add example

ceed.py

@@ -50,7 +50,7 @@ _LICENSE = ""
 # TODO: Add link to the official dataset URLs here
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
-_REPO_NC = ("https://huggingface.co/datasets/AI4EPS/quakeflow_nc/resolve/main/waveform_h5",)
+_REPO_NC = "https://huggingface.co/datasets/AI4EPS/quakeflow_nc/resolve/main/waveform_h5"
 _FILES_NC = [
     "1987.h5",
     "1988.h5",

example.py

@@ -0,0 +1,41 @@
+# %%
+import numpy as np
+from datasets import load_dataset
+from torch.utils.data import DataLoader
+
+# %%
+ceed = load_dataset(
+    "./ceed.py",
+    name="station_test",
+    # name="event_test",
+    split="test",
+    download_mode="force_redownload",
+)
+
+# print the first sample of the iterable dataset
+for example in ceed:
+    print("\nIterable test\n")
+    print(example.keys())
+    for key in example.keys():
+        if key == "data":
+            print(key, np.array(example[key]).shape)
+        else:
+            print(key, example[key])
+    break
+
+# %%
+ceed = ceed.with_format("torch")
+dataloader = DataLoader(ceed, batch_size=8, num_workers=0, collate_fn=lambda x: x)
+
+for batch in dataloader:
+    print("\nDataloader test\n")
+    print(f"Batch size: {len(batch)}")
+    print(batch[0].keys())
+    for key in batch[0].keys():
+        if key == "data":
+            print(key, np.array(batch[0][key]).shape)
+        else:
+            print(key, batch[0][key])
+    break
+
+# %%