mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-10-03 01:58:11 +08:00
TS typing for Dataframe (#2382)
* initial TS typing * first cut at Dataframe TS typing * more Dataframe typing * comments * more Dataframe cleanup * PR review fixes and improvements
This commit is contained in:
Bruce Martin
@@ -6,7 +6,8 @@ describe("dataframe constructor", () => {
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expect(df).toBeDefined();
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expect(df.dims).toEqual([0, 0]);
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expect(df).toHaveLength(0);
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expect(df.icol(0)).not.toBeDefined();
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expect(df.ihasCol(0)).toBeFalsy();
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expect(() => df.icol(0)).toThrow(RangeError);
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});
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test("create with default indices", () => {
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@@ -23,13 +24,19 @@ describe("dataframe constructor", () => {
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expect(df.at(2, 1)).toEqual(1);
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expect(df.iat(0, 0)).toEqual(0);
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expect(df.iat(2, 1)).toEqual(1);
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expect(Array.from(df.rowIndex.labels())).toEqual(
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df.rowIndex.getLabels(df.rowIndex.getOffsets(df.rowIndex.labels()))
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);
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expect(Array.from(df.colIndex.labels())).toEqual(
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df.colIndex.getLabels(df.colIndex.getOffsets(df.colIndex.labels()))
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);
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});
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test("create with labelled indices", () => {
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const df = new Dataframe.Dataframe(
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[3, 2],
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[new Int32Array([0, 1, 2]), new Int32Array([3, 4, 5])],
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'DenseInt32Index' is not assignab... Remove this comment to see the full error message
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new Dataframe.DenseInt32Index([2, 1, 0]),
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new Dataframe.KeyIndex(["A", "B"])
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);
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@@ -56,7 +63,6 @@ describe("simple data access", () => {
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new Float64Array([0.0, Number.NaN, Number.POSITIVE_INFINITY, 3.14159]),
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["red", "blue", "green", "nan"],
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],
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'DenseInt32Index' is not assignab... Remove this comment to see the full error message
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new Dataframe.DenseInt32Index([3, 2, 1, 0]),
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new Dataframe.KeyIndex(["numbers", "colors"])
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);
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@@ -123,7 +129,9 @@ describe("simple data access", () => {
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expect(df.has(3, "foo")).toBeFalsy();
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expect(df.has(-1, "numbers")).toBeFalsy();
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expect(df.has(-1, -1)).toBeFalsy();
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expect(df.has(null, null)).toBeFalsy();
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expect(
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df.has(null as unknown as number, null as unknown as number)
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).toBeFalsy();
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expect(df.has(0, "foo")).toBeFalsy();
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expect(df.has(99, "numbers")).toBeFalsy();
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expect(df.has(99, "foo")).toBeFalsy();
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@@ -141,12 +149,10 @@ describe("dataframe subsetting", () => {
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["red", "green", "blue"],
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],
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null, // identity index
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["int32", "string", "float32", "colors"])
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);
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test("all rows, one column", () => {
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'string[]' is not assignable to p... Remove this comment to see the full error message
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const dfA = sourceDf.subset(null, ["colors"]);
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expect(dfA).toBeDefined();
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expect(dfA.dims).toEqual([3, 1]);
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@@ -162,7 +168,6 @@ describe("dataframe subsetting", () => {
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});
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test("all rows, two columns", () => {
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'string[]' is not assignable to p... Remove this comment to see the full error message
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const dfB = sourceDf.subset(null, ["float32", "colors"]);
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expect(dfB).toBeDefined();
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expect(dfB.dims).toEqual([3, 2]);
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@@ -232,7 +237,6 @@ describe("dataframe subsetting", () => {
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});
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test("two rows, two colums", () => {
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'string[]' is not assignable to p... Remove this comment to see the full error message
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const dfF = sourceDf.subset([0, 2], ["int32", "float32"]);
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expect(dfF).toBeDefined();
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expect(dfF.dims).toEqual([2, 2]);
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@@ -242,7 +246,6 @@ describe("dataframe subsetting", () => {
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expect(dfF.colIndex.labels()).toEqual(["int32", "float32"]);
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// reverse the row and column order
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'string[]' is not assignable to p... Remove this comment to see the full error message
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const dfFr = sourceDf.subset([2, 0], ["float32", "int32"]);
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expect(dfFr).toBeDefined();
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expect(dfFr.dims).toEqual([2, 2]);
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@@ -255,26 +258,23 @@ describe("dataframe subsetting", () => {
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test("withRowIndex", () => {
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const df = sourceDf.subset(
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'string[]' is not assignable to p... Remove this comment to see the full error message
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["int32", "float32"],
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new Dataframe.DenseInt32Index([3, 2, 1])
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new Dataframe.DenseInt32Index([2, 1])
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);
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expect(df.dims).toEqual([2, 2]);
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expect(df.colIndex).toBeInstanceOf(Dataframe.KeyIndex);
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expect(df.rowIndex).toBeInstanceOf(Dataframe.DenseInt32Index);
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expect(df.at(3, "int32")).toEqual(df.iat(0, 0));
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expect(df.at(2, "int32")).toEqual(df.iat(0, 0));
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});
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test("withRowIndex error checks", () => {
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expect(() =>
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'string[]' is not assignable to p... Remove this comment to see the full error message
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sourceDf.subset(null, ["red"], new Dataframe.IdentityInt32Index(1))
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).toThrow(RangeError);
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expect(() =>
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'string[]' is not assignable to p... Remove this comment to see the full error message
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sourceDf.subset(null, ["red"], new Dataframe.DenseInt32Index([0, 1]))
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).toThrow(RangeError);
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expect(() =>
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'string[]' is not assignable to p... Remove this comment to see the full error message
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sourceDf.subset(null, ["red"], new Dataframe.KeyIndex([0, 1, 2, 3]))
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).toThrow(RangeError);
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});
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@@ -289,14 +289,12 @@ describe("dataframe subsetting", () => {
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new Float32Array([4.4, 5.5, 6.6]),
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["red", "green", "blue"],
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],
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'DenseInt32Index' is not assignab... Remove this comment to see the full error message
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new Dataframe.DenseInt32Index([2, 4, 6]),
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new Dataframe.KeyIndex(["int32", "string", "float32", "colors"])
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);
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const dfA = sourceDf.isubsetMask(
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new Uint8Array([0, 1, 1]),
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'Uint8Array' is not assignable to... Remove this comment to see the full error message
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new Uint8Array([1, 0, 0, 1])
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);
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expect(dfA.dims).toEqual([2, 2]);
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@@ -316,7 +314,6 @@ describe("dataframe subsetting", () => {
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["red", "green", "blue"],
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],
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null, // identity index
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["int32", "string", "float32", "colors"])
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);
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@@ -330,7 +327,6 @@ describe("dataframe subsetting", () => {
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});
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test("all rows, two cols", () => {
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'number[]' is not assignable to p... Remove this comment to see the full error message
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const dfA = sourceDf.isubset(null, [1, 2]);
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expect(dfA.dims).toEqual([3, 2]);
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expect(dfA.icol(0).asArray()).toEqual(["A", "B", "C"]);
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@@ -376,7 +372,6 @@ describe("dataframe factories", () => {
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const dfA = new Dataframe.Dataframe(
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[3, 2],
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[new Int32Array([0, 1, 2]), new Int32Array([3, 4, 5])],
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'DenseInt32Index' is not assignab... Remove this comment to see the full error message
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new Dataframe.DenseInt32Index([2, 1, 0]),
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new Dataframe.KeyIndex(["A", "B"])
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);
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@@ -401,7 +396,6 @@ describe("dataframe factories", () => {
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[true, false],
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["colors", "bools"])
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);
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const dfA = df.withCol("numbers", [1, 0]);
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@@ -425,7 +419,6 @@ describe("dataframe factories", () => {
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[true, false],
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'DenseInt32Index' is not assignab... Remove this comment to see the full error message
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new Dataframe.DenseInt32Index([74, 75])
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);
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const dfA = df.withCol(72, [1, 0]);
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@@ -451,7 +444,6 @@ describe("dataframe factories", () => {
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[true, false],
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'DenseInt32Index' is not assignab... Remove this comment to see the full error message
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new Dataframe.DenseInt32Index([74, 75])
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);
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const dfA = df.withCol(999, [1, 0]);
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@@ -560,7 +552,6 @@ describe("dataframe factories", () => {
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[1, 0],
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["colors", "bools", "numbers"])
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);
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@@ -569,14 +560,11 @@ describe("dataframe factories", () => {
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[3, 1],
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[["red", "blue", "green"]],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["colorsA"])
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);
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// @ts-expect-error ts-migrate(2554) FIXME: Expected 2 arguments, but got 1.
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expect(() => dfA.withColsFrom(dfB)).toThrow(RangeError);
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/* duplicate labels should throw an error */
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// @ts-expect-error ts-migrate(2554) FIXME: Expected 2 arguments, but got 1.
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expect(() => dfA.withColsFrom(dfA)).toThrow(Error);
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});
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@@ -587,18 +575,15 @@ describe("dataframe factories", () => {
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[2, 1],
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[["red", "blue"]],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["colors"])
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);
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const dfB = new Dataframe.Dataframe(
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[2, 1],
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[[true, false]],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["bools"])
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);
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// @ts-expect-error ts-migrate(2554) FIXME: Expected 2 arguments, but got 1.
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const dfLikeA = dfEmpty.withColsFrom(dfA);
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expect(dfLikeA).toBeDefined();
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expect(dfLikeA.dims).toEqual(dfA.dims);
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@@ -607,7 +592,6 @@ describe("dataframe factories", () => {
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expect(dfLikeA.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
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expect(dfLikeA.icol(0).asArray()).toEqual(dfA.icol(0).asArray());
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// @ts-expect-error ts-migrate(2554) FIXME: Expected 2 arguments, but got 1.
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const dfAlsoLikeA = dfA.withColsFrom(dfEmpty);
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expect(dfAlsoLikeA).toBeDefined();
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expect(dfAlsoLikeA.dims).toEqual(dfA.dims);
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@@ -616,7 +600,6 @@ describe("dataframe factories", () => {
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expect(dfAlsoLikeA.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
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expect(dfAlsoLikeA.icol(0).asArray()).toEqual(dfA.icol(0).asArray());
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// @ts-expect-error ts-migrate(2554) FIXME: Expected 2 arguments, but got 1.
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const dfC = dfA.withColsFrom(dfB);
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expect(dfC).toBeDefined();
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expect(dfC.dims).toEqual([2, 2]);
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@@ -633,7 +616,6 @@ describe("dataframe factories", () => {
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[2, 1],
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[["red", "blue"]],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["colors"])
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);
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const dfB = new Dataframe.Dataframe(
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@@ -644,7 +626,6 @@ describe("dataframe factories", () => {
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[1, 0],
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["colors", "bools", "numbers"])
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);
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@@ -677,7 +658,6 @@ describe("dataframe factories", () => {
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[2, 1],
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[["red", "blue"]],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["colors"])
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);
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const dfB = new Dataframe.Dataframe(
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@@ -688,7 +668,6 @@ describe("dataframe factories", () => {
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[1, 0],
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["colors", "bools", "numbers"])
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);
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@@ -712,7 +691,6 @@ describe("dataframe factories", () => {
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[1, 0],
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["colors", "bools", "numbers"])
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);
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const dfA = df.dropCol("colors");
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@@ -784,7 +762,6 @@ describe("dataframe factories", () => {
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[1, 0],
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'DenseInt32Index' is not assignab... Remove this comment to see the full error message
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new Dataframe.DenseInt32Index([102, 101, 100])
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);
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const dfA = df.dropCol(101);
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@@ -811,8 +788,7 @@ describe("dataframe factories", () => {
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new Float64Array(3).fill(1.1),
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]
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);
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// eslint-disable-next-line @typescript-eslint/no-explicit-any --- FIXME: disabled temporarily on migrate to TS.
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const dfB = dfA.mapColumns((col: any, idx: any) => {
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const dfB = dfA.mapColumns((col, idx) => {
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expect(dfA.icol(idx).asArray()).toBe(col);
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return col;
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});
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@@ -855,7 +831,6 @@ describe("dataframe factories", () => {
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[1, 0],
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
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new Dataframe.KeyIndex(["A", "B"])
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);
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const dfB = dfA.renameCol("B", "C");
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@@ -868,8 +843,7 @@ describe("dataframe factories", () => {
|
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});
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describe("dataframe col", () => {
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// eslint-disable-next-line @typescript-eslint/no-explicit-any --- FIXME: disabled temporarily on migrate to TS.
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let df: any = null;
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let df: Dataframe.Dataframe;
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beforeEach(() => {
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df = new Dataframe.Dataframe(
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[2, 2],
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@@ -878,7 +852,6 @@ describe("dataframe col", () => {
|
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[1, 0],
|
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],
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null,
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// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
|
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new Dataframe.KeyIndex(["A", "B"])
|
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);
|
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});
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@@ -887,8 +860,8 @@ describe("dataframe col", () => {
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expect(df).toBeDefined();
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expect(df.col("A")).toBe(df.icol(0));
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expect(df.col("B")).toBe(df.icol(1));
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expect(df.col("undefined")).toBeUndefined();
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expect(df.icol("undefined")).toBeUndefined();
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expect(() => df.col("undefined")).toThrow(RangeError);
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expect(() => df.icol("undefined" as unknown as number)).toThrow(RangeError);
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const colA = df.col("A");
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expect(colA).toBeInstanceOf(Function);
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@@ -942,13 +915,13 @@ describe("dataframe col", () => {
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expect(df.col("A").indexOf(true)).toEqual(0);
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expect(df.col("A").indexOf(false)).toEqual(1);
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expect(df.col("A").indexOf(99)).toBeUndefined();
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expect(df.col("A").indexOf(undefined)).toBeUndefined();
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expect(df.col("A").indexOf(undefined as unknown as number)).toBeUndefined();
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expect(df.col("A").indexOf(1)).toBeUndefined();
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expect(df.col("B").indexOf(1)).toEqual(0);
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expect(df.col("B").indexOf(0)).toEqual(1);
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expect(df.col("B").indexOf(99)).toBeUndefined();
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expect(df.col("B").indexOf(undefined)).toBeUndefined();
|
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expect(df.col("B").indexOf(undefined as unknown as number)).toBeUndefined();
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expect(df.col("B").indexOf(true)).toBeUndefined();
|
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});
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});
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@@ -991,7 +964,7 @@ describe("label indexing", () => {
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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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expect(idx.getOffsets([1, 3])).toEqual(new Int32Array([1, 3]));
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});
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|
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test("subset", () => {
|
||||
@@ -1069,7 +1042,7 @@ describe("label indexing", () => {
|
||||
false,
|
||||
])
|
||||
.labels()
|
||||
).toEqual(new Int32Array([]));
|
||||
).toEqual([]);
|
||||
expect(
|
||||
idx
|
||||
.isubsetMask([
|
||||
@@ -1163,16 +1136,14 @@ describe("label indexing", () => {
|
||||
expect(idx.labels()).toEqual(new Int32Array([99, 1002, 48, 0, 22]));
|
||||
expect(idx.size()).toEqual(5);
|
||||
expect(idx.getLabel(0)).toEqual(99);
|
||||
expect(idx.getLabels(new Int32Array([2, 4]))).toEqual(
|
||||
new Int32Array([48, 22])
|
||||
);
|
||||
expect(idx.getLabels(new Int32Array([2, 4]))).toEqual([48, 22]);
|
||||
expect(idx.getLabels([2, 4])).toEqual([48, 22]);
|
||||
});
|
||||
|
||||
test("offsets", () => {
|
||||
expect(idx.getOffset(1002)).toEqual(1);
|
||||
expect(idx.getOffset(0)).toEqual(3);
|
||||
expect(idx.getOffsets([0, 48])).toEqual([3, 2]);
|
||||
expect(idx.getOffsets([0, 48])).toEqual(new Int32Array([3, 2]));
|
||||
});
|
||||
|
||||
test("subset", () => {
|
||||
@@ -1199,7 +1170,7 @@ describe("label indexing", () => {
|
||||
);
|
||||
expect(
|
||||
idx.isubsetMask([false, false, false, false, false]).labels()
|
||||
).toEqual(new Int32Array([]));
|
||||
).toEqual([]);
|
||||
expect(idx.isubsetMask([true, true, false, true, true]).labels()).toEqual(
|
||||
new Int32Array([99, 1002, 0, 22])
|
||||
);
|
||||
@@ -1301,59 +1272,67 @@ describe("corner cases", () => {
|
||||
const idx = new Dataframe.IdentityInt32Index(10);
|
||||
expect(idx.getOffset(0)).toBe(0);
|
||||
expect(idx.getOffset(9)).toBe(9);
|
||||
expect(idx.getOffset(10)).toBeUndefined();
|
||||
expect(idx.getOffset(-1)).toBeUndefined();
|
||||
expect(idx.getOffset("sort")).toBeUndefined();
|
||||
expect(idx.getOffset("length")).toBeUndefined();
|
||||
expect(idx.getOffset(true)).toBeUndefined();
|
||||
expect(idx.getOffset(0.001)).toBeUndefined();
|
||||
expect(idx.getOffset({})).toBeUndefined();
|
||||
expect(idx.getOffset([])).toBeUndefined();
|
||||
expect(idx.getOffset(new Float32Array())).toBeUndefined();
|
||||
expect(idx.getOffset("__proto__")).toBeUndefined();
|
||||
expect(idx.getOffset(10)).toBe(-1);
|
||||
expect(idx.getOffset(-1)).toBe(-1);
|
||||
expect(idx.getOffset("sort")).toBe(-1);
|
||||
expect(idx.getOffset("length")).toBe(-1);
|
||||
expect(idx.getOffset(true as unknown as string)).toBe(-1);
|
||||
expect(idx.getOffset(0.001)).toBe(-1);
|
||||
expect(idx.getOffset({} as unknown as string)).toBe(-1);
|
||||
expect(idx.getOffset([] as unknown as string)).toBe(-1);
|
||||
expect(idx.getOffset(new Float32Array() as unknown as string)).toBe(-1);
|
||||
expect(idx.getOffset("__proto__")).toBe(-1);
|
||||
|
||||
expect(idx.getLabel(0)).toBe(0);
|
||||
expect(idx.getLabel(9)).toBe(9);
|
||||
expect(idx.getLabel(10)).toBeUndefined();
|
||||
expect(idx.getLabel(-1)).toBeUndefined();
|
||||
expect(idx.getLabel("sort")).toBeUndefined();
|
||||
expect(idx.getLabel("length")).toBeUndefined();
|
||||
expect(idx.getLabel(true)).toBeUndefined();
|
||||
expect(idx.getLabel("sort" as unknown as number)).toBeUndefined();
|
||||
expect(idx.getLabel("length" as unknown as number)).toBeUndefined();
|
||||
expect(idx.getLabel(true as unknown as number)).toBeUndefined();
|
||||
expect(idx.getLabel(0.001)).toBeUndefined();
|
||||
expect(idx.getLabel({})).toBeUndefined();
|
||||
expect(idx.getLabel([])).toBeUndefined();
|
||||
expect(idx.getLabel(new Float32Array())).toBeUndefined();
|
||||
expect(idx.getLabel("__proto__")).toBeUndefined();
|
||||
expect(idx.getLabel({} as unknown as number)).toBeUndefined();
|
||||
expect(idx.getLabel([] as unknown as number)).toBeUndefined();
|
||||
expect(
|
||||
idx.getLabel(new Float32Array() as unknown as number)
|
||||
).toBeUndefined();
|
||||
expect(idx.getLabel("__proto__" as unknown as number)).toBeUndefined();
|
||||
});
|
||||
|
||||
test("dense integer index rejects non-integer labels", () => {
|
||||
const idx = new Dataframe.DenseInt32Index([-10, 0, 3, 9, 10]);
|
||||
expect(idx.getOffset(-10)).toBe(0);
|
||||
expect(idx.getOffset(0)).toBe(1);
|
||||
expect(idx.getOffset(3)).toBe(2);
|
||||
expect(idx.getOffset(9)).toBe(3);
|
||||
expect(idx.getOffset(1)).toBeUndefined();
|
||||
expect(idx.getOffset(11)).toBeUndefined();
|
||||
expect(idx.getOffset(-1)).toBeUndefined();
|
||||
expect(idx.getOffset("sort")).toBeUndefined();
|
||||
expect(idx.getOffset("length")).toBeUndefined();
|
||||
expect(idx.getOffset(true)).toBeUndefined();
|
||||
expect(idx.getOffset(0.001)).toBeUndefined();
|
||||
expect(idx.getOffset({})).toBeUndefined();
|
||||
expect(idx.getOffset([])).toBeUndefined();
|
||||
expect(idx.getOffset(new Float32Array())).toBeUndefined();
|
||||
expect(idx.getOffset("__proto__")).toBeUndefined();
|
||||
expect(idx.getOffset(10)).toBe(4);
|
||||
|
||||
expect(idx.getOffset(1)).toBe(-1);
|
||||
expect(idx.getOffset(11)).toBe(-1);
|
||||
expect(idx.getOffset(-1)).toBe(-1);
|
||||
expect(idx.getOffset("sort")).toBe(-1);
|
||||
expect(idx.getOffset("length")).toBe(-1);
|
||||
expect(idx.getOffset(true as unknown as string)).toBe(-1);
|
||||
expect(idx.getOffset(0.001)).toBe(-1);
|
||||
expect(idx.getOffset({} as unknown as string)).toBe(-1);
|
||||
expect(idx.getOffset([] as unknown as string)).toBe(-1);
|
||||
expect(idx.getOffset(new Float32Array() as unknown as string)).toBe(-1);
|
||||
expect(idx.getOffset("__proto__")).toBe(-1);
|
||||
|
||||
expect(idx.getLabel(0)).toBe(-10);
|
||||
expect(idx.getLabel(4)).toBe(10);
|
||||
expect(idx.getLabel(10)).toBeUndefined();
|
||||
expect(idx.getLabel(-1)).toBeUndefined();
|
||||
expect(idx.getLabel("sort")).toBeUndefined();
|
||||
expect(idx.getLabel("length")).toBeUndefined();
|
||||
expect(idx.getLabel(true)).toBeUndefined();
|
||||
expect(idx.getLabel("sort" as unknown as number)).toBeUndefined();
|
||||
expect(idx.getLabel("length" as unknown as number)).toBeUndefined();
|
||||
expect(idx.getLabel(true as unknown as number)).toBeUndefined();
|
||||
expect(idx.getLabel(0.001)).toBeUndefined();
|
||||
expect(idx.getLabel({})).toBeUndefined();
|
||||
expect(idx.getLabel([])).toBeUndefined();
|
||||
expect(idx.getLabel(new Float32Array())).toBeUndefined();
|
||||
expect(idx.getLabel("__proto__")).toBeUndefined();
|
||||
expect(idx.getLabel({} as unknown as number)).toBeUndefined();
|
||||
expect(idx.getLabel([] as unknown as number)).toBeUndefined();
|
||||
expect(
|
||||
idx.getLabel(new Float32Array() as unknown as number)
|
||||
).toBeUndefined();
|
||||
expect(idx.getLabel("__proto__" as unknown as number)).toBeUndefined();
|
||||
});
|
||||
|
||||
test("Empty dataframe rejects bogus labels", () => {
|
||||
@@ -1361,39 +1340,55 @@ describe("corner cases", () => {
|
||||
|
||||
expect(df.hasCol("sort")).toBeFalsy();
|
||||
expect(df.hasCol(0)).toBeFalsy();
|
||||
expect(df.hasCol(true)).toBeFalsy();
|
||||
expect(df.hasCol(false)).toBeFalsy();
|
||||
expect(df.hasCol([])).toBeFalsy();
|
||||
expect(df.hasCol({})).toBeFalsy();
|
||||
expect(df.hasCol(null)).toBeFalsy();
|
||||
expect(df.hasCol(undefined)).toBeFalsy();
|
||||
expect(df.hasCol(true as unknown as number)).toBeFalsy();
|
||||
expect(df.hasCol(false as unknown as number)).toBeFalsy();
|
||||
expect(df.hasCol([] as unknown as number)).toBeFalsy();
|
||||
expect(df.hasCol({} as unknown as number)).toBeFalsy();
|
||||
expect(df.hasCol(null as unknown as number)).toBeFalsy();
|
||||
expect(df.hasCol(undefined as unknown as number)).toBeFalsy();
|
||||
|
||||
expect(df.col("sort")).toBeUndefined();
|
||||
expect(df.col(0)).toBeUndefined();
|
||||
expect(df.col(true)).toBeUndefined();
|
||||
expect(df.col(false)).toBeUndefined();
|
||||
expect(df.col([])).toBeUndefined();
|
||||
expect(df.col({})).toBeUndefined();
|
||||
expect(df.col(null)).toBeUndefined();
|
||||
expect(df.col(undefined)).toBeUndefined();
|
||||
expect(() => df.col("sort")).toThrow(RangeError);
|
||||
expect(() => df.col(0)).toThrow(RangeError);
|
||||
expect(() => df.col(true as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col(false as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col([] as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col({} as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col(null as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col(undefined as unknown as string)).toThrow(RangeError);
|
||||
|
||||
expect(df.icol("sort")).toBeUndefined();
|
||||
expect(df.icol(0)).toBeUndefined();
|
||||
expect(df.icol(true)).toBeUndefined();
|
||||
expect(df.icol(false)).toBeUndefined();
|
||||
expect(df.icol([])).toBeUndefined();
|
||||
expect(df.icol({})).toBeUndefined();
|
||||
expect(df.icol(null)).toBeUndefined();
|
||||
expect(df.icol(undefined)).toBeUndefined();
|
||||
expect(() => df.icol("sort" as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol(0)).toThrow(RangeError);
|
||||
expect(() => df.icol(true as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol(false as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol([] as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol({} as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol(null as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol(undefined as unknown as number)).toThrow(RangeError);
|
||||
|
||||
expect(df.ihas("sort", "length")).toBeFalsy();
|
||||
expect(df.ihas("0", "0")).toBeFalsy();
|
||||
expect(df.ihas("", "")).toBeFalsy();
|
||||
expect(df.ihas(null, null)).toBeFalsy();
|
||||
expect(df.ihas(undefined, undefined)).toBeFalsy();
|
||||
expect(df.ihas(true, true)).toBeFalsy();
|
||||
expect(df.ihas([], [])).toBeFalsy();
|
||||
expect(df.ihas({}, {})).toBeFalsy();
|
||||
expect(
|
||||
df.ihas("sort" as unknown as number, "length" as unknown as number)
|
||||
).toBeFalsy();
|
||||
expect(
|
||||
df.ihas("0" as unknown as number, "0" as unknown as number)
|
||||
).toBeFalsy();
|
||||
expect(
|
||||
df.ihas("" as unknown as number, "" as unknown as number)
|
||||
).toBeFalsy();
|
||||
expect(
|
||||
df.ihas(null as unknown as number, null as unknown as number)
|
||||
).toBeFalsy();
|
||||
expect(
|
||||
df.ihas(undefined as unknown as number, undefined as unknown as number)
|
||||
).toBeFalsy();
|
||||
expect(
|
||||
df.ihas(true as unknown as number, true as unknown as number)
|
||||
).toBeFalsy();
|
||||
expect(
|
||||
df.ihas([] as unknown as number, [] as unknown as number)
|
||||
).toBeFalsy();
|
||||
expect(
|
||||
df.ihas({} as unknown as number, {} as unknown as number)
|
||||
).toBeFalsy();
|
||||
});
|
||||
|
||||
test("Dataframe rejects bogus labels", () => {
|
||||
@@ -1404,58 +1399,64 @@ describe("corner cases", () => {
|
||||
[1, 0],
|
||||
],
|
||||
null,
|
||||
// @ts-expect-error ts-migrate(2345) FIXME: Argument of type 'KeyIndex' is not assignable to p... Remove this comment to see the full error message
|
||||
new Dataframe.KeyIndex(["A", "B"])
|
||||
);
|
||||
|
||||
expect(df.hasCol("sort")).toBeFalsy();
|
||||
expect(df.hasCol("__proto__")).toBeFalsy();
|
||||
expect(df.hasCol(0)).toBeFalsy();
|
||||
expect(df.hasCol(true)).toBeFalsy();
|
||||
expect(df.hasCol(false)).toBeFalsy();
|
||||
expect(df.hasCol([])).toBeFalsy();
|
||||
expect(df.hasCol({})).toBeFalsy();
|
||||
expect(df.hasCol(null)).toBeFalsy();
|
||||
expect(df.hasCol(undefined)).toBeFalsy();
|
||||
expect(df.hasCol(true as unknown as string)).toBeFalsy();
|
||||
expect(df.hasCol(false as unknown as string)).toBeFalsy();
|
||||
expect(df.hasCol([] as unknown as string)).toBeFalsy();
|
||||
expect(df.hasCol({} as unknown as string)).toBeFalsy();
|
||||
expect(df.hasCol(null as unknown as string)).toBeFalsy();
|
||||
expect(df.hasCol(undefined as unknown as string)).toBeFalsy();
|
||||
|
||||
expect(df.col("sort")).toBeUndefined();
|
||||
expect(df.col("__proto__")).toBeUndefined();
|
||||
expect(df.col(0)).toBeUndefined();
|
||||
expect(df.col(true)).toBeUndefined();
|
||||
expect(df.col(false)).toBeUndefined();
|
||||
expect(df.col([])).toBeUndefined();
|
||||
expect(df.col({})).toBeUndefined();
|
||||
expect(df.col(null)).toBeUndefined();
|
||||
expect(df.col(undefined)).toBeUndefined();
|
||||
expect(() => df.col("sort")).toThrow(RangeError);
|
||||
expect(() => df.col("__proto__")).toThrow(RangeError);
|
||||
expect(() => df.col(0)).toThrow(RangeError);
|
||||
expect(() => df.col(true as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col(false as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col([] as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col({} as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col(null as unknown as string)).toThrow(RangeError);
|
||||
expect(() => df.col(undefined as unknown as string)).toThrow(RangeError);
|
||||
|
||||
expect(df.icol("sort")).toBeUndefined();
|
||||
expect(df.icol("__proto__")).toBeUndefined();
|
||||
expect(df.icol(-1)).toBeUndefined();
|
||||
expect(df.icol(true)).toBeUndefined();
|
||||
expect(df.icol(false)).toBeUndefined();
|
||||
expect(df.icol([])).toBeUndefined();
|
||||
expect(df.icol({})).toBeUndefined();
|
||||
expect(df.icol(null)).toBeUndefined();
|
||||
expect(df.icol(undefined)).toBeUndefined();
|
||||
expect(() => df.icol("sort" as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol("__proto__" as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol(-1)).toThrow(RangeError);
|
||||
expect(() => df.icol(true as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol(false as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol([] as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol({} as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol(null as unknown as number)).toThrow(RangeError);
|
||||
expect(() => df.icol(undefined as unknown as number)).toThrow(RangeError);
|
||||
|
||||
expect(df.ihas("sort", "length")).toBeFalsy();
|
||||
expect(df.ihas("__proto__", "__proto__")).toBeFalsy();
|
||||
expect(
|
||||
df.ihas("sort" as unknown as number, "length" as unknown as number)
|
||||
).toBeFalsy();
|
||||
expect(
|
||||
df.ihas(
|
||||
"__proto__" as unknown as number,
|
||||
"__proto__" as unknown as number
|
||||
)
|
||||
).toBeFalsy();
|
||||
|
||||
expect(df.ihas(-1, 0)).toBeFalsy();
|
||||
expect(df.ihas("0", 0)).toBeFalsy();
|
||||
expect(df.ihas("", 0)).toBeFalsy();
|
||||
expect(df.ihas(null, 0)).toBeFalsy();
|
||||
expect(df.ihas(undefined, 0)).toBeFalsy();
|
||||
expect(df.ihas([], 0)).toBeFalsy();
|
||||
expect(df.ihas({}, 0)).toBeFalsy();
|
||||
expect(df.ihas("0" as unknown as number, 0)).toBeFalsy();
|
||||
expect(df.ihas("" as unknown as number, 0)).toBeFalsy();
|
||||
expect(df.ihas(null as unknown as number, 0)).toBeFalsy();
|
||||
expect(df.ihas(undefined as unknown as number, 0)).toBeFalsy();
|
||||
expect(df.ihas([] as unknown as number, 0)).toBeFalsy();
|
||||
expect(df.ihas({} as unknown as number, 0)).toBeFalsy();
|
||||
|
||||
expect(df.ihas(0, -1)).toBeFalsy();
|
||||
expect(df.ihas(0, "0")).toBeFalsy();
|
||||
expect(df.ihas(0, "")).toBeFalsy();
|
||||
expect(df.ihas(0, null)).toBeFalsy();
|
||||
expect(df.ihas(0, undefined)).toBeFalsy();
|
||||
expect(df.ihas(0, [])).toBeFalsy();
|
||||
expect(df.ihas(0, {})).toBeFalsy();
|
||||
expect(df.ihas(0, "0" as unknown as number)).toBeFalsy();
|
||||
expect(df.ihas(0, "" as unknown as number)).toBeFalsy();
|
||||
expect(df.ihas(0, null as unknown as number)).toBeFalsy();
|
||||
expect(df.ihas(0, undefined as unknown as number)).toBeFalsy();
|
||||
expect(df.ihas(0, [] as unknown as number)).toBeFalsy();
|
||||
expect(df.ihas(0, {} as unknown as number)).toBeFalsy();
|
||||
|
||||
expect(df.has("sort", "length")).toBeFalsy();
|
||||
expect(df.has("length", "sort")).toBeFalsy();
|
||||
@@ -1464,17 +1465,17 @@ describe("corner cases", () => {
|
||||
expect(df.has(-1, "A")).toBeFalsy();
|
||||
expect(df.has("0", "A")).toBeFalsy();
|
||||
expect(df.has("", "A")).toBeFalsy();
|
||||
expect(df.has(null, "A")).toBeFalsy();
|
||||
expect(df.has(undefined, "A")).toBeFalsy();
|
||||
expect(df.has([], "A")).toBeFalsy();
|
||||
expect(df.has({}, "A")).toBeFalsy();
|
||||
expect(df.has(null as unknown as string, "A")).toBeFalsy();
|
||||
expect(df.has(undefined as unknown as string, "A")).toBeFalsy();
|
||||
expect(df.has([] as unknown as string, "A")).toBeFalsy();
|
||||
expect(df.has({} as unknown as string, "A")).toBeFalsy();
|
||||
|
||||
expect(df.has(0, -1)).toBeFalsy();
|
||||
expect(df.has(0, "0")).toBeFalsy();
|
||||
expect(df.has(0, "")).toBeFalsy();
|
||||
expect(df.has(0, null)).toBeFalsy();
|
||||
expect(df.has(0, undefined)).toBeFalsy();
|
||||
expect(df.has(0, [])).toBeFalsy();
|
||||
expect(df.has(0, {})).toBeFalsy();
|
||||
expect(df.has(0, null as unknown as string)).toBeFalsy();
|
||||
expect(df.has(0, undefined as unknown as string)).toBeFalsy();
|
||||
expect(df.has(0, [] as unknown as string)).toBeFalsy();
|
||||
expect(df.has(0, {} as unknown as string)).toBeFalsy();
|
||||
});
|
||||
});
|
||||
|
||||
Reference in New Issue
Block a user