303 lines
9.7 KiB
JavaScript
303 lines
9.7 KiB
JavaScript
import Anomaly from '~/monitoring/components/charts/anomaly.vue';
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import { shallowMount } from '@vue/test-utils';
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import { colorValues } from '~/monitoring/constants';
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import {
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anomalyDeploymentData,
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mockProjectDir,
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anomalyMockGraphData,
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anomalyMockResultValues,
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} from '../../mock_data';
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import { TEST_HOST } from 'helpers/test_constants';
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import MonitorTimeSeriesChart from '~/monitoring/components/charts/time_series.vue';
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const mockWidgets = 'mockWidgets';
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const mockProjectPath = `${TEST_HOST}${mockProjectDir}`;
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jest.mock('~/lib/utils/icon_utils'); // mock getSvgIconPathContent
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const makeAnomalyGraphData = (datasetName, template = anomalyMockGraphData) => {
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const queries = anomalyMockResultValues[datasetName].map((values, index) => ({
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...template.queries[index],
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result: [
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{
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metrics: {},
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values,
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},
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],
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}));
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return { ...template, queries };
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};
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describe('Anomaly chart component', () => {
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let wrapper;
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const setupAnomalyChart = props => {
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wrapper = shallowMount(Anomaly, {
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propsData: { ...props },
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slots: {
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default: mockWidgets,
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},
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sync: false,
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});
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};
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const findTimeSeries = () => wrapper.find(MonitorTimeSeriesChart);
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const getTimeSeriesProps = () => findTimeSeries().props();
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describe('wrapped monitor-time-series-chart component', () => {
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const dataSetName = 'noAnomaly';
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const dataSet = anomalyMockResultValues[dataSetName];
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const inputThresholds = ['some threshold'];
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beforeEach(() => {
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setupAnomalyChart({
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graphData: makeAnomalyGraphData(dataSetName),
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deploymentData: anomalyDeploymentData,
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thresholds: inputThresholds,
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projectPath: mockProjectPath,
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});
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});
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it('is a Vue instance', () => {
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expect(findTimeSeries().exists()).toBe(true);
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expect(findTimeSeries().isVueInstance()).toBe(true);
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});
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describe('receives props correctly', () => {
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describe('graph-data', () => {
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it('receives a single "metric" series', () => {
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const { graphData } = getTimeSeriesProps();
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expect(graphData.queries.length).toBe(1);
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});
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it('receives "metric" with all data', () => {
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const { graphData } = getTimeSeriesProps();
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const query = graphData.queries[0];
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const expectedQuery = makeAnomalyGraphData(dataSetName).queries[0];
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expect(query).toEqual(expectedQuery);
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});
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it('receives the "metric" results', () => {
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const { graphData } = getTimeSeriesProps();
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const { result } = graphData.queries[0];
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const { values } = result[0];
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const [metricDataset] = dataSet;
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expect(values).toEqual(expect.any(Array));
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values.forEach(([, y], index) => {
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expect(y).toBeCloseTo(metricDataset[index][1]);
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});
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});
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});
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describe('option', () => {
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let option;
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let series;
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beforeEach(() => {
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({ option } = getTimeSeriesProps());
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({ series } = option);
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});
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it('contains a boundary band', () => {
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expect(series).toEqual(expect.any(Array));
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expect(series.length).toEqual(2); // 1 upper + 1 lower boundaries
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expect(series[0].stack).toEqual(series[1].stack);
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series.forEach(s => {
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expect(s.type).toBe('line');
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expect(s.lineStyle.width).toBe(0);
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expect(s.lineStyle.color).toMatch(/rgba\(.+\)/);
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expect(s.lineStyle.color).toMatch(s.color);
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expect(s.symbol).toEqual('none');
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});
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});
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it('upper boundary values are stacked on top of lower boundary', () => {
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const [lowerSeries, upperSeries] = series;
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const [, upperDataset, lowerDataset] = dataSet;
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lowerSeries.data.forEach(([, y], i) => {
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expect(y).toBeCloseTo(lowerDataset[i][1]);
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});
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upperSeries.data.forEach(([, y], i) => {
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expect(y).toBeCloseTo(upperDataset[i][1] - lowerDataset[i][1]);
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});
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});
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});
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describe('series-config', () => {
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let seriesConfig;
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beforeEach(() => {
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({ seriesConfig } = getTimeSeriesProps());
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});
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it('display symbols is enabled', () => {
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expect(seriesConfig).toEqual(
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expect.objectContaining({
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type: 'line',
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symbol: 'circle',
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showSymbol: true,
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symbolSize: expect.any(Function),
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itemStyle: {
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color: expect.any(Function),
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},
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}),
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);
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});
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it('does not display anomalies', () => {
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const { symbolSize, itemStyle } = seriesConfig;
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const [metricDataset] = dataSet;
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metricDataset.forEach((v, dataIndex) => {
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const size = symbolSize(null, { dataIndex });
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const color = itemStyle.color({ dataIndex });
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// normal color and small size
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expect(size).toBeCloseTo(0);
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expect(color).toBe(colorValues.primaryColor);
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});
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});
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it('can format y values (to use in tooltips)', () => {
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expect(parseFloat(wrapper.vm.yValueFormatted(0, 0))).toEqual(dataSet[0][0][1]);
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expect(parseFloat(wrapper.vm.yValueFormatted(1, 0))).toEqual(dataSet[1][0][1]);
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expect(parseFloat(wrapper.vm.yValueFormatted(2, 0))).toEqual(dataSet[2][0][1]);
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});
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});
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describe('inherited properties', () => {
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it('"deployment-data" keeps the same value', () => {
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const { deploymentData } = getTimeSeriesProps();
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expect(deploymentData).toEqual(anomalyDeploymentData);
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});
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it('"thresholds" keeps the same value', () => {
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const { thresholds } = getTimeSeriesProps();
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expect(thresholds).toEqual(inputThresholds);
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});
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it('"projectPath" keeps the same value', () => {
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const { projectPath } = getTimeSeriesProps();
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expect(projectPath).toEqual(mockProjectPath);
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});
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});
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});
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});
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describe('with no boundary data', () => {
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const dataSetName = 'noBoundary';
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const dataSet = anomalyMockResultValues[dataSetName];
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beforeEach(() => {
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setupAnomalyChart({
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graphData: makeAnomalyGraphData(dataSetName),
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deploymentData: anomalyDeploymentData,
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});
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});
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describe('option', () => {
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let option;
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let series;
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beforeEach(() => {
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({ option } = getTimeSeriesProps());
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({ series } = option);
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});
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it('does not display a boundary band', () => {
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expect(series).toEqual(expect.any(Array));
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expect(series.length).toEqual(0); // no boundaries
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});
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it('can format y values (to use in tooltips)', () => {
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expect(parseFloat(wrapper.vm.yValueFormatted(0, 0))).toEqual(dataSet[0][0][1]);
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expect(wrapper.vm.yValueFormatted(1, 0)).toBe(''); // missing boundary
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expect(wrapper.vm.yValueFormatted(2, 0)).toBe(''); // missing boundary
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});
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});
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});
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describe('with one anomaly', () => {
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const dataSetName = 'oneAnomaly';
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const dataSet = anomalyMockResultValues[dataSetName];
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beforeEach(() => {
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setupAnomalyChart({
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graphData: makeAnomalyGraphData(dataSetName),
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deploymentData: anomalyDeploymentData,
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});
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});
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describe('series-config', () => {
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it('displays one anomaly', () => {
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const { seriesConfig } = getTimeSeriesProps();
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const { symbolSize, itemStyle } = seriesConfig;
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const [metricDataset] = dataSet;
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const bigDots = metricDataset.filter((v, dataIndex) => {
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const size = symbolSize(null, { dataIndex });
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return size > 0.1;
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});
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const redDots = metricDataset.filter((v, dataIndex) => {
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const color = itemStyle.color({ dataIndex });
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return color === colorValues.anomalySymbol;
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});
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expect(bigDots.length).toBe(1);
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expect(redDots.length).toBe(1);
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});
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});
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});
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describe('with offset', () => {
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const dataSetName = 'negativeBoundary';
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const dataSet = anomalyMockResultValues[dataSetName];
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const expectedOffset = 4; // Lowst point in mock data is -3.70, it gets rounded
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beforeEach(() => {
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setupAnomalyChart({
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graphData: makeAnomalyGraphData(dataSetName),
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deploymentData: anomalyDeploymentData,
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});
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});
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describe('receives props correctly', () => {
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describe('graph-data', () => {
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it('receives a single "metric" series', () => {
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const { graphData } = getTimeSeriesProps();
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expect(graphData.queries.length).toBe(1);
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});
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it('receives "metric" results and applies the offset to them', () => {
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const { graphData } = getTimeSeriesProps();
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const { result } = graphData.queries[0];
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const { values } = result[0];
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const [metricDataset] = dataSet;
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expect(values).toEqual(expect.any(Array));
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values.forEach(([, y], index) => {
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expect(y).toBeCloseTo(metricDataset[index][1] + expectedOffset);
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});
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});
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});
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});
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describe('option', () => {
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it('upper boundary values are stacked on top of lower boundary, plus the offset', () => {
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const { option } = getTimeSeriesProps();
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const { series } = option;
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const [lowerSeries, upperSeries] = series;
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const [, upperDataset, lowerDataset] = dataSet;
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lowerSeries.data.forEach(([, y], i) => {
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expect(y).toBeCloseTo(lowerDataset[i][1] + expectedOffset);
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});
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upperSeries.data.forEach(([, y], i) => {
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expect(y).toBeCloseTo(upperDataset[i][1] - lowerDataset[i][1]);
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});
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});
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});
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});
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});
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