def k_fold_cross_validation(X, K, randomise = False):
"""
Generates K (training, validation) pairs from the items in X.
Each pair is a partition of X, where validation is an iterable
of length len(X)/K. So each training iterable is of length (K-1)*len(X)/K.
If randomise is true, a copy of X is shuffled before partitioning,
otherwise its order is preserved in training and validation.
"""
if randomise: from random import shuffle; X=list(X); shuffle(X)
for k in xrange(K):
training = [x for i, x in enumerate(X) if i % K != k]
validation = [x for i, x in enumerate(X) if i % K == k]
yield training, validation
X = [i for i in xrange(97)]
for training, validation in k_fold_cross_validation(X, K=7):
for x in X: assert (x in training) ^ (x in validation), x