RFC: clean up max projection

1. Remove ImageStack.max_proj.  Steer users towards using Filter.MaxProject.
2. Move the core functionality of max_proj to _max_proj() as it is used commonly in internal code.
3. Refactor ISS notebook to use Filter.MaxProject.

#2 is somewhat debatable.  I feel there is a good case that all internal code that wants to run max_projection should already have been reduced.

Test plan: travis

notebooks/py/ISS.py

@@ -22,6 +22,7 @@
 import pprint
 
 from starfish import data, FieldOfView
+from starfish.image import Filter
 from starfish.types import Features, Axes
 from starfish.util.plot import imshow_plane
 # EPY: END code
@@ -80,13 +81,19 @@
 imshow_plane(single_plane, title="Round: 0, Channel: 0")
 # EPY: END code
 
+# EPY: START code
+# We use a handful of max projections.  Initialize them.
+rcz_max_projection = Filter.MaxProject(dims={Axes.ROUND, Axes.CH, Axes.ZPLANE})
+cz_max_projection = Filter.MaxProject(dims={Axes.CH, Axes.ZPLANE})
+# EPY: END code
+
 # EPY: START markdown
 #'dots' is a general stain for all possible transcripts. This image should correspond to the maximum projcection of all color channels within a single imaging round. This auxiliary image is useful for registering images from multiple imaging rounds to this reference image. We'll see an example of this further on in the notebook
 # EPY: END markdown
 
 # EPY: START code
 dots = fov.get_image("dots")
-dots_single_plane = dots.max_proj(Axes.ROUND, Axes.CH, Axes.ZPLANE)
+dots_single_plane = rcz_max_projection.run(dots)
 imshow_plane(dots_single_plane, title="Anchor channel, all RNA molecules")
 # EPY: END code
 
@@ -96,7 +103,7 @@
 
 # EPY: START code
 nuclei = fov.get_image("nuclei")
-nuclei_single_plane = nuclei.max_proj(Axes.ROUND, Axes.CH, Axes.ZPLANE)
+nuclei_single_plane = rcz_max_projection.run(nuclei)
 imshow_plane(nuclei_single_plane, title="Nuclei (DAPI) channel")
 # EPY: END code
 
@@ -107,8 +114,6 @@
 # EPY: END markdown
 
 # EPY: START code
-from starfish.image import Filter
-
 # filter raw data
 masking_radius = 15
 filt = Filter.WhiteTophat(masking_radius, is_volume=False)
@@ -145,8 +150,9 @@
 # EPY: START code
 from starfish.image import ApplyTransform, LearnTransform
 
+per_round_max_projected = cz_max_projection.run(imgs)
 learn_translation = LearnTransform.Translation(reference_stack=dots, axes=Axes.ROUND, upsampling=1000)
-transforms_list = learn_translation.run(imgs.max_proj(Axes.CH, Axes.ZPLANE))
+transforms_list = learn_translation.run(per_round_max_projected)
 warp = ApplyTransform.Warp()
 registered_imgs = warp.run(filtered_imgs, transforms_list=transforms_list, in_place=False, verbose=True)
 # EPY: END code
@@ -211,12 +217,6 @@
 stain_thresh = .22  # binary mask for overall cells // binarization of stain
 min_dist = 57
 
-registered_mp = registered_imgs.max_proj(Axes.CH, Axes.ZPLANE).xarray.squeeze()
-stain = np.mean(registered_mp, axis=0)
-stain = stain/stain.max()
-nuclei = nuclei.max_proj(Axes.ROUND, Axes.CH, Axes.ZPLANE)
-
-
 seg = Segment.Watershed(
     nuclei_threshold=dapi_thresh,
     input_threshold=stain_thresh,
@@ -255,10 +255,10 @@
 GENE2 = 'VIM'
 
 rgb = np.zeros(registered_imgs.tile_shape + (3,))
-nuclei_mp = nuclei.max_proj(Axes.ROUND, Axes.CH, Axes.ZPLANE)
+nuclei_mp = rcz_max_projection.run(nuclei)
 nuclei_numpy = nuclei_mp._squeezed_numpy(Axes.ROUND, Axes.CH, Axes.ZPLANE)
 rgb[:,:,0] = nuclei_numpy
-dots_mp = dots.max_proj(Axes.ROUND, Axes.CH, Axes.ZPLANE)
+dots_mp = rcz_max_projection.run(dots)
 dots_mp_numpy = dots_mp._squeezed_numpy(Axes.ROUND, Axes.CH, Axes.ZPLANE)
 rgb[:,:,1] = dots_mp_numpy
 do = rgb2gray(rgb)

starfish/core/errors.py

@@ -1,3 +1,10 @@
+class DeprecatedAPIError(Exception):
+    """
+    Raised when using an API that has been deprecated.
+    """
+    pass
+
+
 class DataFormatWarning(Warning):
     """
     Warnings given by starfish when the data is not formatted as expected, though not fatally.

starfish/core/image/_filter/max_proj.py

@@ -1,5 +1,5 @@
 import warnings
-from typing import Iterable, Optional, Union
+from typing import Iterable
 
 from starfish.core.imagestack.imagestack import ImageStack
 from starfish.core.types import Axes
@@ -13,7 +13,7 @@ class MaxProject(FilterAlgorithmBase):
 
     Parameters
     ----------
-    dims : Axes
+    dims : Iterable[Axes]
         one or more Axes to project over
 
     See Also
@@ -22,8 +22,7 @@ class MaxProject(FilterAlgorithmBase):
 
     """
 
-    def __init__(self, dims: Iterable[Union[Axes, str]]) -> None:
-
+    def __init__(self, dims: Iterable[Axes]) -> None:
         warnings.warn(
             "Filter.MaxProject is being deprecated in favor of Filter.Reduce(func='max')",
             DeprecationWarning,
@@ -35,9 +34,7 @@ def __init__(self, dims: Iterable[Union[Axes, str]]) -> None:
     def run(
             self,
             stack: ImageStack,
-            in_place: bool = False,
             verbose: bool = False,
-            n_processes: Optional[int] = None,
             *args,
     ) -> ImageStack:
         """Perform filtering of an image stack
@@ -46,21 +43,16 @@ def run(
         ----------
         stack : ImageStack
             Stack to be filtered.
-        in_place : bool
-            if True, process ImageStack in-place, otherwise return a new stack
         verbose : bool
             if True, report on filtering progress (default = False)
-        n_processes : Optional[int]
-            Number of parallel processes to devote to calculating the filter
 
         Returns
         -------
         ImageStack :
-            If in-place is False, return the results of filter as a new stack. Otherwise return the
-            original stack.
+            The max projection of an image across one or more axis.
 
         """
-        return stack.max_proj(*tuple(Axes(dim) for dim in self.dims))
+        return stack._max_proj(*self.dims)
 
     @staticmethod
     @click.command("MaxProject")
@@ -75,4 +67,5 @@ def run(
              "--dims r --dims c")
     @click.pass_context
     def _cli(ctx, dims):
-        ctx.obj["component"]._cli_run(ctx, MaxProject(dims))
+        formatted_dims = [Axes(dim) for dim in dims]
+        ctx.obj["component"]._cli_run(ctx, MaxProject(formatted_dims))

starfish/core/image/_filter/test/test_api_contract.py

@@ -7,9 +7,7 @@
 - constructor accepts 3d and 2d data, where default is 2d
 - values emitted by a filter are floats between 0 and 1 (inclusive)
 - exposes a `run`() method
-- run accepts an in-place parameter which defaults to True
 - run always returns an ImageStack (if in-place, returns a reference to the modified input data)
-- run accepts an `n_processes` parameter which determines
 - run accepts a `verbose` parameter, which triggers tqdm to print progress
 
 To add a new filter, simply add default

starfish/core/image/_segment/watershed.py

@@ -77,7 +77,7 @@ def run(
         """
 
         # create a 'stain' for segmentation
-        mp = primary_images.max_proj(Axes.CH, Axes.ZPLANE)
+        mp = primary_images._max_proj(Axes.CH, Axes.ZPLANE)
         mp_numpy = mp._squeezed_numpy(Axes.CH, Axes.ZPLANE)
         stain = np.mean(mp_numpy, axis=0)
         stain = stain / stain.max()
@@ -87,7 +87,7 @@ def run(
         disk_size_markers = None
         disk_size_mask = None
 
-        nuclei_mp = nuclei.max_proj(Axes.ROUND, Axes.CH, Axes.ZPLANE)
+        nuclei_mp = nuclei._max_proj(Axes.ROUND, Axes.CH, Axes.ZPLANE)
         nuclei__mp_numpy = nuclei_mp._squeezed_numpy(Axes.ROUND, Axes.CH, Axes.ZPLANE)
         self._segmentation_instance = _WatershedSegmenter(nuclei__mp_numpy, stain)
         label_image = self._segmentation_instance.segment(

starfish/core/imagestack/imagestack.py

@@ -36,7 +36,7 @@
 from tqdm import tqdm
 
 from starfish.core.config import StarfishConfig
-from starfish.core.errors import DataFormatWarning
+from starfish.core.errors import DataFormatWarning, DeprecatedAPIError
 from starfish.core.imagestack import indexing_utils
 from starfish.core.imagestack.parser import TileCollectionData, TileKey
 from starfish.core.imagestack.parser.crop import CropParameters, CroppedTileCollectionData
@@ -1136,6 +1136,9 @@ def tile_opener(tileset_path: Path, tile, ext):
             tile_format=tile_format)
 
     def max_proj(self, *dims: Axes) -> "ImageStack":
+        raise DeprecatedAPIError("Please Filter.MaxProject to do max projection operations.")
+
+    def _max_proj(self, *dims: Axes) -> "ImageStack":
         """return a max projection over one or more axis of the image tensor
 
         Parameters
@@ -1147,9 +1150,8 @@ def max_proj(self, *dims: Axes) -> "ImageStack":
         -------
         np.ndarray :
             max projection
-
         """
-        max_projection = self._data.max([dim.value for dim in dims])
+        max_projection = self.xarray.max([dim.value for dim in dims])
         max_projection = max_projection.expand_dims(tuple(dim.value for dim in dims))
         max_projection = max_projection.transpose(*self.xarray.dims)
         physical_coords: MutableMapping[Coordinates, Sequence[Number]] = {}
@@ -1160,7 +1162,7 @@ def max_proj(self, *dims: Axes) -> "ImageStack":
             if axis in dims:
                 # this axis was projected out of existence.
                 assert coord.value not in max_projection.coords
-                physical_coords[coord] = [np.average(self._data.coords[coord.value])]
+                physical_coords[coord] = [np.average(self.xarray.coords[coord.value])]
             else:
                 physical_coords[coord] = max_projection.coords[coord.value]
         max_proj_stack = ImageStack.from_numpy(max_projection.values, coordinates=physical_coords)

starfish/core/imagestack/test/test_max_proj.py

@@ -4,6 +4,7 @@
 
 from starfish import data
 from starfish.core.types import Axes, PhysicalCoordinateTypes
+from starfish.image import Filter
 from .factories import imagestack_with_coords_factory
 from .imagestack_test_utils import verify_physical_coordinates
 from ..imagestack import ImageStack
@@ -13,8 +14,9 @@ def test_max_projection_preserves_dtype():
     original_dtype = np.float32
     array = np.ones((2, 2, 2), dtype=original_dtype)
     image = ImageStack.from_numpy(array.reshape((1, 1, 2, 2, 2)))
+    max_projector = Filter.MaxProject(dims={Axes.CH, Axes.ROUND, Axes.ZPLANE})
 
-    max_projection = image.max_proj(Axes.CH, Axes.ROUND, Axes.ZPLANE)
+    max_projection = max_projector.run(image)
     assert max_projection.xarray.dtype == original_dtype
 
 
@@ -24,9 +26,11 @@ def test_max_projection_preserves_dtype():
 
 
 def test_max_projection_preserves_coordinates():
+    max_projector = Filter.MaxProject(dims={Axes.CH, Axes.ROUND, Axes.ZPLANE})
+
     e = data.ISS(use_test_data=True)
     nuclei = e.fov().get_image('nuclei')
-    nuclei_proj = nuclei.max_proj(Axes.ROUND, Axes.CH, Axes.ZPLANE)
+    nuclei_proj = max_projector.run(nuclei)
     # Since this data already has only 1 round, 1 ch, 1 zplane
     # let's just assert that the max_proj operation didn't change anything
     assert nuclei.xarray.equals(nuclei_proj.xarray)
@@ -44,6 +48,6 @@ def test_max_projection_preserves_coordinates():
 
     stack = imagestack_with_coords_factory(stack_shape, physical_coords)
 
-    stack_proj = stack.max_proj(Axes.ROUND, Axes.CH, Axes.ZPLANE)
+    stack_proj = max_projector.run(stack)
     expected_z = np.average(Z_COORDS)
     verify_physical_coordinates(stack_proj, X_COORDS, Y_COORDS, expected_z)

starfish/core/spots/_detect_spots/detect.py

@@ -222,7 +222,7 @@ def detect_spots(data_stack: ImageStack,
 
     if reference_image is not None:
         if reference_image_max_projection_axes is not None:
-            reference_image = reference_image.max_proj(*reference_image_max_projection_axes)
+            reference_image = reference_image._max_proj(*reference_image_max_projection_axes)
             data_image = reference_image._squeezed_numpy(*reference_image_max_projection_axes)
         else:
             data_image = reference_image.xarray