MOD: Purging VerificationDataSaving from porepy.

src/porepy/examples/mandel_biot.py

@@ -38,7 +38,6 @@
 from porepy.models.derived_models.biot import BiotPoromechanics
 from porepy.numerics.linalg.matrix_operations import sparse_array_to_row_col_data
 from porepy.utils.examples_utils import VerificationUtils
-from porepy.viz.data_saving_model_mixin import VerificationDataSaving
 
 # PorePy typings
 number = pp.number
@@ -116,7 +115,7 @@ class MandelSaveData:
     """Current simulation time."""
 
 
-class MandelDataSaving(VerificationDataSaving):
+class MandelDataSaving(pp.PorePyModel):
     """Mixin class to save relevant data."""
 
     darcy_flux: Callable[[list[pp.Grid]], pp.ad.Operator]

src/porepy/examples/terzaghi_biot.py

@@ -50,7 +50,6 @@
 from porepy.applications.convergence_analysis import ConvergenceAnalysis
 from porepy.models.derived_models.biot import BiotPoromechanics
 from porepy.utils.examples_utils import VerificationUtils
-from porepy.viz.data_saving_model_mixin import VerificationDataSaving
 
 # PorePy typings
 number = pp.number
@@ -100,7 +99,7 @@ class TerzaghiSaveData:
     """Current simulation time."""
 
 
-class TerzaghiDataSaving(VerificationDataSaving):
+class TerzaghiDataSaving(pp.PorePyModel):
     """Mixin class to save relevant data."""
 
     exact_sol: TerzaghiExactSolution

src/porepy/models/derived_models/biot.py

@@ -77,11 +77,7 @@
 """
 
 import porepy as pp
-from porepy.models.poromechanics import (
-    ConstitutiveLawsPoromechanics,
-    Poromechanics,
-    SolutionStrategyPoromechanics,
-)
+from porepy.models.poromechanics import Poromechanics, SolutionStrategyPoromechanics
 
 
 class SolutionStrategyBiot(SolutionStrategyPoromechanics):
@@ -100,8 +96,17 @@ def set_materials(self):
 class ConstitutiveLawsBiot(
     pp.constitutive_laws.SpecificStorage,
     pp.constitutive_laws.BiotPoroMechanicsPorosity,
-    ConstitutiveLawsPoromechanics,
-): ...
+):
+    """Additional constitutive laws required for the Biot-Poromechanics model.
+
+    Note:
+        These are additions and do not contain everything a poromechanical model needs.
+        Intention behind this choice include a cleaner MRO in the
+        :class:`BiotPoromechanics`.
+
+    """
+
+    ...
 
 
 class BiotPoromechanics(  # type: ignore[misc]

src/porepy/models/protocol.py

@@ -16,7 +16,7 @@
 """
 
 from pathlib import Path
-from typing import TYPE_CHECKING, Callable, Literal, Optional, Protocol, Sequence
+from typing import TYPE_CHECKING, Any, Callable, Literal, Optional, Protocol, Sequence
 
 import numpy as np
 import scipy.sparse as sps
@@ -537,6 +537,9 @@ class SolutionStrategyProtocol(Protocol):
         """Time step as an automatic differentiation scalar."""
         nonlinear_solver_statistics: pp.SolverStatistics
         """Solver statistics for the nonlinear solver."""
+        results: list[Any]
+        """A list of results collected by the data saving mixin in
+        :meth:`~porepy.viz.data_saving_model_mixin.DataSavingMixin.collect_data`."""
 
         @property
         def time_step_indices(self) -> np.ndarray:

src/porepy/models/solution_strategy.py

@@ -114,6 +114,9 @@ def __init__(self, params: Optional[dict] = None):
         """Restart options. The template is provided in `SolutionStrategy.__init__`."""
         self.ad_time_step = pp.ad.Scalar(self.time_manager.dt)
         """Time step as an automatic differentiation scalar."""
+        self.results: list[Any] = []
+        """A list of results collected by the data saving mixin in
+        :meth:`~porepy.viz.data_saving_model_mixin.DataSavingMixin.collect_data`."""
 
         self.set_solver_statistics()
 

src/porepy/viz/data_saving_model_mixin.py

@@ -10,7 +10,7 @@
 from __future__ import annotations
 
 from pathlib import Path
-from typing import Optional, Union
+from typing import Any, Optional, Union
 
 import numpy as np
 
@@ -29,14 +29,19 @@ class DataSavingMixin(pp.PorePyModel):
     def save_data_time_step(self) -> None:
         """Export the model state at a given time step and log time.
 
-        The options for exporting times are:
-            * `None`: All time steps are exported
-            * `list`: Export if time is in the list. If the list is empty, then no
-            times are exported.
+        The options for exporting times can be given as ``params['times_to_export']``:
+
+        - ``None``: All time steps are exported.
+        - ``list``: Export if time is in the list. If the list is empty, then no
+          times are exported.
 
         In addition, save the solver statistics to file if the option is set.
 
+        Finally, :meth:`collect_data` is called and stored in :attr:`results` for
+        data collection and verification in runtime.
+
         """
+
         # Fetching the desired times to export.
         times_to_export = self.params.get("times_to_export", None)
         if times_to_export is None:
@@ -55,6 +60,39 @@ def save_data_time_step(self) -> None:
         # Save solver statistics to file.
         self.nonlinear_solver_statistics.save()
 
+        # Collecting and storing data in runtime for analysis.
+        if not self._is_time_dependent():  # stationary problem
+            if (
+                self.nonlinear_solver_statistics.num_iteration > 0
+            ):  # avoid saving initial condition
+                collected_data = self.collect_data()
+                if collected_data is not None:
+                    self.results.append(collected_data)
+        else:  # time-dependent problem
+            t = self.time_manager.time  # current time
+            scheduled = self.time_manager.schedule[1:]  # scheduled times except t_init
+            if any(np.isclose(t, scheduled)):
+                collected_data = self.collect_data()
+                if collected_data is not None:
+                    self.results.append(collected_data)
+
+    def collect_data(self) -> Any:
+        """Collect relevant simulation data to be stored in attr:`results`.
+
+        Override to collect data respectively. By default, this method returns None and
+        nothing is stored.
+
+        For stationary problems, this method is called in every iteration. For time
+        dependent problems, it is called after convergence of a time step which is
+        scheduled by the time manager.
+
+        Returns:
+            Any data structure relevant for future verification. By default, None.
+            If it is not None, it is stored in :attr:`results`.
+
+        """
+        return None
+
     def write_pvd_and_vtu(self) -> None:
         """Helper function for writing the .vtu and .pvd files and time information."""
         self.exporter.write_vtu(self.data_to_export(), time_dependent=True)
@@ -237,29 +275,3 @@ def load_data_from_pvd(
         self.time_manager.load_time_information(times_file)
         self.time_manager.set_time_and_dt_from_exported_steps(time_index)
         self.exporter._time_step_counter = time_index
-
-
-class VerificationDataSaving(DataSavingMixin):
-    """Class to store relevant data for a generic verification setup."""
-
-    results: list
-    """List of objects containing the results of the verification."""
-
-    def save_data_time_step(self) -> None:
-        """Save data to the `results` list."""
-        if not self._is_time_dependent():  # stationary problem
-            if (
-                self.nonlinear_solver_statistics.num_iteration > 0
-            ):  # avoid saving initial condition
-                collected_data = self.collect_data()
-                self.results.append(collected_data)
-        else:  # time-dependent problem
-            t = self.time_manager.time  # current time
-            scheduled = self.time_manager.schedule[1:]  # scheduled times except t_init
-            if any(np.isclose(t, scheduled)):
-                collected_data = self.collect_data()
-                self.results.append(collected_data)
-
-    def collect_data(self):
-        """Collect relevant data for the verification setup."""
-        raise NotImplementedError()

tests/applications/test_convergence_analysis.py

@@ -26,7 +26,6 @@
 )
 from porepy.models.fluid_mass_balance import SinglePhaseFlow
 from porepy.utils.txt_io import read_data_from_txt
-from porepy.viz.data_saving_model_mixin import VerificationDataSaving
 
 
 # -----> Fixtures that are required on a module level.
@@ -461,7 +460,7 @@ class StationaryModelSaveData:
         error_var_0: float  # error associated with variable 0
         error_var_1: float  # error associated with variable 1
 
-    class StationaryModelDataSaving(VerificationDataSaving):
+    class StationaryModelDataSaving(pp.PorePyModel):
         """Class that collects and store data."""
 
         def collect_data(self) -> StationaryModelSaveData:
@@ -528,7 +527,7 @@ class TimeDependentModelSaveData:
         error_var_0: float  # error associated with variable 0
         error_var_1: float  # error associated with variable 1
 
-    class TimeDependentModelDataSaving(VerificationDataSaving):
+    class TimeDependentModelDataSaving(pp.PorePyModel):
         """Class that collects and store data."""
 
         def collect_data(self) -> TimeDependentModelSaveData:

tests/functional/setups/manu_flow_comp_2d_frac.py

@@ -34,7 +34,6 @@
 
 import porepy as pp
 from porepy.applications.convergence_analysis import ConvergenceAnalysis
-from porepy.viz.data_saving_model_mixin import VerificationDataSaving
 from tests.functional.setups.manu_flow_incomp_frac_2d import (
     ManuIncompSaveData,
     ManuIncompUtils,
@@ -75,7 +74,7 @@ class ManuCompSaveData(ManuIncompSaveData):
     """Current simulation time."""
 
 
-class ManuCompDataSaving(VerificationDataSaving):
+class ManuCompDataSaving(pp.PorePyModel):
     """Mixin class to store relevant data."""
 
     darcy_flux: Callable[[list[pp.Grid]], pp.ad.Operator]

tests/functional/setups/manu_flow_incomp_frac_2d.py

@@ -25,7 +25,6 @@
 from porepy.applications.convergence_analysis import ConvergenceAnalysis
 from porepy.applications.md_grids.domains import nd_cube_domain
 from porepy.utils.examples_utils import VerificationUtils
-from porepy.viz.data_saving_model_mixin import VerificationDataSaving
 
 # PorePy typings
 number = pp.number
@@ -97,7 +96,7 @@ class ManuIncompSaveData:
     """Exact pressure in the matrix."""
 
 
-class ManuIncompDataSaving(VerificationDataSaving):
+class ManuIncompDataSaving(pp.PorePyModel):
     """Mixin class to save relevant data."""
 
     darcy_flux: Callable[[list[pp.Grid]], pp.ad.Operator]

tests/functional/setups/manu_poromech_nofrac_2d.py

@@ -60,7 +60,6 @@
 from porepy.applications.convergence_analysis import ConvergenceAnalysis
 from porepy.applications.md_grids.domains import nd_cube_domain
 from porepy.utils.examples_utils import VerificationUtils
-from porepy.viz.data_saving_model_mixin import VerificationDataSaving
 
 # PorePy typings
 number = pp.number
@@ -112,7 +111,7 @@ class ManuPoroMechSaveData:
     """Current simulation time."""
 
 
-class ManuPoroMechDataSaving(VerificationDataSaving):
+class ManuPoroMechDataSaving(pp.PorePyModel):
     """Mixin class to save relevant data."""
 
     darcy_flux: Callable[[list[pp.Grid]], pp.ad.Operator]

tests/functional/setups/manu_thermoporomech_nofrac_2d.py

@@ -47,7 +47,6 @@
 import porepy as pp
 from porepy.applications.convergence_analysis import ConvergenceAnalysis
 from porepy.applications.md_grids.domains import nd_cube_domain
-from porepy.viz.data_saving_model_mixin import VerificationDataSaving
 
 # PorePy typings
 number = pp.number
@@ -116,7 +115,7 @@ class ManuThermoPoroMechSaveData:
     time: number
 
 
-class ManuThermoPoroMechDataSaving(VerificationDataSaving):
+class ManuThermoPoroMechDataSaving(pp.PorePyModel):
     """Mixin class to save relevant data."""
 
     exact_sol: ManuThermoPoroMechExactSolution2d
@@ -138,6 +137,12 @@ class ManuThermoPoroMechDataSaving(VerificationDataSaving):
 
     """
 
+    energy_flux: Callable[[list[pp.Grid]], pp.ad.Operator]
+    """Method that returns the energy fluxes in the form of an Ad operator. Usually
+    provided by the mixin class
+    :class:`porepy.models.energy_balance.EnergyBalanceEquations`.
+
+    """
     darcy_flux: Callable[[list[pp.Grid]], pp.ad.Operator]
     """Method that returns the Darcy fluxes in the form of an Ad operator. Usually
     provided by the mixin class :class:`porepy.models.constitutive_laws.DarcysLaw`.

tests/functional/test_mandel.py

@@ -78,7 +78,9 @@ def results() -> list[MandelSaveData]:
 
 
 @pytest.mark.parametrize("time_index", [0, 1])
-def test_error_primary_and_secondary_variables(time_index: int, results):
+def test_error_primary_and_secondary_variables(
+    time_index: int, results: list[MandelSaveData]
+):
     """Checks error for pressure, displacement, flux, force, and consolidation degree.
 
     Physical parameters used in this test have been adapted from [1].

tests/functional/test_manu_flow_comp_frac.py

@@ -109,14 +109,15 @@ def actual_l2_errors(
         "reference_variable_values": reference_values,
         "meshing_arguments": {"cell_size": 0.125},
         "time_manager": pp.TimeManager([0, 0.5, 1.0], 0.5, True),
+        "times_to_export": [],  # Suppress output for tests
     }
 
     # Retrieve actual L2-relative errors.
     errors: list[list[dict[str, float]]] = []
     # Loop through models, i.e., 2d and 3d.
     for model in [ManuCompFlowSetup2d, ManuCompFlowSetup3d]:
         # Make deep copy of params to avoid nasty bugs.
-        setup = model(deepcopy(model_params))
+        setup: pp.PorePyModel = model(deepcopy(model_params))
         pp.run_time_dependent_model(setup, {})
         errors_setup: list[dict[str, float]] = []
         # Loop through results, i.e., results for each scheduled time.
@@ -279,6 +280,7 @@ def actual_ooc(
                     "material_constants": material_constants,
                     "reference_variable_values": reference_values,
                     "meshing_arguments": {"cell_size": 0.125},
+                    "times_to_export": [],  # Suppress output for tests
                 }
                 # Use 4 levels of refinement for 2d and 3 levels for 3d
                 if model_idx == 0:

tests/functional/test_manu_flow_incomp_frac.py

@@ -82,14 +82,17 @@ def actual_l2_errors(material_constants: dict) -> list[dict[str, float]]:
         "grid_type": "cartesian",
         "material_constants": material_constants,
         "meshing_arguments": {"cell_size": 0.125},
+        "times_to_export": [],  # Suppress output for tests
     }
 
     # Retrieve actual L2-relative errors
     errors: list[dict[str, float]] = []
     # Loop through models, i.e., 2d and 3d
     for model in [ManuIncompFlowSetup2d, ManuIncompFlowSetup3d]:
         # Make deep copy of params to avoid nasty bugs.
-        setup = model(deepcopy(model_params))
+        setup: ManuIncompFlowSetup2d | ManuIncompFlowSetup3d = model(
+            deepcopy(model_params)
+        )
         pp.run_time_dependent_model(setup)
         errors.append(
             {
@@ -217,6 +220,7 @@ def actual_ooc(material_constants: dict) -> list[list[dict[str, float]]]:
                     "grid_type": grid_type,
                     "material_constants": material_constants,
                     "meshing_arguments": {"cell_size": 0.125},
+                    "times_to_export": [],  # Suppress output for tests
                 }
                 # Use 4 levels of refinement for 2d and 3 levels for 3d
                 if model_idx == 0:

tests/functional/test_manu_poromech_nofrac.py

@@ -96,14 +96,15 @@ def actual_l2_errors(material_constants: dict) -> list[list[dict[str, float]]]:
         "meshing_arguments": {"cell_size": 0.25},
         "manufactured_solution": "nordbotten_2016",
         "time_manager": pp.TimeManager([0, 0.5, 1.0], 0.5, True),
+        "times_to_export": [],  # Suppress output for tests
     }
 
     # Retrieve actual L2-relative errors.
     errors: list[list[dict[str, float]]] = []
     # Loop through models, i.e., 2d and 3d.
     for model in [ManuPoroMechSetup2d, ManuPoroMechSetup3d]:
         # Make deep copy of params to avoid nasty bugs.
-        setup = model(deepcopy(model_params))
+        setup: pp.PorePyModel = model(deepcopy(model_params))
         pp.run_time_dependent_model(setup)
         errors_setup: list[dict[str, float]] = []
         # Loop through results, i.e., results for each scheduled time.
@@ -251,6 +252,7 @@ def actual_ooc(material_constants: dict) -> list[list[dict[str, float]]]:
                     "grid_type": grid_type,
                     "material_constants": material_constants,
                     "meshing_arguments": {"cell_size": 0.25},
+                    "times_to_export": [],  # Suppress output for tests
                 }
                 # Use 4 levels of refinement for 2d and 3 levels for 3d.
                 if model_idx == 0: