Merge pull request #713 from bnmajor/roi-multiscales

Add get_roi_multiscales method

Author: thewtex

examples/integrations/itk/SelectROI.ipynb

@@ -45,8 +45,9 @@
    "source": [
     "import itk\n",
     "import pooch\n",
-    "from ngff_zarr import to_multiscales, ngff_image_to_itk_image, Methods\n",
-    "from itkwidgets import view"
+    "from ngff_zarr import ngff_image_to_itk_image\n",
+    "from itkwidgets import view\n",
+    "import zarr"
    ]
   },
   {
@@ -235,8 +236,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Slices for loaded scale:       (slice(0, 250, None), slice(0, 350, None), slice(120, 173, None))\n",
-      "Slices with default parameter: (slice(0, 250, None), slice(0, 350, None), slice(120, 173, None))\n"
+      "Slices for loaded scale:       (slice(0, 250, None), slice(0, 350, None), slice(122, 170, None))\n",
+      "Slices with default parameter: (slice(0, 250, None), slice(0, 350, None), slice(122, 170, None))\n"
      ]
     }
    ],
@@ -246,6 +247,13 @@
     "print(f'Slices with default parameter: {default_roi_slices}')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### The ROI region will return the physical, world coordinates for the selection"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 10,
@@ -256,10 +264,8 @@
    },
    "outputs": [],
    "source": [
-    "# Create a new viewer using only the data in the ROI determined above\n",
-    "# get_roi_image will return a dict of ngff images with the keys representing the names for each\n",
-    "# For our example we should have one entry under \"Image\"\n",
-    "roi_image = viewer.get_roi_image(loaded_scale)"
+    "# Get the selected region for the current level\n",
+    "roi_region = viewer.get_roi_region()"
    ]
   },
   {
@@ -274,7 +280,8 @@
     {
      "data": {
       "text/plain": [
-       "NgffImage(data=dask.array<getitem, shape=(250, 350, 53), dtype=int16, chunksize=(128, 128, 45), chunktype=numpy.ndarray>, dims=['z', 'y', 'x'], scale={'z': 0.2734, 'y': 0.2734, 'x': 0.2734}, translation={'x': 25.973146382696534, 'y': -6.971699714660643, 'z': -6.971699953079224}, name='Image', axes_units={'z': None, 'y': None, 'x': None}, computed_callbacks=[])"
+       "[{'x': 26.70976023219073, 'y': -6.971699714660643, 'z': -6.971699953079224},\n",
+       " {'x': 39.35382616126007, 'y': 88.71824073791504, 'z': 61.378257513046265}]"
       ]
      },
      "execution_count": 11,
@@ -283,14 +290,7 @@
     }
    ],
    "source": [
-    "roi_image"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "#### The ROI region will return the physical, world coordinates for the selection"
+    "roi_region"
    ]
   },
   {
@@ -303,8 +303,9 @@
    },
    "outputs": [],
    "source": [
-    "# Get the selected region for the current level\n",
-    "roi_region = viewer.get_roi_region()"
+    "# get_roi_image will return an ngff image for the currently selected image\n",
+    "# optionally a name can also be passed in to select a specific image if more than one image or label is loaded\n",
+    "roi_image = viewer.get_roi_image(loaded_scale)"
    ]
   },
   {
@@ -319,8 +320,7 @@
     {
      "data": {
       "text/plain": [
-       "[{'x': 25.973146382696534, 'y': -6.971699714660643, 'z': -6.971699953079224},\n",
-       " {'x': 40.14316091031731, 'y': 88.71824073791504, 'z': 61.378257513046265}]"
+       "NgffImage(data=dask.array<getitem, shape=(250, 350, 48), dtype=int16, chunksize=(128, 128, 42), chunktype=numpy.ndarray>, dims=['z', 'y', 'x'], scale={'z': 0.2734, 'y': 0.2734, 'x': 0.2734}, translation={'x': 26.70976023219073, 'y': -6.971699714660643, 'z': -6.971699953079224}, name='Image', axes_units={'z': None, 'y': None, 'x': None}, computed_callbacks=[])"
       ]
      },
      "execution_count": 13,
@@ -329,7 +329,7 @@
     }
    ],
    "source": [
-    "roi_region"
+    "roi_image"
    ]
   },
   {
@@ -342,8 +342,8 @@
    },
    "outputs": [],
    "source": [
-    "# Create an itk image from the ngff image returned from get_roi_image\n",
-    "itk_image = ngff_image_to_itk_image(roi_image)"
+    "# Optionally we can also grab the ngff images for all scales\n",
+    "roi_multiscales = viewer.get_roi_multiscale()"
    ]
   },
   {
@@ -354,6 +354,30 @@
      "skip-execution"
     ]
    },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Multiscales(images=[NgffImage(data=dask.array<rechunk-merge, shape=(250, 350, 48), dtype=int16, chunksize=(128, 128, 48), chunktype=numpy.ndarray>, dims=['z', 'y', 'x'], scale={'z': 0.2734, 'y': 0.2734, 'x': 0.2734}, translation={'x': 26.70976023219073, 'y': -6.971699714660643, 'z': -6.971699953079224}, name='Image', axes_units={'z': None, 'y': None, 'x': None}, computed_callbacks=[]), NgffImage(data=dask.array<rechunk-merge, shape=(250, 175, 48), dtype=int16, chunksize=(128, 128, 48), chunktype=numpy.ndarray>, dims=['z', 'y', 'x'], scale={'z': 0.2734, 'y': 0.5468, 'x': 0.2734}, translation={'z': -6.971699953079224, 'y': -6.8349997146606425, 'x': 26.70976023219073}, name='image', axes_units=None, computed_callbacks=[])], metadata=Metadata(axes=[Axis(name='z', type='space', unit=None), Axis(name='y', type='space', unit=None), Axis(name='x', type='space', unit=None)], datasets=[Dataset(path='scale0/Image', coordinateTransformations=[Scale(scale=[0.2734, 0.2734, 0.2734], type='scale'), Translation(translation=[-6.971699953079224, -6.971699714660643, 26.70976023219073], type='translation')]), Dataset(path='scale1/Image', coordinateTransformations=[Scale(scale=[0.2734, 0.5468, 0.2734], type='scale'), Translation(translation=[-6.971699953079224, -6.8349997146606425, 26.70976023219073], type='translation')])], coordinateTransformations=None, name='Image', version='0.4'), scale_factors=[{'x': 1, 'y': 2, 'z': 1}], method=<Methods.DASK_IMAGE_GAUSSIAN: 'dask_image_gaussian'>, chunks={'z': 128, 'y': 128, 'x': 128})"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "roi_multiscales"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "tags": [
+     "skip-execution"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -402,7 +426,8 @@
     }
    ],
    "source": [
-    "viewer2 = view(itk_image, rotate=True)"
+    "# Create a new viewer using only the data in the ROI determined above\n",
+    "viewer2 = view(roi_multiscales, rotate=True)"
    ]
   },
   {
@@ -416,7 +441,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 17,
    "metadata": {
     "tags": [
      "skip-execution"

itkwidgets/cell_watcher.py

@@ -181,27 +181,35 @@ async def _execute_next_request(self):
             else:
                 self.kernel._publish_status("idle")
 
-        self.current_request = None
-        if self.all_getters_resolved:
+        if not self.results:
+            self.current_request = None
+        if self.all_getters_resolved and not self._events.empty():
             # Continue processing the remaining queued tasks
             self.create_task(self.execute_next_request)
 
     def update_namespace(self):
         # Update the namespace variables with the results from the getters
         # FIXME: This is a temporary "fix" and does not handle updating output
         keys = [k for k in self.shell.user_ns.keys()]
-        for key in keys:
-            value = self.shell.user_ns[key]
-            if asyncio.isfuture(value) and (isinstance(value, FuturePromise) or isinstance(value, asyncio.Task)):
-                # Getters/setters return futures
-                # They should all be resolved now, so use the result
-                self.shell.user_ns[key] = value.result()
-        self.results.clear()
+        try:
+            for key in keys:
+                value = self.shell.user_ns[key]
+                if asyncio.isfuture(value) and (isinstance(value, FuturePromise) or isinstance(value, asyncio.Task)):
+                    # Getters/setters return futures
+                    # They should all be resolved now, so use the result
+                    self.shell.user_ns[key] = value.result()
+            self.results.clear()
+        except Exception as e:
+            self.results.clear()
+            self.abort_all = True
+            self.create_task(self._execute_next_request)
+            raise e
 
     def _callback(self, *args, **kwargs):
         # After each getter/setter resolves check if they've all resolved
         if self.all_getters_resolved:
             self.update_namespace()
+            self.current_request = None
             self.create_task(self.execute_next_request)
 
     def post_run_cell(self, response):

itkwidgets/viewer.py

@@ -8,7 +8,12 @@
 from typing import List, Union, Tuple
 from IPython.display import display, HTML
 from IPython.lib import backgroundjobs as bg
-from ngff_zarr import from_ngff_zarr, to_ngff_image, NgffImage
+from ngff_zarr import (
+    from_ngff_zarr,
+    to_ngff_image,
+    Multiscales,
+    NgffImage
+)
 import uuid
 
 from ._method_types import deferred_methods
@@ -434,6 +439,30 @@ async def get_roi_image(self, scale: int = -1, name: str = 'Image') -> NgffImage
             )
         raise ValueError(f'No image data found for {name}.')
 
+    @fetch_value
+    async def get_roi_multiscale(self, name: str = 'Image') -> Multiscales:
+        """Build and return a new Multiscales NgffImage for the ROI.
+
+        :param name: Name of the loaded image data to use. 'Image', the
+        default, selects the first loaded image.
+        :type name:  str
+
+        :return: roi_multiscales
+        :rtype:  Multiscales NgffImage
+        """
+        if store := self.stores.get(name):
+            multiscales = from_ngff_zarr(store)
+            scales = range(len(multiscales.images))
+            images = [await self.get_roi_image(s) for s in scales]
+            return Multiscales(
+                images=images,
+                metadata=multiscales.metadata,
+                scale_factors=multiscales.scale_factors,
+                method=multiscales.method,
+                chunks=multiscales.chunks
+            )
+        raise ValueError(f'No image data found for {name}.')
+
     @fetch_value
     async def get_roi_region(self):
         """Get the current region of interest in world / physical space.