{"action":"created","comment":{"url":"https://api.github.com/repos/mne-tools/mne-python/pulls/comments/47428688","id":47428688,"diff_hunk":"@@ -0,0 +1,374 @@\n+# Author: Mainak Jas <mainak.jas@telecom-paristech.fr>\n+#\n+# License: BSD (3-clause)\n+\n+import os.path as op\n+import numpy as np\n+import warnings\n+\n+from ...utils import logger, verbose\n+from ..utils import _read_segments_file\n+from ..meas_info import _empty_info, create_info\n+from ..base import _BaseRaw, _check_update_montage\n+from ..constants import FIFF\n+from ...channels.montage import Montage\n+from ...epochs import _BaseEpochs\n+from ...event import read_events\n+from ...externals.six import string_types\n+\n+\n+def _get_info(eeg, montage, eog=None):\n+    \"\"\"Get measurement info.\n+    \"\"\"\n+    info = _empty_info(sfreq=eeg.srate)\n+    info['nchan'] = eeg.nbchan\n+\n+    # add the ch_names and info['chs'][idx]['loc']\n+    path = None\n+    if len(eeg.chanlocs) > 0:\n+        ch_names, pos = [], []\n+        kind = 'user_defined'\n+        selection = np.arange(len(eeg.chanlocs))\n+        locs_available = True\n+        for chanloc in eeg.chanlocs:\n+            ch_names.append(chanloc.labels)\n+            loc_x = chanloc.X if len(chanloc.X) > 0 else 0.\n+            loc_y = chanloc.Y if len(chanloc.Y) > 0 else 0.\n+            loc_z = chanloc.Z if len(chanloc.Z) > 0 else 0.\n+            locs = np.r_[loc_x, loc_y, loc_z]\n+            if np.unique(locs).size == 1:\n+                locs_available = False\n+                break\n+            pos.append(locs)\n+        if locs_available:\n+            montage = Montage(np.array(pos), ch_names, kind, selection)\n+    elif isinstance(montage, string_types):\n+        path = op.dirname(montage)\n+\n+    if montage is None:\n+        info = create_info(ch_names, eeg.srate)\n+    else:\n+        _check_update_montage(info, montage, path=path,\n+                              update_ch_names=True)\n+\n+    info['buffer_size_sec'] = 1.  # reasonable default\n+    # update the info dict\n+    cal = 1e-6\n+    if eog is None:\n+        eog = []\n+    for ch in info['chs']:\n+        ch['cal'] = cal\n+        if ch['ch_name'].startswith('EOG') or ch['ch_name'] in eog:\n+            ch['coil_type'] = FIFF.FIFFV_COIL_NONE\n+            ch['kind'] = FIFF.FIFFV_EOG_CH\n+\n+    return info\n+\n+\n+def read_raw_eeglab(input_fname, montage=None, eog=None, preload=False,\n+                    verbose=None):\n+    \"\"\"Read an EEGLAB .set file\n+\n+    Parameters\n+    ----------\n+    input_fname : str\n+        Path to the .set file. If the data is stored in a separate .fdt file,\n+        it is expected to be in the same folder as the .set file.\n+    montage : str | None | instance of montage\n+        Path or instance of montage containing electrode positions.\n+        If None, sensor locations are (0,0,0). See the documentation of\n+        :func:`mne.channels.read_montage` for more information.\n+    eog : list or tuple\n+        Names of channels or list of indices that should be designated\n+        EOG channels. If None (default), the channel names beginning with\n+        ``EOG`` are used.\n+    preload : bool or str (default False)\n+        Preload data into memory for data manipulation and faster indexing.\n+        If True, the data will be preloaded into memory (fast, requires\n+        large amount of memory). If preload is a string, preload is the\n+        file name of a memory-mapped file which is used to store the data\n+        on the hard drive (slower, requires less memory). Note that\n+        preload=False will be effective only if the data is stored in a\n+        separate binary file.\n+    verbose : bool, str, int, or None\n+        If not None, override default verbose level (see mne.verbose).\n+\n+    Returns\n+    -------\n+    raw : Instance of RawEEGLAB\n+        A Raw object containing EEGLAB .set data.\n+\n+    Notes\n+    -----\n+    .. versionadded:: 0.11.0\n+\n+    See Also\n+    --------\n+    mne.io.Raw : Documentation of attribute and methods.\n+    \"\"\"\n+    return RawEEGLAB(input_fname=input_fname, montage=montage, eog=eog,\n+                     preload=preload, verbose=verbose)\n+\n+\n+def read_epochs_eeglab(input_fname, events=None, event_id=None, montage=None,\n+                       verbose=None):\n+    \"\"\"Reader function for EEGLAB epochs files\n+\n+    Parameters\n+    ----------\n+    input_fname : str\n+        Path to the .set file. If the data is stored in a separate .fdt file,\n+        it is expected to be in the same folder as the .set file.\n+    events : str | array, shape (n_events, 3) | None\n+        Path to events file. If array, it is the events typically returned\n+        by the read_events function. If some events don't match the events\n+        of interest as specified by event_id, they will be marked as 'IGNORED'\n+        in the drop log. If None, it is constructed from the EEGLAB (.set) file\n+        with each unique event encoded with a different integer.\n+    event_id : int | list of int | dict | None\n+        The id of the event to consider. If dict,\n+        the keys can later be used to acces associated events. Example:\n+        dict(auditory=1, visual=3). If int, a dict will be created with\n+        the id as string. If a list, all events with the IDs specified\n+        in the list are used. If None, the event_id is constructed from the\n+        EEGLAB (.set) file with each descriptions copied from `eventtype`.\n+    montage : str | None | instance of montage\n+        Path or instance of montage containing electrode positions.\n+        If None, sensor locations are (0,0,0). See the documentation of\n+        :func:`mne.channels.read_montage` for more information.\n+    verbose : bool, str, int, or None\n+        If not None, override default verbose level (see mne.verbose).\n+\n+    Returns\n+    -------\n+    epochs : instance of Epochs\n+        The epochs.\n+\n+    Notes\n+    -----\n+    .. versionadded:: 0.11.0\n+\n+\n+    See Also\n+    --------\n+    mne.Epochs : Documentation of attribute and methods.\n+    \"\"\"\n+    epochs = EpochsEEGLAB(input_fname=input_fname, events=events,\n+                          event_id=event_id, montage=montage, verbose=verbose)\n+    return epochs\n+\n+\n+class RawEEGLAB(_BaseRaw):\n+    \"\"\"Raw object from EEGLAB .set file.\n+\n+    Parameters\n+    ----------\n+    input_fname : str\n+        Path to the .set file. If the data is stored in a separate .fdt file,\n+        it is expected to be in the same folder as the .set file.\n+    montage : str | None | instance of montage\n+        Path or instance of montage containing electrode positions.\n+        If None, sensor locations are (0,0,0). See the documentation of\n+        :func:`mne.channels.read_montage` for more information.\n+    eog : list or tuple\n+        Names of channels or list of indices that should be designated\n+        EOG channels. If None (default), the channel names beginning with\n+        ``EOG`` are used.\n+    preload : bool or str (default False)\n+        Preload data into memory for data manipulation and faster indexing.\n+        If True, the data will be preloaded into memory (fast, requires\n+        large amount of memory). If preload is a string, preload is the\n+        file name of a memory-mapped file which is used to store the data\n+        on the hard drive (slower, requires less memory).\n+    verbose : bool, str, int, or None\n+        If not None, override default verbose level (see mne.verbose).\n+\n+    Returns\n+    -------\n+    raw : Instance of RawEEGLAB\n+        A Raw object containing EEGLAB .set data.\n+\n+    Notes\n+    -----\n+    .. versionadded:: 0.11.0\n+\n+    See Also\n+    --------\n+    mne.io.Raw : Documentation of attribute and methods.\n+    \"\"\"\n+    @verbose\n+    def __init__(self, input_fname, montage, eog=None, preload=False,\n+                 verbose=None):\n+        \"\"\"Read EEGLAB .set file.\n+        \"\"\"\n+        from scipy import io\n+        basedir = op.dirname(input_fname)\n+        eeg = io.loadmat(input_fname, struct_as_record=False,\n+                         squeeze_me=True)['EEG']\n+        if eeg.trials != 1:\n+            raise TypeError('The number of trials is %d. It must be 1 for raw'\n+                            ' files. Please use `mne.io.read_epochs_eeglab` if'\n+                            'the .set file contains epochs.' % eeg.trials)","path":"mne/io/eeglab/eeglab.py","position":211,"original_position":211,"commit_id":"34d5b74cec8edb3da4e55092d4a94a8fb2572ac4","original_commit_id":"34d5b74cec8edb3da4e55092d4a94a8fb2572ac4","user":{"login":"agramfort","id":161052,"avatar_url":"https://avatars.githubusercontent.com/u/161052?v=3","gravatar_id":"","url":"https://api.github.com/users/agramfort","html_url":"https://github.com/agramfort","followers_url":"https://api.github.com/users/agramfort/followers","following_url":"https://api.github.com/users/agramfort/following{/other_user}","gists_url":"https://api.github.com/users/agramfort/gists{/gist_id}","starred_url":"https://api.github.com/users/agramfort/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/agramfort/subscriptions","organizations_url":"https://api.github.com/users/agramfort/orgs","repos_url":"https://api.github.com/users/agramfort/repos","events_url":"https://api.github.com/users/agramfort/events{/privacy}","received_events_url":"https://api.github.com/users/agramfort/received_events","type":"User","site_admin":false},"body":"space missing before \"the\"","created_at":"2015-12-12T07:24:00Z","updated_at":"2015-12-12T07:24:00Z","html_url":"https://github.com/mne-tools/mne-python/pull/2676#discussion_r47428688","pull_request_url":"https://api.github.com/repos/mne-tools/mne-python/pulls/2676","_links":{"self":{"href":"https://api.github.com/repos/mne-tools/mne-python/pulls/comments/47428688"},"html":{"href":"https://github.com/mne-tools/mne-python/pull/2676#discussion_r47428688"},"pull_request":{"href":"https://api.github.com/repos/mne-tools/mne-python/pulls/2676"}}},"pull_request":{"url":"https://api.github.com/repos/mne-tools/mne-python/pulls/2676","id":52793451,"html_url":"https://github.com/mne-tools/mne-python/pull/2676","diff_url":"https://github.com/mne-tools/mne-python/pull/2676.diff","patch_url":"https://github.com/mne-tools/mne-python/pull/2676.patch","issue_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2676","number":2676,"state":"open","locked":false,"title":"WIP eeglab .set reader","user":{"login":"jasmainak","id":15852194,"avatar_url":"https://avatars.githubusercontent.com/u/15852194?v=3","gravatar_id":"","url":"https://api.github.com/users/jasmainak","html_url":"https://github.com/jasmainak","followers_url":"https://api.github.com/users/jasmainak/followers","following_url":"https://api.github.com/users/jasmainak/following{/other_user}","gists_url":"https://api.github.com/users/jasmainak/gists{/gist_id}","starred_url":"https://api.github.com/users/jasmainak/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jasmainak/subscriptions","organizations_url":"https://api.github.com/users/jasmainak/orgs","repos_url":"https://api.github.com/users/jasmainak/repos","events_url":"https://api.github.com/users/jasmainak/events{/privacy}","received_events_url":"https://api.github.com/users/jasmainak/received_events","type":"User","site_admin":false},"body":"closes https://github.com/mne-tools/mne-python/issues/2672\r\n\r\nvery much WIP and works only for the sample data provided by EEGLAB at the moment. If anyone has files to share, I'd be happy to try them.\r\n\r\nTODOs\r\n- [x] Fix scaling issue when plotting `raw`\r\n- [x] Check if chanlocs already exists in the `set` file\r\n- [x] Check if data already exists in the `set` file\r\n- [x] Handle epochs data","created_at":"2015-12-06T23:01:47Z","updated_at":"2015-12-12T07:24:00Z","closed_at":null,"merged_at":null,"merge_commit_sha":"e2fec25289b865bc8c48aa8d174a1eabdb769d67","assignee":null,"milestone":{"url":"https://api.github.com/repos/mne-tools/mne-python/milestones/7","html_url":"https://github.com/mne-tools/mne-python/milestones/0.11","labels_url":"https://api.github.com/repos/mne-tools/mne-python/milestones/7/labels","id":1288558,"number":7,"title":"0.11","description":"","creator":{"login":"dengemann","id":1908618,"avatar_url":"https://avatars.githubusercontent.com/u/1908618?v=3","gravatar_id":"","url":"https://api.github.com/users/dengemann","html_url":"https://github.com/dengemann","followers_url":"https://api.github.com/users/dengemann/followers","following_url":"https://api.github.com/users/dengemann/following{/other_user}","gists_url":"https://api.github.com/users/dengemann/gists{/gist_id}","starred_url":"https://api.github.com/users/dengemann/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/dengemann/subscriptions","organizations_url":"https://api.github.com/users/dengemann/orgs","repos_url":"https://api.github.com/users/dengemann/repos","events_url":"https://api.github.com/users/dengemann/events{/privacy}","received_events_url":"https://api.github.com/users/dengemann/received_events","type":"User","site_admin":false},"open_issues":3,"closed_issues":26,"state":"open","created_at":"2015-09-03T15:20:08Z","updated_at":"2015-12-11T21:29:22Z","due_on":"2015-12-18T05:00:00Z","closed_at":null},"commits_url":"https://api.github.com/repos/mne-tools/mne-python/pulls/2676/commits","review_comments_url":"https://api.github.com/repos/mne-tools/mne-python/pulls/2676/comments","review_comment_url":"https://api.github.com/repos/mne-tools/mne-python/pulls/comments{/number}","comments_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2676/comments","statuses_url":"https://api.github.com/repos/mne-tools/mne-python/statuses/34d5b74cec8edb3da4e55092d4a94a8fb2572ac4","head":{"label":"jasmainak:eeglab_io","ref":"eeglab_io","sha":"34d5b74cec8edb3da4e55092d4a94a8fb2572ac4","user":{"login":"jasmainak","id":15852194,"avatar_url":"https://avatars.githubusercontent.com/u/15852194?v=3","gravatar_id":"","url":"https://api.github.com/users/jasmainak","html_url":"https://github.com/jasmainak","followers_url":"https://api.github.com/users/jasmainak/followers","following_url":"https://api.github.com/users/jasmainak/following{/other_user}","gists_url":"https://api.github.com/users/jasmainak/gists{/gist_id}","starred_url":"https://api.github.com/users/jasmainak/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jasmainak/subscriptions","organizations_url":"https://api.github.com/users/jasmainak/orgs","repos_url":"https://api.github.com/users/jasmainak/repos","events_url":"https://api.github.com/users/jasmainak/events{/privacy}","received_events_url":"https://api.github.com/users/jasmainak/received_events","type":"User","site_admin":false},"repo":{"id":47331320,"name":"mne-python","full_name":"jasmainak/mne-python","owner":{"login":"jasmainak","id":15852194,"avatar_url":"https://avatars.githubusercontent.com/u/15852194?v=3","gravatar_id":"","url":"https://api.github.com/users/jasmainak","html_url":"https://github.com/jasmainak","followers_url":"https://api.github.com/users/jasmainak/followers","following_url":"https://api.github.com/users/jasmainak/following{/other_user}","gists_url":"https://api.github.com/users/jasmainak/gists{/gist_id}","starred_url":"https://api.github.com/users/jasmainak/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jasmainak/subscriptions","organizations_url":"https://api.github.com/users/jasmainak/orgs","repos_url":"https://api.github.com/users/jasmainak/repos","events_url":"https://api.github.com/users/jasmainak/events{/privacy}","received_events_url":"https://api.github.com/users/jasmainak/received_events","type":"User","site_admin":false},"private":false,"html_url":"https://github.com/jasmainak/mne-python","description":"MNE 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