Merge remote-tracking branch 'upstream/master' into test_hackathon

.github/workflows/ci_pipeline.yml

@@ -144,7 +144,53 @@ jobs:
           path: |
             data_libpressio
             coverage_libpressio_3.10.dat
-           
+         
+  user_monodomain_tests_linux:
+    runs-on: ubuntu-latest
+
+    defaults:
+      run:
+        shell: bash -l {0}
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+
+      - name: Install Conda environment with Micromamba
+        uses: mamba-org/setup-micromamba@v1
+        with:
+          environment-file: "pySDC/projects/Monodomain/etc/environment-monodomain.yml"
+          create-args: >-
+              python=3.10
+
+      - name: Compile C++ ionic models
+        env:
+          IONIC_MODELS_PATH: "pySDC/projects/Monodomain/problem_classes/ionicmodels/cpp"
+        run: |
+          c++ -O3 -Wall -shared -std=c++11 -fPIC -fvisibility=hidden $(python3 -m pybind11 --includes) ${IONIC_MODELS_PATH}/bindings_definitions.cpp -o ${IONIC_MODELS_PATH}/ionicmodels$(python3-config --extension-suffix)
+      
+      - name: Run pytest for CPU stuff
+        run: |
+          echo "print('Loading sitecustomize.py...')
+          import coverage
+          coverage.process_startup() " > sitecustomize.py
+          coverage run -m pytest --continue-on-collection-errors -v --durations=0 pySDC/tests -m monodomain
+
+      - name: Make coverage report
+        run: |
+          mv data data_monodomain
+          coverage combine
+          mv .coverage coverage_monodomain_3.10.dat
+
+      - name: Uploading artifacts
+        uses: actions/upload-artifact@v3
+        with:
+          name: cpu-test-artifacts
+          path: |
+            data_monodomain
+            coverage_monodomain_3.10.dat
+
+
 #  user_cpu_tests_macos:
 #    runs-on: macos-12
 #
@@ -206,6 +252,7 @@ jobs:
       - lint
       - user_cpu_tests_linux
       - user_libpressio_tests
+      - user_monodomain_tests_linux
 #       - wait_for_gitlab
 
     defaults:

CITATION.cff

@@ -21,9 +21,9 @@ authors:
     orcid: https://orcid.org/0000-0002-8869-0784
     affiliation: "Hamburg University of Technology, Institute of Mathematics, 21073 Hamburg, Germany"
 
-version: 5.4.2
+version: 5.4.3
 doi: 10.5281/zenodo.594191
-date-released: 2024-02-08
+date-released: 2024-03-27
 keywords: 
   - "parallel-in-time"
   - "spectral deferred corrections"

README.md

@@ -105,7 +105,7 @@ The JU receives support from the European Union's Horizon 2020 research
 and innovation programme and Belgium, France, Germany, and Switzerland.
 This project also received funding from the [German Federal Ministry of
 Education and Research](https://www.bmbf.de/bmbf/en/home/home_node.html)
-(BMBF) grant 16HPC047. The project also received help from the
+(BMBF) grants  16HPC047 and 16ME0679K. Supported by the European Union - NextGenerationEU. The project also received help from the
 [Helmholtz Platform for Research Software Engineering - Preparatory
 Study (HiRSE_PS)](https://www.helmholtz-hirse.de/).
 

docs/source/conf.py

@@ -72,7 +72,7 @@
 # The short X.Y version.
 version = '5.4'
 # The full version, including alpha/beta/rc tags.
-release = '5.4.2'
+release = '5.4.3'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

docs/source/index.rst

@@ -52,6 +52,7 @@ Projects
    projects/DAE.rst
    projects/compression.rst
    projects/second_order.rst
+   projects/monodomain.rst
 
 
 API documentation

docs/source/projects/monodomain.rst

@@ -0,0 +1 @@
+.. include:: /../../pySDC/projects/Monodomain/README.rst

pySDC/core/Lagrange.py

@@ -88,7 +88,7 @@ class LagrangeApproximation(object):
         The associated barycentric weights
     """
 
-    def __init__(self, points):
+    def __init__(self, points, fValues=None):
         points = np.asarray(points).ravel()
 
         diffs = points[:, None] - points[None, :]
@@ -110,6 +110,20 @@ def analytic(diffs):
         self.points = points
         self.weights = weights
 
+        # Store function values if provided
+        if fValues is not None:
+            fValues = np.asarray(fValues)
+            if fValues.shape != points.shape:
+                raise ValueError(f'fValues {fValues.shape} has not the correct shape: {points.shape}')
+        self.fValues = fValues
+
+    def __call__(self, t):
+        assert self.fValues is not None, "cannot evaluate polynomial without fValues"
+        t = np.asarray(t)
+        values = self.getInterpolationMatrix(t.ravel()).dot(self.fValues)
+        values.shape = t.shape
+        return values
+
     @property
     def n(self):
         return self.points.size

pySDC/implementations/convergence_controller_classes/adaptivity.py

@@ -208,6 +208,7 @@ def setup(self, controller, params, description, **kwargs):
             'residual_max_tol': 1e9,
             'maxiter': description['sweeper_params'].get('maxiter', 99),
             'interpolate_between_restarts': True,
+            'abort_at_growing_residual': True,
             **super().setup(controller, params, description, **kwargs),
         }
         if defaults['restol_rel']:
@@ -232,7 +233,12 @@ def determine_restart(self, controller, S, **kwargs):
                 self.trigger_restart_upon_nonconvergence(S)
             elif self.get_local_error_estimate(controller, S, **kwargs) > self.params.e_tol:
                 S.status.restart = True
-        elif S.status.time_size == 1 and self.res_last_iter < S.levels[0].status.residual and S.status.iter > 0:
+        elif (
+            S.status.time_size == 1
+            and self.res_last_iter < S.levels[0].status.residual
+            and S.status.iter > 0
+            and self.params.abort_at_growing_residual
+        ):
             self.trigger_restart_upon_nonconvergence(S)
         elif S.levels[0].status.residual > self.params.residual_max_tol:
             self.trigger_restart_upon_nonconvergence(S)

pySDC/implementations/hooks/log_solution.py

@@ -1,4 +1,7 @@
 from pySDC.core.Hooks import hooks
+import pickle
+import os
+import numpy as np
 
 
 class LogSolution(hooks):
@@ -63,3 +66,79 @@ def post_iteration(self, step, level_number):
             type='u',
             value=L.uend,
         )
+
+
+class LogToFile(hooks):
+    r"""
+    Hook for logging the solution to file after the step using pickle.
+
+    Please configure the hook to your liking by manipulating class attributes.
+    You must set a custom path to a directory like so:
+
+    ```
+    LogToFile.path = '/my/directory/'
+    ```
+
+    Keep in mind that the hook will overwrite files without warning!
+    You can give a custom file name by setting the ``file_name`` class attribute and give a custom way of rendering the
+    index associated with individual files by giving a different lambda function ``format_index`` class attribute. This
+    lambda should accept one index and return one string.
+
+    You can also give a custom ``logging_condition`` lambda, accepting the current level if you want to log selectively.
+
+    Importantly, you may need to change ``process_solution``. By default, this will return a numpy view of the solution.
+    Of course, if you are not using numpy, you need to change this. Again, this is a lambda accepting the level.
+
+    After the fact, you can use the classmethod `get_path` to get the path to a certain data or the `load` function to
+    directly load the solution at a given index. Just configure the hook like you did when you recorded the data
+    beforehand.
+
+    Finally, be aware that using this hook with MPI parallel runs may lead to different tasks overwriting files. Make
+    sure to give a different `file_name` for each task that writes files.
+    """
+
+    path = None
+    file_name = 'solution'
+    logging_condition = lambda L: True
+    process_solution = lambda L: {'t': L.time + L.dt, 'u': L.uend.view(np.ndarray)}
+    format_index = lambda index: f'{index:06d}'
+
+    def __init__(self):
+        super().__init__()
+        self.counter = 0
+
+        if self.path is None:
+            raise ValueError('Please set a path for logging as the class attribute `LogToFile.path`!')
+
+        if os.path.isfile(self.path):
+            raise ValueError(
+                f'{self.path!r} is not a valid path to log to because a file of the same name exists. Please supply a directory'
+            )
+
+        if not os.path.isdir(self.path):
+            os.mkdir(self.path)
+
+    def post_step(self, step, level_number):
+        if level_number > 0:
+            return None
+
+        L = step.levels[level_number]
+
+        if type(self).logging_condition(L):
+            path = self.get_path(self.counter)
+            data = type(self).process_solution(L)
+
+            with open(path, 'wb') as file:
+                pickle.dump(data, file)
+
+            self.counter += 1
+
+    @classmethod
+    def get_path(cls, index):
+        return f'{cls.path}/{cls.file_name}_{cls.format_index(index)}.pickle'
+
+    @classmethod
+    def load(cls, index):
+        path = cls.get_path(index)
+        with open(path, 'rb') as file:
+            return pickle.load(file)