Use dtype from SlideData constructor

pathml/core/h5managers.py

@@ -15,12 +15,12 @@
 import pathml.core
 import pathml.core.masks
 import pathml.core.tile
-from pathml.core.utils import readcounts
+from pathml.core.utils import readcounts, get_tiles_dtype
 
 
 class h5pathManager:
  """
- Interface between slidedata object and data management on disk by h5py.
+ Interface between SlideData object and data management on disk by h5py.
  """
 
  def __init__(self, h5path=None, slidedata=None):
@@ -50,9 +50,12 @@ def __init__(self, h5path=None, slidedata=None):
  self.counts.filename = (
  str(self.countspath.name) + "/tmpfile.h5ad"
  )
+ # Default to float16 if there are no tiles
+ self.dtype = get_tiles_dtype(h5path) or np.dtype('float16')
 
  else:
  assert slidedata, f"must pass slidedata object to create h5path"
+ self.dtype = slidedata.dtype
  # initialize h5path file hierarchy
  # fields
  fieldsgroup = self.h5.create_group("fields")
@@ -137,7 +140,7 @@ def add_tile(self, tile):
  compression="gzip",
  compression_opts=5,
  shuffle=True,
- dtype="float16",
+ dtype=self.dtype,
  )
 
  # save tile_shape as an attribute to enforce consistency

pathml/core/slide_data.py

@@ -14,6 +14,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import pathml.core
+from pathml.core.utils import get_tiles_dtype
 import pathml.preprocessing.pipeline
 from pathml.core.slide_types import SlideType
 
@@ -73,6 +74,7 @@ class SlideData:
  time_series (bool, optional): Flag indicating whether the image is a time series.
  Defaults to ``None``. Ignored if ``slide_type`` is specified.
  counts (anndata.AnnData): object containing counts matrix associated with image quantification
+ dtype (np.dtype): datatype for image storage
  """
 
  def __init__(
@@ -176,11 +178,15 @@ def __init__(
  self.name = name
  self.labels = labels
  self.slide_type = slide_type
+ self.dtype = np.dtype('float16') if dtype is None else np.dtype(dtype)
 
  if _load_from_h5path:
  # populate the SlideData object from existing h5path file
  with h5py.File(filepath, "r") as f:
  self.h5manager = pathml.core.h5managers.h5pathManager(h5path=f)
+ self.dtype = get_tiles_dtype(f)
+ if dtype != self.dtype and dtype is not None:
+ logger.info(f"using dtype {self.dtype} from h5path instead of {dtype}")
  self.name = self.h5manager.h5["fields"].attrs["name"]
  self.labels = {
  key: val
@@ -211,6 +217,7 @@ def __repr__(self):
  if self.backend:
  out.append(f"backend={repr(self.backend)}")
  out.append(f"image shape: {self.shape}")
+ out.append(f"image dtype: {self.dtype}")
  try:
  nlevels = self.slide.level_count
  except:

pathml/core/utils.py

@@ -11,8 +11,6 @@
 import anndata
 import h5py
 import numpy as np
-import pathml.core.slide_backends
-import pathml.core.slide_data
 
 
 # TODO: Fletcher32 checksum?
@@ -115,3 +113,22 @@ def readcounts(h5):
  for ds in h5.keys():
  h5.copy(ds, f)
  return anndata.read_h5ad(path.name)
+
+def get_tiles_dtype(h5):
+ """
+ Returns the dtype of tile images in h5path file.
+
+ Returns:
+ np.dtype or None if no tiles in file
+ """
+ # Check that all tiles have the same dtype as the first tile
+ dtype = None
+ for tile in h5["tiles"]:
+ tile_dtype = h5["tiles"][tile]['array'].dtype
+ if dtype is None:
+ dtype = tile_dtype
+ assert (
+ dtype == tile_dtype,
+ f"all tiles must have the same dtype. Tile {tile} has dtype {tile_dtype} instead of {dtype}"
+ )
+ return dtype

tests/core_tests/test_h5managers.py

@@ -44,16 +44,25 @@ def test_h5manager2(tileHE):
 
 
 def test_tile_dtype_HE(tileHE):
- """make sure that retrieved tiles and corresponding masks are float16"""
+ """Test that tiles have default float16 dtype and masks are bool"""
  slidedata = HESlide("tests/testdata/small_HE.svs")
  slidedata.tiles.add(tileHE)
  tile_retrieved = slidedata.tiles[tileHE.coords]
  assert tile_retrieved.image.dtype == np.float16
  assert tile_retrieved.masks["testmask"].dtype == bool
 
+def test_tile_dtype_HE_uint8(tileHE):
+ """Test that tiles have modified uint8 dtype and masks are bool"""
+ slidedata = HESlide("tests/testdata/small_HE.svs", dtype=np.dtype('uint8'))
+ slidedata.tiles.add(tileHE)
+ tile_retrieved = slidedata.tiles[tileHE.coords]
+ import pdb; pdb.set_trace()
+ assert tile_retrieved.image.dtype == np.uint8
+ assert tile_retrieved.masks["testmask"].dtype == bool
+
 
 def test_tile_dtype_IF(tileVectra, vectra_slide):
- """make sure that retrieved tiles and corresponding masks are float16"""
+ """Test that tiles have float16 dtype and masks have bool dtype."""
  vectra_slide.tiles.add(tileVectra)
  tile_retrieved = vectra_slide.tiles[tileVectra.coords]
  assert tile_retrieved.image.dtype == np.float16