mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-30 23:38:11 +08:00
Dataframe, part deux - add varData and summarize() (#608)
* initial dataframe commit * initial dataframe port of core app * rename variables for clarity * remove unused import * comment out unused code * fix array handling bug in crossfilter dimension creation * allow creation of empty dataframes * handle non-existent columns * handle non-existent columns * revise tests for new dataframe * comments for clarity * comments for clarity * generate bulk add placeholder with real gene names * fix bug in gene name adding * more dataframe unit tests * fix bug - subset from current world, not universe * put cut and pasted code into a single function * improve caching of crossfilter * remove cascading update bug from graph * more performance work * improve state handling for scatterplot * performance optimization of critical path * add column summarization * dataframe utils * add callOnceLazy * fix tests * minor updates found during review * fix misspelling * remove RESTv02 from function names * comment cleanup * cut/icut col parameter defaults to null * break up large test * improve tests and comments on dataframe at/has functions * add Dataframe withCol/dropCol * expression varData now stored in a dataframe * dead code cleanup * use dataframe.summarize() * test cases for Dataframe.col.summarize * update test cases for new dataframe summarize * improve naming * use new hasCol API * add comments * add more Dataframe.withCol tests * add ability to specify row index in cut operation * retire subsetVarData function * correctly handle expression subsetting * lint and improve comments * rename cut to subset * changes based on PR review
This commit is contained in:
Bruce Martin
@@ -0,0 +1,253 @@
|
||||
import * as Dataframe from "../../../src/util/dataframe";
|
||||
|
||||
function float32Conversion(f) {
|
||||
return new Float32Array([f])[0];
|
||||
}
|
||||
|
||||
describe("Dataframe column summary", () => {
|
||||
test("empty column test", () => {
|
||||
const df = Dataframe.Dataframe.create([0, 1], [[]]);
|
||||
const summary = df.icol(0).summarize();
|
||||
expect(summary).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: [],
|
||||
categoryCounts: new Map(),
|
||||
numCategories: 0
|
||||
})
|
||||
);
|
||||
});
|
||||
|
||||
test("simple test", () => {
|
||||
const df = new Dataframe.Dataframe(
|
||||
[1, 6],
|
||||
[
|
||||
["n1"],
|
||||
["hi"],
|
||||
[true],
|
||||
new Float32Array([39.3]),
|
||||
new Int32Array([99]),
|
||||
[1]
|
||||
],
|
||||
null,
|
||||
new Dataframe.KeyIndex([
|
||||
"name",
|
||||
"nameString",
|
||||
"nameBoolean",
|
||||
"nameFloat32",
|
||||
"nameInt32",
|
||||
"nameCategorical"
|
||||
])
|
||||
);
|
||||
|
||||
expect(df.icol(0).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: ["n1"],
|
||||
categoryCounts: new Map([["n1", 1]]),
|
||||
numCategories: 1
|
||||
})
|
||||
);
|
||||
expect(df.icol(1).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: ["hi"],
|
||||
categoryCounts: new Map([["hi", 1]]),
|
||||
numCategories: 1
|
||||
})
|
||||
);
|
||||
expect(df.icol(2).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: [true],
|
||||
categoryCounts: new Map([[true, 1]]),
|
||||
numCategories: 1
|
||||
})
|
||||
);
|
||||
expect(df.icol(3).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: false,
|
||||
min: float32Conversion(39.3),
|
||||
max: float32Conversion(39.3),
|
||||
nan: 0,
|
||||
ninf: 0,
|
||||
pinf: 0
|
||||
})
|
||||
);
|
||||
expect(df.icol(4).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: false,
|
||||
min: 99,
|
||||
max: 99,
|
||||
nan: 0,
|
||||
ninf: 0,
|
||||
pinf: 0
|
||||
})
|
||||
);
|
||||
expect(df.icol(5).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: [1],
|
||||
categoryCounts: new Map([[1, 1]]),
|
||||
numCategories: 1
|
||||
})
|
||||
);
|
||||
});
|
||||
|
||||
test("multi test", () => {
|
||||
const df = new Dataframe.Dataframe(
|
||||
[3, 6],
|
||||
[
|
||||
["n0", "n1", "n2"],
|
||||
["hi", "hi", "bye"],
|
||||
[false, true, true],
|
||||
new Float32Array([39.3, 39.3, 0]),
|
||||
new Int32Array([99, 99, 99]),
|
||||
[1, false, "0"]
|
||||
],
|
||||
null,
|
||||
new Dataframe.KeyIndex([
|
||||
"name",
|
||||
"nameString",
|
||||
"nameBoolean",
|
||||
"nameFloat32",
|
||||
"nameInt32",
|
||||
"nameCategorical"
|
||||
])
|
||||
);
|
||||
|
||||
expect(df.icol(0).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: expect.arrayContaining(["n0", "n1", "n2"]),
|
||||
categoryCounts: new Map([["n0", 1], ["n1", 1], ["n2", 1]]),
|
||||
numCategories: 3
|
||||
})
|
||||
);
|
||||
expect(df.icol(1).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: expect.arrayContaining(["hi", "bye"]),
|
||||
categoryCounts: new Map([["hi", 2], ["bye", 1]]),
|
||||
numCategories: 2
|
||||
})
|
||||
);
|
||||
expect(df.icol(2).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: expect.arrayContaining([true, false]),
|
||||
categoryCounts: new Map([[true, 2], [false, 1]]),
|
||||
numCategories: 2
|
||||
})
|
||||
);
|
||||
expect(df.icol(3).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: false,
|
||||
min: 0,
|
||||
max: float32Conversion(39.3),
|
||||
nan: 0,
|
||||
ninf: 0,
|
||||
pinf: 0
|
||||
})
|
||||
);
|
||||
expect(df.icol(4).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: false,
|
||||
min: 99,
|
||||
max: 99,
|
||||
nan: 0,
|
||||
ninf: 0,
|
||||
pinf: 0
|
||||
})
|
||||
);
|
||||
expect(df.icol(5).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: expect.arrayContaining([1, false, "0"]),
|
||||
categoryCounts: new Map([[1, 1], [false, 1], ["0", 1]]),
|
||||
numCategories: 3
|
||||
})
|
||||
);
|
||||
});
|
||||
|
||||
test("non-finite numbers", () => {
|
||||
const df = new Dataframe.Dataframe(
|
||||
[4, 6],
|
||||
[
|
||||
["n0", "n1", "n2", "n2"],
|
||||
["hi", "hi", "bye", "bye"],
|
||||
[false, true, true, true],
|
||||
new Float32Array([
|
||||
39.3,
|
||||
Number.NEGATIVE_INFINITY,
|
||||
Number.NaN,
|
||||
Number.POSITIVE_INFINITY
|
||||
]),
|
||||
new Int32Array([99, 99, 99, 99]),
|
||||
[1, false, "0", "0"]
|
||||
],
|
||||
null,
|
||||
new Dataframe.KeyIndex([
|
||||
"name",
|
||||
"nameString",
|
||||
"nameBoolean",
|
||||
"nameFloat32",
|
||||
"nameInt32",
|
||||
"nameCategorical"
|
||||
])
|
||||
);
|
||||
|
||||
expect(df.icol(0).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: expect.arrayContaining(["n0", "n1", "n2"]),
|
||||
categoryCounts: new Map([["n0", 1], ["n1", 1], ["n2", 2]]),
|
||||
numCategories: 3
|
||||
})
|
||||
);
|
||||
expect(df.icol(1).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: expect.arrayContaining(["hi", "bye"]),
|
||||
categoryCounts: new Map([["hi", 2], ["bye", 1]]),
|
||||
numCategories: 2
|
||||
})
|
||||
);
|
||||
expect(df.icol(2).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: expect.arrayContaining([true, false]),
|
||||
categoryCounts: new Map([[true, 2], [false, 1]]),
|
||||
numCategories: 2
|
||||
})
|
||||
);
|
||||
expect(df.icol(3).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: false,
|
||||
min: float32Conversion(39.3),
|
||||
max: float32Conversion(39.3),
|
||||
nan: 1,
|
||||
ninf: 1,
|
||||
pinf: 1
|
||||
})
|
||||
);
|
||||
expect(df.icol(4).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: false,
|
||||
min: 99,
|
||||
max: 99,
|
||||
nan: 0,
|
||||
ninf: 0,
|
||||
pinf: 0
|
||||
})
|
||||
);
|
||||
expect(df.icol(5).summarize()).toEqual(
|
||||
expect.objectContaining({
|
||||
categorical: true,
|
||||
categories: expect.arrayContaining([1, false, "0"]),
|
||||
categoryCounts: new Map([[1, 1], [false, 1], ["0", 1]]),
|
||||
numCategories: 3
|
||||
})
|
||||
);
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user