import React from 'react' import PropTypes from 'prop-types' import { Bar, CartesianGrid, ComposedChart, ErrorBar, ResponsiveContainer, Scatter, XAxis, YAxis } from 'recharts' import { AVAILABLE_METRICS, METRIC_NAMES, METRIC_NAMES_SHORT, METRIC_UNITS } from '../../../util/available-metrics' import { mean, std } from 'mathjs' import approx from 'approximate-number' import { Bullseye, Card, CardActions, CardBody, CardHeader, CardTitle, EmptyState, EmptyStateBody, EmptyStateIcon, Grid, GridItem, Spinner, Title, } from '@patternfly/react-core' import { ErrorCircleOIcon, CubesIcon } from '@patternfly/react-icons' import { usePortfolioScenarios } from '../../../data/project' import NewScenario from '../../projects/NewScenario' import PortfolioResultInfo from './PortfolioResultInfo' const PortfolioResults = ({ portfolioId }) => { const { status, data: scenarios = [] } = usePortfolioScenarios(portfolioId) if (status === 'loading') { return ( Loading Results ) } else if (status === 'error') { return ( Unable to connect There was an error retrieving data. Check your connection and try again. ) } else if (scenarios.length === 0) { return ( No results No results are currently available for this portfolio. Run a scenario to obtain simulation results. ) } const dataPerMetric = {} AVAILABLE_METRICS.forEach((metric) => { dataPerMetric[metric] = scenarios .filter((scenario) => scenario.results) .map((scenario) => ({ name: scenario.name, value: mean(scenario.results[metric]), errorX: std(scenario.results[metric]), })) }) return ( {AVAILABLE_METRICS.map((metric) => ( {METRIC_NAMES[metric]} approx(tick)} label={{ value: METRIC_UNITS[metric], position: 'bottom', offset: 0 }} type="number" /> ))} ) } PortfolioResults.propTypes = { portfolioId: PropTypes.string, } export default PortfolioResults