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": "" } ] )