Moved solve_system to generic ProblemDAE class

Parallel-in-Time · Oct 31, 2023 · 76efa6a · 76efa6a
1 parent c325087
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diff --git a/pySDC/projects/DAE/misc/ProblemDAE.py b/pySDC/projects/DAE/misc/ProblemDAE.py
@@ -1,25 +1,64 @@
 import numpy as np
+from scipy.optimize import root
 
-from pySDC.core.Problem import ptype
+from pySDC.core.Problem import ptype, WorkCounter
 from pySDC.implementations.datatype_classes.mesh import mesh
 
 
 class ptype_dae(ptype):
-    """
-    Interface class for DAE problems. Ensures that all parameters are passed that are needed by DAE sweepers
+    r"""
+    This class implements a generic DAE class and illustrates the interface class for DAE problems.
+    It ensures that all parameters are passed that are needed by DAE sweepers.
+
+    Parameters
+    ----------
+    nvars : int
+        Number of unknowns of the problem class.
+    newton_tol : float
+        Tolerance for the nonlinear solver.
+
+    Attributes
+    ----------
+    work_counters : WorkCounter
+        Counts the work, here the number of function calls during the nonlinear solve is logged.
     """
 
     dtype_u = mesh
     dtype_f = mesh
 
     def __init__(self, nvars, newton_tol):
-        """
-        Initialization routine
-
-        Args:
-            problem_params (dict): custom parameters for the example
-            dtype_u: mesh data type (will be passed parent class)
-            dtype_f: mesh data type (will be passed parent class)
-        """
+        """Initialization routine"""
         super().__init__((nvars, None, np.dtype('float64')))
         self._makeAttributeAndRegister('nvars', 'newton_tol', localVars=locals(), readOnly=True)
+
+        self.work_counters['newton'] = WorkCounter()
+
+    def solve_system(self, impl_sys, u0, t):
+        r"""
+        Solver for nonlinear implicit system (defined in sweeper).
+
+        Parameters
+        ----------
+        impl_sys : callable
+            Implicit system to be solved.
+        u0 : dtype_u
+            Initial guess for solver.
+        t : float
+            Current time :math:`t`.
+
+        Returns
+        -------
+        me : dtype_u
+            Numerical solution.
+        """
+
+        me = self.dtype_u(self.init)
+        opt = root(
+            impl_sys,
+            u0,
+            method='hybr',
+            tol=self.newton_tol,
+        )
+        me[:] = opt.x
+        self.work_counters['newton'].niter += opt.nfev
+        return me
diff --git a/pySDC/projects/DAE/problems/simple_DAE.py b/pySDC/projects/DAE/problems/simple_DAE.py
@@ -1,7 +1,6 @@
 import warnings
 import numpy as np
 from scipy.interpolate import interp1d
-from scipy.optimize import root
 
 from pySDC.projects.DAE.misc.ProblemDAE import ptype_dae
 from pySDC.core.Problem import WorkCounter
@@ -38,8 +37,7 @@ class pendulum_2d(ptype_dae):
     ----------
     work_counters : WorkCounter
         Counts the work, i.e., number of function calls of right-hand side is called and stored in
-        ``work_counters['rhs']``, the number of function calls of the Newton-like solver is stored in
-        ``work_counters['newton']``.
+        ``work_counters['rhs']``.
 
     References
     ----------
@@ -57,7 +55,6 @@ def __init__(self, nvars, newton_tol):
         # solution = data[:, 1:]
         # self.u_ref = interp1d(t, solution, kind='cubic', axis=0, fill_value='extrapolate')
         self.t_end = 0.0
-        self.work_counters['newton'] = WorkCounter()
         self.work_counters['rhs'] = WorkCounter()
 
     def eval_f(self, u, du, t):
@@ -86,36 +83,6 @@ def eval_f(self, u, du, t):
         self.work_counters['rhs']()
         return f
 
-    def solve_system(self, impl_sys, u0, t):
-        r"""
-        Solver for nonlinear implicit system (defined in sweeper).
-
-        Parameters
-        ----------
-        impl_sys : callable
-            Implicit system to be solved.
-        u0 : dtype_u
-            Initial guess for solver.
-        t : float
-            Current time :math:`t`.
-
-        Returns
-        -------
-        me : dtype_u
-            Numerical solution.
-        """
-
-        me = self.dtype_u(self.init)
-        opt = root(
-            impl_sys,
-            u0,
-            method='hybr',
-            tol=self.newton_tol,
-        )
-        me[:] = opt.x
-        self.work_counters['newton'].niter += opt.nfev
-        return me
-
     def u_exact(self, t):
         """
         Approximation of the exact solution generated by spline interpolation of an extremely accurate numerical reference solution.
@@ -177,8 +144,7 @@ class simple_dae_1(ptype_dae):
     ----------
     work_counters : WorkCounter
         Counts the work, i.e., number of function calls of right-hand side is called and stored in
-        ``work_counters['rhs']``, the number of function calls of the Newton-like solver is stored in
-        ``work_counters['newton']``.
+        ``work_counters['rhs']``.
 
     References
     ----------
@@ -190,7 +156,6 @@ def __init__(self, nvars, newton_tol):
         """Initialization routine"""
         super().__init__(nvars, newton_tol)
 
-        self.work_counters['newton'] = WorkCounter()
         self.work_counters['rhs'] = WorkCounter()
 
     def eval_f(self, u, du, t):
@@ -222,36 +187,6 @@ def eval_f(self, u, du, t):
         self.work_counters['rhs']()
         return f
 
-    def solve_system(self, impl_sys, u0, t):
-        r"""
-        Solver for nonlinear implicit system (defined in sweeper).
-
-        Parameters
-        ----------
-        impl_sys : callable
-            Implicit system to be solved.
-        u0 : dtype_u
-            Initial guess for solver.
-        t : float
-            Current time :math:`t`.
-
-        Returns
-        -------
-        me : dtype_u
-            Numerical solution.
-        """
-
-        me = self.dtype_u(self.init)
-        opt = root(
-            impl_sys,
-            u0,
-            method='hybr',
-            tol=self.newton_tol,
-        )
-        me[:] = opt.x
-        self.work_counters['newton'].niter += opt.nfev
-        return me
-
     def u_exact(self, t):
         """
         Routine for the exact solution.
@@ -297,8 +232,7 @@ class problematic_f(ptype_dae):
         Specific parameter of the problem.
     work_counters : WorkCounter
         Counts the work, i.e., number of function calls of right-hand side is called and stored in
-        ``work_counters['rhs']``, the number of function calls of the Newton-like solver is stored in
-        ``work_counters['newton']``.
+        ``work_counters['rhs']``
 
     References
     ----------
@@ -312,7 +246,6 @@ def __init__(self, nvars, newton_tol, eta=1):
         self._makeAttributeAndRegister('eta', localVars=locals())
 
         self.work_counters['rhs'] = WorkCounter()
-        self.work_counters['newton'] = WorkCounter()
 
     def eval_f(self, u, du, t):
         r"""
@@ -340,36 +273,6 @@ def eval_f(self, u, du, t):
         self.work_counters['rhs']()
         return f
 
-    def solve_system(self, impl_sys, u0, t):
-        r"""
-        Solver for nonlinear implicit system (defined in sweeper).
-
-        Parameters
-        ----------
-        impl_sys : callable
-            Implicit system to be solved.
-        u0 : dtype_u
-            Initial guess for solver.
-        t : float
-            Current time :math:`t`.
-
-        Returns
-        -------
-        me : dtype_u
-            Numerical solution.
-        """
-
-        me = self.dtype_u(self.init)
-        opt = root(
-            impl_sys,
-            u0,
-            method='hybr',
-            tol=self.newton_tol,
-        )
-        me[:] = opt.x
-        self.work_counters['newton'].niter += opt.nfev
-        return me
-
     def u_exact(self, t):
         """
         Routine for the exact solution.

diff --git a/pySDC/projects/DAE/problems/synchronous_machine.py b/pySDC/projects/DAE/problems/synchronous_machine.py
@@ -1,7 +1,6 @@
 import numpy as np
 import warnings
 from scipy.interpolate import interp1d
-from scipy.optimize import root
 
 from pySDC.projects.DAE.misc.ProblemDAE import ptype_dae
 from pySDC.core.Problem import WorkCounter
@@ -147,8 +146,7 @@ class synchronous_machine_infinite_bus(ptype_dae):
         Defines the mechanical torque applied to the rotor shaft.
     work_counters : WorkCounter
         Counts the work, i.e., number of function calls of right-hand side is called and stored in
-        ``work_counters['rhs']``, the number of function calls of the Newton-like solver is stored in
-        ``work_counters['newton']``.
+        ``work_counters['rhs']``.
 
     References
     ----------
@@ -191,7 +189,6 @@ def __init__(self, nvars, newton_tol):
         self.T_m = 0.854
 
         self.work_counters['rhs'] = WorkCounter()
-        self.work_counters['newton'] = WorkCounter()
 
     def eval_f(self, u, du, t):
         r"""
@@ -269,36 +266,6 @@ def eval_f(self, u, du, t):
         self.work_counters['rhs']()
         return f
 
-    def solve_system(self, impl_sys, u0, t):
-        r"""
-        Solver for nonlinear implicit system (defined in sweeper).
-
-        Parameters
-        ----------
-        impl_sys : callable
-            Implicit system to be solved.
-        u0 : dtype_u
-            Initial guess for solver.
-        t : float
-            Current time :math:`t`.
-
-        Returns
-        -------
-        me : dtype_u
-            Numerical solution.
-        """
-
-        me = self.dtype_u(self.init)
-        opt = root(
-            impl_sys,
-            u0,
-            method='hybr',
-            tol=self.newton_tol,
-        )
-        me[:] = opt.x
-        self.work_counters['newton'].niter += opt.nfev
-        return me
-
     def u_exact(self, t):
         """
         Approximation of the exact solution generated by spline interpolation of an extremely accurate numerical reference solution.