def test_chart_data_all_locations(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state')
self.assertListEqual(data['all_locations'],
[{
'loc_name': 'st3',
'percent': 0.0
}, {
'loc_name': 'st4',
'percent': 0.0
}, {
'loc_name': 'st5',
'percent': 0.0
}, {
'loc_name': 'st6',
'percent': 0.0
}, {
'loc_name': 'st7',
'percent': 0.0
}, {
'loc_name': 'st2',
'percent': 20.58047493403694
}, {
'loc_name': 'st1',
'percent': 22.71293375394322
}])
def test_chart_data_pink(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state')
self.assertDictEqual(
data['chart_data'][0], {
"color":
ChartColors.PINK,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.0,
"x": 1488326400000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.7478260869565218,
"x": 1491004800000,
"weighed": 3450,
"unweighed": 1655
}, {
"y": 0.7856115107913669,
"x": 1493596800000,
"weighed": 3475,
"unweighed": 1480
}],
"key":
"% Normal"
})
def test_chart_data_top_five(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state')
self.assertListEqual(data['top_five'], [
{
'loc_name': 'st3',
'percent': 0.0
},
{
'loc_name': 'st4',
'percent': 0.0
},
{
'loc_name': 'st5',
'percent': 0.0
},
{
'loc_name': 'st6',
'percent': 0.0
},
{
'loc_name': 'st7',
'percent': 0.0
},
])
def test_chart_data_orange(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state')
self.assertDictEqual(
data['chart_data'][1], {
"color":
ChartColors.ORANGE,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.0,
"x": 1488326400000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.23154848046309695,
"x": 1491004800000,
"weighed": 3455,
"unweighed": 1655
}, {
"y": 0.1867816091954023,
"x": 1493596800000,
"weighed": 3480,
"unweighed": 1465
}],
"key":
"% Moderately Underweight (-2 SD)"
})
def test_chart_data_pink(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state')
self.assertDictEqual(
data['chart_data'][0], {
"color":
ChartColors.PINK,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.0,
"x": 1488326400000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.7467438494934877,
"x": 1491004800000,
"weighed": 3455,
"unweighed": 1655
}, {
"y": 0.7844827586206896,
"x": 1493596800000,
"weighed": 3480,
"unweighed": 1465
}],
"key":
"% Normal"
})
def test_chart_data_red(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state')
self.assertDictEqual(
data['chart_data'][2], {
"color":
ChartColors.RED,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.0,
"x": 1488326400000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.02170767004341534,
"x": 1491004800000,
"weighed": 3455,
"unweighed": 1655
}, {
"y": 0.028735632183908046,
"x": 1493596800000,
"weighed": 3480,
"unweighed": 1465
}],
"key":
"% Severely Underweight (-3 SD) "
})
def test_chart_data_location_type(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1)
},
loc_level='state'
)
self.assertEquals(data['location_type'], 'State')
def test_chart_data_elements_length(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1),
'aggregation_level': 1
},
loc_level='state')
self.assertEqual(len(data['chart_data']), 3)
def test_chart_data_elements_length(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1)
},
loc_level='state'
)
self.assertEquals(len(data['chart_data']), 3)
def test_chart_data_location_type(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1),
'aggregation_level': 1
},
loc_level='state')
self.assertEqual(data['location_type'], 'State')
def test_chart_data_keys_length(self):
self.maxDiff = None
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1),
'aggregation_level': 1
},
loc_level='state')
self.assertEqual(len(data), 5)
def test_chart_data_all_locations(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state')
self.assertListEqual(data['all_locations'], [
{
"loc_name": "st2",
"percent": 20.58047493403694
},
{
"loc_name": "st1",
"percent": 22.71293375394322
},
])
def test_chart_data_bottom_five(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1)
},
loc_level='state'
)
self.assertListEqual(
data['bottom_five'],
[
{'loc_name': 'st6', 'percent': 0.0},
{'loc_name': 'st7', 'percent': 0.0},
{'loc_name': 'st3', 'percent': 0.0},
{'loc_name': 'st2', 'percent': 20.58047493403694},
{'loc_name': 'st1', 'percent': 22.71293375394322}
]
)
def test_chart_data_top_five(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1)
},
loc_level='state'
)
self.assertListEqual(
data['top_five'],
[
{'loc_name': 'st4', 'percent': 0.0},
{'loc_name': 'st5', 'percent': 0.0},
{'loc_name': 'st6', 'percent': 0.0},
{'loc_name': 'st7', 'percent': 0.0},
{'loc_name': 'st3', 'percent': 0.0}
]
)
def test_chart_data_top_five(self):
self.maxDiff = None
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1),
'aggregation_level': 1
},
loc_level='state')
self.assertListEqual(data['top_five'], [{
'loc_name': 'st7',
'percent': 0.0
}, {
'loc_name': 'st2',
'percent': 20.37037037037037
}, {
'loc_name': 'st1',
'percent': 22.71293375394322
}])
def test_chart_data_bottom_five(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state')
self.assertListEqual(data['bottom_five'], [{
'loc_name': 'st5',
'percent': 0.0
}, {
'loc_name': 'st6',
'percent': 0.0
}, {
'loc_name': 'st7',
'percent': 0.0
}, {
'loc_name': 'st2',
'percent': 20.37037037037037
}, {
'loc_name': 'st1',
'percent': 22.71293375394322
}])
def test_chart_data_red(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1)
},
loc_level='state'
)
self.assertDictEqual(
data['chart_data'][2],
{
"color": ChartColors.RED,
"classed": "dashed",
"strokeWidth": 2,
"values": [
{
"y": 0.0,
"x": 1485907200000,
"weighed": 0,
"unweighed": 0
},
{
"y": 0.0,
"x": 1488326400000,
"weighed": 0,
"unweighed": 0
},
{
"y": 0.02170767004341534,
"x": 1491004800000,
"weighed": 3455,
"unweighed": 1655
},
{
"y": 0.028735632183908046,
"x": 1493596800000,
"weighed": 3480,
"unweighed": 1480
}
],
"key": "% Severely Underweight (-3 SD) "
}
)
def test_chart_data_orange(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1)
},
loc_level='state'
)
self.assertDictEqual(
data['chart_data'][1],
{
"color": ChartColors.ORANGE,
"classed": "dashed",
"strokeWidth": 2,
"values": [
{
"y": 0.0,
"x": 1485907200000,
"weighed": 0,
"unweighed": 0
},
{
"y": 0.0,
"x": 1488326400000,
"weighed": 0,
"unweighed": 0
},
{
"y": 0.23154848046309695,
"x": 1491004800000,
"weighed": 3455,
"unweighed": 1655
},
{
"y": 0.1867816091954023,
"x": 1493596800000,
"weighed": 3480,
"unweighed": 1480
}
],
"key": "% Moderately Underweight (-2 SD)"
}
)
def test_chart_data_pink(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1)
},
loc_level='state'
)
self.assertDictEqual(
data['chart_data'][0],
{
"color": ChartColors.PINK,
"classed": "dashed",
"strokeWidth": 2,
"values": [
{
"y": 0.0,
"x": 1485907200000,
"weighed": 0,
"unweighed": 0
},
{
"y": 0.0,
"x": 1488326400000,
"weighed": 0,
"unweighed": 0
},
{
"y": 0.7467438494934877,
"x": 1491004800000,
"weighed": 3455,
"unweighed": 1655
},
{
"y": 0.7844827586206896,
"x": 1493596800000,
"weighed": 3480,
"unweighed": 1480
}
],
"key": "% Normal"
}
)
def test_chart_data_orange(self):
self.maxDiff = None
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1),
'aggregation_level': 1
},
loc_level='state')
self.assertDictEqual(
data['chart_data'][1], {
"color":
ChartColors.ORANGE,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.0,
"x": 1488326400000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.23043478260869565,
"x": 1491004800000,
"weighed": 690,
"unweighed": 331
}, {
"y": 0.1856115107913669,
"x": 1493596800000,
"weighed": 695,
"unweighed": 294
}],
"key":
"% Moderately Underweight (-2 SD)"
})
def test_chart_data_red(self):
self.maxDiff = None
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1),
'aggregation_level': 1
},
loc_level='state')
self.assertDictEqual(
data['chart_data'][2], {
"color":
ChartColors.RED,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.0,
"x": 1488326400000,
"weighed": 0,
"unweighed": 0
}, {
"y": 0.021739130434782608,
"x": 1491004800000,
"weighed": 690,
"unweighed": 331
}, {
"y": 0.02877697841726619,
"x": 1493596800000,
"weighed": 695,
"unweighed": 294
}],
"key":
"% Severely Underweight (-3 SD) "
})
def test_chart_data(self):
self.assertDictEqual(
get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state'),
{
"location_type":
"State",
"bottom_five": [
{
"loc_name": "st1",
"percent": 15.157894736842104
},
{
"loc_name": "st2",
"percent": 15.17509727626459
},
],
"top_five": [
{
"loc_name": "st1",
"percent": 15.157894736842104
},
{
"loc_name": "st2",
"percent": 15.17509727626459
},
],
"chart_data": [{
"color":
ChartColors.PINK,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"all": 0
}, {
"y": 0.0,
"x": 1488326400000,
"all": 0
}, {
"y": 0.5048923679060665,
"x": 1491004800000,
"all": 5110
}, {
"y": 0.5520728008088979,
"x": 1493596800000,
"all": 4945
}],
"key":
"% Normal"
}, {
"color":
ChartColors.ORANGE,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"all": 0
}, {
"y": 0.0,
"x": 1488326400000,
"all": 0
}, {
"y": 0.15655577299412915,
"x": 1491004800000,
"all": 5110
}, {
"y": 0.13144590495449948,
"x": 1493596800000,
"all": 4945
}],
"key":
"% Moderately Underweight (-2 SD)"
}, {
"color":
ChartColors.RED,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"all": 0
}, {
"y": 0.0,
"x": 1488326400000,
"all": 0
}, {
"y": 0.014677103718199608,
"x": 1491004800000,
"all": 5110
}, {
"y": 0.020222446916076844,
"x": 1493596800000,
"all": 4945
}],
"key":
"% Severely Underweight (-3 SD) "
}],
"all_locations": [
{
"loc_name": "st1",
"percent": 15.157894736842104
},
{
"loc_name": "st2",
"percent": 15.17509727626459
},
]
})
def test_chart_data_keys_length(self):
data = get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state')
self.assertEquals(len(data), 5)
def test_chart_data(self):
self.assertDictEqual(
get_prevalence_of_undernutrition_data_chart(
'icds-cas',
config={
'month': (2017, 5, 1)
},
loc_level='state'
),
{
"location_type": "State",
"bottom_five": [
{
"loc_name": "st2",
"percent": 14.648729446935725
},
{
"loc_name": "st1",
"percent": 15.857605177993527
}
],
"top_five": [
{
"loc_name": "st2",
"percent": 14.648729446935725
},
{
"loc_name": "st1",
"percent": 15.857605177993527
}
],
"chart_data": [
{
"color": "#fee0d2",
"classed": "dashed",
"strokeWidth": 2,
"values": [
{
"y": 0.0,
"x": 1485907200000,
"all": 0
},
{
"y": 0.0,
"x": 1488326400000,
"all": 0
},
{
"y": 0.4976228209191759,
"x": 1491004800000,
"all": 6310
},
{
"y": 0.5897435897435898,
"x": 1493596800000,
"all": 6435
}
],
"key": "% Normal"
},
{
"color": "#fc9272",
"classed": "dashed",
"strokeWidth": 2,
"values": [
{
"y": 0.0,
"x": 1485907200000,
"all": 0
},
{
"y": 0.0,
"x": 1488326400000,
"all": 0
},
{
"y": 0.1434231378763867,
"x": 1491004800000,
"all": 6310
},
{
"y": 0.1351981351981352,
"x": 1493596800000,
"all": 6435
}
],
"key": "% Moderately Underweight (-2 SD)"
},
{
"color": "#de2d26",
"classed": "dashed",
"strokeWidth": 2,
"values": [
{
"y": 0.0,
"x": 1485907200000,
"all": 0
},
{
"y": 0.0,
"x": 1488326400000,
"all": 0
},
{
"y": 0.011885895404120444,
"x": 1491004800000,
"all": 6310
},
{
"y": 0.017094017094017096,
"x": 1493596800000,
"all": 6435
}
],
"key": "% Severely Underweight (-3 SD) "
}
],
"all_locations": [
{
"loc_name": "st2",
"percent": 14.648729446935725
},
{
"loc_name": "st1",
"percent": 15.857605177993527
}
]
}
)
def test_chart_data(self):
self.assertDictEqual(
get_prevalence_of_undernutrition_data_chart(
'icds-cas', config={'month': (2017, 5, 1)}, loc_level='state'),
{
"location_type":
"State",
"bottom_five": [{
"loc_name": "st2",
"percent": 19.06614785992218
}, {
"loc_name": "st1",
"percent": 20.63157894736842
}],
"top_five": [{
"loc_name": "st2",
"percent": 19.06614785992218
}, {
"loc_name": "st1",
"percent": 20.63157894736842
}],
"chart_data": [{
"color":
ChartColors.PINK,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"all": 0
}, {
"y": 0.0,
"x": 1488326400000,
"all": 0
}, {
"y": 0.6144814090019569,
"x": 1491004800000,
"all": 5110
}, {
"y": 0.7674418604651163,
"x": 1493596800000,
"all": 4945
}],
"key":
"% Normal"
}, {
"color":
ChartColors.ORANGE,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"all": 0
}, {
"y": 0.0,
"x": 1488326400000,
"all": 0
}, {
"y": 0.1771037181996086,
"x": 1491004800000,
"all": 5110
}, {
"y": 0.17593528816986856,
"x": 1493596800000,
"all": 4945
}],
"key":
"% Moderately Underweight (-2 SD)"
}, {
"color":
ChartColors.RED,
"classed":
"dashed",
"strokeWidth":
2,
"values": [{
"y": 0.0,
"x": 1485907200000,
"all": 0
}, {
"y": 0.0,
"x": 1488326400000,
"all": 0
}, {
"y": 0.014677103718199608,
"x": 1491004800000,
"all": 5110
}, {
"y": 0.022244691607684528,
"x": 1493596800000,
"all": 4945
}],
"key":
"% Severely Underweight (-3 SD) "
}],
"all_locations": [{
"loc_name": "st2",
"percent": 19.06614785992218
}, {
"loc_name": "st1",
"percent": 20.63157894736842
}]
})
