mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-17 05:47:58 +08:00
ffd6273419
* 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
254 lines
6.2 KiB
JavaScript
254 lines
6.2 KiB
JavaScript
import * as Dataframe from "../../../src/util/dataframe";
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function float32Conversion(f) {
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return new Float32Array([f])[0];
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}
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describe("Dataframe column summary", () => {
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test("empty column test", () => {
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const df = Dataframe.Dataframe.create([0, 1], [[]]);
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const summary = df.icol(0).summarize();
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expect(summary).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: [],
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categoryCounts: new Map(),
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numCategories: 0
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})
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);
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});
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test("simple test", () => {
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const df = new Dataframe.Dataframe(
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[1, 6],
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[
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["n1"],
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["hi"],
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[true],
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new Float32Array([39.3]),
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new Int32Array([99]),
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[1]
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],
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null,
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new Dataframe.KeyIndex([
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"name",
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"nameString",
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"nameBoolean",
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"nameFloat32",
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"nameInt32",
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"nameCategorical"
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])
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);
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expect(df.icol(0).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: ["n1"],
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categoryCounts: new Map([["n1", 1]]),
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numCategories: 1
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})
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);
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expect(df.icol(1).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: ["hi"],
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categoryCounts: new Map([["hi", 1]]),
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numCategories: 1
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})
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);
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expect(df.icol(2).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: [true],
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categoryCounts: new Map([[true, 1]]),
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numCategories: 1
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})
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);
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expect(df.icol(3).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: float32Conversion(39.3),
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max: float32Conversion(39.3),
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nan: 0,
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ninf: 0,
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pinf: 0
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})
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);
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expect(df.icol(4).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: 99,
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max: 99,
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nan: 0,
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ninf: 0,
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pinf: 0
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})
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);
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expect(df.icol(5).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: [1],
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categoryCounts: new Map([[1, 1]]),
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numCategories: 1
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})
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);
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});
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test("multi test", () => {
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const df = new Dataframe.Dataframe(
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[3, 6],
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[
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["n0", "n1", "n2"],
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["hi", "hi", "bye"],
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[false, true, true],
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new Float32Array([39.3, 39.3, 0]),
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new Int32Array([99, 99, 99]),
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[1, false, "0"]
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],
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null,
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new Dataframe.KeyIndex([
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"name",
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"nameString",
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"nameBoolean",
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"nameFloat32",
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"nameInt32",
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"nameCategorical"
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])
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);
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expect(df.icol(0).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining(["n0", "n1", "n2"]),
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categoryCounts: new Map([["n0", 1], ["n1", 1], ["n2", 1]]),
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numCategories: 3
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})
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);
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expect(df.icol(1).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining(["hi", "bye"]),
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categoryCounts: new Map([["hi", 2], ["bye", 1]]),
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numCategories: 2
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})
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);
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expect(df.icol(2).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining([true, false]),
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categoryCounts: new Map([[true, 2], [false, 1]]),
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numCategories: 2
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})
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);
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expect(df.icol(3).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: 0,
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max: float32Conversion(39.3),
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nan: 0,
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ninf: 0,
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pinf: 0
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})
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);
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expect(df.icol(4).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: 99,
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max: 99,
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nan: 0,
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ninf: 0,
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pinf: 0
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})
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);
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expect(df.icol(5).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining([1, false, "0"]),
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categoryCounts: new Map([[1, 1], [false, 1], ["0", 1]]),
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numCategories: 3
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})
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);
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});
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test("non-finite numbers", () => {
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const df = new Dataframe.Dataframe(
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[4, 6],
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[
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["n0", "n1", "n2", "n2"],
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["hi", "hi", "bye", "bye"],
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[false, true, true, true],
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new Float32Array([
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39.3,
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Number.NEGATIVE_INFINITY,
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Number.NaN,
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Number.POSITIVE_INFINITY
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]),
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new Int32Array([99, 99, 99, 99]),
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[1, false, "0", "0"]
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],
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null,
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new Dataframe.KeyIndex([
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"name",
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"nameString",
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"nameBoolean",
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"nameFloat32",
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"nameInt32",
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"nameCategorical"
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])
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);
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expect(df.icol(0).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining(["n0", "n1", "n2"]),
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categoryCounts: new Map([["n0", 1], ["n1", 1], ["n2", 2]]),
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numCategories: 3
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})
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);
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expect(df.icol(1).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining(["hi", "bye"]),
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categoryCounts: new Map([["hi", 2], ["bye", 1]]),
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numCategories: 2
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})
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);
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expect(df.icol(2).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining([true, false]),
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categoryCounts: new Map([[true, 2], [false, 1]]),
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numCategories: 2
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})
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);
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expect(df.icol(3).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: float32Conversion(39.3),
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max: float32Conversion(39.3),
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nan: 1,
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ninf: 1,
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pinf: 1
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})
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);
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expect(df.icol(4).summarize()).toEqual(
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expect.objectContaining({
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categorical: false,
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min: 99,
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max: 99,
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nan: 0,
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ninf: 0,
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pinf: 0
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})
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);
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expect(df.icol(5).summarize()).toEqual(
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expect.objectContaining({
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categorical: true,
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categories: expect.arrayContaining([1, false, "0"]),
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categoryCounts: new Map([[1, 1], [false, 1], ["0", 1]]),
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numCategories: 3
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})
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);
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});
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});
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