Minor additions/typos

Author: jluethi

docs/image_list.md

@@ -34,10 +34,12 @@ Before running a given task, Fractal prepares an appropriate image list by extra
 The set of type filters to be applied before running a task is obtained by combining these sources:
 
 1. The dataset may have `type_filters` set - this is the source with lowest priority.
+    * Example: A prior workflow ran and set [output filters](#output-filters) of `type_filters = {"is_3D": False}"`. These output filters were added to the dataset when the prior workflow finished.
     * Example: I manually set `type_filters = {"illumination_corrected": False}"` through Fractal, by modifying the dataset, because I want to process raw images.
-2. The manifest of a tasks package may specify that a task has some required `input_types` (e.g. a projection task may have `input_types = {"is_3D": True}`), which are used as filters.
+2. The manifest of a tasks package may specify that a task has some required `input_types`, which are used as filters.
+    * Example: An "Project Image (HCS Plate)" task with `input_types={"is_3D": True}`, meaning that it cannot run on images with type `is_3D=False`.
     * Example: An "Illumination correction" task with `input_types={"illumination_corrected": False}`, meaning that it cannot run on images with type `illumination_correction=True`.
-    * Example: Am "Apply Registration to Image" task with `input_types={"registered": False}`, meaning that it cannot run on images with type `registered=True`.
+    * Example: An "Apply Registration to Image" task with `input_types={"registered": False}`, meaning that it cannot run on images with type `registered=True`.
 3. For a task within a workflow, it is possible to specify some additional `type_filters`.
     * Example: I may need a workflow that includes a 3D->2D projection task but then switches back to 3D images in a later task. I can achieve this by setting `type_filters = {"is_3D": True}` for the relevant task, so that from this task onwards the 3D images are processed (and not the 2D ones).
 
@@ -47,12 +49,12 @@ The task manifest may include the `output_types` property for a specific task. I
 
 Examples:
 
-* A 3D->2D projection task typically has `output_types = {"is_3D": False}`: from this task onwards, the 2D images are processed (not the raw 3D images).
-* An illumination-correction task would have `output_types = {"illumination_corrected": True}`: from this task onwards, the registered images are processed (not the raw images).
+* A 3D->2D projection task typically has `output_types = {"is_3D": False}`: from this task onwards, the 2D images are processed (not the raw 3D images). And the images generated by this task have their type set to `"is_3D": False`.
+* An illumination-correction task would have `output_types = {"illumination_corrected": True}`: from this task onwards, the illumination corrected images are processed (not the raw images). And the images generated by this task have their type set to `"illumination_corrected": True`.
 
 ### Attribute filters
 
-The set of attribute filters to be applied before running a task is defined upon submission of a job, and they do not change during the job execution. These filters offer a way to process a subset of the whole dataset (e.g. only a few wells rather than the whole plate, or only a given multiplexing acquisition cycle).
+The set of attribute filters to be applied before running a task is defined upon submission of a job, and they do not change during the job execution. These filters offer a way to process a subset of the whole dataset (e.g. only a few wells rather than the whole plate, or only a given multiplexing acquisition cycle). In Fractal web, the "Continue Workflow" dialogue is prepopulated with the attribute filters from the dataset (if any are set), but users are able to change the attribute filters to any setting they want.
 
 
 ## Examples

docs/tasks_spec.md

@@ -111,7 +111,7 @@ Tasks can optionally return updates to the image list (this is true for all task
 
 For tasks that create new images or edit relevant image properties, `task_output` must include an `image_list_updates` property so the server can update its metadata about that image.
 
-> NOTE: if both `image_list_updates` and `image_list_removals` are empty, in the task output, then `fractal-server` includes all the filtered image list into `image_list_updates`, so that they are updated with the appropriate `types` (see also [the image-list page](./image_list.md#image-types)).
+> NOTE: if both `image_list_updates` and `image_list_removals` are empty in the task output, then `fractal-server` includes all the filtered image list into `image_list_updates`, so that they are updated with the appropriate `types` (see also [the image-list page](./image_list.md#image-types)).
 
 Task outputs with image list updates are returned as a dictionary that contains the `image_list_updates` key and a list containing the updates to individual images. The updates need to be for unique `zarr_url`s and each update needs to contain the `zarr_url` of the image it’s providing an update for. Additionally, they can provide an `origin` key, an `attributes` key and a `types` key. The `origin` key describes the `zarr_url` of another image already in the image list and will take the existing attributes and types from that image. Attributes and types can also be directly set by a task.