def charts(self):
data = self.rows
ret = []
sum_all = 0
colors = []
if data:
data = data[0]
for key in self.vals_config[data.title]:
if getattr(data, key, None):
sum_all = sum_all + getattr(data, key)
for key in self.vals_config[data.title]:
if getattr(data, key, None):
entry = {}
entry['value'] = round(float(getattr(data, key)) * 100 / float((sum_all or 1)), 1)
colors.append(self.chart_config[key]['color'])
entry['label'] = self.chart_config[key]['display']
params = (
entry['value'],
getattr(data, key), entry['label'],
self.config['startdate'].strftime("%b %Y")
)
entry['description'] = "%.1f%% (%d) %s (%s)" % params
ret.append(entry)
chart = PieChart('', '', ret, color=colors)
chart.marginLeft = 10
chart.marginRight = 10
chart.height = 500
return [chart]
def charts(self):
data = self.rows
ret = []
sum_all = 0
colors = []
if data:
data = data[0]
for key in self.vals_config[data.title]:
if getattr(data, key, None):
sum_all = sum_all + getattr(data, key)
for key in self.vals_config[data.title]:
if getattr(data, key, None):
entry = {}
entry['value'] = round(float(getattr(data, key)) * 100 / float((sum_all or 1)), 1)
colors.append(self.chart_config[key]['color'])
entry['label'] = self.chart_config[key]['display']
params = (
entry['value'],
getattr(data, key), entry['label'],
self.config['startdate'].strftime("%b %Y")
)
entry['description'] = "%.1f%% (%d) %s (%s)" % params
ret.append(entry)
chart = PieChart('', '', ret, color=colors)
chart.marginLeft = 10
chart.marginRight = 10
chart.height = 500
return [chart]
def charts(self):
if 'location_id' in self.request.GET: # hack: only get data if we're loading an actual report
return [
PieChart(None, _('Current Reporting'),
self.master_pie_chart_data())
]
def charts(self):
case_finding_sql_data = self.case_finding_sql_data[0]
sputum_conversion_report = ReportFactory.from_spec(
StaticReportConfiguration.by_id('static-%s-sputum_conversion' %
self.domain),
include_prefilters=True)
filter_values = {'date': self.datespan}
locations_id = [
Choice(value=location_id, display='')
for location_id in self.report_config.locations_id if location_id
]
if locations_id:
filter_values['village'] = locations_id
if self.report_config.is_migrated is not None:
filter_values['is_migrated'] = Choice(
value=self.report_config.is_migrated, display='')
sputum_conversion_report.set_filter_values(filter_values)
sputum_conversion_data = sputum_conversion_report.get_data()[0]
charts_sql_data = self.charts_sql_data[0]
treatment_outcome_sql_data = self.treatment_outcome_sql_data[0]
default_value = {'sort_key': 0}
chart = PieChart(title=_('Cases by Gender'), key='gender', values=[])
chart.data = [{
'label':
_('Male'),
'value':
case_finding_sql_data.get('male_total', default_value)['sort_key']
}, {
'label':
_('Female'),
'value':
case_finding_sql_data.get('female_total',
default_value)['sort_key']
}, {
'label':
_('Transgender'),
'value':
case_finding_sql_data.get('transgender_total',
default_value)['sort_key']
}]
chart2 = MultiBarChart(_('Cases By Type'),
x_axis=Axis(''),
y_axis=Axis(''))
chart2.stacked = False
chart2.showLegend = False
positive_smear = case_finding_sql_data.get('new_positive_tb_pulmonary',
default_value)['sort_key']
negative_smear = case_finding_sql_data.get('new_negative_tb_pulmonary',
default_value)['sort_key']
positive_extra_pulmonary = case_finding_sql_data.get(
'new_positive_tb_extrapulmonary', default_value)['sort_key']
relapse_cases = case_finding_sql_data.get('recurrent_positive_tb',
default_value)['sort_key']
failure_cases = case_finding_sql_data.get('failure_positive_tb',
default_value)['sort_key']
lfu_cases = case_finding_sql_data.get('lfu_positive_tb',
default_value)['sort_key']
others_cases = case_finding_sql_data.get('others_positive_tb',
default_value)['sort_key']
chart2.add_dataset(_('New'), [{
'x': 'Smear +ve',
'y': positive_smear
}, {
'x': 'Smear -ve',
'y': negative_smear
}, {
'x': 'EP',
'y': positive_extra_pulmonary
}])
chart2.add_dataset(_('Retreatment'), [{
'x': 'Relapse',
'y': relapse_cases
}, {
'x': 'Failure',
'y': failure_cases
}, {
'x': 'Treatment After Default',
'y': lfu_cases
}, {
'x': 'Others',
'y': others_cases
}])
chart3 = MultiBarChart('Sputum Conversion By Patient Type', Axis(''),
Axis(''))
chart3.stacked = True
chart3.add_dataset('Positive', [
{
'x':
_('New Sputum +ve (2 month IP)'),
'y':
sputum_conversion_data.get(
'new_sputum_positive_patient_2months_ip', 0)
},
{
'x':
_('New Sputum +ve (3 month IP)'),
'y':
sputum_conversion_data.get(
'new_sputum_positive_patient_3months_ip', 0)
},
{
'x':
_('Cat II (3 month IP)'),
'y':
sputum_conversion_data.get('positive_endofip_patients_cat2', 0)
},
])
chart3.add_dataset(_('Negative'), [
{
'x':
_('New Sputum +ve (2 month IP)'),
'y':
sputum_conversion_data.get(
'new_sputum_negative_patient_2months_ip', 0)
},
{
'x':
_('New Sputum +ve (3 month IP)'),
'y':
sputum_conversion_data.get(
'new_sputum_negative_patient_3months_ip', 0)
},
{
'x':
_('Cat II (3 month IP)'),
'y':
sputum_conversion_data.get('negative_endofip_patients_cat2', 0)
},
])
chart3.add_dataset('NA', [
{
'x':
_('New Sputum +ve (2 month IP)'),
'y':
sputum_conversion_data.get('new_sputum_na_patient_2months_ip',
0)
},
{
'x':
_('New Sputum +ve (3 month IP)'),
'y':
sputum_conversion_data.get('new_sputum_na_patient_3months_ip',
0)
},
{
'x': _('Cat II (3 month IP)'),
'y': sputum_conversion_data.get('na_endofip_patients_cat2', 0)
},
])
chart4 = PieChart(title=_('Total number of patients by category'),
key='',
values=[])
chart4.data = [{
'label':
_('Cat1'),
'value':
charts_sql_data.get('cat1_patients', default_value)['sort_key']
}, {
'label':
_('Cat2'),
'value':
charts_sql_data.get('cat2_patients', default_value)['sort_key']
}]
chart5 = MultiBarChart('Outcome By Type', Axis(''), Axis(''))
chart5.stacked = True
chart5.add_dataset(_('Cured'), [{
'x':
_('New'),
'y':
treatment_outcome_sql_data.get('new_patients_cured',
default_value)['sort_key']
}, {
'x':
_('Retreatment'),
'y':
treatment_outcome_sql_data.get('recurrent_patients_cured',
default_value)['sort_key']
}])
chart5.add_dataset('Treatment Complete', [{
'x':
_('New'),
'y':
treatment_outcome_sql_data.get('new_patients_treatment_complete',
default_value)['sort_key']
}, {
'x':
_('Retreatment'),
'y':
treatment_outcome_sql_data.get(
'recurrent_patients_treatment_complete',
default_value)['sort_key']
}])
chart5.add_dataset('Died', [{
'x':
_('New'),
'y':
treatment_outcome_sql_data.get('new_patients_died',
default_value)['sort_key']
}, {
'x':
_('Retreatment'),
'y':
treatment_outcome_sql_data.get('recurrent_patients_died',
default_value)['sort_key']
}])
chart5.add_dataset(_('Failure'), [{
'x':
_('New'),
'y':
treatment_outcome_sql_data.get('new_patients_treatment_failure',
default_value)['sort_key']
}, {
'x':
_('Retreatment'),
'y':
treatment_outcome_sql_data.get(
'recurrent_patients_treatment_failure',
default_value)['sort_key']
}])
chart5.add_dataset(_('Loss to Follow-up'), [{
'x':
_('New'),
'y':
treatment_outcome_sql_data.get('new_patients_loss_to_follow_up',
default_value)['sort_key']
}, {
'x':
_('Retreatment'),
'y':
treatment_outcome_sql_data.get(
'recurrent_patients_loss_to_follow_up',
default_value)['sort_key']
}])
chart5.add_dataset(_('Regimen Changed'), [{
'x':
_('New'),
'y':
treatment_outcome_sql_data.get('new_patients_regimen_changed',
default_value)['sort_key']
}, {
'x':
_('Retreatment'),
'y':
treatment_outcome_sql_data.get(
'recurrent_patients_regimen_changed',
default_value)['sort_key']
}])
chart5.add_dataset('Not Evaluated', [{
'x':
_('New'),
'y':
treatment_outcome_sql_data.get('new_patients_not_evaluated',
default_value)['sort_key']
}, {
'x':
_('Retreatment'),
'y':
treatment_outcome_sql_data.get('recurrent_patients_not_evaluated',
default_value)['sort_key']
}])
return [chart, chart2, chart3, chart4, chart5]
def charts(self):
if 'location_id' in self.request.GET: # hack: only get data if we're loading an actual report
chart = PieChart(_('Current Reporting'), 'current_reporting', [])
chart.data = self.master_pie_chart_data()
return [chart]
def get_chart(self, rows, x_label, y_label, data_provider):
def _get_label_with_percentage(row):
return "%s [%d: %s%%]" % (row[0]['html'], int(row[-2]['html']), str(int(row[-1]['html'][:-1])))
if isinstance(data_provider, NutritionBirthWeightDetails):
chart = PieChart(data_provider.chart_title, '',
[{'label': _get_label_with_percentage(row),
'value': int(row[-1]['html'][:-1])} for row in rows[2:]], ['red', 'green'])
chart.showLabels = False
chart.marginLeft = 20
chart.marginRight = 0
chart.marginBottom = 20
elif isinstance(data_provider, DeliveryPlaceDetailsExtended):
chart = PieChart(data_provider.chart_title, '',
[{'label': _get_label_with_percentage(row),
'value': int(row[-1]['html'][:-1])} for row in rows[1:]])
chart.showLabels = False
elif isinstance(data_provider, (PostnatalCareOverview, ImmunizationOverview)):
chart = MultiBarChart(data_provider.chart_title, x_axis=Axis(x_label), y_axis=Axis(y_label, '.2%'))
chart.rotateLabels = -45
chart.marginBottom = 150
chart.marginLeft = 45
chart.marginRight = 0
if isinstance(data_provider, ImmunizationOverview):
chart.stacked = True
chart.add_dataset('Percentage',
[{'x': row[0]['html'],
'y': int(row[3]['html'][:-1]) / 100.0} for row in rows],
color='green')
chart.add_dataset('Dropout Percentage',
[{'x': row[0]['html'],
'y': int(row[-1]['html'][:-1]) / 100.0} for row in rows],
color='red')
else:
chart.add_dataset('Percentage',
[{'x': row[0]['html'], 'y':int(row[-1]['html'][:-1]) / 100.0} for row in rows])
elif isinstance(data_provider, AnteNatalCareServiceOverviewExtended):
chart1 = MultiBarChart('ANC Visits', x_axis=Axis(x_label), y_axis=Axis(y_label, '.2%'))
chart2 = MultiBarChart('Maternal TT & IFA', x_axis=Axis(x_label), y_axis=Axis(y_label, '.2%'))
chart1.rotateLabels = -45
chart2.rotateLabels = -45
chart1.marginBottom = 150
chart2.marginBottom = 150
chart1.marginLeft = 20
chart2.marginLeft = 45
chart1.marginRight = 0
chart2.marginRight = 0
chart1.add_dataset('Percentage', [{'x': row[0]['html'],
'y': int(row[-1]['html'][:-1]) / 100.0} for row in rows[1:6]])
chart2.add_dataset('Percentage', [{'x': row[0]['html'],
'y': int(row[-1]['html'][:-1]) / 100.0} for row in rows[6:12]])
return [chart1, chart2]
elif isinstance(data_provider, ChildrenDeathsByMonth):
chart = MultiBarChart(data_provider.chart_title, x_axis=Axis(x_label, dateFormat="%B"),
y_axis=Axis(y_label, '.2%'))
chart.rotateLabels = -45
chart.marginBottom = 50
chart.marginLeft = 20
chart.add_dataset('Percentage', [{'x': row[0],
'y': int(row[-1]['html'][:-1]) / 100.0} for row in rows])
else:
chart = PieChart(data_provider.chart_title, '', [{'label': _get_label_with_percentage(row),
'value': int(row[-1]['html'][:-1])} for row in rows])
chart.showLabels = False
chart.marginLeft = 20
chart.marginRight = 0
chart.marginBottom = 0
return [chart]
def charts(self):
case_finding_sql_data = self.case_finding_sql_data[0]
sputum_conversion_report = ReportFactory.from_spec(
StaticReportConfiguration.by_id('static-%s-sputum_conversion' % self.domain), include_prefilters=True
)
filter_values = {'date': QuarterFilter.get_value(self.request, self.domain)}
locations_id = [
Choice(value=location_id, display='') for location_id in self.report_config.locations_id
if location_id
]
if locations_id:
filter_values['village'] = locations_id
sputum_conversion_report.set_filter_values(filter_values)
sputum_conversion_data = sputum_conversion_report.get_data()[0]
charts_sql_data = self.charts_sql_data[0]
treatment_outcome_sql_data = self.treatment_outcome_sql_data[0]
default_value = {'sort_key': 0}
chart = PieChart(title=_('Cases by Gender'), key='gender', values=[])
chart.data = [
{'label': _('Male'), 'value': case_finding_sql_data.get('male_total', default_value)['sort_key']},
{
'label': _('Female'),
'value': case_finding_sql_data.get('female_total', default_value)['sort_key']
},
{
'label': _('Transgender'),
'value': case_finding_sql_data.get('transgender_total', default_value)['sort_key']
}
]
chart2 = MultiBarChart(_('Cases By Type'), x_axis=Axis(''), y_axis=Axis(''))
chart2.stacked = False
chart2.showLegend = False
positive_smear = case_finding_sql_data.get('new_positive_tb_pulmonary', default_value)['sort_key']
negative_smear = case_finding_sql_data.get('new_negative_tb_pulmonary', default_value)['sort_key']
positive_extra_pulmonary = case_finding_sql_data.get(
'new_positive_tb_extrapulmonary', default_value
)['sort_key']
relapse_cases = case_finding_sql_data.get('recurrent_positive_tb', default_value)['sort_key']
failure_cases = case_finding_sql_data.get('failure_positive_tb', default_value)['sort_key']
lfu_cases = case_finding_sql_data.get('lfu_positive_tb', default_value)['sort_key']
others_cases = case_finding_sql_data.get('others_positive_tb', default_value)['sort_key']
chart2.add_dataset(
_('New'),
[
{'x': 'Smear +ve', 'y': positive_smear},
{'x': 'Smear -ve', 'y': negative_smear},
{'x': 'EP', 'y': positive_extra_pulmonary}
]
)
chart2.add_dataset(
_('Retreatment'), [
{'x': 'Relapse', 'y': relapse_cases},
{'x': 'Failure', 'y': failure_cases},
{'x': 'Treatment After Default', 'y': lfu_cases},
{'x': 'Others', 'y': others_cases}
]
)
chart3 = MultiBarChart('Sputum Conversion By Patient Type', Axis(''), Axis(''))
chart3.stacked = True
chart3.add_dataset('Positive', [
{
'x': _('New Sputum +ve (2 month IP)'),
'y': sputum_conversion_data.get('new_sputum_positive_patient_2months_ip', 0)
},
{
'x': _('New Sputum +ve (3 month IP)'),
'y': sputum_conversion_data.get('new_sputum_positive_patient_3months_ip', 0)
},
{
'x': _('Cat II (3 month IP)'),
'y': sputum_conversion_data.get('positive_endofip_patients_cat2', 0)
},
])
chart3.add_dataset(_('Negative'), [
{
'x': _('New Sputum +ve (2 month IP)'),
'y': sputum_conversion_data.get('new_sputum_negative_patient_2months_ip', 0)
},
{
'x': _('New Sputum +ve (3 month IP)'),
'y': sputum_conversion_data.get('new_sputum_negative_patient_3months_ip', 0)
},
{
'x': _('Cat II (3 month IP)'),
'y': sputum_conversion_data.get('negative_endofip_patients_cat2', 0)
},
])
chart3.add_dataset('NA', [
{
'x': _('New Sputum +ve (2 month IP)'),
'y': sputum_conversion_data.get('new_sputum_na_patient_2months_ip', 0)
},
{
'x': _('New Sputum +ve (3 month IP)'),
'y': sputum_conversion_data.get('new_sputum_na_patient_3months_ip', 0)
},
{
'x': _('Cat II (3 month IP)'),
'y': sputum_conversion_data.get('na_endofip_patients_cat2', 0)
},
])
chart4 = PieChart(
title=_('Total number of patients by category'), key='', values=[]
)
chart4.data = [
{
'label': _('Cat1'),
'value': charts_sql_data.get('cat1_patients', default_value)['sort_key']
},
{
'label': _('Cat2'),
'value': charts_sql_data.get('cat2_patients', default_value)['sort_key']
}
]
chart5 = MultiBarChart('Outcome By Type', Axis(''), Axis(''))
chart5.stacked = True
chart5.add_dataset(_('Cured'), [
{
'x': _('New'),
'y': treatment_outcome_sql_data.get('new_patients_cured', default_value)['sort_key']
},
{
'x': _('Retreatment'),
'y': treatment_outcome_sql_data.get('recurrent_patients_cured', default_value)['sort_key']
}
])
chart5.add_dataset('Treatment Complete', [
{
'x': _('New'),
'y': treatment_outcome_sql_data.get('new_patients_treatment_complete', default_value)['sort_key']
},
{
'x': _('Retreatment'),
'y': treatment_outcome_sql_data.get(
'recurrent_patients_treatment_complete', default_value)['sort_key']
}
])
chart5.add_dataset('Died', [
{
'x': _('New'),
'y': treatment_outcome_sql_data.get('new_patients_died', default_value)['sort_key']
},
{
'x': _('Retreatment'),
'y': treatment_outcome_sql_data.get('recurrent_patients_died', default_value)['sort_key']
}
])
chart5.add_dataset(_('Failure'), [
{
'x': _('New'),
'y': treatment_outcome_sql_data.get('new_patients_treatment_failure', default_value)['sort_key']
},
{
'x': _('Retreatment'),
'y': treatment_outcome_sql_data.get(
'recurrent_patients_treatment_failure', default_value
)['sort_key']
}
])
chart5.add_dataset(_('Loss to Follow-up'), [
{
'x': _('New'),
'y': treatment_outcome_sql_data.get('new_patients_loss_to_follow_up', default_value)['sort_key']
},
{
'x': _('Retreatment'),
'y': treatment_outcome_sql_data.get(
'recurrent_patients_loss_to_follow_up', default_value
)['sort_key']
}
])
chart5.add_dataset(_('Regimen Changed'), [
{
'x': _('New'),
'y': treatment_outcome_sql_data.get('new_patients_regimen_changed', default_value)['sort_key']
},
{
'x': _('Retreatment'),
'y': treatment_outcome_sql_data.get(
'recurrent_patients_regimen_changed', default_value
)['sort_key']
}
])
chart5.add_dataset('Not Evaluated', [
{
'x': _('New'),
'y': treatment_outcome_sql_data.get('new_patients_not_evaluated', default_value)['sort_key']
},
{
'x': _('Retreatment'),
'y': treatment_outcome_sql_data.get('recurrent_patients_not_evaluated', default_value)['sort_key']
}
])
return [
chart,
chart2,
chart3,
chart4,
chart5
]
def charts(self):
if 'location_id' in self.request.GET: # hack: only get data if we're loading an actual report
return [PieChart(None, **self._chart_data())]
return []
def get_chart(self, rows, x_label, y_label, data_provider):
def _get_label_with_percentage(row):
return "%s [%d: %s%%]" % (row[0]["html"], int(row[-2]["html"]), str(int(row[-1]["html"][:-1])))
if isinstance(data_provider, NutritionBirthWeightDetails):
chart = PieChart(
data_provider.chart_title,
"",
[{"label": _get_label_with_percentage(row), "value": int(row[-1]["html"][:-1])} for row in rows[2:]],
["red", "green"],
)
chart.showLabels = False
chart.marginLeft = 20
chart.marginRight = 0
chart.marginBottom = 20
elif isinstance(data_provider, DeliveryPlaceDetailsExtended):
chart = PieChart(
data_provider.chart_title,
"",
[{"label": _get_label_with_percentage(row), "value": int(row[-1]["html"][:-1])} for row in rows[1:]],
)
chart.showLabels = False
elif isinstance(data_provider, (PostnatalCareOverview, ImmunizationOverview)):
chart = MultiBarChart(data_provider.chart_title, x_axis=Axis(x_label), y_axis=Axis(y_label, ".2%"))
chart.rotateLabels = -45
chart.marginBottom = 150
chart.marginLeft = 45
chart.marginRight = 0
if isinstance(data_provider, ImmunizationOverview):
chart.stacked = True
chart.add_dataset(
"Percentage",
[{"x": row[0]["html"], "y": int(row[3]["html"][:-1]) / 100.0} for row in rows],
color="green",
)
chart.add_dataset(
"Dropout Percentage",
[{"x": row[0]["html"], "y": int(row[-1]["html"][:-1]) / 100.0} for row in rows],
color="red",
)
else:
chart.add_dataset(
"Percentage", [{"x": row[0]["html"], "y": int(row[-1]["html"][:-1]) / 100.0} for row in rows]
)
elif isinstance(data_provider, AnteNatalCareServiceOverviewExtended):
chart1 = MultiBarChart("ANC Visits", x_axis=Axis(x_label), y_axis=Axis(y_label, ".2%"))
chart2 = MultiBarChart("Maternal TT & IFA", x_axis=Axis(x_label), y_axis=Axis(y_label, ".2%"))
chart1.rotateLabels = -45
chart2.rotateLabels = -45
chart1.marginBottom = 150
chart2.marginBottom = 150
chart1.marginLeft = 20
chart2.marginLeft = 45
chart1.marginRight = 0
chart2.marginRight = 0
chart1.add_dataset(
"Percentage", [{"x": row[0]["html"], "y": int(row[-1]["html"][:-1]) / 100.0} for row in rows[1:6]]
)
chart2.add_dataset(
"Percentage", [{"x": row[0]["html"], "y": int(row[-1]["html"][:-1]) / 100.0} for row in rows[6:12]]
)
return [chart1, chart2]
elif isinstance(data_provider, ChildrenDeathsByMonth):
chart = MultiBarChart(
data_provider.chart_title, x_axis=Axis(x_label, dateFormat="%B"), y_axis=Axis(y_label, ".2%")
)
chart.rotateLabels = -45
chart.marginBottom = 50
chart.marginLeft = 20
chart.add_dataset("Percentage", [{"x": row[0], "y": int(row[-1]["html"][:-1]) / 100.0} for row in rows])
else:
chart = PieChart(
data_provider.chart_title,
"",
[{"label": _get_label_with_percentage(row), "value": int(row[-1]["html"][:-1])} for row in rows],
)
chart.showLabels = False
chart.marginLeft = 20
chart.marginRight = 0
chart.marginBottom = 0
return [chart]
def charts(self):
if 'location_id' in self.request.GET: # hack: only get data if we're loading an actual report
chart = PieChart(_('Current Reporting'), 'current_reporting', [])
chart.data = self.master_pie_chart_data()
return [chart]
def get_chart(self, rows, x_label, y_label, data_provider):
def _get_label_with_percentage(row):
return "%s [%s%%]" % (row[0]['html'], str(int(row[-1]['html'][:-1])))
if isinstance(data_provider, NutritionBirthWeightDetails):
chart = PieChart('BirthWeight', '',
[{'label': "%s [%s%%]" % (row[0]['html'], str(int(row[-1]['html'][:-1]))),
'value': int(row[-1]['html'][:-1])} for row in rows[2:]], ['red', 'green'])
chart.showLabels = False
elif isinstance(data_provider, DeliveryPlaceDetailsExtended):
chart = PieChart('', '', [{'label': _get_label_with_percentage(row),
'value': int(row[-1]['html'][:-1])} for row in rows[1:]])
chart.showLabels = False
elif isinstance(data_provider, (PostnatalCareOverview, ImmunizationOverview)):
chart = MultiBarChart('', x_axis=Axis(x_label), y_axis=Axis(y_label, '.2%'))
chart.rotateLabels = -45
chart.marginBottom = 120
if isinstance(data_provider, ImmunizationOverview):
chart.stacked = True
chart.add_dataset('Percentage',
[{'x': row[0]['html'],
'y': int(row[3]['html'][:-1]) / 100.0} for row in rows],
color='green')
chart.add_dataset('Dropout Percentage',
[{'x': row[0]['html'],
'y': int(row[-1]['html'][:-1]) / 100.0} for row in rows],
color='red')
else:
chart.add_dataset('Percentage',
[{'x': row[0]['html'], 'y':int(row[-1]['html'][:-1]) / 100.0} for row in rows])
elif isinstance(data_provider, AnteNatalCareServiceOverviewExtended):
chart1 = MultiBarChart('', x_axis=Axis(x_label), y_axis=Axis(y_label, '.2%'))
chart2 = MultiBarChart('', x_axis=Axis(x_label), y_axis=Axis(y_label, '.2%'))
chart1.rotateLabels = -45
chart2.rotateLabels = -45
chart1.marginBottom = 120
chart2.marginBottom = 120
chart1.add_dataset('Percentage', [{'x': row[0]['html'],
'y': int(row[-1]['html'][:-1]) / 100.0} for row in rows[1:6]])
chart2.add_dataset('Percentage', [{'x': row[0]['html'],
'y': int(row[-1]['html'][:-1]) / 100.0} for row in rows[6:12]])
return [chart1, chart2]
elif isinstance(data_provider, ChildrenDeathsByMonth):
chart = LineChart('Seasonal Variation of Child Deaths', x_axis=Axis(x_label, dateFormat="%B"),
y_axis=Axis(y_label, '.2%'))
chart.rotateLabels = -45
chart.marginBottom = 120
months_mapping = dict((v, k) for k, v in enumerate(calendar.month_abbr))
chart.add_dataset('Percentage', [{'x': datetime.date(1, months_mapping[row[0][:3]], 1),
'y': int(row[-1]['html'][:-1]) / 100.0} for row in rows])
else:
chart = PieChart('', '', [{'label': "%s [%s%%]" % (row[0]['html'], str(int(row[-1]['html'][:-1]))),
'value': int(row[-1]['html'][:-1])} for row in rows])
chart.showLabels = False
return [chart]
def get_chart(self, rows, x_label, y_label, data_provider):
def _get_label_with_percentage(row):
return "%s [%s%%]" % (row[0], str(float(row[-1]['html'][:-1])))
if isinstance(data_provider,
(ClosedMotherCasesBreakdown, ClosedChildCasesBreakdown)):
chart = PieChart('', '', [{
'label': _get_label_with_percentage(row),
'value': float(row[-1]['html'][:-1])
} for row in rows])
elif isinstance(data_provider, NutritionBirthWeightDetails):
chart = PieChart('BirthWeight', '', [{
'label':
"%s [%s%%]" %
(row[0]['html'], str(float(row[-1]['html'][:-1]))),
'value':
float(row[-1]['html'][:-1])
} for row in rows[1:]], ['red', 'green'])
elif isinstance(data_provider, DeliveryPlaceDetailsExtended):
chart = PieChart('', '', [{
'label': _get_label_with_percentage(row),
'value': float(row[-1]['html'][:-1])
} for row in rows[1:]])
elif isinstance(data_provider,
(PostnatalCareOverview, ImmunizationOverview)):
chart = MultiBarChart('',
x_axis=Axis(x_label),
y_axis=Axis(y_label, '.2%'))
chart.rotateLabels = -45
chart.marginBottom = 120
if isinstance(data_provider, ImmunizationOverview):
chart.stacked = True
chart.add_dataset('Percentage',
[{
'x': row[0]['html'],
'y': float(row[3]['html'][:-1]) / 100
} for row in rows],
color='green')
chart.add_dataset('Dropout Percentage',
[{
'x': row[0]['html'],
'y': float(row[-1]['html'][:-1]) / 100
} for row in rows],
color='red')
else:
chart.add_dataset('Percentage',
[{
'x': row[0]['html'],
'y': float(row[-1]['html'][:-1]) / 100
} for row in rows])
elif isinstance(data_provider, AnteNatalCareServiceOverviewExtended):
chart1 = MultiBarChart('',
x_axis=Axis(x_label),
y_axis=Axis(y_label, '.2%'))
chart2 = MultiBarChart('',
x_axis=Axis(x_label),
y_axis=Axis(y_label, '.2%'))
chart1.rotateLabels = -45
chart2.rotateLabels = -45
chart1.marginBottom = 120
chart2.marginBottom = 120
chart1.add_dataset('Percentage',
[{
'x': row[0]['html'],
'y': float(row[-1]['html'][:-1]) / 100
} for row in rows[1:6]])
chart2.add_dataset('Percentage',
[{
'x': row[0]['html'],
'y': float(row[-1]['html'][:-1]) / 100
} for row in rows[6:12]])
return [chart1, chart2]
elif isinstance(data_provider, ChildrenDeathsByMonth):
chart = LineChart('Seasonal Variation of Child Deaths',
x_axis=Axis(x_label, dateFormat="%B"),
y_axis=Axis(y_label, '.2%'))
chart.rotateLabels = -45
chart.marginBottom = 120
months_mapping = dict(
(v, k) for k, v in enumerate(calendar.month_abbr))
chart.add_dataset(
'Percentage',
[{
'x': datetime.date(1, months_mapping[row[0][:3]], 1),
'y': float(row[-1]['html'][:-1]) / 100
} for row in rows])
else:
chart = PieChart('', '', [{
'label':
"%s [%s%%]" %
(row[0]['html'], str(float(row[-1]['html'][:-1]))),
'value':
float(row[-1]['html'][:-1])
} for row in rows])
return [chart]
