added datasets for nb4

ark_example.py

@@ -48,22 +48,29 @@ _URL_DATA = {
     "image_data": "./data/image_data.zip",
     "cell_table": "./data/segmentation/cell_table.zip",
     "deepcell_output": "./data/segmentation/deepcell_output.zip",
-    "example_pixel_output_dir": "./data/segmentation/example_pixel_output_dir.zip"
+    "example_pixel_output_dir": "./data/segmentation/example_pixel_output_dir.zip",
+    "example_cell_output_dir": "./data/segmentation/example_cell_output_dir.zip",
 }
 
 _URL_DATASET_CONFIGS = {
-    "nb1": {"image_data": _URL_DATA["image_data"]},
-    "nb2": {
+    "segment_image_data": {"image_data": _URL_DATA["image_data"]},
+    "cluster_pixels": {
         "image_data": _URL_DATA["image_data"],
         "cell_table": _URL_DATA["cell_table"],
         "deepcell_output": _URL_DATA["deepcell_output"],
     },
-    "nb3": {
+    "cluster_cells": {
         "image_data": _URL_DATA["image_data"],
         "cell_table": _URL_DATA["cell_table"],
         "deepcell_output": _URL_DATA["deepcell_output"],
-        "example_pixel_output_dir": _URL_DATA["example_pixel_output_dir"]
-    }
+        "example_pixel_output_dir": _URL_DATA["example_pixel_output_dir"],
+    },
+    "post_clustering": {
+        "image_data": _URL_DATA["image_data"],
+        "cell_table": _URL_DATA["cell_table"],
+        "deepcell_output": _URL_DATA["deepcell_output"],
+        "example_cell_output_dir": _URL_DATA["example_cell_output_dir"],
+    },
 }
 
 
@@ -87,7 +94,7 @@ TMA24_R9C1 -> fov10
 class ArkExample(datasets.GeneratorBasedBuilder):
     """The Dataset consists of 11 FOVs"""
 
-    VERSION = datasets.Version("0.0.2")
+    VERSION = datasets.Version("0.0.3")
 
     # This is an example of a dataset with multiple configurations.
     # If you don't want/need to define several sub-sets in your dataset,
@@ -98,35 +105,47 @@ class ArkExample(datasets.GeneratorBasedBuilder):
     # BUILDER_CONFIG_CLASS = MyBuilderConfig
 
     # You will be able to load one or the other configurations in the following list with
-    # data = datasets.load_dataset('my_dataset', 'nb1')
-    # data = datasets.load_dataset('my_dataset', 'nb2')
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(
-            name="nb1",
+            name="segment_image_data",
             version=VERSION,
-            description="This dataset contains only the 12 FOVs, and their 22 channels.",
+            description="This configuration contains data used by notebook 1; contains only the 12 FOVs, and their 22 channels.",
         ),
         datasets.BuilderConfig(
-            name="nb2",
+            name="cluster_pixels",
             version=VERSION,
-            description="This dataset is a superset of the nb1 and contains data from notebook 1 in order to start with notebook 2. \
-                Therefore you can start at any notebook with this dataset.",
+            description="This configuration contains data used by notebook 2, Pixel Clustering (Pixie Pipeline #1).",
         ),
         datasets.BuilderConfig(
-            name="nb3",
+            name="cluster_cells",
             version=VERSION,
-            description="This dataset contains pixel data generated from Notebook 2 in the Pixie pipeline."
-        )
+            description="This configuration contains data used by notebook 3, Cell Clustering (Pixie Pipeline #2).",
+        ),
+        datasets.BuilderConfig(
+            name="post_clustering",
+            version=VERSION,
+            description="This configuration contains data used by notebook 4 - Post Clustering.",
+        ),
     ]
 
     def _info(self):
         # This is the name of the configuration selected in BUILDER_CONFIGS above
-        if self.config.name in ["nb1", "nb2", "nb3", "nb4"]:
+        if self.config.name in [
+            "segment_image_data",
+            "cluster_pixels",
+            "cluster_cells",
+            "post_clustering",
+        ]:
             features = datasets.Features(
-                {f: datasets.Value("string") for f in _URL_DATASET_CONFIGS[self.config.name].keys()}
+                {
+                    f: datasets.Value("string")
+                    for f in _URL_DATASET_CONFIGS[self.config.name].keys()
+                }
             )
         else:
-            ValueError("dataset name is incorrect.")
+            ValueError(
+                f"Dataset name is incorrect, options include {list(_URL_DATASET_CONFIGS.keys())}"
+            )
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
             description=_DESCRIPTION,

data/segmentation/example_cell_output_dir.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ad78b0f72ede2eeaa05f5befb1f556a86f667a7dcdc31d5f5dc45cc1d933884f
+size 4197412