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JohnGriffiths committed Jun 21, 2024
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2 changes: 1 addition & 1 deletion .buildinfo
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# Sphinx build info version 1
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
config: fd29871f31cba0ba4269cba42e8b6ebf
config: f43e356d84e74a6ccecdbab8dd44ba1e
tags: 645f666f9bcd5a90fca523b33c5a78b7
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from mne.time_frequency import tfr_morlet

# EEG-Noteooks functions
from eegnb.analysis.utils import load_data
from eegnb.analysis.analysis_utils import load_data
from eegnb.datasets import fetch_dataset

# sphinx_gallery_thumbnail_number = 1
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},
"outputs": [],
"source": [
"# Standard pythonic importa\nimport os,sys,glob,numpy as np,pandas as pd\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\nfrom matplotlib import pyplot as plt\nimport matplotlib.patches as patches\n\n# MNE functions\nfrom mne import Epochs, find_events, concatenate_raws\nfrom mne.time_frequency import tfr_morlet\n\n# EEG-Notebooks functions\nfrom eegnb.datasets import datasets\nfrom eegnb.analysis.utils import load_data"
"# Standard pythonic importa\nimport os,sys,glob,numpy as np,pandas as pd\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\nfrom matplotlib import pyplot as plt\nimport matplotlib.patches as patches\n\n# MNE functions\nfrom mne import Epochs, find_events, concatenate_raws\nfrom mne.time_frequency import tfr_morlet\n\n# EEG-Notebooks functions\nfrom eegnb.datasets import datasets\nfrom eegnb.analysis.analysis_utils import load_data"
]
},
{
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},
"outputs": [],
"source": [
"from eegnb import generate_save_fn\nfrom eegnb.devices.eeg import EEG\nfrom eegnb.experiments import VisualN170\n\n# Define some variables\nboard_name = \"muse2\" # board name\nexperiment_name = \"visual_n170\" # experiment name\nsubject_id = 0 # test subject id\nsession_nb = 0 # session number\nrecord_duration = 120 # recording duration\n\n# generate save path\nsave_fn = generate_save_fn(board_name, experiment_name, subject_id, session_nb)\n\n# create device object\neeg_device = EEG(device=board_name)\n\n# Experiment type\nexperiment = VisualN170(duration=record_duration, eeg=eeg_device, save_fn=save_fn)"
"from eegnb import generate_save_fn\nfrom eegnb.devices.eeg import EEG\nfrom eegnb.experiments import VisualN170\n\n# Define some variables\nboard_name = \"muse2\" # board name\nexperiment_name = \"visual_n170\" # experiment name\nsubject_id = 0 # test subject id\nsession_nb = 0 # session number\nrecord_duration = 120 # recording duration\n\n# generate save path\nsave_fn = generate_save_fn(board_name, experiment_name, subject_id, session_nb)\n\n# create device object\neeg_device = EEG(device=board_name)\n\n# Experiment type\nexperiment = VisualN170(duration=record_duration, eeg=eeg_device, save_fn=save_fn, use_vr=False)"
]
},
{
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},
"outputs": [],
"source": [
"# Some standard pythonic imports\nimport os, numpy as np, pandas as pd\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\nfrom matplotlib import pyplot as plt\n\n# MNE functions\nfrom mne import Epochs,find_events\nfrom mne.time_frequency import tfr_morlet\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.utils import load_data,plot_conditions\nfrom eegnb.datasets import fetch_dataset"
"# Some standard pythonic imports\nimport os, numpy as np, pandas as pd\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\nfrom matplotlib import pyplot as plt\n\n# MNE functions\nfrom mne import Epochs,find_events\nfrom mne.time_frequency import tfr_morlet\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.analysis_utils import load_data,plot_conditions\nfrom eegnb.datasets import fetch_dataset"
]
},
{
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},
"outputs": [],
"source": [
"# Standard Pythonic imports\nimport os,sys,glob,numpy as np, pandas as pd\nimport scipy\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\nfrom matplotlib import pyplot as plt\nimport matplotlib.patches as patches\n\n# MNE functions\nfrom mne import Epochs, find_events, concatenate_raws\nfrom mne.time_frequency import tfr_morlet\n\n# EEG-Noteooks functions\nfrom eegnb.analysis.utils import load_data\nfrom eegnb.datasets import fetch_dataset"
"# Standard Pythonic imports\nimport os,sys,glob,numpy as np, pandas as pd\nimport scipy\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\nfrom matplotlib import pyplot as plt\nimport matplotlib.patches as patches\n\n# MNE functions\nfrom mne import Epochs, find_events, concatenate_raws\nfrom mne.time_frequency import tfr_morlet\n\n# EEG-Noteooks functions\nfrom eegnb.analysis.analysis_utils import load_data\nfrom eegnb.datasets import fetch_dataset"
]
},
{
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eeg_device = EEG(device=board_name)

# Experiment type
experiment = VisualN170(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
experiment = VisualN170(duration=record_duration, eeg=eeg_device, save_fn=save_fn, use_vr=False)

###################################################################################################
# Run experiment
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from mne.decoding import Vectorizer

# EEG-Notebooks functions
from eegnb.analysis.utils import load_data
from eegnb.analysis.analysis_utils import load_data
from eegnb.datasets import fetch_dataset

# Scikit-learn and Pyriemann ML functionalities
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},
"outputs": [],
"source": [
"# Some standard pythonic imports\nimport warnings\nwarnings.filterwarnings('ignore')\nimport os,numpy as np,pandas as pd\nfrom collections import OrderedDict\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\n\n# MNE functions\nfrom mne import Epochs,find_events\nfrom mne.decoding import Vectorizer\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.utils import load_data\nfrom eegnb.datasets import fetch_dataset\n\n# Scikit-learn and Pyriemann ML functionalities\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\nfrom sklearn.model_selection import cross_val_score, StratifiedShuffleSplit\nfrom pyriemann.estimation import ERPCovariances, XdawnCovariances\nfrom pyriemann.tangentspace import TangentSpace\nfrom pyriemann.classification import MDM"
"# Some standard pythonic imports\nimport warnings\nwarnings.filterwarnings('ignore')\nimport os,numpy as np,pandas as pd\nfrom collections import OrderedDict\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\n\n# MNE functions\nfrom mne import Epochs,find_events\nfrom mne.decoding import Vectorizer\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.analysis_utils import load_data\nfrom eegnb.datasets import fetch_dataset\n\n# Scikit-learn and Pyriemann ML functionalities\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\nfrom sklearn.model_selection import cross_val_score, StratifiedShuffleSplit\nfrom pyriemann.estimation import ERPCovariances, XdawnCovariances\nfrom pyriemann.tangentspace import TangentSpace\nfrom pyriemann.classification import MDM"
]
},
{
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from mne.time_frequency import tfr_morlet

# EEG-Notebooks functions
from eegnb.analysis.utils import load_data,plot_conditions
from eegnb.analysis.analysis_utils import load_data,plot_conditions
from eegnb.datasets import fetch_dataset

# sphinx_gallery_thumbnail_number = 3
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},
"outputs": [],
"source": [
"# Some standard pythonic imports\nimport os\nfrom matplotlib import pyplot as plt \nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# MNE functions\nfrom mne import Epochs,find_events\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.utils import load_data,plot_conditions\nfrom eegnb.datasets import fetch_dataset"
"# Some standard pythonic imports\nimport os\nfrom matplotlib import pyplot as plt \nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# MNE functions\nfrom mne import Epochs,find_events\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.analysis_utils import load_data,plot_conditions\nfrom eegnb.datasets import fetch_dataset"
]
},
{
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},
"outputs": [],
"source": [
"# Some standard pythonic imports\nimport warnings\nwarnings.filterwarnings('ignore')\nimport os,numpy as np,pandas as pd\nfrom collections import OrderedDict\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\n\n# MNE functions\nfrom mne import Epochs,find_events\nfrom mne.decoding import Vectorizer\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.utils import load_data\nfrom eegnb.datasets import fetch_dataset\n\n# Scikit-learn and Pyriemann ML functionalities\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\nfrom sklearn.model_selection import cross_val_score, StratifiedShuffleSplit\nfrom pyriemann.estimation import Covariances, ERPCovariances, XdawnCovariances\nfrom pyriemann.spatialfilters import CSP\nfrom pyriemann.tangentspace import TangentSpace\nfrom pyriemann.classification import MDM"
"# Some standard pythonic imports\nimport warnings\nwarnings.filterwarnings('ignore')\nimport os,numpy as np,pandas as pd\nfrom collections import OrderedDict\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\n\n# MNE functions\nfrom mne import Epochs,find_events\nfrom mne.decoding import Vectorizer\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.analysis_utils import load_data\nfrom eegnb.datasets import fetch_dataset\n\n# Scikit-learn and Pyriemann ML functionalities\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\nfrom sklearn.model_selection import cross_val_score, StratifiedShuffleSplit\nfrom pyriemann.estimation import Covariances, ERPCovariances, XdawnCovariances\nfrom pyriemann.spatialfilters import CSP\nfrom pyriemann.tangentspace import TangentSpace\nfrom pyriemann.classification import MDM"
]
},
{
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},
"outputs": [],
"source": [
"# Some standard pythonic imports\nimport os\nfrom matplotlib import pyplot as plt\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# MNE functions\nfrom mne import Epochs,find_events\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.utils import load_data,plot_conditions\nfrom eegnb.datasets import fetch_dataset"
"# Some standard pythonic imports\nimport os\nfrom matplotlib import pyplot as plt\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\n\n# MNE functions\nfrom mne import Epochs,find_events\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.analysis_utils import load_data,plot_conditions\nfrom eegnb.datasets import fetch_dataset"
]
},
{
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},
"outputs": [],
"source": [
"# Some standard pythonic imports\nimport os,numpy as np#,sys,glob,pandas as pd\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\nfrom matplotlib import pyplot as plt\nimport matplotlib.patches as patches\n\n# MNE functions\nfrom mne import Epochs,find_events#, concatenate_raws\nfrom mne.time_frequency import tfr_morlet\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.utils import load_data,plot_conditions\nfrom eegnb.datasets import fetch_dataset"
"# Some standard pythonic imports\nimport os,numpy as np#,sys,glob,pandas as pd\nfrom collections import OrderedDict\nimport warnings\nwarnings.filterwarnings('ignore')\nfrom matplotlib import pyplot as plt\nimport matplotlib.patches as patches\n\n# MNE functions\nfrom mne import Epochs,find_events#, concatenate_raws\nfrom mne.time_frequency import tfr_morlet\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.analysis_utils import load_data,plot_conditions\nfrom eegnb.datasets import fetch_dataset"
]
},
{
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from mne.decoding import Vectorizer

# EEG-Notebooks functions
from eegnb.analysis.utils import load_data
from eegnb.analysis.analysis_utils import load_data
from eegnb.datasets import fetch_dataset

# Scikit-learn and Pyriemann ML functionalities
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from mne.time_frequency import tfr_morlet

# EEG-Notebooks functions
from eegnb.analysis.utils import load_data,plot_conditions
from eegnb.analysis.analysis_utils import load_data,plot_conditions
from eegnb.datasets import fetch_dataset

# sphinx_gallery_thumbnail_number = 1
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Expand Up @@ -22,7 +22,7 @@

# EEG-Notebooks functions
from eegnb.datasets import datasets
from eegnb.analysis.utils import load_data
from eegnb.analysis.analysis_utils import load_data

# sphinx_gallery_thumbnail_number = 1

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from mne.decoding import Vectorizer

# EEG-Notebooks functions
from eegnb.analysis.utils import load_data
from eegnb.analysis.analysis_utils import load_data
from eegnb.datasets import fetch_dataset

# Scikit-learn and Pyriemann ML functionalities
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},
"outputs": [],
"source": [
"# Some standard pythonic imports\nimport warnings\nwarnings.filterwarnings('ignore')\nimport os,numpy as np,pandas as pd\nfrom collections import OrderedDict\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\n\n# MNE functions\nfrom mne import Epochs,find_events\nfrom mne.decoding import Vectorizer\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.utils import load_data\nfrom eegnb.datasets import fetch_dataset\n\n# Scikit-learn and Pyriemann ML functionalities\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\nfrom sklearn.model_selection import cross_val_score, StratifiedShuffleSplit\nfrom pyriemann.estimation import ERPCovariances, XdawnCovariances, Xdawn\nfrom pyriemann.tangentspace import TangentSpace\nfrom pyriemann.classification import MDM"
"# Some standard pythonic imports\nimport warnings\nwarnings.filterwarnings('ignore')\nimport os,numpy as np,pandas as pd\nfrom collections import OrderedDict\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\n\n# MNE functions\nfrom mne import Epochs,find_events\nfrom mne.decoding import Vectorizer\n\n# EEG-Notebooks functions\nfrom eegnb.analysis.analysis_utils import load_data\nfrom eegnb.datasets import fetch_dataset\n\n# Scikit-learn and Pyriemann ML functionalities\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\nfrom sklearn.model_selection import cross_val_score, StratifiedShuffleSplit\nfrom pyriemann.estimation import ERPCovariances, XdawnCovariances, Xdawn\nfrom pyriemann.tangentspace import TangentSpace\nfrom pyriemann.classification import MDM"
]
},
{
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from mne import Epochs,find_events

# EEG-Notebooks functions
from eegnb.analysis.utils import load_data,plot_conditions
from eegnb.analysis.analysis_utils import load_data,plot_conditions
from eegnb.datasets import fetch_dataset

# sphinx_gallery_thumbnail_number = 3
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from mne import Epochs,find_events

# EEG-Notebooks functions
from eegnb.analysis.utils import load_data,plot_conditions
from eegnb.analysis.analysis_utils import load_data,plot_conditions
from eegnb.datasets import fetch_dataset

# sphinx_gallery_thumbnail_number = 3
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11 changes: 11 additions & 0 deletions auto_examples/index.html
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</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../getting_started/running_experiments.html#using-jupyter-notebooks-or-a-custom-script">Using Jupyter Notebooks or a custom script</a></li>
<li class="toctree-l2"><a class="reference internal" href="../getting_started/running_experiments.html#using-virtual-reality">Using virtual reality</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#heads-up-display">Heads up display</a><ul>
<li class="toctree-l4"><a class="reference internal" href="../getting_started/running_experiments.html#features-to-be-added-in-future-releases">Features to be added in future releases:</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#prerequisites">Prerequisites:</a></li>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#id1"></a></li>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#steps-for-running-experiment-in-vr">Steps for running experiment in VR</a></li>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#other-experiments-can-have-vr-added-too">Other experiments can have VR added too.</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../getting_started/data_zipper.html">Data Zipping</a><ul>
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</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="../getting_started/running_experiments.html#using-jupyter-notebooks-or-a-custom-script">Using Jupyter Notebooks or a custom script</a></li>
<li class="toctree-l2"><a class="reference internal" href="../getting_started/running_experiments.html#using-virtual-reality">Using virtual reality</a><ul>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#heads-up-display">Heads up display</a><ul>
<li class="toctree-l4"><a class="reference internal" href="../getting_started/running_experiments.html#features-to-be-added-in-future-releases">Features to be added in future releases:</a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#prerequisites">Prerequisites:</a></li>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#id1"></a></li>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#steps-for-running-experiment-in-vr">Steps for running experiment in VR</a></li>
<li class="toctree-l3"><a class="reference internal" href="../getting_started/running_experiments.html#other-experiments-can-have-vr-added-too">Other experiments can have VR added too.</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="../getting_started/data_zipper.html">Data Zipping</a><ul>
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