Merge branch 'develop' into #282-restructure-example-directory

.github/workflows/periodic_benchmarks.yaml

@@ -22,6 +22,11 @@ jobs:
     runs-on: [self-hosted, macOS, ARM64]
     if: github.repository == 'pybop-team/PyBOP'
     steps:
+      - name: Cleanup build folder
+        run: |
+          rm -rf ./* || true
+          rm -rf ./.??* || true
+
       - uses: actions/checkout@v4
 
       - name: Install python & create virtualenv

.github/workflows/scheduled_tests.yaml

@@ -113,6 +113,11 @@ jobs:
       matrix: ${{fromJson(needs.filter_pybamm_matrix.outputs.filtered_pybop_matrix)}}
 
     steps:
+      - name: Cleanup build folder
+        run: |
+          rm -rf ./* || true
+          rm -rf ./.??* || true
+
       - uses: actions/checkout@v4
       - name: Install python & create virtualenv
         shell: bash

CHANGELOG.md

@@ -2,6 +2,7 @@
 
 ## Features
 
+- [#379](https://github.com/pybop-team/PyBOP/pull/379) - Adds model.simulateS1 to weekly benchmarks.
 - [#174](https://github.com/pybop-team/PyBOP/issues/174) - Adds new logo and updates Readme for accessibility.
 - [#316](https://github.com/pybop-team/PyBOP/pull/316) - Adds Adam with weight decay (AdamW) optimiser, adds depreciation warning for pints.Adam implementation.
 - [#271](https://github.com/pybop-team/PyBOP/issues/271) - Aligns the output of the optimisers via a generalisation of Result class.

benchmarks/benchmark_model.py

@@ -81,3 +81,13 @@ def time_model_simulate(self, model, parameter_set):
             parameter_set (str): The name of the parameter set being used.
         """
         self.problem._model.simulate(inputs=self.inputs, t_eval=self.t_eval)
+
+    def time_model_simulateS1(self, model, parameter_set):
+        """
+        Benchmark the simulateS1 method of the model.
+
+        Args:
+            model (pybop.Model): The model class being benchmarked.
+            parameter_set (str): The name of the parameter set being used.
+        """
+        self.problem._model.simulateS1(inputs=self.inputs, t_eval=self.t_eval)