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{ |
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"name": "Postgraphile Schema", |
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"schemaPath": "postgraphile-schema.graphql", |
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"extensions": { |
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"endpoints": { |
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"Remote SWAPI GraphQL Endpoint": { |
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"url": "http://localhost:5433/graphql", |
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"headers": { |
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"user-agent": "JS GraphQL" |
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}, |
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"introspect": true |
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} |
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} |
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} |
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} |
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import gql from 'graphql-tag' |
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import possiblePositions from '@/app/euromat/possiblePositions' |
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export function getPositionById (id) { |
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return possiblePositions.find(option => option.id === id).position |
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} |
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export const apolloThesesQuery = gql`{
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allQuestions(orderBy: ROW_ID_ASC) { |
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nodes { |
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category: categoryByCategoryRowId { |
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id |
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title |
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} |
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title |
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rowId |
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id |
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} |
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} |
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}` |
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export const apolloThesesUpdate = data => data.allQuestions.nodes.map(node => ({ |
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id: node.rowId, |
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thesis: { |
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de: node.title |
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}, |
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category: { |
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de: node.category ? node.category.title : '' |
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} |
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})) |
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export const apolloThesesCountQuery = gql`{
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allQuestions { |
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totalCount |
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} |
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}` |
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export const apolloThesesCountUpdate = data => data.allQuestions.totalCount |
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export const apolloPersonsForResultsQuery = gql`{
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allPeople(condition: {role: KANDIMAT_CANDIDATE}) { |
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nodes { |
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id |
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firstName |
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lastName |
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rowId |
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answers: answersByPersonRowId { |
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nodes { |
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id |
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position |
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questionRowId |
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text |
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} |
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} |
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} |
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} |
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}` |
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export const apolloPersonsForResultsUpdate = data => data.allPeople.nodes.map(person => ({ |
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id: person.rowId, |
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name: `${person.firstName} ${person.lastName}`, |
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token: person.firstName.charAt(0) + person.lastName.charAt(0), |
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positions: person.answers.nodes.map(answer => ({ |
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thesis: answer.questionRowId, |
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position: getPositionById(answer.position), |
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statement: { |
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de: answer.text |
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} |
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})) |
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})) |
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export const apolloPersonPositionsQuery = gql` |
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query Person($partyId: Int!) { |
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personByRowId(rowId: $partyId) { |
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id |
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firstName |
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lastName |
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answers: answersByPersonRowId { |
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nodes { |
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id |
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position |
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personRowId |
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text |
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question: questionByQuestionRowId { |
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id |
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rowId |
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} |
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} |
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} |
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} |
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}` |
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export const apolloPersonPositionsUpdate = data => { |
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const person = data.personByRowId |
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return { |
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id: person.rowId, |
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name: `${person.firstName} ${person.lastName}`, |
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token: person.firstName.charAt(0) + person.lastName.charAt(0), |
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theses: person.answers ? person.answers.nodes.map(answer => { |
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const question = answer.question |
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return question ? { |
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id: question.rowId, |
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position: getPositionById(answer.position), |
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statement: answer.text, |
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showStatement: false |
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} : null |
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}) : [] |
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} |
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} |
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import { evalPointsPerThesisPerParty, getPartiesWithScores, getTotalMaxPoints } from '@/app/euromat/scoring' |
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const positionDef = ['positive', 'neutral', 'negative', 'skipped'] |
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// See offficial Rechenmodell of bpb from 2019
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const rechenmodellGrid = [ |
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[0, 0, 0, 0, 0, false], |
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[0, 0, 2, 0, 1, false], |
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[0, 2, 2, 0, 0, false], |
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[0, 0, 0, 0, 2, false], |
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[1, 1, 0, 2, 2, true], |
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[0, 0, 2, 0, 0, false], |
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[0, 2, 2, 1, 0, false], |
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[0, 0, 0, 2, 2, false], |
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[2, 0, 2, 2, 1, false], |
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[1, 2, 2, 2, 1, false], |
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[2, 2, 0, 0, 2, false], |
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[0, 2, 2, 2, 2, false], |
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[0, 2, 0, 0, 3, false], |
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[0, 2, 1, 2, 2, false], |
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[2, 0, 0, 1, 2, false], |
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[2, 0, 0, 0, 2, true], |
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[2, 0, 0, 2, 3, false], |
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[0, 0, 0, 0, 2, false], |
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[2, 0, 0, 0, 1, false], |
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[2, 0, 0, 0, 1, false], |
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[0, 0, 2, 2, 2, true], |
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[2, 2, 1, 2, 2, false], |
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[2, 2, 0, 2, 2, false], |
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[2, 2, 2, 0, 2, false], |
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[0, 2, 0, 2, 1, false], |
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[1, 2, 2, 0, 0, false], |
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[2, 0, 2, 0, 0, false], |
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[2, 0, 0, 2, 2, false], |
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[0, 2, 0, 2, 1, false], |
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[1, 2, 0, 2, 2, false], |
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[0, 1, 2, 0, 0, false], |
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[1, 2, 2, 0, 1, false], |
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[2, 0, 2, 2, 1, false], |
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[0, 2, 2, 2, 2, false], |
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[0, 2, 0, 0, 0, false], |
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[0, 2, 0, 0, 1, false], |
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[2, 2, 2, 2, 0, false], |
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[2, 0, 0, 2, 0, false] |
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] |
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const rechenmodellExpectedTotalScorePerParty = [44, 37, 28, 50] |
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const rechenmodellExpectedMaxScore = 78 |
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const testParties = [1, 2, 3, 4].map(partyId => ({ |
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id: partyId, |
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token: 'idontcare', |
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positions: rechenmodellGrid.map((thesis, index) => ({ |
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thesis: index, |
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position: positionDef[thesis[partyId - 1]] |
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})) |
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})) |
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const testAnswers = rechenmodellGrid.map((thesis, index) => ({ |
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position: positionDef[thesis[4]], |
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thesis: index |
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})) |
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const testEmphasis = rechenmodellGrid |
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.map((thesis, index) => ({ |
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...thesis, |
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thesis: index |
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})) |
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.filter((thesis, index) => thesis[5]) |
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.map(thesis => ({ thesis: thesis.thesis })) |
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describe('The getPartiesWithScores function', () => { |
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it('returns the correct total scores according to the Rechenmodell example of bpb', () => { |
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const resultPartiesWithScores = getPartiesWithScores(testAnswers, testEmphasis, testParties) |
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expect(resultPartiesWithScores.map(party => party.score)).toEqual(rechenmodellExpectedTotalScorePerParty) |
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}) |
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}) |
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describe('The getTotalMaxPoints function', () => { |
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it('returns the correct maximum score points according to the Rechenmodell example of bpb', () => { |
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const resultTotalMaxPoints = getTotalMaxPoints(testAnswers, testEmphasis) |
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expect(resultTotalMaxPoints).toEqual(rechenmodellExpectedMaxScore) |
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}) |
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}) |
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describe('The evalPointsPerThesisPerParty fucntion', () => { |
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test.each` |
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partyPosition | userPosition | expectedScore | expectedScoreWithEmphasis |
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${'negative'} | ${'negative'} | ${2} | ${4} |
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${'negative'} | ${'neutral'} | ${1} | ${2} |
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${'negative'} | ${'positive'} | ${0} | ${0} |
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${'negative'} | ${'skipped'} | ${0} | ${0} |
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${'neutral'} | ${'negative'} | ${1} | ${2} |
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${'neutral'} | ${'neutral'} | ${2} | ${4} |
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${'neutral'} | ${'positive'} | ${1} | ${2} |
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${'neutral'} | ${'skipped'} | ${0} | ${0} |
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${'positive'} | ${'negative'} | ${0} | ${0} |
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${'positive'} | ${'neutral'} | ${1} | ${2} |
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${'positive'} | ${'positive'} | ${2} | ${4} |
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${'positive'} | ${'skipped'} | ${0} | ${0} |
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${'skipped'} | ${'negative'} | ${0} | ${0} |
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${'skipped'} | ${'neutral'} | ${0} | ${0} |
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${'skipped'} | ${'positive'} | ${0} | ${0} |
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${'skipped'} | ${'skipped'} | ${0} | ${0} |
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`('returns the correct score (according to the Rechenmodell of the bpb' +
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' if the party position is $partyPosition and the user\'s position is $userPosition', |
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({ partyPosition, userPosition, expectedScore, expectedScoreWithEmphasis }) => { |
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const resultScore = evalPointsPerThesisPerParty(partyPosition, userPosition, false) |
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const resultScoreWithEmphasis = evalPointsPerThesisPerParty(partyPosition, userPosition, true) |
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expect(resultScore).toEqual(expectedScore) |
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expect(resultScoreWithEmphasis).toEqual(expectedScoreWithEmphasis) |
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}) |
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}) |
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export const IPDATA_URL = 'https://api.ipdata.co/?api-key=test' |
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import { loadContent } from '@/helper/content' |
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import options from './options' |
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import theses from ' | ||||