mahehu / decmeg Goto Github PK

I am new to this field and I wanted to recreate what you have done. However, when I executed python train.py I got a few warnings and the following error. Can you please take a look at those? Thank you.

warning 1: In the decimate() method (line number 125)

/home/chandrahas/anaconda3/envs/mne/lib/python3.6/site-packages/scipy/signal/_arraytools.py:45: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result.
b = a[a_slice]
/home/chandrahas/anaconda3/envs/mne/lib/python3.6/site-packages/scipy/signal/signaltools.py:3463: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use arr[tuple(seq)] instead of arr[seq]. In the future this will be interpreted as an array index, arr[np.array(seq)], which will result either in an error or a different result.
return y[sl]

warning 2: at train.py --> clf.fit(X, y, X_subj) (line number 329)

/home/chandrahas/anaconda3/envs/mne/lib/python3.6/site-packages/sklearn/linear_model/logistic.py:433: FutureWarning: Default solver will be changed to 'lbfgs' in 0.22. Specify a solver to silence this warning.
FutureWarning)

ERROR:

Traceback (most recent call last):
File "train.py", line 380, in
estimateCvScore = estimateCvScore)
File "train.py", line 332, in run
clf.fit(X, y, X_subj)
File "/home/chandrahas/Downloads/Thesis/DecMeg2014_kaggle_competition/Second_Place/decmeg-master/IterativeTrainer.py", line 138, in fit
self.clf.fit(X_aug, y_aug)
File "/home/chandrahas/Downloads/Thesis/DecMeg2014_kaggle_competition/Second_Place/decmeg-master/LrCollection.py", line 165, in fit
clf.fit(view, y)
File "/home/chandrahas/anaconda3/envs/mne/lib/python3.6/site-packages/sklearn/linear_model/logistic.py", line 1305, in fit
sample_weight=sample_weight)
File "/home/chandrahas/anaconda3/envs/mne/lib/python3.6/site-packages/sklearn/svm/base.py", line 881, in fit_liblinear
" class: %r" % classes[0])
ValueError: This solver needs samples of at least 2 classes in the data, but the data contains only one class: 1.0

Hi, I am trying to use LinearSVC + Randomforest in your code. My data has 578 trials, 70 channels and 11 features but it is throwing me the following error. Can you tell me what is the problem?

Traceback (most recent call last):
File "", line 1, in
File "C:\Users\Sarwat\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 685, in runfile
execfile(filename, namespace)
File "C:\Users\Sarwat\Anaconda3\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 85, in execfile
exec(compile(open(filename, 'rb').read(), filename, 'exec'), namespace)
File "C:/Users/Sarwat/Desktop/EEG/EEG.py", line 352, in
estimateCvScore = estimateCvScore,
File "C:/Users/Sarwat/Desktop/EEG/EEG.py", line 274, in run
clf.fit(X[trainIdx, :, :,np.newaxis], y[trainIdx], X[testIdx,:,:])
File "C:\Users\Sarwat\Desktop\EEG\IterativeTrainer.py", line 141, in fit
self.clf.fit(X_aug, y_aug)
File "C:\Users\Sarwat\Desktop\EEG\LrCollection.py", line 147, in fit
for col in range(X.shape[1]):
IndexError: tuple index out of range