cv_example.py

import numpy as np
import scipy.sparse
import macau

import row_split

## generate random toy data
Y = scipy.sparse.rand(100, 20, 0.5)

## random folds for cross-validation
nfolds = 5
ridx = np.random.permutation(Y.shape[0])
fold_idx = np.array_split(ridx, nfolds)

## executing all folds:
results = []
for fold in range(nfolds):
    test_rows = fold_idx[fold]
    Ytrain, Ytest = row_split.make_train_test_rows(Y, test_rows)
    
    result = macau.macau(Y=Ytrain, Ytest=Ytest, num_latent=2, precision="probit")
    results.append(result)

row_split.py

from scipy.sparse import csr_matrix
import numpy as np

def make_train_test_rows(Y, test_rows):
    """Splits Y into two matrices of the original shape."""
    Ycoo  = Y.tocoo()
    is_test  = np.zeros(Y.shape[0], dtype=np.bool)
    is_test[test_rows] = True

    test  = is_test[Ycoo.row]
    train = (test == False)

    y_csr_train = csr_matrix((Ycoo.data[train], (Ycoo.row[train], Ycoo.col[train])), shape=Y.shape)
    y_csr_test  = csr_matrix((Ycoo.data[test], (Ycoo.row[test], Ycoo.col[test])), shape=Y.shape)
    return y_csr_train, y_csr_test