def test_many_iter_ecp():
# warm starting with the previously found solution should take 0 iterations
data, cone = ex.many_iter_ecp()
sol = scs.solve(data, cone)
assert sol['info']['iter'] >= 500
sol = scs.solve(data, cone, warm_start = sol)
assert sol['info']['iter'] == 0
def test_many_iter_ecp():
# warm starting with the previously found solution should take 0 iterations
data, cone = ex.many_iter_ecp()
sol = scs.solve(data, cone)
assert sol['info']['iter'] >= 500
sol = scs.solve(data, cone, warm_start=sol)
assert sol['info']['iter'] == 0
def test_many_iter_ecp_tol():
# warm starting with a solution at a lower tolerance should reduce
# the number of iterations needed
data, cone = ex.many_iter_ecp()
# intially takes ~920 iters for eps 1e-4
sol = scs.solve(data, cone, eps=1e-4)
assert sol['info']['iter'] >= 800
# ~640 for eps 1e-3
sol = scs.solve(data, cone, eps=1e-3)
assert 500 <= sol['info']['iter'] <= 700
# use 1e-3 sol as warm start for 1e-4
# extra digit only takes ~280 iters more
sol = scs.solve(data, cone, warm_start = sol, eps=1e-4)
assert sol['info']['iter'] < 300
def test_b_len():
data, cone = ex.simple_lp()
b = data['b']
b = np.append(b, b)
data['b'] = b
with pytest.raises(ValueError):
sol = scs.solve(data, cone)
def test_numdim_b():
data, cone = ex.simple_lp()
b = data['b']
b = np.array(b, ndmin=2).T
data['b'] = b
with pytest.raises(ValueError):
sol = scs.solve(data, cone)
def test_warm():
data, cone, true_x = ex.simple_pcp()
# computing a fresh solution takes some number of iters
sol = scs.solve(data, cone)
assert sol['info']['iter'] >= 10
# should take 0 iterations
sol = scs.solve(data, cone, warm_start = sol)
assert sol['info']['iter'] == 0
# change solution a bit
sol['x'] *= 2
# perturbing the solution should take a few iterations to correct
sol = scs.solve(data, cone, warm_start = sol)
assert sol['info']['iter'] >= 3
def test_warm():
data, cone, true_x = ex.simple_pcp()
# computing a fresh solution takes some number of iters
sol = scs.solve(data, cone)
assert sol['info']['iter'] >= 10
# should take 0 iterations
sol = scs.solve(data, cone, warm_start=sol)
assert sol['info']['iter'] == 0
# change solution a bit
sol['x'] *= 2
# perturbing the solution should take a few iterations to correct
sol = scs.solve(data, cone, warm_start=sol)
assert sol['info']['iter'] >= 3
def test_cone_size():
# test that the solve method recognizes that the length of the cone
# does not match the number of rows of A
data, cone = ex.simple_lp()
cone['l'] = 5
with pytest.raises(ValueError):
sol = scs.solve(data, cone)
def test_b_len():
data, cone = ex.simple_lp()
b = data['b']
b = np.append(b,b)
data['b'] = b
with pytest.raises(ValueError):
sol = scs.solve(data, cone)
def test_numdim_b():
data, cone = ex.simple_lp()
b = data['b']
b = np.array(b, ndmin=2).T
data['b'] = b
with pytest.raises(ValueError):
sol = scs.solve(data, cone)
def test_many_iter_ecp_tol():
# warm starting with a solution at a lower tolerance should reduce
# the number of iterations needed
data, cone = ex.many_iter_ecp()
# intially takes ~920 iters for eps 1e-4
sol = scs.solve(data, cone, eps=1e-4)
assert sol['info']['iter'] >= 800
# ~640 for eps 1e-3
sol = scs.solve(data, cone, eps=1e-3)
assert 500 <= sol['info']['iter'] <= 700
# use 1e-3 sol as warm start for 1e-4
# extra digit only takes ~280 iters more
sol = scs.solve(data, cone, warm_start=sol, eps=1e-4)
assert sol['info']['iter'] < 300
def test_solve():
data, cone = ex.simple_lp()
m,n = data['A'].shape
ws = dict(x=np.zeros(n), y=np.zeros(m), s=np.zeros(m))
sol = scs.solve(data, cone, warm_start = ws)
# make sure sol and ws contain *different* numpy arrays
assert any(ws['x'] != sol['x'])
assert any(ws['y'] != sol['y'])
assert any(ws['s'] != sol['s'])
def test_solve():
data, cone = ex.simple_lp()
m, n = data['A'].shape
ws = dict(x=np.zeros(n), y=np.zeros(m), s=np.zeros(m))
sol = scs.solve(data, cone, warm_start=ws)
# make sure sol and ws contain *different* numpy arrays
assert any(ws['x'] != sol['x'])
assert any(ws['y'] != sol['y'])
assert any(ws['s'] != sol['s'])
def test_simple_direct():
data, cone = ex.simple_lp()
sol = scs.solve(data, cone, use_indirect=False)
def test_extra_arg():
data, cone = ex.simple_lp()
sol = scs.solve(data, cone, eps=1e-9, alpha=.1, nonsense_arg='nonsense')
def test_b():
data, cone = ex.simple_lp()
data['b'] = data['b'].astype(np.float32)
with pytest.raises(ValueError):
sol = scs.solve(data, cone)
def test_A_indptr():
data, cone = ex.simple_lp()
data['A'].indptr = data['A'].indptr.astype(np.int32)
with pytest.warns(UserWarning):
sol = scs.solve(data, cone)
def test_simple_lp():
data, cone = ex.simple_lp()
sol = scs.solve(data, cone)
def test_simple_pcp():
data, cone, true_x = ex.simple_pcp()
sol = scs.solve(data, cone, eps=1e-6)
assert np.allclose(sol['x'], true_x)
def test_b():
data, cone = ex.simple_lp()
data['b'] = data['b'].astype(np.float32)
with pytest.raises(ValueError):
sol = scs.solve(data, cone)
def test_str_output():
data, cone = ex.simple_lp()
sol = scs.solve(data, cone)
assert sol['info']['status'] == 'Solved'
def test_A_data():
data, cone = ex.simple_lp()
data['A'].data = data['A'].data.astype(np.float32)
with pytest.warns(UserWarning):
sol = scs.solve(data, cone)
def test_A_indptr():
data, cone = ex.simple_lp()
data['A'].indptr = data['A'].indptr.astype(np.int32)
with pytest.warns(UserWarning):
sol = scs.solve(data, cone)
def test_A_data():
data, cone = ex.simple_lp()
data['A'].data = data['A'].data.astype(np.float32)
with pytest.warns(UserWarning):
sol = scs.solve(data, cone)