| /* | |
| * Licensed to the Apache Software Foundation (ASF) under one | |
| * or more contributor license agreements. See the NOTICE file | |
| * distributed with this work for additional information | |
| * regarding copyright ownership. The ASF licenses this file | |
| * to you under the Apache License, Version 2.0 (the | |
| * "License"); you may not use this file except in compliance | |
| * with the License. You may obtain a copy of the License at | |
| * | |
| * http://www.apache.org/licenses/LICENSE-2.0 | |
| * | |
| * Unless required by applicable law or agreed to in writing, | |
| * software distributed under the License is distributed on an | |
| * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | |
| * KIND, either express or implied. See the License for the | |
| * specific language governing permissions and limitations | |
| * under the License. | |
| */ | |
| /* global Float32Array */ | |
| import SeriesData from '@/src/data/SeriesData'; | |
| import Model from '@/src/model/Model'; | |
| import { createSourceFromSeriesDataOption, Source, createSource } from '@/src/data/Source'; | |
| import { OptionDataItemObject, | |
| OptionDataValue, | |
| SOURCE_FORMAT_ARRAY_ROWS, | |
| SOURCE_FORMAT_ORIGINAL } from '@/src/util/types'; | |
| import SeriesDimensionDefine from '@/src/data/SeriesDimensionDefine'; | |
| import OrdinalMeta from '@/src/data/OrdinalMeta'; | |
| import DataStore from '@/src/data/DataStore'; | |
| import { DefaultDataProvider } from '@/src/data/helper/dataProvider'; | |
| import { SeriesDataSchema } from '@/src/data/helper/SeriesDataSchema'; | |
| const ID_PREFIX = 'e\0\0'; | |
| const NAME_REPEAT_PREFIX = '__ec__'; | |
| describe('SeriesData', function () { | |
| describe('Data Manipulation', function () { | |
| it('initData 1d', function () { | |
| const data = new SeriesData(['x', 'y'], new Model()); | |
| data.initData([10, 20, 30]); | |
| expect(data.get('x', 0)).toEqual(10); | |
| expect(data.get('x', 1)).toEqual(20); | |
| expect(data.get('x', 2)).toEqual(30); | |
| expect(data.get('y', 1)).toEqual(20); | |
| }); | |
| it('initData 2d', function () { | |
| const data = new SeriesData(['x', 'y'], new Model()); | |
| data.initData([[10, 15], [20, 25], [30, 35]]); | |
| expect(data.get('x', 1)).toEqual(20); | |
| expect(data.get('y', 1)).toEqual(25); | |
| }); | |
| it('initData 2d yx', function () { | |
| const data = new SeriesData(['y', 'x'], new Model()); | |
| data.initData([[10, 15], [20, 25], [30, 35]]); | |
| expect(data.get('x', 1)).toEqual(25); | |
| expect(data.get('y', 1)).toEqual(20); | |
| }); | |
| it('Data with option 1d', function () { | |
| const data = new SeriesData(['x', 'y'], new Model()); | |
| data.initData([ | |
| 1, | |
| { | |
| value: 2, | |
| somProp: 'foo' | |
| } as OptionDataItemObject<OptionDataValue> | |
| ]); | |
| expect(data.getItemModel(1).get('somProp' as any)).toEqual('foo'); | |
| expect(data.getItemModel(0).get('somProp' as any)).toBeNull(); | |
| }); | |
| it('Empty data', function () { | |
| const data = new SeriesData(['x', 'y'], new Model()); | |
| data.initData([1, '-']); | |
| expect(data.get('y', 1)).toBeNaN(); | |
| }); | |
| it('getRawValue', function () { | |
| const data1 = new SeriesData(['x', 'y'], new Model()); | |
| // here construct a new data2 because if we only use one data | |
| // to call initData() twice, data._chunkCount will be accumulated | |
| // to 1 instead of 0. | |
| const data2 = new SeriesData(['x', 'y'], new Model()); | |
| data1.initData([1, 2, 3]); | |
| expect(data1.getItemModel(1).option).toEqual(2); | |
| data2.initData([[10, 15], [20, 25], [30, 35]]); | |
| expect(data2.getItemModel(1).option).toEqual([20, 25]); | |
| }); | |
| it('indexOfRawIndex', function () { | |
| const data = new SeriesData(['x'], new Model()); | |
| data.initData([]); | |
| expect(data.indexOfRawIndex(1)).toEqual(-1); | |
| const data1 = new SeriesData(['x'], new Model()); | |
| data1.initData([0]); | |
| expect(data1.indexOfRawIndex(0)).toEqual(0); | |
| expect(data1.indexOfRawIndex(1)).toEqual(-1); | |
| const data2 = new SeriesData(['x'], new Model()); | |
| data2.initData([0, 1, 2, 3]); | |
| expect(data2.indexOfRawIndex(1)).toEqual(1); | |
| expect(data2.indexOfRawIndex(2)).toEqual(2); | |
| expect(data2.indexOfRawIndex(5)).toEqual(-1); | |
| const data3 = new SeriesData(['x'], new Model()); | |
| data3.initData([0, 1, 2, 3, 4]); | |
| expect(data3.indexOfRawIndex(2)).toEqual(2); | |
| expect(data3.indexOfRawIndex(3)).toEqual(3); | |
| expect(data3.indexOfRawIndex(5)).toEqual(-1); | |
| data3.filterSelf(function (idx) { | |
| return idx >= 2; | |
| }); | |
| expect(data3.indexOfRawIndex(2)).toEqual(0); | |
| }); | |
| it('getDataExtent', function () { | |
| const data = new SeriesData(['x', 'y'], new Model()); | |
| data.initData([1, 2, 3]); | |
| expect(data.getDataExtent('x')).toEqual([1, 3]); | |
| expect(data.getDataExtent('y')).toEqual([1, 3]); | |
| }); | |
| it('Data types', function () { | |
| const data = new SeriesData([{ | |
| name: 'x', | |
| type: 'int' | |
| }, { | |
| name: 'y', | |
| type: 'float' | |
| }], new Model()); | |
| data.initData([[1.1, 1.1]]); | |
| expect(data.get('x', 0)).toEqual(1); | |
| expect(data.get('y', 0)).toBeCloseTo(1.1, 5); | |
| }); | |
| it('map', function () { | |
| const data = new SeriesData(['x', 'y'], new Model()); | |
| data.initData([[10, 15], [20, 25], [30, 35]]); | |
| expect(data.map(['x', 'y'], function (x: number, y: number) { | |
| return [x + 2, y + 2]; | |
| }).mapArray('x', function (x) { | |
| return x; | |
| })).toEqual([12, 22, 32]); | |
| }); | |
| it('mapArray', function () { | |
| const data = new SeriesData(['x', 'y'], new Model()); | |
| data.initData([[10, 15], [20, 25], [30, 35]]); | |
| expect(data.mapArray(['x', 'y'], function (x, y) { | |
| return [x, y]; | |
| })).toEqual([[10, 15], [20, 25], [30, 35]]); | |
| }); | |
| it('filterSelf', function () { | |
| const data = new SeriesData(['x', 'y'], new Model()); | |
| data.initData([[10, 15], [20, 25], [30, 35]]); | |
| expect(data.filterSelf(['x', 'y'], function (x, y) { | |
| return x < 30 && x > 10; | |
| }).mapArray('x', function (x) { | |
| return x; | |
| })).toEqual([20]); | |
| }); | |
| it('dataProvider', function () { | |
| const data = new SeriesData(['x', 'y'], new Model()); | |
| const typedArray = new Float32Array([10, 10, 20, 20]); | |
| const source = createSourceFromSeriesDataOption(typedArray); | |
| data.initData({ | |
| count: function (): number { | |
| return typedArray.length / 2; | |
| }, | |
| getItem: function (idx: number): number[] { | |
| return [typedArray[idx * 2], typedArray[idx * 2 + 1]]; | |
| }, | |
| getSource: function (): Source { | |
| return source; | |
| } | |
| }); | |
| expect(data.mapArray(['x', 'y'], function (x, y) { | |
| return [x, y]; | |
| })).toEqual([[10, 10], [20, 20]]); | |
| expect(data.getRawDataItem(0)).toEqual([10, 10]); | |
| expect(data.getItemModel(0).option).toEqual([10, 10]); | |
| }); | |
| }); | |
| describe('Data store', function () { | |
| it('should guess ordinal correctly', function () { | |
| const source = createSource([['A', 15], ['B', 25], ['C', 35]], { | |
| dimensions: ['A', 'B'], | |
| seriesLayoutBy: null, | |
| sourceHeader: false | |
| }, SOURCE_FORMAT_ORIGINAL); | |
| expect(source.dimensionsDefine[0].type).toEqual('ordinal'); | |
| }); | |
| function createStore() { | |
| const provider = new DefaultDataProvider([['A', 15], ['B', 25], ['C', 35]]); | |
| const store = new DataStore(); | |
| store.initData(provider, [{type: 'ordinal'}, {type: 'float'}]); | |
| return store; | |
| } | |
| it('SeriesData can still get other dims value from store when only part of dims are given.', function () { | |
| const source = createSource( | |
| [['A', 15, 20, 'cat'], ['B', 25, 30, 'mouse'], ['C', 35, 40, 'dog']], | |
| { | |
| dimensions: null, | |
| seriesLayoutBy: null, | |
| sourceHeader: false | |
| }, | |
| SOURCE_FORMAT_ARRAY_ROWS | |
| ); | |
| const store = new DataStore(); | |
| store.initData(new DefaultDataProvider(source), [ | |
| {type: 'ordinal'}, {type: 'float'}, {type: 'float'}, {type: 'ordinal'} | |
| ]); | |
| const schema = new SeriesDataSchema({ | |
| source: source, | |
| dimensions: [ | |
| { type: 'float', name: 'dim1', storeDimIndex: 1 }, | |
| { type: 'ordinal', name: 'dim3', storeDimIndex: 3 } | |
| ], | |
| fullDimensionCount: 2, | |
| dimensionOmitted: true | |
| }); | |
| const data = new SeriesData(schema, null); | |
| data.initData(store); | |
| // Store should be the same. | |
| expect(data.getStore()).toBe(store); | |
| // Get self dim | |
| expect(data.get('dim1', 0)).toEqual(15); | |
| expect(data.get('dim1', 1)).toEqual(25); | |
| // Get other dim | |
| expect(data.getStore().get(0, 0)).toEqual('A'); | |
| expect(data.getStore().get(0, 1)).toEqual('B'); | |
| expect(data.getStore().get(2, 0)).toEqual(20); | |
| expect(data.getStore().get(2, 1)).toEqual(30); | |
| // Get all | |
| expect(data.getValues(['dim3', 'dim1'], 0)).toEqual(['cat', 15]); | |
| expect(data.getValues(1)).toEqual(['B', 25, 30, 'mouse']); | |
| }); | |
| it('SeriesData#cloneShallow should share store', function () { | |
| const store = createStore(); | |
| const dims = [{ type: 'float', name: 'dim2' }]; | |
| const data = new SeriesData(dims, null); | |
| data.initData(store); | |
| const data2 = data.cloneShallow(); | |
| expect(data2.getStore()).toBe(data.getStore()); | |
| }); | |
| }); | |
| describe('Data read', function () { | |
| it('indicesOfNearest', function () { | |
| const data = new SeriesData(['value'], new Model()); | |
| // ---- index: 0 1 2 3 4 5 6 7 | |
| data.initData([10, 20, 30, 35, 40, 40, 35, 50]); | |
| expect(data.indicesOfNearest('value', 24.5)).toEqual([1]); | |
| expect(data.indicesOfNearest('value', 25)).toEqual([1]); | |
| expect(data.indicesOfNearest('value', 25.5)).toEqual([2]); | |
| expect(data.indicesOfNearest('value', 25.5)).toEqual([2]); | |
| expect(data.indicesOfNearest('value', 41)).toEqual([4, 5]); | |
| expect(data.indicesOfNearest('value', 39)).toEqual([4, 5]); | |
| expect(data.indicesOfNearest('value', 41)).toEqual([4, 5]); | |
| expect(data.indicesOfNearest('value', 36)).toEqual([3, 6]); | |
| expect(data.indicesOfNearest('value', 50.6, 0.5)).toEqual([]); | |
| expect(data.indicesOfNearest('value', 50.5, 0.5)).toEqual([7]); | |
| }); | |
| }); | |
| describe('id_and_name', function () { | |
| function makeOneByOneChecker(list: SeriesData) { | |
| let getIdDataIndex = 0; | |
| let getNameDataIndex = 0; | |
| return { | |
| nextIdEqualsTo: function (expectedId: string): void { | |
| expect(list.getId(getIdDataIndex)).toEqual(expectedId); | |
| getIdDataIndex++; | |
| }, | |
| nextNameEqualsTo: function (expectedName: string): void { | |
| expect(list.getName(getNameDataIndex)).toEqual(expectedName); | |
| getNameDataIndex++; | |
| }, | |
| currGetIdDataIndex: function (): number { | |
| return getIdDataIndex; | |
| }, | |
| currGetNameDataIndex: function (): number { | |
| return getNameDataIndex; | |
| } | |
| }; | |
| } | |
| describe('only_name_declared', function () { | |
| function doChecks(list: SeriesData) { | |
| const oneByOne = makeOneByOneChecker(list); | |
| oneByOne.nextIdEqualsTo('a'); | |
| oneByOne.nextIdEqualsTo('b'); | |
| oneByOne.nextIdEqualsTo(`b${NAME_REPEAT_PREFIX}2`); | |
| oneByOne.nextIdEqualsTo('c'); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}4`); | |
| oneByOne.nextIdEqualsTo(`c${NAME_REPEAT_PREFIX}2`); | |
| oneByOne.nextIdEqualsTo('d'); | |
| oneByOne.nextIdEqualsTo(`c${NAME_REPEAT_PREFIX}3`); | |
| oneByOne.nextNameEqualsTo('a'); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo('c'); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo('c'); | |
| oneByOne.nextNameEqualsTo('d'); | |
| oneByOne.nextNameEqualsTo('c'); | |
| } | |
| it('sourceFormatOriginal', function () { | |
| const list = new SeriesData(['x', 'y'], new Model()); | |
| list.initData([ | |
| { value: 10, name: 'a' }, | |
| { value: 20, name: 'b' }, | |
| { value: 30, name: 'b' }, | |
| { value: 40, name: 'c' }, | |
| { value: 50 }, // name not declared | |
| { value: 60, name: 'c' }, | |
| { value: 70, name: 'd' }, | |
| { value: 80, name: 'c' } | |
| ]); | |
| doChecks(list); | |
| }); | |
| it('sourceFormatArrayRows', function () { | |
| const list = new SeriesData( | |
| [ | |
| 'x', | |
| { name: 'q', type: 'ordinal', otherDims: { itemName: 0 } } | |
| ], | |
| new Model() | |
| ); | |
| const source = createSource( | |
| [ | |
| [ 10, 'a' ], | |
| [ 20, 'b' ], | |
| [ 30, 'b' ], | |
| [ 40, 'c' ], | |
| [ 50, null ], | |
| [ 60, 'c' ], | |
| [ 70, 'd' ], | |
| [ 80, 'c' ] | |
| ], | |
| { | |
| seriesLayoutBy: 'column', | |
| sourceHeader: 0, | |
| dimensions: null | |
| }, | |
| SOURCE_FORMAT_ARRAY_ROWS | |
| ); | |
| list.initData(source); | |
| doChecks(list); | |
| }); | |
| }); | |
| describe('id_name_declared_sourceFormat_original', function () { | |
| it('sourceFormatOriginal', function () { | |
| const list = new SeriesData(['x'], new Model()); | |
| const oneByOne = makeOneByOneChecker(list); | |
| list.initData([ | |
| { value: 0, id: 'myId_10' }, | |
| { value: 10, id: 555 }, // numeric id. | |
| { value: 20, id: '666%' }, | |
| { value: 30, id: 'myId_good', name: 'b' }, | |
| { value: 40, name: 'b' }, | |
| { value: 50, id: null }, | |
| { value: 60, id: undefined }, | |
| { value: 70, id: NaN }, | |
| { value: 80, id: '' }, | |
| { value: 90, name: 'b' }, | |
| { value: 100 }, | |
| { value: 110, id: 'myId_better' }, | |
| { value: 120, id: 'myId_better' } // duplicated id. | |
| ]); | |
| oneByOne.nextIdEqualsTo('myId_10'); | |
| oneByOne.nextIdEqualsTo('555'); | |
| oneByOne.nextIdEqualsTo('666%'); | |
| oneByOne.nextIdEqualsTo('myId_good'); | |
| oneByOne.nextIdEqualsTo('b'); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo('NaN'); | |
| oneByOne.nextIdEqualsTo(''); | |
| oneByOne.nextIdEqualsTo(`b${NAME_REPEAT_PREFIX}2`); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo('myId_better'); | |
| oneByOne.nextIdEqualsTo('myId_better'); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| list.appendData([ | |
| { value: 200, id: 'myId_best' }, | |
| { value: 210, id: 999 }, // numeric id. | |
| { value: 220, id: '777px' }, | |
| { value: 230, name: 'b' }, | |
| { value: 240 } | |
| ]); | |
| oneByOne.nextIdEqualsTo('myId_best'); | |
| oneByOne.nextIdEqualsTo('999'); | |
| oneByOne.nextIdEqualsTo('777px'); | |
| oneByOne.nextIdEqualsTo(`b${NAME_REPEAT_PREFIX}3`); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo(''); | |
| list.appendValues([], ['b', 'c', null]); | |
| oneByOne.nextIdEqualsTo(`b${NAME_REPEAT_PREFIX}4`); | |
| oneByOne.nextIdEqualsTo('c'); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo('c'); | |
| oneByOne.nextNameEqualsTo(''); | |
| }); | |
| }); | |
| describe('id_name_declared_sourceFormat_arrayRows', function () { | |
| it('no_ordinalMeta', function () { | |
| testArrayRowsInSource([ | |
| { name: 'x', type: 'number' }, | |
| { name: 'p', type: 'ordinal', otherDims: { itemId: 0 } }, | |
| { name: 'q', type: 'ordinal', otherDims: { itemName: 0 } } | |
| ]); | |
| }); | |
| it('has_ordinalMeta', function () { | |
| const ordinalMetaP = new OrdinalMeta({ | |
| categories: [], | |
| needCollect: true, | |
| deduplication: true | |
| }); | |
| const ordinalMetaQ = new OrdinalMeta({ | |
| categories: [], | |
| needCollect: true, | |
| deduplication: true | |
| }); | |
| testArrayRowsInSource([ | |
| { name: 'x', type: 'number' }, | |
| { name: 'p', type: 'ordinal', otherDims: { itemId: 0 }, ordinalMeta: ordinalMetaP }, | |
| { name: 'q', type: 'ordinal', otherDims: { itemName: 0 }, ordinalMeta: ordinalMetaQ } | |
| ]); | |
| }); | |
| function testArrayRowsInSource(dimensionsInfo: SeriesDimensionDefine[]): void { | |
| const list = new SeriesData(dimensionsInfo, new Model()); | |
| const oneByOne = makeOneByOneChecker(list); | |
| const source = createSource( | |
| [ | |
| [0, 'myId_10', null], | |
| [10, 555, null], // numeric id. | |
| [20, '666%', null], | |
| [30, 'myId_good', 'b'], | |
| [40, null, 'b'], | |
| [50, null, null], | |
| [60, undefined, null], | |
| [70, NaN, null], | |
| [80, '', null], | |
| [90, null, 'b'], | |
| [100, null, null], | |
| [110, 'myId_better', null], | |
| [120, 'myId_better', null] // duplicated id. | |
| ], | |
| { | |
| seriesLayoutBy: 'column', | |
| sourceHeader: 0, | |
| dimensions: null | |
| }, | |
| SOURCE_FORMAT_ARRAY_ROWS | |
| ); | |
| list.initData(source); | |
| oneByOne.nextIdEqualsTo('myId_10'); | |
| oneByOne.nextIdEqualsTo('555'); | |
| oneByOne.nextIdEqualsTo('666%'); | |
| oneByOne.nextIdEqualsTo('myId_good'); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo('NaN'); | |
| oneByOne.nextIdEqualsTo(''); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo('myId_better'); | |
| oneByOne.nextIdEqualsTo('myId_better'); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| list.appendData([ | |
| [ 200, 'myId_best', null ], | |
| [ 210, 999, null ], // numeric id. | |
| [ 220, '777px', null], | |
| [ 230, null, 'b' ], | |
| [ 240, null, null ] | |
| ]); | |
| oneByOne.nextIdEqualsTo('myId_best'); | |
| oneByOne.nextIdEqualsTo('999'); | |
| oneByOne.nextIdEqualsTo('777px'); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo(''); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo(''); | |
| list.appendValues([], ['b', 'c', null]); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextIdEqualsTo(`${ID_PREFIX}${oneByOne.currGetIdDataIndex()}`); | |
| oneByOne.nextNameEqualsTo('b'); | |
| oneByOne.nextNameEqualsTo('c'); | |
| oneByOne.nextNameEqualsTo(''); | |
| } | |
| }); | |
| }); | |
| }); |