def test_io_datagenerator_x_batches():
X = numpy.random.randn(500, 13)
w = numpy.ones(500)
data = DataGenerator(X)
X_ = numpy.concatenate([batch[0] for batch in data.batches()])
w_ = numpy.concatenate([batch[1] for batch in data.batches()])
assert_almost_equal(X, X_)
assert_almost_equal(w, w_)
data = DataGenerator(X, batch_size=123)
X_ = numpy.concatenate([batch[0] for batch in data.batches()])
w_ = numpy.concatenate([batch[1] for batch in data.batches()])
assert_almost_equal(X, X_)
assert_almost_equal(w, w_)
data = DataGenerator(X, batch_size=1)
X_ = numpy.concatenate([batch[0] for batch in data.batches()])
w_ = numpy.concatenate([batch[1] for batch in data.batches()])
assert_almost_equal(X, X_)
assert_almost_equal(w, w_)
data = DataGenerator(X, batch_size=506)
X_ = numpy.concatenate([batch[0] for batch in data.batches()])
w_ = numpy.concatenate([batch[1] for batch in data.batches()])
assert_almost_equal(X, X_)
assert_almost_equal(w, w_)
def test_io_datagenerator_wy_batches():
X = numpy.random.randn(500, 13)
w = numpy.abs(numpy.random.randn(500))
y = numpy.random.randint(5, size=500)
data = DataGenerator(X, w, y)
y_ = numpy.concatenate([batch[1] for batch in data.batches()])
w_ = numpy.concatenate([batch[2] for batch in data.batches()])
assert_almost_equal(y, y_)
assert_almost_equal(w, w_)
data = DataGenerator(X, w, y, batch_size=123)
y_ = numpy.concatenate([batch[1] for batch in data.batches()])
w_ = numpy.concatenate([batch[2] for batch in data.batches()])
assert_almost_equal(y, y_)
assert_almost_equal(w, w_)
data = DataGenerator(X, w, y, batch_size=1)
y_ = numpy.concatenate([batch[1] for batch in data.batches()])
w_ = numpy.concatenate([batch[2] for batch in data.batches()])
assert_almost_equal(y, y_)
assert_almost_equal(w, w_)
data = DataGenerator(X, w, y, batch_size=506)
y_ = numpy.concatenate([batch[1] for batch in data.batches()])
w_ = numpy.concatenate([batch[2] for batch in data.batches()])
assert_almost_equal(y, y_)
assert_almost_equal(w, w_)
def test_io_datagenerator_w_batches():
X = numpy.random.randn(500, 13)
w = numpy.abs(numpy.random.randn(500))
data = DataGenerator(X, w)
w_ = numpy.concatenate([batch[1] for batch in data.batches()])
assert_almost_equal(w, w_)
data = DataGenerator(X, w, batch_size=123)
w_ = numpy.concatenate([batch[1] for batch in data.batches()])
assert_almost_equal(w, w_)
data = DataGenerator(X, w, batch_size=1)
w_ = numpy.concatenate([batch[1] for batch in data.batches()])
assert_almost_equal(w, w_)
data = DataGenerator(X, w, batch_size=506)
w_ = numpy.concatenate([batch[1] for batch in data.batches()])
assert_almost_equal(w, w_)
