pixie-transformer v1.2.3
Pixie Transformer
Pixie Transformer is transforming a Raw/Response JSON Payload into your expected JSON Payload. It's make your life easy and convenience without any logic required in your code. You just need to configure Dimension, Measurement (1 or Multiple), Additional Dimension Binding, Condition, Sorting, Mathematic Formula and etc. Generated Pixie Dataset payload mostly used for chart series dataset, map dataset, analysis dataset and etc. Depend on your requirement too...
Pixie Transformer, Suitable used for:
- Highcharts
- Chart.js
- Amchart
- Any Visualization Tools and Other(s).
- Any Dataset, You Wish to Transform Easily Without Any Logic.
Table of Contents
Library Interface
Class
- Dimension(column: string, category: TYPE, rename?: string, defaultValue?: any, isIncremental: boolean)
- Measurement(row: string, condition: Array, dimensionListBind: boolean, float?: number, formula?: string, rename?: string, defaultValue?: any, isIncremental: boolean)
- Condition(key: string, condition: CONDITION, match: string | number, rename?: string, toUpperCase?: boolean)
- Aggregate(data: any, dimension: Dimension, measurement: Array, dimensionList?: Array)
- Sort (sortType: SORT, sortProperty?: any, naturalSort?: boolean)
- Pixie (aggregate?: Aggregate, sort?: Sort, debug?: boolean)
Enum
- CONDITION
- TYPE
- SORT
Feature
- Sorting
- Aggregating
- Pixing
Pixie Function
- pixieGroup(pixieData: any, groupByKey: string): Array;
- pixieSumGroupBy(pixieData: any, groupByKey: string, sumKey: string): Array;
- pixieSumBy(pixieData: any, sumKey: string): number
- pixieSumByEachObject(pixieData: any, sumByKey: Array): Array;
- pixieAddKey(pixieData: any, key: any, value: any): Array;
- pixieReplaceValue(pixieData: any, key: any, value: any): Array;
- pixiePluckIncrement(pixieData: any, key: any, rename: any = 'x'): Array;
Installation
npm install pixie-transformer --save
Usage
How to Use It
import { Dimension, Measurement, Aggregate, Sort, Pixie, SORT, TYPE, CONDITION, Condition } from 'pixie-transformer';
First, we need some JSON data
const firstDataset = [
{ projectId: 'omakDec12<V03', date: '2018-12-12', failed: 6.3, firstPass: 194.0, rework: 0.0 },
{ projectId: 'omakDec10<V03', date: '2018-12-10', failed: 1.9, firstPass: 201.1, rework: 10.0 },
{ projectId: 'omakDec03<V03', date: '2018-12-11', failed: 90.0, firstPass: 202.9, rework: 0.0 },
{ projectId: 'ChrSept', date: '2018-12-13', failed: 10.0, firstPass: 250.01, rework: 0.0 }
];
const secondDataset = [
{ timestamp: '2018-10-13T04:57:16.000+00:00', serialNumber: 'Omak_aa181030125646-1', status: 'PASSED', measured: '5.295931E-5' },
{ timestamp: '2018-01-30T04:57:50.000+00:00', serialNumber: 'Omak_ab181030125720-1', status: 'PASSED', measured: '5.306795E-5' },
{ timestamp: '2018-10-31T04:58:25.000+00:00', serialNumber: 'Omak_aa181030125754-1', status: 'pass', measured: '5.306223E-5' },
{ timestamp: '2018-11-30T04:58:59.000+00:00', serialNumber: 'Omak_aa181030125829-1', status: 'FAIL', measured: '5.297646E-5' },
{ timestamp: '2018-09-30T04:59:33.000+00:00', serialNumber: 'Omak_aa181030125902-1', status: 'Anomaly', measured: '5.302792E-5' }
];
Dimension & Measurement
const dimension = new Dimension('date', TYPE.DATE);
const measurementList = [new Measurement('firstPass', CONDITION.NONE)];
const dataAgg = new Aggregate(firstDataset, dimension, measurementList);
const sort = new Sort(SORT.ACS, ['date']);
const pixie = new Pixie(dataAgg, sort);
const pixieData = pixie.getPixie();
Expected Response
pixieData = {
firstPass: [{ x: 1544400000000, y: 201.1 },
{ x: 1544486400000, y: 202.9 },
{ x: 1544572800000, y: 194 },
{ x: 1544659200000, y: 250.01 }]
};
Measurement With Condition & Additional Dimension Binding
const dimension = new Dimension('timestamp', TYPE.DATE);
const conditionList = [
new Condition('status', CONDITION.CONTAIN, 'pass', 'pass'),
new Condition('status', CONDITION.CONTAIN, 'PASS', 'pass'),
new Condition('status', CONDITION.EQUAL, 'Anomaly')
];
const measurementList = [new Measurement('measured', conditionList, true)];
const dimensionList = [new Dimension('serialNumber', TYPE.ANY)];
const dataAgg = new Aggregate(secondDataset, dimension, measurementList, dimensionList);
const sort = new Sort(SORT.ACS, ['timestamp']);
const pixie = new Pixie(dataAgg, sort);
const pixieData = pixie.getPixie();
Expected Response
pixieData = {
measured: {
pass: [
{ x: 1517288270000, y: 0.00005306795, serialNumber: 'Omak_ab181030125720-1' },
{ x: 1539406636000, y: 0.00005295931, serialNumber: 'Omak_aa181030125646-1' },
{ x: 1540961905000, y: 0.00005306223, serialNumber: 'Omak_aa181030125754-1' }
],
Anomaly: [{ x: 1538283573000, y: 0.00005302792, serialNumber: 'Omak_aa181030125902-1' }],
unknown: [{ x: 1543553939000, y: 0.00005297646, serialNumber: 'Omak_aa181030125829-1' }]
}
};
Mathematic Formula
const dimension = new Dimension('date', TYPE.DATE);
const yieldMath = '(firstPass+rework)/(firstPass+rework+failed)*100';
const dimensionList = [new Dimension('projectId', TYPE.ANY)];
const measurementList = [new Measurement('yieldMath', CONDITION.NONE, true, 2, yieldMath)];
const dataAgg = new Aggregate(firstDataset, dimension, measurementList, dimensionList);
const sort = new Sort(SORT.ACS, ['date']);
const pixie = new Pixie(dataAgg, sort);
const pixieData = pixie.getPixie();
Expected Response
pixieData = {
yieldMath: [
{ x: 1544400000000, y: 99.11, projectId: 'omakDec10<V03' },
{ x: 1544486400000, y: 69.27, projectId: 'omakDec03<V03' },
{ x: 1544572800000, y: 96.85, projectId: 'omakDec12<V03' },
{ x: 1544659200000, y: 96.15, projectId: 'ChrSept' }
]
};
Pixie Function
pixieData = pixie.getPixie();
// pixieData from getPixie
pixieData = {
measured: [
{ x: 1517288270000, y: 0.00005306795, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125720-1' },
{ x: 1538283573000, y: 0.00005302792, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1' },
{ x: 1539406636000, y: 0.00005295931, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1' },
{ x: 1540961905000, y: 0.00005306223, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1' },
{ x: 1543553939000, y: 0.00005297646, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1' }
]
};
Last but not least, you can use Pixie Function to transform new Pixie Dataset which doesn’t in your current payload.
pixieGroup(groupByKey: T): Array;
const pixieProtoData = pixieData.measured.pixieGroup('serialNumber');
// OR
const pixieProtoData = pixieGroup(rawPixieData.measured, 'serialNumber');
Expected Response
const pixieProtoData = [
{
serialNumber: 'Omak_aa181030125720-1',
data: [{ x: 1517288270000, y: 0.00005306795, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125720-1' }]
},
{
serialNumber: 'Omak_aa181030125646-1',
data: [
{ x: 1538283573000, y: 0.00005302792, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1' },
{ x: 1539406636000, y: 0.00005295931, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1' }
]
},
{
serialNumber: 'Omak_aa181030125754-1',
data: [
{ x: 1540961905000, y: 0.00005306223, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1' },
{ x: 1543553939000, y: 0.00005297646, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1' }
]
}
];
pixieSumGroupBy(groupByKey: string, sumByKey: T): Array;
const pixieProtoData = pixieData.measured.pixieSumGroupBy('serialNumber', 'nominal');
// OR
const pixieProtoData = pixieSumGroupBy(rawPixieData.measured, 'serialNumber', 'nominal');
Expected Response
const pixieProtoData = [
{ x: 1517288270000, y: 0.00005306795, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125720-1' },
{ x: 1538283573000, y: 0.00005302792, fixtureId: 3080, nominal: 0.0001388, serialNumber: 'Omak_aa181030125646-1' },
{ x: 1540961905000, y: 0.00005306223, fixtureId: 3080, nominal: 0.0001388, serialNumber: 'Omak_aa181030125754-1' }
];
pixieSumBy(sumByKey: T): number;
const pixieProtoData = pixieData.measured.pixieSumBy('fixtureId');
// OR
const pixieProtoData = pixieSumBy(rawPixieData.measured, 'fixtureId');
Expected Response
const pixieProtoData = 15400;
pixieSumByEachObject(sumByKey: Array): Array;
const pixieProtoData = pixieData.measured.pixieSumByEachObject(['fixtureId', 'x']);
// OR
const pixieProtoData = pixieSumByEachObject(rawPixieData.measured, ['fixtureId', 'x']);
Expected Response
const pixieProtoData = [
{ x: 1517288270000, y: 0.00005306795, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125720-1', total: 1517288273080 },
{ x: 1538283573000, y: 0.00005302792, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1', total: 1538283576080 },
{ x: 1539406636000, y: 0.00005295931, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1', total: 1539406639080 },
{ x: 1540961905000, y: 0.00005306223, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1', total: 1540961908080 },
{ x: 1543553939000, y: 0.00005297646, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1', total: 1543553942080 }
];
pixieAddKey(key: T, value: T): Array;
const pixieProtoData = pixieData.measured.pixieAddKey('type', 'scatter');
// OR
const pixieProtoData = pixieAddKey(rawPixieData.measured, 'type', 'scatter');
Expected Response
const pixieProtoData = [
{ type: 'scatter', x: 1517288270000, y: 0.00005306795, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125720-1' },
{ type: 'scatter', x: 1538283573000, y: 0.00005302792, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1' },
{ type: 'scatter', x: 1539406636000, y: 0.00005295931, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1' },
{ type: 'scatter', x: 1540961905000, y: 0.00005306223, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1' },
{ type: 'scatter', x: 1543553939000, y: 0.00005297646, fixtureId: 3080, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1' }
];
pixieReplaceValue(key: T, value: T): Array;
const pixieProtoData = pixieData.measured.pixieReplaceValue('fixtureId', 1530);
// OR
const pixieProtoData = pixieReplaceValue(rawPixieData.measured, 'fixtureId', 1530);
Expected Response
const pixieProtoData = [
{ x: 1517288270000, y: 0.00005306795, fixtureId: 1530, nominal: 0.0000694, serialNumber: 'Omak_aa181030125720-1' },
{ x: 1538283573000, y: 0.00005302792, fixtureId: 1530, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1' },
{ x: 1539406636000, y: 0.00005295931, fixtureId: 1530, nominal: 0.0000694, serialNumber: 'Omak_aa181030125646-1' },
{ x: 1540961905000, y: 0.00005306223, fixtureId: 1530, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1' },
{ x: 1543553939000, y: 0.00005297646, fixtureId: 1530, nominal: 0.0000694, serialNumber: 'Omak_aa181030125754-1' }
];
pixiePluckIncrement(key: T, renameX?: T): Array;
const pixieProtoData = pixieData.measured.pixiePluckIncrement('y');
// OR
const pixieProtoData = pixiePluckIncrement(rawPixieData.measured, 'y');
Expected Response
const pixieProtoData = [
{ x: 0, y: 0.00005306795 },
{ x: 1, y: 0.00005302792 },
{ x: 2, y: 0.00005295931 },
{ x: 3, y: 0.00005306223 },
{ x: 4, y: 0.00005297646 }
];
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
License
MIT @ Brian Koh Ping Weng
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