Commit a674a8a0 authored by Filipa Lacerda's avatar Filipa Lacerda

Merge branch 'mw-productivity-analytics-utils-transform-scatter-data' into 'master'

Productivity Analytics: Add transformScatterData utility method

See merge request gitlab-org/gitlab!18249
parents b385dc26 389791f8
......@@ -44,6 +44,49 @@ export const initDateArray = (startDate, endDate) => {
return Array.from({ length: days + 1 }, () => []);
};
/**
* Transforms the raw scatter data into a data strucuture that allows easy access.
* It creates a two dimensional array where each item in the first dimension corresponds to one day (date).
*
* I.e., the first item corresponds to the start date, the second item corresponds to the start date plus one day,
* the last item corresponds to the end date.
*
* For each date, we store an array of individual MRs for the particular date (i.e, the second dimension) in the following form:
* { merged_at: '2019-09-01T04:55:05.757Z', metric: 10 }
*
* Given that startDate=2019-09-01 and endDate=2019-09-03 we receive the following data structure:
* [
* [{ merged_at: '2019-09-01T04:55:05.757Z', metric: 10 }, { merged_at: '2019-09-01T14:12:09.757Z', metric: 8 }, { ... }] // 2019-09-01
* [{ merged_at: '2019-09-02T08:29:33.748Z', metric: 7 }, ... ] // 2019-09-02
* [{ merged_at: '2019-09-03T21:29:49.351Z', metric: 24 }, ... ] // 2019-09-03
* ]
*
* @param {*} data - The raw data received from the API.
* @param {*} startDate - The start date selected by the user minus an additional offset in days (e.g., 30 days).
* @param {*} endDate - The end date selected by the user.
* @returns {Array} The transformed data array (first item corresponds to start date, last item to end date)
*/
export const transformScatterData = (data, startDate, endDate) => {
const result = initDateArray(startDate, endDate);
const totalItems = result.length;
Object.keys(data).forEach(id => {
const mergedAtDate = new Date(data[id].merged_at);
const d = new Date();
d.setDate(mergedAtDate.getDate());
d.setMonth(mergedAtDate.getMonth());
d.setFullYear(mergedAtDate.getFullYear());
const dayDiff = getDayDifference(d, endDate);
if (dayDiff > -1) {
const idx = totalItems - (dayDiff + 1);
result[idx].push(data[id]);
}
});
return result;
};
/**
* Transforms a given data object into an array
* which will be used as series data for the scatterplot chart.
......
......@@ -2,6 +2,7 @@ import {
getLabelsEndpoint,
getMilestonesEndpoint,
initDateArray,
transformScatterData,
getScatterPlotData,
getMedianLineData,
} from 'ee/analytics/productivity_analytics/utils';
......@@ -45,6 +46,29 @@ describe('Productivity Analytics utils', () => {
});
});
describe('transformScatterData', () => {
it('transforms the raw scatter data into a two-dimensional array and groups by date', () => {
const startDate = new Date('2019-08-01');
const endDate = new Date('2019-08-03');
const data = {
1: { merged_at: '2019-08-01T11:10:00.000Z', metric: 10 },
2: { merged_at: '2019-08-01T12:11:00.000Z', metric: 20 },
3: { merged_at: '2019-08-02T13:13:00.000Z', metric: 30 },
4: { merged_at: '2019-08-03T14:14:00.000Z', metric: 40 },
};
const result = transformScatterData(data, startDate, endDate);
const expected = [
[
{ merged_at: '2019-08-01T11:10:00.000Z', metric: 10 },
{ merged_at: '2019-08-01T12:11:00.000Z', metric: 20 },
],
[{ merged_at: '2019-08-02T13:13:00.000Z', metric: 30 }],
[{ merged_at: '2019-08-03T14:14:00.000Z', metric: 40 }],
];
expect(result).toEqual(expected);
});
});
describe('getScatterPlotData', () => {
it('filters out data before given "dateInPast", transforms the data and sorts by date ascending', () => {
const dateInPast = new Date(2019, 7, 9); // '2019-08-09T22:00:00.000Z';
......
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