Files
cellxgene/client/__tests__/util/dataframe/dataframe.test.js
Bruce Martin eaae6df5e3 TS Revert (1) (#2402)
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Co-authored-by: maniarathi <mani.arathi@gmail.com>
Co-authored-by: Madison Dunitz <madison.dunitz@chanzuckerberg.com>

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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>
2021-08-23 15:01:36 -07:00

1441 lines
47 KiB
JavaScript

import * as Dataframe from "../../../src/util/dataframe";
describe("dataframe constructor", () => {
test("empty dataframe", () => {
const df = new Dataframe.Dataframe([0, 0], []);
expect(df).toBeDefined();
expect(df.dims).toEqual([0, 0]);
expect(df).toHaveLength(0);
expect(df.icol(0)).not.toBeDefined();
});
test("create with default indices", () => {
const df = new Dataframe.Dataframe(
[3, 2],
[new Int32Array(3).fill(0), new Int32Array(3).fill(1)]
);
expect(df).toBeDefined();
expect(df.dims).toEqual([3, 2]);
expect(df.rowIndex).toBeInstanceOf(Dataframe.IdentityInt32Index);
expect(df.colIndex).toBeInstanceOf(Dataframe.IdentityInt32Index);
expect(df.at(0, 0)).toEqual(0);
expect(df.at(2, 1)).toEqual(1);
expect(df.iat(0, 0)).toEqual(0);
expect(df.iat(2, 1)).toEqual(1);
});
test("create with labelled indices", () => {
const df = new Dataframe.Dataframe(
[3, 2],
[new Int32Array([0, 1, 2]), new Int32Array([3, 4, 5])],
new Dataframe.DenseInt32Index([2, 1, 0]),
new Dataframe.KeyIndex(["A", "B"])
);
expect(df).toBeDefined();
expect(df.dims).toEqual([3, 2]);
expect(df.rowIndex).toBeInstanceOf(Dataframe.DenseInt32Index);
expect(df.colIndex).toBeInstanceOf(Dataframe.KeyIndex);
expect(df.rowIndex.labels()).toEqual(new Int32Array([2, 1, 0]));
expect(df.colIndex.labels()).toEqual(["A", "B"]);
expect(df.at(0, "A")).toEqual(2);
expect(df.at(2, "B")).toEqual(3);
expect(df.iat(0, 0)).toEqual(0);
expect(df.iat(2, 1)).toEqual(5);
});
});
describe("simple data access", () => {
const df = new Dataframe.Dataframe(
[4, 2],
[
new Float64Array([0.0, Number.NaN, Number.POSITIVE_INFINITY, 3.14159]),
["red", "blue", "green", "nan"],
],
new Dataframe.DenseInt32Index([3, 2, 1, 0]),
new Dataframe.KeyIndex(["numbers", "colors"])
);
test("iat", () => {
expect(df).toBeDefined();
// present
expect(df.iat(0, 0)).toEqual(0.0);
expect(df.iat(0, 1)).toEqual("red");
expect(df.iat(1, 0)).toEqual(Number.NaN);
expect(df.iat(1, 1)).toEqual("blue");
expect(df.iat(2, 0)).toEqual(Number.POSITIVE_INFINITY);
expect(df.iat(2, 1)).toEqual("green");
expect(df.iat(3, 0)).toEqual(3.14159);
expect(df.iat(3, 1)).toEqual("nan");
// labels out of range have no defined behavior
});
test("at", () => {
expect(df).toBeDefined();
// present
expect(df.at(3, "numbers")).toEqual(0.0);
expect(df.at(3, "colors")).toEqual("red");
expect(df.at(2, "numbers")).toEqual(Number.NaN);
expect(df.at(2, "colors")).toEqual("blue");
expect(df.at(1, "numbers")).toEqual(Number.POSITIVE_INFINITY);
expect(df.at(1, "colors")).toEqual("green");
expect(df.at(0, "numbers")).toEqual(3.14159);
expect(df.at(0, "colors")).toEqual("nan");
// labels out of range have no defined behavior
});
test("ihas", () => {
expect(df).toBeDefined();
// present
expect(df.ihas(0, 0)).toBeTruthy();
expect(df.ihas(1, 1)).toBeTruthy();
expect(df.ihas(3, 1)).toBeTruthy();
// not present
expect(df.ihas(-1, -1)).toBeFalsy();
expect(df.ihas(0, 99)).toBeFalsy();
expect(df.ihas(99, 0)).toBeFalsy();
expect(df.ihas(99, 99)).toBeFalsy();
expect(df.ihas(-1, 0)).toBeFalsy();
expect(df.ihas(0, -1)).toBeFalsy();
});
test("has", () => {
expect(df).toBeDefined();
// present
expect(df.has(3, "numbers")).toBeTruthy();
expect(df.has(0, "numbers")).toBeTruthy();
expect(df.has(3, "colors")).toBeTruthy();
expect(df.has(0, "colors")).toBeTruthy();
// not present
expect(df.has(3, "foo")).toBeFalsy();
expect(df.has(-1, "numbers")).toBeFalsy();
expect(df.has(-1, -1)).toBeFalsy();
expect(df.has(null, null)).toBeFalsy();
expect(df.has(0, "foo")).toBeFalsy();
expect(df.has(99, "numbers")).toBeFalsy();
expect(df.has(99, "foo")).toBeFalsy();
});
});
describe("dataframe subsetting", () => {
describe("subset", () => {
const sourceDf = new Dataframe.Dataframe(
[3, 4],
[
new Int32Array([0, 1, 2]),
["A", "B", "C"],
new Float32Array([4.4, 5.5, 6.6]),
["red", "green", "blue"],
],
null, // identity index
new Dataframe.KeyIndex(["int32", "string", "float32", "colors"])
);
test("all rows, one column", () => {
const dfA = sourceDf.subset(null, ["colors"]);
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([3, 1]);
expect(dfA.iat(0, 0)).toEqual("red");
expect(dfA.at(2, "colors")).toEqual("blue");
expect(dfA.col("colors").asArray()).toEqual(["red", "green", "blue"]);
expect(dfA.icol(0).asArray()).toEqual(["red", "green", "blue"]);
expect(dfA.col("colors").asArray()).toEqual(
sourceDf.col("colors").asArray()
);
expect(dfA.rowIndex.labels()).toEqual(sourceDf.rowIndex.labels());
expect(dfA.colIndex.labels()).toEqual(["colors"]);
});
test("all rows, two columns", () => {
const dfB = sourceDf.subset(null, ["float32", "colors"]);
expect(dfB).toBeDefined();
expect(dfB.dims).toEqual([3, 2]);
expect(dfB.iat(0, 0)).toBeCloseTo(4.4);
expect(dfB.iat(0, 1)).toEqual("red");
expect(dfB.at(2, "colors")).toEqual("blue");
expect(dfB.at(2, "float32")).toBeCloseTo(6.6);
expect(dfB.col("colors").asArray()).toEqual(["red", "green", "blue"]);
expect(dfB.col("float32").asArray()).toEqual(
new Float32Array([4.4, 5.5, 6.6])
);
expect(dfB.icol(0).asArray()).toEqual(dfB.col("float32").asArray());
expect(dfB.icol(1).asArray()).toEqual(dfB.col("colors").asArray());
expect(dfB.col("colors").asArray()).toEqual(
sourceDf.col("colors").asArray()
);
expect(dfB.col("float32").asArray()).toEqual(
sourceDf.col("float32").asArray()
);
expect(dfB.rowIndex.labels()).toEqual(sourceDf.rowIndex.labels());
expect(dfB.colIndex.labels()).toEqual(["float32", "colors"]);
});
test("one row, all columns", () => {
const dfC = sourceDf.subset([1], null);
expect(dfC).toBeDefined();
expect(dfC.dims).toEqual([1, 4]);
expect(dfC.iat(0, 0)).toEqual(1);
expect(dfC.iat(0, 1)).toEqual("B");
expect(dfC.iat(0, 2)).toBeCloseTo(5.5);
expect(dfC.iat(0, 3)).toEqual("green");
expect(dfC.rowIndex.labels()).toEqual(new Int32Array([1]));
expect(dfC.colIndex.labels()).toEqual(sourceDf.colIndex.labels());
});
test("two rows, all columns", () => {
const dfD = sourceDf.subset([0, 2], null);
expect(dfD).toBeDefined();
expect(dfD.dims).toEqual([2, 4]);
expect(dfD.icol(0).asArray()).toEqual(new Int32Array([0, 2]));
expect(dfD.icol(1).asArray()).toEqual(["A", "C"]);
expect(dfD.icol(2).asArray()).toEqual(new Float32Array([4.4, 6.6]));
expect(dfD.icol(3).asArray()).toEqual(["red", "blue"]);
expect(dfD.rowIndex.labels()).toEqual(new Int32Array([0, 2]));
expect(dfD.colIndex.labels()).toEqual(sourceDf.colIndex.labels());
// reverse the row order
const dfDr = sourceDf.subset([2, 0], null);
expect(dfDr.icol(0).asArray()).toEqual(new Int32Array([2, 0]));
expect(dfDr.icol(1).asArray()).toEqual(["C", "A"]);
expect(dfDr.icol(2).asArray()).toEqual(new Float32Array([6.6, 4.4]));
expect(dfDr.icol(3).asArray()).toEqual(["blue", "red"]);
expect(dfDr.rowIndex.labels()).toEqual(new Int32Array([2, 0]));
expect(dfDr.colIndex.labels()).toEqual(sourceDf.colIndex.labels());
});
test("all rows, all columns", () => {
const dfE = sourceDf.subset(null, null);
expect(dfE).toBeDefined();
expect(dfE.dims).toEqual([3, 4]);
expect(dfE.icol(0).asArray()).toEqual(sourceDf.icol(0).asArray());
expect(dfE.icol(1).asArray()).toEqual(sourceDf.icol(1).asArray());
expect(dfE.icol(2).asArray()).toEqual(sourceDf.icol(2).asArray());
expect(dfE.icol(3).asArray()).toEqual(sourceDf.icol(3).asArray());
expect(dfE.rowIndex.labels()).toEqual(sourceDf.rowIndex.labels());
expect(dfE.colIndex.labels()).toEqual(sourceDf.colIndex.labels());
});
test("two rows, two colums", () => {
const dfF = sourceDf.subset([0, 2], ["int32", "float32"]);
expect(dfF).toBeDefined();
expect(dfF.dims).toEqual([2, 2]);
expect(dfF.icol(0).asArray()).toEqual(new Int32Array([0, 2]));
expect(dfF.icol(1).asArray()).toEqual(new Float32Array([4.4, 6.6]));
expect(dfF.rowIndex.labels()).toEqual(new Int32Array([0, 2]));
expect(dfF.colIndex.labels()).toEqual(["int32", "float32"]);
// reverse the row and column order
const dfFr = sourceDf.subset([2, 0], ["float32", "int32"]);
expect(dfFr).toBeDefined();
expect(dfFr.dims).toEqual([2, 2]);
expect(dfFr.icol(0).asArray()).toEqual(new Float32Array([6.6, 4.4]));
expect(dfFr.icol(1).asArray()).toEqual(new Int32Array([2, 0]));
expect(dfFr.rowIndex.labels()).toEqual(new Int32Array([2, 0]));
expect(dfFr.colIndex.labels()).toEqual(["float32", "int32"]);
});
test("withRowIndex", () => {
const df = sourceDf.subset(
null,
["int32", "float32"],
new Dataframe.DenseInt32Index([3, 2, 1])
);
expect(df.colIndex).toBeInstanceOf(Dataframe.KeyIndex);
expect(df.rowIndex).toBeInstanceOf(Dataframe.DenseInt32Index);
expect(df.at(3, "int32")).toEqual(df.iat(0, 0));
});
test("withRowIndex error checks", () => {
expect(() =>
sourceDf.subset(null, ["red"], new Dataframe.IdentityInt32Index(1))
).toThrow(RangeError);
expect(() =>
sourceDf.subset(null, ["red"], new Dataframe.DenseInt32Index([0, 1]))
).toThrow(RangeError);
expect(() =>
sourceDf.subset(null, ["red"], new Dataframe.KeyIndex([0, 1, 2, 3]))
).toThrow(RangeError);
});
});
test("isubsetMask", () => {
const sourceDf = new Dataframe.Dataframe(
[3, 4],
[
new Int32Array([0, 1, 2]),
["A", "B", "C"],
new Float32Array([4.4, 5.5, 6.6]),
["red", "green", "blue"],
],
new Dataframe.DenseInt32Index([2, 4, 6]),
new Dataframe.KeyIndex(["int32", "string", "float32", "colors"])
);
const dfA = sourceDf.isubsetMask(
new Uint8Array([0, 1, 1]),
new Uint8Array([1, 0, 0, 1])
);
expect(dfA.dims).toEqual([2, 2]);
expect(dfA.icol(0).asArray()).toEqual(new Int32Array([1, 2]));
expect(dfA.icol(1).asArray()).toEqual(["green", "blue"]);
expect(dfA.rowIndex.labels()).toEqual(new Int32Array([4, 6]));
expect(dfA.colIndex.labels()).toEqual(["int32", "colors"]);
});
describe("isubset", () => {
const sourceDf = new Dataframe.Dataframe(
[3, 4],
[
new Int32Array([0, 1, 2]),
["A", "B", "C"],
new Float32Array([4.4, 5.5, 6.6]),
["red", "green", "blue"],
],
null, // identity index
new Dataframe.KeyIndex(["int32", "string", "float32", "colors"])
);
test("one row, all cols", () => {
const dfA = sourceDf.isubset([1], null);
expect(dfA.dims).toEqual([1, 4]);
expect(dfA.icol(0).asArray()).toEqual(new Int32Array([1]));
expect(dfA.icol(1).asArray()).toEqual(["B"]);
expect(dfA.icol(2).asArray()).toEqual(new Float32Array([5.5]));
expect(dfA.icol(3).asArray()).toEqual(["green"]);
});
test("all rows, two cols", () => {
const dfA = sourceDf.isubset(null, [1, 2]);
expect(dfA.dims).toEqual([3, 2]);
expect(dfA.icol(0).asArray()).toEqual(["A", "B", "C"]);
expect(dfA.icol(1).asArray()).toEqual(new Float32Array([4.4, 5.5, 6.6]));
expect(dfA.col("string")).toBe(dfA.icol(0));
expect(dfA.col("float32")).toBe(dfA.icol(1));
});
test("out of order rows", () => {
const dfA = sourceDf.isubset([2, 0], null);
expect(dfA.dims).toEqual([2, 4]);
expect(dfA.icol(0).asArray()).toEqual(new Int32Array([2, 0]));
expect(dfA.icol(1).asArray()).toEqual(["C", "A"]);
expect(dfA.icol(2).asArray()).toEqual(new Float32Array([6.6, 4.4]));
expect(dfA.icol(3).asArray()).toEqual(["blue", "red"]);
});
});
});
describe("dataframe factories", () => {
test("create", () => {
const df = Dataframe.Dataframe.create(
[3, 3],
[
new Array(3).fill(0),
new Int16Array(3).fill(99),
new Float64Array(3).fill(1.1),
]
);
expect(df).toBeDefined();
expect(df.dims).toEqual([3, 3]);
expect(df).toHaveLength(3);
expect(df.iat(0, 0)).toEqual(0);
expect(df.iat(1, 1)).toEqual(99);
expect(df.iat(2, 2)).toBeCloseTo(1.1);
expect(df.iat(0, 0)).toEqual(df.at(0, 0));
expect(df.iat(1, 1)).toEqual(df.at(1, 1));
expect(df.iat(2, 2)).toEqual(df.at(2, 2));
});
test("clone", () => {
const dfA = new Dataframe.Dataframe(
[3, 2],
[new Int32Array([0, 1, 2]), new Int32Array([3, 4, 5])],
new Dataframe.DenseInt32Index([2, 1, 0]),
new Dataframe.KeyIndex(["A", "B"])
);
const dfB = dfA.clone();
expect(dfB).not.toBe(dfA);
expect(dfB.dims).toEqual(dfA.dims);
expect(dfB).toHaveLength(dfA.length);
expect(dfB.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
expect(dfB.colIndex.labels()).toEqual(dfA.colIndex.labels());
for (let i = 0, l = dfB.dims[1]; i < l; i += 1) {
expect(dfB.icol(i).asArray()).toEqual(dfA.icol(i).asArray());
}
});
describe("withCol", () => {
test("KeyIndex", () => {
const df = new Dataframe.Dataframe(
[2, 2],
[
["red", "blue"],
[true, false],
],
null,
new Dataframe.KeyIndex(["colors", "bools"])
);
const dfA = df.withCol("numbers", [1, 0]);
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([2, 3]);
expect(dfA.icol(0).asArray()).toEqual(["red", "blue"]);
expect(dfA.icol(1).asArray()).toEqual([true, false]);
expect(dfA.icol(2).asArray()).toEqual([1, 0]);
expect(dfA.col("numbers").asArray()).toEqual([1, 0]);
expect(dfA.colIndex.labels()).toEqual(["colors", "bools", "numbers"]);
expect(df.colIndex.labels()).toEqual(["colors", "bools"]);
expect(df.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
});
test("DenseInt32Index", () => {
const df = new Dataframe.Dataframe(
[2, 2],
[
["red", "blue"],
[true, false],
],
null,
new Dataframe.DenseInt32Index([74, 75])
);
const dfA = df.withCol(72, [1, 0]);
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([2, 3]);
expect(dfA.icol(0).asArray()).toEqual(["red", "blue"]);
expect(dfA.icol(1).asArray()).toEqual([true, false]);
expect(dfA.icol(2).asArray()).toEqual([1, 0]);
expect(dfA.col(74).asArray()).toEqual(["red", "blue"]);
expect(dfA.col(75).asArray()).toEqual([true, false]);
expect(dfA.col(72).asArray()).toEqual([1, 0]);
expect(dfA.colIndex.labels()).toEqual(new Int32Array([74, 75, 72]));
expect(df.colIndex.labels()).toEqual(new Int32Array([74, 75]));
expect(df.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
});
test("DenseInt32Index promote", () => {
const df = new Dataframe.Dataframe(
[2, 2],
[
["red", "blue"],
[true, false],
],
null,
new Dataframe.DenseInt32Index([74, 75])
);
const dfA = df.withCol(999, [1, 0]);
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([2, 3]);
expect(dfA.icol(0).asArray()).toEqual(["red", "blue"]);
expect(dfA.icol(1).asArray()).toEqual([true, false]);
expect(dfA.icol(2).asArray()).toEqual([1, 0]);
expect(dfA.col(74).asArray()).toEqual(["red", "blue"]);
expect(dfA.col(75).asArray()).toEqual([true, false]);
expect(dfA.col(999).asArray()).toEqual([1, 0]);
expect(dfA.colIndex.labels()).toEqual(new Int32Array([74, 75, 999]));
expect(df.colIndex.labels()).toEqual(new Int32Array([74, 75]));
expect(df.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
});
test("IdentityInt32Index with last", () => {
const df = new Dataframe.Dataframe(
[2, 2],
[
["red", "blue"],
[true, false],
],
null,
null
);
const dfA = df.withCol(2, [1, 0]);
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([2, 3]);
expect(dfA.icol(0).asArray()).toEqual(["red", "blue"]);
expect(dfA.icol(1).asArray()).toEqual([true, false]);
expect(dfA.icol(2).asArray()).toEqual([1, 0]);
expect(dfA.col(0).asArray()).toEqual(["red", "blue"]);
expect(dfA.col(1).asArray()).toEqual([true, false]);
expect(dfA.col(2).asArray()).toEqual([1, 0]);
expect(dfA.colIndex.labels()).toEqual(new Int32Array([0, 1, 2]));
expect(df.colIndex.labels()).toEqual(new Int32Array([0, 1]));
expect(df.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
});
test("IdentityInt32Index promote", () => {
const df = new Dataframe.Dataframe(
[2, 2],
[
["red", "blue"],
[true, false],
],
null,
null
);
const dfA = df.withCol(99, [1, 0]);
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([2, 3]);
expect(dfA.icol(0).asArray()).toEqual(["red", "blue"]);
expect(dfA.icol(1).asArray()).toEqual([true, false]);
expect(dfA.icol(2).asArray()).toEqual([1, 0]);
expect(dfA.col(0).asArray()).toEqual(["red", "blue"]);
expect(dfA.col(1).asArray()).toEqual([true, false]);
expect(dfA.col(99).asArray()).toEqual([1, 0]);
expect(dfA.colIndex.labels()).toEqual(new Int32Array([0, 1, 99]));
expect(df.colIndex.labels()).toEqual(new Int32Array([0, 1]));
expect(df.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
});
describe("handle column dimensions correctly", () => {
/*
there are two conditions:
- empty dataframe - will accept an add of any dimensionality
- non-empty dataframe - added column must match row-count dimension
*/
test("empty.withCol", () => {
const edf = Dataframe.Dataframe.empty();
const df = edf.withCol("foo", [1, 2, 3]);
expect(edf).toBeDefined();
expect(df).toBeDefined();
expect(edf).not.toEqual(df);
expect(df.dims).toEqual([3, 1]);
expect(df.icol(0).asArray()).toEqual([1, 2, 3]);
});
test("withCol dimension check", () => {
const dfA = new Dataframe.Dataframe([1, 1], [["a"]]);
expect(() => {
dfA.withCol(1, []);
}).toThrow(RangeError);
});
});
});
describe("withColsFrom", () => {
test("error conditions", () => {
/*
make sure we catch common errors:
- duplicate column names
- dimensionality difference
*/
const dfA = new Dataframe.Dataframe(
[2, 3],
[
["red", "blue"],
[true, false],
[1, 0],
],
null,
new Dataframe.KeyIndex(["colors", "bools", "numbers"])
);
/* different dimensionality should throw error */
const dfB = new Dataframe.Dataframe(
[3, 1],
[["red", "blue", "green"]],
null,
new Dataframe.KeyIndex(["colorsA"])
);
expect(() => dfA.withColsFrom(dfB)).toThrow(RangeError);
/* duplicate labels should throw an error */
expect(() => dfA.withColsFrom(dfA)).toThrow(Error);
});
test("simple", () => {
/* simple test that it works as expected in common case */
const dfEmpty = Dataframe.Dataframe.empty();
const dfA = new Dataframe.Dataframe(
[2, 1],
[["red", "blue"]],
null,
new Dataframe.KeyIndex(["colors"])
);
const dfB = new Dataframe.Dataframe(
[2, 1],
[[true, false]],
null,
new Dataframe.KeyIndex(["bools"])
);
const dfLikeA = dfEmpty.withColsFrom(dfA);
expect(dfLikeA).toBeDefined();
expect(dfLikeA.dims).toEqual(dfA.dims);
expect(dfLikeA.colIndex.labels()).toEqual(dfA.colIndex.labels());
expect(dfLikeA.rowIndex).toEqual(dfA.rowIndex);
expect(dfLikeA.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
expect(dfLikeA.icol(0).asArray()).toEqual(dfA.icol(0).asArray());
const dfAlsoLikeA = dfA.withColsFrom(dfEmpty);
expect(dfAlsoLikeA).toBeDefined();
expect(dfAlsoLikeA.dims).toEqual(dfA.dims);
expect(dfAlsoLikeA.colIndex.labels()).toEqual(dfA.colIndex.labels());
expect(dfAlsoLikeA.rowIndex).toEqual(dfA.rowIndex);
expect(dfAlsoLikeA.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
expect(dfAlsoLikeA.icol(0).asArray()).toEqual(dfA.icol(0).asArray());
const dfC = dfA.withColsFrom(dfB);
expect(dfC).toBeDefined();
expect(dfC.dims).toEqual([2, 2]);
expect(dfC.colIndex.labels()).toEqual(["colors", "bools"]);
expect(dfC.rowIndex).toEqual(dfA.rowIndex);
expect(dfC.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
expect(dfC.col("colors").asArray()).toEqual(["red", "blue"]);
expect(dfC.col("bools").asArray()).toEqual([true, false]);
});
test("column picking", () => {
const dfEmpty = Dataframe.Dataframe.empty();
const dfA = new Dataframe.Dataframe(
[2, 1],
[["red", "blue"]],
null,
new Dataframe.KeyIndex(["colors"])
);
const dfB = new Dataframe.Dataframe(
[2, 3],
[
["red", "blue"],
[true, false],
[1, 0],
],
null,
new Dataframe.KeyIndex(["colors", "bools", "numbers"])
);
const dfX = dfEmpty.withColsFrom(dfB, ["colors", "bools"]);
expect(dfX).toBeDefined();
expect(dfX.dims).toEqual([2, 2]);
expect(dfX.colIndex.labels()).toEqual(["colors", "bools"]);
expect(dfX.rowIndex).toEqual(dfB.rowIndex);
expect(dfX.icol(0).asArray()).toEqual(dfB.icol(0).asArray());
const dfY = dfA.withColsFrom(dfB, ["numbers"]);
expect(dfY).toBeDefined();
expect(dfY.dims).toEqual([2, 2]);
expect(dfY.colIndex.labels()).toEqual(["colors", "numbers"]);
expect(dfY.rowIndex).toEqual(dfA.rowIndex);
expect(dfY.icol(0).asArray()).toEqual(dfA.icol(0).asArray());
const dfZ = dfA.withColsFrom(dfEmpty, []);
expect(dfZ).toBeDefined();
expect(dfZ.dims).toEqual(dfA.dims);
expect(dfZ.colIndex.labels()).toEqual(dfA.colIndex.labels());
expect(dfZ.rowIndex).toEqual(dfA.rowIndex);
expect(dfZ.icol(0).asArray()).toEqual(dfA.icol(0).asArray());
expect(() => dfA.withColsFrom(dfB, ["bools", "colors"])).toThrow();
});
test("column aliasing", () => {
const dfA = new Dataframe.Dataframe(
[2, 1],
[["red", "blue"]],
null,
new Dataframe.KeyIndex(["colors"])
);
const dfB = new Dataframe.Dataframe(
[2, 3],
[
["red", "blue"],
[true, false],
[1, 0],
],
null,
new Dataframe.KeyIndex(["colors", "bools", "numbers"])
);
const dfX = dfA.withColsFrom(dfB, { colors: "_colors", bools: "_bools" });
expect(dfX).toBeDefined();
expect(dfX.dims).toEqual([2, 3]);
expect(dfX.colIndex.labels()).toEqual(["colors", "_colors", "_bools"]);
expect(dfX.rowIndex).toEqual(dfA.rowIndex);
expect(dfX.icol(0).asArray()).toEqual(dfA.icol(0).asArray());
expect(dfX.col("_colors").asArray()).toBe(dfB.col("colors").asArray());
});
});
describe("dropCol", () => {
test("KeyIndex", () => {
const df = new Dataframe.Dataframe(
[2, 3],
[
["red", "blue"],
[true, false],
[1, 0],
],
null,
new Dataframe.KeyIndex(["colors", "bools", "numbers"])
);
const dfA = df.dropCol("colors");
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([2, 2]);
expect(dfA.icol(0).asArray()).toEqual([true, false]);
expect(dfA.icol(1).asArray()).toEqual([1, 0]);
expect(dfA.col("numbers").asArray()).toEqual([1, 0]);
expect(dfA.colIndex.labels()).toEqual(["bools", "numbers"]);
expect(df.colIndex.labels()).toEqual(["colors", "bools", "numbers"]);
expect(df.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
});
test("IdentityInt32Index drop first", () => {
const df = new Dataframe.Dataframe(
[2, 3],
[
["red", "blue"],
[true, false],
[1, 0],
],
null,
null
);
const dfA = df.dropCol(0);
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([2, 2]);
expect(dfA.icol(0).asArray()).toEqual([true, false]);
expect(dfA.icol(1).asArray()).toEqual([1, 0]);
expect(df.col(1).asArray()).toEqual(dfA.col(1).asArray());
expect(df.col(2).asArray()).toEqual(dfA.col(2).asArray());
expect(dfA.colIndex.labels()).toEqual(new Int32Array([1, 2]));
expect(df.colIndex.labels()).toEqual(new Int32Array([0, 1, 2]));
expect(df.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
});
test("IdentityInt32Index drop last", () => {
const df = new Dataframe.Dataframe(
[2, 3],
[
["red", "blue"],
[true, false],
[1, 0],
],
null,
null
);
const dfA = df.dropCol(2);
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([2, 2]);
expect(dfA.icol(0).asArray()).toEqual(["red", "blue"]);
expect(dfA.icol(1).asArray()).toEqual([true, false]);
expect(df.col(0).asArray()).toEqual(dfA.col(0).asArray());
expect(df.col(1).asArray()).toEqual(dfA.col(1).asArray());
expect(dfA.colIndex.labels()).toEqual(new Int32Array([0, 1]));
expect(df.colIndex.labels()).toEqual(new Int32Array([0, 1, 2]));
expect(df.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
});
test("DenseInt32Index", () => {
const df = new Dataframe.Dataframe(
[2, 3],
[
["red", "blue"],
[true, false],
[1, 0],
],
null,
new Dataframe.DenseInt32Index([102, 101, 100])
);
const dfA = df.dropCol(101);
expect(dfA).toBeDefined();
expect(dfA.dims).toEqual([2, 2]);
expect(dfA.icol(0).asArray()).toEqual(["red", "blue"]);
expect(dfA.icol(1).asArray()).toEqual([1, 0]);
expect(dfA.col(100).asArray()).toEqual([1, 0]);
expect(dfA.col(102).asArray()).toEqual(["red", "blue"]);
expect(dfA.colIndex.labels()).toEqual(new Int32Array([102, 100]));
expect(df.colIndex.labels()).toEqual(new Int32Array([102, 101, 100]));
expect(df.rowIndex.labels()).toEqual(dfA.rowIndex.labels());
});
});
describe("mapColumns", () => {
test("identity", () => {
const dfA = Dataframe.Dataframe.create(
[3, 3],
[
new Array(3).fill(0),
new Int16Array(3).fill(99),
new Float64Array(3).fill(1.1),
]
);
const dfB = dfA.mapColumns((col, idx) => {
expect(dfA.icol(idx).asArray()).toBe(col);
return col;
});
expect(dfA).not.toBe(dfB);
expect(dfA.dims).toEqual(dfB.dims);
for (let c = 0; c < dfA.dims[1]; c += 1) {
expect(dfA.icol(c).asArray()).toBe(dfB.icol(c).asArray());
}
});
test("transform", () => {
const dfA = Dataframe.Dataframe.create(
[3, 3],
[new Array(3).fill(0), new Array(3).fill(0), new Array(3).fill(0)]
);
const dfB = dfA.mapColumns(() => new Array(3).fill(1));
expect(dfA).not.toBe(dfB);
expect(dfB.iat(0, 0)).toEqual(1);
expect(dfB.iat(0, 1)).toEqual(1);
expect(dfB.iat(0, 2)).toEqual(1);
});
test("columns", () => {
const df = Dataframe.Dataframe.create(
[3, 3],
[new Array(3).fill(0), new Array(3).fill(0), new Array(3).fill(0)]
);
expect(df).toBeDefined();
expect(df.columns()).toHaveLength(3);
expect(df.columns()[0]).toEqual(df.icol(0));
expect(df.columns()[2]).toEqual(df.icol(2));
});
test("renameCol", () => {
const dfA = new Dataframe.Dataframe(
[2, 2],
[
[true, false],
[1, 0],
],
null,
new Dataframe.KeyIndex(["A", "B"])
);
const dfB = dfA.renameCol("B", "C");
expect(dfA.colIndex.labels()).toEqual(["A", "B"]);
expect(dfB.colIndex.labels()).toEqual(["A", "C"]);
expect(dfA.dims).toMatchObject(dfB.dims);
expect(dfA.columns()).toMatchObject(dfB.columns());
});
});
});
describe("dataframe col", () => {
let df = null;
beforeEach(() => {
df = new Dataframe.Dataframe(
[2, 2],
[
[true, false],
[1, 0],
],
null,
new Dataframe.KeyIndex(["A", "B"])
);
});
test("col", () => {
expect(df).toBeDefined();
expect(df.col("A")).toBe(df.icol(0));
expect(df.col("B")).toBe(df.icol(1));
expect(df.col("undefined")).toBeUndefined();
expect(df.icol("undefined")).toBeUndefined();
const colA = df.col("A");
expect(colA).toBeInstanceOf(Function);
expect(colA.asArray).toBeInstanceOf(Function);
expect(colA.has).toBeInstanceOf(Function);
expect(colA.ihas).toBeInstanceOf(Function);
expect(colA.indexOf).toBeInstanceOf(Function);
expect(colA.iget).toBeInstanceOf(Function);
});
test("col.asArray", () => {
expect(df).toBeDefined();
expect(df.col("A").asArray()).toEqual([true, false]);
expect(df.icol(0).asArray()).toEqual([true, false]);
expect(df.col("B").asArray()).toEqual([1, 0]);
expect(df.icol(1).asArray()).toEqual([1, 0]);
});
test("col.has", () => {
expect(df).toBeDefined();
expect(df.col("A").has(-1)).toBe(false);
expect(df.col("A").has(0)).toBe(true);
expect(df.col("A").has(1)).toBe(true);
expect(df.col("A").has(2)).toBe(false);
expect(df.col("B").has(-1)).toBe(false);
expect(df.col("B").has(0)).toBe(true);
expect(df.col("B").has(1)).toBe(true);
expect(df.col("B").has(2)).toBe(false);
});
test("col.ihas", () => {
expect(df).toBeDefined();
expect(df.col("A").ihas(-1)).toBe(false);
expect(df.col("A").ihas(0)).toBe(true);
expect(df.col("A").ihas(1)).toBe(true);
expect(df.col("A").ihas(2)).toBe(false);
expect(df.col("B").ihas(-1)).toBe(false);
expect(df.col("B").ihas(0)).toBe(true);
expect(df.col("B").ihas(1)).toBe(true);
expect(df.col("B").ihas(2)).toBe(false);
});
test("col.iget", () => {
expect(df).toBeDefined();
expect(df.col("A").iget(0)).toEqual(df.iat(0, 0));
expect(df.col("B").iget(1)).toEqual(df.iat(1, 1));
});
test("col.indexOf", () => {
expect(df).toBeDefined();
expect(df.col("A").indexOf(true)).toEqual(0);
expect(df.col("A").indexOf(false)).toEqual(1);
expect(df.col("A").indexOf(99)).toBeUndefined();
expect(df.col("A").indexOf(undefined)).toBeUndefined();
expect(df.col("A").indexOf(1)).toBeUndefined();
expect(df.col("B").indexOf(1)).toEqual(0);
expect(df.col("B").indexOf(0)).toEqual(1);
expect(df.col("B").indexOf(99)).toBeUndefined();
expect(df.col("B").indexOf(undefined)).toBeUndefined();
expect(df.col("B").indexOf(true)).toBeUndefined();
});
});
describe("label indexing", () => {
describe("isLabelIndex", () => {
expect(
Dataframe.isLabelIndex(new Dataframe.IdentityInt32Index(4))
).toBeTruthy();
expect(
Dataframe.isLabelIndex(new Dataframe.DenseInt32Index([2, 4, 99]))
).toBeTruthy();
expect(
Dataframe.isLabelIndex(new Dataframe.KeyIndex(["a", 4, "toasty"]))
).toBeTruthy();
expect(Dataframe.isLabelIndex(false)).toBeFalsy();
expect(Dataframe.isLabelIndex(undefined)).toBeFalsy();
expect(Dataframe.isLabelIndex(null)).toBeFalsy();
expect(Dataframe.isLabelIndex(true)).toBeFalsy();
expect(Dataframe.isLabelIndex([])).toBeFalsy();
expect(Dataframe.isLabelIndex({})).toBeFalsy();
expect(Dataframe.isLabelIndex(Dataframe.IdentityInt32Index)).toBeFalsy();
});
describe("IdentityInt32Index", () => {
const idx = new Dataframe.IdentityInt32Index(12); // [0, 12)
test("create", () => {
expect(Dataframe.isLabelIndex(idx)).toBeTruthy();
});
test("labels", () => {
expect(idx.labels()).toEqual(
new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
);
expect(idx.getLabel(1)).toEqual(1);
expect(idx.getLabels([1, 3])).toEqual([1, 3]);
expect(idx.size()).toEqual(12);
});
test("offsets", () => {
expect(idx.getOffset(1)).toEqual(1);
expect(idx.getOffsets([1, 3])).toEqual([1, 3]);
});
test("subset", () => {
expect(idx.subset([2]).labels()).toEqual([2]);
expect(idx.subset([2, 3, 4]).labels()).toEqual(new Int32Array([2, 3, 4]));
expect(idx.subset([0, 1, 2, 3]).labels()).toEqual(
new Int32Array([0, 1, 2, 3])
);
expect(idx.subset([0, 1, 2, 3, 4])).toBeInstanceOf(
Dataframe.IdentityInt32Index
);
expect(idx.subset([2, 1, 0])).toBeInstanceOf(
Dataframe.IdentityInt32Index
);
expect(idx.subset([1, 2, 3, 4])).toBeInstanceOf(
Dataframe.DenseInt32Index
);
expect(idx.subset([0, 1, 3, 4])).toBeInstanceOf(
Dataframe.DenseInt32Index
);
expect(idx.subset([0, 1, 2, 3, 10])).toBeInstanceOf(
Dataframe.DenseInt32Index
);
expect(idx.subset([4, 3, 2, 1])).toBeInstanceOf(
Dataframe.DenseInt32Index
);
expect(idx.subset([4])).toBeInstanceOf(Dataframe.KeyIndex);
});
test("isubset", () => {
expect(idx.isubset([2]).labels()).toEqual([2]);
expect(idx.isubset([2, 3, 4]).labels()).toEqual(
new Int32Array([2, 3, 4])
);
expect(idx.isubset([0, 1, 2, 3]).labels()).toEqual(
new Int32Array([0, 1, 2, 3])
);
expect(() => idx.isubset([-1001])).toThrow(RangeError);
expect(() => idx.isubset([1001])).toThrow(RangeError);
});
test("isubsetMask", () => {
expect(
idx
.isubsetMask([
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
])
.labels()
).toEqual(new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]));
expect(
idx
.isubsetMask([
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
false,
])
.labels()
).toEqual(new Int32Array([]));
expect(
idx
.isubsetMask([
false,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
true,
])
.labels()
).toEqual(new Int32Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]));
expect(
idx
.isubsetMask([
false,
true,
true,
true,
true,
true,
true,
true,
true,
true,
false,
true,
])
.labels()
).toEqual(new Int32Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 11]));
expect(
idx
.isubsetMask([
false,
true,
true,
false,
true,
true,
true,
true,
true,
true,
true,
false,
])
.labels()
).toEqual(new Int32Array([1, 2, 4, 5, 6, 7, 8, 9, 10]));
expect(() => idx.isubsetMask([])).toThrow(RangeError);
});
test("withLabel", () => {
expect(idx.withLabel(99).labels()).toEqual(
new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 99])
);
expect(idx.withLabel(12).labels()).toEqual(
new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
);
expect(idx.withLabels([12, 13]).labels()).toEqual(
new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13])
);
});
test("dropLabel", () => {
expect(idx.dropLabel(0).labels()).toEqual(
new Int32Array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
);
expect(idx.dropLabel(11).labels()).toEqual(
new Int32Array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
);
expect(idx.dropLabel(5).labels()).toEqual(
new Int32Array([0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11])
);
});
});
describe("DenseInt32Index", () => {
const idx = new Dataframe.DenseInt32Index([99, 1002, 48, 0, 22]);
test("create", () => {
expect(Dataframe.isLabelIndex(idx)).toBeTruthy();
});
test("labels", () => {
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([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]);
});
test("subset", () => {
expect(idx.subset([1002, 0, 99]).labels()).toEqual(
new Int32Array([1002, 0, 99])
);
expect(idx.getOffsets(idx.subset([1002, 0, 99]).labels())).toEqual(
new Int32Array([1, 3, 0])
);
expect(() => idx.subset([-1])).toThrow(RangeError);
});
test("isubset", () => {
expect(idx.isubset([4, 1, 2]).labels()).toEqual(
new Int32Array([22, 1002, 48])
);
expect(() => idx.isubset([-1001])).toThrow(RangeError);
expect(() => idx.isubset([1001])).toThrow(RangeError);
});
test("isubsetMask", () => {
expect(idx.isubsetMask([true, true, true, true, true]).labels()).toEqual(
new Int32Array([99, 1002, 48, 0, 22])
);
expect(
idx.isubsetMask([false, false, false, false, false]).labels()
).toEqual(new Int32Array([]));
expect(idx.isubsetMask([true, true, false, true, true]).labels()).toEqual(
new Int32Array([99, 1002, 0, 22])
);
expect(
idx.isubsetMask([false, true, true, true, false]).labels()
).toEqual(new Int32Array([1002, 48, 0]));
expect(() => idx.isubsetMask([])).toThrow(RangeError);
});
test("withLabel", () => {
expect(idx.withLabel(88).labels()).toEqual(
new Int32Array([99, 1002, 48, 0, 22, 88])
);
expect(idx.withLabel(88).getOffset(88)).toEqual(5);
expect(idx.withLabels([88, 99]).labels()).toEqual(
new Int32Array([99, 1002, 48, 0, 22, 88, 99])
);
});
test("dropLabel", () => {
expect(idx.dropLabel(48).labels()).toEqual(
new Int32Array([99, 1002, 0, 22])
);
});
});
describe("KeyIndex", () => {
const idx = new Dataframe.KeyIndex(["red", "green", "blue"]);
test("create", () => {
expect(Dataframe.isLabelIndex(idx)).toBeTruthy();
expect(() => new Dataframe.KeyIndex(["dup", "dup"])).toThrow(Error);
expect(new Dataframe.KeyIndex().size()).toEqual(0);
});
test("labels", () => {
expect(idx.labels()).toEqual(["red", "green", "blue"]);
expect(idx.size()).toEqual(3);
expect(idx.getLabel(1)).toEqual("green");
expect(idx.getLabels([2, 0])).toEqual(["blue", "red"]);
});
test("offsets", () => {
expect(idx.getOffset("blue")).toEqual(2);
});
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"]);
});
});
});
describe("corner cases", () => {
/* error/corner cases */
test("identity integer index rejects non-integer labels", () => {
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.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(0.001)).toBeUndefined();
expect(idx.getLabel({})).toBeUndefined();
expect(idx.getLabel([])).toBeUndefined();
expect(idx.getLabel(new Float32Array())).toBeUndefined();
expect(idx.getLabel("__proto__")).toBeUndefined();
});
test("dense integer index rejects non-integer labels", () => {
const idx = new Dataframe.DenseInt32Index([-10, 0, 3, 9, 10]);
expect(idx.getOffset(0)).toBe(1);
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.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(0.001)).toBeUndefined();
expect(idx.getLabel({})).toBeUndefined();
expect(idx.getLabel([])).toBeUndefined();
expect(idx.getLabel(new Float32Array())).toBeUndefined();
expect(idx.getLabel("__proto__")).toBeUndefined();
});
test("Empty dataframe rejects bogus labels", () => {
const df = Dataframe.Dataframe.empty();
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.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.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.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();
});
test("Dataframe rejects bogus labels", () => {
const df = new Dataframe.Dataframe(
[2, 2],
[
[true, false],
[1, 0],
],
null,
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.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.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.ihas("sort", "length")).toBeFalsy();
expect(df.ihas("__proto__", "__proto__")).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, -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.has("sort", "length")).toBeFalsy();
expect(df.has("length", "sort")).toBeFalsy();
expect(df.has("__proto__", "__proto__")).toBeFalsy();
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(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();
});
});