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[ML] Data Frame Analytics results view: add link to custom visualizations for viewing scatterplot charts (#149647)
## Summary This PR adds a link to the custom visualization UI from scatterplot matrix charts in the data frame analytics job wizard and results views. This allows you to view the data and edit the visualization inside the custom visualization editor, and then save it to a dashboard to explore the data alongside other contextual information. <img width="884" alt="image" src="https://user-images.githubusercontent.com/7405507/215125288-9d5527fa-6074-42bd-98f1-2c04cd025432.png"> Related meta issue: https://github.com/elastic/kibana/issues/131551 ### Checklist Delete any items that are not applicable to this PR. - [ ] Any text added follows [EUI's writing guidelines](https://elastic.github.io/eui/#/guidelines/writing), uses sentence case text and includes [i18n support](https://github.com/elastic/kibana/blob/main/packages/kbn-i18n/README.md) - [ ] [Documentation](https://www.elastic.co/guide/en/kibana/master/development-documentation.html) was added for features that require explanation or tutorials - [ ] [Unit or functional tests](https://www.elastic.co/guide/en/kibana/master/development-tests.html) were updated or added to match the most common scenarios - [ ] Any UI touched in this PR is usable by keyboard only (learn more about [keyboard accessibility](https://webaim.org/techniques/keyboard/)) - [ ] Any UI touched in this PR does not create any new axe failures (run axe in browser: [FF](https://addons.mozilla.org/en-US/firefox/addon/axe-devtools/), [Chrome](https://chrome.google.com/webstore/detail/axe-web-accessibility-tes/lhdoppojpmngadmnindnejefpokejbdd?hl=en-US)) - [ ] If a plugin configuration key changed, check if it needs to be allowlisted in the cloud and added to the [docker list](https://github.com/elastic/kibana/blob/main/src/dev/build/tasks/os_packages/docker_generator/resources/base/bin/kibana-docker) - [ ] This renders correctly on smaller devices using a responsive layout. (You can test this [in your browser](https://www.browserstack.com/guide/responsive-testing-on-local-server)) - [ ] This was checked for [cross-browser compatibility](https://www.elastic.co/support/matrix#matrix_browsers) --------- Co-authored-by: Kibana Machine <42973632+kibanamachine@users.noreply.github.com>
This commit is contained in:
Melissa Alvarez
GitHub
parent
a32b5a450a
commit
e534d87843
6 changed files with 203 additions and 23 deletions
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@ -12,8 +12,12 @@ import { __IntlProvider as IntlProvider } from '@kbn/i18n-react';
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import { euiLightVars as euiThemeLight } from '@kbn/ui-theme';
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import { createFilterManagerMock } from '@kbn/data-plugin/public/query/filter_manager/filter_manager.mock';
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import { ScatterplotMatrix } from './scatterplot_matrix';
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const mockFilterManager = createFilterManagerMock();
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const mockEsSearch = jest.fn((body) => ({
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hits: { hits: [{ fields: { x: [1], y: [2] } }, { fields: { x: [2], y: [3] } }] },
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}));
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@ -21,6 +25,26 @@ jest.mock('../../contexts/kibana', () => ({
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useMlApiContext: () => ({
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esSearch: mockEsSearch,
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}),
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useMlKibana: () => ({
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services: {
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application: {
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navigateToApp: jest.fn(),
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},
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data: {
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query: {
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filterManager: mockFilterManager,
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timefilter: {
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timefilter: {
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getTime: jest.fn(() => {
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return { from: '', to: '' };
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}),
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getRefreshInterval: jest.fn(),
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},
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},
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},
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},
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},
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}),
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}));
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const mockEuiTheme = euiThemeLight;
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@ -5,9 +5,9 @@
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* 2.0.
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*/
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import React, { useMemo, useEffect, useState, FC } from 'react';
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import React, { useMemo, useEffect, useState, FC, useCallback } from 'react';
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import type * as estypes from '@elastic/elasticsearch/lib/api/typesWithBodyKey';
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import rison from '@kbn/rison';
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import {
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EuiCallOut,
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@ -17,12 +17,14 @@ import {
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EuiFlexItem,
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EuiFormRow,
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EuiIconTip,
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EuiLink,
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EuiSelect,
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EuiSpacer,
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EuiSwitch,
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} from '@elastic/eui';
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import { i18n } from '@kbn/i18n';
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import { Query } from '@kbn/data-plugin/common/query';
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import { DataView } from '@kbn/data-views-plugin/public';
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import { stringHash } from '@kbn/ml-string-hash';
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@ -31,7 +33,7 @@ import { isRuntimeMappings } from '../../../../common/util/runtime_field_utils';
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import { RuntimeMappings } from '../../../../common/types/fields';
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import { getCombinedRuntimeMappings } from '../data_grid';
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import { useMlApiContext } from '../../contexts/kibana';
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import { useMlApiContext, useMlKibana } from '../../contexts/kibana';
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import { getProcessedFields } from '../data_grid';
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import { useCurrentEuiTheme } from '../color_range_legend';
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@ -101,6 +103,7 @@ export interface ScatterplotMatrixProps {
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searchQuery?: estypes.QueryDslQueryContainer;
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runtimeMappings?: RuntimeMappings;
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indexPattern?: DataView;
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query?: Query;
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}
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export const ScatterplotMatrix: FC<ScatterplotMatrixProps> = ({
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@ -112,9 +115,13 @@ export const ScatterplotMatrix: FC<ScatterplotMatrixProps> = ({
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searchQuery,
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runtimeMappings,
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indexPattern,
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query,
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}) => {
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const { esSearch } = useMlApiContext();
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const kibana = useMlKibana();
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const {
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services: { application, data },
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} = kibana;
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// dynamicSize is optionally used for outlier charts where the scatterplot marks
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// are sized according to outlier_score
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const [dynamicSize, setDynamicSize] = useState<boolean>(false);
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@ -142,6 +149,8 @@ export const ScatterplotMatrix: FC<ScatterplotMatrixProps> = ({
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{ items: any[]; backgroundItems: any[]; columns: string[]; messages: string[] } | undefined
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>();
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const { euiTheme } = useCurrentEuiTheme();
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// formats the array of field names for EuiComboBox
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const fieldOptions = useMemo(
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() =>
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@ -172,7 +181,77 @@ export const ScatterplotMatrix: FC<ScatterplotMatrixProps> = ({
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setDynamicSize(!dynamicSize);
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};
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const { euiTheme } = useCurrentEuiTheme();
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const getCustomVisualizationLink = useCallback(() => {
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const { columns } = splom!;
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const outlierScoreField =
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resultsField !== undefined ? `${resultsField}.${OUTLIER_SCORE_FIELD}` : undefined;
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const vegaSpec = getScatterplotMatrixVegaLiteSpec(
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true,
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[],
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[],
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columns,
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euiTheme,
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resultsField,
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color,
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legendType,
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dynamicSize
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);
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vegaSpec.$schema = 'https://vega.github.io/schema/vega-lite/v5.json';
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vegaSpec.title = `Scatterplot matrix for ${index}`;
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const fieldsToFetch = [
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...columns,
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// Add outlier_score field in fetch if it's available so custom visualization can use it
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...(outlierScoreField ? [outlierScoreField] : []),
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// Add field to color code by in fetch so custom visualization can use it - usually for classfication jobs
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...(color ? [color] : []),
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];
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vegaSpec.data = {
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url: {
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'%context%': true,
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...(indexPattern?.timeFieldName
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? { ['%timefield%']: `${indexPattern?.timeFieldName}` }
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: {}),
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index,
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body: {
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fields: fieldsToFetch,
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size: fetchSize,
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_source: false,
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},
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},
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format: { property: 'hits.hits' },
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};
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const globalState = encodeURIComponent(
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rison.encode({
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filters: data.query.filterManager.getFilters(),
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refreshInterval: data.query.timefilter.timefilter.getRefreshInterval(),
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time: data.query.timefilter.timefilter.getTime(),
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})
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);
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const appState = encodeURIComponent(
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rison.encode({
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filters: [],
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linked: false,
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query,
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uiState: {},
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vis: {
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aggs: [],
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params: {
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spec: JSON.stringify(vegaSpec, null, 2),
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},
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},
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})
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);
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const basePath = `/create?type=vega&_g=${globalState}&_a=${appState}`;
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return { path: basePath };
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// eslint-disable-next-line react-hooks/exhaustive-deps
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}, [splom]);
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useEffect(() => {
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if (fields.length === 0) {
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@ -316,6 +395,7 @@ export const ScatterplotMatrix: FC<ScatterplotMatrixProps> = ({
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const { items, backgroundItems, columns } = splom;
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return getScatterplotMatrixVegaLiteSpec(
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false,
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items,
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backgroundItems,
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columns,
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@ -442,6 +522,29 @@ export const ScatterplotMatrix: FC<ScatterplotMatrixProps> = ({
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</EuiFormRow>
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</EuiFlexItem>
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)}
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{splom ? (
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<EuiFlexItem grow={false}>
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<EuiLink
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onClick={async () => {
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const customVisLink = getCustomVisualizationLink();
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await application.navigateToApp('visualize#', {
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path: customVisLink.path,
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openInNewTab: false,
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});
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}}
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data-test-subj="mlSplomoExploreInCustomVisualizationLink"
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>
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<EuiIconTip
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content={i18n.translate('xpack.ml.splom.exploreInCustomVisualizationLabel', {
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defaultMessage:
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'Explore scatterplot charts in Vega based custom visualization',
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})}
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type="visVega"
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size="l"
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/>
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</EuiLink>
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</EuiFlexItem>
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) : null}
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</EuiFlexGroup>
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{splom.messages.length > 0 && (
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@ -26,7 +26,7 @@ import {
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describe('getColorSpec()', () => {
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it('should return only user selection conditions and the default color for non-outlier specs', () => {
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const colorSpec = getColorSpec(euiThemeLight);
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const colorSpec = getColorSpec(false, euiThemeLight);
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expect(colorSpec).toEqual({
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condition: [{ selection: USER_SELECTION }, { selection: SINGLE_POINT_CLICK }],
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@ -35,7 +35,7 @@ describe('getColorSpec()', () => {
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});
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it('should return user selection condition and conditional spec for outliers', () => {
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const colorSpec = getColorSpec(euiThemeLight, 'outlier_score');
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const colorSpec = getColorSpec(false, euiThemeLight, 'outlier_score');
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expect(colorSpec).toEqual({
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condition: {
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@ -53,7 +53,13 @@ describe('getColorSpec()', () => {
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it('should return user selection condition and a field based spec for non-outlier specs with legendType supplied', () => {
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const colorName = 'the-color-field';
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const colorSpec = getColorSpec(euiThemeLight, undefined, colorName, LEGEND_TYPES.NOMINAL);
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const colorSpec = getColorSpec(
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false,
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euiThemeLight,
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undefined,
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colorName,
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LEGEND_TYPES.NOMINAL
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);
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expect(colorSpec).toEqual({
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condition: {
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@ -70,10 +76,18 @@ describe('getColorSpec()', () => {
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});
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describe('getScatterplotMatrixVegaLiteSpec()', () => {
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const forCustomLink = false;
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it('should return the default spec for non-outliers without a legend', () => {
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const data = [{ x: 1, y: 1 }];
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const vegaLiteSpec = getScatterplotMatrixVegaLiteSpec(data, [], ['x', 'y'], euiThemeLight);
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const vegaLiteSpec = getScatterplotMatrixVegaLiteSpec(
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forCustomLink,
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data,
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[],
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['x', 'y'],
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euiThemeLight
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);
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const specForegroundLayer = vegaLiteSpec.spec.layer[0];
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// A valid Vega Lite spec shouldn't throw an error when compiled.
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@ -103,6 +117,7 @@ describe('getScatterplotMatrixVegaLiteSpec()', () => {
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const data = [{ x: 1, y: 1 }];
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const vegaLiteSpec = getScatterplotMatrixVegaLiteSpec(
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forCustomLink,
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data,
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[],
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['x', 'y'],
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@ -151,6 +166,7 @@ describe('getScatterplotMatrixVegaLiteSpec()', () => {
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const data = [{ x: 1, y: 1 }];
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const vegaLiteSpec = getScatterplotMatrixVegaLiteSpec(
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forCustomLink,
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data,
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[],
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['x', 'y'],
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@ -196,6 +212,7 @@ describe('getScatterplotMatrixVegaLiteSpec()', () => {
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const data = [{ ['x.a']: 1, ['y[a]']: 1 }];
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const vegaLiteSpec = getScatterplotMatrixVegaLiteSpec(
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forCustomLink,
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data,
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[],
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['x.a', 'y[a]'],
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@ -29,8 +29,10 @@ export const COLOR_SELECTION = euiPaletteColorBlind()[2];
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export const COLOR_RANGE_OUTLIER = [euiPaletteColorBlind()[1], euiPaletteColorBlind()[2]];
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export const COLOR_RANGE_NOMINAL = euiPaletteColorBlind({ rotations: 2 });
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export const COLOR_RANGE_QUANTITATIVE = euiPalettePositive(5);
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const CUSTOM_VIS_FIELDS_PATH = 'fields';
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export const getColorSpec = (
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forCustomVisLink: boolean,
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euiTheme: typeof euiThemeLight,
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escapedOutlierScoreField?: string,
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color?: string,
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@ -58,7 +60,10 @@ export const getColorSpec = (
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return {
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condition: {
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selection: USER_SELECTION,
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field: getEscapedVegaFieldName(color ?? '00FF00'),
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field: `${forCustomVisLink ? `${CUSTOM_VIS_FIELDS_PATH}.` : ''}${getEscapedVegaFieldName(
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color ?? '00FF00'
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// When creating the custom link - this field is returned in an array so we need to access it
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)}${forCustomVisLink ? '[0]' : ''}`,
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type: legendType,
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scale: {
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range:
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@ -76,6 +81,7 @@ export const getColorSpec = (
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};
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const getVegaSpecLayer = (
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forCustomVisLink: boolean,
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isBackground: boolean,
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values: VegaValue[],
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colorSpec: any,
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@ -117,7 +123,8 @@ const getVegaSpecLayer = (
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};
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return {
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data: { values: [...values] },
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// Don't need to add static data for custom vis links
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...(forCustomVisLink ? {} : { data: { values: [...values] } }),
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mark: {
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...(outliers && dynamicSize
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? {
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@ -133,7 +140,9 @@ const getVegaSpecLayer = (
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? {
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transform: [
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{
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calculate: `datum['${escapedOutlierScoreField}'] >= mlOutlierScoreThreshold.cutoff`,
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calculate: `datum${
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forCustomVisLink ? `.${CUSTOM_VIS_FIELDS_PATH}` : ''
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}['${escapedOutlierScoreField}'] >= mlOutlierScoreThreshold.cutoff`,
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as: 'is_outlier',
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},
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],
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@ -154,7 +163,9 @@ const getVegaSpecLayer = (
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opacity: {
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condition: {
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value: 1,
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test: `(datum['${escapedOutlierScoreField}'] >= mlOutlierScoreThreshold.cutoff)`,
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test: `(datum${
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forCustomVisLink ? `.${CUSTOM_VIS_FIELDS_PATH}` : ''
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}['${escapedOutlierScoreField}'] >= mlOutlierScoreThreshold.cutoff)`,
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},
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value: 0.5,
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},
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@ -162,19 +173,27 @@ const getVegaSpecLayer = (
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: {}),
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...(outliers
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? {
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order: { field: escapedOutlierScoreField },
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order: {
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field: `${
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forCustomVisLink ? `${CUSTOM_VIS_FIELDS_PATH}.` : ''
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}${escapedOutlierScoreField}`,
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},
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size: {
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...(!dynamicSize
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? {
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condition: {
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value: 40,
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test: `(datum['${escapedOutlierScoreField}'] >= mlOutlierScoreThreshold.cutoff)`,
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test: `(datum${
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forCustomVisLink ? `.${CUSTOM_VIS_FIELDS_PATH}` : ''
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}['${escapedOutlierScoreField}'] >= mlOutlierScoreThreshold.cutoff)`,
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},
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value: 8,
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}
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: {
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type: LEGEND_TYPES.QUANTITATIVE,
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field: escapedOutlierScoreField,
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field: `${
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forCustomVisLink ? `${CUSTOM_VIS_FIELDS_PATH}.` : ''
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}${escapedOutlierScoreField}`,
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scale: {
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type: 'linear',
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range: [8, 200],
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@ -197,7 +216,14 @@ const getVegaSpecLayer = (
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tooltip: [
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...(color !== undefined
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? // @ts-ignore
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[{ type: colorSpec.condition.type, field: getEscapedVegaFieldName(color) }]
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[
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{
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type: colorSpec.condition.type,
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field: `${
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forCustomVisLink ? `${CUSTOM_VIS_FIELDS_PATH}.` : ''
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}${getEscapedVegaFieldName(color)}`,
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},
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]
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: []),
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...vegaColumns.map((d) => ({
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type: LEGEND_TYPES.QUANTITATIVE,
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@ -207,7 +233,9 @@ const getVegaSpecLayer = (
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? [
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{
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type: LEGEND_TYPES.QUANTITATIVE,
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field: escapedOutlierScoreField,
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field: `${
|
||||
forCustomVisLink ? `${CUSTOM_VIS_FIELDS_PATH}.` : ''
|
||||
}${escapedOutlierScoreField}`,
|
||||
format: '.3f',
|
||||
},
|
||||
]
|
||||
|
|
@ -215,21 +243,22 @@ const getVegaSpecLayer = (
|
|||
],
|
||||
},
|
||||
...(isBackground ? {} : selection),
|
||||
width: SCATTERPLOT_SIZE,
|
||||
height: SCATTERPLOT_SIZE,
|
||||
...(forCustomVisLink ? {} : { width: SCATTERPLOT_SIZE }),
|
||||
...(forCustomVisLink ? {} : { height: SCATTERPLOT_SIZE }),
|
||||
};
|
||||
};
|
||||
|
||||
// Escapes the characters .[] in field names with double backslashes
|
||||
// since VEGA treats dots/brackets in field names as nested values.
|
||||
// See https://vega.github.io/vega-lite/docs/field.html for details.
|
||||
function getEscapedVegaFieldName(fieldName: string) {
|
||||
return fieldName.replace(/([\.|\[|\]])/g, '\\$1');
|
||||
function getEscapedVegaFieldName(fieldName: string, prependString: string = '') {
|
||||
return `${prependString}${fieldName.replace(/([\.|\[|\]])/g, '\\$1')}`;
|
||||
}
|
||||
|
||||
type VegaValue = Record<string, string | number>;
|
||||
|
||||
export const getScatterplotMatrixVegaLiteSpec = (
|
||||
forCustomVisLink: boolean,
|
||||
values: VegaValue[],
|
||||
backgroundValues: VegaValue[],
|
||||
columns: string[],
|
||||
|
|
@ -240,12 +269,15 @@ export const getScatterplotMatrixVegaLiteSpec = (
|
|||
dynamicSize?: boolean
|
||||
): TopLevelSpec => {
|
||||
const vegaValues = values;
|
||||
const vegaColumns = columns.map(getEscapedVegaFieldName);
|
||||
const vegaColumns = columns.map((column) =>
|
||||
getEscapedVegaFieldName(column, forCustomVisLink ? 'fields.' : '')
|
||||
);
|
||||
const outliers = resultsField !== undefined;
|
||||
|
||||
const escapedOutlierScoreField = `${resultsField}\\.${OUTLIER_SCORE_FIELD}`;
|
||||
|
||||
const colorSpec = getColorSpec(
|
||||
forCustomVisLink,
|
||||
euiTheme,
|
||||
resultsField && escapedOutlierScoreField,
|
||||
color,
|
||||
|
|
@ -282,6 +314,7 @@ export const getScatterplotMatrixVegaLiteSpec = (
|
|||
spec: {
|
||||
layer: [
|
||||
getVegaSpecLayer(
|
||||
forCustomVisLink,
|
||||
false,
|
||||
vegaValues,
|
||||
colorSpec,
|
||||
|
|
@ -298,6 +331,7 @@ export const getScatterplotMatrixVegaLiteSpec = (
|
|||
if (backgroundValues.length) {
|
||||
schema.spec.layer.unshift(
|
||||
getVegaSpecLayer(
|
||||
forCustomVisLink,
|
||||
true,
|
||||
backgroundValues,
|
||||
colorSpec,
|
||||
|
|
|
|||
|
|
@ -225,6 +225,7 @@ export const ExplorationPageWrapper: FC<Props> = ({
|
|||
<ExpandableSectionSplom
|
||||
fields={scatterplotFieldOptions}
|
||||
index={jobConfig?.dest.index}
|
||||
indexPattern={indexPattern}
|
||||
color={
|
||||
jobType === ANALYSIS_CONFIG_TYPE.REGRESSION ||
|
||||
jobType === ANALYSIS_CONFIG_TYPE.CLASSIFICATION
|
||||
|
|
|
|||
|
|
@ -145,6 +145,7 @@ export const OutlierExploration: FC<ExplorationProps> = React.memo(({ jobId }) =
|
|||
index={jobConfig?.dest.index}
|
||||
resultsField={jobConfig?.dest.results_field}
|
||||
searchQuery={searchQuery}
|
||||
query={query}
|
||||
/>
|
||||
)}
|
||||
{showLegacyFeatureInfluenceFormatCallout && (
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue