Add support for z and l cones to SCS

3 files changed, 26 insertions, 14 deletions

diff --git a/sumofsquares/constraints.py b/sumofsquares/constraints.py
index f287a23..5f5609f 100644
--- a/sumofsquares/constraints.py
+++ b/sumofsquares/constraints.py
@@ -64,19 +64,17 @@ class NonNegative(Constraint[E]):
     the domain in set to `None` then it is interpreted as being non-negative
     everywhere.
 
+    If the expression is a column vector, the interpretation is row-wise. In
+    other words each row must be non-negative on the domain (or everywhere if
+    not specified). In other words the vector is in the non-negative orthant of
+    R^n.
+
     **Note:** In this package, non-negativitiy of non-affine constraint will
     always eventually be replaced by the sufficient condition that the
     expression can be written as a sum-of-squares, hence this constraint can
     also be understood as `expression` being SOS.
     """
 
-    # This was part of the docstring but is not implemented yet
-    # TODO: implement what is says below
-    #
-    # If the expression is a column vector, the interpretation is row-wise. In
-    # other words each row must be non-negative on the domain (or everywhere if
-    # not specified).
-
     expression: E 
     domain: BasicSemialgebraicSet[E] | None = None
 
diff --git a/sumofsquares/problems.py b/sumofsquares/problems.py
index e6ca747..6737341 100644
--- a/sumofsquares/problems.py
+++ b/sumofsquares/problems.py
@@ -228,9 +228,19 @@ class SOSProblem(Problem):
 
                 state, deg = c.expression.degree().apply(state)
 
+                if isinstance(c.expression.shape[0], int):
+                    nrows = c.expression.shape[0]
+                else:
+                    state, shape = c.expression.shape[0].apply(state)
+                    nrows = shape.at(0, 0).constant() 
+
+                # It is a vector column goes in the non-negative orthant
+                if nrows > 1:
+                    constraints.append(c)
+
                 # Polynomial non-negativity contraints is converted to PSD
                 # constraint of SOS quadratic form
-                if deg.scalar().constant() > 1:
+                elif deg.scalar().constant() > 1:
                     # TODO: it seems to work fine even without .symmetric(). Why?
                     cnew = c.expression.quadratic_in(x).symmetric()
                     constraints.append(PositiveSemiDefinite(cnew))
diff --git a/sumofsquares/solver/scs.py b/sumofsquares/solver/scs.py
index faad4e1..7217b2c 100644
--- a/sumofsquares/solver/scs.py
+++ b/sumofsquares/solver/scs.py
@@ -84,9 +84,9 @@ def solve_cone(prob: ConicProblem, verbose: bool = False,
     #   q    second order cone
     #   s    positive semidefinite cone
     #   ep   exponential cone
-    #   ep*  dual exponential cone
+    #   ed   dual exponential cone
     #   p    power cone
-    #   p*   dual power cone
+    #   -p   dual power cone
     #
     # In their documentation they call the linear coefficient c. Here we use q.
 
@@ -96,11 +96,15 @@ def solve_cone(prob: ConicProblem, verbose: bool = False,
     if prob.q is not None:
         q = prob.q
 
-    if prob.constraints["z"]:
-        raise NotImplementedError
+    for (linear, constant) in prob.constraints["z"]:
+        # -1 because RHS
+        b_rows.append(-constant)
+        A_rows.append(np.hstack(tuple(m for m in linear)))
 
-    if prob.constraints["l"]:
-        raise NotImplementedError
+    for (linear, constant) in prob.constraints["l"]:
+        # -1 because RHS
+        b_rows.append(-constant)
+        A_rows.append(np.hstack(tuple(m for m in linear)))
 
     if prob.constraints["b"]:
         raise NotImplementedError