Test RawDataset with refactored code

.gitattributes

@@ -57,3 +57,13 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.0 filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.1 filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.2 filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.3 filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.4 filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.5 filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.6 filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.7 filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.8 filter=lfs diff=lfs merge=lfs -text
+dataset.zarr/recording_0/data/0.9 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,68 @@
+---
+tags:
+- braindecode
+- eeg
+- neuroscience
+- brain-computer-interface
+license: unknown
+---
+
+# EEG Dataset
+
+This dataset was created using [braindecode](https://braindecode.org), a library for deep learning with EEG/MEG/ECoG signals.
+
+## Dataset Information
+
+- **Number of recordings**: 1
+- **Number of channels**: 26
+- **Sampling frequency**: 250.0 Hz
+- **Data type**: Continuous (Raw)
+- **Number of windows**: 96735
+- **Total size**: 19.23 MB
+- **Storage format**: zarr
+
+## Usage
+
+To load this dataset:
+
+```python
+from braindecode.datasets import BaseConcatDataset
+
+# Load dataset from Hugging Face Hub
+dataset = BaseConcatDataset.from_pretrained("username/dataset-name")
+
+# Access data
+X, y, metainfo = dataset[0]
+# X: EEG data (n_channels, n_times)
+# y: label/target
+# metainfo: window indices
+```
+
+## Using with PyTorch DataLoader
+
+```python
+from torch.utils.data import DataLoader
+
+# Create DataLoader for training
+train_loader = DataLoader(
+    dataset,
+    batch_size=32,
+    shuffle=True,
+    num_workers=4
+)
+
+# Training loop
+for X, y, _ in train_loader:
+    # X shape: [batch_size, n_channels, n_times]
+    # y shape: [batch_size]
+    # Process your batch...
+```
+
+## Dataset Format
+
+This dataset is stored in **Zarr** format, optimized for:
+- Fast random access during training (critical for PyTorch DataLoader)
+- Efficient compression with blosc
+- Cloud-native storage compatibility
+
+For more information about braindecode, visit: https://braindecode.org

dataset.zarr/.zattrs

@@ -0,0 +1,5 @@
+{
+    "braindecode_version": "1.0",
+    "dataset_type": "RawDataset",
+    "n_datasets": 1
+}

dataset.zarr/.zgroup

@@ -0,0 +1,3 @@
+{
+    "zarr_format": 2
+}

dataset.zarr/recording_0/.zattrs

@@ -0,0 +1,4 @@
+{
+    "description": "{\"subject\":1,\"session\":\"0train\",\"run\":\"0\"}",
+    "info": "{\"ch_names\": [\"Fz\", \"FC3\", \"FC1\", \"FCz\", \"FC2\", \"FC4\", \"C5\", \"C3\", \"C1\", \"Cz\", \"C2\", \"C4\", \"C6\", \"CP3\", \"CP1\", \"CPz\", \"CP2\", \"CP4\", \"P1\", \"Pz\", \"P2\", \"POz\", \"EOG1\", \"EOG2\", \"EOG3\", \"stim\"], \"sfreq\": 250.0, \"ch_types\": [\"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eeg\", \"eog\", \"eog\", \"eog\", \"stim\"], \"lowpass\": 125.0, \"highpass\": 0.0}"
+}

dataset.zarr/recording_0/.zgroup

@@ -0,0 +1,3 @@
+{
+    "zarr_format": 2
+}

dataset.zarr/recording_0/data/.zarray

@@ -0,0 +1,22 @@
+{
+    "chunks": [
+        26,
+        10000
+    ],
+    "compressor": {
+        "blocksize": 0,
+        "clevel": 5,
+        "cname": "zstd",
+        "id": "blosc",
+        "shuffle": 1
+    },
+    "dtype": "<f4",
+    "fill_value": 0.0,
+    "filters": null,
+    "order": "C",
+    "shape": [
+        26,
+        96735
+    ],
+    "zarr_format": 2
+}

dataset.zarr/recording_0/data/0.0

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f0d416ee3e6b778ab8b42529aee9bf920750744abdad277920b29b2be0930ca8
+size 772956

dataset.zarr/recording_0/data/0.1

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:60e0a401f4b5c8eb2078ca2c7200c3b1f924302b71ee4872b5590c5b98e0ac29
+size 772139

dataset.zarr/recording_0/data/0.2

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:46b6924f76115e45061fff393e667e994b60f74ff4eeea71b0a956ab1755cefb
+size 772348

dataset.zarr/recording_0/data/0.3

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b3e685e3e0830c7399fd20d234bc3830f02969da7d3529ff6d20a7dde7db1fd6
+size 774500

dataset.zarr/recording_0/data/0.4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9e82e5adea4c1eb2c353f439667bc66f25e62061383d45a123929e039892e4b2
+size 778745

dataset.zarr/recording_0/data/0.5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1e1205f9a26dc6b754e7a2634894a61fe94c530024a219469cc8fece5c6dc283
+size 776102

dataset.zarr/recording_0/data/0.6

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:75a1e302a9076977ce79646851704334e2a8847905f156a5338573ba1a2cda1b
+size 774672

dataset.zarr/recording_0/data/0.7

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6f0a52d770b1e4794ef6ba47f1ea22036f2412861d85ff465668c3748f10d3ac
+size 776431

dataset.zarr/recording_0/data/0.8

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:755ccafd06f815aa293bacc10c730b1a2a0fb56cfdd036128a02e78fedb5acca
+size 775441

dataset.zarr/recording_0/data/0.9

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3ed692e5817a09f5c0bc28b88789a61dd8a63d26fb66002881e02c1be202b01a
+size 527352

format_info.json

@@ -0,0 +1,9 @@
+{
+  "format": "zarr",
+  "compression": "blosc",
+  "compression_level": 5,
+  "braindecode_version": "1.3.0",
+  "n_recordings": 1,
+  "total_samples": 96735,
+  "total_size_mb": 19.23
+}