount = deptline['Performed']
            deptpubishedcount = deptline['Published']

            workflow = getToolByName(self.context, 'portal_workflow')
            arstate = workflow.getInfoFor(analysis.aq_parent, 'review_state', '')
            if (arstate == 'published'):
                deptpubishedcount += 1
                grouppublishedcount += 1
                totalpublishedcount += 1

            if (analysis.getResult()):
                deptperformedcount += 1
                groupperformedcount += 1
                totalperformedcount += 1

            group_performedrequested_ratio = float(groupperformedcount)/float(grouptotalcount)
            group_publishedperformed_ratio = groupperformedcount > 0 and float(grouppublishedcount)/float(groupperformedcount) or 0

            anl_performedrequested_ratio = float(deptperformedcount)/float(depttotalcount)
            anl_publishedperformed_ratio = deptperformedcount > 0 and float(deptpubishedcount)/float(deptperformedcount) or 0

            dataline['Requested'] = grouptotalcount
            dataline['Performed'] = groupperformedcount
            dataline['Published'] = grouppublishedcount
            dataline['PerformedRequestedRatio'] = group_performedrequested_ratio
            dataline['PerformedRequestedRatioPercentage'] = ('{0:.0f}'.format(group_performedrequested_ratio*100))+"%"
            dataline['PublishedPerformedRatio'] = group_publishedperformed_ratio
            dataline['PublishedPerformedRatioPercentage'] = ('{0:.0f}'.format(group_publishedperformed_ratio*100))+"%"

            deptline['Requested'] = depttotalcount
            deptline['Performed'] = deptperformedcount
            deptline['Published'] = deptpubishedcount
            deptline['PerformedRequestedRatio'] = anl_performedrequested_ratio
            deptline['PerformedRequestedRatioPercentage'] = ('{0:.0f}'.format(anl_performedrequested_ratio*100))+"%"
            deptline['PublishedPerformedRatio'] = anl_publishedperformed_ratio
            deptline['PublishedPerformedRatioPercentage'] = ('{0:.0f}'.format(anl_publishedperformed_ratio*100))+"%"

            dataline['Departments'][department]=deptline
            datalines[group] = dataline

        # Footer total data
        total_performedrequested_ratio = float(totalperformedcount)/float(totalcount)
        total_publishedperformed_ratio = totalperformedcount > 0 and float(totalpublishedcount)/float(totalperformedcount) or 0

        footline = {'Requested': totalcount,
                    'Performed': totalperformedcount,
                    'Published': totalpublishedcount,
                    'PerformedRequestedRatio': total_performedrequested_ratio,
                    'PerformedRequestedRatioPercentage': ('{0:.0f}'.format(total_performedrequested_ratio*100))+"%",
                    'PublishedPerformedRatio': total_publishedperformed_ratio,
                    'PublishedPerformedRatioPercentage': ('{0:.0f}'.format(total_publishedperformed_ratio*100))+"%" }

        footlines['Total'] = footline;

        self.report_data = {'parameters': parms,
                            'datalines': datalines,
                            'footlines': footlines }

        return {'report_title': _('Analyses summary per department'),
                'report_data': self.template()}