def test_ndgrid_2():
X = np.random.RandomState(0).randn(100, 2)
ndgrid = NDGrid(n_bins_per_feature=2, min=-5, max=5)
labels = ndgrid.fit([X]).predict([X])[0]
mask0 = np.logical_and(X[:, 0] < 0, X[:, 1] < 0)
assert np.all(labels[mask0] == 0)
mask1 = np.logical_and(X[:, 0] > 0, X[:, 1] < 0)
assert np.all(labels[mask1] == 1)
mask2 = np.logical_and(X[:, 0] < 0, X[:, 1] > 0)
assert np.all(labels[mask2] == 2)
mask3 = np.logical_and(X[:, 0] > 0, X[:, 1] > 0)
assert np.all(labels[mask3] == 3)
def test_ndgrid_3():
X = np.random.RandomState(0).randn(100, 3)
ndgrid = NDGrid(n_bins_per_feature=2, min=-5, max=5)
labels = ndgrid.fit([X]).predict([X])[0]
operators = [np.less, np.greater]
x = X[:, 0]
y = X[:, 1]
z = X[:, 2]
it = itertools.product(operators, repeat=3)
for indx, (op_z, op_y, op_x) in enumerate(it):
mask = np.logical_and.reduce((op_x(x, 0), op_y(y, 0), op_z(z, 0)))
assert np.all(labels[mask] == indx)
