def test_sector_data_tooltips_data(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor')
self.assertDictEqual(
data['tooltips_data'], {
"s2": {
"weighed": 182,
"severely_underweight": 4,
"moderately_underweight": 54,
"normal": 124,
"total": 326
},
"s1": {
"weighed": 134,
"severely_underweight": 8,
"moderately_underweight": 36,
"normal": 90,
"total": 144
},
None: {
"weighed": 158,
"severely_underweight": 6,
"moderately_underweight": 45,
"normal": 107,
"total": 235
}
})
def test_sector_data_tooltips_data(self):
self.maxDiff = None
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
'aggregation_level': 4
},
location_id='b1',
loc_level='supervisor')
self.assertDictEqual(
data['tooltips_data'], {
"s2": {
"weighed": 91,
"severely_underweight": 2,
"moderately_underweight": 27,
"normal": 62,
"total": 163
},
"s1": {
"weighed": 67,
"severely_underweight": 4,
"moderately_underweight": 18,
"normal": 45,
"total": 72
}
})
def test_sector_data_keys_length(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor')
self.assertEquals(len(data), 3)
def test_sector_data(self):
self.assertDictEqual(
get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor'),
{
"info":
"Percentage of children between 0-5 years enrolled for ICDS services with weight-for-age"
" less than -2 standard deviations of the WHO Child Growth Standards median."
" <br/><br/>Children who are moderately "
"or severely underweight have a higher risk of mortality",
"tooltips_data": {
u"s2": {
"total": 326,
"severely_underweight": 4,
"moderately_underweight": 74,
"normal": 236
},
u"s1": {
"total": 144,
"severely_underweight": 8,
"moderately_underweight": 42,
"normal": 92
},
None: {
"total": 235,
"severely_underweight": 6,
"moderately_underweight": 58,
"normal": 164
}
},
"chart_data": [{
"color":
MapColors.BLUE,
"classed":
"dashed",
"strokeWidth":
2,
"values": [[None, 0.2723404255319149],
["s1", 0.3472222222222222],
["s2", 0.2392638036809816]],
"key":
""
}]
})
def test_sector_data_keys_length(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor'
)
self.assertEquals(len(data), 3)
def test_sector_data_info(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor')
self.assertEquals(
data['info'],
underweight_children_help_text(age_label="0-5 years", html=True))
def test_sector_data_info(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor'
)
self.assertEquals(
data['info'],
underweight_children_help_text(age_label="0-5 years", html=True)
)
def test_sector_data_info(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor')
self.assertEquals(
data['info'],
"Percentage of children between 0-5 years enrolled for Anganwadi Services with weight-for-age"
" less than -2 standard deviations of the WHO Child Growth Standards median."
" <br/><br/>Children who are moderately "
"or severely underweight have a higher risk of mortality")
def test_sector_data(self):
self.assertDictEqual(
get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
'aggregation_level': 4
},
location_id='b1',
loc_level='supervisor'),
{
"info":
"Percentage of children between 0-5 years enrolled for ICDS services"
" with weight-for-age less than -2 standard deviations"
" of the WHO Child Growth Standards median. <br/><br/>"
"Children who are moderately or severely underweight have a higher risk of mortality",
"tooltips_data": {
"s2": {
"total": 163,
"severely_underweight": 2,
"moderately_underweight": 37,
"normal": 118
},
"s1": {
"total": 72,
"severely_underweight": 4,
"moderately_underweight": 21,
"normal": 46
}
},
"chart_data": [{
"color":
"#006fdf",
"classed":
"dashed",
"strokeWidth":
2,
"values": [["s1", 0.3472222222222222],
["s2", 0.2392638036809816]],
"key":
""
}]
})
def test_sector_data_info(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor')
self.assertEquals(
data['info'],
"Of the total children enrolled for Anganwadi services and weighed, the percentage of children "
"between 0-5 years who were moderately/severely underweight in the current month. "
"<br/><br/>"
"Children who are moderately or severely underweight have a higher risk of mortality. "
)
def test_sector_data_tooltips_data(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor'
)
self.assertDictEqual(
data['tooltips_data'],
{
"s2": {
"weighed": 182,
"severely_underweight": 4,
"moderately_underweight": 54,
"normal": 124,
"total": 326
},
"s1": {
"weighed": 134,
"severely_underweight": 8,
"moderately_underweight": 36,
"normal": 90,
"total": 144
},
None: {
"weighed": 158,
"severely_underweight": 6,
"moderately_underweight": 45,
"normal": 107,
"total": 235
}
}
)
def test_sector_data_chart_data(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor')
self.assertListEqual(data['chart_data'], [{
"color":
MapColors.BLUE,
"classed":
"dashed",
"strokeWidth":
2,
"values": [[None, 0.3227848101265823], ["s1", 0.3283582089552239],
["s2", 0.31868131868131866]],
"key":
""
}])
def test_sector_data_chart_data(self):
data = get_prevalence_of_undernutrition_sector_data(
'icds-cas',
config={
'month': (2017, 5, 1),
'state_id': 'st1',
'district_id': 'd1',
'block_id': 'b1',
},
location_id='b1',
loc_level='supervisor'
)
self.assertListEqual(
data['chart_data'],
[
{
"color": MapColors.BLUE,
"classed": "dashed",
"strokeWidth": 2,
"values": [
[
None,
0.3227848101265823
],
[
"s1",
0.3283582089552239
],
[
"s2",
0.31868131868131866
]
],
"key": ""
}
]
)
