feat: fully support ome zarr

frontend/src/const.ts

@@ -78,6 +78,7 @@ export const XFORM_FILE_TYPE = "https://voluba.apps.hbp.eu/@types/transform"
 type CoordSpace = Record<'x'|'y'|'z', export_nehuba.Dimension>
 
 export const cvtToNm = {
+  micrometer: (v: number) => v * 1e3,
   pm: (v: number) => v * 1e-3,
   nm: (v: number) => v,
   μm: (v: number) => v * 1e3,
@@ -91,6 +92,7 @@ export const cvtToNm = {
 export type VoxelUnit = keyof typeof cvtToNm
 
 export const cvtNmTo: Record<VoxelUnit, (nm: number) => number> = {
+  micrometer: (v: number) => v * 1e-3,
   pm: v => v * 1e3,
   nm: v => v,
   μm: v => v * 1e-3,
@@ -231,6 +233,7 @@ type Volume = {
     'neuroglancer/precomputed'?: string
     'neuroglancer/precomputed/surface'?: string
     'neuroglancer/n5'?: string
+    'neuroglancer/zarr'?: string
   }
 }
 
@@ -261,6 +264,7 @@ export function parseGSUrl(url: string): string {
 const protocol: Record<string, keyof Volume['providers']> = {
   "precomputed://": "neuroglancer/precomputed",
   "n5://": "neuroglancer/n5",
+  "zarr://": "neuroglancer/zarr",
 }
 
 export function extractProtocolUrl(ngUrl: string): Volume {
@@ -417,3 +421,47 @@ export type EbrainsWorkflowPollResponse = {
   progresses: EbrainsPublishResult[]
   user: User
 }
+
+export type ZarrAttrs = {
+  multiscales: {
+    name: string
+    version: string
+    axes: {
+      name: "x" | "y" | "z" | string
+      type: "space" | string
+      units: "micrometer" | string
+    }[]
+    datasets: {
+      coordinateTransformations: {
+        scale: number[]
+        type: "scale" | string
+      }[]
+      path: string
+    }[]
+  }[]
+}
+
+export type BloscCompressor = {
+  blocksize: 0 | number
+  clevel: number
+  cname: "zstd" | string
+  id: "blosc"
+  shuffle: 1 | number
+}
+
+export type CompressorType = BloscCompressor
+
+export type ZarrArray = {
+  chunks: number[]
+  dimension_separator: string
+
+  dtype: "<u2" | string
+
+  order: "C" | "F"
+  shape: number[]
+  zarr_format: number
+
+  compressor: CompressorType
+  fill_value: 0
+  filters: unknown
+}

frontend/src/state/inputs/selectors.ts

@@ -1,7 +1,7 @@
 import { createSelector, select } from '@ngrx/store';
 import { nameSpace, LocalState } from './consts';
 import { Observable, combineLatest, distinctUntilChanged, forkJoin, from, map, of, pipe, switchMap, throwError } from 'rxjs';
-import { arrayEqual, canBeConverted, cvtToNm, TVolume, parseGSUrl } from 'src/const';
+import { arrayEqual, canBeConverted, cvtToNm, TVolume, parseGSUrl, ZarrAttrs, ZarrArray } from 'src/const';
 
 
 const featureSelector = (state: any) => state[nameSpace] as LocalState;
@@ -55,6 +55,7 @@ const incInfoPipe = pipe(
     const volume = incoming.volumes[0]
     const precomputedUrl = volume.providers["neuroglancer/precomputed"]
     const n5Url = volume.providers["neuroglancer/n5"]
+    const zarrUrl = volume.providers["neuroglancer/zarr"]
     if (!!precomputedUrl) {
       return from(
         fetch(`${precomputedUrl}/info`).then(res => res.json() as Promise<{ scales: { size: number[], resolution: number[] }[] }>)
@@ -82,6 +83,58 @@ const incInfoPipe = pipe(
         })
       )
     }
+    if (!!zarrUrl) {
+
+      return from(
+        fetch(parseGSUrl(`${zarrUrl}/.zattrs`)).then(res => res.json() as Promise<ZarrAttrs>)
+      ).pipe(
+        switchMap(zarrattr => {
+          const { multiscales } = zarrattr
+          if (multiscales.length !== 1) {
+            return throwError(() => new Error(`Can only deal with one dataset, but got ${multiscales.length}`)) 
+          }
+          const scale = multiscales[0]
+          const { axes, datasets } = scale
+          if (axes.length !== 3) {
+            return throwError(() => new Error(`Can only deal with axes with length 3`))
+          }
+          for (const { type, units } of axes){
+            if (type !== "space") {
+              return throwError(() => new Error(`Can only deal with space axes`))
+            }
+          }
+          if (datasets.length === 0) {
+            return throwError(() => new Error(`must have at least one dataset`)) 
+          }
+          const dataset = datasets[0]
+          const { coordinateTransformations, path } = dataset
+          if (coordinateTransformations.length !== 1) {
+            return throwError(() => new Error(`Can only deal with one coordate transforms, but got ${coordinateTransformations.length}`)) 
+          }
+          const coordinateTransformation = coordinateTransformations[0]
+          const { scale: _scale } = coordinateTransformation
+
+          return from(
+            fetch(parseGSUrl(`${zarrUrl}/${path}/.zarray`)).then(res => res.json() as Promise<ZarrArray>)
+          ).pipe(
+            map(({ shape }) => {
+              return {
+                "neuroglancer/zarr": {
+                  axes,
+                  datasets: [
+                    {
+                      scale: _scale,
+                      shape
+                    }
+                  ]
+                }
+              } as IncInfo
+            })
+          )
+
+        })
+      )
+    }
     return throwError(() => new Error(`volume is neither precomputed nor n5`))
   })
 )
@@ -117,6 +170,20 @@ export const incVoxelSize = pipe(
         return cvtToNm[unit](resolution[idx])
       })
     }
+    if (!!v["neuroglancer/zarr"]) {
+      const { datasets, axes } = v["neuroglancer/zarr"]
+      const dataset = datasets[0]
+      const { scale, shape } = dataset
+      return (scale as number[]).map((v, idx: number) => {
+        const unit = axes[idx].units
+        if (!(unit in cvtToNm)) {
+          console.warn(`${unit} cannot be converted. Using 1 as default`)
+          return 1
+        }
+        return cvtToNm[unit as keyof typeof cvtToNm](v)
+      })
+
+    }
     console.warn(`v voxel size cannot be found: ${v}`)
     return null
   })
@@ -139,7 +206,12 @@ export const incVoxelExtents = pipe(
       const { dimensions } = s0 as { blockSize: number[], dimensions: number[] }
       return dimensions
     }
-    console.warn(`v voxel size cannot be found: ${v}`)
+    if (!!v["neuroglancer/zarr"]) {
+      const { datasets } = v["neuroglancer/zarr"]
+      const dataset = datasets[0]
+      return dataset.shape as number[]
+    }
+    console.warn(`voxel extent cannot be found: ${v}`)
     return null
   })
 )

frontend/src/views/input-volumes/input-volumes.component.html

@@ -171,10 +171,10 @@
                     </mat-label>
                     <input type="text" formControlName="url" matInput>
                     <mat-hint>
-                        Neuroglancer URL, must start with precomputed:// or n5://
+                        Neuroglancer URL, must start with precomputed://, zarr:// or n5://
                     </mat-hint>
                     <mat-error *ngIf="newVolumeCtrl.controls.url.errors">
-                        Malformed URL. Must start with <code>precomputed://</code> or <code>n5://</code>
+                        Malformed URL. Must start with <code>precomputed://</code>, <code>zarr://</code> or <code>n5://</code>
                     </mat-error>
                 </mat-form-field>
             </form>