WIP: feat(ts): add downsampleItkWasm method

Author: thewtex

ts/src/io/to_multiscales.ts

@@ -10,12 +10,14 @@ import {
   createMultiscales,
 } from "../utils/factory.ts";
 import { getMethodMetadata } from "../utils/method_metadata.ts";
+import { downsampleItkwasm } from "../methods/itkwasm.ts";
 
 export interface ToNgffImageOptions {
   dims?: string[];
   scale?: Record<string, number>;
   translation?: Record<string, number>;
   name?: string;
+  shape?: number[]; // Explicit shape for typed arrays
 }
 
 /**
@@ -34,10 +36,11 @@ export async function toNgffImage(
     scale = {},
     translation = {},
     name = "image",
+    shape: explicitShape,
   } = options;
 
   // Determine data shape and create typed array
-  let typedData: Float32Array;
+  let typedData: Float32Array | Uint8Array | Uint16Array;
   let shape: number[];
 
   if (Array.isArray(data)) {
@@ -78,18 +81,34 @@ export async function toNgffImage(
     }
   } else {
     // ArrayLike (already a typed array)
-    typedData = new Float32Array(data as ArrayLike<number>);
-    shape = [typedData.length];
+    // Use explicit shape if provided, otherwise infer from data length and dims
+    if (explicitShape) {
+      shape = [...explicitShape];
+    } else {
+      // Try to infer shape - this is a best guess
+      shape = [data.length];
+    }
+
+    // Preserve the original typed array type
+    if (data instanceof Uint8Array) {
+      typedData = data;
+    } else if (data instanceof Uint16Array) {
+      typedData = data;
+    } else {
+      typedData = new Float32Array(data as ArrayLike<number>);
+    }
   }
 
-  // Adjust shape to match dims length
-  while (shape.length < dims.length) {
-    shape.unshift(1);
+  // Adjust shape to match dims length if not explicitly provided
+  if (!explicitShape) {
+    while (shape.length < dims.length) {
+      shape.unshift(1);
+    }
   }
 
-  if (shape.length > dims.length) {
+  if (shape.length !== dims.length) {
     throw new Error(
-      `Data dimensionality (${shape.length}) exceeds dims length (${dims.length})`,
+      `Shape dimensionality (${shape.length}) must match dims length (${dims.length})`,
     );
   }
 
@@ -109,7 +128,7 @@ export async function toNgffImage(
 
   // Write data to zarr array
   await zarr.set(zarrArray, [], {
-    data: typedData,
+    data: typedData as Float32Array,
     shape,
     stride: calculateStride(shape),
   });
@@ -147,19 +166,40 @@ export interface ToMultiscalesOptions {
  * @param options - Configuration options
  * @returns Multiscales object
  */
-export function toMultiscales(
+export async function toMultiscales(
   image: NgffImage,
   options: ToMultiscalesOptions = {},
-): Multiscales {
+): Promise<Multiscales> {
   const {
     scaleFactors = [2, 4],
     method = Methods.ITKWASM_GAUSSIAN,
     chunks: _chunks,
   } = options;
 
-  // For now, create only the base image (no actual downsampling)
-  // This is a simplified implementation for testing metadata functionality
-  const images = [image];
+  let images: NgffImage[];
+
+  // Check if we should perform actual downsampling
+  if (
+    method === Methods.ITKWASM_GAUSSIAN ||
+    method === Methods.ITKWASM_BIN_SHRINK ||
+    method === Methods.ITKWASM_LABEL_IMAGE
+  ) {
+    // Perform actual downsampling using ITK-Wasm
+    const smoothing = method === Methods.ITKWASM_GAUSSIAN
+      ? "gaussian"
+      : method === Methods.ITKWASM_BIN_SHRINK
+      ? "bin_shrink"
+      : "label_image";
+
+    images = await downsampleItkwasm(
+      image,
+      scaleFactors as (Record<string, number> | number)[],
+      smoothing,
+    );
+  } else {
+    // Fallback: create only the base image (no actual downsampling)
+    images = [image];
+  }
 
   // Create axes from image dimensions
   const axes = image.dims.map((dim) => {
@@ -178,14 +218,14 @@ export function toMultiscales(
     }
   });
 
-  // Create datasets
-  const datasets = [
-    createDataset(
-      "0",
-      image.dims.map((dim) => image.scale[dim]),
-      image.dims.map((dim) => image.translation[dim]),
-    ),
-  ];
+  // Create datasets for all images
+  const datasets = images.map((img, index) => {
+    return createDataset(
+      `${index}`,
+      img.dims.map((dim) => img.scale[dim]),
+      img.dims.map((dim) => img.translation[dim]),
+    );
+  });
 
   // Create metadata with method information
   const methodMetadata = getMethodMetadata(method);