<commit_before>## Follow notes in : 
http://blog.mdda.net/oss/2014/10/13/ipython-on-fedora/
http://blog.mdda.net/oss/2014/10/19/pygtk-for-virtualenv/
http://blog.mdda.net/oss/2014/10/20/directories-in-ipython/

Additionally : hickle
sudo yum install hdf5-devel
(env) pip install hickle


ipython notebook
# and open a browser to http://localhost:8888/
%matplotlib inline

mkdir -p data/feat/{Dog_1,Dog_2,Dog_3,Dog_4,Dog_5,Patient_1,Patient_2}
## NO mkdir -p data/model/{Dog_1,Dog_2,Dog_3,Dog_4,Dog_5,Patient_1,Patient_2}

cd data/orig
tar -xzf Dog1.tar.gz
tar -xzf Dog2.tar.gz
tar -xzf Dog3.tar.gz

tar -xzf Dog4.tar.gz
tar -xzf Dog5.tar.gz
tar -xzf Patient1.tar.gz
tar -xzf Patient2.tar.gz
cd ../..

## Create the loader csv
python src/survey.py --patient Dog_1
python src/survey.py --patient Dog_2

python src/survey.py --patient Dog_3
python src/survey.py --patient Dog_4
python src/survey.py --patient Dog_5
python src/survey.py --patient Patient_1
python src/survey.py --patient Patient_2


## Preprocess all the training and test files into features 
#  Dog_2     :: (~0.5sec each => 1543 in 16min)

python src/preprocess.py --patient Dog_2 --fft 1 --scale 0 --train 0
python src/preprocess.py --patient Dog_2 --fft 0 --scale 1 --train 1 
python src/preprocess.py --patient Dog_2 --fft 0 --scale 1 --train 0 

#  Patient_2 :: (~ 25sec each =>  211 in 89min)


# CPU verison : 3m10s
python src/contractive_autoencode.py --patient Dog_2 --layer 1 --train 1
python src/contractive_autoencode.py --patient Dog_2 --layer 1 --train 0



# GPU (OpenCL) version : NOT WORKING
THEANO_FLAGS=mode=FAST_RUN,device=opencl0:0,floatX=float32,exception_verbosity=high,optimizer=fast_compile  optirun --no-xorg python src/contractive_autoencode.py 



# Works to test loader :
python src/graph.py 

import sys
sys.path.append('../src')
import EEG

Data<commit_msg>Time for bed<commit_after>## Follow notes in : 
http://blog.mdda.net/oss/2014/10/13/ipython-on-fedora/
http://blog.mdda.net/oss/2014/10/19/pygtk-for-virtualenv/
http://blog.mdda.net/oss/2014/10/20/directories-in-ipython/

Additionally : hickle
sudo yum install hdf5-devel
(env) pip install hickle


ipython notebook
# and open a browser to http://localhost:8888/
%matplotlib inline

mkdir -p data/feat/{Dog_1,Dog_2,Dog_3,Dog_4,Dog_5,Patient_1,Patient_2}
## NO mkdir -p data/model/{Dog_1,Dog_2,Dog_3,Dog_4,Dog_5,Patient_1,Patient_2}

cd data/orig
tar -xzf Dog1.tar.gz
tar -xzf Dog2.tar.gz
tar -xzf Dog3.tar.gz
tar -xzf Dog4.tar.gz
tar -xzf Dog5.tar.gz

=== HERE === 

tar -xzf Patient1.tar.gz
tar -xzf Patient2.tar.gz
cd ../..

## Create the loader csv
python src/survey.py --patient Dog_1
python src/survey.py --patient Dog_2
python src/survey.py --patient Dog_3
python src/survey.py --patient Dog_4      & 
python src/survey.py --patient Dog_5      &

=== HERE === 

python src/survey.py --patient Patient_1
python src/survey.py --patient Patient_2


## Preprocess all the training and test files into features 
#  Dog_2     :: (~0.5sec each => 1543 in 16min)

python src/preprocess.py --patient Dog_2 --fft 1 --scale 0 --train 1
python src/preprocess.py --patient Dog_2 --fft 0 --scale 1 --train 1 
python src/preprocess.py --patient Dog_2 --fft 0 --scale 1 --train 0 

python src/preprocess.py --patient Dog_1 --fft 1 --scale 0 --train 1 &
python src/preprocess.py --patient Dog_3 --fft 1 --scale 0 --train 1 &

=== HERE === 

#  Patient_2 :: (~ 25sec each =>  211 in 89min)


# CPU verison : 3m10s

python src/contractive_autoencode.py --patient Dog_2 --layer 1 --train 1
python src/contractive_autoencode.py --patient Dog_2 --layer 1 --train 0



# GPU (OpenCL) version : NOT WORKING
THEANO_FLAGS=mode=FAST_RUN,device=opencl0:0,floatX=float32,exception_verbosity=high,optimizer=fast_compile  optirun --no-xorg python src/contractive_autoencode.py 



# Works to test loader :
python src/graph.py 

import sys
sys.path.append('../src')
import EEG

Data
{'fraction_non_alphanumeric': 0.13200306983883345, 'fraction_numerical': 0.05269889997441801, 'mean_word_length': 3.4994246260069044, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 7, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '1236515', 'n_tokens_mistral': 1669, 'n_tokens_neox': 1472, 'n_words': 388}