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* revert all commits to before Typescript migration * update compat workflow to match latest deps (#2335) * update compat workflow to match latest deps * attempt to debug * attempt to debug * remove debugging code * typo * update deps to match desktop (#2340) * fix: don't run lint with `--fix` on push tests (#2273) * fix: don't run lint with `--fix` on push tests * npx Co-authored-by: maniarathi <mani.arathi@gmail.com> Co-authored-by: Madison Dunitz <madison.dunitz@chanzuckerberg.com> * rename X_approx_distribution to X_approximate_distribution (#2337) * Correctly handle non-finite numbers in heuristic determination of X distribution (#2342) * handle non-finites explicitly * improve and test edge case handling for distribution estimation * revert debugging changes * code readability * clean up type inferencing (#2332) * unit tests for 64 bit conversion * clean up type handling * type inference tests * more type inference fixes * use schema to determine user intent for data typing * stop using deprecated API * fbs type encoding test * add missing test * add more tests * correctly infer X type for CXG adaptor * lint * fix typo * ts migration * cleanup from PR review * lint * PR review changes * remove unused packages from client (#2359) * remove unused packages from client * add missing peer dep * fix: disable FE auth testing on compatibility tests (#2377) * update: release process (#2277) Co-authored-by: maniarathi <mani.arathi@gmail.com> * fix: remove spaces in param setup (#2380) * delete deploy workflow (#2396) * undo reformatting which now does not pass lint * fix snapshots which changed due to npm dep changes * add missing quoting to snapshot * another snapshot typo fix * TS Revert (2) - replay PR #2347 and #2354 (#2403) * replay edits from PR 2347 * TS Revert (3) - replay edits in PR #2327 (#2404) * replay edits in PR 2327 * TS Revert (4) - replay PR #2355 (#2405) * replay edits in PR 2355 * add additional babel config * reformat with new prettier config Co-authored-by: Severiano Badajoz <sbadajoz@chanzuckerberg.com> Co-authored-by: maniarathi <mani.arathi@gmail.com> Co-authored-by: Madison Dunitz <madison.dunitz@chanzuckerberg.com>
95 lines
2.6 KiB
JavaScript
95 lines
2.6 KiB
JavaScript
import * as Dataframe from "../../../src/util/dataframe";
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describe("Dataframe column histogram", () => {
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test("categorical by categorical", () => {
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const df = new Dataframe.Dataframe(
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[3, 3],
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[["n1", "n2", "n3"], ["c1", "c2", "c3"], new Int32Array([0, 1, 2])],
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null,
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new Dataframe.KeyIndex(["name", "cat", "value"])
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);
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const h1 = df.col("cat").histogram(df.col("name"));
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expect(h1).toMatchObject(
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new Map([
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["n1", new Map([["c1", 1]])],
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["n2", new Map([["c2", 1]])],
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["n3", new Map([["c3", 1]])],
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])
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);
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// memoized?
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expect(df.col("cat").histogram(df.col("name"))).toMatchObject(h1);
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});
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test("continuous by categorical", () => {
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const df = new Dataframe.Dataframe(
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[3, 3],
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[["n1", "n2", "n3"], ["c1", "c2", "c3"], new Int32Array([0, 1, 2])],
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null,
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new Dataframe.KeyIndex(["name", "cat", "value"])
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);
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const h1 = df.col("value").histogram(3, [0, 2], df.col("name"));
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expect(h1).toMatchObject(
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new Map([
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["n1", [1, 0, 0]],
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["n2", [0, 1, 0]],
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["n3", [0, 0, 1]],
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])
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);
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// memoized?
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expect(df.col("value").histogram(3, [0, 2], df.col("name"))).toMatchObject(
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h1
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);
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});
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test("categorical", () => {
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const df = new Dataframe.Dataframe(
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[3, 3],
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[["n1", "n2", "n3"], ["c1", "c2", "c3"], new Int32Array([0, 1, 2])],
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null,
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new Dataframe.KeyIndex(["name", "cat", "value"])
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);
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const h1 = df.col("cat").histogram();
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expect(h1).toMatchObject(
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new Map([
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["c1", 1],
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["c2", 1],
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["c3", 1],
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])
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);
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// memoized?
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expect(df.col("value").histogram(3, [0, 2])).toMatchObject(h1);
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});
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test("continuous", () => {
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const df = new Dataframe.Dataframe(
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[3, 3],
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[["n1", "n2", "n3"], ["c1", "c2", "c3"], new Int32Array([0, 1, 2])],
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null,
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new Dataframe.KeyIndex(["name", "cat", "value"])
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);
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const h1 = df.col("value").histogram(3, [0, 2]);
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expect(h1).toMatchObject([1, 1, 1]);
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// memoized?
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expect(df.col("value").histogram(3, [0, 2])).toMatchObject(h1);
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});
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test("continuous thesholds correct", () => {
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const vals = [0, 1, 9, 10, 11, 20, 99, 100];
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const df = new Dataframe.Dataframe(
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[8, 2],
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[new Int32Array(vals), new Float32Array(vals)]
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);
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expect(df.col(0).histogram(5, [0, 100])).toEqual([5, 1, 0, 0, 2]);
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expect(df.col(1).histogram(5, [0, 100])).toEqual([5, 1, 0, 0, 2]);
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expect(df.col(0).histogram(2, [0, 10])).toEqual([2, 2]);
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expect(df.col(0).histogram(10, [0, 100])).toEqual([
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3, 2, 1, 0, 0, 0, 0, 0, 0, 2,
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]);
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});
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});
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