Add support to download all EEGEyeNet DOTS data.

eoglearn/datasets/eegeyenet.py

@@ -1,35 +1,49 @@
+import pandas as pd
+from pathlib import Path
+
 from .utils import _fetch_dataset
 
-PARAMS = {
-    "EP10_DOTS": list(
-        [
-            dict(
-                url="https://osf.io/download/u2hct/",
-                archive_name="EP10_DOTS1_EEG.mat",
-                folder_name="EEGEYENET-Data/dots/EP10",
-                hash="md5:3e05afdf9c873ac34cb2ffc1141256a3",
-                dataset_name="EEGEYENET",
-            )
-        ]
-    ),
-}
 
-DOTS = {"EP10": PARAMS["EP10_DOTS"]}
+def _get_urls_df():
+    return pd.read_csv(Path(__file__).parent / "eegeyenet_urls.csv")
+
+
+def _get_params(subject, run):
+    df = _get_urls_df()
+    row = df.loc[(df.subject == subject.upper()) & (df.run == int(run))]
+    assert len(row) == 1
+    row = row.T.squeeze()
+    return dict(
+                url=row["url"],
+                archive_name=f"{subject}_DOTS{run}_EEG.mat",
+                folder_name=f"EEGEYENET-Data/dots/{subject}",
+                hash=row["hash"],
+                dataset_name="EEGEYENET")
+
+
+def get_subjects_runs():
+    """Get dictionary of {subject: [lists of runs]}.
+
+    Returns
+    -------
+    dict
+        Dictionary of subjects with the runs as values.
+    """
+    df = _get_urls_df()
+    return {subject: df.run.values[df.subject == subject]
+            for subject in df.subject.unique()}
 
 
-def fetch_eegeyenet(subject="EP10", run=0, fetch_dataset_kwargs=None):
+def fetch_eegeyenet(subject="EP10", run=1, fetch_dataset_kwargs=None):
     """Fetch a sample file from the EEG Eyenet dataset.
 
     Parameters
     ----------
     subject : str
         Subject identifier. Defaults to ``'EP10'``.
     run : int | str
-        Which run to download. Most Participants completed 6 runs of the task, saved
-        to 6 different files. integers are treated as indices, i.e. ``0`` for subject
-        ``"EP10"``corresponds to ``"EP10_DOTS1_EEG.mat"``. If ``str``, it must be the
-        exact filename to download for the ``subject``, ie. ``"EP10_DOTS1_EEG.mat"``.
-        Defaults to ``0``.
+        Which run to download. Most Participants completed 6 runs of the task,
+        saved to 6 different files. Defaults to ``1``.
     fetch_dataset_kwargs : dict | None
         Keyword arguments to pass to :func:`~mne.datasets.fetch_dataset`.
         if ``None``, no keyword arguments are passed. Defaults to ``None``.
@@ -41,13 +55,21 @@ def fetch_eegeyenet(subject="EP10", run=0, fetch_dataset_kwargs=None):
     """
     if not fetch_dataset_kwargs:
         fetch_dataset_kwargs = dict()
-    if isinstance(run, int):
-        dataset_params = DOTS[subject][run]
-    elif isinstance(run, str):
-        run = [run for run in DOTS[subject] if run["archive_name"] == run][0]
-        dataset_params = DOTS[subject][run]
-    else:
-        raise ValueError("run must be an integer or string, not {}".format(type(run)))
-    fetch_dataset_kwargs["dataset_params"] = dataset_params
+    run = int(run)
+    runs = get_subjects_runs()
+    if subject not in runs or run not in runs[subject]:
+        raise ValueError("subject and run not available. See "
+                         "get_subjects_runs() for information on "
+                         "available subjects and runs.")
+
+    fetch_dataset_kwargs["dataset_params"] = _get_params(subject, run)
     fpath = _fetch_dataset(fetch_dataset_kwargs=fetch_dataset_kwargs)
+    fpath = fpath / fetch_dataset_kwargs["dataset_params"]["archive_name"]
+
+    # mne.datasets.fetch_dataset will not download a new run if the subject
+    # folder already exist
+    if not fpath.exists():
+        fetch_dataset_kwargs["force_update"] = True
+        _fetch_dataset(fetch_dataset_kwargs=fetch_dataset_kwargs)
+
     return fpath

eoglearn/datasets/eegeyenet_urls.csv

@@ -0,0 +1,178 @@
+subject,run,url,hash
+EP10,1,https://osf.io/download/u2hct,md5:3e05afdf9c873ac34cb2ffc1141256a3
+EP10,2,https://osf.io/download/28cvb,md5:1bebd24bc8a8eeb4165c44122d1aff8d
+EP10,3,https://osf.io/download/g3cn4,md5:c261df6e43da9122577f580f7df85022
+EP10,4,https://osf.io/download/dy96c,md5:fdddde6fd1b52bc8f6d23c5c1c74687e
+EP10,5,https://osf.io/download/y5sme,md5:1157814a462e4fee47d59782d65261ed
+EP10,6,https://osf.io/download/ktvmp,md5:7bad553a41dcf69b7adca63809a6263d
+EP12,1,https://osf.io/download/9ftm4,md5:39c9ef4d6fc95f6e3b6fd85243b01d18
+EP12,2,https://osf.io/download/28euv,md5:012bc78b849b01c464389292bd242535
+EP12,3,https://osf.io/download/a96qp,md5:0565c68248b8aa8cf5f365bb18bd0732
+EP12,4,https://osf.io/download/7pk6e,md5:114097073449bb4163feff424f62aaf1
+EP12,5,https://osf.io/download/ef52s,md5:92a6781bf181e2c70345bc7a6aae5a1a
+EP12,6,https://osf.io/download/rhzwk,md5:d314b61d48bfcb392d8e1c7d47639e52
+EP14,2,https://osf.io/download/wb4yq,md5:e71bdda1ceae67235e84f146b7c145a3
+EP14,3,https://osf.io/download/fqwzk,md5:0db420dc3528a8864a63a022a8515017
+EP14,4,https://osf.io/download/xedk6,md5:e1680283ee3d2ebd39587088bc4d52e9
+EP14,5,https://osf.io/download/jx9bf,md5:e9bd5ec4bd9a48c0e882169cd00552f8
+EP14,6,https://osf.io/download/84znd,md5:3a6b67f20a6b1d8b6a8ea54b5de78657
+EP18,1,https://osf.io/download/b3skm,md5:4898b1ccc7bbded8c2d958a019d008b3
+EP18,2,https://osf.io/download/fpyd6,md5:910fef853e4c06e19b4ea3e4d08afb56
+EP18,3,https://osf.io/download/8rmqz,md5:f514a43481afd5ddf73edc1fcc2578cc
+EP18,4,https://osf.io/download/tpr6u,md5:9f1e44cffee45a1b444ab79d046d2208
+EP18,5,https://osf.io/download/8s5ng,md5:53c99d608ff38dc2db1505ef9c4ce9fd
+EP18,6,https://osf.io/download/bscqz,md5:422cb0d51e3dc970abe62ce79c55f193
+EP23,1,https://osf.io/download/8qhja,md5:69b8c1ad800a64b96a234a1570be3920
+EP23,2,https://osf.io/download/pqbf5,md5:3ec8b4af142e384a354fba0a19c99155
+EP23,3,https://osf.io/download/wb6r8,md5:164ab01c9e049e26dc3ee18a53ccc37d
+EP23,4,https://osf.io/download/mhcx5,md5:955c00e622bceee53785736b811154c7
+EP23,5,https://osf.io/download/k8vxu,md5:b782743c75b1c787f5c23cee8051b611
+EP23,6,https://osf.io/download/a8bv3,md5:32bc655e75a0cb830b69e2cdb9082ce6
+EP24,1,https://osf.io/download/bk4xy,md5:c725d2bd7ddc5ecc6f50b9b3c72e255e
+EP24,2,https://osf.io/download/qm9db,md5:10c2f75826e70fee72ca8ab039a8ade3
+EP24,3,https://osf.io/download/cbmdz,md5:21b46ae5960c2ed6b94d503483773523
+EP24,4,https://osf.io/download/d9wuc,md5:3c2f327f4225dc8bed79c21a58bab7d5
+EP24,5,https://osf.io/download/qjaf6,md5:13a6873c8242573c885670f865a215f7
+EP24,6,https://osf.io/download/hwp47,md5:7f37ce8f740cc58011e3790efbeb5d52
+EP26,1,https://osf.io/download/6mhyx,md5:a5c35305ca0d80b568ff0811ee4fd0da
+EP26,2,https://osf.io/download/my2e5,md5:c298599cb9b21af7e0110a603aa40cc6
+EP26,3,https://osf.io/download/mt6db,md5:4ce12918693498322106fe68d81413d0
+EP26,4,https://osf.io/download/9mjcr,md5:8f88adac2f4bd42729cd9152350be798
+EP26,5,https://osf.io/download/2kh8e,md5:172a8da7dc76112a14e835ddb26d68a8
+EP26,6,https://osf.io/download/8ajyk,md5:81138616059826b05085e9e1ed6c8996
+EP28,1,https://osf.io/download/72nsb,md5:ce4b98093cf56db3096a080aa117d0cb
+EP28,2,https://osf.io/download/urwt7,md5:ad20689b555bab330842bbdda73bbaa5
+EP28,3,https://osf.io/download/ztqgr,md5:8176300c98a8798f787ce69bad76e0a7
+EP28,4,https://osf.io/download/djw3p,md5:a4a15754678d08768ed1c52d17e08a80
+EP28,5,https://osf.io/download/dxq8j,md5:b89da3e5a5370db0b78aafdb996b43b9
+EP28,6,https://osf.io/download/57qkn,md5:260dd0c87ce3a0f5eb7fb53beabdbc60
+EP29,1,https://osf.io/download/c8kxa,md5:d5f38e30b663eff9ec13c527cb35e27e
+EP29,2,https://osf.io/download/cqebr,md5:f1fb8e8b53e69cfdaaf2d66ae5424338
+EP29,3,https://osf.io/download/3e5k4,md5:8e144c46a461b654e3851b2295df3194
+EP29,4,https://osf.io/download/ps4j7,md5:032925a15aa5d55b5f8e240c4a54f842
+EP29,5,https://osf.io/download/aeb35/,md5:18bb7513a4888c33c14b12b5d33d19b1
+EP29,6,https://osf.io/download/e8xz5/,md5:a648d7131d7a127a06c5944fc7343161
+EP35,1,https://osf.io/download/bek4z,md5:9cd6a0e636c67189bdeb90e5aa72001a
+EP35,2,https://osf.io/download/yr6c3,md5:b88bf71939113d8eedf1317e8804559a
+EP35,3,https://osf.io/download/xqmus,md5:317f5217637ce450fd1324742f369328
+EP35,4,https://osf.io/download/r7cf9/,md5:267419c7929052d9c6ce2aa4a8439258
+EP35,5,https://osf.io/download/z6jp3,md5:832d1c2f3f3e895084052e2f9f6c2810
+EP35,6,https://osf.io/download/72vgs,md5:763773fe1106d85ca9edc90e81ecc8cc
+EP37,1,https://osf.io/download/xm8ne,md5:9253c4d210f522bb6399c885427922aa
+EP37,2,https://osf.io/download/v4acf,md5:2cbc631b48d124f2102e6b69492b7076
+EP37,3,https://osf.io/download/ybuq5,md5:2bc4b19619abf3223617aa2e630f3d55
+EP37,4,https://osf.io/download/p93vy,md5:51ac42e001196f4385d4199770071579
+EP37,5,https://osf.io/download/6r3fw,md5:0afa88c59a2ea03c2ddd82c08f0a6fd9
+EP37,6,https://osf.io/download/jfvcy,md5:c5dbfd2a4e8cf0b6ee01a50bb69fa6ce
+EP39,1,https://osf.io/download/v97f5,md5:3e1450b5bdc1acffbc4c7ebc0271d4b2
+EP39,2,https://osf.io/download/bvmq3,md5:f027b131628e0e475c7131d86d9d75d8
+EP39,3,https://osf.io/download/ahucz,md5:3170ab4b53bc983041b49d9e6267b106
+EP39,4,https://osf.io/download/9dzth,md5:c1e7d99a29e13e5508fad799fa7cfe1e
+EP39,5,https://osf.io/download/qwhcu,md5:5e60bc4a3fe76b9a2abae7225822c2ea
+EP39,6,https://osf.io/download/n5g34,md5:dd99d2d86fd636a0cf20605258d6c2b0
+EP41,1,https://osf.io/download/gxjkd,md5:2666332645f0596003f2fe6f42165f27
+EP41,2,https://osf.io/download/qdb56,md5:8d8999efa0075b63fd9856a3d1dbc3c0
+EP41,4,https://osf.io/download/t2mx5,md5:dd8f256b8baa810adffa2603c8f39fed
+EP41,5,https://osf.io/download/wpcz9,md5:61b9867bc03325af6b5566edba223657
+EP41,6,https://osf.io/download/b3726,md5:e786d137e9e72ea3079223708a1a86cc
+EP46,1,https://osf.io/download/q69b8,md5:c672d91beebbc12a322fb1073fb15d96
+EP46,2,https://osf.io/download/z7enq,md5:d0d73c294002b8e9186f4a92cb3a8393
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+EP46,4,https://osf.io/download/upbn4,md5:aa62d7bd0ddb6f38b69878dd4b23a07f
+EP46,5,https://osf.io/download/j27du,md5:6412d29846ff5b5a50af132ef98bbedd
+EP46,6,https://osf.io/download/a6hwd,md5:9ca89ef40384f3bbcb483113131aed0c
+EP49,1,https://osf.io/download/gnyeq,md5:fc3fff47ecf894509437bb3b439abb1f
+EP49,2,https://osf.io/download/23vyh,md5:fbd7179d8746262e3b9c6ba6af740ee2
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+EP49,4,https://osf.io/download/hg25k,md5:48dde5cbe59ebda4d545b5ac1d051cfd
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