Throw an error if the destructured options contains an unknown key.

This avoids silent errors when the caller misspells an option.

js/MultiMatrix.js

@@ -14,7 +14,10 @@ export class MultiMatrix {
      * Each matrix should correspond to a different modality, named according to its key.
      * All matrices should have data for the same set of cells, i.e., same number of columns.
      */
-    constructor({ store = {} } = {}) {
+    constructor(options = {}) {
+        const { store = {}, ...others } = options;
+        utils.checkOtherOptions(others);
+
         this.#store = store;
         this.#ncols = null;
 

js/ScranMatrix.js

@@ -82,7 +82,10 @@ export class ScranMatrix {
      * If `buffer` was supplied, the returned array is a view into it.
      * Note that this may be invalidated on the next allocation on the Wasm heap.
      */
-    row(i, { buffer = null } = {}) {
+    row(i, options = {}) {
+        let { buffer = null, ...others } = options;
+        utils.checkOtherOptions(others);
+
         if (buffer != null) {
             this.#matrix.row(i, buffer.offset);
             return buffer.array();
@@ -111,7 +114,10 @@ export class ScranMatrix {
      * If `buffer` was supplied, the returned array is a view into it.
      * Note that this may be invalidated on the next allocation on the Wasm heap.
      */
-    column(i, { buffer = null } = {}) {
+    column(i, options = {}) {
+        let { buffer = null, ...others } = options;
+        utils.checkOtherOptions(others);
+
         if (buffer != null) {
             this.#matrix.column(i, buffer.offset);
             return buffer.array();

js/aggregateAcrossCells.js

@@ -39,7 +39,9 @@ export class AggregateAcrossCellsResults {
      * @return {Float64Array|Float64WasmArray} Array of length equal to the number of genes, containing the per-gene sum of values across across all cells in the specified `group`.
      * If `average = true` in {@linkcode aggregateAcrossCells}, each element is the mean value instead.
      */
-    groupSums(group, { copy = true } = {}) {
+    groupSums(group, options = {}) {
+        const { copy = true, ...others } = options;
+        utils.checkOtherOptions(others);
         return utils.possibleCopy(this.#results.group_sums(group), copy);
     }
 
@@ -57,7 +59,9 @@ export class AggregateAcrossCellsResults {
      * If `average = true` in {@linkcode aggregateAcrossCells}, each element is the mean value instead.
      * If `buffer` is supplied, the function returns `buffer` if `asTypedArray = false`, or a view on `buffer` if `asTypedArray = true`.
      */
-    allSums({ asTypedArray = true, buffer = null } = {}) {
+    allSums(options = {}) {
+        let { asTypedArray = true, buffer = null, ...others } = options;
+        utils.checkOtherOptions(others);
         let tmp = null;
 
         try {
@@ -83,7 +87,9 @@ export class AggregateAcrossCellsResults {
      * @return {Float64Array|Float64WasmArray} Array of length equal to the number of genes, containing the number of cells with detected expression for each gene in the specified `group`.
      * If `average = true` in {@linkcode aggregateAcrossCells}, each element is the proportion of detected cells instead.
      */
-    groupDetected(group, { copy = true } = {}) {
+    groupDetected(group, options = {}) {
+        const { copy = true, ...others } = options;
+        utils.checkOtherOptions(others);
         return utils.possibleCopy(this.#results.group_detected(group), copy);
     }
 
@@ -100,7 +106,9 @@ export class AggregateAcrossCellsResults {
      * If `average = true` in {@linkcode aggregateAcrossCells}, each element is the proportion of detected cells instead.
      * If `buffer` is supplied, the function returns `buffer` if `asTypedArray = false`, or a view on `buffer` if `asTypedArray = true`.
      */
-    allDetected({ asTypedArray = true, buffer = null } = {}) {
+    allDetected(options = {}) {
+        let { asTypedArray = true, buffer = null, ...others } = options;
+        utils.checkOtherOptions(others);
         let tmp = null;
 
         try {
@@ -144,7 +152,9 @@ export class AggregateAcrossCellsResults {
  *
  * @return {AggregateAcrossCellsResults} Object containing the aggregation results.
  */
-export function aggregateAcrossCells(x, groups, { average = false, numberOfThreads = null } = {}) {
+export function aggregateAcrossCells(x, groups, options = {}) {
+    const { average = false, numberOfThreads = null, ...others } = options;
+    utils.checkOtherOptions(others);
     var group_data;
     var output;
     let nthreads = utils.chooseNumberOfThreads(numberOfThreads);

js/block.js

@@ -20,7 +20,9 @@ import * as fac from "./factorize.js";
  *
  * If `buffer` was supplied, it is used as the return value. 
  */
-export function createBlock(ncells, { buffer = null } = {}) {
+export function createBlock(ncells, options = {}) {
+    let { buffer = null, ...other } = options;
+    utils.checkOtherOptions(other);
     let total = 0;
     ncells.forEach(x => { total += x; });
 
@@ -62,7 +64,9 @@ export function subsetBlock(x, subset, { filter = null, buffer = null } = {}) {
 }
 
 // Soft-deprecated, just use subsetFactor().
-export function filterBlock(x, filter, { buffer = null } = {}) {
+export function filterBlock(x, filter, options = {}) {
+    let { buffer = null, ...other } = options;
+    utils.checkOtherOptions(other);
     return subsetBlock(x, filter, { buffer: buffer, filter: true });
 }
 

js/buildSnnGraph.js

@@ -52,7 +52,9 @@ export class BuildSnnGraphResults {
  *
  * @return {BuildSnnGraphResults} Object containing the graph.
  */
-export function buildSnnGraph(x, { scheme = "rank", neighbors = 10, numberOfThreads = null } = {}) {
+export function buildSnnGraph(x, options = {}) {
+    const { scheme = "rank", neighbors = 10, numberOfThreads = null, ...others } = options;
+    utils.checkOtherOptions(others);
     var output;
     var my_neighbors;
     let nthreads = utils.chooseNumberOfThreads(numberOfThreads);

js/chooseHvgs.js

@@ -16,9 +16,12 @@ import { ModelGeneVariancesResults } from "./modelGeneVariances.js";
  * @return {Uint8WasmArray} Array of length equal to the number of genes.
  * Highly variable genes are marked with a value of 1 and all other genes have values of zero.
  */
-export function chooseHvgs(x, { number = 4000, minimum = 0 } = {}) {
+export function chooseHvgs(x, options = {}) {
+    const { number = 4000, minimum = 0, ...others } = options;
+    utils.checkOtherOptions(others);
     let stat;
     let chosen;
+
     try {
         if (x instanceof ModelGeneVariancesResults) {
             stat = x.residuals({ copy: "view" });
@@ -27,11 +30,13 @@ export function chooseHvgs(x, { number = 4000, minimum = 0 } = {}) {
         }
         chosen = utils.createUint8WasmArray(stat.length);
         wasm.call(module => module.choose_highly_variable_genes(stat.length, stat.offset, chosen.offset, number, minimum));
+
     } catch (e) {
         chosen.free();
         throw e;
     } finally {
         stat.free();
     }
+
     return chosen;
 }

js/clusterGraph.js

@@ -10,7 +10,7 @@ export class ClusterMultilevelResults {
     #id;
     #results;
 
-    constructor(id, raw, filled = true) {
+    constructor(id, raw) {
         this.#id = id;
         this.#results = raw;
     }
@@ -36,7 +36,9 @@ export class ClusterMultilevelResults {
      *
      * @return {number} The modularity at the specified level.
      */
-    modularity({ level = null } = {}) {
+    modularity(options = {}) {
+        let { level = null, ...others } = options;
+        utils.checkOtherOptions(others);
         if (level == null) {
             level = this.bestLevel();
         }
@@ -51,7 +53,9 @@ export class ClusterMultilevelResults {
      *
      * @return {Int32Array|Int32WasmArray} Array containing the cluster membership for each cell.
      */
-    membership({ level = null, copy = true } = {}) {
+    membership(options = {}) {
+        let { level = null, copy = true, ...others } = options;
+        utils.checkOtherOptions(others);
         if (level == null) {
             level = -1;
         }
@@ -79,7 +83,7 @@ export class ClusterWalktrapResults {
     #id;
     #results;
 
-    constructor(id, raw, filled = true) {
+    constructor(id, raw) {
         this.#id = id;
         this.#results = raw;
     }
@@ -98,7 +102,9 @@ export class ClusterWalktrapResults {
      * Set to `null` to obtain the largest modularity across all merge steps.
      * @return {number} The modularity at the specified merge step, or the maximum modularity across all merge steps.
      */
-    modularity({ at = null } = {}) {
+    modularity(options = {}) {
+        let { at = null, ...others } = options;
+        utils.checkOtherOptions(others);
         if (at === null) {
             at = -1;
         }
@@ -110,7 +116,9 @@ export class ClusterWalktrapResults {
      * @param {boolean|string} [options.copy=true] - Whether to copy the results from the Wasm heap, see {@linkcode possibleCopy}.
      * @return {Int32Array|Int32WasmArray} Array containing the cluster membership for each cell.
      */
-    membership({ copy = true } = {}) {
+    membership(options = {}) {
+        const { copy = true, ...others } = options;
+        utils.checkOtherOptions(others);
         return utils.possibleCopy(this.#results.membership(), copy);
     }
 
@@ -157,7 +165,9 @@ export class ClusterLeidenResults {
      *
      * @return {(Int32Array|Int32WasmArray)} Array containing the cluster membership for each cell.
      */
-    membership({ copy = true } = {}) {
+    membership(options = {}) {
+        const { copy = true, ...others } = options;
+        utils.checkOtherOptions(others);
         return utils.possibleCopy(this.#results.membership(), copy);
     }
 
@@ -193,15 +203,18 @@ export class ClusterLeidenResults {
  * @return {ClusterMultiLevelResults|ClusterWalktrapResults|ClusterLeidenResults} Object containing the clustering results.
  * The class of this object depends on the choice of `method`.
  */
-export function clusterGraph(x, { 
-    method = "multilevel", 
-    multiLevelResolution = 1, 
-    leidenResolution = 1, 
-    leidenModularityObjective = false,
-    walktrapSteps = 4
-} = {}) {
-    var output;
+export function clusterGraph(x, options = {}) {
+    const { 
+        method = "multilevel", 
+        multiLevelResolution = 1, 
+        leidenResolution = 1, 
+        leidenModularityObjective = false,
+        walktrapSteps = 4,
+        ...others
+    } = options;
+    utils.checkOtherOptions(others);
 
+    var output;
     try {
         if (method == "multilevel") {
             output = gc.call(

js/clusterKmeans.js

@@ -10,7 +10,7 @@ export class ClusterKmeansResults {
     #id;
     #results;
 
-    constructor(id, raw, filled = true) {
+    constructor(id, raw) {
         this.#results = raw;
         this.#id = id;
     }
@@ -34,7 +34,9 @@ export class ClusterKmeansResults {
      * @param {boolean|string} [options.copy=true] - Whether to copy the results from the Wasm heap, see {@linkcode possibleCopy}.
      * @return {Int32Array|Int32WasmArray} Array containing the cluster assignment for each cell.
      */
-    clusters({ copy = true } = {}) {
+    clusters(options = {}) {
+        const { copy = true, ...others } = options;
+        utils.checkOtherOptions(others);
         return utils.possibleCopy(this.#results.clusters(), copy);
     }
 
@@ -43,7 +45,9 @@ export class ClusterKmeansResults {
      * @param {boolean|string} [options.copy=true] - Whether to copy the results from the Wasm heap, see {@linkcode possibleCopy}.
      * @return {Int32Array|Int32WasmArray} Array containing the number of cells in each cluster.
      */
-    sizes({ copy = true } = {}) {
+    sizes(options = {}) {
+        const { copy = true, ...others } = options;
+        utils.checkOtherOptions(others);
         return utils.possibleCopy(this.#results.cluster_sizes(), copy);
     }
 
@@ -53,7 +57,9 @@ export class ClusterKmeansResults {
      * @return {Float64Array|Float64WasmArray} Array containing the cluster centers in column-major format,
      * where rows are dimensions and columns are the clusters.
      */
-    centers({ copy = true } = {}) {
+    centers(options = {}) {
+        const { copy = true, ...others } = options;
+        utils.checkOtherOptions(others);
         return utils.possibleCopy(this.#results.centers(), copy);
     }
 
@@ -88,7 +94,7 @@ export class ClusterKmeansResults {
  * Cluster cells using k-means.
  * A variety of initialization and refinement algorithms can be used here, see the [**kmeans** documentation](https://github.com/LTLA/CppKmeans) for more details.
  *
-* @param {(RunPcaResults|Float64WasmArray|Array|TypedArray)} x - Numeric coordinates of each cell in the dataset.
+ * @param {(RunPcaResults|Float64WasmArray|Array|TypedArray)} x - Numeric coordinates of each cell in the dataset.
  * For array inputs, this is expected to be in column-major format where the rows are the variables and the columns are the cells.
  * For a {@linkplain RunPcaResults} input, we extract the principal components.
  * @param {number} clusters Number of clusters to create.
@@ -115,18 +121,22 @@ export class ClusterKmeansResults {
  *
  * @return {ClusterKmeansResults} Object containing the clustering results.
  */
-export function clusterKmeans(x, clusters, { 
-    numberOfDims = null, 
-    numberOfCells = null, 
-    initMethod = "var-part", 
-    initSeed = 5768, 
-    initVarPartSizeAdjust = 1, 
-    initVarPartOptimize = true, 
-    refineMethod = "hartigan-wong",
-    refineLloydIterations = 100,
-    refineHartiganWongIterations = 10,
-    numberOfThreads = null 
-} = {}) {
+export function clusterKmeans(x, clusters, options = {}) {
+    let { 
+        numberOfDims = null, 
+        numberOfCells = null, 
+        initMethod = "var-part", 
+        initSeed = 5768, 
+        initVarPartSizeAdjust = 1, 
+        initVarPartOptimize = true, 
+        refineMethod = "hartigan-wong",
+        refineLloydIterations = 100,
+        refineHartiganWongIterations = 10,
+        numberOfThreads = null,
+        ...others
+    } = options;
+    utils.checkOtherOptions(others);
+
     var buffer;
     var output;
     let nthreads = utils.chooseNumberOfThreads(numberOfThreads);

js/computeClrm1Factors.js

@@ -18,7 +18,9 @@ import * as wa from "wasmarrays.js";
  * Note that the factors are not centered and should be passed to {@linkcode centerSizeFactors} before calling {@linkcode normalizeCounts}.
  * If `buffer` is supplied, the function returns `buffer` if `asTypedArray = false`, or a view on `buffer` if `asTypedArray = true`.
  */
-export function computeClrm1Factors(x, { asTypedArray = true, buffer = null, priorCount = 10, numberOfThreads = null } = {}) {
+export function computeClrm1Factors(x, options = {}) {
+    let { asTypedArray = true, buffer = null, priorCount = 10, numberOfThreads = null, ...others } = options;
+    utils.checkOtherOptions(others);
     var local_buffer = null;
     let nthreads = utils.chooseNumberOfThreads(numberOfThreads);
 

js/delayed.js

@@ -21,7 +21,9 @@ import * as wasm from "./wasm.js";
  * @return {ScranMatrix} A ScranMatrix containing the delayed arithmetic operation on `x`.
  * If `inPlace = true`, this is a reference to `x`, otherwise it is a new ScranMatrix.
  */
-export function delayedArithmetic(x, operation, value, { right = true, along = "row", inPlace = false } = {}) {
+export function delayedArithmetic(x, operation, value, options = {}) {
+    const { right = true, along = "row", inPlace = false, ...others } = options;
+    utils.checkOtherOptions(others);
     let xcopy;
     let vbuffer;
     let target;
@@ -68,7 +70,9 @@ export function delayedArithmetic(x, operation, value, { right = true, along = "
  * @return {ScranMatrix} A ScranMatrix containing the delayed math operation on `x`.
  * If `inPlace = true`, this is a reference to `x`, otherwise it is a new ScranMatrix.
  */
-export function delayedMath(x, operation, { logBase = null, inPlace = false } = {}) {
+export function delayedMath(x, operation, options = {}) {
+    let { logBase = null, inPlace = false, ...others } = options;
+    utils.checkOtherOptions(others);
     let xcopy;
     let target;
 
@@ -104,7 +108,9 @@ export function delayedMath(x, operation, { logBase = null, inPlace = false } =
  * @return {ScranMatrix} A ScranMatrix containing the transposition of `x`.
  * If `inPlace = true`, this is a reference to `x`, otherwise it is a new ScranMatrix.
  */
-export function transpose(x, { inPlace = false } = {}) {
+export function transpose(x, options = {}) {
+    const { inPlace = false, ...others } = options;
+    utils.checkOtherOptions(others);
     let xcopy;
     let target;