+ plots, + enc

deno_jupyter_bug.ipynb

@@ -27,7 +27,7 @@
    ],
    "source": [
     "const document = null;\n",
-    "import * as p from \"https://l12.xyz/x/shortcuts/raw/plots.ts\"\n"
+    "import * as p from \"https://l12.xyz/x/shortcuts/raw/plots.ts\";"
    ]
   }
  ],

encoding.ts

@@ -1,6 +1,6 @@
 import pl from "npm:nodejs-polars";
 
-export function oneHotEncoding(dataframe) {
+export function oneHotEncoding(dataframe: pl.DataFrame): pl.DataFrame {
   let df = pl.DataFrame();
   for (const columnName of dataframe.columns) {
     const column = dataframe[columnName];
@@ -12,3 +12,85 @@ export function oneHotEncoding(dataframe) {
   }
   return df;
 }
+
+export function polynomialTransform(
+  dataframe: pl.DataFrame,
+  degree = 2,
+  interaction_only = false,
+  include_bias = true,
+): pl.DataFrame {
+  let polyRecords: number[][] = [];
+  dataframe.map((X: number[]) => {
+    polyRecords.push(
+      polynomialFeatures(X, degree, interaction_only, include_bias),
+    );
+  });
+  return pl.readRecords(polyRecords);
+}
+
+export function polynomialFeatures(
+  X: number[],
+  degree = 2,
+  interaction_only = false,
+  include_bias = true,
+): number[] {
+  let features = [...X];
+  let prev_chunk = [...X];
+  const indices = Array.from({ length: X.length }, (_, i) => i);
+  for (let d = 1; d < degree; d++) {
+    const new_chunk: any[] = [];
+    for (let i = 0; i < (interaction_only ? X.length - d : X.length); i++) {
+      const v = X[i];
+      const next_index = new_chunk.length;
+      for (let j = i + (interaction_only ? 1 : 0); j < prev_chunk.length; j++) {
+        new_chunk.push(v * prev_chunk[j]);
+      }
+      indices[i] = next_index;
+    }
+    features = features.concat(new_chunk);
+    prev_chunk = new_chunk;
+  }
+  if (include_bias) {
+    features.unshift(1);
+  }
+  return features;
+}
+
+/**
+ * Adds missing rows at given interval, uses mean of previous and next value.
+ * Example for one feature: [1, 2, 4, 5] -> [1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5]
+ * @param feature
+ * @param df
+ * @param bin
+ */
+export function augmentMeanForward(
+  feature: string,
+  df: pl.DataFrame,
+  interval = 100,
+) {
+  let sorted = df.sort(feature);
+  let result = sorted.head(0);
+  let n: null | number = null;
+  for (let i = 0; i < sorted.height - 1; i++) {
+    let p1 = n ?? sorted.row(i).at(-1);
+    let p2 = sorted.row(i + 1).at(-1);
+    if (p2 - p1 > interval) {
+      let avg = (p1 + p2) / 2;
+      result = pl.concat([
+        result,
+        pl.concat([result.tail(2), sorted.slice({ offset: i + 1, length: 2 })])
+          .shift(-1)
+          .fillNull("mean")
+          .tail(1),
+      ]);
+      if (p2 - avg > interval) {
+        i--;
+        n = avg;
+        continue;
+      }
+      result = pl.concat([result, sorted.slice(1, i)]);
+      n = null;
+    }
+  }
+  return result;
+}

expr.ts

@@ -12,9 +12,8 @@ export const fillzero = (
   value = 0.0001,
 ) => (pl.all().replaceStrict(0, value, pl.all()));
 
-export const ScaleExpr: pl.Expr = (pl.all().minus(pl.all().min())).div(
-  pl.all().max().minus(pl.all().min()),
-);
-export const StdNormExpr: pl.Expr = pl.all().minus(pl.all().mean()).div(
-  pl.all().std(),
-);
+export const minmaxScale = (col: pl.Expr) =>
+  (col.minus(col.min())).div(col.max().minus(col.min()));
+
+export const standardScale = (col: pl.Expr) =>
+  (col.minus(col.mean())).div(col.std());

plots.ts

@@ -208,3 +208,50 @@ export function threeChart(data: any[], x = "column", opts = { width: 800 }) {
     }),
   };
 }
+
+export function distPlot(...data: number[][]) {
+  const colors = [
+    "red",
+    "blue",
+    "green",
+    "orange",
+    "purple",
+    "brown",
+    "pink",
+    "gray",
+    "black",
+    "cyan",
+    "magenta",
+    "yellow",
+    "lightblue",
+    "lightgreen",
+    "lightgray",
+  ];
+  const plt = Plot.plot({
+    margin: 50,
+    width: 1200,
+    marks: [
+      Plot.hexgrid(),
+      data.map((a, i) =>
+        Plot.areaY(
+          a,
+          Plot.binX({ y: "count" }, {
+            x: (x: number) => x,
+            fill: colors[i % colors.length],
+            curve: "catmull-rom",
+            fillOpacity: .5,
+          }),
+        )
+      ),
+    ],
+    document,
+  });
+  plt.setAttribute("xmlns", "http://www.w3.org/2000/svg");
+  return {
+    [Symbol.for("Jupyter.display")]: () => ({
+      "text/html": `<img src='data:image/svg+xml;base64,${
+        btoa(unescape(encodeURIComponent(plt)))
+      }'>`,
+    }),
+  };
+}