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TS migration. #2288. (#2328)

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* Added TS. Updated build and linting config. Added types.

* [ts-migrate][.] Rename files from JS/JSX to TS/TSX

Co-authored-by: ts-migrate <>

* [ts-migrate][.] Run TS Migrate

Co-authored-by: ts-migrate <>

* Corrected files mangled by ts-migrate.

* Updated lint config, minor linting.

* Re-enabled Husky.

* Updated tests and config.

* Reverted webpack devtool config.

* Removed obsolete snapshots.

* Added annotations snap.

* Updated tsconfig includes wrt linting.

* Removed ts-migrate.

Co-authored-by: Timmy Huang <tihuan@users.noreply.github.com>
This commit is contained in:
Mim Hastie
2021-07-26 20:18:17 +00:00
committed by GitHub
co-authored by ts-migrate Timmy Huang
parent 7328cbdbd5
commit 934cc5c69b
206 changed files with 4719 additions and 2085 deletions
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client/__tests__/util/dataframe/histogram.test.js
-103
View File
@@ -1,103 +0,0 @@
import * as Dataframe from "../../../src/util/dataframe";
describe("Dataframe column histogram", () => {
test("categorical by categorical", () => {
const df = new Dataframe.Dataframe(
[3, 3],
[["n1", "n2", "n3"], ["c1", "c2", "c3"], new Int32Array([0, 1, 2])],
null,
new Dataframe.KeyIndex(["name", "cat", "value"])
);
const h1 = df.col("cat").histogram(df.col("name"));
expect(h1).toMatchObject(
new Map([
["n1", new Map([["c1", 1]])],
["n2", new Map([["c2", 1]])],
["n3", new Map([["c3", 1]])],
])
);
// memoized?
expect(df.col("cat").histogram(df.col("name"))).toMatchObject(h1);
});
test("continuous by categorical", () => {
const df = new Dataframe.Dataframe(
[3, 3],
[["n1", "n2", "n3"], ["c1", "c2", "c3"], new Int32Array([0, 1, 2])],
null,
new Dataframe.KeyIndex(["name", "cat", "value"])
);
const h1 = df.col("value").histogram(3, [0, 2], df.col("name"));
expect(h1).toMatchObject(
new Map([
["n1", [1, 0, 0]],
["n2", [0, 1, 0]],
["n3", [0, 0, 1]],
])
);
// memoized?
expect(df.col("value").histogram(3, [0, 2], df.col("name"))).toMatchObject(
h1
);
});
test("categorical", () => {
const df = new Dataframe.Dataframe(
[3, 3],
[["n1", "n2", "n3"], ["c1", "c2", "c3"], new Int32Array([0, 1, 2])],
null,
new Dataframe.KeyIndex(["name", "cat", "value"])
);
const h1 = df.col("cat").histogram();
expect(h1).toMatchObject(
new Map([
["c1", 1],
["c2", 1],
["c3", 1],
])
);
// memoized?
expect(df.col("value").histogram(3, [0, 2])).toMatchObject(h1);
});
test("continuous", () => {
const df = new Dataframe.Dataframe(
[3, 3],
[["n1", "n2", "n3"], ["c1", "c2", "c3"], new Int32Array([0, 1, 2])],
null,
new Dataframe.KeyIndex(["name", "cat", "value"])
);
const h1 = df.col("value").histogram(3, [0, 2]);
expect(h1).toMatchObject([1, 1, 1]);
// memoized?
expect(df.col("value").histogram(3, [0, 2])).toMatchObject(h1);
});
test("continuous thesholds correct", () => {
const vals = [0, 1, 9, 10, 11, 20, 99, 100];
const df = new Dataframe.Dataframe(
[8, 2],
[new Int32Array(vals), new Float32Array(vals)]
);
expect(df.col(0).histogram(5, [0, 100])).toEqual([5, 1, 0, 0, 2]);
expect(df.col(1).histogram(5, [0, 100])).toEqual([5, 1, 0, 0, 2]);
expect(df.col(0).histogram(2, [0, 10])).toEqual([2, 2]);
expect(df.col(0).histogram(10, [0, 100])).toEqual([
3,
2,
1,
0,
0,
0,
0,
0,
0,
2,
]);
});
});