def test_minmax_scaler_clip(setup, feature_range):
# test behaviour of the parameter 'clip' in MinMaxScaler
X = iris
scaler = MinMaxScaler(feature_range=feature_range, clip=True).fit(X)
X_min, X_max = mt.min(X, axis=0), mt.max(X, axis=0)
X_test = [mt.r_[X_min[:2] - 10, X_max[2:] + 10]]
X_transformed = scaler.transform(X_test)
assert_allclose(X_transformed, [[
feature_range[0], feature_range[0], feature_range[1], feature_range[1]
]])
def testMinmaxScalerClip(self):
for feature_range in [(0, 1), (-10, 10)]:
# test behaviour of the paramter 'clip' in MinMaxScaler
X = self.iris
scaler = MinMaxScaler(feature_range=feature_range,
clip=True).fit(X)
X_min, X_max = mt.min(X, axis=0), mt.max(X, axis=0)
X_test = [mt.r_[X_min[:2] - 10, X_max[2:] + 10]]
X_transformed = scaler.transform(X_test)
assert_allclose(X_transformed, [[
feature_range[0], feature_range[0], feature_range[1],
feature_range[1]
]])
def test_minmax_scale_axis1(setup):
X = iris
X_trans = minmax_scale(X, axis=1)
assert_array_almost_equal(mt.min(X_trans, axis=1), 0)
assert_array_almost_equal(mt.max(X_trans, axis=1), 1)
def testMinmaxScaleAxis1(self):
X = self.iris
X_trans = minmax_scale(X, axis=1)
assert_array_almost_equal(mt.min(X_trans, axis=1), 0)
assert_array_almost_equal(mt.max(X_trans, axis=1), 1)