Dataframe, part deux - add varData and summarize() (#608)

* initial dataframe commit

* initial dataframe port of core app

* rename variables for clarity

* remove unused import

* comment out unused code

* fix array handling bug in crossfilter dimension creation

* allow creation of empty dataframes

* handle non-existent columns

* handle non-existent columns

* revise tests for new dataframe

* comments for clarity

* comments for clarity

* generate bulk add placeholder with real gene names

* fix bug in gene name adding

* more dataframe unit tests

* fix bug - subset from current world, not universe

* put cut and pasted code into a single function

* improve caching of crossfilter

* remove cascading update bug from graph

* more performance work

* improve state handling for scatterplot

* performance optimization of critical path

* add column summarization

* dataframe utils

* add callOnceLazy

* fix tests

* minor updates found during review

* fix misspelling

* remove RESTv02 from function names

* comment cleanup

* cut/icut col parameter defaults to null

* break up large test

* improve tests and comments on dataframe at/has functions

* add Dataframe withCol/dropCol

* expression varData now stored in a dataframe

* dead code cleanup

* use dataframe.summarize()

* test cases for Dataframe.col.summarize

* update test cases for new dataframe summarize

* improve naming

* use new hasCol API

* add comments

* add more Dataframe.withCol tests

* add ability to specify row index in cut operation

* retire subsetVarData function

* correctly handle expression subsetting

* lint and improve comments

* rename cut to subset

* changes based on PR review
This commit is contained in:
Bruce Martin
2019-02-28 08:34:22 -08:00
committed by GitHub
parent 2bae696986
commit ffd6273419
21 changed files with 910 additions and 1140 deletions
@@ -8,7 +8,6 @@ import {
obsAnnoDimensionName,
layoutDimensionName
} from "../../../src/util/nameCreators";
import * as kvCache from "../../../src/util/stateManager/keyvalcache";
/*
Helper - creates universe, world, corssfilter and dimensionMap from
@@ -55,28 +54,13 @@ describe("createWorldFromEntireUniverse", () => {
expect(world).toMatchObject(
expect.objectContaining({
api: "0.2",
nObs: universe.nObs,
nVar: universe.nVar,
schema: universe.schema,
obsAnnotations: universe.obsAnnotations,
varAnnotations: universe.varAnnotations,
obsLayout: universe.obsLayout,
summary: expect.objectContaining({
obs: _(REST.schema.schema.annotations.obs)
.filter(v => v.name !== "name")
.keyBy("name")
.mapValues(() => expect.any(Object))
.value(),
var: _(REST.schema.schema.annotations.var)
.filter(v => v.name !== "name")
.keyBy("name")
.mapValues(() => expect.any(Object))
.value()
}),
varDataCache: expect.any(Object)
varData: expect.any(Dataframe.Dataframe)
})
);
});
@@ -121,18 +105,13 @@ describe("createWorldFromCurrentSelection", () => {
expect(world).toMatchObject(
expect.objectContaining({
api: "0.2",
nObs: matchingIndices.length,
nVar: universe.nVar,
schema: universe.schema,
obsAnnotations: expect.any(Dataframe.Dataframe),
varAnnotations: universe.varAnnotations,
obsLayout: expect.any(Dataframe.Dataframe),
summary: {
obs: expect.any(Object) /* we could do better! */,
var: expect.any(Object) /* we could do better! */
},
varDataCache: expect.any(Object)
varData: expect.any(Dataframe.Dataframe)
})
);
@@ -183,60 +162,14 @@ describe("createObsDimensionMap", () => {
});
});
describe("subsetVarData", () => {
test("when world eq universe", () => {
const { universe, world } = defaultBigBang();
/* create a mock varData array for subsetting */
const sourceVarData = new Float32Array(universe.nObs);
/* expect literally the same object back */
const result = World.subsetVarData(world, universe, sourceVarData);
expect(result).toBe(sourceVarData);
});
test("when world neq universe", () => {
const { universe, world, crossfilter, dimensionMap } = defaultBigBang();
/* create a mock varData array for subsetting */
const sourceVarData = Float32Array.from(_.range(universe.nObs));
/* mock a selection */
dimensionMap[obsAnnoDimensionName("field1")].filterRange([0, 5]);
dimensionMap[obsAnnoDimensionName("field3")].filterExact(false);
/* create the world from the selection */
const newWorld = World.createWorldFromCurrentSelection(
universe,
world,
crossfilter
);
expect(newWorld.obsAnnotations.rowIndex.keys()).toEqual(
new Int32Array([0, 2])
);
/* expect a subset */
const result = World.subsetVarData(newWorld, universe, sourceVarData);
expect(result).not.toBe(sourceVarData);
expect(result).toHaveLength(newWorld.nObs);
/* check that we have expected source var content */
expect(result).toMatchObject(new Float32Array([0, 2]));
});
});
describe("createVarDimension", () => {
describe("createVarDataDimension", () => {
/* create default universe */
const { world, crossfilter } = defaultBigBang();
/* create a mock var data cache */
const varDataCache = kvCache.set(
kvCache.create(),
world.varData = world.varData.withCol(
"GENE",
Float32Array.from(_.range(world.nObs))
);
const result = World.createVarDimension(
world,
varDataCache,
crossfilter,
"GENE"
);
const result = World.createVarDataDimension(world, crossfilter, "GENE");
expect(result).toBeInstanceOf(Crossfilter.ScalarDimension);
});