MAINT: Attempt to improve progressbar

Author: Yuriyzabegaev

src/porepy/models/model_runner.py

@@ -12,7 +12,10 @@
 
 import porepy as pp
 from porepy.models.solution_strategy import SolutionStrategy
-from porepy.time.time_step_status import TimeStepperStatusFailure
+from porepy.time.time_step_status import (
+    TimeStepperStatusFailure,
+    TimeStepperStatusSuccess,
+)
 from porepy.time.time_stepper import TimeStepper
 from porepy.utils.ui_and_logging import DummyProgressBar
 from porepy.utils.ui_and_logging import (
@@ -219,6 +222,7 @@ def init_time_progressbar(self) -> None:
         use_progress_bar = (
             self.params.get("progressbars", False) and self._is_time_dependent
         )
+        use_progress_bar = True
         if use_progress_bar and progressbar_class is DummyProgressBar:
             logger.warning(
                 "Progress bars are requested, but `tqdm` is not installed. The time"
@@ -232,26 +236,22 @@ def init_time_progressbar(self) -> None:
         self.params.update({"_nl_progress_bar_position": 1})
 
         if use_progress_bar:
-            # Create a time bar of length of expected number of time steps, estimated
-            # from the initial time step size.
-            # NOTE: Adaptive time stepping updates the bar proportionally if step sizes
-            # change from initial time step size.
-            expected_time_steps: int = int(
-                np.round(
-                    (
-                        self.model.time_manager.schedule[-1]
-                        - self.model.time_manager.schedule[0]
-                    )
-                    / self.model.time_manager.dt
-                )
-            )
+            # Create a time bar of length of expected simulation time.
+
+            # Creating a custom format string. Difference from the default: it converts
+            # the simulation time (done/total) to the a scientific format with :.1e.
+            l_bar = "{desc}: {percentage:3.0f}%|"
+            r_bar = "| {n:.1e}/{total:.1e} [{elapsed}<{remaining}, {rate_fmt}{postfix}]"
+            bar_format = l_bar + "{bar}" + r_bar
 
             # NOTE: If tqdm is not installed, this returns a DummyProgressBar instance.
             self.time_progressbar = progressbar_class(
-                range(expected_time_steps),
+                total=self.model.time_manager.schedule[-1],
                 desc="Time loop",
                 position=0,
                 dynamic_ncols=True,
+                bar_format=bar_format,
+                postfix=self._progressbar_postfix(),
             )
         else:
             self.time_progressbar = DummyProgressBar()
@@ -295,13 +295,17 @@ def _run_time_dependent(self) -> ModelRunnerStatus:
 
         with logging_redirect_tqdm([logging.root]):
             while not self.model.time_manager.final_time_reached():
+                # Update the progressbar before the time step.
+                self.time_progressbar.set_postfix_str(self._progressbar_postfix())
+
                 # Perform the time step.
                 time_step_status = self.time_stepper.perform_time_step(
                     self.model, self.solver
                 )
 
-                # Progressbar update.
-                self.update_time_progressbar()
+                # Update the progressbar after the time step.
+                if isinstance(time_step_status, TimeStepperStatusSuccess):
+                    self.time_progressbar.update(n=time_step_status.dt)
 
                 # Abort simulation if time step was stopped.
                 match time_step_status:
@@ -314,15 +318,6 @@ def _run_time_dependent(self) -> ModelRunnerStatus:
                 return ModelRunnerStatusSuccess()
             return ModelRunnerStatusFailure("Final time was not reached.")
 
-    def update_time_progressbar(self) -> None:
-        """Update the time progressbar with the current time and time step size."""
-        self.time_progressbar.set_postfix_str(
-            f"Time step size {self.model.time_manager.dt:.2e}"
-        )
-        self.time_progressbar.update(
-            n=np.round(
-                self.model.time_manager.time
-                / self.model.time_manager.time_final
-                * self.time_progressbar.total
-            )
-        )
+    def _progressbar_postfix(self) -> str:
+        """Formats a progressbar postfix string with dt."""
+        return f"Δt={self.model.time_manager.dt:.1e}"

src/porepy/time/time_step_status.py

@@ -62,6 +62,11 @@ def serialize(self) -> str:
 class TimeStepperStatusSuccess(TimeStepperStatus):
     """The TimeStepper made a time step successfully."""
 
+    dt: float
+    """Simulation time step magnitude."""
+    time: float
+    """Simulation time at the end of the time step (t0 + dt)."""
+
     nonlinear_solver_status: NonlinearSolverStatusConverged
     """Nonlinear solver status that caused the time step success."""
 

src/porepy/time/time_stepper.py

@@ -152,9 +152,13 @@ def _compute_next_time_step(
                 # The problem is time-dependent and linear.
                 num_iterations = 1
 
+            current_dt = self.time_manager.dt
+            new_time = self.time_manager.time
             self.time_manager.compute_time_step(iterations=num_iterations)
             return TimeStepperStatusSuccess(
-                nonlinear_solver_status=nonlinear_solver_status
+                dt=current_dt,
+                time=new_time,
+                nonlinear_solver_status=nonlinear_solver_status,
             )
 
         elif isinstance(nonlinear_solver_status, NonlinearSolverStatusFailed):

tests/numerics/nonlinear/test_nonlinear_solvers.py

@@ -33,10 +33,12 @@
 def time_step_success() -> TimeStepperStatusSuccess:
     """Create a successful time-step status for statistics tests."""
     return TimeStepperStatusSuccess(
+        time=1.0,
+        dt=0.5,
         nonlinear_solver_status=NonlinearSolverStatusConverged(
             convergence_statuses=ConvergenceStatusCollection(),
             divergence_statuses=ConvergenceStatusCollection(),
-        )
+        ),
     )
 
 

tests/time/test_time_stepper.py

@@ -805,3 +805,14 @@ def test_solve_failure_time_dependent_statistics(statistics_path: Path):
     }
 
     assert DeepDiff(data, reference_data) == {}
+
+
+if __name__ == "__main__":
+    test_model_time_step_control(
+        {
+            "num_nonlinear_iterations": [8, 8, 8, 8, 8, 8],
+            "time_step_converged": [True, True, True, True, True, True],
+            "exported_dt_expected": [1, 0.4, 0.16, 0.1, 0.1, 0.1],
+            "schedule_end": 1.86,
+        },
+    )

tests/viz/test_solver_statistics.py

@@ -11,7 +11,6 @@
 from porepy.numerics.nonlinear.convergence_check import (
     ConvergenceInfoCollection,
     ConvergenceInfoHistory,
-    ConvergenceStatus,
     ConvergenceStatusCollection,
     ConvergenceStatusHistory,
 )
@@ -76,7 +75,9 @@ def time_stepper_status(
     if status == "converged":
         solver_status = nonlinear_solver_status(status)
         assert isinstance(solver_status, NonlinearSolverStatusConverged)
-        return TimeStepperStatusSuccess(nonlinear_solver_status=solver_status)
+        return TimeStepperStatusSuccess(
+            time=1.0, dt=0.5, nonlinear_solver_status=solver_status
+        )
     elif status == "continue_iterating":
         return TimeStepperStatusContinueIterating(
             attempt=0, nonlinear_solver_status=nonlinear_solver_status("failed")