""" Unit test for Linear Programming via Simplex Algorithm. """ import numpy as np from numpy.testing import assert_, assert_allclose, assert_equal from pytest import raises as assert_raises from scipy.optimize._linprog_util import _clean_inputs, _LPProblem from copy import deepcopy from datetime import date def test_aliasing(): """ Test for ensuring that no objects referred to by `lp` attributes, `c`, `A_ub`, `b_ub`, `A_eq`, `b_eq`, `bounds`, have been modified by `_clean_inputs` as a side effect. """ lp = _LPProblem( c=1, A_ub=[[1]], b_ub=[1], A_eq=[[1]], b_eq=[1], bounds=(-np.inf, np.inf) ) lp_copy = deepcopy(lp) _clean_inputs(lp) assert_(lp.c == lp_copy.c, "c modified by _clean_inputs") assert_(lp.A_ub == lp_copy.A_ub, "A_ub modified by _clean_inputs") assert_(lp.b_ub == lp_copy.b_ub, "b_ub modified by _clean_inputs") assert_(lp.A_eq == lp_copy.A_eq, "A_eq modified by _clean_inputs") assert_(lp.b_eq == lp_copy.b_eq, "b_eq modified by _clean_inputs") assert_(lp.bounds == lp_copy.bounds, "bounds modified by _clean_inputs") def test_aliasing2(): """ Similar purpose as `test_aliasing` above. """ lp = _LPProblem( c=np.array([1, 1]), A_ub=np.array([[1, 1], [2, 2]]), b_ub=np.array([[1], [1]]), A_eq=np.array([[1, 1]]), b_eq=np.array([1]), bounds=[(-np.inf, np.inf), (None, 1)] ) lp_copy = deepcopy(lp) _clean_inputs(lp) assert_allclose(lp.c, lp_copy.c, err_msg="c modified by _clean_inputs") assert_allclose(lp.A_ub, lp_copy.A_ub, err_msg="A_ub modified by _clean_inputs") assert_allclose(lp.b_ub, lp_copy.b_ub, err_msg="b_ub modified by _clean_inputs") assert_allclose(lp.A_eq, lp_copy.A_eq, err_msg="A_eq modified by _clean_inputs") assert_allclose(lp.b_eq, lp_copy.b_eq, err_msg="b_eq modified by _clean_inputs") assert_(lp.bounds == lp_copy.bounds, "bounds modified by _clean_inputs") def test_missing_inputs(): c = [1, 2] A_ub = np.array([[1, 1], [2, 2]]) b_ub = np.array([1, 1]) A_eq = np.array([[1, 1], [2, 2]]) b_eq = np.array([1, 1]) assert_raises(TypeError, _clean_inputs) assert_raises(TypeError, _clean_inputs, _LPProblem(c=None)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_ub=A_ub)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_ub=A_ub, b_ub=None)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, b_ub=b_ub)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_ub=None, b_ub=b_ub)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_eq=A_eq)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_eq=A_eq, b_eq=None)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, b_eq=b_eq)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_eq=None, b_eq=b_eq)) def test_too_many_dimensions(): cb = [1, 2, 3, 4] A = np.random.rand(4, 4) bad2D = [[1, 2], [3, 4]] bad3D = np.random.rand(4, 4, 4) assert_raises(ValueError, _clean_inputs, _LPProblem(c=bad2D, A_ub=A, b_ub=cb)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=cb, A_ub=bad3D, b_ub=cb)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=cb, A_ub=A, b_ub=bad2D)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=cb, A_eq=bad3D, b_eq=cb)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=cb, A_eq=A, b_eq=bad2D)) def test_too_few_dimensions(): bad = np.random.rand(4, 4).ravel() cb = np.random.rand(4) assert_raises(ValueError, _clean_inputs, _LPProblem(c=cb, A_ub=bad, b_ub=cb)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=cb, A_eq=bad, b_eq=cb)) def test_inconsistent_dimensions(): m = 2 n = 4 c = [1, 2, 3, 4] Agood = np.random.rand(m, n) Abad = np.random.rand(m, n + 1) bgood = np.random.rand(m) bbad = np.random.rand(m + 1) boundsbad = [(0, 1)] * (n + 1) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_ub=Abad, b_ub=bgood)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_ub=Agood, b_ub=bbad)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_eq=Abad, b_eq=bgood)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, A_eq=Agood, b_eq=bbad)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, bounds=boundsbad)) assert_raises(ValueError, _clean_inputs, _LPProblem(c=c, bounds=[[1, 2], [2, 3], [3, 4], [4, 5, 6]])) def test_type_errors(): lp = _LPProblem( c=[1, 2], A_ub=np.array([[1, 1], [2, 2]]), b_ub=np.array([1, 1]), A_eq=np.array([[1, 1], [2, 2]]), b_eq=np.array([1, 1]), bounds=[(0, 1)] ) bad = "hello" assert_raises(TypeError, _clean_inputs, lp._replace(c=bad)) assert_raises(TypeError, _clean_inputs, lp._replace(A_ub=bad)) assert_raises(TypeError, _clean_inputs, lp._replace(b_ub=bad)) assert_raises(TypeError, _clean_inputs, lp._replace(A_eq=bad)) assert_raises(TypeError, _clean_inputs, lp._replace(b_eq=bad)) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=bad)) assert_raises(ValueError, _clean_inputs, lp._replace(bounds="hi")) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=["hi"])) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=[("hi")])) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=[(1, "")])) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=[(1, 2), (1, "")])) assert_raises(TypeError, _clean_inputs, lp._replace(bounds=[(1, date(2020, 2, 29))])) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=[[[1, 2]]])) def test_non_finite_errors(): lp = _LPProblem( c=[1, 2], A_ub=np.array([[1, 1], [2, 2]]), b_ub=np.array([1, 1]), A_eq=np.array([[1, 1], [2, 2]]), b_eq=np.array([1, 1]), bounds=[(0, 1)] ) assert_raises(ValueError, _clean_inputs, lp._replace(c=[0, None])) assert_raises(ValueError, _clean_inputs, lp._replace(c=[np.inf, 0])) assert_raises(ValueError, _clean_inputs, lp._replace(c=[0, -np.inf])) assert_raises(ValueError, _clean_inputs, lp._replace(c=[np.nan, 0])) assert_raises(ValueError, _clean_inputs, lp._replace(A_ub=[[1, 2], [None, 1]])) assert_raises(ValueError, _clean_inputs, lp._replace(b_ub=[np.inf, 1])) assert_raises(ValueError, _clean_inputs, lp._replace(A_eq=[[1, 2], [1, -np.inf]])) assert_raises(ValueError, _clean_inputs, lp._replace(b_eq=[1, np.nan])) def test__clean_inputs1(): lp = _LPProblem( c=[1, 2], A_ub=[[1, 1], [2, 2]], b_ub=[1, 1], A_eq=[[1, 1], [2, 2]], b_eq=[1, 1], bounds=None ) lp_cleaned = _clean_inputs(lp) assert_allclose(lp_cleaned.c, np.array(lp.c)) assert_allclose(lp_cleaned.A_ub, np.array(lp.A_ub)) assert_allclose(lp_cleaned.b_ub, np.array(lp.b_ub)) assert_allclose(lp_cleaned.A_eq, np.array(lp.A_eq)) assert_allclose(lp_cleaned.b_eq, np.array(lp.b_eq)) assert_equal(lp_cleaned.bounds, [(0, np.inf)] * 2) assert_(lp_cleaned.c.shape == (2,), "") assert_(lp_cleaned.A_ub.shape == (2, 2), "") assert_(lp_cleaned.b_ub.shape == (2,), "") assert_(lp_cleaned.A_eq.shape == (2, 2), "") assert_(lp_cleaned.b_eq.shape == (2,), "") def test__clean_inputs2(): lp = _LPProblem( c=1, A_ub=[[1]], b_ub=1, A_eq=[[1]], b_eq=1, bounds=(0, 1) ) lp_cleaned = _clean_inputs(lp) assert_allclose(lp_cleaned.c, np.array(lp.c)) assert_allclose(lp_cleaned.A_ub, np.array(lp.A_ub)) assert_allclose(lp_cleaned.b_ub, np.array(lp.b_ub)) assert_allclose(lp_cleaned.A_eq, np.array(lp.A_eq)) assert_allclose(lp_cleaned.b_eq, np.array(lp.b_eq)) assert_equal(lp_cleaned.bounds, [(0, 1)]) assert_(lp_cleaned.c.shape == (1,), "") assert_(lp_cleaned.A_ub.shape == (1, 1), "") assert_(lp_cleaned.b_ub.shape == (1,), "") assert_(lp_cleaned.A_eq.shape == (1, 1), "") assert_(lp_cleaned.b_eq.shape == (1,), "") def test__clean_inputs3(): lp = _LPProblem( c=[[1, 2]], A_ub=np.random.rand(2, 2), b_ub=[[1], [2]], A_eq=np.random.rand(2, 2), b_eq=[[1], [2]], bounds=[(0, 1)] ) lp_cleaned = _clean_inputs(lp) assert_allclose(lp_cleaned.c, np.array([1, 2])) assert_allclose(lp_cleaned.b_ub, np.array([1, 2])) assert_allclose(lp_cleaned.b_eq, np.array([1, 2])) assert_equal(lp_cleaned.bounds, [(0, 1)] * 2) assert_(lp_cleaned.c.shape == (2,), "") assert_(lp_cleaned.b_ub.shape == (2,), "") assert_(lp_cleaned.b_eq.shape == (2,), "") def test_bad_bounds(): lp = _LPProblem(c=[1, 2]) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=(1, 2, 2))) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=[(1, 2, 2)])) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=[(1, 2), (1, 2, 2)])) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=[(1, 2), (1, 2), (1, 2)])) lp = _LPProblem(c=[1, 2, 3, 4]) assert_raises(ValueError, _clean_inputs, lp._replace(bounds=[(1, 2, 3, 4), (1, 2, 3, 4)])) def test_good_bounds(): lp = _LPProblem(c=[1, 2]) lp_cleaned = _clean_inputs(lp) # lp.bounds is None by default assert_equal(lp_cleaned.bounds, [(0, np.inf)] * 2) lp_cleaned = _clean_inputs(lp._replace(bounds=[])) assert_equal(lp_cleaned.bounds, [(0, np.inf)] * 2) lp_cleaned = _clean_inputs(lp._replace(bounds=[[]])) assert_equal(lp_cleaned.bounds, [(0, np.inf)] * 2) lp_cleaned = _clean_inputs(lp._replace(bounds=(1, 2))) assert_equal(lp_cleaned.bounds, [(1, 2)] * 2) lp_cleaned = _clean_inputs(lp._replace(bounds=[(1, 2)])) assert_equal(lp_cleaned.bounds, [(1, 2)] * 2) lp_cleaned = _clean_inputs(lp._replace(bounds=[(1, None)])) assert_equal(lp_cleaned.bounds, [(1, np.inf)] * 2) lp_cleaned = _clean_inputs(lp._replace(bounds=[(None, 1)])) assert_equal(lp_cleaned.bounds, [(-np.inf, 1)] * 2) lp_cleaned = _clean_inputs(lp._replace(bounds=[(None, None), (-np.inf, None)])) assert_equal(lp_cleaned.bounds, [(-np.inf, np.inf)] * 2) lp = _LPProblem(c=[1, 2, 3, 4]) lp_cleaned = _clean_inputs(lp) # lp.bounds is None by default assert_equal(lp_cleaned.bounds, [(0, np.inf)] * 4) lp_cleaned = _clean_inputs(lp._replace(bounds=(1, 2))) assert_equal(lp_cleaned.bounds, [(1, 2)] * 4) lp_cleaned = _clean_inputs(lp._replace(bounds=[(1, 2)])) assert_equal(lp_cleaned.bounds, [(1, 2)] * 4) lp_cleaned = _clean_inputs(lp._replace(bounds=[(1, None)])) assert_equal(lp_cleaned.bounds, [(1, np.inf)] * 4) lp_cleaned = _clean_inputs(lp._replace(bounds=[(None, 1)])) assert_equal(lp_cleaned.bounds, [(-np.inf, 1)] * 4) lp_cleaned = _clean_inputs(lp._replace(bounds=[(None, None), (-np.inf, None), (None, np.inf), (-np.inf, np.inf)])) assert_equal(lp_cleaned.bounds, [(-np.inf, np.inf)] * 4)