| library charted.test.chaintransform; |
| |
| import 'package:charted/charts/charts.dart'; |
| import 'package:charted/core/utils.dart'; |
| import 'package:unittest/unittest.dart'; |
| import 'package:observable/observable.dart'; |
| |
| main() { |
| List COLUMNS = [ |
| new ChartColumnSpec(label:'Continent', type:ChartColumnSpec.TYPE_STRING), |
| new ChartColumnSpec(label:'Country', type:ChartColumnSpec.TYPE_STRING), |
| new ChartColumnSpec(label:'City', type:ChartColumnSpec.TYPE_STRING), |
| new ChartColumnSpec(label:'Stats1'), |
| new ChartColumnSpec(label:'Stats2'), |
| new ChartColumnSpec(label:'Stats3') |
| ]; |
| |
| const List DATA = const [ |
| const['America', 'USA', 'LA', 4.51, 7, 1000], |
| const['America', 'USA', 'SF', 9.50, 50, 2000], |
| const['Asia', 'Japan', 'Tokyo', 1.50, 99, 2000], |
| const['Asia', 'Japan', 'Kyoto', 5.10, 66, 4000], |
| const['Asia', 'Taiwan', 'Taipei', 3.50, 127, 1337], |
| const['Asia', 'Japan', 'Osaka', 4.50, 19, 2000], |
| const['Asia', 'Taiwan', 'Tainan', 1.50, 10, 100], |
| const['Europe', 'France', 'Nice', 2.50, 29, 6000], |
| const['Europe', 'France', 'Paris', 6.50, 129, 3000], |
| const['Europe', 'Germany', 'Berlin', 10.99, 999, 10000], |
| const['Europe', 'England', 'London', 2.50, 10, 3000], |
| const['America', 'USA', 'NY', 3.50, 17, 4000], |
| const['America', 'Brazil', 'Brasilia', 1.50, 27, 6000], |
| const['America', 'Argentina', 'Buenos Aires', 5.50, 37, 2000], |
| const['America', 'Brazil', 'Rio de Janeiro', 2.50, 52, 3000], |
| ]; |
| |
| ChartData inputData = new ChartData(COLUMNS, DATA); |
| |
| test('Filter out sum aggregated rows whose stats2 is above 1000', () { |
| AggregationTransformer aggrTransformer = new AggregationTransformer( |
| [0, 1, 2], [3, 4, 5]); |
| FilterDefinition fd = new FilterDefinition(4, (value) => (value <= 1000)); |
| FilterTransformer filterTransformer = new FilterTransformer([fd]); |
| ChartData result = filterTransformer.transform( |
| aggrTransformer.transform(inputData)); |
| // Expected data: |
| // [America, , , 27.0, 190.0, 18000.0] |
| // [Asia, , , 16.1, 321.0, 9437.0] |
| // [Europe, , , 22.49, 1167.0, 22000.0] -- Filtered out |
| |
| // [America, , , 27.0, 190.0, 18000.0] |
| expect(result.rows.elementAt(0).elementAt(3), closeTo(27.01, EPSILON)); |
| expect(result.rows.elementAt(0).elementAt(4), equals(190)); |
| expect(result.rows.elementAt(0).elementAt(5), equals(18000)); |
| |
| // [Asia, , , 16.1, 321.0, 9437.0] |
| expect(result.rows.elementAt(1).elementAt(3), closeTo(16.1, EPSILON)); |
| expect(result.rows.elementAt(1).elementAt(4), equals(321)); |
| expect(result.rows.elementAt(1).elementAt(5), equals(9437)); |
| |
| }); |
| |
| test('Filter out rows whose stats3 is below 4000', () { |
| FilterDefinition fd = new FilterDefinition(5, (value) => (value >= 4000)); |
| FilterTransformer transformer = new FilterTransformer([fd]); |
| ChartData result = transformer.transform(inputData); |
| // Expected data: |
| // ['Asia', 'Japan', 'Kyoto', 5.10, 66, 4000], |
| // ['Europe', 'France', 'Nice', 2.50, 29, 6000], |
| // ['Europe', 'Germany', 'Berlin', 10.99, 999, 10000], |
| // ['America', 'USA', 'NY', 3.50, 17, 4000], |
| // ['America', 'Brazil', 'Brasilia', 1.50, 27, 6000], |
| |
| // ['Asia', 'Japan', 'Kyoto', 5.10, 66, 4000] |
| expect(result.rows.elementAt(0).elementAt(0), equals('Asia')); |
| expect(result.rows.elementAt(0).elementAt(1), equals('Japan')); |
| expect(result.rows.elementAt(0).elementAt(2), equals('Kyoto')); |
| expect(result.rows.elementAt(0).elementAt(3), equals(5.10)); |
| expect(result.rows.elementAt(0).elementAt(4), equals(66)); |
| expect(result.rows.elementAt(0).elementAt(5), equals(4000)); |
| |
| // ['Europe', 'Germany', 'Berlin', 10.99, 999, 10000] |
| expect(result.rows.elementAt(2).elementAt(0), equals('Europe')); |
| expect(result.rows.elementAt(2).elementAt(1), equals('Germany')); |
| expect(result.rows.elementAt(2).elementAt(2), equals('Berlin')); |
| expect(result.rows.elementAt(2).elementAt(3), equals(10.99)); |
| expect(result.rows.elementAt(2).elementAt(4), equals(999)); |
| expect(result.rows.elementAt(2).elementAt(5), equals(10000)); |
| |
| // ['America', 'Brazil', 'Brasilia', 1.50, 27, 6000], |
| expect(result.rows.elementAt(4).elementAt(0), equals('America')); |
| expect(result.rows.elementAt(4).elementAt(1), equals('Brazil')); |
| expect(result.rows.elementAt(4).elementAt(2), equals('Brasilia')); |
| expect(result.rows.elementAt(4).elementAt(3), equals(1.5)); |
| expect(result.rows.elementAt(4).elementAt(4), equals(27)); |
| expect(result.rows.elementAt(4).elementAt(5), equals(6000)); |
| }); |
| |
| test('Grouping by country-continent-city with less fact columns, the ' + |
| 'filter out rows whose stats3 (column4) is less than 8000', () { |
| AggregationTransformer aggrTransformer = new AggregationTransformer( |
| [1, 2, 0], [5, 3]); |
| |
| ChartData aggrResult = aggrTransformer.transform(inputData); |
| // Result at this point: |
| // [Argentina, , , 2000.0, 5.50] |
| // [Brazil, , , 9000.0, 4.00] |
| // [England, , , 3000.0, 2.50] |
| // [France, , , 9000.0, 9.00] |
| // ... |
| |
| FilterDefinition fd = new FilterDefinition(3, (value) => (value >= 8000)); |
| FilterTransformer transformer = new FilterTransformer([fd]); |
| (aggrResult as Observable).deliverChanges(); |
| ChartData result = transformer.transform(aggrResult); |
| |
| // Result at this point: |
| // [Brazil, , , 9000.0, 4.00] |
| // [France, , , 9000.0, 9.00] |
| // ... |
| |
| // Brazil |
| expect(result.rows.elementAt(0).elementAt(3), equals(9000)); |
| expect(result.rows.elementAt(0).elementAt(4), closeTo(4, EPSILON)); |
| |
| // France |
| expect(result.rows.elementAt(1).elementAt(3), equals(9000)); |
| expect(result.rows.elementAt(1).elementAt(4), closeTo(9, EPSILON)); |
| }); |
| |
| } |