update examples

examples/hcs_zarr.py

@@ -4,73 +4,55 @@
 # and adds an extra well-position to an existing dataset.
 # It can be run as a plain Python script, or as interactive cells in some IDEs.
 
+import os
+
 import numpy as np
 
-from iohub.ngff import HCSZarr
+from iohub.ngff import open_ome_zarr
 
-import os
+# %%
+# Set storage path
+
+store_path = f'{os.path.expanduser("~/")}hcs.zarr'
 
 # %%
-# Write 5D data to multiple wells
+# Write 5D data to multiple wells.
+# While the NGFF specification allows for arbitrary names,
+# the ome-zarr-py library (thus the napari-ome-zarr plugin)
+# only load positions and arrays with name '0'.
 
 position_list = (
     ("A", "1", "0"),
     ("H", 10, 0),
     ("Control", "Blank", 0),
 )
 
-file_path = f'{os.path.expanduser("~/")}hcs.zarr'
-
-with HCSZarr.open(
-    file_path, mode="a", channel_names=["DAPI", "GFP", "Brightfield"]
-) as dataset:
-    for row, col, fov in position_list:
-        position = dataset.create_position(row, col, fov)
-        position["raw"] = np.random.randint(
-            0, np.iinfo(np.uint16).max, size=(5, 3, 2, 32, 32), dtype=np.uint16
-        )
-# "raw" is the custom name for the array in the OME-Zarr file.
-# The default name is "0".
-# Dragging above hcs.zarr into napari-ome-zarr doesn't load the array,
-# since the plugin expects the array name to default to "0" .
-# The following zarr will open with each position shown as a tile:
-
-file_path = f'{os.path.expanduser("~/")}hcs_default.zarr'
-
-with HCSZarr.open(
-    file_path, mode="a", channel_names=["DAPI", "GFP", "Brightfield"]
+with open_ome_zarr(
+    store_path,
+    layout="hcs",
+    mode="a",
+    channel_names=["DAPI", "GFP", "Brightfield"],
 ) as dataset:
+    # create and write to positions
     for row, col, fov in position_list:
         position = dataset.create_position(row, col, fov)
         position["0"] = np.random.randint(
             0, np.iinfo(np.uint16).max, size=(5, 3, 2, 32, 32), dtype=np.uint16
         )
-
-# Examine the shape, size, dtype, and chunks of the array at a position.
-print(f'Array 0 @ Well A1, FOV 0:\n'
-      f'shape:{dataset["A"]["1"]["0"]["0"].shape}\n'
-      f'size:{dataset["A"]["1"]["0"]["0"].size}\n'
-      f'dtype:{dataset["A"]["1"]["0"]["0"].dtype}\n'
-      f'chunks:{dataset["A"]["1"]["0"]["0"].chunks}\n')
+    # print dataset summary
+    dataset.print_tree()
 
 # %%
 # Append a channel to all the positions
 
-file_path = f'{os.path.expanduser("~/")}hcs_default.zarr'
-
-with HCSZarr.open(file_path, mode="r+") as dataset:
+with open_ome_zarr(store_path, mode="r+") as dataset:
     for name, position in dataset.positions():
-        print(name)
+        print(f"Appending a channel to position: {name}")
         position.append_channel("Segmentation", resize_arrays=True)
-        position['0'][:, 3] = np.random.randint(
+        position["0"][:, 3] = np.random.randint(
             0, np.iinfo(np.uint16).max, size=(5, 2, 32, 32), dtype=np.uint16
         )
-
-print(f'Array 0 @ Well A1, FOV 0:\n'
-      f'shape:{dataset["A"]["1"]["0"]["0"].shape}\n'
-      f'size:{dataset["A"]["1"]["0"]["0"].size}\n'
-      f'dtype:{dataset["A"]["1"]["0"]["0"].dtype}\n'
-      f'chunks:{dataset["A"]["1"]["0"]["0"].chunks}\n')
+    dataset.print_tree()
 
 # %%
 # Try viewing the images with napari-ome-zarr

examples/ome_zarr.py

@@ -8,7 +8,7 @@
 
 import numpy as np
 
-from iohub.ngff import OMEZarrFOV
+from iohub.ngff import open_ome_zarr
 
 # %%
 # Write 5D data to a new Zarr store
@@ -17,16 +17,17 @@
     0, np.iinfo(np.uint16).max, size=(5, 2, 3, 32, 32), dtype=np.uint16
 )
 
-with OMEZarrFOV.open(
-    "ome.zarr", mode="a", channel_names=["DAPI", "GFP"]
+with open_ome_zarr(
+    "ome.zarr", layout="fov", mode="a", channel_names=["DAPI", "GFP"]
 ) as dataset:
     dataset["0"] = tczyx
 
 # %%
 # Opening in read-only mode prevents writing
 
-with OMEZarrFOV.open("ome.zarr", mode="r") as dataset:
+with open_ome_zarr("ome.zarr", layout="auto", mode="r") as dataset:
     img = dataset["0"]
+    print(img)
     print(img.numpy())
     try:
         img[0, 0, 0, 0, 0] = 0
@@ -40,7 +41,7 @@
     0, np.iinfo(np.uint16).max, size=(1, 2, 3, 32, 32), dtype=np.uint16
 )
 
-with OMEZarrFOV.open("ome.zarr", mode="r+") as dataset:
+with open_ome_zarr("ome.zarr", layout="fov", mode="r+") as dataset:
     img = dataset["0"]
     print(img.shape)
     img.append(new_1czyx, axis=0)
@@ -53,7 +54,7 @@
     0, np.iinfo(np.uint16).max, size=(3, 32, 32), dtype=np.uint16
 )
 
-dataset = OMEZarrFOV.open("ome.zarr", mode="r+")
+dataset = open_ome_zarr("ome.zarr", mode="r+")
 dataset.append_channel("New", resize_arrays=True)
 dataset["0"][0, 2] = new_zyx
 dataset.close()