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Add "mixed" standard form representation #3201

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merged 6 commits into from
Apr 2, 2024
Merged

Add "mixed" standard form representation #3201

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927c46c
Add 'mixed' option to standard form writer
jsiirola Mar 18, 2024
64211e1
Fix error when removing unused variables
jsiirola Mar 18, 2024
3f17164
Merge branch 'main' into mixed-standard-form
jsiirola Mar 20, 2024
56b513d
add tests for mixed standard form
jsiirola Mar 20, 2024
2f1d4a0
NFC: apply black
jsiirola Mar 21, 2024
8c4fb77
Remove debugging; expand comment explaining difference in cut-and-pas…
jsiirola Apr 1, 2024
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63 changes: 48 additions & 15 deletions pyomo/repn/plugins/standard_form.py
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Original file line number Diff line number Diff line change
Expand Up @@ -139,6 +139,15 @@ class LinearStandardFormCompiler(object):
description='Add slack variables and return `min cTx s.t. Ax == b`',
),
)
CONFIG.declare(
'mixed_form',
ConfigValue(
default=False,
domain=bool,
description='Return A in mixed form (the comparison operator is a '
'mix of <=, ==, and >=)',
),
)
CONFIG.declare(
'show_section_timing',
ConfigValue(
Expand Down Expand Up @@ -332,6 +341,9 @@ def write(self, model):
# Tabulate constraints
#
slack_form = self.config.slack_form
mixed_form = self.config.mixed_form
if slack_form and mixed_form:
raise ValueError("cannot specify both slack_form and mixed_form")
rows = []
rhs = []
con_data = []
Expand Down Expand Up @@ -372,7 +384,30 @@ def write(self, model):
f"model contains a trivially infeasible constraint, '{con.name}'"
)

if slack_form:
if mixed_form:
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Is it more likely that a user will want mixed_form over slack_form?

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Users will probably do the regular form first, and then maybe the slack form. However, I am working on some (more efficient) solver interfaces (a rewrite of gurobi_direct) that will use the mixed_form.

N = len(repn.linear)
_data = np.fromiter(repn.linear.values(), float, N)
_index = np.fromiter(map(var_order.__getitem__, repn.linear), float, N)
if ub == lb:
rows.append(RowEntry(con, 0))
rhs.append(ub - offset)
con_data.append(_data)
con_index.append(_index)
con_index_ptr.append(con_index_ptr[-1] + N)
else:
if ub is not None:
rows.append(RowEntry(con, 1))
rhs.append(ub - offset)
con_data.append(_data)
con_index.append(_index)
con_index_ptr.append(con_index_ptr[-1] + N)
if lb is not None:
rows.append(RowEntry(con, -1))
rhs.append(lb - offset)
con_data.append(_data)
con_index.append(_index)
con_index_ptr.append(con_index_ptr[-1] + N)
elif slack_form:
_data = list(repn.linear.values())
_index = list(map(var_order.__getitem__, repn.linear))
if lb == ub: # TODO: add tolerance?
Expand Down Expand Up @@ -437,24 +472,22 @@ def write(self, model):
# at the index pointer list (an O(num_var) operation).
c_ip = c.indptr
A_ip = A.indptr
active_var_idx = list(
filter(
lambda i: A_ip[i] != A_ip[i + 1] or c_ip[i] != c_ip[i + 1],
range(len(columns)),
)
)
nCol = len(active_var_idx)
active_var_mask = (A_ip[1:] > A_ip[:-1]) | (c_ip[1:] > c_ip[:-1])

# Masks on NumPy arrays are very fast. Build the reduced A
# indptr and then check if we actually have to manipulate the
# columns
augmented_mask = np.concatenate((active_var_mask, [True]))
reduced_A_indptr = A.indptr[augmented_mask]
nCol = len(reduced_A_indptr) - 1
if nCol != len(columns):
# Note that the indptr can't just use range() because a var
# may only appear in the objectives or the constraints.
columns = list(map(columns.__getitem__, active_var_idx))
active_var_idx.append(c.indptr[-1])
columns = [v for k, v in zip(active_var_mask, columns) if k]
c = scipy.sparse.csc_array(
(c.data, c.indices, c.indptr.take(active_var_idx)), [c.shape[0], nCol]
(c.data, c.indices, c.indptr[augmented_mask]), [c.shape[0], nCol]
)
active_var_idx[-1] = A.indptr[-1]
# active_var_idx[-1] = len(columns)
A = scipy.sparse.csc_array(
Comment on lines -455 to 489
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Did you intend to leave this comment?

(A.data, A.indices, A.indptr.take(active_var_idx)), [A.shape[0], nCol]
(A.data, A.indices, reduced_A_indptr), [A.shape[0], nCol]
)

if self.config.nonnegative_vars:
Expand Down
41 changes: 41 additions & 0 deletions pyomo/repn/tests/test_standard_form.py
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Original file line number Diff line number Diff line change
Expand Up @@ -42,6 +42,23 @@ def test_linear_model(self):
self.assertTrue(np.all(repn.c == np.array([0, 0, 0])))
self.assertTrue(np.all(repn.A == np.array([[-1, -2, 0], [0, 1, 4]])))
self.assertTrue(np.all(repn.rhs == np.array([-3, 5])))
self.assertEqual(repn.rows, [(m.c, -1), (m.d, 1)])
self.assertEqual(repn.columns, [m.x, m.y[1], m.y[3]])

def test_almost_dense_linear_model(self):
m = pyo.ConcreteModel()
m.x = pyo.Var()
m.y = pyo.Var([1, 2, 3])
m.c = pyo.Constraint(expr=m.x + 2 * m.y[1] + 4 * m.y[3] >= 10)
m.d = pyo.Constraint(expr=5 * m.x + 6 * m.y[1] + 8 * m.y[3] <= 20)

repn = LinearStandardFormCompiler().write(m)

self.assertTrue(np.all(repn.c == np.array([0, 0, 0])))
self.assertTrue(np.all(repn.A == np.array([[-1, -2, -4], [5, 6, 8]])))
self.assertTrue(np.all(repn.rhs == np.array([-10, 20])))
self.assertEqual(repn.rows, [(m.c, -1), (m.d, 1)])
self.assertEqual(repn.columns, [m.x, m.y[1], m.y[3]])

def test_linear_model_row_col_order(self):
m = pyo.ConcreteModel()
Expand All @@ -57,6 +74,8 @@ def test_linear_model_row_col_order(self):
self.assertTrue(np.all(repn.c == np.array([0, 0, 0])))
self.assertTrue(np.all(repn.A == np.array([[4, 0, 1], [0, -1, -2]])))
self.assertTrue(np.all(repn.rhs == np.array([5, -3])))
self.assertEqual(repn.rows, [(m.d, 1), (m.c, -1)])
self.assertEqual(repn.columns, [m.y[3], m.x, m.y[1]])

def test_suffix_warning(self):
m = pyo.ConcreteModel()
Expand Down Expand Up @@ -222,6 +241,28 @@ def test_alternative_forms(self):
)
self._verify_solution(soln, repn, True)

repn = LinearStandardFormCompiler().write(
m, mixed_form=True, column_order=col_order
)

self.assertEqual(
repn.rows, [(m.c, -1), (m.d, 1), (m.e, 1), (m.e, -1), (m.f, 0)]
)
self.assertEqual(list(map(str, repn.x)), ['x', 'y[0]', 'y[1]', 'y[3]'])
self.assertEqual(
list(v.bounds for v in repn.x), [(None, None), (0, 10), (-5, 10), (-5, -2)]
)
ref = np.array(
[[1, 0, 2, 0], [0, 0, 1, 4], [0, 1, 6, 0], [0, 1, 6, 0], [1, 1, 0, 0]]
)
self.assertTrue(np.all(repn.A == ref))
self.assertTrue(np.all(repn.b == np.array([3, 5, 6, -3, 8])))
self.assertTrue(np.all(repn.c == np.array([[-1, 0, -5, 0], [1, 0, 0, 15]])))
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@emma58 emma58 Apr 2, 2024 •
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EEEEEK, I didn't notice this before--should we really let a "standard form" have more than one objective? This caused me a moment of terror on the the thought that I would definitely assume c is a vector of the same dimension as the number of columns in A... The matrix c makes sense to me from a writer perspective. From a user/transformation perspective, we're always going to need to be checking that this isn't the case... But I guess we have to do that anyway, so why not here?

# Note that the mixed_form solution is a mix of inequality and
# equality constraints, so we cannot (easily) reuse the
# _verify_solutions helper (as in the above cases):
# self._verify_solution(soln, repn, False)

repn = LinearStandardFormCompiler().write(
m, slack_form=True, nonnegative_vars=True, column_order=col_order
)
Expand Down