#conda create -n deepeeg

#source activate deepeeg

#chomd +x install.sh

#bash install.sh

#!git clone https://github.com/kylemath/eeg-notebooks_v0.1

#python

from utils import *

data_dir = '/Users/kylemathewson/Desktop/'

exp = 'bikepark'

#subs = [ '009']

subs = ['005', '007', '009', '010', '012', '013', '014', '015', '016', '019']

sessions = ['quiet','traffic']

nsesh = len(sessions)

event_id = {'Standard': 1, 'Target': 2}

#https://martinos.org/mne/stable/auto_tutorials/plot_visualize_evoked.html

epochs = []

for sub in subs:

    print('Loading data for subject ' + sub)

    #Load Data

    raw = LoadBVData(sub,sessions,data_dir,exp)

    #Pre-Process EEG Data

    epochs.append(PreProcess(raw,event_id,emcp=True,rereference=True,

                        plot_erp=True))

epochs = concatenate_epochs(epochs) 

print(epochs)

#Engineer Features for Model

feats = FeatureEngineer(epochs,model_type='NN',electrode_median=False)

#Create Model

model,_ = CreateModel(feats, units=[16,16], dropout=.15)

#Train with validation, then Test

TrainTestVal(model,feats)