mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-10-01 09:48:11 +08:00
Redux refactor (#1571)
* refactor categorical controls state * lint * fix race condition in tests * fix typo * add missing update on subset * remove obsolete code * update jest and puppeteer major version; update all minors * update when label changes * remove lint from tests; increase timeouts in e2e tests * initial refactoring to new async annomatrix * refine error handling * fix bad merge * add continuous legend * lint * fix memoization in color table creators * partial implementation of user defined annotations * add new annotations action creator file * first pass at user annotations * additional user annotation bug fixes * user annotation auto-save * unit test cleanup * lint * refactor into multiple files * cleanup * add column GC * fix several bugs in user annotations * remove debug code * no anonymous functions * undo redo cleanup * file cleanup * scatterplot * performance * cleanup * remove old code * render in parallel with load * fix race condition * simply graph rendering * render throttle DRY * fix category label order * fix typo in e2e test setup * re-fix the e2e test setup * be more tolerant of races * anno matrix unit tests * temp disable reembedding * pilot port continuous histo to react-async * name change * lint * fix repaint bug * typo fix * update snap to match new ids * world/universe name cleanup * move annoMatrix to src dir * use private underscore naming convention * fix corner case in all selected * name cleanup * add layout control * init edge case * lint * port scatterplot * fix label indexing bug and improve tests * port category to react-async * fix user annotation labelling while subset * select all of prev layout on layout switch * fix race with crossfilter update * prettier lint * fix misleading comment * fix url composition in loader * first pass at crossfilter tests * lint * lint * fix typo * improved error handling for network errors * fix memoization bug * add memo * refactor for performnce * add missing single-value handling in select exact parser * small bugs discovered by tests * lint * additional crossfilter unit tests * remove extraneous comment * add support for automatic category determination * lint * fix render bug in category * take advantage of schema categories guarantee * lint * do not clear history when resetting * enhanced annomatrix gc * lint * finish renaming to follow conventions; fix clone race bug * lint * add priority based loading to improve initial data load UX * crossfilter cache perf * perf tuning * remove timers * documentation * PR review changes * PR review changes * more PR review edits * improve clarity of comment * more PR review fixes * port centroidLabels to use react-async * remove dead code * pr review updates * oops, remove logging
This commit is contained in:
Bruce Martin
@@ -918,115 +918,342 @@ describe("dataframe col", () => {
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});
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describe("label indexing", () => {
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test("IdentityInt32Index", () => {
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describe("isLabelIndex", () => {
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expect(
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Dataframe.isLabelIndex(new Dataframe.IdentityInt32Index(4))
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).toBeTruthy();
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expect(
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Dataframe.isLabelIndex(new Dataframe.DenseInt32Index([2, 4, 99]))
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).toBeTruthy();
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expect(
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Dataframe.isLabelIndex(new Dataframe.KeyIndex(["a", 4, "toasty"]))
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).toBeTruthy();
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expect(Dataframe.isLabelIndex(false)).toBeFalsy();
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expect(Dataframe.isLabelIndex(undefined)).toBeFalsy();
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expect(Dataframe.isLabelIndex(null)).toBeFalsy();
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expect(Dataframe.isLabelIndex(true)).toBeFalsy();
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expect(Dataframe.isLabelIndex([])).toBeFalsy();
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expect(Dataframe.isLabelIndex({})).toBeFalsy();
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expect(Dataframe.isLabelIndex(Dataframe.IdentityInt32Index)).toBeFalsy();
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});
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describe("IdentityInt32Index", () => {
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const idx = new Dataframe.IdentityInt32Index(12); // [0, 12)
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expect(Dataframe.isLabelIndex(idx)).toBeTruthy();
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test("create", () => {
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expect(Dataframe.isLabelIndex(idx)).toBeTruthy();
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});
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expect(idx.labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
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);
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expect(idx.getLabel(1)).toEqual(1);
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expect(idx.getOffset(1)).toEqual(1);
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expect(idx.getOffsets([1, 3])).toEqual([1, 3]);
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expect(idx.getLabels([1, 3])).toEqual([1, 3]);
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expect(idx.size()).toEqual(12);
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test("labels", () => {
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expect(idx.labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
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);
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expect(idx.getLabel(1)).toEqual(1);
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expect(idx.getLabels([1, 3])).toEqual([1, 3]);
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expect(idx.size()).toEqual(12);
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});
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expect(idx.subset([2]).labels()).toEqual([2]);
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expect(idx.subset([2, 3, 4]).labels()).toEqual(new Int32Array([2, 3, 4]));
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expect(idx.subset([0, 1, 2, 3]).labels()).toEqual(
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new Int32Array([0, 1, 2, 3])
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);
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test("offsets", () => {
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expect(idx.getOffset(1)).toEqual(1);
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expect(idx.getOffsets([1, 3])).toEqual([1, 3]);
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});
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expect(idx.isubset([2]).labels()).toEqual([2]);
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expect(idx.isubset([2, 3, 4]).labels()).toEqual(new Int32Array([2, 3, 4]));
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expect(idx.isubset([0, 1, 2, 3]).labels()).toEqual(
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new Int32Array([0, 1, 2, 3])
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);
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test("subset", () => {
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expect(idx.subset([2]).labels()).toEqual([2]);
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expect(idx.subset([2, 3, 4]).labels()).toEqual(new Int32Array([2, 3, 4]));
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expect(idx.subset([0, 1, 2, 3]).labels()).toEqual(
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new Int32Array([0, 1, 2, 3])
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);
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expect(idx.subset([0, 1, 2, 3, 4])).toBeInstanceOf(
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Dataframe.IdentityInt32Index
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);
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expect(idx.subset([2, 1, 0])).toBeInstanceOf(
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Dataframe.IdentityInt32Index
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);
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expect(idx.subset([1, 2, 3, 4])).toBeInstanceOf(
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Dataframe.DenseInt32Index
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);
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expect(idx.subset([0, 1, 3, 4])).toBeInstanceOf(
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Dataframe.DenseInt32Index
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);
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expect(idx.subset([0, 1, 2, 3, 10])).toBeInstanceOf(
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Dataframe.DenseInt32Index
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);
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expect(idx.subset([4, 3, 2, 1])).toBeInstanceOf(
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Dataframe.DenseInt32Index
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);
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expect(idx.subset([4])).toBeInstanceOf(Dataframe.KeyIndex);
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});
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expect(idx.subset([0, 1, 2, 3, 4])).toBeInstanceOf(
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Dataframe.IdentityInt32Index
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);
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expect(idx.subset([2, 1, 0])).toBeInstanceOf(Dataframe.IdentityInt32Index);
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expect(idx.subset([1, 2, 3, 4])).toBeInstanceOf(Dataframe.DenseInt32Index);
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expect(idx.subset([0, 1, 3, 4])).toBeInstanceOf(Dataframe.DenseInt32Index);
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expect(idx.subset([0, 1, 2, 3, 10])).toBeInstanceOf(
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Dataframe.DenseInt32Index
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);
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expect(idx.subset([4, 3, 2, 1])).toBeInstanceOf(Dataframe.DenseInt32Index);
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expect(idx.subset([4])).toBeInstanceOf(Dataframe.KeyIndex);
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test("isubset", () => {
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expect(idx.isubset([2]).labels()).toEqual([2]);
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expect(idx.isubset([2, 3, 4]).labels()).toEqual(
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new Int32Array([2, 3, 4])
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);
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expect(idx.isubset([0, 1, 2, 3]).labels()).toEqual(
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new Int32Array([0, 1, 2, 3])
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);
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expect(() => idx.isubset([-1001])).toThrow(RangeError);
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expect(() => idx.isubset([1001])).toThrow(RangeError);
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});
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expect(idx.withLabel(99).labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 99])
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);
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expect(idx.dropLabel(0).labels()).toEqual(
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new Int32Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
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);
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expect(idx.dropLabel(11).labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
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);
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expect(idx.dropLabel(5).labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11])
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);
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test("isubsetMask", () => {
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expect(
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idx
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.isubsetMask([
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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])
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.labels()
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).toEqual(new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]));
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expect(
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idx
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.isubsetMask([
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false,
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false,
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false,
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false,
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false,
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false,
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false,
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false,
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false,
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false,
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false,
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false,
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])
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.labels()
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).toEqual(new Int32Array([]));
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expect(
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idx
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.isubsetMask([
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false,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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])
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.labels()
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).toEqual(new Int32Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]));
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expect(
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idx
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.isubsetMask([
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false,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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true,
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false,
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true,
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])
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.labels()
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).toEqual(new Int32Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 11]));
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expect(
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idx
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.isubsetMask([
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false,
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true,
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true,
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false,
|
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true,
|
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true,
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true,
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true,
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true,
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true,
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true,
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false,
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])
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.labels()
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).toEqual(new Int32Array([1, 2, 4, 5, 6, 7, 8, 9, 10]));
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expect(() => idx.isubsetMask([])).toThrow(RangeError);
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});
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test("withLabel", () => {
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expect(idx.withLabel(99).labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 99])
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);
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expect(idx.withLabel(12).labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
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);
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expect(idx.withLabels([12, 13]).labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13])
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);
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});
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test("dropLabel", () => {
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expect(idx.dropLabel(0).labels()).toEqual(
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new Int32Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
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);
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expect(idx.dropLabel(11).labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
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);
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expect(idx.dropLabel(5).labels()).toEqual(
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new Int32Array([0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11])
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);
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});
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});
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test("DenseInt32Index", () => {
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describe("DenseInt32Index", () => {
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const idx = new Dataframe.DenseInt32Index([99, 1002, 48, 0, 22]);
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expect(Dataframe.isLabelIndex(idx)).toBeTruthy();
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test("create", () => {
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expect(Dataframe.isLabelIndex(idx)).toBeTruthy();
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});
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expect(idx.labels()).toEqual(new Int32Array([99, 1002, 48, 0, 22]));
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expect(idx.size()).toEqual(5);
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expect(idx.getOffset(1002)).toEqual(1);
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expect(idx.getOffset(0)).toEqual(3);
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expect(idx.getLabel(0)).toEqual(99);
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expect(idx.getLabels(new Int32Array([2, 4]))).toEqual(
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new Int32Array([48, 22])
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);
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expect(idx.getLabels([2, 4])).toEqual([48, 22]);
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expect(idx.getOffsets([0, 48])).toEqual([3, 2]);
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test("labels", () => {
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expect(idx.labels()).toEqual(new Int32Array([99, 1002, 48, 0, 22]));
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expect(idx.size()).toEqual(5);
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expect(idx.getLabel(0)).toEqual(99);
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expect(idx.getLabels(new Int32Array([2, 4]))).toEqual(
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new Int32Array([48, 22])
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);
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expect(idx.getLabels([2, 4])).toEqual([48, 22]);
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});
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expect(idx.subset([1002, 0, 99]).labels()).toEqual(
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new Int32Array([1002, 0, 99])
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);
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expect(idx.getOffsets(idx.subset([1002, 0, 99]).labels())).toEqual(
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new Int32Array([1, 3, 0])
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);
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expect(idx.isubset([4, 1, 2]).labels()).toEqual(
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new Int32Array([22, 1002, 48])
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);
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test("offsets", () => {
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expect(idx.getOffset(1002)).toEqual(1);
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expect(idx.getOffset(0)).toEqual(3);
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expect(idx.getOffsets([0, 48])).toEqual([3, 2]);
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});
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expect(idx.withLabel(88).labels()).toEqual(
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new Int32Array([99, 1002, 48, 0, 22, 88])
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);
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expect(idx.withLabel(88).getOffset(88)).toEqual(5);
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expect(idx.dropLabel(48).labels()).toEqual(
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new Int32Array([99, 1002, 0, 22])
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);
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test("subset", () => {
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expect(idx.subset([1002, 0, 99]).labels()).toEqual(
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new Int32Array([1002, 0, 99])
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);
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expect(idx.getOffsets(idx.subset([1002, 0, 99]).labels())).toEqual(
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new Int32Array([1, 3, 0])
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);
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expect(() => idx.subset([-1])).toThrow(RangeError);
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});
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|
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test("isubset", () => {
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expect(idx.isubset([4, 1, 2]).labels()).toEqual(
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new Int32Array([22, 1002, 48])
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||||
);
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expect(() => idx.isubset([-1001])).toThrow(RangeError);
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expect(() => idx.isubset([1001])).toThrow(RangeError);
|
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});
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|
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test("isubsetMask", () => {
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expect(idx.isubsetMask([true, true, true, true, true]).labels()).toEqual(
|
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new Int32Array([99, 1002, 48, 0, 22])
|
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);
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expect(
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idx.isubsetMask([false, false, false, false, false]).labels()
|
||||
).toEqual(new Int32Array([]));
|
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expect(idx.isubsetMask([true, true, false, true, true]).labels()).toEqual(
|
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new Int32Array([99, 1002, 0, 22])
|
||||
);
|
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expect(
|
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idx.isubsetMask([false, true, true, true, false]).labels()
|
||||
).toEqual(new Int32Array([1002, 48, 0]));
|
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expect(() => idx.isubsetMask([])).toThrow(RangeError);
|
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});
|
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|
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test("withLabel", () => {
|
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expect(idx.withLabel(88).labels()).toEqual(
|
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new Int32Array([99, 1002, 48, 0, 22, 88])
|
||||
);
|
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expect(idx.withLabel(88).getOffset(88)).toEqual(5);
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expect(idx.withLabels([88, 99]).labels()).toEqual(
|
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new Int32Array([99, 1002, 48, 0, 22, 88, 99])
|
||||
);
|
||||
});
|
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test("dropLabel", () => {
|
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expect(idx.dropLabel(48).labels()).toEqual(
|
||||
new Int32Array([99, 1002, 0, 22])
|
||||
);
|
||||
});
|
||||
});
|
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|
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test("KeyIndex", () => {
|
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describe("KeyIndex", () => {
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const idx = new Dataframe.KeyIndex(["red", "green", "blue"]);
|
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|
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expect(Dataframe.isLabelIndex(idx)).toBeTruthy();
|
||||
test("create", () => {
|
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expect(Dataframe.isLabelIndex(idx)).toBeTruthy();
|
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expect(() => new Dataframe.KeyIndex(["dup", "dup"])).toThrow(Error);
|
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expect(new Dataframe.KeyIndex().size()).toEqual(0);
|
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});
|
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|
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expect(idx.labels()).toEqual(["red", "green", "blue"]);
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expect(idx.size()).toEqual(3);
|
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expect(idx.getOffset("blue")).toEqual(2);
|
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expect(idx.getLabel(1)).toEqual("green");
|
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test("labels", () => {
|
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expect(idx.labels()).toEqual(["red", "green", "blue"]);
|
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expect(idx.size()).toEqual(3);
|
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expect(idx.getLabel(1)).toEqual("green");
|
||||
expect(idx.getLabels([2, 0])).toEqual(["blue", "red"]);
|
||||
});
|
||||
|
||||
expect(idx.subset(["green"]).labels()).toEqual(["green"]);
|
||||
expect(idx.subset(["green", "red"]).labels()).toEqual(["green", "red"]);
|
||||
expect(idx.isubset([2, 1, 0]).labels()).toEqual(["blue", "green", "red"]);
|
||||
test("offsets", () => {
|
||||
expect(idx.getOffset("blue")).toEqual(2);
|
||||
});
|
||||
|
||||
expect(idx.withLabel("yo").labels()).toEqual([
|
||||
"red",
|
||||
"green",
|
||||
"blue",
|
||||
"yo",
|
||||
]);
|
||||
expect(idx.withLabel("yo").getOffset("yo")).toEqual(3);
|
||||
expect(idx.dropLabel("blue").labels()).toEqual(["red", "green"]);
|
||||
test("subset", () => {
|
||||
expect(idx.subset(["green"]).labels()).toEqual(["green"]);
|
||||
expect(idx.subset(["green", "red"]).labels()).toEqual(["green", "red"]);
|
||||
});
|
||||
|
||||
test("isubset", () => {
|
||||
expect(idx.isubset([2, 1, 0]).labels()).toEqual(["blue", "green", "red"]);
|
||||
expect(() => idx.isubset([-1001])).toThrow(RangeError);
|
||||
expect(() => idx.isubset([1001])).toThrow(RangeError);
|
||||
});
|
||||
|
||||
test("isubsetMask", () => {
|
||||
expect(idx.isubsetMask([true, true, true]).labels()).toEqual([
|
||||
"red",
|
||||
"green",
|
||||
"blue",
|
||||
]);
|
||||
expect(idx.isubsetMask([false, false, false]).labels()).toEqual([]);
|
||||
expect(idx.isubsetMask([true, false, true]).labels()).toEqual([
|
||||
"red",
|
||||
"blue",
|
||||
]);
|
||||
expect(() => idx.isubsetMask([])).toThrow(RangeError);
|
||||
});
|
||||
|
||||
test("withLabel", () => {
|
||||
expect(idx.withLabel("yo").labels()).toEqual([
|
||||
"red",
|
||||
"green",
|
||||
"blue",
|
||||
"yo",
|
||||
]);
|
||||
expect(idx.withLabel("yo").getOffset("yo")).toEqual(3);
|
||||
expect(idx.withLabels(["hey", "there"]).labels()).toEqual([
|
||||
"red",
|
||||
"green",
|
||||
"blue",
|
||||
"hey",
|
||||
"there",
|
||||
]);
|
||||
});
|
||||
|
||||
test("dropLabel", () => {
|
||||
expect(idx.dropLabel("blue").labels()).toEqual(["red", "green"]);
|
||||
});
|
||||
});
|
||||
});
|
||||
|
||||
|
||||
Reference in New Issue
Block a user