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README.md

@@ -2457,7 +2457,7 @@ Like [Plot.mapY](#plotmapymap-options), but applies the normalize map method wit
 Plot.map({y: Plot.window(24)}, {x: "Date", y: "Close", stroke: "Symbol"})
 ```
 
-Returns a window map method for the given window size *k*, suitable for use with Plot.map. For additional options to the window transform, replace the number *k* with an object with properties *k*, *anchor*, or *reduce*.
+Returns a window map method for the given window size *k*, suitable for use with Plot.map. For additional options to the window transform, replace the number *k* with an object with properties *k*, *anchor*, *reduce*, or *strict*.
 
 #### Plot.windowX(*k*, *options*)
 

src/transforms/window.d.ts

@@ -22,19 +22,101 @@ export type WindowReducerFunction = (values: any[]) => any;
 export type WindowReducer = WindowReducerName | WindowReducerFunction;
 
 export interface WindowOptions {
-  k?: number;
+  /**
+   * The size (number of consecutive values) in the window; includes the current
+   * value.
+   */
+  k: number;
+
+  /**
+   * How to produce a summary statistic from the **k** values in the current
+   * window. The reducer may be specified as:
+   *
+   * * *min* - the minimum
+   * * *max* - the maximum
+   * * *mean* (default) - the mean (average)
+   * * *median* - the median
+   * * *mode* - the mode (most common occurrence)
+   * * *pXX* - the percentile value, where XX is a number in [00,99]
+   * * *sum* - the sum of values
+   * * *deviation* - the standard deviation
+   * * *variance* - the variance per [Welford’s algorithm](https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Welford's_online_algorithm)
+   * * *difference* - the difference between the last and first window value
+   * * *ratio* - the ratio of the last and first window value
+   * * *first* - the first value
+   * * *last* - the last value
+   * * a function to be passed an array of **k** values
+   */
   reduce?: WindowReducer;
+
+  /**
+   * How to align the rolling window, placing the current value:
+   *
+   * * *start* - as the first element in the window
+   * * *middle* (default) - in the middle of the window, rounding down if **k** is even
+   * * *end* - as the last element in the window
+   */
   anchor?: "start" | "middle" | "end";
-  shift?: "leading" | "centered" | "trailing"; // deprecated!
+
+  /** @deprecated See **anchor**. */
+  shift?: "leading" | "centered" | "trailing";
+
+  /**
+   * If true, the output start values or end values or both (depending on the
+   * **anchor**) of each series may be undefined since there are not enough
+   * elements to create a window of size **k**; output values may also be
+   * undefined if some of the input values in the corresponding window are
+   * undefined.
+   *
+   * If false (the default), the window will be automatically truncated as
+   * needed, and undefined input values are ignored. For example, if **k** is 24
+   * and **anchor** is *middle*, then the initial 11 values have effective
+   * window sizes of 13, 14, 15, … 23, and likewise the last 12 values have
+   * effective window sizes of 23, 22, 21, … 12. Values computed with a
+   * truncated window may be noisy; if you would prefer to not show this data,
+   * set the **strict** option to true.
+   */
   strict?: boolean;
 }
 
+/**
+ * Computes a moving window of *x*, *x1*, and *x2* channel values and then
+ * derives a summary statistic from values in the current window, say to compute
+ * a rolling average. The window options can be specified as the first argument,
+ * or grouped with the *options*. For example, the following are equivalent:
+ *
+ * ```js
+ * Plot.windowX(24, {x: "Anomaly", y: "Date"});
+ * Plot.windowX({k: 24, reduce: "mean", x: "Anomaly", y: "Date"});
+ * Plot.windowX({k: 24, reduce: "mean"}, {x: "Anomaly", y: "Date"});
+ * ```
+ */
 export function windowX<T>(options?: T & WindowOptions): Transformed<T>;
-
 export function windowX<T>(windowOptions?: WindowOptions | number, options?: T): Transformed<T>;
 
+/**
+ * Computes a moving window of *y*, *y1*, and *y2* channel values around and
+ * then derives a summary statistic from values in the current window, say to
+ * compute a rolling average. The window options can be specified as the first
+ * argument, or grouped with the *options*. For example, the following are
+ * equivalent:
+ *
+ * ```js
+ * Plot.windowY(24, {x: "Date", y: "Anomaly"});
+ * Plot.windowY({k: 24, reduce: "mean", x: "Date", y: "Anomaly"});
+ * Plot.windowY({k: 24, reduce: "mean"}, {x: "Date", y: "Anomaly"});
+ * ```
+ */
 export function windowY<T>(options?: T & WindowOptions): Transformed<T>;
-
 export function windowY<T>(windowOptions?: WindowOptions | number, options?: T): Transformed<T>;
 
+/**
+ * Returns a window map method suitable for use with Plot.map. The options are
+ * the window size *k*, or an object with properties *k*, *anchor*, *reduce*, or
+ * *strict*.
+ *
+ * ```js
+ * Plot.map({y: Plot.window(24)}, {x: "Date", y: "Close", stroke: "Symbol"})
+ * ```
+ */
 export function window(options?: WindowOptions | number): Map;