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renamed datautils -> datautil
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robintibor committed Jul 3, 2017
1 parent dd4ca21 commit 7e6cf64
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2 changes: 1 addition & 1 deletion braindecode/experiments/experiment.py
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import pandas as pd

from braindecode.datautils.splitters import concatenate_sets
from braindecode.datautil.splitters import concatenate_sets
from braindecode.experiments.stopcriteria import MaxEpochs, ColumnBelow, Or
from braindecode.torchext.util import np_to_var, set_random_seeds

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4 changes: 1 addition & 3 deletions braindecode/experiments/monitors.py
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@@ -1,8 +1,6 @@
import numpy as np
import time

from braindecode.trial_segment import compute_trial_start_stop_samples


class MisclassMonitor(object):
def __init__(self, exponentiate_preds=False, col_suffix='misclass'):
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def monitor_set(self, setname, all_preds, all_losses,
all_batch_sizes, all_targets, dataset):
return {}
return {}
9 changes: 4 additions & 5 deletions docs/notebooks/TrialWise_Decoding.ipynb
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"%load_ext autoreload\n",
"%autoreload 2\n",
"import os\n",
"os.sys.path.insert(0, '/home/schirrmr/braindecode/code/braindecode2/')"
"os.sys.path.insert(0, '/home/schirrmr/braindecode/code/braindecode/')"
]
},
{
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"editable": true
},
"source": [
"Braindecode has a minimalistic ```SignalAndTarget``` class, with attributes `X` for the signal and `y` for the labels. For trialwise decoding, X should have these dimensions: trials x channels x timesteps."
"Braindecode has a minimalistic ```SignalAndTarget``` class, with attributes `X` for the signal and `y` for the labels. `X` should have these dimensions: trials x channels x timesteps."
]
},
{
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},
"outputs": [],
"source": [
"from braindecode.datautils.signal_target import SignalAndTarget\n",
"from braindecode.datautil.signal_target import SignalAndTarget\n",
"from braindecode.torchext.util import set_random_seeds\n",
"\n",
"train_set = SignalAndTarget(X[:60], y=y[:60])\n",
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],
"source": [
"from braindecode.torchext.util import np_to_var, var_to_np\n",
"from braindecode.datautils.iterators import get_balanced_batches\n",
"from braindecode.datautil.iterators import get_balanced_batches\n",
"import torch.nn.functional as F\n",
"from numpy.random import RandomState\n",
"rng = RandomState((2017,6,30))\n",
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}
],
"metadata": {
"celltoolbar": "Edit Metadata",
"kernelspec": {
"display_name": "Python 3",
"language": "python",
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