Cloud-volume tile source: allow caching of info and provenance data

The content of both files can be stored in the stack's metadata field
within the `ngreInfo` and `ngpreProvenance` entries. This can speed up
tile rendering significantly.

django/applications/catmaid/control/tile.py

@@ -11,7 +11,7 @@
 from django.conf import settings
 from django.http import HttpRequest, HttpResponse
 
-from catmaid.models import UserRole, TileSourceTypes
+from catmaid.models import UserRole, TileSourceTypes, Stack
 from catmaid.control.common import ConfigurationError, get_request_bool
 from catmaid.control.authentication import requires_user_role
 
@@ -119,14 +119,31 @@ def get_cloudvolume_tile(project_id, stack_id, scale, height, width, x, y, z,
     scale_to_fit = False
     effective_scale = 1.0
     voxel_offset = (0, 0, 0)
+
+    # Use a cached info file, if availavle. This avoids fetching the info file
+    # for every tile.
+    stack = Stack.objects.get(id=stack_id)
+    infoKey = 'ngpreInfo'
+    if stack.metadata and infoKey in stack.metadata:
+        info = stack.metadata.get(infoKey)
+    else:
+        info = None
+    provenanceKey = 'ngpreProvenance'
+    if stack.metadata and provenanceKey in stack.metadata:
+        provenance = stack.metadata.get(provenanceKey)
+    else:
+        provenance = None
+
     try:
         cv = cloudvolume.CloudVolume(basename, use_https=True, parallel=False,
-                cache=cache, mip=mip, bounded=False, fill_missing=fill_missing)
+                cache=cache, mip=mip, bounded=False, fill_missing=fill_missing,
+                info=info, provenance=provenance)
         cutout = cv[x:(x + width), y:(y + height), z]
     except cloudvolume.exceptions.ScaleUnavailableError as e:
         logger.info(f'Need to use extra scaling, because mip level {mip} is not available: {e}')
         cv_test = cloudvolume.CloudVolume(basename, use_https=True, parallel=False,
-                cache=cache, bounded=False, fill_missing=fill_missing)
+                cache=cache, bounded=False, fill_missing=fill_missing,
+                                          info=info, provenance=provenance)
         # Find mip closest to the request
         min_mip = None
         min_mip_dist = float('infinity')

django/applications/catmaid/models.py

@@ -157,7 +157,11 @@ class Stack(models.Model):
             "stack. Supported is the boolean field \"clamp\" which can be set "
             "\"to \"false\" to disable tile access clamping as well as the 3-tuple "
             "\"voxelOffset\", which can be used to offset the voxels space of "
-            "the stack by the respective vector.")
+            "the stack by the respective vector. Some mirror types support "
+            "reading custom configuration information from this field. For "
+            "instance the cloud-volume tile source can cache the 'info' file "
+            "of a Neuroglancer Precopmuted info file in the 'ngpreInfo' metadata "
+            "field.")
     attribution = models.TextField(blank=True, null=True,
             help_text="Attribution or citation information for this dataset.")
     canary_location = Integer3DField(default=(0, 0, 0), help_text="Stack space "

sphinx-doc/source/tile_sources.rst

@@ -368,6 +368,14 @@ Tile source types are listed by the enumeration integer ID referenced by
 
   Currently, only HTTPS mode is supported (i.e. no explicit credentials).
 
+  If the dataset is stored in Neuroglancer Precomputed format, this tile source
+  checks for special entries in the stack's ``metadata`` field: ``ngepreInfo``
+  and ``ngepreProvenance``. Both fields act as a cache for the real dataset data
+  and can speed up tile rendering significantly. The first field is simply the
+  datasets info file. The second one is the datasets ``provenance`` file, and
+  can be set to ``{"owners": [], "sources": [], "processing": [], "description":
+  ""}`` if the file is not available.
+
 14. Neuroglancer precomputed image blocks
 *****************************************