Expose acceleration_trust_factor in Python bindings

Plumbs the new ScsSettings.acceleration_trust_factor field through
the Cython kwargs interface. Defaults to math.inf (no cap, matches
current SCS HEAD behavior); positive finite values activate the
trust-region + adaptive-r mode from the underlying aa library.

Bumps scs_source submodule to pick up the C-side change.

Validation rejects NaN and non-positive values. Adds coverage tests
for the default, finite/inf sweep, and rejection cases.

Author: bodono

scs/scsobject.h

@@ -490,6 +490,7 @@ static int SCS_init(SCS *self, PyObject *args, PyObject *kwargs) {
                     "acceleration_type_1",
                     "acceleration_regularization",
                     "acceleration_relaxation",
+                    "acceleration_trust_factor",
                     "write_data_filename",
                     "log_csv_filename",
                     NULL};
@@ -499,15 +500,15 @@ static int SCS_init(SCS *self, PyObject *args, PyObject *kwargs) {
    on Windows where sizeof(long) < sizeof(long long) (LLP64 model). */
 #ifdef DLONG
 #ifdef SFLOAT
-  char *argparse_string = "(LL)O!O!O!OOOO!O!O!|O!O!O!LfffffffLLLffzz";
+  char *argparse_string = "(LL)O!O!O!OOOO!O!O!|O!O!O!LfffffffLLLfffzz";
 #else
-  char *argparse_string = "(LL)O!O!O!OOOO!O!O!|O!O!O!LdddddddLLLddzz";
+  char *argparse_string = "(LL)O!O!O!OOOO!O!O!|O!O!O!LdddddddLLLdddzz";
 #endif
 #else
 #ifdef SFLOAT
-  char *argparse_string = "(ii)O!O!O!OOOO!O!O!|O!O!O!ifffffffiiiffzz";
+  char *argparse_string = "(ii)O!O!O!OOOO!O!O!|O!O!O!ifffffffiiifffzz";
 #else
-  char *argparse_string = "(ii)O!O!O!OOOO!O!O!|O!O!O!idddddddiiiddzz";
+  char *argparse_string = "(ii)O!O!O!OOOO!O!O!|O!O!O!idddddddiiidddzz";
 #endif
 #endif
 
@@ -547,6 +548,7 @@ static int SCS_init(SCS *self, PyObject *args, PyObject *kwargs) {
           &(stgs->acceleration_type_1),
           &(stgs->acceleration_regularization),
           &(stgs->acceleration_relaxation),
+          &(stgs->acceleration_trust_factor),
           &(stgs->write_data_filename),
           &(stgs->log_csv_filename))) {
     /* PyArg_ParseTupleAndKeywords already set an informative TypeError
@@ -835,6 +837,16 @@ static int SCS_init(SCS *self, PyObject *args, PyObject *kwargs) {
     free_py_scs_data(d, k, stgs, &ps);
     return finish_with_error("acceleration_relaxation must be in [0, 2]");
   }
+  /* acceleration_trust_factor: INFINITY (default) disables; positive
+   * finite values turn on the trust-region + adaptive-r mode in aa.
+   * NaN and non-positive values are rejected. */
+  if (isnan((double)stgs->acceleration_trust_factor) ||
+      stgs->acceleration_trust_factor <= 0) {
+    free_py_scs_data(d, k, stgs, &ps);
+    return finish_with_error(
+        "acceleration_trust_factor must be positive (math.inf for no cap, "
+        "the default)");
+  }
   if (!isfinite((double)stgs->scale) || stgs->scale <= 0) {
     free_py_scs_data(d, k, stgs, &ps);
     return finish_with_error("scale must be a positive finite number");

scs_source

@@ -2779,6 +2779,32 @@ def test_acceleration_regularization_zero_allowed():
     assert sol["info"]["status"] in ("solved", "solved_inaccurate")
 
 
+def test_acceleration_trust_factor_default_inf():
+    """Default acceleration_trust_factor is +inf (no cap, current behavior)."""
+    solver = scs.SCS(_make_data(), _CONE, verbose=False)
+    sol = solver.solve()
+    assert sol["info"]["status"] in ("solved", "solved_inaccurate")
+
+
+@pytest.mark.parametrize("trust_factor", [0.5, 1.0, 2.0, 10.0, float("inf")])
+def test_acceleration_trust_factor_in_range(trust_factor):
+    """Positive finite values enable trust-region + adaptive r; inf disables."""
+    solver = scs.SCS(
+        _make_data(), _CONE,
+        acceleration_trust_factor=trust_factor,
+        verbose=False,
+    )
+    sol = solver.solve()
+    assert sol["info"]["status"] in ("solved", "solved_inaccurate")
+
+
+@pytest.mark.parametrize("bad", [-1.0, 0.0, float("nan")])
+def test_acceleration_trust_factor_invalid_rejected(bad):
+    with pytest.raises(ValueError, match="acceleration_trust_factor"):
+        scs.SCS(_make_data(), _CONE,
+                acceleration_trust_factor=bad, verbose=False)
+
+
 # ===========================================================================
 # 73. Power cone with different exponents
 # ===========================================================================