"""
Various routines to load/access MNIST data.
"""

import os
import numpy

from pylearn.io.pmat import PMat
from pylearn.datasets.config import data_root # config
from pylearn.datasets.dataset import Dataset

def caltech_silhouette():

    rval = Dataset()

    
    path = os.path.join(data_root(), 'caltech_silhouettes')

    rval.train = Dataset.Obj(x=numpy.load(os.path.join(path,'train_data.npy')),
                             y=numpy.load(os.path.join(path,'train_labels.npy')))
    rval.valid = Dataset.Obj(x=numpy.load(os.path.join(path,'val_data.npy')),
                             y=numpy.load(os.path.join(path,'val_labels.npy')))
    rval.test  = Dataset.Obj(x=numpy.load(os.path.join(path,'test_data.npy')),
                             y=numpy.load(os.path.join(path,'test_labels.npy')))

    rval.n_classes = 101
    rval.img_shape = (28,28)

    return rval

def caltech_silhouette2():

    rval = Dataset()

    from scipy import io 
    path = '/data/lisa6/desjagui/caltech101_silhouettes_28_split1.mat'

    data = io.loadmat(open(path,'r'))

    rval.train = Dataset.Obj(x=data['train_data'], y=data['train_labels'])
    rval.valid = Dataset.Obj(x=data['val_data'],   y=data['val_labels'])
    rval.test  = Dataset.Obj(x=data['test_data'],  y=data['test_labels'])
    rval.n_classes = 101
    rval.img_shape = (28,28)

    return rval