fix: default solver is 'cg' when none specified

LoopStructural/interpolators/_discrete_interpolator.py

@@ -62,7 +62,6 @@ def __init__(self, support, data={}, c=None, up_to_date=False):
         self.interpolation_weights = {}
         logger.info("Creating discrete interpolator with {} degrees of freedom".format(self.nx))
         self.type = InterpolatorType.BASE_DISCRETE
-        self.c = np.zeros(self.support.n_nodes)
 
     @property
     def nx(self) -> int:
@@ -140,7 +139,7 @@ def reset(self):
         """
         self.constraints = {}
         self.c_ = 0
-        logger.debug("Resetting interpolation constraints")
+        logger.info("Resetting interpolation constraints")
 
     def add_constraints_to_least_squares(self, A, B, idc, w=1.0, name="undefined"):
         """
@@ -511,14 +510,15 @@ def build_inequality_matrix(self):
             mats.append(c['matrix'])
             bounds.append(c['bounds'])
         if len(mats) == 0:
-            return None, None
+            return sparse.csr_matrix((0, self.nx), dtype=float), np.zeros((0, 3))
         Q = sparse.vstack(mats)
         bounds = np.vstack(bounds)
         return Q, bounds
 
     def solve_system(
         self,
         solver: Optional[Union[Callable[[sparse.csr_matrix, np.ndarray], np.ndarray], str]] = None,
+        tol: Optional[float] = None,
         solver_kwargs: dict = {},
     ) -> bool:
         """
@@ -557,10 +557,18 @@ def solve_system(
                     f'Unknown solver {solver} using cg. \n Available solvers are cg and lsmr or a custom solver as a callable function'
                 )
                 solver = 'cg'
+        if solver is None:
+            solver = 'cg'
         if solver == 'cg':
             logger.info("Solving using cg")
-            ATA = A.T.dot(A)
-            ATB = A.T.dot(b)
+            if 'atol' not in solver_kwargs or 'rtol' not in solver_kwargs:
+                if tol is not None:
+                    solver_kwargs['atol'] = tol
+
+            ATA = A.T @ A
+            ATB = A.T @ b
+            logger.info(f"Solver kwargs: {solver_kwargs}")
+
             res = sparse.linalg.cg(ATA, ATB, **solver_kwargs)
             if res[1] > 0:
                 logger.warning(
@@ -571,6 +579,13 @@ def solve_system(
             return True
         elif solver == 'lsmr':
             logger.info("Solving using lsmr")
+            if 'atol' not in solver_kwargs:
+                if tol is not None:
+                    solver_kwargs['atol'] = tol
+            if 'btol' not in solver_kwargs:
+                if tol is not None:
+                    solver_kwargs['btol'] = tol
+            logger.info(f"Solver kwargs: {solver_kwargs}")
             res = sparse.linalg.lsmr(A, b, **solver_kwargs)
             if res[1] == 1 or res[1] == 4 or res[1] == 2 or res[1] == 5:
                 self.c = res[0]
@@ -622,6 +637,7 @@ def solve_system(
             except ValueError as e:
                 logger.error(f"ADMM solver failed: {e}")
                 return False
+        logger.info(f"{solver} not recognised")
         return False
 
     def update(self) -> bool:
@@ -641,7 +657,8 @@ def update(self) -> bool:
             return False
         if not self.up_to_date:
             self.setup_interpolator()
-            return self.solve_system(self.solver)
+            self.up_to_date = self.solve_system(self.solver)
+            return self.up_to_date
 
     def evaluate_value(self, locations: np.ndarray) -> np.ndarray:
         """Evaluate the value of the interpolator at location