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# Author: Tom Dupre la Tour
#
# License: BSD 3 clause
import numpy as np
from numpy.testing import assert_array_equal
import scipy.sparse as sp
from sklearn.utils.seq_dataset import ArrayDataset, CSRDataset
from sklearn.datasets import load_iris
from sklearn.utils.testing import assert_equal
iris = load_iris()
X = iris.data.astype(np.float64)
y = iris.target.astype(np.float64)
X_csr = sp.csr_matrix(X)
sample_weight = np.arange(y.size, dtype=np.float64)
def assert_csr_equal(X, Y):
X.eliminate_zeros()
Y.eliminate_zeros()
assert_equal(X.shape[0], Y.shape[0])
assert_equal(X.shape[1], Y.shape[1])
assert_array_equal(X.data, Y.data)
assert_array_equal(X.indices, Y.indices)
assert_array_equal(X.indptr, Y.indptr)
def test_seq_dataset():
dataset1 = ArrayDataset(X, y, sample_weight, seed=42)
dataset2 = CSRDataset(X_csr.data, X_csr.indptr, X_csr.indices,
y, sample_weight, seed=42)
for dataset in (dataset1, dataset2):
for i in range(5):
# next sample
xi_, yi, swi, idx = dataset._next_py()
xi = sp.csr_matrix((xi_), shape=(1, X.shape[1]))
assert_csr_equal(xi, X_csr[idx])
assert_equal(yi, y[idx])
assert_equal(swi, sample_weight[idx])
# random sample
xi_, yi, swi, idx = dataset._random_py()
xi = sp.csr_matrix((xi_), shape=(1, X.shape[1]))
assert_csr_equal(xi, X_csr[idx])
assert_equal(yi, y[idx])
assert_equal(swi, sample_weight[idx])
def test_seq_dataset_shuffle():
dataset1 = ArrayDataset(X, y, sample_weight, seed=42)
dataset2 = CSRDataset(X_csr.data, X_csr.indptr, X_csr.indices,
y, sample_weight, seed=42)
# not shuffled
for i in range(5):
_, _, _, idx1 = dataset1._next_py()
_, _, _, idx2 = dataset2._next_py()
assert_equal(idx1, i)
assert_equal(idx2, i)
for i in range(5):
_, _, _, idx1 = dataset1._random_py()
_, _, _, idx2 = dataset2._random_py()
assert_equal(idx1, idx2)
seed = 77
dataset1._shuffle_py(seed)
dataset2._shuffle_py(seed)
for i in range(5):
_, _, _, idx1 = dataset1._next_py()
_, _, _, idx2 = dataset2._next_py()
assert_equal(idx1, idx2)
_, _, _, idx1 = dataset1._random_py()
_, _, _, idx2 = dataset2._random_py()
assert_equal(idx1, idx2)
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