run prettier(2.0.5) (#1438)

client/__tests__/util/dataframe/dataframe.test.js

@@ -53,7 +53,7 @@ describe("simple data access", () => {
     [4, 2],
     [
       new Float64Array([0.0, Number.NaN, Number.POSITIVE_INFINITY, 3.14159]),
-      ["red", "blue", "green", "nan"]
+      ["red", "blue", "green", "nan"],
     ],
     new Dataframe.DenseInt32Index([3, 2, 1, 0]),
     new Dataframe.KeyIndex(["numbers", "colors"])
@@ -136,7 +136,7 @@ describe("dataframe subsetting", () => {
         new Int32Array([0, 1, 2]),
         ["A", "B", "C"],
         new Float32Array([4.4, 5.5, 6.6]),
-        ["red", "green", "blue"]
+        ["red", "green", "blue"],
       ],
       null,
       new Dataframe.KeyIndex(["int32", "string", "float32", "colors"])
@@ -258,7 +258,7 @@ describe("dataframe subsetting", () => {
         new Int32Array([0, 1, 2]),
         ["A", "B", "C"],
         new Float32Array([4.4, 5.5, 6.6]),
-        ["red", "green", "blue"]
+        ["red", "green", "blue"],
       ],
       new Dataframe.DenseInt32Index([2, 4, 6]),
       new Dataframe.KeyIndex(["int32", "string", "float32", "colors"])
@@ -283,7 +283,7 @@ describe("dataframe factories", () => {
       [
         new Array(3).fill(0),
         new Int16Array(3).fill(99),
-        new Float64Array(3).fill(1.1)
+        new Float64Array(3).fill(1.1),
       ]
     );
 
@@ -323,7 +323,7 @@ describe("dataframe factories", () => {
         [2, 2],
         [
           ["red", "blue"],
-          [true, false]
+          [true, false],
         ],
         null,
         new Dataframe.KeyIndex(["colors", "bools"])
@@ -346,7 +346,7 @@ describe("dataframe factories", () => {
         [2, 2],
         [
           ["red", "blue"],
-          [true, false]
+          [true, false],
         ],
         null,
         new Dataframe.DenseInt32Index([74, 75])
@@ -371,7 +371,7 @@ describe("dataframe factories", () => {
         [2, 2],
         [
           ["red", "blue"],
-          [true, false]
+          [true, false],
         ],
         null,
         new Dataframe.DenseInt32Index([74, 75])
@@ -396,7 +396,7 @@ describe("dataframe factories", () => {
         [2, 2],
         [
           ["red", "blue"],
-          [true, false]
+          [true, false],
         ],
         null,
         null
@@ -421,7 +421,7 @@ describe("dataframe factories", () => {
         [2, 2],
         [
           ["red", "blue"],
-          [true, false]
+          [true, false],
         ],
         null,
         null
@@ -479,7 +479,7 @@ describe("dataframe factories", () => {
         [
           ["red", "blue"],
           [true, false],
-          [1, 0]
+          [1, 0],
         ],
         null,
         new Dataframe.KeyIndex(["colors", "bools", "numbers"])
@@ -553,7 +553,7 @@ describe("dataframe factories", () => {
         [
           ["red", "blue"],
           [true, false],
-          [1, 0]
+          [1, 0],
         ],
         null,
         new Dataframe.KeyIndex(["colors", "bools", "numbers"])
@@ -595,7 +595,7 @@ describe("dataframe factories", () => {
         [
           ["red", "blue"],
           [true, false],
-          [1, 0]
+          [1, 0],
         ],
         null,
         new Dataframe.KeyIndex(["colors", "bools", "numbers"])
@@ -618,7 +618,7 @@ describe("dataframe factories", () => {
         [
           ["red", "blue"],
           [true, false],
-          [1, 0]
+          [1, 0],
         ],
         null,
         new Dataframe.KeyIndex(["colors", "bools", "numbers"])
@@ -641,7 +641,7 @@ describe("dataframe factories", () => {
         [
           ["red", "blue"],
           [true, false],
-          [1, 0]
+          [1, 0],
         ],
         null,
         null
@@ -665,7 +665,7 @@ describe("dataframe factories", () => {
         [
           ["red", "blue"],
           [true, false],
-          [1, 0]
+          [1, 0],
         ],
         null,
         null
@@ -689,7 +689,7 @@ describe("dataframe factories", () => {
         [
           ["red", "blue"],
           [true, false],
-          [1, 0]
+          [1, 0],
         ],
         null,
         new Dataframe.DenseInt32Index([102, 101, 100])
@@ -715,7 +715,7 @@ describe("dataframe factories", () => {
         [
           new Array(3).fill(0),
           new Int16Array(3).fill(99),
-          new Float64Array(3).fill(1.1)
+          new Float64Array(3).fill(1.1),
         ]
       );
       const dfB = dfA.mapColumns((col, idx) => {
@@ -760,7 +760,7 @@ describe("dataframe factories", () => {
         [2, 2],
         [
           [true, false],
-          [1, 0]
+          [1, 0],
         ],
         null,
         new Dataframe.KeyIndex(["A", "B"])
@@ -781,7 +781,7 @@ describe("dataframe col", () => {
       [2, 2],
       [
         [true, false],
-        [1, 0]
+        [1, 0],
       ],
       null,
       new Dataframe.KeyIndex(["A", "B"])

client/__tests__/util/dataframe/histogram.test.js

@@ -14,7 +14,7 @@ describe("Dataframe column histogram", () => {
       new Map([
         ["n1", new Map([["c1", 1]])],
         ["n2", new Map([["c2", 1]])],
-        ["n3", new Map([["c3", 1]])]
+        ["n3", new Map([["c3", 1]])],
       ])
     );
     // memoized?
@@ -31,7 +31,11 @@ describe("Dataframe column histogram", () => {
 
     const h1 = df.col("value").histogram(3, [0, 2], df.col("name"));
     expect(h1).toMatchObject(
-      new Map([["n1", [1, 0, 0]], ["n2", [0, 1, 0]], ["n3", [0, 0, 1]]])
+      new Map([
+        ["n1", [1, 0, 0]],
+        ["n2", [0, 1, 0]],
+        ["n3", [0, 0, 1]],
+      ])
     );
     // memoized?
     expect(df.col("value").histogram(3, [0, 2], df.col("name"))).toMatchObject(
@@ -48,7 +52,13 @@ describe("Dataframe column histogram", () => {
     );
 
     const h1 = df.col("cat").histogram();
-    expect(h1).toMatchObject(new Map([["c1", 1], ["c2", 1], ["c3", 1]]));
+    expect(h1).toMatchObject(
+      new Map([
+        ["c1", 1],
+        ["c2", 1],
+        ["c3", 1],
+      ])
+    );
     // memoized?
     expect(df.col("value").histogram(3, [0, 2])).toMatchObject(h1);
   });
@@ -87,7 +97,7 @@ describe("Dataframe column histogram", () => {
       0,
       0,
       0,
-      2
+      2,
     ]);
   });
 });

client/__tests__/util/dataframe/summarize.test.js

@@ -13,7 +13,7 @@ describe("Dataframe column summary", () => {
         categorical: true,
         categories: [],
         categoryCounts: new Map(),
-        numCategories: 0
+        numCategories: 0,
       })
     );
   });
@@ -27,7 +27,7 @@ describe("Dataframe column summary", () => {
         [true],
         new Float32Array([39.3]),
         new Int32Array([99]),
-        [1]
+        [1],
       ],
       null,
       new Dataframe.KeyIndex([
@@ -36,7 +36,7 @@ describe("Dataframe column summary", () => {
         "nameBoolean",
         "nameFloat32",
         "nameInt32",
-        "nameCategorical"
+        "nameCategorical",
       ])
     );
 
@@ -45,7 +45,7 @@ describe("Dataframe column summary", () => {
         categorical: true,
         categories: ["n1"],
         categoryCounts: new Map([["n1", 1]]),
-        numCategories: 1
+        numCategories: 1,
       })
     );
     expect(df.icol(1).summarize()).toEqual(
@@ -53,7 +53,7 @@ describe("Dataframe column summary", () => {
         categorical: true,
         categories: ["hi"],
         categoryCounts: new Map([["hi", 1]]),
-        numCategories: 1
+        numCategories: 1,
       })
     );
     expect(df.icol(2).summarize()).toEqual(
@@ -61,7 +61,7 @@ describe("Dataframe column summary", () => {
         categorical: true,
         categories: [true],
         categoryCounts: new Map([[true, 1]]),
-        numCategories: 1
+        numCategories: 1,
       })
     );
     expect(df.icol(3).summarize()).toEqual(
@@ -71,7 +71,7 @@ describe("Dataframe column summary", () => {
         max: float32Conversion(39.3),
         nan: 0,
         ninf: 0,
-        pinf: 0
+        pinf: 0,
       })
     );
     expect(df.icol(4).summarize()).toEqual(
@@ -81,7 +81,7 @@ describe("Dataframe column summary", () => {
         max: 99,
         nan: 0,
         ninf: 0,
-        pinf: 0
+        pinf: 0,
       })
     );
     expect(df.icol(5).summarize()).toEqual(
@@ -89,7 +89,7 @@ describe("Dataframe column summary", () => {
         categorical: true,
         categories: [1],
         categoryCounts: new Map([[1, 1]]),
-        numCategories: 1
+        numCategories: 1,
       })
     );
   });
@@ -103,7 +103,7 @@ describe("Dataframe column summary", () => {
         [false, true, true],
         new Float32Array([39.3, 39.3, 0]),
         new Int32Array([99, 99, 99]),
-        [1, false, "0"]
+        [1, false, "0"],
       ],
       null,
       new Dataframe.KeyIndex([
@@ -112,7 +112,7 @@ describe("Dataframe column summary", () => {
         "nameBoolean",
         "nameFloat32",
         "nameInt32",
-        "nameCategorical"
+        "nameCategorical",
       ])
     );
 
@@ -120,24 +120,34 @@ describe("Dataframe column summary", () => {
       expect.objectContaining({
         categorical: true,
         categories: expect.arrayContaining(["n0", "n1", "n2"]),
-        categoryCounts: new Map([["n0", 1], ["n1", 1], ["n2", 1]]),
-        numCategories: 3
+        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
+        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
+        categoryCounts: new Map([
+          [true, 2],
+          [false, 1],
+        ]),
+        numCategories: 2,
       })
     );
     expect(df.icol(3).summarize()).toEqual(
@@ -147,7 +157,7 @@ describe("Dataframe column summary", () => {
         max: float32Conversion(39.3),
         nan: 0,
         ninf: 0,
-        pinf: 0
+        pinf: 0,
       })
     );
     expect(df.icol(4).summarize()).toEqual(
@@ -157,15 +167,19 @@ describe("Dataframe column summary", () => {
         max: 99,
         nan: 0,
         ninf: 0,
-        pinf: 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
+        categoryCounts: new Map([
+          [1, 1],
+          [false, 1],
+          ["0", 1],
+        ]),
+        numCategories: 3,
       })
     );
   });
@@ -181,10 +195,10 @@ describe("Dataframe column summary", () => {
           39.3,
           Number.NEGATIVE_INFINITY,
           Number.NaN,
-          Number.POSITIVE_INFINITY
+          Number.POSITIVE_INFINITY,
         ]),
         new Int32Array([99, 99, 99, 99]),
-        [1, false, "0", "0"]
+        [1, false, "0", "0"],
       ],
       null,
       new Dataframe.KeyIndex([
@@ -193,7 +207,7 @@ describe("Dataframe column summary", () => {
         "nameBoolean",
         "nameFloat32",
         "nameInt32",
-        "nameCategorical"
+        "nameCategorical",
       ])
     );
 
@@ -201,24 +215,34 @@ describe("Dataframe column summary", () => {
       expect.objectContaining({
         categorical: true,
         categories: expect.arrayContaining(["n0", "n1", "n2"]),
-        categoryCounts: new Map([["n0", 1], ["n1", 1], ["n2", 2]]),
-        numCategories: 3
+        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
+        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
+        categoryCounts: new Map([
+          [true, 2],
+          [false, 1],
+        ]),
+        numCategories: 2,
       })
     );
     expect(df.icol(3).summarize()).toEqual(
@@ -228,7 +252,7 @@ describe("Dataframe column summary", () => {
         max: float32Conversion(39.3),
         nan: 1,
         ninf: 1,
-        pinf: 1
+        pinf: 1,
       })
     );
     expect(df.icol(4).summarize()).toEqual(
@@ -238,15 +262,19 @@ describe("Dataframe column summary", () => {
         max: 99,
         nan: 0,
         ninf: 0,
-        pinf: 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
+        categoryCounts: new Map([
+          [1, 1],
+          [false, 1],
+          ["0", 1],
+        ]),
+        numCategories: 3,
       })
     );
   });