mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-10-03 12:08:11 +08:00
refactoring - immutable crossfilter (#647)
* immutable crossfilter * PR review changes
This commit is contained in:
@@ -3,6 +3,7 @@ import * as Universe from "../../../src/util/stateManager/universe";
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import * as World from "../../../src/util/stateManager/world";
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import * as Dataframe from "../../../src/util/dataframe";
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import Crossfilter from "../../../src/util/typedCrossfilter";
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import { DimTypes } from "../../../src/util/typedCrossfilter/crossfilter";
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import * as REST from "./sampleResponses";
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import {
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obsAnnoDimensionName,
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@@ -26,15 +27,15 @@ const defaultBigBang = () => {
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/* create world */
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const world = World.createWorldFromEntireUniverse(universe);
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/* create crossfilter */
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const crossfilter = Crossfilter(world.obsAnnotations);
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/* create dimension map */
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const dimensionMap = World.createObsDimensionMap(crossfilter, world);
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const crossfilter = World.createObsDimensions(
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new Crossfilter(world.obsAnnotations),
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world
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);
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return {
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universe,
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world,
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crossfilter,
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dimensionMap
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crossfilter
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};
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};
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@@ -71,13 +72,16 @@ describe("createWorldFromCurrentSelection", () => {
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const {
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universe,
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world: originalWorld,
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crossfilter,
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dimensionMap
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crossfilter: originalCrossfilter
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} = defaultBigBang();
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/* mock a selection */
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dimensionMap[obsAnnoDimensionName("field1")].filterRange([0, 5]);
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dimensionMap[obsAnnoDimensionName("field3")].filterExact(false);
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let crossfilter = originalCrossfilter
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.select(obsAnnoDimensionName("field1"), { mode: "range", lo: 0, hi: 5 })
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.select(obsAnnoDimensionName("field3"), {
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mode: "exact",
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values: [false]
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});
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/* create the world from the selection */
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const world = World.createWorldFromCurrentSelection(
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@@ -86,7 +90,7 @@ describe("createWorldFromCurrentSelection", () => {
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crossfilter
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);
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expect(world).toBeDefined();
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expect(world.nObs).toEqual(crossfilter.countFiltered());
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expect(world.nObs).toEqual(crossfilter.countSelected());
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/*
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calculate expected values and match against result
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@@ -136,43 +140,32 @@ describe("createObsDimensionMap", () => {
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- check that dimension typing is sane
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*/
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const { dimensionMap } = defaultBigBang();
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const { crossfilter } = defaultBigBang();
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const annotationNames = _.map(
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REST.schema.schema.annotations.obs,
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c => c.name
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);
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const schemaByObsName = _.keyBy(REST.schema.schema.annotations.obs, "name");
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expect(dimensionMap).toBeDefined();
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expect(crossfilter).toBeDefined();
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annotationNames.forEach(name => {
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const dim = dimensionMap[obsAnnoDimensionName(name)];
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const dim = crossfilter.dimensions[obsAnnoDimensionName(name)];
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if (name === "name") {
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expect(dim).toBeUndefined();
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} else {
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const { type } = schemaByObsName[name];
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if (type === "string" || type === "boolean" || type === "categorical") {
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expect(dim).toBeInstanceOf(Crossfilter.EnumDimension);
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expect(dim.dim).toBeInstanceOf(DimTypes.enum);
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} else {
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expect(dim).toBeInstanceOf(Crossfilter.ScalarDimension);
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expect(dim.dim).toBeInstanceOf(DimTypes.scalar);
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}
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}
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});
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expect(dimensionMap[layoutDimensionName("XY")]).toBeInstanceOf(
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Crossfilter.SpatialDimension
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);
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expect(
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crossfilter.dimensions[layoutDimensionName("XY")].dim
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).toBeInstanceOf(DimTypes.spatial);
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});
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});
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describe("createVarDataDimension", () => {
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/* create default universe */
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const { world, crossfilter } = defaultBigBang();
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world.varData = world.varData.withCol(
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"GENE",
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Float32Array.from(_.range(world.nObs))
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);
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const result = World.createVarDataDimension(world, crossfilter, "GENE");
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expect(result).toBeInstanceOf(Crossfilter.ScalarDimension);
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});
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describe("worldEqUniverse", () => {
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const { universe, world } = defaultBigBang();
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const result = World.worldEqUniverse(world, universe);
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@@ -0,0 +1,330 @@
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import _ from "lodash";
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import { polygonContains } from "d3";
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import Crossfilter from "../../../src/util/typedCrossfilter";
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const someData = [
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{
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date: "2011-11-14T16:17:54Z",
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quantity: 2,
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total: 190,
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tip: 100,
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type: "tab",
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productIDs: ["001"],
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coords: [0, 0]
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},
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{
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date: "2011-11-14T16:20:19Z",
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quantity: 2,
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total: 190,
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tip: 100,
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type: "tab",
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productIDs: ["001", "005"],
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coords: [0.4, 0.4]
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},
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{
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date: "2011-11-14T16:28:54Z",
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quantity: 1,
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total: 300,
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tip: 200,
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type: "visa",
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productIDs: ["004", "005"],
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coords: [0.3, 0.1]
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},
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{
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date: "2011-11-14T16:30:43Z",
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quantity: 2,
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total: 90,
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tip: 0,
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type: "tab",
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productIDs: ["001", "002"],
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coords: [0.392, 0.1]
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},
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{
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date: "2011-11-14T16:48:46Z",
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quantity: 2,
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total: 90,
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tip: 0,
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type: "tab",
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productIDs: ["005"],
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coords: [0.7, 0.0482]
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},
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{
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date: "2011-11-14T16:53:41Z",
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quantity: 2,
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total: 90,
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tip: 0,
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type: "tab",
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productIDs: ["001", "004", "005"],
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coords: [0.9999, 1.0]
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},
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{
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date: "2011-11-14T16:54:06Z",
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quantity: 1,
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total: 100,
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tip: 0,
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type: "cash",
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productIDs: ["001", "002", "003", "004", "005"],
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coords: [0.384, 0.6938]
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},
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{
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date: "2011-11-14T16:58:03Z",
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quantity: 2,
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total: 90,
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tip: 0,
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type: "tab",
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productIDs: ["001"],
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coords: [0.4822, 0.482]
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},
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{
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date: "2011-11-14T17:07:21Z",
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quantity: 2,
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total: 90,
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tip: 0,
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type: "tab",
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productIDs: ["004", "005"],
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coords: [0.2234, 0]
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},
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{
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date: "2011-11-14T17:22:59Z",
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quantity: 2,
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total: 90,
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tip: 0,
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type: "tab",
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productIDs: ["001", "002", "004", "005"],
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coords: [0.382, 0.38485]
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},
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{
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date: "2011-11-14T17:25:45Z",
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quantity: 2,
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total: 200,
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tip: 0,
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type: "cash",
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productIDs: ["002"],
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coords: [0.998, 0.8472]
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},
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{
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date: "2011-11-14T17:29:52Z",
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quantity: 1,
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total: 200,
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tip: 100,
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type: "visa",
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productIDs: ["004"],
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coords: [0.8273, 0.3384]
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}
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];
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let payments = null;
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beforeEach(() => {
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payments = new Crossfilter(someData);
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});
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describe("ImmutableTypedCrossfilter", () => {
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test("create crossfilter", () => {
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expect(payments).toBeDefined();
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expect(payments.size()).toEqual(someData.length);
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expect(payments.all()).toEqual(someData);
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const p = payments
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.addDimension("quantity", "scalar", (i, d) => d[i].quantity, Int32Array)
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.select("quantity", { mode: "all" });
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expect(p).toBeDefined();
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expect(p.all()).toEqual(someData);
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expect(p.size()).toEqual(someData.length);
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expect(p.isElementSelected(0)).toBeTruthy();
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expect(p.countSelected()).toEqual(someData.length);
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expect(p.allSelected()).toEqual(someData);
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});
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test("immutability", () => {
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/*
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the following should return a new crossfilter:
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- addDimension()
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- delDimension()
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- select
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*/
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const p2 = payments.addDimension(
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"quantity",
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"scalar",
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(i, data) => data[i].quantity,
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Int32Array
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);
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expect(payments).not.toBe(p2);
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const p3 = p2.select("quantity", { mode: "all" });
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expect(p3).not.toBe(p2);
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const p4 = p3.delDimension("quantity");
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expect(p4).not.toBe(p3);
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});
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test("select all and none", () => {
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let p = payments
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.addDimension("quantity", "scalar", (i, d) => d[i].quantity, Int32Array)
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.addDimension("tip", "scalar", (i, d) => d[i].tip, Float32Array)
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.addDimension("total", "scalar", (i, d) => d[i].total, Float32Array)
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.addDimension("type", "enum", (i, d) => d[i].type);
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expect(p).toBeDefined();
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/* expect all records to be selected - default init state */
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expect(p.allSelected()).toEqual(someData);
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expect(p.countSelected()).toEqual(someData.length);
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expect(p.allSelectedMask()).toEqual(
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new Uint8Array(someData.length).fill(1)
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);
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expect(p.fillByIsSelected(new Uint8Array(someData.length), 99, 0)).toEqual(
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new Uint8Array(someData.length).fill(99)
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);
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for (let i = 0; i < someData.length; i += 1) {
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expect(p.isElementSelected(i)).toBeTruthy();
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}
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/* expect a selectAll on one dimension to change nothing */
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p = p.select("tip", { mode: "all" });
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expect(p.allSelected()).toEqual(someData);
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/* ditto */
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p = p.select("quantity", { mode: "all" });
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expect(p.allSelected()).toEqual(someData);
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/* select none on one dimension */
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p = p.select("type", { mode: "none" });
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expect(p.allSelected()).toEqual([]);
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expect(p.countSelected()).toEqual(0);
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expect(p.allSelectedMask()).toEqual(
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new Uint8Array(someData.length).fill(0)
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);
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expect(p.fillByIsSelected(new Uint8Array(someData.length), 99, 0)).toEqual(
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new Uint8Array(someData.length).fill(0)
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);
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for (let i = 0; i < someData.length; i += 1) {
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expect(p.isElementSelected(i)).toBeFalsy();
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}
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p = p.select("quantity", { mode: "none" });
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expect(p.allSelected()).toEqual([]);
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// invert the first none; should have no effect because type is
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// still not filtered.
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p = p.select("quantity", { mode: "all" });
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expect(p.allSelected()).toEqual([]);
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/* select all of type; should select all records */
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p = p.select("type", { mode: "all" });
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expect(p.allSelected()).toEqual(someData);
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});
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describe("scalar dimension", () => {
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let p;
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beforeEach(() => {
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p = payments
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.addDimension("quantity", "scalar", (i, d) => d[i].quantity, Int32Array)
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.addDimension("tip", "scalar", (i, d) => d[i].tip, Float32Array)
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.select("tip", { mode: "all" });
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});
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/*
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select modes: all, none, exact, range
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*/
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test("all", () => {
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expect(p.select("quantity", { mode: "all" }).countSelected()).toEqual(
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someData.length
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);
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});
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test("none", () => {
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expect(p.select("quantity", { mode: "none" }).countSelected()).toEqual(0);
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});
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test.each([[[]], [[2]], [[2, 1]], [[9, 82]], [[0, 1]]])("exact: %p", v =>
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expect(
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p.select("quantity", { mode: "exact", values: v }).countSelected()
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).toEqual(_.filter(someData, d => v.includes(d.quantity)).length)
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);
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test.each([[0, 1], [1, 2], [0, 99], [99, 100000]])("range %p", (lo, hi) =>
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expect(
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p.select("quantity", { mode: "range", lo, hi }).countSelected()
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).toEqual(
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_.filter(someData, d => d.quantity >= lo && d.quantity < hi).length
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)
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);
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test("bad mode", () => {
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expect(() => p.select("type", { mode: "bad mode" })).toThrow(Error);
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});
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});
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describe("enum dimension", () => {
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let p;
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beforeEach(() => {
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p = payments.addDimension("type", "enum", (i, d) => d[i].type);
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});
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test("all", () => {
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expect(p.select("type", { mode: "all" }).countSelected()).toEqual(
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someData.length
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);
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});
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test("none", () => {
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expect(p.select("type", { mode: "none" }).countSelected()).toEqual(0);
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});
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test.each([
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[[]],
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[["tab"]],
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[["visa"]],
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[["visa", "tab"]],
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[["cash", "tab", "visa"]]
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])("exact: %p", v =>
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expect(
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p.select("type", { mode: "exact", values: v }).countSelected()
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).toEqual(_.filter(someData, d => v.includes(d.type)).length)
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);
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test("range", () => {
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expect(() => p.select("type", { mode: "range", lo: 0, hi: 9 })).toThrow(
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Error
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);
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});
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test("bad mode", () => {
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expect(() => p.select("type", { mode: "bad mode" })).toThrow(Error);
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});
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});
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describe("spatial dimension", () => {
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let p;
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beforeEach(() => {
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const X = someData.map(r => r.coords[0]);
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const Y = someData.map(r => r.coords[1]);
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p = payments.addDimension("coords", "spatial", X, Y);
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});
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test("all", () => {
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expect(p.select("coords", { mode: "all" }).countSelected()).toEqual(
|
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someData.length
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);
|
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});
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test("none", () => {
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expect(p.select("coords", { mode: "none" }).countSelected()).toEqual(0);
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});
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test.each([[0, 0, 1, 1], [0, 0, 0.5, 0.5], [0.5, 0.5, 1, 1]])(
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"within-rect %d %d %d %d",
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(x0, y0, x1, y1) => {
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expect(
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p
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.select("coords", { mode: "within-rect", x0, y0, x1, y1 })
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.allSelected()
|
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).toEqual(
|
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_.filter(someData, d => {
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const [x, y] = d.coords;
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return x0 <= x && x < x1 && y0 <= y && y < y1;
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})
|
||||
);
|
||||
}
|
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);
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|
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test.each([
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[[[0, 0], [0, 1], [1, 1], [1, 0]]],
|
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[[[0, 0], [0, 0.5], [0.5, 0.5], [0.5, 0]]]
|
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])("within-polygon %p", polygon => {
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expect(
|
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p.select("coords", { mode: "within-polygon", polygon }).allSelected()
|
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).toEqual(_.filter(someData, d => polygonContains(polygon, d.coords)));
|
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});
|
||||
});
|
||||
});
|
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@@ -1,590 +0,0 @@
|
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// jshint esversion: 6
|
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import _ from "lodash";
|
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import crossfilter from "../../../src/util/typedCrossfilter";
|
||||
|
||||
const someData = [
|
||||
{
|
||||
date: "2011-11-14T16:17:54Z",
|
||||
quantity: 2,
|
||||
total: 190,
|
||||
tip: 100,
|
||||
type: "tab",
|
||||
productIDs: ["001"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T16:20:19Z",
|
||||
quantity: 2,
|
||||
total: 190,
|
||||
tip: 100,
|
||||
type: "tab",
|
||||
productIDs: ["001", "005"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T16:28:54Z",
|
||||
quantity: 1,
|
||||
total: 300,
|
||||
tip: 200,
|
||||
type: "visa",
|
||||
productIDs: ["004", "005"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T16:30:43Z",
|
||||
quantity: 2,
|
||||
total: 90,
|
||||
tip: 0,
|
||||
type: "tab",
|
||||
productIDs: ["001", "002"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T16:48:46Z",
|
||||
quantity: 2,
|
||||
total: 90,
|
||||
tip: 0,
|
||||
type: "tab",
|
||||
productIDs: ["005"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T16:53:41Z",
|
||||
quantity: 2,
|
||||
total: 90,
|
||||
tip: 0,
|
||||
type: "tab",
|
||||
productIDs: ["001", "004", "005"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T16:54:06Z",
|
||||
quantity: 1,
|
||||
total: 100,
|
||||
tip: 0,
|
||||
type: "cash",
|
||||
productIDs: ["001", "002", "003", "004", "005"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T16:58:03Z",
|
||||
quantity: 2,
|
||||
total: 90,
|
||||
tip: 0,
|
||||
type: "tab",
|
||||
productIDs: ["001"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T17:07:21Z",
|
||||
quantity: 2,
|
||||
total: 90,
|
||||
tip: 0,
|
||||
type: "tab",
|
||||
productIDs: ["004", "005"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T17:22:59Z",
|
||||
quantity: 2,
|
||||
total: 90,
|
||||
tip: 0,
|
||||
type: "tab",
|
||||
productIDs: ["001", "002", "004", "005"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T17:25:45Z",
|
||||
quantity: 2,
|
||||
total: 200,
|
||||
tip: 0,
|
||||
type: "cash",
|
||||
productIDs: ["002"]
|
||||
},
|
||||
{
|
||||
date: "2011-11-14T17:29:52Z",
|
||||
quantity: 1,
|
||||
total: 200,
|
||||
tip: 100,
|
||||
type: "visa",
|
||||
productIDs: ["004"]
|
||||
}
|
||||
];
|
||||
|
||||
function groupReduce(data, valueMap, valueReduce, valueInit) {
|
||||
return _.reduce(
|
||||
data,
|
||||
(acc, value) => {
|
||||
const k = valueMap(value);
|
||||
let r = _.find(acc, o => o.key === k);
|
||||
if (!r) {
|
||||
r = { key: k, value: valueInit() };
|
||||
acc.push(r);
|
||||
}
|
||||
r.value = valueReduce(r.value, value);
|
||||
return acc;
|
||||
},
|
||||
[]
|
||||
).sort((a, b) => (a.key < b.key ? -1 : a.key > b.key ? 1 : 0));
|
||||
}
|
||||
|
||||
function groupCount(data, map) {
|
||||
return groupReduce(data, map, p => p + 1, () => 0);
|
||||
}
|
||||
|
||||
function groupSum(data, map) {
|
||||
return groupReduce(
|
||||
data,
|
||||
map,
|
||||
(p, v) => {
|
||||
p += map(v);
|
||||
return p;
|
||||
},
|
||||
() => 0
|
||||
);
|
||||
}
|
||||
|
||||
let payments = null;
|
||||
beforeEach(() => {
|
||||
payments = crossfilter(someData);
|
||||
});
|
||||
|
||||
describe("typedCrossfilter", () => {
|
||||
test("alloc and free", () => {
|
||||
expect(payments).toBeDefined();
|
||||
expect(payments.size()).toEqual(someData.length);
|
||||
expect(payments.all()).toEqual(someData);
|
||||
|
||||
const quantity = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].quantity,
|
||||
Int32Array
|
||||
);
|
||||
expect(quantity).toBeDefined();
|
||||
expect(quantity.id()).toBeDefined();
|
||||
|
||||
quantity.dispose();
|
||||
expect(payments.size()).toEqual(someData.length);
|
||||
expect(payments.all()).toEqual(someData);
|
||||
});
|
||||
|
||||
test("filterAll and filterNone", () => {
|
||||
expect(payments).toBeDefined();
|
||||
const quantity = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].quantity,
|
||||
Int32Array
|
||||
);
|
||||
const tip = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].tip,
|
||||
Float32Array
|
||||
);
|
||||
const total = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].total,
|
||||
Float32Array
|
||||
);
|
||||
const type = payments.dimension(
|
||||
crossfilter.EnumDimension,
|
||||
(i, data) => data[i].type
|
||||
);
|
||||
|
||||
expect(quantity).toBeDefined();
|
||||
expect(tip).toBeDefined();
|
||||
expect(total).toBeDefined();
|
||||
expect(type).toBeDefined();
|
||||
|
||||
// initially, all should be filtered
|
||||
expect(payments.allFiltered()).toHaveLength(payments.size());
|
||||
expect(payments.allFiltered()).toEqual(payments.all());
|
||||
expect(payments.countFiltered()).toEqual(someData.length);
|
||||
|
||||
// filterAll
|
||||
tip.filterAll(); // should change nothing
|
||||
expect(payments.allFiltered()).toEqual(payments.all());
|
||||
expect(payments.countFiltered()).toEqual(someData.length);
|
||||
|
||||
// ditto
|
||||
total.filterAll();
|
||||
expect(payments.allFiltered()).toEqual(payments.all());
|
||||
expect(payments.countFiltered()).toEqual(someData.length);
|
||||
|
||||
// filterNone
|
||||
type.filterNone();
|
||||
expect(payments.allFiltered()).toEqual([]);
|
||||
expect(payments.countFiltered()).toEqual(0);
|
||||
|
||||
quantity.filterNone();
|
||||
expect(payments.allFiltered()).toEqual([]);
|
||||
expect(payments.countFiltered()).toEqual(0);
|
||||
|
||||
// invert the first none; should have no effect because type is
|
||||
// still not filtered
|
||||
quantity.filterAll();
|
||||
expect(payments.allFiltered()).toEqual([]);
|
||||
expect(payments.countFiltered()).toEqual(0);
|
||||
|
||||
// filter all of type; should select all
|
||||
type.filterAll();
|
||||
expect(payments.allFiltered()).toEqual(payments.all());
|
||||
expect(payments.countFiltered()).toEqual(payments.size());
|
||||
});
|
||||
|
||||
test("filterExact", () => {
|
||||
expect(payments).toBeDefined();
|
||||
const quantity = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].quantity,
|
||||
Int32Array
|
||||
);
|
||||
const tip = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].tip,
|
||||
Float32Array
|
||||
);
|
||||
const type = payments.dimension(
|
||||
crossfilter.EnumDimension,
|
||||
(i, data) => data[i].type
|
||||
);
|
||||
|
||||
quantity.filterExact(1);
|
||||
expect(payments.countFiltered()).toEqual(
|
||||
_.countBy(someData, "quantity")[1]
|
||||
);
|
||||
expect(payments.allFiltered()).toEqual(_.filter(someData, { quantity: 1 }));
|
||||
|
||||
tip.filterExact(0);
|
||||
expect(payments.allFiltered()).toEqual(
|
||||
_.filter(someData, { tip: 0, quantity: 1 })
|
||||
);
|
||||
|
||||
type.filterExact("cash");
|
||||
expect(payments.allFiltered()).toEqual(
|
||||
_.filter(someData, { tip: 0, quantity: 1, type: "cash" })
|
||||
);
|
||||
});
|
||||
|
||||
test("filterRange", () => {
|
||||
expect(payments).toBeDefined();
|
||||
const quantity = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].quantity,
|
||||
Int32Array
|
||||
);
|
||||
const tip = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].tip,
|
||||
Float32Array
|
||||
);
|
||||
const total = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].total,
|
||||
Float32Array
|
||||
);
|
||||
const type = payments.dimension(
|
||||
crossfilter.EnumDimension,
|
||||
(i, data) => data[i].type
|
||||
);
|
||||
|
||||
tip.filterRange([0, 91]);
|
||||
expect(payments.allFiltered()).toEqual(
|
||||
_(someData)
|
||||
.filter(r => r.tip >= 0 && r.tip < 91)
|
||||
.value()
|
||||
);
|
||||
|
||||
tip.filterRange([0, 90]);
|
||||
expect(payments.allFiltered()).toEqual(
|
||||
_(someData)
|
||||
.filter(r => r.tip >= 0 && r.tip < 90)
|
||||
.value()
|
||||
);
|
||||
|
||||
tip.filterRange([1, 90]);
|
||||
expect(payments.allFiltered()).toEqual(
|
||||
_(someData)
|
||||
.filter(r => r.tip >= 1 && r.tip < 91)
|
||||
.value()
|
||||
);
|
||||
});
|
||||
|
||||
test("filterEnum", () => {
|
||||
expect(payments).toBeDefined();
|
||||
const quantity = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].quantity,
|
||||
Int32Array
|
||||
);
|
||||
const tip = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].tip,
|
||||
Float32Array
|
||||
);
|
||||
const total = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].total,
|
||||
Float32Array
|
||||
);
|
||||
const type = payments.dimension(
|
||||
crossfilter.EnumDimension,
|
||||
(i, data) => data[i].type
|
||||
);
|
||||
|
||||
type.filterEnum(["tab", "cash"]);
|
||||
expect(payments.allFiltered()).toEqual(
|
||||
_(someData)
|
||||
.filter(r => r.type === "cash" || r.type === "tab")
|
||||
.value()
|
||||
);
|
||||
|
||||
tip.filterEnum([0, 100]);
|
||||
expect(payments.allFiltered()).toEqual(
|
||||
_(someData)
|
||||
.filter(r => r.type === "cash" || r.type === "tab")
|
||||
.filter(r => r.tip === 0 || r.tip === 100)
|
||||
.value()
|
||||
);
|
||||
});
|
||||
|
||||
test("more than 32 dimensions", () => {
|
||||
expect(payments).toBeDefined();
|
||||
const quantity = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].quantity,
|
||||
Int32Array
|
||||
);
|
||||
const tip = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].tip,
|
||||
Float32Array
|
||||
);
|
||||
const total = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].total,
|
||||
Float32Array
|
||||
);
|
||||
const type = payments.dimension(
|
||||
crossfilter.EnumDimension,
|
||||
(i, data) => data[i].type
|
||||
);
|
||||
|
||||
// Create a bunch of fake dimensions to ensure we can handle > 32
|
||||
let dimMap = {};
|
||||
for (let i = 0; i < 65; i++) {
|
||||
dimMap[i] = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
() => Math.random(),
|
||||
Float32Array
|
||||
);
|
||||
expect(dimMap[i]).toBeDefined();
|
||||
expect(dimMap[i].id()).toBeDefined();
|
||||
}
|
||||
|
||||
// everything should start as selected/filtered
|
||||
expect(payments.countFiltered()).toEqual(someData.length);
|
||||
|
||||
dimMap[0].filterAll();
|
||||
dimMap[64].filterAll();
|
||||
expect(payments.countFiltered()).toEqual(someData.length);
|
||||
|
||||
dimMap[33].filterNone();
|
||||
expect(payments.allFiltered()).toEqual([]);
|
||||
|
||||
dimMap[33].filterAll();
|
||||
expect(payments.allFiltered()).toEqual(someData);
|
||||
});
|
||||
|
||||
test("group, default mapping, default reducer, no filter", () => {
|
||||
expect(payments).toBeDefined();
|
||||
|
||||
const quantity = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].quantity,
|
||||
Int32Array
|
||||
);
|
||||
const tip = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].tip,
|
||||
Int32Array
|
||||
);
|
||||
const type = payments.dimension(
|
||||
crossfilter.EnumDimension,
|
||||
(i, data) => data[i].type
|
||||
);
|
||||
const total = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].total,
|
||||
Int32Array
|
||||
);
|
||||
|
||||
_.each(
|
||||
{
|
||||
tip: tip.group(r => r),
|
||||
type: type.group(),
|
||||
total: total.group(),
|
||||
quantity: quantity.group()
|
||||
},
|
||||
(grp, k) => {
|
||||
const whatWeExpect = groupCount(someData, v => v[k]);
|
||||
expect(grp.all()).toEqual(whatWeExpect);
|
||||
expect(grp.size()).toEqual(whatWeExpect.length);
|
||||
expect(grp.dispose()).toEqual(grp);
|
||||
}
|
||||
);
|
||||
});
|
||||
|
||||
test("group, custom map, default reducer, no filters", () => {
|
||||
expect(payments).toBeDefined();
|
||||
|
||||
// custom mapping in groups only works for scalar types. Enums do not
|
||||
// currently implement it.
|
||||
|
||||
const tip = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].tip,
|
||||
Int32Array
|
||||
);
|
||||
const totalX10 = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].total * 10,
|
||||
Int32Array
|
||||
);
|
||||
const type = payments.dimension(
|
||||
crossfilter.EnumDimension,
|
||||
(i, data) => data[i].type
|
||||
);
|
||||
|
||||
const paymentsByTip_A = tip.group();
|
||||
const paymentsByTip_B = tip.group(r => 10 * r);
|
||||
const paymentsByType = type.group(); // identity only
|
||||
const paymentsByTotalX10_A = totalX10.group();
|
||||
const paymentsByTotalX10_B = totalX10.group(r => r / 10);
|
||||
|
||||
expect(paymentsByTip_A.all()).toEqual(groupCount(someData, v => v.tip));
|
||||
expect(paymentsByTip_B.all()).toEqual(
|
||||
groupCount(someData, v => 10 * v.tip)
|
||||
);
|
||||
expect(paymentsByType.all()).toEqual(groupCount(someData, v => v.type));
|
||||
expect(paymentsByTotalX10_A.all()).toEqual(
|
||||
groupCount(someData, v => 10 * v.total)
|
||||
);
|
||||
expect(paymentsByTotalX10_B.all()).toEqual(
|
||||
groupCount(someData, v => (10 * v.total) / 10)
|
||||
);
|
||||
|
||||
for (let i of [
|
||||
paymentsByTip_A,
|
||||
paymentsByTip_B,
|
||||
paymentsByType,
|
||||
paymentsByTotalX10_A,
|
||||
paymentsByTotalX10_B,
|
||||
tip,
|
||||
totalX10,
|
||||
type
|
||||
]) {
|
||||
expect(i.dispose()).toEqual(i);
|
||||
}
|
||||
});
|
||||
|
||||
test("group, default map, custom reducer, no filters", () => {
|
||||
expect(payments).toBeDefined();
|
||||
|
||||
const total = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].total,
|
||||
Float32Array
|
||||
);
|
||||
const type = payments.dimension(
|
||||
crossfilter.EnumDimension,
|
||||
(i, data) => data[i].type
|
||||
);
|
||||
|
||||
const paymentsByTotal = total.group();
|
||||
const paymentsByType = type.group();
|
||||
|
||||
// reduceCount
|
||||
expect(paymentsByTotal.reduceCount()).toEqual(paymentsByTotal);
|
||||
expect(paymentsByTotal.all()).toEqual(groupCount(someData, v => v.total));
|
||||
|
||||
// reduceSum
|
||||
expect(paymentsByTotal.reduceSum(v => v.total)).toEqual(paymentsByTotal);
|
||||
expect(paymentsByTotal.all()).toEqual(groupSum(someData, v => v.total));
|
||||
|
||||
// use custom reducers (my reducers) - count by three, init 1
|
||||
expect(
|
||||
paymentsByTotal.reduce((p, v) => (p += 3), (p, v) => (p -= 3), () => 1)
|
||||
).toEqual(paymentsByTotal);
|
||||
expect(paymentsByTotal.all()).toEqual(
|
||||
groupReduce(someData, v => v.total, (p, v) => p + 3, () => 1)
|
||||
);
|
||||
|
||||
for (let i of [paymentsByTotal, paymentsByType, type]) {
|
||||
expect(i.dispose()).toEqual(i);
|
||||
}
|
||||
});
|
||||
|
||||
test("group, default map, default reducer, filters", () => {
|
||||
// From the docs:
|
||||
// Note: a grouping intersects the crossfilter's current filters, except for the
|
||||
// associated dimension's filter. Thus, group methods consider only records that
|
||||
// satisfy every filter except this dimension's filter. So, if the crossfilter of
|
||||
// payments is filtered by type and total, then group by total only observes the
|
||||
// filter by type.
|
||||
|
||||
expect(payments).toBeDefined();
|
||||
|
||||
const tip = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].tip,
|
||||
Int32Array
|
||||
);
|
||||
const total = payments.dimension(
|
||||
crossfilter.ScalarDimension,
|
||||
(i, data) => data[i].total,
|
||||
Int32Array
|
||||
);
|
||||
const type = payments.dimension(
|
||||
crossfilter.EnumDimension,
|
||||
(i, data) => data[i].type
|
||||
);
|
||||
|
||||
const paymentsByTip = tip.group();
|
||||
const paymentsByTotal = total.group();
|
||||
const paymentsByType = type.group();
|
||||
|
||||
// 1. confirm that changing the filter on a dimension does NOT change that
|
||||
// dimensions groups.
|
||||
{
|
||||
tip.filterAll(), total.filterAll(), type.filterAll();
|
||||
let before = _.cloneDeep(paymentsByTip.all());
|
||||
tip.filterExact(0);
|
||||
expect(paymentsByTip.all()).toEqual(before);
|
||||
}
|
||||
|
||||
// 2. confirm that changing a filter on a different dimension DOES change
|
||||
// all other groups.
|
||||
{
|
||||
tip.filterAll(), total.filterAll(), type.filterAll();
|
||||
const before = _.cloneDeep([paymentsByTotal.all(), paymentsByType.all()]);
|
||||
tip.filterExact(0);
|
||||
const after = [paymentsByTotal.all(), paymentsByType.all()];
|
||||
expect(after).not.toEqual(before);
|
||||
expect(after).toEqual([
|
||||
groupReduce(
|
||||
someData,
|
||||
v => v.total,
|
||||
(p, v) => (v.tip !== 0 ? p : p + 1),
|
||||
() => 0
|
||||
),
|
||||
groupReduce(
|
||||
someData,
|
||||
v => v.type,
|
||||
(p, v) => (v.tip !== 0 ? p : p + 1),
|
||||
() => 0
|
||||
)
|
||||
]);
|
||||
}
|
||||
|
||||
for (let i of [
|
||||
paymentsByTip,
|
||||
paymentsByTotal,
|
||||
paymentsByType,
|
||||
tip,
|
||||
total,
|
||||
type
|
||||
]) {
|
||||
expect(i.dispose()).toEqual(i);
|
||||
}
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user